Theres Fey, Nicole Thurner, Ulrike Haidn, Friederike Mumm, Birgit Haberland, Rachel Wuerstlein, Sebastian Theurich, Georg Wolfrum, Marie-Louise Troidl, Susan Müller, Claudia Bausewein, Timo Schinköthe, Volker Heinemann, Nicole Erickson
Background: Digital patient-reported outcome (ePRO) tools have the potential to enhance supportive care in oncology and support timely and accurate identification of patients' needs.
Objective: This study aimed to develop, implement, and evaluate a user‑friendly, web‑based digital screening tool at a German Comprehensive Cancer Center (CCC) that systematically and efficiently assesses cancer patients' supportive care needs and enables direct referral to appropriate supportive services through seamless integration with the hospital information system.
Methods: An interdisciplinary team collaborated with the Information Technology (IT) department and the company CANKADO, an ePRO provider, to create a 14-item digital questionnaire. The tool incorporated validated instruments, such as the Distress Thermometer, the Nutrition Risk Screening (NRS), and a short form of the Integrated Palliative care Outcome Scale (IPOS), aligned with German Cancer Society certification criteria. Patients accessed the questionnaire via Quick Response (QR) codes. Screening results were automatically transferred to the HIS, where supportive care requests (SCRs) were generated automatically if indicated.
Results: Between June 2024 and May 2025, a total of 8,855 QR codes were generated. 4,909 of the questionnaires were complete and valid for analysis. This information produced 3,324 SCRs. Digital screenings resulted in a SCR in 22.4 % of cases for psycho-oncology, 18.7 % for nutrition, and 27.6 % for palliative care. The digital screening maintained or slightly improved screening rates compared to prior methods.
Conclusions: The implementation of a digital supportive care screening was feasible and effective within the CCC setting. Future efforts focus on overcoming barriers for patients with limited digital access or capabilities to ensure delivery of equitable supportive care delivery.
{"title":"Scan, Screen, Support - A Digital Pathway to Assess Supportive Care Needs in Oncology: An Implementation Study.","authors":"Theres Fey, Nicole Thurner, Ulrike Haidn, Friederike Mumm, Birgit Haberland, Rachel Wuerstlein, Sebastian Theurich, Georg Wolfrum, Marie-Louise Troidl, Susan Müller, Claudia Bausewein, Timo Schinköthe, Volker Heinemann, Nicole Erickson","doi":"10.2196/82392","DOIUrl":"https://doi.org/10.2196/82392","url":null,"abstract":"<p><strong>Background: </strong>Digital patient-reported outcome (ePRO) tools have the potential to enhance supportive care in oncology and support timely and accurate identification of patients' needs.</p><p><strong>Objective: </strong>This study aimed to develop, implement, and evaluate a user‑friendly, web‑based digital screening tool at a German Comprehensive Cancer Center (CCC) that systematically and efficiently assesses cancer patients' supportive care needs and enables direct referral to appropriate supportive services through seamless integration with the hospital information system.</p><p><strong>Methods: </strong>An interdisciplinary team collaborated with the Information Technology (IT) department and the company CANKADO, an ePRO provider, to create a 14-item digital questionnaire. The tool incorporated validated instruments, such as the Distress Thermometer, the Nutrition Risk Screening (NRS), and a short form of the Integrated Palliative care Outcome Scale (IPOS), aligned with German Cancer Society certification criteria. Patients accessed the questionnaire via Quick Response (QR) codes. Screening results were automatically transferred to the HIS, where supportive care requests (SCRs) were generated automatically if indicated.</p><p><strong>Results: </strong>Between June 2024 and May 2025, a total of 8,855 QR codes were generated. 4,909 of the questionnaires were complete and valid for analysis. This information produced 3,324 SCRs. Digital screenings resulted in a SCR in 22.4 % of cases for psycho-oncology, 18.7 % for nutrition, and 27.6 % for palliative care. The digital screening maintained or slightly improved screening rates compared to prior methods.</p><p><strong>Conclusions: </strong>The implementation of a digital supportive care screening was feasible and effective within the CCC setting. Future efforts focus on overcoming barriers for patients with limited digital access or capabilities to ensure delivery of equitable supportive care delivery.</p>","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":" ","pages":""},"PeriodicalIF":2.7,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146167227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Javier De La Hoz-M, Karime Montes-Escobar, Carlos Alfredo Salas-Macias, Martha Fors, Santiago J Ballaz
<p><strong>Background: </strong>Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major factors include smoking, obesity, and hypertension, though its etiology is uncertain. While surgery is effective for localized RCC, treatments for metastatic RCC have advanced significantly due to better diagnostic, prognostic, and predictive tools. Despite this progress, challenges remain, including long-term drug resistance and the complexity of RCC as a diverse group of diseases rather than a single entity.</p><p><strong>Objective: </strong>The aim of this bibliometric review was a comprehensive analysis of the topics and trends in RCC research, offering a foundation for future investigations.</p><p><strong>Methods: </strong>We used R "Bibliometrix" to conduct a bibliographic search in Scopus and PubMed covering publications from 1975 to 2023 to statistically assess the distribution of publications associated with RCC by year, journal, and country. Topic modeling of RCC research was conducted using latent Dirichlet allocation, a Bayesian network-based probabilistic algorithm that identifies unobserved thematic clusters in a collection of text documents. Trends in the retrieved themes were then characterized by using regression slopes over time, across countries, and in different journals. These trends were visualized as a heatmap, which was then used for hierarchical clustering to group similar topics based on their correlation strengths.