@Article{info:doi/10.2196/66614, author="Hirata, Mika and Yamaji, Noyuri and Iwamoto, Shotaro and Hasegawa, Ayaka and Miyachi, Mitsuru and Yamaguchi, Takashi and Hasegawa, Daisuke and Ota, Erika and Yotani, Nobuyuki and ", title="Pain Assessment Tools for Infants, Children, and Adolescents With Cancer: Protocol for a Scoping Review", journal="JMIR Res Protoc", year="2025", month="Apr", day="28", volume="14", pages="e66614", keywords="pediatric", keywords="infants", keywords="children", keywords="adolescents", keywords="pediatric cancer", keywords="developmental stage", keywords="pain assessment tool", keywords="scoping review", abstract="Background: Pain management in children with cancer may be inadequate due to poor pain assessment, and evaluation using suitable tools is necessary. Despite the availability of many pain assessment scales, few studies have summarized the existing assessment tools, making it challenging to select a suitable scale. Objective: This scoping review aims to map existing pain assessment tools for children with cancer and provide a comprehensive overview of pediatric cancer-related pain screening and assessment tools. Methods: The scoping review will be conducted according to the guidelines by the Joanna Briggs Institute and reported following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) framework. Electronic databases, including PubMed, CINAHL, CENTRAL, ICHUSHI (Japan Medical Abstracts Society), and Embase, will be searched to identify eligible studies, without date or language restrictions. We defined the eligibility criteria based on the PCC (Population, Concept, and Context) format. Studies that focused on assessment tools for evaluating pain in children (aged 0-18 years) with cancer in a hospital or at home will be included. Although there are no restrictions on study design, protocols and conference abstracts will be excluded. Two or more reviewers will select studies by reviewing the full text of relevant articles identified by titles and abstracts, and disagreements will be resolved through discussion. Two or more reviewers will extract predefined data items, including characteristics of included studies (eg, author name, title of publication, year of publication, purpose of study, study setting, study population, outline of the assessment tool, study design, and findings) and the characteristics of assessment tools (eg, types of tools, target population, assessor, validity, instructions, precautions, and advantages and disadvantages of the tools). Pain assessment tools will be summarized in tabular format and described in a narrative synthesis. Results: Through electronic database searches on November 20, 2023, we identified 3748 articles. This review will provide a comprehensive overview of pain assessment tools. The final report is planned for submission to a peer-reviewed journal in 2025. Conclusions: This scoping review is the first comprehensive effort to map existing tools on pediatric cancer-related pain assessment tools for infants, children, and adolescents aged <18 years, according to developmental stages. Based on the findings of this study, we will discuss future clinical and research implications for pain assessment and management in children with cancer. The findings are expected to enhance pain management practices in children with cancer and inform health care providers, policy makers, and other stakeholders. International Registered Report Identifier (IRRID): DERR1-10.2196/66614 ", doi="10.2196/66614", url="https://www.researchprotocols.org/2025/1/e66614" } @Article{info:doi/10.2196/70522, author="Burgess, L. Jefferey and Beitel, C. Shawn and Calkins, M. Miriam and Furlong, A. Melissa and Louzado Feliciano, Paola and Kolar Gabriel, Jamie and Grant, Casey and Goodrich, M. Jaclyn and Graber, M. Judith and Healy, Olivia and Hollister, James and Hughes, Jeff and Jahnke, Sara and Kern, Krystal and Leeb, A. Frank and Caban-Martinez, J. Alberto and Mayer, C. Alexander and Osgood, Russell and Porter, Cynthia and Ranganathan, Sreenivasan and Stapleton, M. Heather and Schaefer Solle, Natasha and Toennis, Christine and Urwin, J. Derek and Valenti, Michelle and Gulotta, J. John", title="The Fire Fighter Cancer Cohort Study: Protocol for a Longitudinal Occupational Cohort Study", journal="JMIR Res Protoc", year="2025", month="Apr", day="22", volume="14", pages="e70522", keywords="firefighter", keywords="cancer", keywords="prospective cohort study", keywords="biomonitoring", keywords="protocol", abstract="Background: Firefighters are at an increased risk of cancer and other health conditions compared with the general population. However, the specific exposures and mechanisms contributing to these risks are not fully understood. This information is critical to formulate and test protective interventions. Objective: The purpose of the Fire Fighter Cancer Cohort Study (FFCCS) is to conduct community-engaged research with the fire service to advance the evaluation and reduction of firefighter exposures, along with understanding and mitigating effects leading to an increased risk of cancer and other health conditions. This involves establishing a long-term (>30 years) firefighter multicenter prospective cohort study. Methods: The structure of the FFCCS includes a fire service oversight and planning board to provide guidance and foster communication between researchers and fire organizations; a data coordinating center overseeing survey data collection and data management; an exposure assessment center working with quantitative exposure data to construct a firefighter job exposure matrix; and a biomarker analysis center, including a biorepository. Together, the centers evaluate the association between firefighter exposures and toxic health effects. Firefighter research liaisons are involved in all phases of the research. The FFCCS research design primarily uses a set of core and project-specific survey questions accompanied by a collection of biological samples (blood and urine) for the analysis of biomarkers of exposure and effect. Data and samples are collected upon entry into the study, with subsequent collection after eligible exposures, and at intervals (eg, 1-2 years) after enrollment. FFCCS data collection and analysis have been developed to evaluate unique exposures for specific firefighter groups; cancer risks; and end points in addition to cancer, such as reproductive outcomes. Recruitment is carried out with coordination from partnering fire departments and eligible participants, including active career and volunteer firefighters in the United States. Results: The FFCCS protocol development was first funded by the US Federal Emergency Management Agency in 2016, with enrollment beginning in February 2018. As of September 2024, >6200 participants from >275 departments across 31 states have enrolled, including recruit and incumbent firefighters. Biological samples have been analyzed for measures of exposure and effect. Specific groups enrolled in the FFCCS include career and volunteer structural firefighters, women firefighters, trainers, fire investigators, wildland firefighters, firefighters responding to wildland-urban interface fires, and airport firefighters. Peer-reviewed published results include measurement of exposures and the toxic effects of firefighting exposure. Whenever possible, research results are provided back to individual participants. Conclusions: The FFCCS is a unique, community-engaged, multicenter prospective cohort study focused on the fire service. Study results contribute to the evaluation of exposures, effects, and preventive interventions across multiple sectors of the US fire service, with broad implications nationally. International Registered Report Identifier (IRRID): DERR1-10.2196/70522 ", doi="10.2196/70522", url="https://www.researchprotocols.org/2025/1/e70522" } @Article{info:doi/10.2196/64544, author="Lee, Denise and Vaid, Akhil and Menon, M. Kartikeya and Freeman, Robert and Matteson, S. David and Marin, L. Michael and Nadkarni, N. Girish", title="Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study", journal="JMIR Form Res", year="2025", month="Apr", day="7", volume="9", pages="e64544", keywords="natural language processing", keywords="large language model", keywords="artificial intelligence", keywords="thyroid cancer", keywords="endocrine surgery", keywords="framework", keywords="privacy", keywords="medical", keywords="surgical pathology", keywords="report", keywords="NLP", keywords="medical question", abstract="Background: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinical narrative reports. However, the use of LLMs in the health care setting is limited by cost, computing power, and patient privacy concerns. Specifically, as interest in LLM-based clinical applications grows, regulatory safeguards must be established to avoid exposure of patient data through the public domain. The use of open-source LLMs deployed behind institutional firewalls may ensure the protection of private patient data. In this study, we evaluated the extraction performance of a locally deployed LLM for automated MQA from surgical pathology reports. Objective: We compared the performance of human reviewers and a locally deployed LLM tasked with extracting key histologic and staging information from surgical pathology reports. Methods: A total of 84 thyroid cancer surgical pathology reports were assessed by two independent reviewers and the open-source FastChat-T5 3B-parameter LLM using institutional computing resources. Longer text reports were split into 1200-character-long segments, followed by conversion to embeddings. Three segments with the highest similarity scores were integrated to create the final context for the LLM. The context was then made part of the question it was directed to answer. Twelve medical questions for staging and thyroid cancer recurrence risk data extraction were formulated and answered for each report. The time to respond and concordance of answers were evaluated. The concordance rate for each pairwise comparison (human-LLM and human-human) was calculated as the total number of concordant answers divided by the total number of answers for each of the 12 questions. The average concordance rate and associated error of all questions were tabulated for each pairwise comparison and evaluated with two-sided t tests. Results: Out of a total of 1008 questions answered, reviewers 1 and 2 had an average (SD) concordance rate of responses of 99\% (1\%; 999/1008 responses). The LLM was concordant with reviewers 1 and 2 at an overall average (SD) rate of 89\% (7\%; 896/1008 responses) and 89\% (7.2\%; 903/1008 responses). The overall time to review and answer questions for all reports was 170.7, 115, and 19.56 minutes for Reviewers 1, 2, and the LLM, respectively. Conclusions: The locally deployed LLM can be used for MQA with considerable time-saving and acceptable accuracy in responses. Prompt engineering and fine-tuning may further augment automated data extraction from clinical narratives for the provision of real-time, essential clinical insights. ", doi="10.2196/64544", url="https://formative.jmir.org/2025/1/e64544" } @Article{info:doi/10.2196/66286, author="Luo, Jia-Yuan and Deng, Yu-Long and Lu, Shang-Yi and Chen, Si-Yan and He, Rong-Quan and Qin, Di-Yuan and Chi, Bang-Teng and Chen, Gang and Yang, Xia and Peng, Wei", title="Current Status and Future Directions of Ferroptosis Research in Breast Cancer: Bibliometric Analysis", journal="Interact J Med Res", year="2025", month="Feb", day="26", volume="14", pages="e66286", keywords="breast cancer", keywords="ferroptosis", keywords="bibliometric", keywords="malignancy", keywords="cancer studies", keywords="treatment", keywords="bibliometric analysis", keywords="VOSviewer", keywords="China", keywords="United States", keywords="breast carcinoma", keywords="mammary cancer", keywords="strategy", keywords="trends", keywords="bibliography", keywords="review", keywords="disparities", keywords="forecast", keywords="treatment strategies", keywords="advancements", abstract="Background: Ferroptosis, as a novel modality of cell death, holds significant potential in elucidating the pathogenesis and advancing therapeutic strategies for breast cancer. Objective: This study aims to comprehensively analyze current ferroptosis research and future trends, guiding breast cancer research advancements and innovative treatment strategies. Methods: This research used the R package Bibliometrix (Department of Economic and Statistical Sciences at the University of Naples Federico II), VOSviewer (Centre for Science and Technology Studies at Leiden University), and CiteSpace (Drexel University's College of Information Science and Technology), to conduct a bibliometric analysis of 387 papers on breast cancer and ferroptosis from the Web of Science Core Collection. The analysis covers authors, institutions, journals, countries or regions, publication volumes, citations, and keywords. Results: The number of publications related to this field has surged annually, with China and the United States collaborating closely and leading in output. Sun Yat-sen University stands out among the institutions, while the journal Frontiers in Oncology and the author Efferth T contribute significantly to the field. Highly cited papers within the domain primarily focus on the induction of ferroptosis, protein regulation, and comparisons with other modes of cell death, providing a foundation for breast cancer treatment. Keyword analysis highlights the maturity of glutathione peroxidase 4-related research, with breast cancer subtypes emerging as motor themes and the tumor microenvironment, immunotherapy, and prognostic models identified as basic themes. Furthermore, the application of nanoparticles serves as an additional complement to the basic themes. Conclusions: The current research status in the field of ferroptosis and breast cancer primarily focuses on the exploration of relevant theoretical mechanisms, whereas future trends and mechanisms emphasize the investigation of therapeutic strategies, particularly the clinical application of immunotherapy related to the tumor microenvironment. Nanotherapy has demonstrated significant clinical potential in this domain. Future research directions should deepen the exploration in this field and accelerate the clinical translation of research findings to provide new insights and directions for the innovation and development of breast cancer treatment strategies. ", doi="10.2196/66286", url="https://www.i-jmr.org/2025/1/e66286" } @Article{info:doi/10.2196/63626, author="Kuerbanjiang, Warisijiang and Peng, Shengzhe and Jiamaliding, Yiershatijiang and Yi, Yuexiong", title="Performance Evaluation of Large Language Models in Cervical Cancer Management Based on a Standardized Questionnaire: Comparative Study", journal="J Med Internet Res", year="2025", month="Feb", day="5", volume="27", pages="e63626", keywords="large language model", keywords="cervical cancer", keywords="screening", keywords="artificial intelligence", keywords="model interpretability", abstract="Background: Cervical cancer remains the fourth leading cause of death among women globally, with a particularly severe burden in