TY - JOUR AU - Ziegler, Jasmin AU - Erpenbeck, Pascal Marcel AU - Fuchs, Timo AU - Saibold, Anna AU - Volkmer, Paul-Christian AU - Schmidt, Guenter AU - Eicher, Johanna AU - Pallaoro, Peter AU - De Souza Falguera, Renata AU - Aubele, Fabio AU - Hagedorn, Marlien AU - Vansovich, Ekaterina AU - Raffler, Johannes AU - Ringshandl, Stephan AU - Kerscher, Alexander AU - Maurer, Karolin Julia AU - Kühnel, Brigitte AU - Schenkirsch, Gerhard AU - Kampf, Marvin AU - Kapsner, A. Lorenz AU - Ghanbarian, Hadieh AU - Spengler, Helmut AU - Soto-Rey, Iñaki AU - Albashiti, Fady AU - Hellwig, Dirk AU - Ertl, Maximilian AU - Fette, Georg AU - Kraska, Detlef AU - Boeker, Martin AU - Prokosch, Hans-Ulrich AU - Gulden, Christian PY - 2025/4/15 TI - Bridging Data Silos in Oncology with Modular Software for Federated Analysis on Fast Healthcare Interoperability Resources: Multisite Implementation Study JO - J Med Internet Res SP - e65681 VL - 27 KW - real-world data KW - real-world evidence KW - oncology KW - electronic health records KW - federated analysis KW - HL7 FHIR KW - cancer registries KW - interoperability KW - observational research network N2 - Background: Real-world data (RWD) from sources like administrative claims, electronic health records, and cancer registries offer insights into patient populations beyond the tightly regulated environment of randomized controlled trials. To leverage this and to advance cancer research, 6 university hospitals in Bavaria have established a joint research IT infrastructure. Objective: This study aimed to outline the design, implementation, and deployment of a modular data transformation pipeline that transforms oncological RWD into a Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) format and then into a tabular format in preparation for a federated analysis (FA) across the 6 Bavarian Cancer Research Center university hospitals. Methods: To harness RWD effectively, we designed a pipeline to convert the oncological basic dataset (oBDS) into HL7 FHIR format and prepare it for FA. The pipeline handles diverse IT infrastructures and systems while maintaining privacy by keeping data decentralized for analysis. To assess the functionality and validity of our implementation, we defined a cohort to address two specific medical research questions. We evaluated our findings by comparing the results of the FA with reports from the Bavarian Cancer Registry and the original data from local tumor documentation systems. Results: We conducted an FA of 17,885 cancer cases from 2021/2022. Breast cancer was the most common diagnosis at 3 sites, prostate cancer ranked in the top 2 at 4 sites, and malignant melanoma was notably prevalent. Gender-specific trends showed larynx and esophagus cancers were more common in males, while breast and thyroid cancers were more frequent in females. Discrepancies between the Bavarian Cancer Registry and our data, such as higher rates of malignant melanoma (3400/63,771, 5.3% vs 1921/17,885, 10.7%) and lower representation of colorectal cancers (8100/63,771, 12.7% vs 1187/17,885, 6.6%) likely result from differences in the time periods analyzed (2019 vs 2021/2022) and the scope of data sources used. The Bavarian Cancer Registry reports approximately 3 times more cancer cases than the 6 university hospitals alone. Conclusions: The modular pipeline successfully transformed oncological RWD across 6 hospitals, and the federated approach preserved privacy while enabling comprehensive analysis. Future work will add support for recent oBDS versions, automate data quality checks, and integrate additional clinical data. Our findings highlight the potential of federated health data networks and lay the groundwork for future research that can leverage high-quality RWD, aiming to contribute valuable knowledge to the field of cancer research. UR - https://www.jmir.org/2025/1/e65681 UR - http://dx.doi.org/10.2196/65681 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/65681 ER - TY - JOUR AU - Lee, Denise AU - Vaid, Akhil AU - Menon, M. Kartikeya AU - Freeman, Robert AU - Matteson, S. David AU - Marin, L. Michael AU - Nadkarni, N. Girish PY - 2025/4/7 TI - Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study JO - JMIR Form Res SP - e64544 VL - 9 KW - natural language processing KW - large language model KW - artificial intelligence KW - thyroid cancer KW - endocrine surgery KW - framework KW - privacy KW - medical KW - surgical pathology KW - report KW - NLP KW - medical question N2 - 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. UR - https://formative.jmir.org/2025/1/e64544 UR - http://dx.doi.org/10.2196/64544 ID - info:doi/10.2196/64544 ER - TY - JOUR AU - Kim, Yesol AU - Kim, Geonah AU - Cho, Hyeonmi AU - Kim, Yeonju AU - Choi, Mona PY - 2025/2/4 TI - Application of Patient-Generated Health Data Among Older Adults With Cancer: Scoping Review JO - J Med Internet Res SP - e57379 VL - 27 KW - patient-generated health data KW - wearable devices KW - patient-reported outcomes KW - patient-centered care KW - older adults KW - cancer KW - scoping review N2 - 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 UR - https://www.jmir.org/2025/1/e57379 UR - http://dx.doi.org/10.2196/57379 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/57379 ER - TY - JOUR AU - Helissey, Carole AU - Cavallero, Sophie AU - Guitard, Nathalie AU - Thery, Hélène AU - Parnot, Charles AU - Schernberg, Antoine AU - Aissa, Imen AU - Raffin, Florent AU - Le Coz, Christine AU - Mondot, Stanislas AU - Christopoulos, Christos AU - Malek, Karim AU - Malaurie, Emmanuelle AU - Blanchard, Pierre AU - Chargari, Cyrus AU - Francois, Sabine PY - 2024/12/12 TI - Correlation Between Electronic Patient-Reported Outcomes and Biological Markers of Key Parameters in Acute Radiation Cystitis Among Patients With Prostate Cancer (RABBIO): Prospective Observational Study JO - JMIR Cancer SP - e48225 VL - 10 KW - prostate cancer KW - acute radiation cystitis KW - e-PRO KW - quality of life KW - biomarkers KW - electronic patient-reported outcome N2 - Background: Despite advances in radiation techniques, radiation cystitis (RC) remains a significant cause of morbidity from pelvic radiotherapy, which may affect patients? quality of life (QoL). The pathophysiology of RC is not well understood, which limits the development of effective treatments. Objective: The Radiotoxicity Bladder Biomarkers study aims to investigate the correlation between blood and urinary biomarkers and the intensity of acute RC symptoms and QoL in patients undergoing localized prostate cancer radiotherapy. Methods: This study included patients with low- or intermediate-risk localized prostate cancer who were eligible for localized radiotherapy. Blood and urinary biomarkers were analyzed before radiotherapy was initiated and at weeks 4 and 12 of radiation therapy. Patients completed questionnaires related to RC symptoms and QoL (International Prostate Symptom Score and Functional Assessment of Cancer Therapy-Prostate [FACT-P]) using a digital remote monitoring platform. The information was processed by means of an algorithm, which classified patients according to the severity of symptoms and adverse events reported. Levels of blood and urinary biomarkers were tested with the severity of acute RC symptoms and patient-reported QoL. Results: A total of 401 adverse events questionnaires were collected over the duration of this study from 20 patients. The most frequently reported adverse events at week 4 were pollakiuria, constipation, and diarrhea. In comparison with baseline, the mean FACT-P score decreased at week 4. A significant increase in the proportion of M2 phenotype cells (CD206+, CD163+, CD204+) at W12 compared to W0 was observed. An increase in serum and urine levels of macrophage colony-stimulating factor (M-CSF), hepatocyte growth factor, and macrophagic inflammatory protein was observed at week 12 compared to baseline levels. Baseline serum and urine M-CSF concentrations showed a significant negative correlation with FACT-P scores at weeks 4 and 12 (r=?0.65, P=.04, and r=?0.76, P=.02, respectively). Conclusions: The Radiotoxicity Bladder Biomarkers study is the first to explore the overexpression of inflammatory proteins in blood and urine of patients with symptoms of acute RC. These preliminary findings suggest that serum and urine levels of hepatocyte growth factor, M-CSF, and macrophagic inflammatory protein, as well as macrophage polarization, are mobilized after prostate radiotherapy. The elevated M-CSF levels in serum and urine at baseline were associated with the deterioration of QoL during radiotherapy. The results of this study may help to develop mitigation strategies to limit radiation damage to the bladder. Trial Registration: ClinicalTrials.gov NCT05246774; https://clinicaltrials.gov/study/NCT05246774 UR - https://cancer.jmir.org/2024/1/e48225 UR - http://dx.doi.org/10.2196/48225 ID - info:doi/10.2196/48225 ER - TY - JOUR AU - McClaine, Sean AU - Fedor, Jennifer AU - Bartel, Christianna AU - Chen, Leeann AU - Durica, C. Krina AU - Low, A. Carissa PY - 2024/12/10 TI - Engagement With Daily Symptom Reporting, Passive Smartphone Sensing, and Wearable Device Data Collection During Chemotherapy: Longitudinal Observational Study JO - JMIR Cancer SP - e57347 VL - 10 KW - cancer KW - chemotherapy KW - remote monitoring KW - mobile health KW - wearable device KW - mobile phone KW - oncology KW - metastases KW - chemo KW - mHealth KW - mobile application KW - digital health KW - digital intervention N2 - Background: Chemotherapy can cause symptoms that impair quality of life and functioning. Remote monitoring of daily symptoms and activity during outpatient treatment may enable earlier detection and management of emerging toxicities but requires patients, including older and acutely ill patients, to engage with technology to report symptoms through smartphones and to charge and wear mobile devices. Objective: This study aimed to identify factors associated with participant engagement with collecting 3 data streams (ie, daily patient-reported symptom surveys, passive smartphone sensing, and a wearable Fitbit device [Google]) during chemotherapy. Methods: We enrolled 162 patients receiving outpatient chemotherapy into a 90-day prospective study. Patients were asked to install apps on their smartphones to rate daily symptoms and to collect passive sensor data and to wear a Fitbit device for the duration of the study. Participants completed baseline demographic and quality of life questionnaires, and clinical information was extracted from the electronic medical record. We fit a series of logistic generalized estimating equations to evaluate the association between demographic and clinical factors and daily engagement with each data stream. Results: Participants completed daily surveys on 61% (SD 27%) of days and collected sufficient smartphone data and wearable sensor data on 73% (SD 35%) and 70% (SD 33%) of enrolled days, respectively, on average. Relative to White participants, non-White patients demonstrated lower odds of engagement with both symptom surveys (odds ratio [OR] 0.49, 95% CI 0.29-0.81; P=.006) and wearable data collection (OR 0.35, 95% CI 0.17-0.73; P=.005). Patients with stage 4 cancer also exhibited lower odds of engagement with symptom reporting than those with earlier stage disease (OR 0.69, 95% CI 0.48-1.00; P=.048), and patients were less likely to complete symptom ratings on the weekend (OR 0.90, 95% CI 0.83-0.97; P=.008). Older patients (OR 1.03, 95% CI 1.01-1.06; P=.01) and those who reported better cognitive functioning at study entry (OR 1.18, 95% CI 1.03-1.34; P=.02) were more likely to engage with Fitbit data collection, and patients who reported higher levels of depressive symptoms were less likely to engage with smartphone data collection (OR 1.18, 95% CI 1.03-1.36; P=.02). Conclusions: Remote patient monitoring during chemotherapy has the potential to improve clinical management, but only if patients engage with these systems. Our results suggest significant associations between demographic and clinical factors and long-term engagement with smartphone and wearable device assessments during chemotherapy. Non-White participants, those with metastatic cancer, or those with existing cognitive impairment may benefit from additional resources to optimize engagement. Contrary to hypotheses, older adults were more likely than younger adults to engage consistently with wearable device assessments. UR - https://cancer.jmir.org/2024/1/e57347 UR - http://dx.doi.org/10.2196/57347 UR - http://www.ncbi.nlm.nih.gov/pubmed/39656513 ID - info:doi/10.2196/57347 ER - TY - JOUR AU - Geeraerts, Joran AU - Pivodic, Lara AU - Rosquin, Lise AU - Naert, Eline AU - Crombez, Geert AU - De Ridder, Mark AU - Van den Block, Lieve PY - 2024/11/5 TI - Uncovering the Daily Experiences of People Living With Advanced Cancer Using an Experience Sampling Method Questionnaire: Development, Content Validation, and Optimization Study JO - JMIR Cancer SP - e57510 VL - 10 KW - cancer KW - quality of life KW - ecological momentary assessment KW - experience sampling method KW - telemedicine KW - mHealth KW - eHealth KW - patient outcome assessment KW - validated instruments N2 - Background: The experience sampling method (ESM), a self-report method that typically uses multiple assessments per day, can provide detailed knowledge of the daily experiences of people with cancer, potentially informing oncological care. The use of the ESM among people with advanced cancer is limited, and no validated ESM questionnaires have been developed specifically for oncology. Objective: This study aims to develop, content validate, and optimize the digital Experience Sampling Method for People Living With Advanced Cancer (ESM-AC) questionnaire, covering multidimensional domains and contextual factors. Methods: A 3-round mixed methods study was designed in accordance with the Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) and the European Organization for Research and Treatment of Cancer guidelines. The study included semistructured interviews with 43 people with stage IV breast cancer or stage III to IV lung cancer and 8 health care professionals. Round 1 assessed the appropriateness, relative importance, relevance, and comprehensiveness of an initial set of ESM items that were developed based on the existing questionnaires. Round 2 tested the comprehensibility of ESM items. Round 3 tested the usability of the digital ESM-AC questionnaire using the m-Path app. Analyses included descriptive statistics and qualitative content analysis. Results: Following the first round, we developed an initial core set of 68 items (to be used with all patients) and a supplementary set (optional; patients select items), both covering physical, psychological, social, spiritual-existential, and global well-being domains and concurrent contexts in which experiences occur. We categorized items to be assessed multiple times per day as momentary items (eg, ?At this moment, I feel tired?), once a day in the morning as morning items (eg, ?Last night, I slept well?), or once a day in the evening as evening items (eg, ?Today, I felt hopeful?). We used participants? evaluations to optimize the questionnaire items, the digital app, and its onboarding manual. This resulted in the ESM-AC questionnaire, which comprised a digital core questionnaire containing 31 momentary items, 2 morning items, and 7 evening items and a supplementary set containing 39 items. Participants largely rated the digital questionnaire as ?easy to use,? with an average score of 4.5 (SD 0.5) on a scale from 1 (?completely disagree?) to 5 (?completely agree?). Conclusions: We developed the ESM-AC questionnaire, a content-validated digital questionnaire for people with advanced breast or lung cancer. It showed good usability when administered on smartphone devices. Future research should evaluate the potential of this ESM tool to uncover daily experiences of people with advanced breast or lung cancer, explore its clinical utility, and extend its validation to other populations with advanced diseases. UR - https://cancer.jmir.org/2024/1/e57510 UR - http://dx.doi.org/10.2196/57510 UR - http://www.ncbi.nlm.nih.gov/pubmed/ ID - info:doi/10.2196/57510 ER - TY - JOUR AU - Garcia-Saiso, Sebastian AU - Marti, Myrna AU - Pesce, Karina AU - Luciani, Silvana AU - Mujica, Oscar AU - Hennis, Anselm AU - D'Agostino, Marcelo PY - 2024/8/12 TI - Artificial Intelligence as a Potential Catalyst to a More Equitable Cancer Care JO - JMIR Cancer SP - e57276 VL - 10 KW - digital health KW - public health KW - cancer KW - artificial intelligence KW - AI KW - catalyst KW - cancer care KW - cost KW - costs KW - demographic KW - epidemiological KW - change KW - changes KW - healthcare KW - equality KW - health system KW - mHealth KW - mobile health UR - https://cancer.jmir.org/2024/1/e57276 UR - http://dx.doi.org/10.2196/57276 UR - http://www.ncbi.nlm.nih.gov/pubmed/39133537 ID - info:doi/10.2196/57276 ER - TY - JOUR AU - Baum, Eleonore AU - Thiel, Christian AU - Kobleder, Andrea AU - Bernhardsgrütter, Daniela AU - Engst, Ramona AU - Maurer, Carola AU - Koller, Antje PY - 2024/7/29 TI - Using a Mobile Messenger Service as a Digital Diary to Capture Patients? Experiences Along Their Interorganizational Treatment Path in Gynecologic Oncology: Lessons Learned JO - JMIR Cancer SP - e52985 VL - 10 KW - mobile apps KW - computer security KW - confidentiality KW - data collection KW - oncology KW - breast neoplasms KW - mobile phone UR - https://cancer.jmir.org/2024/1/e52985 UR - http://dx.doi.org/10.2196/52985 UR - http://www.ncbi.nlm.nih.gov/pubmed/39073852 ID - info:doi/10.2196/52985 ER - TY - JOUR AU - Shinn, H. Eileen AU - Garden, S. Adam AU - Peterson, K. Susan AU - Leupi, J. Dylan AU - Chen, Minxing AU - Blau, Rachel AU - Becerra, Laura AU - Rafeedi, Tarek AU - Ramirez, Julian AU - Rodriquez, Daniel AU - VanFossen, Finley AU - Zehner, Sydney AU - Mercier, P. Patrick AU - Wang, Joseph AU - Hutcheson, Kate AU - Hanna, Ehab AU - Lipomi, J. Darren PY - 2024/2/28 TI - Iterative Patient Testing of a Stimuli-Responsive Swallowing Activity Sensor to Promote Extended User Engagement During the First Year After Radiation: Multiphase Remote and In-Person Observational Cohort Study JO - JMIR Cancer SP - e47359 VL - 10 KW - user-centered design KW - patients with head and neck cancer KW - dysphagia throat sensor N2 - Background: Frequent sensor-assisted monitoring of changes in swallowing function may help improve detection of radiation-associated dysphagia before it becomes permanent. While our group has prototyped an epidermal strain/surface electromyography sensor that can detect minute changes in swallowing muscle movement, it is unknown whether patients with head and neck cancer would be willing to wear such a device at home after radiation for several months. Objective: We iteratively assessed patients? design preferences and perceived barriers to long-term use of the prototype sensor. Methods: In study 1 (questionnaire only), survivors of pharyngeal cancer who were 3-5 years post treatment and part of a larger prospective study were asked their design preferences for a hypothetical throat sensor and rated their willingness to use the sensor at home during the first year after radiation. In studies 2 and 3 (iterative user testing), patients with and survivors of head and neck cancer attending visits at MD Anderson?s Head and Neck Cancer Center were recruited for two rounds of on-throat testing with prototype sensors while completing a series of swallowing tasks. Afterward, participants were asked about their willingness to use the sensor during the first year post radiation. In study 2, patients also rated the sensor?s ease of use and comfort, whereas in study 3, preferences were elicited regarding haptic feedback. Results: The majority of respondents in study 1 (116/138, 84%) were willing to wear the sensor 9 months after radiation, and participant willingness rates were similar in studies 2 (10/14, 71.4%) and 3 (12/14, 85.7%). The most prevalent reasons for participants? unwillingness to wear the sensor were 9 months being excessive, unwanted increase in responsibility, and feeling self-conscious. Across all three studies, the sensor?s ability to detect developing dysphagia increased willingness the most compared to its appearance and ability to increase adherence to preventive speech pathology exercises. Direct haptic signaling was also rated highly, especially to indicate correct sensor placement and swallowing exercise performance. Conclusions: Patients and survivors were receptive to the idea of wearing a personalized risk sensor for an extended period during the first year after radiation, although this may have been limited to well-educated non-Hispanic participants. A significant minority of patients expressed concern with various aspects of the sensor?s burden and its appearance. Trial Registration: ClinicalTrials.gov NCT03010150; https://clinicaltrials.gov/study/NCT03010150 UR - https://cancer.jmir.org/2024/1/e47359 UR - http://dx.doi.org/10.2196/47359 UR - http://www.ncbi.nlm.nih.gov/pubmed/38416544 ID - info:doi/10.2196/47359 ER - TY - JOUR AU - Dong, Pei AU - Mao, Ayan AU - Qiu, Wuqi AU - Li, Guanglin PY - 2024/2/27 TI - Improvement of Cancer Prevention and Control: Reflection on the Role of Emerging Information Technologies JO - J Med Internet Res SP - e50000 VL - 26 KW - emerging information technologies KW - cancer KW - prevention and control UR - https://www.jmir.org/2024/1/e50000 UR - http://dx.doi.org/10.2196/50000 UR - http://www.ncbi.nlm.nih.gov/pubmed/38412009 ID - info:doi/10.2196/50000 ER - TY - JOUR AU - Su, Zhenzhen AU - Zhang, Liyan AU - Lian, Xuemin AU - Guan, Miaomiao PY - 2024/2/26 TI - Virtual Reality?Based Exercise Rehabilitation in Cancer-Related Dysfunctions: Scoping Review JO - J Med Internet Res SP - e49312 VL - 26 KW - virtual reality KW - cancer KW - virtual reality?based exercise rehabilitation KW - cancer-related dysfunction KW - rehabilitation KW - scoping review N2 - Background: Virtual reality?based exercise rehabilitation (VRER) is a promising intervention for patients with cancer-related dysfunctions (CRDs). However, studies focusing on VRER for CRDs are lacking, and the results are inconsistent. Objective: We aimed to review the application of VRER in patients with CRDs. Methods: This scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist framework. Publications were included from the time of database establishment to October 14, 2023. The databases were PubMed, Embase, Scopus, Cochrane, Web of Science, ProQuest, arXiv, IEEE Xplore, MedRxiv, CNKI, Wanfang Data, VIP, and SinoMed. The population included patients with cancer. A virtual reality (VR) system or device was required to be provided in exercise rehabilitation as an intervention. Eligible studies focused on VRER used for CRDs. Study selection and data extraction were performed by 2 reviewers independently. Extracted data included authors, year, country, study type, groups, sample size, participant age, cancer type, existing or potential CRDs, VR models and devices, intervention programs and durations, effectiveness, compliance, satisfaction, and safety. Results: We identified 25 articles, and among these, 12 (48%) were randomized clinical trials, 11 (44%) were other experimental studies, and 2 (8%) were observational studies. The total sample size was 1174 (range 6-136). Among the 25 studies, 22 (88%), 2 (8%), and 1 (4%) included nonimmersive VR, immersive VR, and augmented reality, respectively, which are models of VRER. Commercial game programs (17/25, 68%) were the most popular interventions of VRER, and their duration ranged from 3 to 12 weeks. Using these models and devices, VRER was mostly applied in patients with breast cancer (14/25, 56%), leukemia (8/25, 32%), and lung cancer (3/25, 12%). Furthermore, 6 CRDs were intervened by VRER, and among these, postmastectomy syndromes were the most common (10/25, 40%). Overall, 74% (17/23) of studies reported positive results, including significant improvements in limb function, joint range of motion, edema rates, cognition, respiratory disturbance index, apnea, activities of daily living, and quality of life. The compliance rate ranged from 56% to 100%. Overall, 32% (8/25) of studies reported on patient satisfaction, and of these, 88% (7/8) reported satisfaction with VRER. Moreover, 13% (1/8) reported mild sickness as an adverse event. Conclusions: We found that around half of the studies reported using VRER in patients with breast cancer and postmastectomy dysfunctions through nonimmersive models and commercial game programs having durations of 3-12 weeks. In addition, most studies showed that VRER was effective owing to virtualization and interaction. Therefore, VRER may be an alternate intervention for patients with CRDs. However, as the conclusions were drawn from data with acknowledged inconsistencies and limited satisfaction reports, studies with larger sample sizes and more outcome indictors are required. UR - https://www.jmir.org/2024/1/e49312 UR - http://dx.doi.org/10.2196/49312 UR - http://www.ncbi.nlm.nih.gov/pubmed/38407951 ID - info:doi/10.2196/49312 ER - TY - JOUR AU - Gong, Jeong Eun AU - Bang, Seok Chang AU - Lee, Jun Jae AU - Jeong, Min Hae AU - Baik, Ho Gwang AU - Jeong, Hoon Jae AU - Dick, Sigmund AU - Lee, Hun Gi PY - 2023/10/30 TI - Clinical Decision Support System for All Stages of Gastric Carcinogenesis in Real-Time Endoscopy: Model Establishment and Validation Study JO - J Med Internet Res SP - e50448 VL - 25 KW - atrophy KW - intestinal metaplasia KW - metaplasia KW - deep learning KW - endoscopy KW - gastric neoplasms KW - neoplasm KW - neoplasms KW - internal medicine KW - cancer KW - oncology KW - decision support KW - real time KW - gastrointestinal KW - gastric KW - intestinal KW - machine learning KW - clinical decision support system KW - CDSS KW - computer aided KW - diagnosis KW - diagnostic KW - carcinogenesis N2 - Background: Our research group previously established a deep-learning?based clinical decision support system (CDSS) for real-time endoscopy-based detection and classification of gastric neoplasms. However, preneoplastic conditions, such as atrophy and intestinal metaplasia (IM) were not taken into account, and there is no established model that classifies all stages of gastric carcinogenesis. Objective: This study aims to build and validate a CDSS for real-time endoscopy for all stages of gastric carcinogenesis, including atrophy and IM. Methods: A total of 11,868 endoscopic images were used for training and internal testing. The primary outcomes were lesion classification accuracy (6 classes: advanced gastric cancer, early gastric cancer, dysplasia, atrophy, IM, and normal) and atrophy and IM lesion segmentation rates for the segmentation model. The following tests were carried out to validate the performance of lesion classification accuracy: (1) external testing using 1282 images from another institution and (2) evaluation of the classification accuracy of atrophy and IM in real-world procedures in a prospective manner. To estimate the clinical utility, 2 experienced endoscopists were invited to perform a blind test with the same data set. A CDSS was constructed by combining the established 6-class lesion classification model and the preneoplastic lesion segmentation model with the previously established lesion detection model. Results: The overall lesion classification accuracy (95% CI) was 90.3% (89%-91.6%) in the internal test. For the performance validation, the CDSS achieved 85.3% (83.4%-97.2%) overall accuracy. The per-class external test accuracies for atrophy and IM were 95.3% (92.6%-98%) and 89.3% (85.4%-93.2%), respectively. CDSS-assisted endoscopy showed an accuracy of 92.1% (88.8%-95.4%) for atrophy and 95.5% (92%-99%) for IM in the real-world application of 522 consecutive screening endoscopies. There was no significant difference in the overall accuracy between the invited endoscopists and established CDSS in the prospective real-clinic evaluation (P=.23). The CDSS demonstrated a segmentation rate of 93.4% (95% CI 92.4%-94.4%) for atrophy or IM lesion segmentation in the internal testing. Conclusions: The CDSS achieved high performance in terms of computer-aided diagnosis of all stages of gastric carcinogenesis and demonstrated real-world application potential. UR - https://www.jmir.org/2023/1/e50448 UR - http://dx.doi.org/10.2196/50448 UR - http://www.ncbi.nlm.nih.gov/pubmed/37902818 ID - info:doi/10.2196/50448 ER - TY - JOUR AU - Li, Yufei AU - Chen, Weihong AU - Liang, Yanjing AU - Yang, Ling AU - Hou, Lili PY - 2023/10/23 TI - Evaluation of Mobile Health Technology Interventions for the Postdischarge Management of Patients With Head and Neck Cancer: Scoping Review JO - JMIR Mhealth Uhealth SP - e49051 VL - 11 KW - head and neck cancer KW - mobile health technology KW - postdischarge KW - self-management KW - rehabilitation N2 - Background: Patients with head and neck cancer (HNC) often experience various types and degrees of complications and functional impairment following surgery or radiotherapy. Consequently, these patients require extensive postdischarge rehabilitation, either at home or in the community. Numerous studies have shown the advantages of mobile Health (mHealth) technology in assisting patients with cancer with self-management and rehabilitation during the postdischarge period. However, few reviews have focused on the intervention, management, and evaluation of mHealth technology in postdischarge patients with HNC. Objective: This study aimed to conduct a scoping review of mHealth technology apps and interventions currently available to patients discharged from hospitals after receiving treatment for HNC. This study sought to identify and summarize the types and effectiveness of existing mHealth interventions as well as the differences in their outcome assessments. Methods: The PubMed, Embase, Web of Science, and CINAHL databases were used to identify studies with no publication time limits. The keywords ?mobile health technology? and ?head and neck cancer? were combined to address the main concepts of the research questions. Results: Of the 1625 papers identified, 13 (0.8%) met the inclusion and exclusion criteria. Most studies (n=8, 61.5%) were randomized controlled trials (RCTs) and cohort studies. These studies were conducted in 6 countries. The main aims of the mHealth interventions in these studies are as follows: (1) symptom monitoring and assessment, (2) rehabilitation training, (3) access to medical health information, (4) telehealth advisers, (5) peer communication and support, and (6) follow-up/review reminders. The outcome evaluations of the 13 included studies were grouped into 4 categories: (1) technology usability and patient satisfaction, (2) self-management of symptoms and patient-reported outcome?related indicators, (3) adherence, and (4) health-related quality of life. Conclusions: A limited number of studies have investigated the use of mHealth technology in the postdischarge self-management of patients with HNC. The existing literature suggests that mHealth technology can effectively assist patients with HNC in self-management and postdischarge interventions. It plays an important role in addressing patients? health information needs, reducing both their somatic and psychological burdens, and improving their overall quality of life. Future research should prioritize conducting additional high-quality RCTs to evaluate the usability and analyze the cost-effectiveness of mHealth technology. UR - https://mhealth.jmir.org/2023/1/e49051 UR - http://dx.doi.org/10.2196/49051 UR - http://www.ncbi.nlm.nih.gov/pubmed/37870887 ID - info:doi/10.2196/49051 ER - TY - JOUR AU - Oyedele, K. Natasha AU - Lansey, G. Dina AU - Chiew, Calvin AU - Chan, Cupid AU - Quon, Harry AU - Dean, T. Lorraine PY - 2023/9/14 TI - Development and Testing of a Mobile App to Collect Social Determinants of Health Data in Cancer Settings: Interview Study JO - JMIR Form Res SP - e48737 VL - 7 KW - social determinants of health KW - mobile apps KW - medical oncology KW - mobile phone N2 - Background: Social determinants of health (SDOH) such as lack of basic resources, housing, transportation, and social isolation play an important role for patients on the cancer care continuum. Health systems? current technological solutions for identifying and managing patients? SDOH data largely focus on information recorded in the electronic health record by providers, which is often inaccessible to patients to contribute to or modify. Objective: We developed and tested a patient-centric SDOH screening tool designed for use on patients? personal mobile phone that preserves patient privacy and confidentiality, collects information about the unmet social needs of patients with cancer, and communicates them to the provider. Methods: We interviewed 22 patients with cancer, oncologists, and social workers associated with a US-based comprehensive cancer center to better understand how patients? SDOH information is collected and reported. After triangulating data obtained from thematic analysis of interviews, an environmental scan, and a literature search of validated tools to collect SDOH data, we developed an SDOH screening tool mobile app and conducted a pilot study of 16 dyadic pairs of patients and cancer care team members at the same cancer center. We collected patient SDOH data using 36 survey items covering 7 SDOH domains and used validated scales and follow-up interviews to assess the app?s usability and acceptability among patients and cancer care team members. Results: Formative interviews with patients and care team members revealed that transportation, financial challenges, food insecurity, and low health literacy were common SDOH challenges and that a mobile app that collected those data, shared those data with care team members, and offered supportive resources could be useful and valuable. In the pilot study, 25% (4/16) of app-using patients reported having at least one of the abovementioned social needs; the most common social need was social isolation (7/16, 44%). Patients rated the mobile app as easy to use, accurately capturing their SDOH, and preserving their privacy but suggested that the app could be more helpful by connecting patients to actual resources. Providers reported high acceptability and usability of the app. Conclusions: Use of a brief, patient-centric, mobile app?based SDOH screening tool can effectively capture SDOH of patients with cancer for care team members in a way that preserves patient privacy and that is acceptable and usable for patients and care team members. However, only collecting SDOH information is not sufficient; usefulness can be increased by connecting patients directly to resources to address their unmet social needs. UR - https://formative.jmir.org/2023/1/e48737 UR - http://dx.doi.org/10.2196/48737 UR - http://www.ncbi.nlm.nih.gov/pubmed/37707880 ID - info:doi/10.2196/48737 ER - TY - JOUR AU - Siglen, Elen AU - Vetti, Høberg Hildegunn AU - Augestad, Mirjam AU - Steen, M. Vidar AU - Lunde, Åshild AU - Bjorvatn, Cathrine PY - 2023/9/1 TI - Evaluation of the Rosa Chatbot Providing Genetic Information to Patients at Risk of Hereditary Breast and Ovarian Cancer: Qualitative Interview Study JO - J Med Internet Res SP - e46571 VL - 25 KW - chatbot KW - chatbots KW - genetic KW - trust KW - acceptability KW - perception KW - perceived KW - genetic counseling KW - hybrid health care KW - digital health tool KW - digital information tool KW - digital health technology KW - virtual assistant KW - hereditary breast and ovarian cancer KW - hereditary KW - genetic testing KW - technology KW - genetic clinic KW - digital tool KW - ovarian cancer KW - breast cancer KW - information retrieval KW - women?s health KW - breast KW - ovarian KW - cancer KW - oncology KW - mobile phone N2 - Background: Genetic testing has become an integrated part of health care for patients with breast or ovarian cancer, and the increasing demand for genetic testing is accompanied by an increasing need for easy access to reliable genetic information for patients. Therefore, we developed a chatbot app (Rosa) that is able to perform humanlike digital conversations about genetic BRCA testing. Objective: Before implementing this new information service in daily clinical practice, we wanted to explore 2 aspects of chatbot use: the perceived utility and trust in chatbot technology among healthy patients at risk of hereditary cancer and how interaction with a chatbot regarding sensitive information about hereditary cancer influences patients. Methods: Overall, 175 healthy individuals at risk of hereditary breast and ovarian cancer were invited to test the chatbot, Rosa, before and after genetic counseling. To secure a varied sample, participants were recruited from all cancer genetic clinics in Norway, and the selection was based on age, gender, and risk of having a BRCA pathogenic variant. Among the 34.9% (61/175) of participants who consented for individual interview, a selected subgroup (16/61, 26%) shared their experience through in-depth interviews via video. The semistructured interviews covered the following topics: usability, perceived usefulness, trust in the information received via the chatbot, how Rosa influenced the user, and thoughts about future use of digital tools in health care. The transcripts were analyzed using the stepwise-deductive inductive approach. Results: The overall finding was that the chatbot was very welcomed by the participants. They appreciated the 24/7 availability wherever they were and the possibility to use it to prepare for genetic counseling and to repeat and ask questions about what had been said afterward. As Rosa was created by health care professionals, they also valued the information they received as being medically correct. Rosa was referred to as being better than Google because it provided specific and reliable answers to their questions. The findings were summed up in 3 concepts: ?Anytime, anywhere?; ?In addition, not instead?; and ?Trustworthy and true.? All participants (16/16) denied increased worry after reading about genetic testing and hereditary breast and ovarian cancer in Rosa. Conclusions: Our results indicate that a genetic information chatbot has the potential to contribute to easy access to uniform information for patients at risk of hereditary breast and ovarian cancer, regardless of geographical location. The 24/7 availability of quality-assured information, tailored to the specific situation, had a reassuring effect on our participants. It was consistent across concepts that Rosa was a tool for preparation and repetition; however, none of the participants (0/16) supported that Rosa could replace genetic counseling if hereditary cancer was confirmed. This indicates that a chatbot can be a well-suited digital companion to genetic counseling. UR - https://www.jmir.org/2023/1/e46571 UR - http://dx.doi.org/10.2196/46571 UR - http://www.ncbi.nlm.nih.gov/pubmed/37656502 ID - info:doi/10.2196/46571 ER - TY - JOUR AU - Liu, Jen-Hsuan AU - Shih, Chih-Yuan AU - Huang, Hsien-Liang AU - Peng, Jen-Kuei AU - Cheng, Shao-Yi AU - Tsai, Jaw-Shiun AU - Lai, Feipei PY - 2023/8/18 TI - Evaluating the Potential of Machine Learning and Wearable Devices in End-of-Life Care in Predicting 7-Day Death Events Among Patients With Terminal Cancer: Cohort Study JO - J Med Internet Res SP - e47366 VL - 25 KW - artificial intelligence KW - end-of-life care KW - machine learning KW - palliative care KW - survival prediction KW - terminal cancer KW - wearable device N2 - Background: An accurate prediction of mortality in end-of-life care is crucial but presents challenges. Existing prognostic tools demonstrate moderate performance in predicting survival across various time frames, primarily in in-hospital settings and single-time evaluations. However, these tools may fail to capture the individualized and diverse trajectories of patients. Limited evidence exists regarding the use of artificial intelligence (AI) and wearable devices, specifically among patients with cancer at the end of life. Objective: This study aimed to investigate the potential of using wearable devices and AI to predict death events among patients with cancer at the end of life. Our hypothesis was that continuous monitoring through smartwatches can offer valuable insights into the progression of patients at the end of life and enable the prediction of changes in their condition, which could ultimately enhance personalized care, particularly in outpatient or home care settings. Methods: This prospective study was conducted at the National Taiwan University Hospital. Patients diagnosed with cancer and receiving end-of-life care were invited to enroll in wards, outpatient clinics, and home-based care settings. Each participant was given a smartwatch to collect physiological data, including steps taken, heart rate, sleep time, and blood oxygen saturation. Clinical assessments were conducted weekly. The participants were followed until the end of life or up to 52 weeks. With these input features, we evaluated the prediction performance of several machine learning?based classifiers and a deep neural network in 7-day death events. We used area under the receiver operating characteristic curve (AUROC), F1-score, accuracy, and specificity as evaluation metrics. A Shapley additive explanations value analysis was performed to further explore the models with good performance. Results: From September 2021 to August 2022, overall, 1657 data points were collected from 40 patients with a median survival time of 34 days, with the detection of 28 death events. Among the proposed models, extreme gradient boost (XGBoost) yielded the best result, with an AUROC of 96%, F1-score of 78.5%, accuracy of 93%, and specificity of 97% on the testing set. The Shapley additive explanations value analysis identified the average heart rate as the most important feature. Other important features included steps taken, appetite, urination status, and clinical care phase. Conclusions: We demonstrated the successful prediction of patient deaths within the next 7 days using a combination of wearable devices and AI. Our findings highlight the potential of integrating AI and wearable technology into clinical end-of-life care, offering valuable insights and supporting clinical decision-making for personalized patient care. It is important to acknowledge that our study was conducted in a relatively small cohort; thus, further research is needed to validate our approach and assess its impact on clinical care. Trial Registration: ClinicalTrials.gov NCT05054907; https://classic.clinicaltrials.gov/ct2/show/NCT05054907 UR - https://www.jmir.org/2023/1/e47366 UR - http://dx.doi.org/10.2196/47366 UR - http://www.ncbi.nlm.nih.gov/pubmed/37594793 ID - info:doi/10.2196/47366 ER - TY - JOUR AU - Li, He AU - Teng, Yi AU - Yan, Xinxin AU - Cao, Maomao AU - Yang, Fan AU - He, Siyi AU - Zhang, Shaoli AU - Li, Qianru AU - Xia, Changfa AU - Li, Kai AU - Chen, Wanqing PY - 2023/6/1 TI - Profiles and Findings of Population-Based Esophageal Cancer Screening With Endoscopy in China: Systematic Review and Meta-analysis JO - JMIR Public Health Surveill SP - e45360 VL - 9 KW - esophageal cancer KW - screening KW - high-risk individuals KW - detection rates KW - China N2 - Background: Population-based esophageal cancer (EC) screening trials and programs have been conducted in China for decades; however, screening strategies have been adopted in different regions and screening profiles are unclear. Objective: We performed a meta-analysis to profile EC screening in China by positivity rate, compliance rate, and endoscopy findings, aiming to provide explicit evidence and recommendations for EC screening programs. Methods: English (PubMed, Embase) and Chinese (China National Knowledge Infrastructure, Wanfang) language databases were systematically searched for population-based EC screening studies in the Chinese population until December 31, 2022. A meta-analysis was performed by standard methodology using a random-effects model. Pooled prevalence rates were calculated for three groups: high-risk areas with a universal endoscopy strategy, rural China with a risk-stratified endoscopic screening (RSES) strategy, and urban China with an RSES strategy. Positive cases included lesions of severe dysplasia, carcinoma in situ, intramucosal carcinoma, submucosal carcinoma, and invasive carcinoma. Results: The pooled positivity rate of the high-risk population was higher in rural China (44.12%) than in urban China (23.11%). The compliance rate of endoscopic examinations was the highest in rural China (52.40%), followed by high-risk areas (50.11%), and was the lowest in urban China (23.67%). The pooled detection rate of positive cases decreased from 1.03% (95% CI 0.82%-1.30%) in high-risk areas to 0.48% (95% CI 0.25%-0.93%) in rural China and 0.12% (95% CI 0.07%-0.21%) in urban China. The pooled detection rate of low-grade intraepithelial neoplasia (LGIN) was also in the same order, being the highest in high-risk areas (3.99%, 95% CI 2.78%-5.69%), followed by rural China (2.55%, 95% CI 1.03%-6.19%) and urban China (0.34%, 95% CI 0.14%-0.81%). Higher detection rates of positive cases and LGIN were observed among males than among females and at older ages. The pooled early detection rate was 81.90% (95% CI 75.58%-86.88%), which was similar to the rates in high-risk areas (82.09%), in rural China (80.76%), and in urban China (80.08%). Conclusions: Under the current screening framework, a higher screening benefit was observed in high-risk areas than in other regions. To promote EC screening and reduce the current inequality of screening in China, more focus should be given to optimizing strategies of high-risk individual assessment and surveillance management to improve compliance with endoscopic examination. Trial Registration: PROSPERO CRD42022375720; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=375720 UR - https://publichealth.jmir.org/2023/1/e45360 UR - http://dx.doi.org/10.2196/45360 UR - http://www.ncbi.nlm.nih.gov/pubmed/37261899 ID - info:doi/10.2196/45360 ER - TY - JOUR AU - Gao, Ying AU - Li, Shu AU - Jin, Yujing AU - Zhou, Lengxiao AU - Sun, Shaomei AU - Xu, Xiaoqian AU - Li, Shuqian AU - Yang, Hongxi AU - Zhang, Qing AU - Wang, Yaogang PY - 2022/12/29 TI - An Assessment of the Predictive Performance of Current Machine Learning?Based Breast Cancer Risk Prediction Models: Systematic Review JO - JMIR Public Health Surveill SP - e35750 VL - 8 IS - 12 KW - breast cancer KW - machine learning KW - risk prediction KW - cancer KW - oncology KW - systemic review KW - review KW - meta-analysis KW - cancer research KW - risk model N2 - Background: Several studies have explored the predictive performance of machine learning?based breast cancer risk prediction models and have shown controversial conclusions. Thus, the performance of the current machine learning?based breast cancer risk prediction models and their benefits and weakness need to be evaluated for the future development of feasible and efficient risk prediction models. Objective: The aim of this review was to assess the performance and the clinical feasibility of the currently available machine learning?based breast cancer risk prediction models. Methods: We searched for papers published until June 9, 2021, on machine learning?based breast cancer risk prediction models in PubMed, Embase, and Web of Science. Studies describing the development or validation models for predicting future breast cancer risk were included. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias and the clinical applicability of the included studies. The pooled area under the curve (AUC) was calculated using the DerSimonian and Laird random-effects model. Results: A total of 8 studies with 10 data sets were included. Neural network was the most common machine learning method for the development of breast cancer risk prediction models. The pooled AUC of the machine learning?based optimal risk prediction model reported in each study was 0.73 (95% CI 0.66-0.80; approximate 95% prediction interval 0.56-0.96), with a high level of heterogeneity between studies (Q=576.07, I2=98.44%; P<.001). The results of head-to-head comparison of the performance difference between the 2 types of models trained by the same data set showed that machine learning models had a slightly higher advantage than traditional risk factor?based models in predicting future breast cancer risk. The pooled AUC of the neural network?based risk prediction model was higher than that of the nonneural network?based optimal risk prediction model (0.71 vs 0.68, respectively). Subgroup analysis showed that the incorporation of imaging features in risk models resulted in a higher pooled AUC than the nonincorporation of imaging features in risk models (0.73 vs 0.61; Pheterogeneity=.001, respectively). The PROBAST analysis indicated that many machine learning models had high risk of bias and poorly reported calibration analysis. Conclusions: Our review shows that the current machine learning?based breast cancer risk prediction models have some technical pitfalls and that their clinical feasibility and reliability are unsatisfactory. UR - https://publichealth.jmir.org/2022/12/e35750 UR - http://dx.doi.org/10.2196/35750 UR - http://www.ncbi.nlm.nih.gov/pubmed/36426919 ID - info:doi/10.2196/35750 ER - TY - JOUR AU - Neil, M. Jordan AU - Senecal, Christian AU - Ballini, Lauren AU - Chang, Yuchiao AU - Goshe, Brett AU - Flores, Efren AU - Ostroff, S. Jamie AU - Park, R. Elyse PY - 2022/8/24 TI - A Multimethod Evaluation of Tobacco Treatment Trial Recruitment Messages for Current Smokers Recently Diagnosed With Cancer: Pilot Factorial Randomized Controlled Trial JO - JMIR Cancer SP - e37526 VL - 8 IS - 3 KW - teachable moment KW - cancer KW - tobacco treatment trial KW - smoking KW - message framing KW - recruitment N2 - Background: A cancer diagnosis can catalyze motivation to quit smoking. Tobacco treatment trials offer cessation resources but have low accrual rates. Digital outreach may improve accrual, but knowledge of how best to recruit smokers with recent diagnoses is limited. Objective: This study aims to identify the message frames that were most effective in promoting intent to talk to a physician about participating in a tobacco treatment trial for smokers recently diagnosed with cancer. Methods: From February to April 2019, current smokers diagnosed within the past 24 months were recruited from a national web-based panel for a multimethod pilot randomized trial (N=99). Participants were randomized to a 2×3 plus control factorial design that tested 3 unique message frames: proximal versus distal threats of smoking, costs of continued smoking versus benefits of quitting, and gains of participating versus losses of not participating in a tobacco treatment trial. The primary outcome was intent to talk to a physician about participating in a tobacco treatment trial. In phase 1, the main effect within each message factor level was examined using ANOVA and compared with the control condition. Other message evaluation and effectiveness measures were collected and explored in a multivariable model predicting intent to talk to a physician. In phase 2, open-text evaluations of the messages were analyzed using natural language processing software (Leximancer) to generate a thematic concept map and Linguistic Inquiry Word Count to identify and compare the prevalence of linguistic markers among message factors. Results: Of the 99 participants, 76 (77%) completed the intervention. Participants who received the cost of continued smoking frame were significantly more likely to intend to talk to their physician about participating in a tobacco treatment trial than those who received the benefits of the quitting frame (mean