JMIR Cancer

Cancer imposes significant physical and emotional distress not only on patients but also on their caregivers. In recent years, there has been a growing focus on the mental and physical well-being of caregivers. Among various psychological interventions, cognitive behavioral therapy (CBT) is widely recognized as one of the most effective approaches. However, traditional CBT is often limited by time and geographical constraints, resulting in delayed or inefficient support for caregivers. Internet-based cognitive behavioral therapy (ICBT) presents a valuable alternative for alleviating the caregiving burden and the negative emotions experienced by caregivers.

Despite its potential to predict and detect early cancer risks, genetic testing remains underutilized by the public. This study, guided by the Health Belief Model, examined key factors influencing an individual’s willingness to undergo genetic testing for cancer, with a particular focus on gender, caregiver status, and participation in online social support groups.

Due to multifaceted outpatient regiments, children receiving hematopoietic stem cell transplant (HCT) are at high risk of medication non-adherence, leading to life-threatening complications. mHealth interventions have proven effective in improving adherence in various pediatric conditions, however adherence intervention literature on HCT is limited.

Defining optimal adjuvant therapeutic strategies for elderly breast cancer patients remains a challenge, given that this population is often overlooked and underserved in clinical research and decision-making tools.

Brain tumours are characterised by high burden of disease that profoundly impact quality of life in patients and their families. Digital health tools hold tremendous potential to enhance supportive care and quality of life for patients with brain tumours and their carers.

Generative AI Chatbots may be useful tools for supporting shared prostate cancer screening decisions, but the information produced by these tools sometimes lack quality or credibility. ‘Prostate Cancer Info’ is a custom GPT chatbot developed to provide plain-language PrCA information only from websites of key authorities on cancer and peer-reviewed literature.

Progression-free survival (PFS) is a crucial endpoint in cancer drug research. The clinician-confirmed cancer progression, namely real-world PFS (rwPFS) in unstructured text (i.e. clinical notes) has been shown to serve as a reasonable surrogate for real-world indicators in ascertaining progression endpoints. Response Evaluation Criteria in Solid Tumors(RECIST) is traditionally used in clinical trials using serial imaging evaluations, which is not practical when working with real-world data. Manual abstraction of clinical progression from unstructured notes continues to be the gold standard. However, this process is a resource-intensive and time-consuming process. Natural Language processing(NLP), a subdomain of machine learning, has shown promise in accelerating the extraction of tumor progression from real world data in recent years.

Artificial intelligence (AI) is a revolutionary upcoming tool yet to be fully integrated into several healthcare sectors, including medical imaging. AI can transform how medical imaging is conducted and interpreted, especially in cardio-oncology.

Relapse is a major event in lymphoma patients. Therefore, early detection may have an impact on quality of life and overall survival. Patient-related outcome measures have demonstrated clinical benefits for patients with lung cancer; however, evidence is lacking in patients with lymphoma. We evaluated the effect of a web-mediated follow-up application for lymphoma patients at high risk of relapse.

Multidisciplinary team (MDT) meetings play a critical role in cancer care by fostering collaboration between different healthcare professionals to develop optimal treatment recommendations. However, meeting scheduling and coordination rely heavily on manual work, making information-sharing and integration challenging. This results in incomplete information, affecting decision-making efficiency and impacting the progress of MDT. This project aimed to optimize and digitize the MDT workflow by interviewing the members of an MDT and implementing an integrated information platform utilizing the Fast Healthcare Interoperability Resources (FHIR) standard. MDT process re-engineering was conducted at a central Taiwan medical center. To digitize the workflow, our hospital adopted the NAVIFY® Tumor Board (NTB), a cloud-based platform integrating medical data using international standards, including logical object identifiers, names, and codes (LOINC), systemized nomenclature of medicine – clinical terms (SNOMED-CT), M-code, and FHIR. We improved our hospital’s information system using application programming interfaces (APIs) to consolidate data from various systems, excluding sensitive cases. Using FHIR, we aggregated, analyzed, and converted the data for seamless integration. Utilizing a user experience design, we gained insights into the lung cancer MDT's processes and needs. We conducted two phases: pre- and post-NTB integration. Ethnographic observations and stakeholder interviews revealed pain points. The affinity diagram method categorized the pain points during the discussion process, leading to efficient solutions. We divided the observation period into two phases: before and after integrating the NTB with the hospital information system (HIS). In Phase 1, there were 83 steps across the six MDT activities, leading to inefficiencies and potential delays in patient care. In Phase 2, we streamlined the tumor board process into 33 steps by introducing new functions and optimizing the data entry for pathologists. We converted the related medical data to the FHIR format using six FHIR resources and improved our HIS by developing functions and APIs to interoperate among various systems; consolidating data from different sources, excluding sensitive cases; and enhancing overall system efficiency. The MDT workflow reduced steps by 67.65%, lowering the coordinated activity time from 30 to 5 minutes. Improved efficiency boosted productivity and coordination in each case of manager feedback. This study optimized and digitized the workflow of MDT meetings, significantly enhancing the efficiency and accuracy of the tumor board process to benefit both medical professionals and patients. Based on FHIR, we integrated the data scattered across different information systems in our hospital and established a system interoperability interface that conformed to the standard. While digitizing the work of MDT meetings, we also promoted the optimization and transformation of related information systems and improved their service quality. We recommend additional research to assess the usability of a tumor board platform.

Cancer is a life-threatening disease and a leading cause of death worldwide, with an estimated 611,000 deaths and over 2 million new cases in the United States in 2024. The rising incidence of major cancers, including among younger individuals, highlights the need for early screening and monitoring of risk factors to manage and decrease cancer risk.

Melanoma currently ranks as the fifth leading cancer diagnosis and is projected to become the second most common cancer in the United States by 2040. Melanoma detected at earlier stages may be treated with less-risky and less-costly therapeutic options.