low-resource settings. A comprehensive approach---from screening to diagnosis and treatment---is essential for effective prevention and management. Large language models (LLMs) have emerged as potential tools to support health care, though their specific role in cervical cancer management remains underexplored. Objective: This study aims to systematically evaluate the performance and interpretability of LLMs in cervical cancer management. Methods: Models were selected from the AlpacaEval leaderboard version 2.0 and based on the capabilities of our computer. The questions inputted into the models cover aspects of general knowledge, screening, diagnosis, and treatment, according to guidelines. The prompt was developed using the Context, Objective, Style, Tone, Audience, and Response (CO-STAR) framework. Responses were evaluated for accuracy, guideline compliance, clarity, and practicality, graded as A, B, C, and D with corresponding scores of 3, 2, 1, and 0. The effective rate was calculated as the ratio of A and B responses to the total number of designed questions. Local Interpretable Model-Agnostic Explanations (LIME) was used to explain and enhance physicians' trust in model outputs within the medical context. Results: Nine models were included in this study, and a set of 100 standardized questions covering general information, screening, diagnosis, and treatment was designed based on international and national guidelines. Seven models (ChatGPT-4.0 Turbo, Claude 2, Gemini Pro, Mistral-7B-v0.2, Starling-LM-7B alpha, HuatuoGPT, and BioMedLM 2.7B) provided stable responses. Among all the models included, ChatGPT-4.0 Turbo ranked first with a mean score of 2.67 (95\% CI 2.54-2.80; effective rate 94.00\%) with a prompt and 2.52 (95\% CI 2.37-2.67; effective rate 87.00\%) without a prompt, outperforming the other 8 models (P<.001). Regardless of prompts, QiZhenGPT consistently ranked among the lowest-performing models, with P<.01 in comparisons against all models except BioMedLM. Interpretability analysis showed that prompts improved alignment with human annotations for proprietary models (median intersection over union 0.43), while medical-specialized models exhibited limited improvement. Conclusions: Proprietary LLMs, particularly ChatGPT-4.0 Turbo and Claude 2, show promise in clinical decision-making involving logical analysis. The use of prompts can enhance the accuracy of some models in cervical cancer management to varying degrees. Medical-specialized models, such as HuatuoGPT and BioMedLM, did not perform as well as expected in this study. By contrast, proprietary models, particularly those augmented with prompts, demonstrated notable accuracy and interpretability in medical tasks, such as cervical cancer management. However, this study underscores the need for further research to explore the practical application of LLMs in medical practice. ", doi="10.2196/63626", url="https://www.jmir.org/2025/1/e63626" } @Article{info:doi/10.2196/57379, author="Kim, Yesol and Kim, Geonah and Cho, Hyeonmi and Kim, Yeonju and Choi, Mona", title="Application of Patient-Generated Health Data Among Older Adults With Cancer: Scoping Review", journal="J Med Internet Res", year="2025", month="Feb", day="4", volume="27", pages="e57379", keywords="patient-generated health data", keywords="wearable devices", keywords="patient-reported outcomes", keywords="patient-centered care", keywords="older adults", keywords="cancer", keywords="scoping review", abstract="Background: The advancement of information and communication technologies has spurred a growing interest in and increased applications of patient-generated health data (PGHD). In particular, PGHD may be promising for older adults with cancer who have increased survival rates and experience a variety of symptoms. Objective: This scoping review aimed to identify the characteristics of research on PGHD as applied to older adults with cancer and to assess the current use of PGHD. Methods: Guided by Arksey and O'Malley as well as the JBI (Joanna Briggs Institute) methodology for scoping reviews, 6 electronic databases were searched: PubMed, Embase, CINAHL, Cochrane Library, Scopus, and Web of Science. In addition, the reference lists of the selected studies were screened to identify gray literature. The researchers independently screened the literature according to the predefined eligibility criteria. Data from the selected studies were extracted, capturing study, participant, and PGHD characteristics. Results: Of the 1090 identified studies, 88 were selected. The publication trend gradually increased, with a majority of studies published since 2017 (69/88, 78\%). Almost half of the studies were conducted in North America (38/88, 43\%), followed by Europe (30/88, 34\%). The most common setting in which the studies were conducted was the participant's home (69/88, 78\%). The treatment status varied; the median sample size was 50 (IQR 33.8-84.0). The devices that were used to measure the PGHD were classified as research-grade wearable devices (57/113, 50.4\%), consumer-grade wearable devices (28/113, 24.8\%), or smartphones or tablet PCs for mobile apps (23/113, 20.4\%). More than half of the studies measured physical activity (69/123, 56.1\%), followed by patient-reported outcomes (23/123, 18.7\%), vital signs (13/123, 10.6\%), and sleep (12/123, 9.8\%). The PGHD were mainly collected passively (63/88, 72\%), and active collection methods were used from 2015 onward (20/88, 23\%). In this review, the stages of PGHD use were classified as follows: (1) identification, monitoring, review, and analysis (88/88, 100\%); (2) feedback and reporting (32/88, 39\%); (3) motivation (30/88, 34\%); and (4) education and coaching (19/88, 22\%). Conclusions: This scoping review provides a comprehensive summary of the overall characteristics and use stages of PGHD in older adults with various types and stages of cancer. Future research should emphasize the use of PGHD, which interacts with patients to provide patient-centered care through patient engagement. By enhancing symptom monitoring, enabling timely interventions, and promoting patient involvement, PGHD have the potential to improve the well-being of older adults with cancer, contributing to better health management and quality of life. Therefore, our findings may provide valuable insights into PGHD that health care providers and researchers can use for geriatric cancer care. Trial Registration: Open Science Framework Registry OSF.IO/FZRD5; https://doi.org/10.17605/OSF.IO/FZRD5 ", doi="10.2196/57379", url="https://www.jmir.org/2025/1/e57379" } @Article{info:doi/10.2196/65286, author="Li, Xue and Wang, Youqing and Li, Huizhang and Wang, Le and Zhu, Juan and Yang, Chen and Du, Lingbin", title="Development of a Prediction Model and Risk Score for Self-Assessment and High-Risk Population Identification in Liver Cancer Screening: Prospective Cohort Study", journal="JMIR Public Health Surveill", year="2024", month="Dec", day="30", volume="10", pages="e65286", keywords="liver cancer", keywords="cancer screening", keywords="cancer surveillance", keywords="prediction model", keywords="early detection", keywords="risk score", keywords="self-assessment", abstract="Background: Liver cancer continues to pose a significant burden in China. To enhance the efficiency of screening, it is crucial to implement population stratification for liver cancer surveillance. Objective: This study aimed to develop a simple prediction model and risk score for liver cancer screening in the general population, with the goal of improving early detection and survival. Methods: This population-based cohort study focused on residents aged 40 to 74 years. Participants were enrolled between 2014 and 2019 and were prospectively followed until June 30, 2021. Data were collected through interviews at enrollment. A Cox proportional hazards regression was used to identify predictors and construct the prediction model. A risk score system was developed based on the weighted factors included in the prediction model. Results: A total of 153,082 study participants (67,586 males and 85,496 females) with a mean age of 55.86 years were included. During 781,125 person-years of follow-up (length of follow-up: median 6.07, IQR 3.07?7.09 years), 290 individuals were diagnosed with liver cancer. Key factors identified for the prediction model and risk score system included age (hazard ratio [HR] 1.06, 95\% CI 1.04?1.08), sex (male: HR 3.41, 95\% CI 2.44?4.78), education level (medium: HR 0.84, 95\% CI 0.61?1.15; high: HR 0.37, 95\% CI 0.17?0.78), cirrhosis (HR 11.93, 95\% CI 7.46?19.09), diabetes (HR 1.59, 95\% CI 1.08?2.34), and hepatitis B surface antigen (HBsAg) status (positive: HR 3.84, 95\% CI 2.38?6.19; unknown: HR 1.04, 95\% CI 0.73?1.49). The model exhibited excellent discrimination in both the development and validation sets, with areas under the curve (AUC) of 0.802, 0.812, and 0.791 for predicting liver cancer at the 1-, 3-, and 5-year periods in the development set and 0.751, 0.763, and 0.712 in the validation set, respectively. Sensitivity analyses applied to the subgroups of participants without cirrhosis and with a negative or unknown HBsAg status yielded similar performances, with AUCs ranging from 0.707 to 0.831. Calibration plots indicated an excellent agreement between the observed and predicted probabilities of developing liver cancer over the 1-, 3-, and 5-year periods. Compared to the low-risk group, participants in the high-risk and moderate-risk groups had 11.88-fold (95\% CI 8.67?16.27) and 3.51-fold (95\% CI 2.58?4.76) higher risks of liver cancer, respectively. Decision curve analysis demonstrated that the risk score provided a higher net benefit compared to the current strategy. To aid in risk stratification for individual participants, a user-friendly web-based scoring system was developed. Conclusions: A straightforward liver cancer prediction model was created by incorporating easily accessible variables. This model enables the identification of asymptomatic individuals who should be prioritized for liver cancer screening. ", doi="10.2196/65286", url="https://publichealth.jmir.org/2024/1/e65286" } @Article{info:doi/10.2196/63155, author="Hermansen, Anna and Pollard, Samantha and McGrail, Kimberlyn and Bansback, Nick and Regier, A. Dean", title="Heuristics Identified in Health Data--Sharing Preferences of Patients With Cancer: Qualitative Focus Group Study", journal="J Med Internet Res", year="2024", month="Dec", day="17", volume="26", pages="e63155", keywords="heuristics", keywords="health data sharing", keywords="cancer patients", keywords="decision-making", keywords="real-world data", keywords="altruism", keywords="trust", keywords="control", keywords="data sharing", keywords="focus group", keywords="precision medicine", keywords="clinical data", keywords="exploratory study", keywords="qualitative", keywords="Canada", keywords="thematic analysis", keywords="informed consent", keywords="patient education", keywords="information technology", keywords="healthcare", keywords="medical informatics", abstract="Background: Evaluating precision oncology outcomes requires access to real-world and clinical trial data. Access is based on consent, and consent is based on patients' informed preferences when deciding to share their data. Decision-making is often modeled using utility theory, but a complex decision context calls for a consideration of how heuristic, intuitive thought processes interact with rational utility maximization. Data-sharing decision-making has been studied using heuristic theory, but almost no heuristic research exists in the health data context. This study explores this evidence gap, applying a qualitative approach to probe for evidence of heuristic mechanisms behind the health data-sharing preferences of those who have experienced cancer. Exploring qualitative decision-making reveals the types of heuristics used and how they are related to the process of decision-making to better understand whether consent mechanisms should consider nonrational processes to better serve patient decision-making. Objective: This study aimed to explore how patients with cancer use heuristics when deciding whether to share their data for research. Methods: The researchers conducted a focus group study of Canadians who have experienced cancer. We recruited participants through an online advertisement, screening individuals based on their ability to increase demographic diversity in the sample. We reviewed the literature on data-sharing platforms to develop a semistructured topic guide on concerns about data sharing, incentives to share, and consent and control. Focus group facilitators led the open-ended discussions about data-sharing preferences that revealed underlying heuristics. Two qualitative analysts coded transcripts using a heuristic framework developed from a review of the literature. Transcripts were analyzed for heuristic instances which were grouped according to sociocultural categories. Using thematic analysis, the analysts generated reflexive themes through norming sessions and consultations. Results: A total of 3 focus groups were held with 19 participants in total. The analysis identified 12 heuristics underlying intentions to share data. From the thematic analysis, we identified how the heuristics of social norms and community building were expressed through altruism; the recognition, reputation, and authority heuristics led to (dis)trust in certain institutions; the need for security prompted the illusion of control and transparency heuristics; and the availability and affect heuristics influenced attitudes around risk and benefit. These thematic relationships all had impacts on the participants' intentions to share their health data. Conclusions: The findings provide a novel qualitative understanding of how health data--sharing decisions and preferences may be based on heuristic processing. As patients consider the extent of risks and benefits, heuristic processes influence their assessment of anticipated outcomes, which may not result in rational, truly informed consent. This study shows how considering heuristic processing when designing current consent mechanisms opens up the opportunity for more meaningful and realistic interactions with the complex decision-making context. ", doi="10.2196/63155", url="https://www.jmir.org/2024/1/e63155" } @Article{info:doi/10.2196/63289, author="Carbunaru, Samuel and Neshatvar, Yassamin and Do, Hyungrok and Murray, Katie and Ranganath, Rajesh and Nayan, Madhur", title="Survival After Radical Cystectomy for Bladder Cancer: Development of a Fair Machine Learning Model", journal="JMIR Med Inform", year="2024", month="Dec", day="13", volume="12", pages="e63289", keywords="machine learning", keywords="bladder cancer", keywords="survival", keywords="prediction", keywords="model", keywords="bias", keywords="fairness", keywords="radical cystectomy", keywords="mortality rate", keywords="algorithmic fairness", keywords="health equity", keywords="healthcare disparities", abstract="Background: Prediction models based on machine learning (ML) methods are being increasingly developed and adopted in health care. However, these models may be prone to