costs 5.13, SD 1.70 vs mean benefits 4.23, SD 1.86; P=.04). Participants who received the proximal risks of continued smoking frame were significantly more likely to seek more information about participating (mean distal 4.83, SD 1.61 vs mean proximal 5.55, SD 1.15; P=.04), and those who received the losses of not participating frame reported significantly improved perceptions of smoking cessation research (mean gain 3.98, SD 0.83 vs mean loss 4.38, SD 0.78; P=.01). Male participants (P=.006) and those with greater message relevancy (P=.001) were significantly more likely to intend to talk to their physician. Participants? perceptions of their smoking habits, as well as their motivation to quit smoking, were prevalent themes in the open-text data. Differences in the percentages of affective words across message frames were identified. Conclusions: Multimethod approaches are needed to develop evidence-based recruitment messages for patients recently diagnosed with cancer. Future tobacco treatment trials should evaluate the effectiveness of different message frames on smoker enrollment rates. Trial Registration: Clinicaltrials.gov NCT05471284; https://clinicaltrials.gov/ct2/show/NCT05471284 UR - https://cancer.jmir.org/2022/3/e37526 UR - http://dx.doi.org/10.2196/37526 UR - http://www.ncbi.nlm.nih.gov/pubmed/36001378 ID - info:doi/10.2196/37526 ER - TY - JOUR AU - Mangsbacka, Maria AU - Gustavell, Tina PY - 2022/5/16 TI - Nurses? Experiences Using an Interactive System to Assess and Manage Treatment-Related Symptoms of Patients With Pancreatic Cancer: Interview Study JO - JMIR Nursing SP - e36654 VL - 5 IS - 1 KW - app KW - health care professionals KW - mobile health KW - mHealth KW - nurses KW - pancreatic cancer KW - person-centered care KW - symptom-management KW - qualitative interview KW - nursing KW - interview N2 - Background: Treatment for pancreatic cancer entails symptom distress and a high burden of self-care. Patient-reported outcomes, collected with the support of mobile health (mHealth), have shown positive effects on symptom management, patient satisfaction, and quality of life for patients with cancer. For mHealth tools to become an integral part of clinical routine, experiences from health care professionals are needed. Objective: The aim of this paper is to describe nurses? experiences of integrating an interactive system (Interaktor) for symptom assessment and management into daily practice, when caring for patients following pancreaticoduodenectomy and during chemotherapy treatment due to pancreatic cancer. Methods: Patients reported symptoms via the Interaktor app daily for 6 months. In the event of alarming symptoms, an alert was triggered to the patient?s nurse who then called the patient to offer advice and support. All nurses (n=8) who assessed patients were interviewed either individually or in a group. Transcribed interviews were analyzed using qualitative thematic analysis. Results: mHealth can facilitate person-centered care by offering nurses a way to gain knowledge about patients and to build relationships. Further, obstacles to implementation could be seen due to a lack of structural prerequisites and uncertainty about multiple ways to interact with patients. Conclusions: The Interaktor system can provide person-centered care. However, to implement mHealth tools as a clinical routine, focus needs to be placed on creating the necessary organizational conditions. UR - https://nursing.jmir.org/2022/1/e36654 UR - http://dx.doi.org/10.2196/36654 UR - http://www.ncbi.nlm.nih.gov/pubmed/35576577 ID - info:doi/10.2196/36654 ER - TY - JOUR AU - Fu, Rosemary Mei AU - Axelrod, Deborah AU - Guth, A. Amber AU - Scagliola, Joan AU - Rampertaap, Kavita AU - El-Shammaa, Nardin AU - Qiu, M. Jeanna AU - McTernan, L. Melissa AU - Frye, Laura AU - Park, S. Christopher AU - Yu, Gary AU - Tilley, Charles AU - Wang, Yao PY - 2022/1/17 TI - A Web- and Mobile-Based Intervention for Women Treated for Breast Cancer to Manage Chronic Pain and Symptoms Related to Lymphedema: Results of a Randomized Clinical Trial JO - JMIR Cancer SP - e29485 VL - 8 IS - 1 KW - pain KW - lymphatic exercises KW - symptoms KW - lymphedema KW - breast cancer KW - health behavior KW - mHealth N2 - Background: The-Optimal-Lymph-Flow (TOLF) is a patient-centered, web- and mobile-based mHealth system that delivers safe, easy, and feasible digital therapy of lymphatic exercises and limb mobility exercises. Objective: The purpose of this randomized clinical trial (RCT) was to evaluate the effectiveness of the web- and mobile-based TOLF system for managing chronic pain and symptoms related to lymphedema. The primary outcome includes pain reduction, and the secondary outcomes focus on symptom relief, limb volume difference measured by infrared perometer, BMI, and quality of life (QOL) related to pain. We hypothesized that participants in the intervention group would have improved pain and symptom experiences, limb volume difference, BMI, and QOL. Methods: A parallel RCT with a control?experimental, pre- and posttest, and repeated-measures design were used. A total of 120 patients were recruited face-to-face at the point of care during clinical visits. Patients were randomized according to pain in a 1:1 ratio into either the arm precaution (AP) control group to improve limb mobility and arm protection or The-Optimal-Lymph flow (TOLF) intervention group to promote lymph flow and limb mobility. Trial outcomes were evaluated at baseline and at week 12 after the intervention. Descriptive statistics, Fisher exact tests, Wilcoxon rank-sum tests, t test, and generalized linear mixed effects models were performed for data analysis. Results: At the study endpoint of 12 weeks, significantly fewer patients in the TOLF intervention group compared with the AP control group reported chronic pain (45% [27/60] vs 70% [42/60]; odds ratio [OR] 0.39, 95% CI 0.17-0.90; P=.02). Patients who received the TOLF intervention were significantly more likely to achieve a complete reduction in pain (50% [23/46] vs 22% [11/51]; OR 3.56, 95% CI 1.39-9.76; P=.005) and soreness (43% [21/49] vs 22% [11/51]; OR 2.60, 95% CI 1.03-6.81; P=.03). Significantly lower median severity scores were found in the TOLF group for chronic pain (MedTOLF=0, IQR 0-1 vs MedAP=1, IQR 0-2; P=.02) and general bodily pain (MedTOLF=1, IQR=0-1.5 vs MedAP=1, IQR 1-3; P=.04). Compared with the AP control group, significantly fewer patients in the TOLF group reported arm/hand swelling (P=.04), heaviness (P=.03), redness (P=.03), and limited movement in shoulder (P=.02) and arm (P=.03). No significant differences between the TOLF and AP groups were found in complete reduction of aching (P=.12) and tenderness (P=.65), mean numbers of lymphedema symptom reported (P=.11), ?5% limb volume differences (P=.48), and BMI (P=.12). Conclusions: The TOLF intervention had significant benefits for breast cancer survivors to manage chronic pain, soreness, general bodily pain, arm/hand swelling, heaviness, and impaired limb mobility. The intervention resulted in a 13% reduction (from 40% [24/60] to 27% [16/60]) in proportions of patients who took pain medications compared with the AP control group, which had a 5% increase (from 40% [24/60] to 45% [27/60]). A 12% reduction (from 27% [16/60] to 15% [9/60]) in proportions of patients with ?5% limb volume differences was found in the TOLF intervention, while a 5% increase in the AP control group (from 40% [24/60] to 45% [27/60]) was found. In conclusion, the TOLF intervention can be a better choice for breast cancer survivors to reduce chronic pain and limb volume. Trial Registration: Clinicaltrials.gov NCT02462226; https://clinicaltrials.gov/ct2/show/NCT02462226 International Registered Report Identifier (IRRID): RR2-10.2196/resprot.5104 UR - https://cancer.jmir.org/2022/1/e29485 UR - http://dx.doi.org/10.2196/29485 UR - http://www.ncbi.nlm.nih.gov/pubmed/35037883 ID - info:doi/10.2196/29485 ER - TY - JOUR AU - Ye, Ye AU - Barapatre, Seemran AU - Davis, K. Michael AU - Elliston, O. Keith AU - Davatzikos, Christos AU - Fedorov, Andrey AU - Fillion-Robin, Jean-Christophe AU - Foster, Ian AU - Gilbertson, R. John AU - Lasso, Andras AU - Miller, V. James AU - Morgan, Martin AU - Pieper, Steve AU - Raumann, E. Brigitte AU - Sarachan, D. Brion AU - Savova, Guergana AU - Silverstein, C. Jonathan AU - Taylor, P. Donald AU - Zelnis, B. Joyce AU - Zhang, Guo-Qiang AU - Cuticchia, Jamie AU - Becich, J. Michael PY - 2021/12/2 TI - Open-source Software Sustainability Models: Initial White Paper From the Informatics Technology for Cancer Research Sustainability and Industry Partnership Working Group JO - J Med Internet Res SP - e20028 VL - 23 IS - 12 KW - open-source software KW - sustainability KW - licensing model KW - financial model KW - product management KW - cancer informatics N2 - 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. UR - https://www.jmir.org/2021/12/e20028 UR - http://dx.doi.org/10.2196/20028 UR - http://www.ncbi.nlm.nih.gov/pubmed/34860667 ID - info:doi/10.2196/20028 ER - TY - JOUR AU - AlShehry, Faiez Nawal AU - Shanker, Raja AU - Zaidi, Ahmed Syed Ziauddin AU - AlGhmlas, Fahad AU - Motabi, Hussein Ibraheem AU - Iqbal, Shahid AU - Butt, Ali Ahmad AU - AlShehri, Hassan AU - Tailor, Khan Imran AU - Altaf, Yasir Syed AU - AlGhamdi, Mubarak AU - Marie, Mohammed AU - AlFayez, Mansour AU - Al Zahrani, Kamal AU - Dwaimah, Mohammed AU - Al-Halouli, Tahani AU - Al-Shakweer, Wafaa AU - AlShehery, Zaher Maied AU - Zaidi, Zia Abdul Rehman AU - Gill, Munawar Atta AU - Albtoosh, Mohammed Belal AU - Ahmed, Musab PY - 2021/11/12 TI - Role of 18F-Fluorodeoxyglucose?Positron Emission Tomography/Computed Tomography Imaging in the Prediction of Prognosis in Patients With Indolent Lymphoma: Prospective Study JO - JMIR Form Res SP - e24936 VL - 5 IS - 11 KW - positron emission tomography KW - lymphoma KW - prognosis KW - indolent lymphoma KW - SUVmax KW - Deauville criteria N2 - Background: The role of fluorodeoxyglucose?positron emission tomography/computed tomography (FDG-PET/CT) in indolent lymphoma has been minimally studied. Objective: This study aims to assess the value of FDG-PET/CT in predicting the prognosis of indolent lymphoma. Methods: We prospectively recruited 42 patients with indolent lymphoma. A total of 2 patients were excluded, and 40 underwent baseline PET/CT and follow-up at various time points. A total of 9 patients were observed only, 7 received 4 doses of rituximab alone, and 24 received chemoimmunotherapy. Metabolic response on follow-up PET/CT was assessed using the maximum standardized uptake value (SUVmax) and Deauville criteria (DC). We aimed to obtain the best SUVmax and DC to predict optimal survival rates, risk stratification, and optimize therapeutic strategies. The mean follow-up from the initial diagnosis was 33.83 months. Results: SUVmax <4.35 at interim PET/CT provided the best discrimination, with a progression-free survival (PFS) of 100% and a median survival time of 106.67 months compared with SUVmax ?4.35 (P=.04), which had a PFS of 43.8% and a median survival time of 50.17 months. This cutoff was also valuable in predicting overall survival at baseline, that is, 100% overall survival with baseline SUVmax <4.35, versus 58.4% for SUVmax ?4.35 (P=.13). The overall survival of patients with a baseline DC score <3.0 was 100%, with a median overall survival of 106.67 months. Conclusions: We demonstrated the utility of PET/CT in indolent lymphomas. SUVmax (<4.35 vs ?4.35) on interim PET/CT performed best in predicting PFS. UR - https://formative.jmir.org/2021/11/e24936 UR - http://dx.doi.org/10.2196/24936 UR - http://www.ncbi.nlm.nih.gov/pubmed/34508363 ID - info:doi/10.2196/24936 ER - TY - JOUR AU - Marron, Manuela AU - Brackmann, Kim Lara AU - Schwarz, Heike AU - Hummel-Bartenschlager, Willempje AU - Zahnreich, Sebastian AU - Galetzka, Danuta AU - Schmitt, Iris AU - Grad, Christian AU - Drees, Philipp AU - Hopf, Johannes AU - Mirsch, Johanna AU - Scholz-Kreisel, Peter AU - Kaatsch, Peter AU - Poplawski, Alicia AU - Hess, Moritz AU - Binder, Harald AU - Hankeln, Thomas AU - Blettner, Maria AU - Schmidberger, Heinz PY - 2021/11/11 TI - Identification of Genetic Predispositions Related to Ionizing Radiation in Primary Human Skin Fibroblasts From Survivors of Childhood and Second Primary Cancer as Well as Cancer-Free Controls: Protocol for the Nested Case-Control Study KiKme JO - JMIR Res Protoc SP - e32395 VL - 10 IS - 11 KW - fibroblast KW - irradiation KW - childhood cancer KW - neoplasm KW - second primary neoplasm KW - second cancer KW - study design KW - participation KW - feasibility KW - cell line N2 - Background: Therapy for a first primary neoplasm (FPN) in childhood with high doses of ionizing radiation is an established risk factor for second primary neoplasms (SPN). An association between exposure to low doses and childhood cancer is also suggested; however, results are inconsistent. As only subgroups of children with FPNs develop SPNs, an interaction