bias and considered unfair if they demonstrate variable performance in population subgroups. An unfair model is of particular concern in bladder cancer, where disparities have been identified in sex and racial subgroups. Objective: This study aims (1) to develop a ML model to predict survival after radical cystectomy for bladder cancer and evaluate for potential model bias in sex and racial subgroups; and (2) to compare algorithm unfairness mitigation techniques to improve model fairness. Methods: We trained and compared various ML classification algorithms to predict 5-year survival after radical cystectomy using the National Cancer Database. The primary model performance metric was the F1-score. The primary metric for model fairness was the equalized odds ratio (eOR). We compared 3 algorithm unfairness mitigation techniques to improve eOR. Results: We identified 16,481 patients; 23.1\% (n=3800) were female, and 91.5\% (n=15,080) were ``White,'' 5\% (n=832) were ``Black,'' 2.3\% (n=373) were ``Hispanic,'' and 1.2\% (n=196) were ``Asian.'' The 5-year mortality rate was 75\% (n=12,290). The best naive model was extreme gradient boosting (XGBoost), which had an F1-score of 0.860 and eOR of 0.619. All unfairness mitigation techniques increased the eOR, with correlation remover showing the highest increase and resulting in a final eOR of 0.750. This mitigated model had F1-scores of 0.86, 0.904, and 0.824 in the full, Black male, and Asian female test sets, respectively. Conclusions: The ML model predicting survival after radical cystectomy exhibited bias across sex and racial subgroups. By using algorithm unfairness mitigation techniques, we improved algorithmic fairness as measured by the eOR. Our study highlights the role of not only evaluating for model bias but also actively mitigating such disparities to ensure equitable health care delivery. We also deployed the first web-based fair ML model for predicting survival after radical cystectomy. ", doi="10.2196/63289", url="https://medinform.jmir.org/2024/1/e63289" } @Article{info:doi/10.2196/59480, author="Gopukumar, Deepika and Menon, Nirup and Schoen, W. Martin", title="Medication Prescription Policy for US Veterans With Metastatic Castration-Resistant Prostate Cancer: Causal Machine Learning Approach", journal="JMIR Med Inform", year="2024", month="Nov", day="19", volume="12", pages="e59480", keywords="prostate cancer", keywords="metastatic castration resistant prostate cancer", keywords="causal survival forest", keywords="machine learning", keywords="heterogeneity", keywords="prescription policy tree", keywords="oncology", keywords="pharmacology", abstract="Background: Prostate cancer is the second leading cause of death among American men. If detected and treated at an early stage, prostate cancer is often curable. However, an advanced stage such as metastatic castration-resistant prostate cancer (mCRPC) has a high risk of mortality. Multiple treatment options exist, the most common included docetaxel, abiraterone, and enzalutamide. Docetaxel is a cytotoxic chemotherapy, whereas abiraterone and enzalutamide are androgen receptor pathway inhibitors (ARPI). ARPIs are preferred over docetaxel due to lower toxicity. No study has used machine learning with patients' demographics, test results, and comorbidities to identify heterogeneous treatment rules that might improve the survival duration of patients with mCRPC. Objective: This study aimed to measure patient-level heterogeneity in the association of medication prescribed with overall survival duration (in the form of follow-up days) and arrive at a set of medication prescription rules using patient demographics, test results, and comorbidities. Methods: We excluded patients with mCRPC who were on docetaxel, cabaxitaxel, mitoxantrone, and sipuleucel-T either before or after the prescription of an ARPI. We included only the African American and white populations. In total, 2886 identified veterans treated for mCRPC who were prescribed either abiraterone or enzalutamide as the first line of treatment from 2014 to 2017, with follow-up until 2020, were analyzed. We used causal survival forests for analysis. The unit level of analysis was the patient. The primary outcome of this study was follow-up days indicating survival duration while on the first-line medication. After estimating the treatment effect, a prescription policy tree was constructed. Results: For 2886 veterans, enzalutamide is associated with an average of 59.94 (95\% CI 35.60-84.28) more days of survival than abiraterone. The increase in overall survival duration for the 2 drugs varied across patient demographics, test results, and comorbidities. Two data-driven subgroups of patients were identified by ranking them on their augmented inverse-propensity weighted (AIPW) scores. The average AIPW scores for the 2 subgroups were 19.36 (95\% CI --16.93 to 55.65) and 100.68 (95\% CI 62.46-138.89). Based on visualization and t test, the AIPW score for low and high subgroups was significant (P=.003), thereby supporting heterogeneity. The analysis resulted in a set of prescription rules for the 2 ARPIs based on a few covariates available to the physicians at the time of prescription. Conclusions: This study of 2886 veterans showed evidence of heterogeneity and that survival days may be improved for certain patients with mCRPC based on the medication prescribed. Findings suggest that prescription rules based on the patient characteristics, laboratory test results, and comorbidities available to the physician at the time of prescription could improve survival by providing personalized treatment decisions. ", doi="10.2196/59480", url="https://medinform.jmir.org/2024/1/e59480" } @Article{info:doi/10.2196/50023, author="Renne, Lorenzo Salvatore and Cammelli, Manuela and Santori, Ilaria and Tassan-Mangina, Marta and Sam{\`a}, Laura and Ruspi, Laura and Sicoli, Federico and Colombo, Piergiuseppe and Terracciano, Maria Luigi and Quagliuolo, Vittorio and Cananzi, Maria Ferdinando Carlo", title="True Mitotic Count Prediction in Gastrointestinal Stromal Tumors: Bayesian Network Model and PROMETheus (Preoperative Mitosis Estimator Tool) Application Development", journal="J Med Internet Res", year="2024", month="Oct", day="22", volume="26", pages="e50023", keywords="GIST mitosis", keywords="risk classification", keywords="mHealth", keywords="mobile health", keywords="neoadjuvant therapy", keywords="patient stratification", keywords="Gastrointestinal Stroma", keywords="preoperative risk", abstract="Background: Gastrointestinal stromal tumors (GISTs) present a complex clinical landscape, where precise preoperative risk assessment plays a pivotal role in guiding therapeutic decisions. Conventional methods for evaluating mitotic count, such as biopsy-based assessments, encounter challenges stemming from tumor heterogeneity and sampling biases, thereby underscoring the urgent need for innovative approaches to enhance prognostic accuracy. Objective: The primary objective of this study was to develop a robust and reliable computational tool, PROMETheus (Preoperative Mitosis Estimator Tool), aimed at refining patient stratification through the precise estimation of mitotic count in GISTs. Methods: Using advanced Bayesian network methodologies, we constructed a directed acyclic graph (DAG) integrating pertinent clinicopathological variables essential for accurate mitotic count prediction on the surgical specimen. Key parameters identified and incorporated into the model encompassed tumor size, location, mitotic count from biopsy specimens, surface area evaluated during biopsy, and tumor response to therapy, when applicable. Rigorous testing procedures, including prior predictive simulations, validation utilizing synthetic data sets were employed. Finally, the model was trained on a comprehensive cohort of real-world GIST cases (n=80), drawn from the repository of the Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Humanitas Research Hospital, with a total of 160 cases analyzed. Results: Our computational model exhibited excellent diagnostic performance on synthetic data. Different model architecture were selected based on lower deviance and robust out-of-sample predictive capabilities. Posterior predictive checks (retrodiction) further corroborated the model's accuracy. Subsequently, PROMETheus was developed. This is an intuitive tool that dynamically computes predicted mitotic count and risk assessment on surgical specimens based on tumor-specific attributes, including size, location, surface area, and biopsy-derived mitotic count, using posterior probabilities derived from the model. Conclusions: The deployment of PROMETheus represents a potential advancement in preoperative risk stratification for GISTs, offering clinicians a precise and reliable means to anticipate mitotic counts on surgical specimens and a solid base to stratify patients for clinical studies. By facilitating tailored therapeutic strategies, this innovative tool is poised to revolutionize clinical decision-making paradigms, ultimately translating into improved patient outcomes and enhanced prognostic precision in the management of GISTs. ", doi="10.2196/50023", url="https://www.jmir.org/2024/1/e50023" } @Article{info:doi/10.2196/58705, author="Manuilova, Iryna and Bossenz, Jan and Weise, Bianka Annemarie and Boehm, Dominik and Strantz, Cosima and Unberath, Philipp and Reimer, Niklas and Metzger, Patrick and Pauli, Thomas and Werle, D. Silke and Schulze, Susann and Hiemer, Sonja and Ustjanzew, Arsenij and Kestler, A. Hans and Busch, Hauke and Brors, Benedikt and Christoph, Jan", title="Identifications of Similarity Metrics for Patients With Cancer: Protocol for a Scoping Review", journal="JMIR Res Protoc", year="2024", month="Sep", day="4", volume="13", pages="e58705", keywords="patient similarity", keywords="cancer research", keywords="patient similarity applications", keywords="precision medicine", keywords="cancer similarity metrics", keywords="scoping review protocol", abstract="Background: Understanding the similarities of patients with cancer is essential to advancing personalized medicine, improving patient outcomes, and developing more effective and individualized treatments. It enables researchers to discover important patterns, biomarkers, and treatment strategies that can have a significant impact on cancer research and oncology. In addition, the identification of previously successfully treated patients supports oncologists in making treatment decisions for a new patient who is clinically or molecularly similar to the previous patient. Objective: The planned review aims to systematically summarize, map, and describe existing evidence to understand how patient similarity is defined and used in cancer research and clinical care. Methods: To systematically identify relevant studies and to ensure reproducibility and transparency of the review process, a comprehensive literature search will be conducted in several bibliographic databases, including Web of Science, PubMed, LIVIVIVO, and MEDLINE, covering the period from 1998 to February 2024. After the initial duplicate deletion phase, a study selection phase will be applied using Rayyan, which consists of 3 distinct steps: title and abstract screening, disagreement resolution, and full-text screening. To ensure the integrity and quality of the selection process, each of these steps is preceded by a pilot testing phase. This methodological process will culminate in the presentation of the final research results in a structured form according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) flowchart. The protocol has been registered in the Journal of Medical Internet Research. Results: This protocol outlines the methodologies used in conducting the scoping review. A search of the specified electronic databases and after removing duplicates resulted in 1183 unique records. As of March 2024, the review process has moved to the full-text evaluation phase. At this stage, data extraction will be conducted using a pretested chart template. Conclusions: The scoping review protocol, centered on these main concepts, aims to systematically map the available evidence on patient similarity among patients with cancer. By defining the types of data sources, approaches, and methods used in the field, and aligning these with the research questions, the review will provide a foundation for future research and clinical application in personalized cancer care. This protocol will guide the literature search, data extraction, and synthesis of findings to achieve the review's objectives. International Registered Report Identifier (IRRID): DERR1-10.2196/58705 ", doi="10.2196/58705", url="https://www.researchprotocols.org/2024/1/e58705", url="http://www.ncbi.nlm.nih.gov/pubmed/39230952" } @Article{info:doi/10.2196/48516, author="Bowers, M. Jennifer and Huelsnitz, O. Chloe and Dwyer, A. Laura and Gibson, P. Laurel and Agurs-Collins, Tanya and Ferrer, A. Rebecca and Acevedo, M. Amanda", title="Measuring Relationship Influences on Romantic Couples' Cancer-Related Behaviors During the COVID-19 Pandemic: Protocol for a Longitudinal Online Study of Dyads and Cancer Survivors", journal="JMIR Res Protoc", year="2024", month="Jul", day="31", volume="13", pages="e48516", keywords="cancer prevention", keywords="COVID-19", keywords="risk perceptions", keywords="dyads", keywords="romantic relationships", keywords="cancer", keywords="oncology", keywords="survivor", keywords="survivors", keywords="dyad", keywords="spouse", keywords="spousal", keywords="partner", keywords="health behavior", keywords="health behaviors", keywords="cohabiting", keywords="cohabit", keywords="study design", keywords="recruit", keywords="recruitment", keywords="methodology", keywords="methods", keywords="enrol", keywords="enrolment", keywords="enroll", keywords="enrollment", abstract="Background: Research has established the effects of romantic relationships on individuals' morbidity and mortality. However, the interplay between relationship functioning, affective processes, and health behaviors has been relatively understudied. During the COVID-19 pandemic, relational processes may influence novel health behaviors such as social distancing and masking. Objective: We describe the design, recruitment, and methods of the relationships, risk perceptions, and cancer-related behaviors during the COVID-19 pandemic study. This study was developed to understand how relational and affective processes influence romantic partners' engagement in cancer prevention behaviors as well as health behaviors introduced or exacerbated by the COVID-19 pandemic. Methods: The relationships, risk perceptions, and cancer-related behaviors during the COVID-19 pandemic study used online survey methods to recruit and enroll 2 cohorts of individuals involved in cohabiting romantic relationships, including 1 cohort of dyads (n=223) and 1 cohort of cancer survivors (n=443). Survey assessments were completed over 2 time points that were 5.57 (SD 3.14) weeks apart on average. Health behaviors assessed included COVID-19 vaccination and social distancing, physical activity, diet, sleep, alcohol use, and smoking behavior. We also examined relationship factors, psychological distress, and household chaos. Results: Data collection occurred between October 2021 and August 2022. During that time, a total of 926 participants were enrolled, of which about two-thirds were from the United Kingdom (n=622, 67.8\%) and one-third were from the United States (n=296, 32.2\%); about two-thirds were married (n=608, 66.2\%) and one-third were members of unmarried couples (n=294, 32\%). In cohorts 1 and 2, the mean age was about 34 and 50, respectively. Out of 478 participants in cohort 1, 19 (4\%) identified as Hispanic or Latino/a, 79 (17\%) as non-Hispanic Asian, 40 (9\%) as non-Hispanic Black or African American, and 306 (64\%) as non-Hispanic White; 62 (13\%) participants identified their sexual orientation as bisexual or pansexual, 359 (75.1\%) as heterosexual or straight, and 53 (11\%) as gay or lesbian. In cohort 2, out of 440 participants, 13 (3\%) identified as Hispanic or Latino/a, 8 (2\%) as non-Hispanic Asian, 5 (1\%) as non-Hispanic Black or African American, and 398 (90.5\%) as non-Hispanic White; 41 (9\%) participants identified their sexual orientation as bisexual or pansexual, 384 (87.3\%) as heterosexual or straight, and 13 (3\%) as gay or lesbian. The overall enrollment rate for individuals was 66.14\% and the overall completion rate was 80.08\%. Conclusions: We discuss best practices for collecting online survey data for studies examining relationships and health, challenges related to the COVID-19 pandemic, recruitment of underrepresented populations, and enrollment of dyads. Recommendations include conducting pilot studies, allowing for extra time in the data collection timeline for marginalized or underserved populations, surplus screening to account for expected attrition within dyads, as well as planning dyad-specific data quality checks. International Registered Report Identifier (IRRID): DERR1-10.2196/48516 ", doi="10.2196/48516", url="https://www.researchprotocols.org/2024/1/e48516" } @Article{info:doi/10.2196/52985, author="Baum, Eleonore and Thiel, Christian and Kobleder, Andrea and Bernhardsgr{\"u}tter, Daniela and Engst, Ramona and Maurer, Carola and Koller, Antje", title="Using a Mobile Messenger Service as a Digital Diary to Capture Patients' Experiences Along Their Interorganizational Treatment Path in Gynecologic Oncology: Lessons Learned", journal="JMIR Cancer", year="2024", month="Jul", day="29", volume="10", pages="e52985", keywords="mobile apps", keywords="computer security", keywords="confidentiality", keywords="data collection", keywords="oncology", keywords="breast neoplasms", keywords="mobile phone", doi="10.2196/52985", url="https://cancer.jmir.org/2024/1/e52985", url="http://www.ncbi.nlm.nih.gov/pubmed/39073852" } @Article{info:doi/10.2196/42123, author="Tsiouris, Angeliki and Mayer, Anna and Wiltink, J{\"o}rg and Ruckes, Christian and Beutel, E. Manfred and Zwerenz, R{\"u}diger", title="Recruitment of Patients With Cancer for a Clinical Trial Evaluating a Web-Based Psycho-Oncological Intervention: Secondary Analysis of a Diversified Recruitment Strategy in a Randomized Controlled Trial", journal="JMIR Cancer", year="2023", month="Nov", day="27", volume="9", pages="e42123", keywords="psycho-oncology", keywords="cancer", keywords="recruitment", keywords="social media", keywords="web-based interventions", keywords="web-based recruitment", abstract="Background: Participant recruitment poses challenges in psycho-oncological intervention research, such as psycho-oncological web-based intervention studies. Strict consecutive recruitment in clinical settings provides important methodological benefits but is often associated with low response rates and reduced practicability and ecological validity. In addition to preexisting recruitment barriers, the protective measures owing to the COVID-19 pandemic restricted recruitment activities in the clinical setting since March 2020. Objective: This study aims to outline the recruitment strategy for a randomized controlled trial evaluating the unguided emotion-based psycho-oncological online self-help (epos), which combined traditional and web-based recruitment. Methods: We developed a combined recruitment strategy including traditional (eg, recruitment in clinics, medical practices, cancer counseling centers, and newspapers) and web-based recruitment (Instagram, Facebook, and web pages). Recruitment was conducted between May 2020 and September 2021. Eligible participants for this study were adult patients with any type of cancer who were currently receiving treatment or in posttreatment care. They were also required to have a good command of the German language and access to a device suitable for web-based interventions, such as a laptop or computer. Results: We analyzed data from 304 participants who were enrolled in a 17-month recruitment period using various recruitment strategies. Web-based and traditional recruitment strategies led to comparable numbers of participants (151/304, 49.7\% vs 153/304, 50.3\%). However, web-based recruitment required much less effort. Regardless of the recruitment strategy, the total sample did not accurately represent patients with cancer currently undergoing treatment for major types of cancer in terms of various sociodemographic characteristics, including but not limited to sex and age. However, among the web-recruited study participants, the proportion of female participants was even higher (P<.001), the mean age was lower (P=.005), private internet use was higher (on weekdays: P=.007; on weekends: P=.02), and the number of those who were currently under treatment was higher (P=.048). Other demographic and medical characteristics revealed no significant differences between the groups. The majority of participants registered as self-referred (236/296, 79.7\%) instead of having followed the recommendation of or study invitation from a health care professional. Conclusions: The combined recruitment strategy helped overcome general and COVID-19--specific recruitment barriers and provided the targeted participant number. Social media recruitment was the most efficient individual recruitment strategy for participant enrollment. Differences in some demographic and medical characteristics emerged, which should be considered in future analyses. Implications and recommendations for social media recruitment based on personal experiences are presented. Trial Registration: German Clinical Trials Register DRKS00021144; https://drks.de/search/en/trial/DRKS00021144 International Registered Report Identifier (IRRID): RR2-10.1016/j.invent.2021.100410 ", doi="10.2196/42123", url="https://cancer.jmir.org/2023/1/e42123", url="http://www.ncbi.nlm.nih.gov/pubmed/38010774" } @Article{info:doi/10.2196/49774, author="Spooner, Caitlin and Vivat, Bella and White, Nicola and Stone, Patrick", title="Developing a Core Outcome Set for Prognostic Research in Palliative Cancer Care: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2023", month="Sep", day="1", volume="12", pages="e49774", keywords="core outcome set", keywords="palliative care", keywords="end-of-life", keywords="prognosis", keywords="advanced cancer", keywords="systematic review", keywords="interviews", keywords="Delphi study", abstract="Background: Studies exploring the impact of receiving end-of-life prognoses in patients with advanced cancer use a variety of different measures to evaluate the outcomes, and thus report often conflicting findings. The standardization of outcomes reported in studies of prognostication in palliative cancer care could enable uniform assessment and reporting, as well as intertrial comparisons. A core outcome set promotes consistency in outcome selection and reporting among studies within a particular population. We aim to develop a set of core outcomes to be used to measure the impact of end-of-life prognostication in palliative cancer care. Objective: This protocol outlines the proposed methodology to develop a core outcome set for measuring the impact of end-of-life prognostication in palliative cancer care. Methods: We will adopt a mixed methods approach consisting of 3 phases using methodology recommended by the Core Outcome Measure in Effectiveness Trials (COMET) initiative. In phase I, we will conduct a systematic review to identify existing outcomes that prognostic studies have previously used, so as to inform the development of items and domains for the proposed core outcome set. Phase II will consist of semistructured interviews with patients with advanced cancer who are receiving palliative care, informal caregivers, and clinicians, to explore their perceptions and experiences of end-of-life prognostication. Outcomes identified in the interviews will be combined with those found in existing literature and taken forward to phase III, a Delphi survey, in which we will ask patients, informal caregivers, clinicians, and relevant researchers to rate these outcomes until consensus is achieved as to which are considered to be the most important for inclusion in the core outcome set. The resulting, prioritized outcomes will be discussed in a consensus meeting to agree and endorse the final core outcome set. Results: Ethical approval was received for this study in September 2022. As of July 2023, we have completed and published the systematic review (phase I) and have started recruitment for phase II. Data analysis for phase II has not yet started. We expect to complete the study by October 2024. Conclusions: This protocol presents the stepwise approach that will be taken to develop a core outcome set for measuring the impact of end-of-life prognostication in palliative cancer care. The final core outcome set has the potential for translation into clinical practice, allowing for consistent evaluation of emerging prognostic algorithms and improving communication of end-of-life prognostication. This study will also potentially facilitate the design of future clinical trials of the impact of end-of-life prognostication in palliative care that are acceptable to key stakeholders. Trial Registration: Core Outcome Measures in Effectiveness Trials 2136; https://www.comet-initiative.org/Studies/Details/2136 International Registered Report Identifier (IRRID): DERR1-10.2196/49774 ", doi="10.2196/49774", url="https://www.researchprotocols.org/2023/1/e49774", url="http://www.ncbi.nlm.nih.gov/pubmed/37656505" } @Article{info:doi/10.2196/49417, author="M{\"u}ller Fiedler, Augusto and Medeiros, Michelle and Fiedler, Dalinda Haidi", title="Targeted Glioblastoma Treatment via Synthesis and Functionalization of Gold Nanoparticles With De Novo--Engineered Transferrin-Like Peptides: Protocol for a Novel Method", journal="JMIR Res Protoc", year="2023", month="Aug", day="11", volume="12", pages="e49417", keywords="gold nanoparticles", keywords="glioblastoma", keywords="blood-brain barrier", keywords="transferrin-like peptides", keywords="drug delivery", keywords="brain tumor", keywords="neuro-oncology", keywords="chemotherapy", keywords="nanoparticle functionalization", keywords="pharmaceuticals", abstract="Background: Glioblastoma multiforme (GBM) is an aggressive brain tumor with limited treatment options due to the blood-brain barrier's (BBB's) impedance and inherent resistance to chemotherapy. Gold nanoparticles (AuNPs) functionalized with transferrin-like peptides show promise in overcoming these challenges, enhancing drug delivery to the brain, and reducing chemotherapy resistance. Objective: The primary goal of this study is to establish a detailed protocol for synthesizing and stabilizing AuNPs, functionalizing them with de novo--engineered transferrin-like peptides, and conjugating them with the chemotherapeutic agent temozolomide. This strategy aims to improve drug delivery across the BBB and circumvent chemotherapy resistance. The secondary objective includes an assessment of the safety and potential for in vivo use of the synthesized nanoparticle complex. Methods: The proposal involves multiple steps with rigorous quality control of AuNP synthesis, stabilization with surfactants, and polyethylene glycol coating. The engineered transferrin-like peptides will be synthesized and attached to the AuNPs' surface, followed by the attachment of temozolomide and O6-methylguanine-DNA methyltransferase inhibitors. The resulting complex will undergo in vitro testing to assess BBB penetration, efficacy against GBM cells, and potential toxicity. Results: Initial preliminary experiments and simulations suggest successful synthesis and stabilization of AuNPs and effective attachment of transferrin-like peptides. We propose peptide attachment verification using Fourier transform infrared spectroscopy and surface plasmon resonance. Additionally, we will conduct pH stability tests to ensure our functionalized AuNPs retain their properties in acidic brain tumor microenvironments. Conclusions: The proposed functionalization of AuNPs with de novo--engineered transferrin-like peptides represents a novel approach to GBM treatment. Our strategy opens new avenues for drug delivery across the BBB and chemotherapy resistance reduction. While we primarily focus on in vitro studies and computational modeling at this stage, successful completion will lead to further development, including in vivo studies and nanoparticle design optimization. This proposal anticipates inspiring future research and funding in neuro-oncology, presenting a potentially innovative and effective treatment option for GBM. International Registered Report Identifier (IRRID): RR1-10.2196/49417 ", doi="10.2196/49417", url="https://www.researchprotocols.org/2023/1/e49417", url="http://www.ncbi.nlm.nih.gov/pubmed/37531222" } @Article{info:doi/10.2196/43059, author="Alpert, Jordan and Kim, (Julia) Hyehyun and McDonnell, Cara and Guo, Yi and George, J. Thomas and Bian, Jiang and Wu, Yonghui", title="Barriers and Facilitators of Obtaining Social Determinants of Health of Patients With Cancer Through the Electronic Health Record Using Natural Language Processing Technology: Qualitative Feasibility Study With Stakeholder Interviews", journal="JMIR Form Res", year="2022", month="Dec", day="27", volume="6", number="12", pages="e43059", keywords="natural language processing", keywords="qualitative", keywords="social determinants of health", keywords="electronic health records", keywords="cancer", keywords="technology", keywords="education", keywords="patient", keywords="clinical", keywords="communication", keywords="data", abstract="Background: Social determinants of health (SDoH), such as geographic neighborhoods, access to health care, education, and social structure, are important factors affecting people's health and health outcomes. The SDoH of patients are scarcely documented in a discrete format in electronic health records (EHRs) but are often available in free-text clinical narratives such as physician notes. Innovative methods like natural language processing (NLP) are being developed to identify and extract SDoH from EHRs, but it is imperative that the input of key stakeholders is included as NLP systems are designed. Objective: This study aims to understand the feasibility, challenges, and benefits of developing an NLP system to uncover SDoH from clinical narratives by conducting