between radiation, genetic, and other risk factors is presumed to influence cancer development. Objective: Therefore, the population-based, nested case-control study KiKme aims to identify differences in genetic predisposition and radiation response between childhood cancer survivors with and without SPNs as well as cancer-free controls. Methods: We conducted a population-based, nested case-control study KiKme. Besides questionnaire information, skin biopsies and saliva samples are available. By measuring individual reactions to different exposures to radiation (eg, 0.05 and 2 Gray) in normal somatic cells of the same person, our design enables us to create several exposure scenarios for the same person simultaneously and measure several different molecular markers (eg, DNA, messenger RNA, long noncoding RNA, copy number variation). Results: Since 2013, 101 of 247 invited SPN patients, 340 of 1729 invited FPN patients, and 150 of 246 invited cancer-free controls were recruited and matched by age and sex. Childhood cancer patients were additionally matched by tumor morphology, year of diagnosis, and age at diagnosis. Participants reported on lifestyle, socioeconomical, and anthropometric factors, as well as on medical radiation history, health, and family history of diseases (n=556). Primary human fibroblasts from skin biopsies of the participants were cultivated (n=499) and cryopreserved (n=3886). DNA was extracted from fibroblasts (n=488) and saliva (n=510). Conclusions: This molecular-epidemiological study is the first to combine observational epidemiological research with standardized experimental components in primary human skin fibroblasts to identify genetic predispositions related to ionizing radiation in childhood and SPNs. In the future, fibroblasts of the participants will be used for standardized irradiation experiments, which will inform analysis of the case-control study and vice versa. Differences between participants will be identified using several molecular markers. With its innovative combination of experimental and observational components, this new study will provide valuable data to forward research on radiation-related risk factors in childhood cancer and SPNs. International Registered Report Identifier (IRRID): DERR1-10.2196/32395 UR - https://www.researchprotocols.org/2021/11/e32395 UR - http://dx.doi.org/10.2196/32395 UR - http://www.ncbi.nlm.nih.gov/pubmed/34762066 ID - info:doi/10.2196/32395 ER - TY - JOUR AU - Sadatmoosavi, Ali AU - Tajedini, Oranus AU - Esmaeili, Omid AU - Abolhasani Zadeh, Firouzeh AU - Khazaneha, Mahdiyeh PY - 2021/10/28 TI - Emerging Trends and Thematic Evolution of Breast Cancer: Knowledge Mapping and Co-Word Analysis JO - JMIR Cancer SP - e26691 VL - 7 IS - 4 KW - scientometrics KW - breast cancer KW - co-word analysis KW - Scimat KW - science mapping N2 - Background: One of the requirements for scientists and researchers to enter any field of science is to have a comprehensive and accurate understanding of that discipline. Objective: This study aims to draw a science map, provide structural analysis, explore the evolution, and determine new trends in research articles published in the field of breast cancer. Methods: This study comprised a descriptive survey with a scientometric approach. Data were collected from MEDLINE using a search strategy based on Medical Subject Heading (MeSH) terms. This study used science mapping, which provides a visual representation and a longitudinal evolution of possible interrelations between scientific areas, documents, or authors, thus reflecting the cognitive architecture of science mapping. For this scientometric evaluation of the topic of breast cancer research, a very long period was considered for data collection. Moreover, due to the availability of numerous publications in the database, the assessment was divided into three different periods ranging from 1988 to 2020. Results: A total of 12,577 records related to scientometric studies were extracted. The field of breast cancer research demonstrated three diagrams containing the most relevant themes for the three chronological periods evaluated. Each diagram was plotted based on the centrality and density linked to each research topic. The research output in the field was observed to revolve around 8 areas or themes: radiation injury, cardiovascular disease, fibroadenoma, antineoplastic agent, estrogen antagonistic, immunohistochemistry, soybean, and epitopes, each represented with different colors. Conclusions: In the strategic diagrams, the themes were both well developed and important for the structuring of a research field. The first quadrant comprised motor themes of the specialty, which present strong centrality and high density (eg, corticosteroid antineoplastic age, stem cell, T-lymphocyte, protein tyrosine kinase, dietary, and phosphatidyl inositol-3-kinase). In the second quadrant of diagram, themes have well-developed internal ties but unimportant external ties, as they are of only marginal importance for the field. These themes are very specialized and peripheral (eg, DNA-binding). In the third quadrant, themes are both weakly developed and marginal. The themes in this quadrant have low density and centrality and mainly represent either emerging or declining themes (eg, ovarian neoplasm). Themes in the fourth quadrant of the strategic diagram are considered important for a research field but are not fully developed. This quadrant contains transversal and general, basic themes (eg, immunohistochemistry). Scientometric analysis of breast cancer research can be regarded as a roadmap for future research and policymaking for this important field. UR - https://cancer.jmir.org/2021/4/e26691 UR - http://dx.doi.org/10.2196/26691 UR - http://www.ncbi.nlm.nih.gov/pubmed/34709188 ID - info:doi/10.2196/26691 ER - TY - JOUR AU - Aggarwal, Pushkar PY - 2021/10/12 TI - Performance of Artificial Intelligence Imaging Models in Detecting Dermatological Manifestations in Higher Fitzpatrick Skin Color Classifications JO - JMIR Dermatol SP - e31697 VL - 4 IS - 2 KW - deep learning KW - melanoma KW - basal cell carcinoma KW - skin of color KW - image recognition KW - dermatology KW - disease KW - convolutional neural network KW - specificity KW - prediction KW - artificial intelligence KW - skin color KW - skin tone N2 - Background: The performance of deep-learning image recognition models is below par when applied to images with Fitzpatrick classification skin types 4 and 5. Objective: The objective of this research was to assess whether image recognition models perform differently when differentiating between dermatological diseases in individuals with darker skin color (Fitzpatrick skin types 4 and 5) than when differentiating between the same dermatological diseases in Caucasians (Fitzpatrick skin types 1, 2, and 3) when both models are trained on the same number of images. Methods: Two image recognition models were trained, validated, and tested. The goal of each model was to differentiate between melanoma and basal cell carcinoma. Open-source images of melanoma and basal cell carcinoma were acquired from the Hellenic Dermatological Atlas, the Dermatology Atlas, the Interactive Dermatology Atlas, and DermNet NZ. Results: The image recognition models trained and validated on images with light skin color had higher sensitivity, specificity, positive predictive value, negative predictive value, and F1 score than the image recognition models trained and validated on images of skin of color for differentiation between melanoma and basal cell carcinoma. Conclusions: A higher number of images of dermatological diseases in individuals with darker skin color than images of dermatological diseases in individuals with light skin color would need to be gathered for artificial intelligence models to perform equally well. UR - https://derma.jmir.org/2021/2/e31697 UR - http://dx.doi.org/10.2196/31697 UR - http://www.ncbi.nlm.nih.gov/pubmed/37632853 ID - info:doi/10.2196/31697 ER - TY - JOUR AU - Naeim, Arash AU - Dry, Sarah AU - Elashoff, David AU - Xie, Zhuoer AU - Petruse, Antonia AU - Magyar, Clara AU - Johansen, Liliana AU - Werre, Gabriela AU - Lajonchere, Clara AU - Wenger, Neil PY - 2021/9/8 TI - Electronic Video Consent to Power Precision Health Research: A Pilot Cohort Study JO - JMIR Form Res SP - e29123 VL - 5 IS - 9 KW - biobanking KW - precision medicine KW - electronic consent KW - privacy KW - pilot study KW - video KW - consent KW - precision KW - innovation KW - efficient KW - cancer KW - education KW - barrier KW - engagement KW - participation N2 - 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. UR - https://formative.jmir.org/2021/9/e29123 UR - http://dx.doi.org/10.2196/29123 UR - http://www.ncbi.nlm.nih.gov/pubmed/34313247 ID - info:doi/10.2196/29123 ER - TY - JOUR AU - Chang, Panchun AU - Dang, Jun AU - Dai, Jianrong AU - Sun, Wenzheng PY - 2021/8/27 TI - Real-Time Respiratory Tumor Motion Prediction Based on a Temporal Convolutional Neural Network: Prediction Model Development Study JO - J Med Internet Res SP - e27235 VL - 23 IS - 8 KW - radiation therapy KW - temporal convolutional neural network KW - respiratory signal prediction KW - neural network KW - deep learning model KW - dynamic tracking N2 - Background: The dynamic tracking of tumors with radiation beams in radiation therapy requires the prediction of real-time target locations prior to beam delivery, as treatment involving radiation beams and gating tracking results in time latency. Objective: In this study, a deep learning model that was based on a temporal convolutional neural network was developed to predict internal target locations by using multiple external markers. Methods: Respiratory signals from 69 treatment fractions of 21 patients with cancer who were treated with the CyberKnife Synchrony device (Accuray Incorporated) were used to train and test the model. The reported model?s performance was evaluated by comparing the model to a long short-term memory model in terms of the root mean square errors (RMSEs) of real and predicted respiratory signals. The effect of the number of external markers was also investigated. Results: The average RMSEs of predicted (ahead time=400 ms) respiratory motion in the superior-inferior, anterior-posterior, and left-right directions and in 3D space were 0.49 mm, 0.28 mm, 0.25 mm, and 0.67 mm, respectively. Conclusions: The experiment results demonstrated that the temporal convolutional neural network?based respiratory prediction model could predict respiratory signals with submillimeter accuracy. UR - https://www.jmir.org/2021/8/e27235 UR - http://dx.doi.org/10.2196/27235 UR - http://www.ncbi.nlm.nih.gov/pubmed/34236336 ID - info:doi/10.2196/27235 ER - TY - JOUR AU - Glicksberg, Scott Benjamin AU - Burns, Shohei AU - Currie, Rob AU - Griffin, Ann AU - Wang, Jane Zhen AU - Haussler, David AU - Goldstein, Theodore AU - Collisson, Eric PY - 2020/3/20 TI - Blockchain-Authenticated Sharing of Genomic and Clinical Outcomes Data of Patients With Cancer: A Prospective Cohort Study JO - J Med Internet Res SP - e16810 VL - 22 IS - 3 KW - data sharing KW - electronic health records KW - genomics KW - medicine KW - blockchain KW - neoplasms N2 - Background: Efficiently sharing health data produced during standard care could dramatically accelerate progress in cancer treatments, but various barriers make this difficult. Not sharing these data to ensure patient privacy is at the cost of little to no learning from real-world data produced during cancer care. Furthermore, recent research has demonstrated a willingness of patients with cancer to share their treatment experiences to fuel research, despite potential risks to privacy. Objective: The objective of this study was to design, pilot, and release a decentralized, scalable, efficient, economical, and secure strategy for the dissemination of deidentified clinical and genomic data with a focus on late-stage cancer. Methods: We created and piloted a blockchain-authenticated system to enable secure sharing of deidentified patient data derived from standard of care imaging, genomic testing, and electronic health records (EHRs), called the Cancer Gene Trust (CGT). We prospectively consented and collected data for a pilot cohort (N=18), which we uploaded to the CGT. EHR data were extracted from both a hospital cancer registry and a common data model (CDM) format to identify optimal data extraction and dissemination practices. Specifically, we scored and compared the level of completeness between two EHR data extraction formats against the gold standard source documentation for patients with available data (n=17). Results: Although the total completeness scores were greater for the registry reports than those for the CDM, this difference was not statistically significant. We did find that some specific data fields, such as histology site, were better captured using the registry reports, which can be used to improve the continually adapting