interviews with key stakeholders: (1) oncologists, (2) data analysts, (3) citizen scientists, and (4) patient navigators. Methods: Individuals who frequently work with SDoH data were invited to participate in semistructured interviews. All interviews were recorded and subsequently transcribed. After coding transcripts and developing a codebook, the constant comparative method was used to generate themes. Results: A total of 16 participants were interviewed (5 data analysts, 4 patient navigators, 4 physicians, and 3 citizen scientists). Three main themes emerged, accompanied by subthemes. The first theme, importance and approaches to obtaining SDoH, describes how every participant (n=16, 100\%) regarded SDoH as important. In particular, proximity to the hospital and income levels were frequently relied upon. Communication about SDoH typically occurs during the initial conversation with the oncologist, but more personal information is often acquired by patient navigators. The second theme, SDoH exists in numerous forms, exemplified how SDoH arises during informal communication and can be difficult to enter into the EHR. The final theme, incorporating SDoH into health services research, addresses how more informed SDoH can be collected. One strategy is to empower patients so they are aware about the importance of SDoH, as well as employing NLP techniques to make narrative data available in a discrete format, which can provide oncologists with actionable data summaries. Conclusions: Extracting SDoH from EHRs was considered valuable and necessary, but obstacles such as narrative data format can make the process difficult. NLP can be a potential solution, but as the technology is developed, it is important to consider how key stakeholders document SDoH, apply the NLP systems, and use the extracted SDoH in health outcome studies. ", doi="10.2196/43059", url="https://formative.jmir.org/2022/12/e43059", url="http://www.ncbi.nlm.nih.gov/pubmed/36574288" } @Article{info:doi/10.2196/35639, author="Thiessen, Maclean and Harris, Daranne and Tang, Patricia and Raffin Bouchal, Shelley and Sinclair, Shane", title="Examining the Development of Information Needs Assessment Questionnaires in Oncology: Protocol for a Scoping Review", journal="JMIR Res Protoc", year="2022", month="Sep", day="1", volume="11", number="9", pages="e35639", keywords="information needs", keywords="cancer", keywords="patient-oriented research", keywords="psychometric", keywords="measure", keywords="questionnaire", keywords="oncology", abstract="Background: Information needs are one of the most prevalent unmet supportive care needs of those living with cancer, including patients and their informal caregivers. Understanding how existing questionnaires for evaluating information needs have been developed is important for guiding appropriate use and informing future research. A literature review examining how information needs assessment questionnaires for use in the cancer context have been developed, with a specific focus on how questionnaire items have been identified, does not exist. Objective: This scoping review will examine how questionnaires for assessing the information needs of those living with cancer have been developed with special focus on how patients, informal caregivers, and health care professionals have been involved in the selection and identification of questionnaire items. Methods: This review will include published studies describing the development and validation of information needs assessment questionnaires for use in the oncology context. MEDLINE (Ovid), Embase (Ovid), CINAHL, Scopus, Web of Science, the Cochrane Database of Systematic Reviews, and PsycInfo will be searched. Articles published at any point up to the date of the search will be eligible for inclusion. One person will screen titles and abstracts, and 2 people will screen and extract data from full-text articles. Results: Results are expected to be available in early 2023. Summary tables and a narrative summary will be used to describe results. Conclusions: This scoping review will assist in identifying appropriate information needs assessment tools to incorporate into clinical and research contexts in oncology. It will also identify if additional information needs assessment tools are needed. International Registered Report Identifier (IRRID): PRR1-10.2196/35639 ", doi="10.2196/35639", url="https://www.researchprotocols.org/2022/9/e35639", url="http://www.ncbi.nlm.nih.gov/pubmed/36048517" } @Article{info:doi/10.2196/35020, author="Ullah, Shahid and Ullah, Farhan and Rahman, Wajeeha and Karras, A. Dimitrios and Ullah, Anees and Ahmad, Gulzar and Ijaz, Muhammad and Gao, Tianshun", title="The Cancer Research Database (CRDB): Integrated Platform to Gain Statistical Insight Into the Correlation Between Cancer and COVID-19", journal="JMIR Cancer", year="2022", month="Jun", day="10", volume="8", number="2", pages="e35020", keywords="cancer database", keywords="COVID-19", keywords="CRDB", keywords="genomics", keywords="PHP", keywords="cancer and COVID-19", keywords="cancer statistics", keywords="cancer research", keywords="health database", keywords="research platform", abstract="Background: The advancement of cancer research has been facilitated through freely available cancer literature, databases, and tools. The age of genomics and big data has given rise to the need for cooperation and data sharing in order to make efficient use of this new information in the COVID-19 pandemic. Although there are many databases for cancer research, their access is not easy owing to different ways of processing and managing the data. There is an absence of a unified platform to manage all of them in a transparent and more comprehensible way. Objective: In this study, an improved integrated cancer research database and platform is provided to facilitate a deeper statistical insight into the correlation between cancer and the COVID-19 pandemic, unifying the collection of almost all previous published cancer databases and defining a model web database for cancer research, and scoring databases on the basis of the variety types of cancer, sample size, completeness of omics results, and user interface. Methods: Databases examined and integrated include the Data Portal database, Genomic database, Proteomic database, Expression database, Gene database, and Mutation database; and it is expected that this launch will sort, save, advance the understanding and encourage the use of these resources in the cancer research environment. Results: To make it easy to search valuable information, 85 cancer databases are provided in the form of a table, and a database of databases named the Cancer Research Database (CRDB) has been built and presented herein. Furthermore, the CRDB has been herein equipped with unique navigation tools in order to be explored by three methods; that is, any single database can be browsed by typing the name in the given search bar, while all categories can be browsed by clicking on the name of the category or image expression icon, thus serving as a facility that could provide all the category databases on a single click. Conclusions: The computational platform (PHP, HTML, CSS, and MySQL) used to build CRDB for the cancer scientific community can be freely investigated and browsed on the internet and is planned to be updated in a timely manner. In addition, based on the proposed platform, the status and diagnoses statistics of cancer during the COVID-19 pandemic have been thoroughly investigated herein using CRDB, thus providing an easy-to-manage, understandable framework that mines knowledge for future researchers. ", doi="10.2196/35020", url="https://cancer.jmir.org/2022/2/e35020", url="http://www.ncbi.nlm.nih.gov/pubmed/35430561" } @Article{info:doi/10.2196/27694, author="Chen, Pei-Chin and Lu, Yun-Ru and Kang, Yi-No and Chang, Chun-Chao", title="The Accuracy of Artificial Intelligence in the Endoscopic Diagnosis of Early Gastric Cancer: Pooled Analysis Study", journal="J Med Internet Res", year="2022", month="May", day="16", volume="24", number="5", pages="e27694", keywords="artificial intelligence", keywords="early gastric cancer", keywords="endoscopy", abstract="Background: Artificial intelligence (AI) for gastric cancer diagnosis has been discussed in recent years. The role of AI in early gastric cancer is more important than in advanced gastric cancer since early gastric cancer is not easily identified in clinical practice. However, to our knowledge, past syntheses appear to have limited focus on the populations with early gastric cancer. Objective: The purpose of this study is to evaluate the diagnostic accuracy of AI in the diagnosis of early gastric cancer from endoscopic images. Methods: We conducted a systematic review from database inception to June 2020 of all studies assessing the performance of AI in the endoscopic diagnosis of early gastric cancer. Studies not concerning early gastric cancer were excluded. The outcome of interest was the diagnostic accuracy (comprising sensitivity, specificity, and accuracy) of AI systems. Study quality was assessed on the basis of the revised Quality Assessment of Diagnostic Accuracy Studies. Meta-analysis was primarily based on a bivariate mixed-effects model. A summary receiver operating curve and a hierarchical summary receiver operating curve were constructed, and the area under the curve was computed. Results: We analyzed 12 retrospective case control studies (n=11,685) in which AI identified early gastric cancer from endoscopic images. The pooled sensitivity and specificity of AI for early gastric cancer diagnosis were 0.86 (95\% CI 0.75-0.92) and 0.90 (95\% CI 0.84-0.93), respectively. The area under the curve was 0.94. Sensitivity analysis of studies using support vector machines and narrow-band imaging demonstrated more consistent results. Conclusions: For early gastric cancer, to our knowledge, this was the first synthesis study on the use of endoscopic images in AI in diagnosis. AI may support the diagnosis of early gastric cancer. However, the collocation of imaging techniques and optimal algorithms remain unclear. Competing models of AI for the diagnosis of early gastric cancer are worthy of future investigation. Trial Registration: PROSPERO CRD42020193223; https://www.crd.york.ac.uk/prospero/display\_record.php?RecordID=193223 ", doi="10.2196/27694", url="https://www.jmir.org/2022/5/e27694", url="http://www.ncbi.nlm.nih.gov/pubmed/35576561" } @Article{info:doi/10.2196/37009, author="Bilodeau, Karine and Gouin, Marie-Michelle and Lecours, Alexandra and Lederer, Val{\'e}rie and Durand, Marie-Jos{\'e} and Kilpatrick, Kelley and Lepage, David and Ladouceur-Deslauriers, Lauriane and Dorta, Tomas", title="Acceptability and Feasibility of a Return-to-Work Intervention for Posttreatment Breast Cancer Survivors: Protocol for a Co-design and Development Study", journal="JMIR Res Protoc", year="2022", month="Apr", day="22", volume="11", number="4", pages="e37009", keywords="co-design", keywords="breast cancer", keywords="intervention", keywords="return-to-work", keywords="primary care", keywords="qualitative", abstract="Background: The mortality rate from breast cancer has been declining for many years, and the population size of working-age survivors is steadily increasing. However, the recurrent side effects of cancer and its treatment can result in multiple disabilities and disruptions to day-to-day life, including work disruptions. Despite the existing knowledge of best practices regarding return to work (RTW) for breast cancer survivors, only a few interdisciplinary interventions have been developed to address the individualized needs and multiple challenges of breast cancer survivors, health care professionals, and employer and insurer representatives. Thus, it seems appropriate to develop RTW interventions collaboratively by using a co-design approach with these specific stakeholders. Objective: This paper presents a protocol for developing and testing an innovative, interdisciplinary pilot intervention based on a co-design approach to better support RTW and job retention after breast cancer treatment. Methods: First, a participatory research approach will be used to develop the intervention in a co-design workshop with 12 to 20 participants, including people affected by cancer, employer and insurer representatives, and health care professionals. Next, a pilot intervention will be tested in a primary care setting with 6 to 8 women affected by breast cancer. The acceptability and feasibility of the pilot intervention will be pretested through semistructured interviews with participants, health care professionals, and involved patient partners. The transcribed data will undergo an iterative content analysis. Results: The first phase of the project---the co-design workshop---was completed in June 2021. The pilot test of the intervention will begin in spring 2022. The results from the test will be available in late 2022. Conclusions: The project will offer novel data regarding the use of the co-design approach for the development of innovative, co-designed interventions. In addition, it will be possible to document the acceptability and feasibility of the pilot intervention with a primary care team. Depending on the results obtained, the intervention could be implemented on a larger scale. International Registered Report Identifier (IRRID): DERR1-10.2196/37009 ", doi="10.2196/37009", url="https://www.researchprotocols.org/2022/4/e37009", url="http://www.ncbi.nlm.nih.gov/pubmed/35451972" } @Article{info:doi/10.2196/35838, author="Lie, C. Hanne and Anderssen, Sigmund and Rueegg, Silvia Corina and Raastad, Truls and Grydeland, May and Thorsen, Lene and Stensrud, Trine and Edvardsen, Elisabeth and Larsen, Hamilton Marie and Torsvik, Kristin Ingrid and Bovim, Peder Lars and G{\"o}tte, Miriam and L{\"a}hteenm{\"a}ki, Maria P{\"a}ivi and Kriemler, Susi and Larsen, B{\ae}kgaard Hanne and Fridh, Kaj Martin and {\O}rstavik, Kristin and Brun, Henrik and Matthews, Iren and Hornset, Else and Ruud, Ellen", title="The Physical Activity and Fitness in Childhood Cancer Survivors (PACCS) Study: Protocol for an International Mixed Methods Study", journal="JMIR Res Protoc", year="2022", month="Mar", day="8", volume="11", number="3", pages="e35838", keywords="childhood cancer survivor", keywords="physical activity", keywords="physical fitness", keywords="barriers", keywords="intervention", keywords="quality of life", keywords="fatigue", abstract="Background: Survivors of childhood cancer represent a growing population with a long life expectancy but high risks of treatment-induced morbidity and premature mortality. Regular physical activity (PA) may improve their long-term health; however, high-quality empirical knowledge is sparse. Objective: The Physical Activity and Fitness in Childhood Cancer Survivors (PACCS) study comprises 4 work packages (WPs) aiming for the objective determination of PA and self-reported health behavior, fatigue, and quality of life (WP 1); physical fitness determination (WP 2); the evaluation of barriers to and facilitators of PA (WP 1 and 3); and the feasibility testing of an intervention to increase PA and physical fitness (WP 4). Methods: The PACCS study will use a mixed methods design, combining patient-reported outcome measures and objective clinical and physiological assessments with qualitative data gathering methods. A total of 500 survivors of childhood cancer aged 9 to 18 years with ?1 year after treatment completion will be recruited in follow-up care clinics in Norway, Denmark, Finland, Germany, and Switzerland. All participants will participate in WP 1, of which approximately 150, 40, and 30 will be recruited to WP 2, WP3, and WP 4, respectively. The reference material for WP 1 is available from existing studies, whereas WP 2 will recruit healthy controls. PA levels will be measured using ActiGraph accelerometers and self-reports. Validated questionnaires will be used to assess health behaviors, fatigue, and quality of life. Physical fitness will be measured by a cardiopulmonary exercise test, isometric muscle strength tests, and muscle power and endurance tests. Limiting factors will be identified via neurological, pulmonary, and cardiac evaluations and the assessment of body composition and muscle size. Semistructured, qualitative interviews, analyzed using systematic text condensation, will identify the perceived barriers to and facilitators of PA for survivors of childhood cancer. In WP 4, we will evaluate the feasibility of a 6-month personalized PA intervention with the involvement of local structures. Results: Ethical approvals have been secured at all participating sites (Norwegian Regional Committee for Medical Research Ethics [2016/953 and 2018/739]; the Oslo University Hospital Data Protection Officer; equivalent institutions in Finland, Denmark [file H-19032270], Germany, and Switzerland [Ethics Committee of Northwestern and Central Switzerland, project ID: 2019-00410]). Data collection for WP 1 to 3 is complete. This will be completed by July 2022 for WP 4. Several publications are already in preparation, and 2 have been published. Conclusions: The PACCS study will generate high-quality knowledge that will contribute to the development of an evidence-based PA intervention for young survivors of childhood cancer to improve their long-term care and health. We will identify physiological, psychological, and social barriers to PA that can be targeted in interventions with immediate benefits for young survivors of childhood cancer in need of rehabilitation. International Registered Report Identifier (IRRID): DERR1-10.2196/35838 ", doi="10.2196/35838", url="https://www.researchprotocols.org/2022/3/e35838", url="http://www.ncbi.nlm.nih.gov/pubmed/35258456" } @Article{info:doi/10.2196/31128, author="Shahzadi, Kiran Syeda and Karuvantevida, Noushad and Banerjee, Yajnavalka", title="A Venomics Approach to the Identification and Characterization of Bioactive Peptides From Animal Venoms for Colorectal Cancer Therapy: Protocol for a Proof-of-Concept Study", journal="JMIR Res Protoc", year="2021", month="Dec", day="21", volume="10", number="12", pages="e31128", keywords="animal venoms", keywords="colorectal cancer", keywords="bioactive peptides", keywords="high-throughput screening", keywords="venom", keywords="cancer", keywords="colorectal", keywords="peptide", keywords="screening", keywords="treatment", keywords="conceptual", keywords="characterize", keywords="development", keywords="therapy", abstract="Background: Cancer is the third leading cause of death in the United Arab Emirates (UAE), after cardiovascular diseases and accidents. In the UAE, colorectal cancer (CRC) is the first and fourth most common cancer in males and females, respectively. Several treatment modalities have been employed for cancer treatment, such as surgery, radiotherapy, chemotherapy, hormone replacement therapy, and immunotherapy. These treatment modalities often elicit adverse effects on normal cells, causing toxic side effects. To circumvent these toxicities, there has been an increased impetus towards the identification of alternate treatment strategies. Animal venoms are rich sources of pharmacologically active polypeptides and proteins. Objective: In this proof-of-concept study, we will apply a high-throughput venomics strategy to identify and characterize anticancer bioactive peptides (BAPs) from 20 different animal venoms, specifically targeting CRC. We chose to focus on CRC because it is one of the foremost health issues in the UAE. Methods: In the initial study, we will screen 2500 different peptides derived from 20 different animal venoms for anticancer activity specifically directed against 3 CRC cell lines and two control cell lines employing the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) colorimetric assay for cytotoxicity. Of the 20 venoms, 3 that exhibit specific and potent anticancer activity directed against the 3 CRC cell lines will be selected; and from these 3 venoms, the specific peptides with anti-CRC activity will be isolated and characterized. Results: This study is at the protocol development stage only, and as such, no results are available. However, we have initiated the groundwork required to disseminate the proposed study, which includes culturing of colorectal cancer cell lines and preparation of venom screens. Conclusions: In summary, the proposed study will generate therapeutic leads to manage and treat one of the leading health issues in the UAE, namely, CRC. International Registered Report Identifier (IRRID): PRR1-10.2196/31128 ", doi="10.2196/31128", url="https://www.researchprotocols.org/2021/12/e31128", url="http://www.ncbi.nlm.nih.gov/pubmed/34932002" } @Article{info:doi/10.2196/20028, author="Ye, Ye and Barapatre, Seemran and Davis, K. Michael and Elliston, O. Keith and Davatzikos, Christos and Fedorov, Andrey and Fillion-Robin, Jean-Christophe and Foster, Ian and Gilbertson, R. John and Lasso, Andras and Miller, V. James and Morgan, Martin and Pieper, Steve and Raumann, E. Brigitte and Sarachan, D. Brion and Savova, Guergana and Silverstein, C. Jonathan and Taylor, P. Donald and Zelnis, B. Joyce and Zhang, Guo-Qiang and Cuticchia, Jamie and Becich, J. Michael", title="Open-source Software Sustainability Models: Initial White Paper From the Informatics Technology for Cancer Research Sustainability and Industry Partnership Working Group", journal="J Med Internet Res", year="2021", month="Dec", day="2", volume="23", number="12", pages="e20028", keywords="open-source software", keywords="sustainability", keywords="licensing model", keywords="financial model", keywords="product management", keywords="cancer informatics", abstract="Background: The National Cancer Institute Informatics Technology for Cancer Research (ITCR) program provides a series of funding mechanisms to create an ecosystem of open-source software (OSS) that serves the needs of cancer research. As the ITCR ecosystem substantially grows, it faces the challenge of the long-term sustainability of the software being developed by ITCR grantees. To address this challenge, the ITCR sustainability and industry partnership working group (SIP-WG) was convened in 2019. Objective: The charter of the SIP-WG is to investigate options to enhance the long-term sustainability of the OSS being developed by ITCR, in part by developing a collection of business model archetypes that can serve as sustainability plans for ITCR OSS development initiatives. The working group assembled models from the ITCR program, from other studies, and from the engagement of its extensive network of relationships with other organizations (eg, Chan Zuckerberg Initiative, Open Source Initiative, and Software Sustainability Institute) in support of this objective. Methods: This paper reviews the existing sustainability models and describes 10 OSS use cases disseminated by the SIP-WG and others, including 3D Slicer, Bioconductor, Cytoscape, Globus, i2b2 (Informatics for Integrating Biology and the Bedside) and tranSMART, Insight Toolkit, Linux, Observational Health Data Sciences and Informatics tools, R, and REDCap (Research Electronic Data Capture), in 10 sustainability aspects: governance, documentation, code quality, support, ecosystem collaboration, security, legal, finance, marketing, and dependency hygiene. Results: Information available to the public reveals that all 10 OSS have effective governance, comprehensive documentation, high code quality, reliable dependency hygiene, strong user and developer support, and active marketing. These OSS include a variety of licensing models (eg, general public license version 2, general public license version 3, Berkeley Software Distribution, and Apache 3) and financial models (eg, federal research funding, industry and membership support, and commercial support). However, detailed information on ecosystem collaboration and security is not publicly provided by most OSS. Conclusions: We recommend 6 essential attributes for research software: alignment with unmet scientific needs, a dedicated development team, a vibrant user community, a feasible licensing model, a sustainable financial model, and effective product management. We also stress important actions to be considered in future ITCR activities that involve the discussion of the sustainability and licensing models for ITCR OSS, the establishment of a central library, the allocation of consulting resources to code quality control, ecosystem collaboration, security, and dependency hygiene. ", doi="10.2196/20028", url="https://www.jmir.org/2021/12/e20028", url="http://www.ncbi.nlm.nih.gov/pubmed/34860667" } @Article{info:doi/10.2196/28393, author="Lei, Fang and Lee, Eunice", title="Cross-Cultural Modification Strategies for Instruments Measuring Health Beliefs About Cancer Screening: Systematic Review", journal="JMIR Cancer", year="2021", month="Nov", day="18", volume="7", number="4", pages="e28393", keywords="cancer screening", keywords="health beliefs", keywords="instrument modification", keywords="strategy", keywords="systematic review", abstract="Background: Modification is an important process by which to adapt an instrument to be used for another culture. However, it is not fully understood how best to modify an instrument to be used appropriately in another culture. Objective: This study aims to synthesize the modification strategies used in the cross-cultural adaptation process for instruments measuring health beliefs about cancer screening. Methods: A systematic review design was used for conducting this study. Keywords including constructs about instrument modification, health belief, and cancer screening were searched in the PubMed, Google Scholar, CINAHL, and PsycINFO databases. Bowling's checklist was used to evaluate methodological rigor of the included articles. Results were reported using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) approach with a narrative method. Results: A total of 1312 articles were initially identified in the databases. After removing duplications and assessing titles, abstracts, and texts of the articles, 18 studies met the inclusion criteria for the study. Based on Flaherty's cultural equivalence model, strategies used in the modification process included rephrasing items and response options to achieve semantic equivalence; changing subjects of items, changing wording of items, adding items, and deleting items to achieve content equivalence; adding subscales and items and deleting subscales and items to achieve criterion equivalence. Solutions used to resolve disagreements in the modification process included consultation with experts or literature search, following the majority, and consultation with the author who developed the scales. Conclusions: This study provides guidance for researchers who want to modify an instrument to be used in another culture. It can potentially give cross-cultural researchers insight into modification strategies and a better understanding of the modification process in cross-cultural instrument adaptation. More research could be done to help researchers better modify cross-cultural instruments to achieve cultural equivalence. ", doi="10.2196/28393", url="https://cancer.jmir.org/2021/4/e28393", url="http://www.ncbi.nlm.nih.gov/pubmed/34792474" } @Article{info:doi/10.2196/29123, author="Naeim, Arash and Dry, Sarah and Elashoff, David and Xie, Zhuoer and Petruse, Antonia and Magyar, Clara and Johansen, Liliana and Werre, Gabriela and Lajonchere, Clara and Wenger, Neil", title="Electronic Video Consent to Power Precision Health Research: A Pilot Cohort Study", journal="JMIR Form Res", year="2021", month="Sep", day="8", volume="5", number="9", pages="e29123", keywords="biobanking", keywords="precision medicine", keywords="electronic consent", keywords="privacy", keywords="pilot study", keywords="video", keywords="consent", keywords="precision", keywords="innovation", keywords="efficient", keywords="cancer", keywords="education", keywords="barrier", keywords="engagement", keywords="participation", abstract="Background: Developing innovative, efficient, and institutionally scalable biospecimen consent for remnant tissue that meets the National Institutes of Health consent guidelines for genomic and molecular analysis is essential for precision medicine efforts in cancer. Objective: This study aims to pilot-test an electronic video consent that individuals could complete largely on their own. Methods: The University of California, Los Angeles developed a video consenting approach designed to be comprehensive yet fast (around 5 minutes) for providing universal consent for remnant biospecimen collection for research. The approach was piloted in 175 patients who were coming in for routine services in laboratory medicine, radiology, oncology, and hospital admissions. The pilot yielded 164 completed postconsent surveys. The pilot assessed the usefulness, ease, and trustworthiness of the video consent. In addition, we explored drivers for opting in or opting out. Results: The pilot demonstrated that the electronic video consent was well received by patients, with high scores for usefulness, ease, and trustworthiness even among patients that opted out of participation. The revised more animated video pilot test in phase 2 was better received in terms of ease of use (P=.005) and the ability to understand the information (P<.001). There were significant differences between those who opted in and opted out in their beliefs concerning the usefulness of tissue, trusting researchers, the importance of contributing to science, and privacy risk (P<.001). The results showed that ``I trust researchers to use leftover biological specimens to promote the public's health'' and ``Sharing a biological sample for research is safe because of the privacy protections in place'' discriminated opt-in statuses were the strongest predictors (both areas under the curve were 0.88). Privacy concerns seemed universal in individuals who opted out. Conclusions: Efforts to better educate the community may be needed to help overcome some of the barriers in engaging individuals to participate in precision health initiatives. ", doi="10.2196/29123", url="https://formative.jmir.org/2021/9/e29123", url="http://www.ncbi.nlm.nih.gov/pubmed/34313247" } @Article{info:doi/10.2196/25789, author="Wang, Quan and Yang, Ke-Lu and Zhang, Zhen and Wang, Zhu and Li, Chen and Li, Lun