CDM. In terms of the overall pilot study, we found that CGT enables rapid integration of real-world data of patients with cancer in a more clinically useful time frame. We also developed an open-source Web application to allow users to seamlessly search, browse, explore, and download CGT data. Conclusions: Our pilot demonstrates the willingness of patients with cancer to participate in data sharing and how blockchain-enabled structures can maintain relationships between individual data elements while preserving patient privacy, empowering findings by third-party researchers and clinicians. We demonstrate the feasibility of CGT as a framework to share health data trapped in silos to further cancer research. Further studies to optimize data representation, stream, and integrity are required. UR - http://www.jmir.org/2020/3/e16810/ UR - http://dx.doi.org/10.2196/16810 UR - http://www.ncbi.nlm.nih.gov/pubmed/32196460 ID - info:doi/10.2196/16810 ER - TY - JOUR AU - Xu, Chenjie AU - Yang, Hongxi AU - Sun, Li AU - Cao, Xinxi AU - Hou, Yabing AU - Cai, Qiliang AU - Jia, Peng AU - Wang, Yaogang PY - 2020/3/12 TI - Detecting Lung Cancer Trends by Leveraging Real-World and Internet-Based Data: Infodemiology Study JO - J Med Internet Res SP - e16184 VL - 22 IS - 3 KW - lung cancer KW - incidence KW - mortality KW - internet searches KW - infodemiology N2 - Background: Internet search data on health-related terms can reflect people?s concerns about their health status in near real time, and hence serve as a supplementary metric of disease characteristics. However, studies using internet search data to monitor and predict chronic diseases at a geographically finer state-level scale are sparse. Objective: The aim of this study was to explore the associations of internet search volumes for lung cancer with published cancer incidence and mortality data in the United States. Methods: We used Google relative search volumes, which represent the search frequency of specific search terms in Google. We performed cross-sectional analyses of the original and disease metrics at both national and state levels. A smoothed time series of relative search volumes was created to eliminate the effects of irregular changes on the search frequencies and obtain the long-term trends of search volumes for lung cancer at both the national and state levels. We also performed analyses of decomposed Google relative search volume data and disease metrics at the national and state levels. Results: The monthly trends of lung cancer-related internet hits were consistent with the trends of reported lung cancer rates at the national level. Ohio had the highest frequency for lung cancer-related search terms. At the state level, the relative search volume was significantly correlated with lung cancer incidence rates in 42 states, with correlation coefficients ranging from 0.58 in Virginia to 0.94 in Oregon. Relative search volume was also significantly correlated with mortality in 47 states, with correlation coefficients ranging from 0.58 in Oklahoma to 0.94 in North Carolina. Both the incidence and mortality rates of lung cancer were correlated with decomposed relative search volumes in all states excluding Vermont. Conclusions: Internet search behaviors could reflect public awareness of lung cancer. Research on internet search behaviors could be a novel and timely approach to monitor and estimate the prevalence, incidence, and mortality rates of a broader range of cancers and even more health issues. UR - http://www.jmir.org/2020/3/e16184/ UR - http://dx.doi.org/10.2196/16184 UR - http://www.ncbi.nlm.nih.gov/pubmed/32163035 ID - info:doi/10.2196/16184 ER - TY - JOUR AU - Keaver, Laura AU - McGough, Aisling AU - Du, Mengxi AU - Chang, Winnie AU - Chomitz, Virginia AU - Allen, D. Jennifer AU - Attai, J. Deanna AU - Gualtieri, Lisa AU - Zhang, Fang Fang PY - 2019/5/28 TI - Potential of Using Twitter to Recruit Cancer Survivors and Their Willingness to Participate in Nutrition Research and Web-Based Interventions: A Cross-Sectional Study JO - JMIR Cancer SP - e7850 VL - 5 IS - 1 KW - social media KW - nutrition survey KW - cancer survivors N2 - Background: Social media is rapidly changing how cancer survivors search for and share health information and can potentially serve as a cost-effective channel to reach cancer survivors and invite them to participate in nutrition intervention programs. Objective: This study aimed to assess the feasibility of using Twitter to recruit cancer survivors for a web-based survey and assess their willingness to complete web-based nutrition surveys, donate biospecimens, and to be contacted about web-based nutrition programs. Methods: We contacted 301 Twitter accounts of cancer organizations, advocates, and survivors to request assistance promoting a web-based survey among cancer survivors. The survey asked respondents whether they would be willing to complete web-based nutrition or lifestyle surveys, donate biospecimens, and be contacted about web-based nutrition programs. Survey promotion rate was assessed by the percentage of Twitter accounts that tweeted the survey link at least once. Survey response was assessed by the number of survey respondents who answered at least 85% (26/30). We compared the characteristics of cancer survivors who responded to this survey with those who participated in the National Health and Nutrition Examination Survey (NHANES) 1999-2010 and evaluated factors associated with willingness to complete web-based surveys, donate biospecimens, and be contacted to participate in web-based nutrition programs among those who responded to the social media survey. Results: Over 10 weeks, 113 Twitter account owners and 165 of their followers promoted the survey, and 444 cancer survivors provided complete responses. Two-thirds of respondents indicated that they would be willing to complete web-based nutrition or lifestyle surveys (297/444, 67.0%) and to be contacted to participate in web-based nutrition interventions (294/444, 66.2%). The percentage of respondents willing to donate biospecimens were 59.3% (263/444) for oral swab, 52.1% (231/444) for urine sample, 37.9% (168/444) for blood sample, and 35.6% (158/444) for stool sample. Compared with a nationally representative sample of 1550 cancer survivors in NHANES, those who responded to the social media survey were younger (53.1 years vs 60.8 years; P<.001), more likely to be female (93.9% [417/444] vs 58.7% [909/1550]; P<.001), non-Hispanic whites (85.4% [379/444] vs 64.0% [992/1550]; P<.001), to have completed college or graduate school (30.1 [133/444] vs 19.9% [308/444]; P<.001), and to be within 5 years of their initial diagnosis (55.2% [244/444] vs 34.1% [528/1550]; P<.001). Survivors younger than 45 years, female, and non-Hispanic whites were more willing to complete web-based nutrition surveys than older (65+ years), male, and racial or ethnic minority survivors. Non-Hispanic whites and breast cancer survivors were more willing to donate biospecimens than those with other race, ethnicity or cancer types. Conclusions: Twitter could be a feasible approach to recruit cancer survivors into nutrition research and web-based interventions with potentially high yields. Specific efforts are needed to recruit survivors who are older, male, racial and ethnic minorities, and from socioeconomically disadvantaged groups when Twitter is used as a recruitment method. UR - http://cancer.jmir.org/2019/1/e7850/ UR - http://dx.doi.org/10.2196/cancer.7850 UR - http://www.ncbi.nlm.nih.gov/pubmed/31140436 ID - info:doi/10.2196/cancer.7850 ER - TY - JOUR AU - Furlong, Eileen AU - Darley, Andrew AU - Fox, Patricia AU - Buick, Alison AU - Kotronoulas, Grigorios AU - Miller, Morven AU - Flowerday, Adrian AU - Miaskowski, Christine AU - Patiraki, Elisabeth AU - Katsaragakis, Stylianos AU - Ream, Emma AU - Armes, Jo AU - Gaiger, Alexander AU - Berg, Geir AU - McCrone, Paul AU - Donnan, Peter AU - McCann, Lisa AU - Maguire, Roma PY - 2019/03/14 TI - Adaptation and Implementation of a Mobile Phone?Based Remote Symptom Monitoring System for People With Cancer in Europe JO - JMIR Cancer SP - e10813 VL - 5 IS - 1 KW - telemedicine KW - methods KW - patient care KW - cancer KW - symptom management N2 - Background: There has been an international shift in health care, which has seen an increasing focus and development of technological and personalized at-home interventions that aim to improve health outcomes and patient-clinician communication. However, there is a notable lack of empirical evidence describing the preparatory steps of adapting and implementing technology of this kind across multiple countries and clinical settings. Objective: This study aimed to describe the steps undertaken in the preparation of a multinational, multicenter randomized controlled trial (RCT) to test a mobile phone?based remote symptom monitoring system, that is, Advanced Symptom Management System (ASyMS), designed to enhance management of chemotherapy toxicities among people with cancer receiving adjuvant chemotherapy versus standard cancer center care. Methods: There were 13 cancer centers across 5 European countries (Austria, Greece, Ireland, Norway, and the United Kingdom). Multiple steps were undertaken, including a scoping review of empirical literature and clinical guidelines, translation and linguistic validation of study materials, development of standardized international care procedures, and the integration and evaluation of the technology within each cancer center. Results: The ASyMS was successfully implemented and deployed in clinical practices across 5 European countries. The rigorous and simultaneous steps undertaken by the research team highlighted the strengths of the system in clinical practice, as well as the clinical and technical changes required to meet the diverse needs of its intended users within each country, before the commencement of the RCT. Conclusions: Adapting and implementing this multinational, multicenter system required close attention to diverse considerations and unique challenges primarily related to communication and clinical and technical issues. Success was dependent on collaborative and transparent communication among academics, the technology industry, translation partners, patients, and clinicians as well as a simultaneous and rigorous methodological approach within the 5 relevant countries. UR - http://cancer.jmir.org/2019/1/e10813/ UR - http://dx.doi.org/10.2196/10813 UR - http://www.ncbi.nlm.nih.gov/pubmed/30869641 ID - info:doi/10.2196/10813 ER - TY - JOUR AU - Brinker, Josef Titus AU - Rudolph, Stefanie AU - Richter, Daniela AU - von Kalle, Christof PY - 2018/05/11 TI - Patient-Centered Mobile Health Data Management Solution for the German Health Care System (The DataBox Project) JO - JMIR Cancer SP - e10160 VL - 4 IS - 1 KW - medical informatics KW - health data management UR - http://cancer.jmir.org/2018/1/e10160/ UR - http://dx.doi.org/10.2196/10160 UR - http://www.ncbi.nlm.nih.gov/pubmed/29752255 ID - info:doi/10.2196/10160 ER - TY - JOUR AU - Jabour, M. Abdulrahman AU - Dixon, E. Brian AU - Jones, F. Josette AU - Haggstrom, A. David PY - 2018/03/01 TI - Toward Timely Data for Cancer Research: Assessment and Reengineering of the Cancer Reporting Process JO - JMIR Cancer SP - e4 VL - 4 IS - 1 KW - neoplasms KW - registries KW - SEER program KW - workflow KW - computer simulation KW - data collection KW - epidemiological monitoring N2 - Background: Cancer registries systematically collect cancer-related data to support cancer surveillance activities. However, cancer data are often unavailable for months to years after diagnosis, limiting its utility. Objective: The objective of this study was to identify the barriers to rapid cancer reporting and identify ways to shorten the turnaround time. Methods: Certified cancer registrars reporting to the Indiana State Department of Health cancer registry participated in a semistructured interview. Registrars were asked to describe the reporting process, estimate the duration of each step, and identify any barriers that may impact the reporting speed. Qualitative data analysis was performed with the intent of generating recommendations for workflow redesign. The existing and redesigned workflows were simulated for comparison. Results: Barriers to rapid reporting included access to medical records from multiple facilities and the waiting period from diagnosis to treatment. The redesigned workflow focused on facilitating data sharing between registrars and applying a more efficient queuing technique while registrars await the delivery of treatment. The simulation results demonstrated that our recommendations to reduce the waiting period and share information could potentially improve the average reporting speed by 87 days. Conclusions: Knowing the time elapsing at each step within the reporting process helps in prioritizing the needs and estimating the impact of future interventions. Where some previous studies focused on automating some of