and Tian, Jin-Hui and Ye, Ying-Jiang and Wang, Shan and Jiang, Ke-Wei", title="Characterization of Global Research Trends and Prospects on Single-Cell Sequencing Technology: Bibliometric Analysis", journal="J Med Internet Res", year="2021", month="Aug", day="10", volume="23", number="8", pages="e25789", keywords="single-cell sequencing", keywords="bibliometric analysis", keywords="cancer", keywords="cancer genomics", keywords="bioinformatics", keywords="cancer subtyping", keywords="tumor dissociation", keywords="tumor microenvironment", keywords="precision medicine", keywords="immunology", keywords="development trends", keywords="hotspots", keywords="research topics", keywords="Web of Science", keywords="CiteSpace", keywords="VOSviewer", keywords="network", abstract="Background: As single-cell sequencing technology has been gradually introduced, it is essential to characterize global collaboration networks and map development trends over the past 20 years. Objective: The aim of this paper was to illustrate collaboration in the field of single-cell sequencing methods and explore key topics and future directions. Methods: Bibliometric analyses were conducted with CiteSpace and VOSviewer software on publications prior to November 2019 from the Web of Science Core Collection about single-cell sequencing methods. Results: Ultimately, we identified 2489 records, which were published in 495 journals by 14,202 authors from 1970 institutes in 61 countries. There was a noticeable increase in publications in 2014. The United States and high-income countries in Europe contributed to most of the records included. Harvard University, Stanford University, Karolinska Institutes, Peking University, and the University of Washington were the biggest nodes in every cluster of the collaboration network, and SA Teichmann, JC Marioni, A Regev, and FC Tang were the top-producing authors. Keywords co-occurrence analysis suggested applications in immunology as a developing research trend. Conclusions: We concluded that the global collaboration network was unformed and that high-income countries contributed more to the rapidly growth of publications of single-cell sequencing technology. Furthermore, the application in immunology might be the next research hotspot and developmental direction. ", doi="10.2196/25789", url="https://www.jmir.org/2021/8/e25789", url="http://www.ncbi.nlm.nih.gov/pubmed/34014832" } @Article{info:doi/10.2196/30730, author="Pratt-Chapman, Mandi and Moses, Jenna and Arem, Hannah", title="Strategies for the Identification and Prevention of Survey Fraud: Data Analysis of a Web-Based Survey", journal="JMIR Cancer", year="2021", month="Jul", day="16", volume="7", number="3", pages="e30730", keywords="cancer survivors", keywords="pandemic", keywords="COVID-19", keywords="fraudulent responses", keywords="survey", keywords="research methods", keywords="cancer patients", keywords="fraud", keywords="CAPTCHA", keywords="data integrity", keywords="online surveys", abstract="Background: To assess the impact of COVID-19 on cancer survivors, we fielded a survey promoted via email and social media in winter 2020. Examination of the data showed suspicious patterns that warranted serious review. Objective: The aim of this paper is to review the methods used to identify and prevent fraudulent survey responses. Methods: As precautions, we included a Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA), a hidden question, and instructions for respondents to type a specific word. To identify likely fraudulent data, we defined a priori indicators that warranted elimination or suspicion. If a survey contained two or more suspicious indicators, the survey was eliminated. We examined differences between the retained and eliminated data sets. Results: Of the total responses (N=1977), nearly three-fourths (n=1408) were dropped and one-fourth (n=569) were retained after data quality checking. Comparisons of the two data sets showed statistically significant differences across almost all demographic characteristics. Conclusions: Numerous precautions beyond the inclusion of a CAPTCHA are needed when fielding web-based surveys, particularly if a financial incentive is offered. ", doi="10.2196/30730", url="https://cancer.jmir.org/2021/3/e30730", url="http://www.ncbi.nlm.nih.gov/pubmed/34269685" } @Article{info:doi/10.2196/25056, author="Lamprell, Klay and Fajardo Pulido, Diana and Tran, Yvonne and Nic Giolla Easpaig, Br{\'o}na and Liauw, Winston and Arnolda, Gaston and Braithwaite, Jeffrey", title="Personal Accounts of Young-Onset Colorectal Cancer Organized as Patient-Reported Data: Protocol for a Mixed Methods Study", journal="JMIR Res Protoc", year="2021", month="Feb", day="26", volume="10", number="2", pages="e25056", keywords="colorectal cancer", keywords="PROMs", keywords="young-onset cancer", keywords="cancer", keywords="patient reported outcome", abstract="Background: Young-onset colorectal cancer is a contemporary issue in need of substantial research input. The incidence of colorectal cancer in adults younger than 50 years is rising in contrast to the decreasing incidence of this cancer in older adults. People with young-onset colorectal cancer may be at that stage of life in which they are establishing their careers, building relationships with long-term partners, raising children, and assembling a financial base for the future. A qualitative study designed to facilitate triangulation with extant quantitative patient-reported data would contribute the first comprehensive resource for understanding how this distinct patient population experiences health services and the outcomes of care throughout the patient pathway. Objective: The aim of this study was to undertake a mixed-methods study of qualitative patient-reported data on young-onset colorectal cancer experiences and outcomes. Methods: This is a study of web-based unsolicited patient stories recounting experiences of health services and clinical outcomes related to young-onset colorectal cancer. Personal Recollections Organized as Data (PROD) is a novel methodology for understanding patients' health experiences in order to improve care. PROD pivots qualitative data collection and analysis around the validated domains and dimensions measured in patient-reported outcome and patient-reported experience questionnaires. PROD involves 4 processes: (1) classifying attributes of the contributing patients, their disease states, their routes to diagnosis, and the clinical features of their treatment and posttreatment; (2) coding texts into the patient-reported experience and patient-reported outcome domains and dimensions, defined a priori, according to phases of the patient pathway; (3) thematic analysis of content within and across each domain; and (4) quantitative text analysis of the narrative content. Results: Relevant patient stories have been identified, and permission has been obtained for use of the texts in primary research. The approval for this study was granted by the Macquarie University Human Research Ethics Committee in June 2020. The analytical framework was established in September 2020, and data collection commenced in October 2020. We will complete the analysis in March 2021 and we aim to publish the results in mid-2021. Conclusions: The findings of this study will identify areas for improvement in the PROD methodology and inform the development of a large-scale study of young-onset colorectal cancer patient narratives. We believe that this will be the first qualitative study to identify and describe the patient pathway from symptom self-identification to help-seeking through to diagnosis, treatment, and to survivorship or palliation for people with young-onset colorectal cancer. International Registered Report Identifier (IRRID): DERR1-10.2196/25056 ", doi="10.2196/25056", url="https://www.researchprotocols.org/2021/2/e25056", url="http://www.ncbi.nlm.nih.gov/pubmed/33635274" } @Article{info:doi/10.2196/11195, author="Dibble, R. Emily and Iott, E. Bradley and Flynn, J. Allen and King, P. Darren and MacEachern, P. Mark and Friedman, P. Charles and Caverly, J. Tanner", title="A Rapid Process for Identifying and Prioritizing Technology-Based Tools for Health System Implementation", journal="JMIR Cancer", year="2018", month="Nov", day="27", volume="4", number="2", pages="e11195", keywords="patient reported outcome measures", keywords="evidence-based practice", keywords="decision support systems, clinical", keywords="medical informatics applications", keywords="practice guidelines as topic", keywords="evidence review", keywords="expert panel", keywords="health information technology", keywords="oncology care model", keywords="clinical decision support", abstract="Background: Health system decisions to put new technologies into clinical practice require a rapid and trustworthy decision-making process informed by best evidence. Objective: This study aimed to present a rapid evidence review process that can be used to inform health system leaders and clinicians seeking to implement new technology tools to improve patient-clinician decision making and patient-oriented outcomes. Methods: The rapid evidence review process we pioneered involved 5 sequential subprocesses: (1) environmental scan, (2) expert panel recruitment, (3) host evidence review panel, (4) analysis, and (5) local validation panel. We conducted an environmental scan of health information technology (IT) literature to identify relevant digital tools in oncology care. We synthesized the recent literature using current evidence review methods, creating visual summaries for use by a national panel of experts. Panelists were taken through a 6-hour modified Delphi process to prioritize tools for implementation. Findings from the rapid evidence review panel were taken to a local validation panel for further rapid review during a 3-hour session. Results: Our rapid evidence review process shows promise for informing decision making by reducing the amount of time and resources needed to identify and prioritize adoption of IT tools. Despite evidence of improved patient outcomes, panelists had substantial concerns about implementing patient-reported outcome tracking tools, voicing concerns about liability, lack of familiarity with new technology, and additional time and workflow changes such tools would require. Instead, clinicians favored technologies that did not require clinician involvement. Conclusions: Health system leaders can use the rapid evidence review process presented here to usefully inform local technology adoption, implementation, and use in practice. ", doi="10.2196/11195", url="http://cancer.jmir.org/2018/2/e11195/", url="http://www.ncbi.nlm.nih.gov/pubmed/30482740" } @Article{info:doi/10.2196/cancer.9918, author="Asfaw, Ayele Alemseged and Yan, H. Connie and Sweiss, Karen and Wirth, Scott and Ramirez, H. Victor and Patel, R. Pritesh and Sharp, K. Lisa", title="Barriers and Facilitators of Using Sensored Medication Adherence Devices in a Diverse Sample of Patients With Multiple Myeloma: Qualitative Study", journal="JMIR Cancer", year="2018", month="Nov", day="12", volume="4", number="2", pages="e12", keywords="antineoplastic therapy", keywords="challenges", keywords="race/ethnicity", keywords="medication adherence", keywords="multiple myeloma", abstract="Background: Many recently approved medications to manage multiple myeloma (MM) are oral, require supportive medications to prevent adverse effects, and are taken under complex schedules. Medication adherence is a concern; however, little attention has been directed toward understanding adherence in MM or associated barriers and facilitators. Advanced sensored medication devices (SMDs) offer opportunities to intervene; however, acceptability among patients with MM, particularly African American patients, is untested. Objective: This study aimed to explore patients' (1) perceptions of their health before MM including experiences with chronic medications, (2) perceptions of adherence barriers and facilitators, and (3) attitudes toward using SMDs. Methods: An in-person, semistructured, qualitative interview was conducted with a convenience sample of patients being treated for MM. Patients were recruited from within an urban, minority-serving, academic medical center that had an established cancer center. A standardized interview guide included questions targeting medication use, attitudes, adherence, barriers, and facilitators. Demographics included the use of cell phone technology. Patients were shown 2 different pill bottles with sensor technology---Medication Event Monitoring System and the SMRxT bottle. After receiving information on the transmission ability of the bottles, patients were asked to discuss their reactions and concerns with the idea of using such a device. Medical records were reviewed to capture information on medication and diagnoses. The interviews were audio-recorded and transcribed. Interviews were independently coded by 2 members of the team with a third member providing guidance. Results: A total of 20 patients with a mean age of 56 years (median=59 years; range=29-71 years) participated in this study and 80\% (16/20) were African American. In addition, 18 (90\%, 18/20) owned a smartphone and 85\% (17/20) were comfortable using the internet, text messaging, and cell phone apps. The average number of medications reported per patient was 13 medications (median=10; range=3-24). Moreover, 14 (70\%, 14/20) patients reported missed doses for a range of reasons such as fatigue, feeling ill, a busy schedule, forgetting, or side effects. Interest in using an SMD ranged from great interest to complete lack of interest. Examples of concerns related to the SMDs included privacy issues, potential added cost, and the size of the bottle (ie, too large). Despite the concerns, 60\% (12/20) of the patients expressed interest in trying a bottle in the future. Conclusions: Results identified numerous patient-reported barriers and facilitators to missed doses of oral anticancer therapy. Many appear to be potentially mutable if uncovered and addressed. SMDs may allow for capture of these data. Although patients expressed concerns with SMDs, most remained willing to use one. A feasibility trial with SMDs is planned. ", doi="10.2196/cancer.9918", url="http://cancer.jmir.org/2018/2/e12/", url="http://www.ncbi.nlm.nih.gov/pubmed/30425032" } @Article{info:doi/10.2196/medinform.9171, author="Zarinabad, Niloufar and Meeus, M. Emma and Manias, Karen and Foster, Katharine and Peet, Andrew", title="Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis", journal="JMIR Med Inform", year="2018", month="May", day="02", volume="6", number="2", pages="e30", keywords="clinical decision support", keywords="real-time systems", keywords="magnetic resonance imaging", abstract="Background: Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective: The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods: The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results: Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions: MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ", doi="10.2196/medinform.9171", url="http://medinform.jmir.org/2018/2/e30/", url="http://www.ncbi.nlm.nih.gov/pubmed/29720361" } @Article{info:doi/10.2196/medinform.8662, author="Zheng, Shuai and Jabbour, K. Salma and O'Reilly, E. Shannon and Lu, J. James and Dong, Lihua and Ding, Lijuan and Xiao, Ying and Yue, Ning and Wang, Fusheng and Zou, Wei", title="Automated Information Extraction on Treatment and Prognosis for Non--Small Cell Lung Cancer Radiotherapy Patients: Clinical Study", journal="JMIR Med Inform", year="2018", month="Feb", day="01", volume="6", number="1", pages="e8", keywords="information extraction", keywords="oncology", keywords="chemoradiation treatment", keywords="prognosis", keywords="non--small cell lung", keywords="information storage and retrieval", keywords="natural language processing", abstract="Background: In outcome studies of oncology patients undergoing radiation, researchers extract valuable information from medical records generated before, during, and after radiotherapy visits, such as survival data, toxicities, and complications. Clinical studies rely heavily on these data to correlate the treatment regimen with the prognosis to develop evidence-based radiation therapy paradigms. These data are available mainly in forms of narrative texts or table formats with heterogeneous vocabularies. Manual extraction of the related information from these data can be time consuming and labor intensive, which is not ideal for large studies. Objective: The objective of this study was to adapt the interactive information extraction platform Information and Data Extraction using Adaptive Learning (IDEAL-X) to extract treatment and prognosis data for patients with locally advanced or inoperable non--small cell lung cancer (NSCLC). Methods: We transformed patient treatment and prognosis documents into normalized structured forms using the IDEAL-X system for easy data navigation. The adaptive learning and user-customized controlled toxicity vocabularies were applied to extract categorized treatment and prognosis data, so as to generate structured output. Results: In total, we extracted data from 261 treatment and prognosis documents relating to 50 patients, with overall precision and recall more than 93\% and 83\%, respectively. For toxicity information extractions, which are important to study patient posttreatment side effects and quality of life, the precision and recall achieved 95.7\% and 94.5\% respectively. Conclusions: The IDEAL-X system is capable of extracting study data regarding NSCLC chemoradiation patients with significant accuracy and effectiveness, and therefore can be used in large-scale radiotherapy clinical data studies. ", doi="10.2196/medinform.8662", url="http://medinform.jmir.org/2018/1/e8/", url="http://www.ncbi.nlm.nih.gov/pubmed/29391345" } @Article{info:doi/10.2196/cancer.6996, author="Hartkopf, D. Andreas and Graf, Joachim and Simoes, Elisabeth and Keilmann, Lucia and Sickenberger, Nina and Gass, Paul and Wallwiener, Diethelm and Matthies, Lina and Taran, Florin-Andrei and Lux, P. Michael and Wallwiener, Stephanie and Belleville, Eric and Sohn, Christof and Fasching, A. Peter and Schneeweiss, Andreas and Brucker, Y. Sara and Wallwiener, Markus", title="Electronic-Based Patient-Reported Outcomes: Willingness, Needs, and Barriers in Adjuvant and Metastatic Breast Cancer Patients", journal="JMIR Cancer", year="2017", month="Aug", day="07", volume="3", number="2", pages="e11", keywords="breast cancer", keywords="patient-reported outcome measures", keywords="electronic patient- reported outcome", keywords="technical skills", keywords="willingness to use", keywords="needs and barriers", abstract="Background: Patient-reported outcomes (PROs) play an increasingly important role as an adjunct to clinical outcome parameters in measuring health-related quality of life (HRQoL). In fact, PROs are already the accepted gold standard for collecting data about patients' subjective perception of their own state of health. Currently, paper-based surveys of PRO still predominate; however, knowledge regarding the feasibility of and barriers to electronic-based PRO (ePRO) acceptance remains limited. Objective: The objective of this trial was to analyze the willingness, specific needs, and barriers of adjuvant breast cancer (aBC) and metastatic breast cancer (mBC) patients in nonexposed (no exposure to electronic assessment) and exposed (after exposure to electronic assessment decision, whether a tablet-based questionnaire is favored) settings before implementing digital ePRO assessment in relation to health status. We also investigated whether providing support can increase the patients' willingness to participate in such programs. Methods: The nonexposed patients only answered a paper-based questionnaire, whereas the exposed patients filled out both paper- and tablet-based questionnaires. The assessment comprised socioeconomic variables, HRQoL, preexisting technical skills, general attitude toward electronic-based surveys, and potential barriers in relation to health status. Furthermore, nonexposed patients were asked about the existing need for technological support structures. In the course of data evaluation, we performed a frequency analysis as well as chi-square tests and Wilcoxon signed-rank tests. Subsequently, relative risks analysis, univariate categorical regression (CATREG), and mediation analyses (Hayes' bias-corrected bootstrap) were performed. Results: A total of 202 female breast cancer patients completed the PRO assessment (nonexposed group: n=96 patients; exposed group: n=106 patients). Self-reported technical skills were higher in exposed patients (2.79 vs 2.33, P ?.001). Significant differences were found in relation to willingness to use ePRO (92.3\% in the exposed group vs 59\% in the nonexposed group; P=.001). Multiple barriers were identified, and most of them showed statistically significant differences in favor of the exposed patients (ie, data security [13\% in the exposed patients vs 30\% in the nonexposed patients; P=.003] and no prior technology usage [5\% in the exposed group vs 15\% in the nonexposed group; P=.02]), whereas the differences in disease burden (somatic dimension: 4\% in the exposed group vs 9\% in the nonexposed group; P=.13) showed no significance. In nonexposed patients, requests for support services were identified, which could increase their ePRO willingness. Conclusions: Significant barriers in relation to HRQoL, cancer-related restrictions, and especially the setting of the survey were identified in this trial. Thus, it is necessary to address and eliminate these barriers to ensure data accuracy and reliability for future ePRO assessments. Exposure seems to be a potential option to increase willingness to use ePRO and to reduce barriers. ", doi="10.2196/cancer.6996", url="http://cancer.jmir.org/2017/2/e11/", url="http://www.ncbi.nlm.nih.gov/pubmed/28784595" } @Article{info:doi/10.2196/medinform.7779, author="Tapi Nzali, Donald Mike and Bringay, Sandra and Lavergne, Christian and Mollevi, Caroline and Opitz, Thomas", title="What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer", journal="JMIR Med Inform", year="2017", month="Jul", day="31", volume="5", number="3", pages="e23", keywords="breast cancer", keywords="text mining", keywords="social media", keywords="unsupervised learning", abstract="Background: Social media dedicated to health are increasingly used by patients and health professionals. They are rich textual resources with content generated through free exchange between patients. We are proposing a method to tackle the problem of retrieving clinically relevant information from such social media in order to analyze the quality of life of patients with breast cancer. Objective: Our aim was to detect the different topics discussed by patients on social media and to relate them to functional and symptomatic dimensions assessed in the internationally standardized self-administered questionnaires used in cancer clinical trials (European Organization for Research and Treatment of Cancer [EORTC] Quality of Life Questionnaire Core 30 [QLQ-C30] and breast cancer module [QLQ-BR23]). Methods: First, we applied a classic text mining technique, latent Dirichlet allocation (LDA), to detect the different topics discussed on social media dealing with breast cancer. We applied the LDA model to 2 datasets composed of messages extracted from public Facebook groups and from a public health forum (cancerdusein.org, a French breast cancer forum) with relevant preprocessing. Second, we applied a customized Jaccard coefficient to automatically compute similarity distance between the topics detected with LDA and the questions in the self-administered questionnaires used to study quality of life. Results: Among the 23 topics present in the self-administered questionnaires, 22 matched with the topics discussed by patients on social media. Interestingly, these topics corresponded to 95\% (22/23) of the forum and 86\% (20/23) of the Facebook group topics. These figures underline that topics related to quality of life are an important concern for patients. However, 5 social media topics had no corresponding topic in the questionnaires, which do not cover all of the patients' concerns. Of these 5 topics, 2 could potentially be used in the questionnaires, and these 2 topics corresponded to a total of 3.10\% (523/16,868) of topics in the cancerdusein.org corpus and 4.30\% (3014/70,092) of the Facebook corpus. Conclusions: We found a good correspondence between detected topics on social media and topics covered by the self-administered questionnaires, which substantiates the sound construction of such questionnaires. We detected new emerging topics from social media that can be used to complete current self-administered questionnaires. Moreover, we confirmed that social media mining is an important source of information for complementary analysis of quality of life. ", doi="10.2196/medinform.7779", url="http://medinform.jmir.org/2017/3/e23/", url="http://www.ncbi.nlm.nih.gov/pubmed/28760725" } @Article{info:doi/10.2196/jmir.6342, author="Hochheimer, J. Camille and Sabo, T. Roy and Krist, H. Alex and Day, Teresa and Cyrus, John and Woolf, H. Steven", title="Methods for Evaluating Respondent Attrition in Web-Based Surveys", journal="J Med Internet Res", year="2016", month="Nov", day="22", volume="18", number="11", pages="e301", keywords="patient dropouts", keywords="surveys and questionnaires", keywords="electronic health records", abstract="Background: Electronic surveys are convenient, cost effective, and increasingly popular tools for collecting information. While the online platform allows researchers to recruit and enroll more participants, there is an increased risk of participant dropout in Web-based research. Often, these dropout trends are simply reported, adjusted for, or ignored altogether. Objective: To propose a conceptual framework that analyzes respondent attrition and demonstrates the utility of these methods with existing survey data. Methods: First, we suggest visualization of attrition trends using bar charts and survival curves. Next, we propose a generalized linear mixed model (GLMM) to detect or confirm significant attrition points. Finally, we suggest applications of existing statistical methods to investigate the effect of internal survey characteristics and patient characteristics on dropout. In order to apply this framework, we conducted a case study; a seventeen-item Informed Decision-Making (IDM) module addressing how and why patients make decisions about cancer screening. Results: Using the framework, we were able to find significant attrition points at Questions 4, 6, 7, and 9, and were also able to identify participant responses and characteristics associated with dropout at these points and overall. Conclusions: When these methods were applied to survey data, significant attrition trends were revealed, both visually and empirically, that can inspire researchers to investigate the factors associated with survey dropout, address whether survey completion is associated with health outcomes, and compare attrition patterns between groups. The framework can be used to extract information beyond simple responses, can be useful during survey development, and can help determine the external validity of survey results. ", doi="10.2196/jmir.6342", url="http://www.jmir.org/2016/11/e301/", url="http://www.ncbi.nlm.nih.gov/pubmed/27876687" } @Article{info:doi/10.2196/resprot.5494, author="Singla, Apresh", title="Protocol for Autologous Fat Grafting for Immediate Reconstruction of Lumpectomy Defects Following Surgery for Breast Cancer", journal="JMIR Res Protoc", year="2016", month="Jul", day="05", volume="5", number="3", pages="e109", keywords="Fat grafting", keywords="lumpectomy defects", abstract="Background: For women undergoing breast conservative surgery or lumpectomy for early stage breast carcinoma, there are limited options for reconstruction. Options include the use of flap surgery and/or implants, and have a significant associated morbidity and cost. Autologous fat grafting is a new alternative that can achieve a good cosmetic result, while reducing patient morbidity and cost by avoiding more extensive surgery. Objective: The primary objectives are to assess patient satisfaction using the Breast-Q questionnaire and to evaluate fat graft volume. The secondary objectives are fat survival and assessment for complication (eg, fat necrosis, cysts), local recurrence, and the number of sessions needed for a satisfactory outcome. Methods: This study is a case series of 100 patients, at a single-center institute spanning one year. The inclusion criteria include: female sex, age 18 to 75, early state breast cancer (confirmed on ultrasound/ positron emission tomography-computed tomography and cytology), amenable to breast conservative surgery, and at least 6 months post-completion of radiotherapy/ hormone/chemotherapy. Exclusion criteria include patients with more advanced stages of breast cancer necessitating total mastectomy, those unsuitable for surgical excision, and those in whom lumpectomy is not feasible. The patients will have follow-up data collected at 6 months, 12 months and 5 years post-operatively. Results: This study will begin enrolment in January 2017. We anticipate that there will be good patient satisfaction with fat grafting. The risk for long-term breast cancer recurrence hasn't been evaluated extensively in literature, however some clinical studies have shown no increased risk of breast cancer in appropriately selected patients at one year. Although some patients may develop complications from fat grafting (eg, necrosis/cysts) this should not confuse the radiological detection of breast cancer recurrence. Conclusions: Fat grafting is proving to be a viable option for reconstruction of lumpectomy defects with good patient satisfaction. The heterogeneous methods of reporting the harvesting of fat in literature may account for the variable outcomes described, and makes it difficult to compare results with similar studies. The long-term risk of breast cancer recurrence with fat grafting for lumpectomy defects is unknown. ", doi="10.2196/resprot.5494", url="http://www.researchprotocols.org/2016/3/e109/", url="http://www.ncbi.nlm.nih.gov/pubmed/27380864" }