the cancer reporting activities, we anticipate much shorter reporting by leveraging health information technologies to target this waiting period. UR - http://cancer.jmir.org/2018/1/e4/ UR - http://dx.doi.org/10.2196/cancer.7515 UR - http://www.ncbi.nlm.nih.gov/pubmed/29496653 ID - info:doi/10.2196/cancer.7515 ER - TY - JOUR AU - Perez, P. Raymond AU - Finnigan, Shanda AU - Patel, Krupa AU - Whitney, Shanell AU - Forrest, Annemarie PY - 2016/12/15 TI - Clinical Trial Electronic Portals for Expedited Safety Reporting: Recommendations from the Clinical Trials Transformation Initiative Investigational New Drug Safety Advancement Project JO - JMIR Cancer SP - e16 VL - 2 IS - 2 KW - clinical trials KW - investigational new drug application KW - risk management N2 - Background: Use of electronic clinical trial portals has increased in recent years to assist with sponsor-investigator communication, safety reporting, and clinical trial management. Electronic portals can help reduce time and costs associated with processing paperwork and add security measures; however, there is a lack of information on clinical trial investigative staff?s perceived challenges and benefits of using portals. Objective: The Clinical Trials Transformation Initiative (CTTI) sought to (1) identify challenges to investigator receipt and management of investigational new drug (IND) safety reports at oncologic investigative sites and coordinating centers and (2) facilitate adoption of best practices for communicating and managing IND safety reports using electronic portals. Methods: CTTI, a public-private partnership to improve the conduct of clinical trials, distributed surveys and conducted interviews in an opinion-gathering effort to record investigator and research staff views on electronic portals in the context of the new safety reporting requirements described in the US Food and Drug Administration?s final rule (Code of Federal Regulations Title 21 Section 312). The project focused on receipt, management, and review of safety reports as opposed to the reporting of adverse events. Results: The top challenge investigators and staff identified in using individual sponsor portals was remembering several complex individual passwords to access each site. Also, certain tasks are time-consuming (eg, downloading reports) due to slow sites or difficulties associated with particular operating systems or software. To improve user experiences, respondents suggested that portals function independently of browsers and operating systems, have intuitive interfaces with easy navigation, and incorporate additional features that would allow users to filter, search, and batch safety reports. Conclusions: Results indicate that an ideal system for sharing expedited IND safety information is through a central portal used by all sponsors. Until this is feasible, electronic reporting portals should at least have consistent functionality. CTTI has issued recommendations to improve the quality and use of electronic portals. UR - http://cancer.jmir.org/2016/2/e16/ UR - http://dx.doi.org/10.2196/cancer.6701 UR - http://www.ncbi.nlm.nih.gov/pubmed/28410179 ID - info:doi/10.2196/cancer.6701 ER - TY - JOUR AU - Janssen, Anna AU - Robinson, Elizabeth Tracy AU - Provan, Pamela AU - Shaw, Tim PY - 2016/06/29 TI - The Sydney West Knowledge Portal: Evaluating the Growth of a Knowledge Portal to Support Translational Research JO - J Med Internet Res SP - e170 VL - 18 IS - 6 KW - knowledge management KW - web-based collaborative networks KW - translational research KW - cancer KW - capacity building KW - enabling factors N2 - Background: The Sydney West Translational Cancer Research Centre is an organization funded to build capacity for translational research in cancer. Translational research is essential for ensuring the integration of best available evidence into practice and for improving patient outcomes. However, there is a low level of awareness regarding what it is and how to conduct it optimally. One solution to addressing this gap is the design and deployment of web-based knowledge portals to disseminate new knowledge and engage with and connect dispersed networks of researchers. A knowledge portal is an web-based platform for increasing knowledge dissemination and management in a specialized area. Objective: To measure the design and growth of an web-based knowledge portal for increasing individual awareness of translational research and to build organizational capacity for the delivery of translational research projects in cancer. Methods: An adaptive methodology was used to capture the design and growth of an web-based knowledge portal in cancer. This involved stakeholder consultations to inform initial design of the portal. Once the portal was live, site analytics were reviewed to evaluate member usage of the portal and to measure growth in membership. Results: Knowledge portal membership grew consistently for the first 18 months after deployment, before leveling out. Analysis of site metrics revealed members were most likely to visit portal pages with community-generated content, particularly pages with a focus on translational research. This was closely followed by pages that disseminated educational material about translational research. Conclusions: Preliminary data from this study suggest that knowledge portals may be beneficial tools for translating new evidence and fostering an environment of communication and collaboration. UR - http://www.jmir.org/2016/6/e170/ UR - http://dx.doi.org/10.2196/jmir.5786 UR - http://www.ncbi.nlm.nih.gov/pubmed/27357641 ID - info:doi/10.2196/jmir.5786 ER - TY - JOUR AU - Mlikotic, Rebecca AU - Parker, Brent AU - Rajapakshe, Rasika PY - 2016/03/22 TI - Assessing the Effects of Participant Preference and Demographics in the Usage of Web-based Survey Questionnaires by Women Attending Screening Mammography in British Columbia JO - J Med Internet Res SP - e70 VL - 18 IS - 3 KW - patient preference KW - patient reported outcomes KW - patient reported outcome measures KW - questionnaires KW - Internet KW - Web-based system KW - survey methods KW - breast cancer screening N2 - Background: Increased usage of Internet applications has allowed for the collection of patient reported outcomes (PROs) and other health data through Web-based communication and questionnaires. While these Web platforms allow for increased speed and scope of communication delivery, there are certain limitations associated with this technology, as survey mode preferences vary across demographic groups. Objective: To investigate the impact of demographic factors and participant preferences on the use of a Web-based questionnaire in comparison with more traditional methods (mail and phone) for women participating in screening mammography in British Columbia, Canada. Methods: A sample of women attending the Screening Mammography Program of British Columbia (SMPBC) participated in a breast cancer risk assessment project. The study questionnaire was administered through one of three modes (ie, telephone, mail, or website platform). Survey mode preferences and actual methods of response were analyzed for participants recruited from Victoria General Hospital. Both univariate and multivariate analyses were used to investigate the association of demographic factors (ie, age, education level, and ethnicity) with certain survey response types. Results: A total of 1192 women successfully completed the study questionnaire at Victoria General Hospital. Mail was stated as the most preferred survey mode (509/1192, 42.70%), followed by website platform (422/1192, 35.40%), and telephone (147/1192, 12.33%). Over 80% (955/1192) of participants completed the questionnaire in the mode previously specified as their most preferred; mail was the most common method of response (688/1192, 57.72%). Mail was also the most preferred type of questionnaire response method when participants responded in a mode other than their original preference. The average age of participants who responded via the Web-based platform (age 52.9, 95% confidence interval [CI] 52.1-53.7) was significantly lower than those who used mail and telephone methods (age 55.9, 95% CI 55.2-56.5; P<.001); each decade of increased age was associated with a 0.97-fold decrease in the odds of using the website platform (P<.001). Web-based participation was more likely for those who completed higher levels of education; each interval increase leading to a 1.83 increase in the odds of website platform usage (P<.001). Ethnicity was not shown to play a role in participant preference for the website platform (P=.96). Conclusions: It is beneficial to consider participant survey mode preference when planning to collect PROs and other patient health data. Younger participants and those of higher education level were more likely to use the website platform questionnaire; Web-based participation failed to vary across ethnic group. Because mail questionnaires were still the most preferred survey mode, it will be important to employ strategies, such as user-friendly design and Web-based support, to ensure that the patient feedback being collected is representative of the population being served. UR - http://www.jmir.org/2016/3/e70/ UR - http://dx.doi.org/10.2196/jmir.5068 UR - http://www.ncbi.nlm.nih.gov/pubmed/27005707 ID - info:doi/10.2196/jmir.5068 ER - TY - JOUR AU - Kilsdonk, Ellen AU - van Dulmen-den Broeder, Eline AU - van der Pal, J. Helena AU - Hollema, Nynke AU - Kremer, C. Leontien AU - van den Heuvel-Eibrink, M. Marry AU - van Leeuwen, E. Flora AU - Jaspers, W. Monique AU - van den Berg, H. Marleen PY - 2015/11/24 TI - Effect of Web-Based Versus Paper-Based Questionnaires and Follow-Up Strategies on Participation Rates of Dutch Childhood Cancer Survivors: A Randomized Controlled Trial JO - JMIR Cancer SP - e11 VL - 1 IS - 2 KW - childhood cancer survivors KW - follow-up strategies KW - participation rates KW - questionnaires KW - questionnaire mode N2 - Background: Questionnaires are widely used in survey research, especially in cohort studies. However, participation in questionnaire studies has been declining over the past decades. Because high participation rates are needed to limit the risk of selection bias and produce valid results, it is important to investigate invitation strategies which may improve participation. Objectives: The purpose of this study is to investigate the effect of Web-based versus paper-based questionnaires on participation rates in a questionnaire survey on late effects among childhood cancer survivors (CCSs). Methods: A total of 750 CCSs were randomized across 3 study arms. The initial invitation in study arms 1 and 2 consisted of a Web-based questionnaire only, whereas in study arm 3 this invitation was complemented with a paper-based version of the questionnaire. The first postal reminder, sent to the nonresponding CCSs in all 3 study arms, consisted of either a reminder letter only (study arms 1 and 3) or a reminder letter complemented with a paper-based questionnaire (study arm 2). The second postal reminder was restricted to CCSs in study arms 1 and 2, with only those in study arm 1 also receiving a paper-based questionnaire. CCSs in study arm 3 received a second reminder by telephone instead of by mail. In contrast to CCSs in study arm 3, CCSs in study arms 1 and 2 received a third reminder, this time by telephone. Results: Overall, 58.1% (436/750) of the CCSs participated in the survey. Participation rates were equal in all 3 study arms with 57.4% (143/249) in arm 1, 60.6% (152/251) in arm 2, and 56.4% (141/250) in arm 3 (P=.09). Participation rates of CCSs who received an initial invitation for the Web-based questionnaire only and CCSs who received an invitation to complete either a paper-based or Web-based questionnaire did not differ (P=.55). After the first postal reminder, participation rates of CCSs invited for the Web-based questionnaire only also did not differ compared with CCSs invited for both the Web-based and paper-based questionnaires (P=.48). In general, CCSs preferred the paper-based over the Web-based questionnaire, and those completing the paper-based questionnaire were more often unemployed (P=.004) and lower educated (P<.001). Conclusion: Invitation strategies offering a Web-based questionnaire without a paper-based alternative at first invitation can be used without compromising participation rates of CCS. Offering the choice between paper- and Web-based questionnaires seems to result in the highest accrual participation rate. Future research should look into the quality of the data delivered by both questionnaires filled in by respondents themselves. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): 84711754; http://www.controlled-trials.com/ISRCTN84711754 (Archived by WebCite at http://www.webcitation.org/6c9ZB8paX) UR - http://cancer.jmir.org/2015/2/e11/ UR - http://dx.doi.org/10.2196/cancer.3905 UR - http://www.ncbi.nlm.nih.gov/pubmed/28410161 ID - info:doi/10.2196/cancer.3905 ER -