</p><p><strong>Results: </strong>A total of 35,228 documents from 3070 sources were found, with a steady yearly growth of 9.86% and 118 participating countries. Thirty topics with the best coherence score were found in 8 crucial domains: treatment and therapies, biomolecular and genetic characteristics, disease characteristics and progression, diagnosis and evaluation, metastasis and dissemination, epidemiology and risk factors, related conditions, and pathological features. The pertinent clustergrams that resulted from the heatmaps mirrored the latent Dirichlet allocation's algorithm identification of major RCC research subjects.</p><p><strong>Conclusions: </strong>Over 50 years, RCC research's focus has shifted from diagnosis and assessment to a more thorough understanding of disease characteristics and progression. Because many patients are diagnosed with abdominal imaging studies, an emerging topic in RCC is diagnostic imaging and radiological evolution. The advances in omics technologies and the function of microRNA signature in the progression, diagnosis, therapy targeting, and prognosis of RCC have garnered a lot of attention. The discovery of the genetic background has enhanced our understanding of the growth of RCC. Drug resistance, local RCC ablation, and postoperative surveillance of RCC recurrence following nephrectomy are key future research avenues. The next generation of drug-targeted therapy and immunotherapy will make it poss
{"title":"Using Latent Dirichlet Allocation Topic Modeling to Uncover Latent Research Topics and Trends in Renal Cell Carcinoma: Bibliometric Review.","authors":"Javier De La Hoz-M, Karime Montes-Escobar, Carlos Alfredo Salas-Macias, Martha Fors, Santiago J Ballaz","doi":"10.2196/78797","DOIUrl":"10.2196/78797","url":null,"abstract":"<p><strong>Background: </strong>Renal cell carcinoma (RCC) is a common, often lethal kidney cancer that originates in the renal cortex. Its incidence is rising, and major factors include smoking, obesity, and hypertension, though its etiology is uncertain. While surgery is effective for localized RCC, treatments for metastatic RCC have advanced significantly due to better diagnostic, prognostic, and predictive tools. Despite this progress, challenges remain, including long-term drug resistance and the complexity of RCC as a diverse group of diseases rather than a single entity.</p><p><strong>Objective: </strong>The aim of this bibliometric review was a comprehensive analysis of the topics and trends in RCC research, offering a foundation for future investigations.</p><p><strong>Methods: </strong>We used R \"Bibliometrix\" to conduct a bibliographic search in Scopus and PubMed covering publications from 1975 to 2023 to statistically assess the distribution of publications associated with RCC by year, journal, and country. Topic modeling of RCC research was conducted using latent Dirichlet allocation, a Bayesian network-based probabilistic algorithm that identifies unobserved thematic clusters in a collection of text documents. Trends in the retrieved themes were then characterized by using regression slopes over time, across countries, and in different journals. These trends were visualized as a heatmap, which was then used for hierarchical clustering to group similar topics based on their correlation strengths.</p><p><strong>Results: </strong>A total of 35,228 documents from 3070 sources were found, with a steady yearly growth of 9.86% and 118 participating countries. Thirty topics with the best coherence score were found in 8 crucial domains: treatment and therapies, biomolecular and genetic characteristics, disease characteristics and progression, diagnosis and evaluation, metastasis and dissemination, epidemiology and risk factors, related conditions, and pathological features. The pertinent clustergrams that resulted from the heatmaps mirrored the latent Dirichlet allocation's algorithm identification of major RCC research subjects.</p><p><strong>Conclusions: </strong>Over 50 years, RCC research's focus has shifted from diagnosis and assessment to a more thorough understanding of disease characteristics and progression. Because many patients are diagnosed with abdominal imaging studies, an emerging topic in RCC is diagnostic imaging and radiological evolution. The advances in omics technologies and the function of microRNA signature in the progression, diagnosis, therapy targeting, and prognosis of RCC have garnered a lot of attention. The discovery of the genetic background has enhanced our understanding of the growth of RCC. Drug resistance, local RCC ablation, and postoperative surveillance of RCC recurrence following nephrectomy are key future research avenues. The next generation of drug-targeted therapy and immunotherapy will make it poss","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e78797"},"PeriodicalIF":2.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12810951/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145991362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karolina L Bryl, Sierra Silverwood, Krupali Desai, Kelsey Schobert, Xiaotong Li, Susan Chimonas, Jun J Mao, Erin F Gillespie
Background: Individuals undergoing cancer treatment often face a high symptom burden that impairs quality of life. Exercise and mind-body therapies have been shown to reduce symptoms but are underused. We developed a digital exercise and mind-body therapy program that effectively reduces symptoms while overcoming in-person delivery barriers. Understanding patient experiences can inform treatment mechanisms and guide digital health interventions in cancer care.
Objective: This study aimed to explore patient experiences with Integrative Medicine at Home (IM@Home), a 12-week live digital program delivering exercise and mind-body therapies tailored to the needs of individuals undergoing cancer treatment.
Methods: This qualitative study was embedded in a randomized clinical basket trial (NCT05053230) evaluating the effects of IM@Home versus enhanced usual care on symptoms and acute health care utilization in adults with solid tumors undergoing active treatment and experiencing moderate or greater fatigue. Using maximum variation sampling, 20 participants were selected for semistructured interviews. Interviews explored participants' experiences with the program, its impact on outcomes, unmet needs, and suggestions for improvement. Transcripts were analyzed using a combined inductive and deductive thematic analysis.
Results: Twenty participants (mean age 63, SD 9.6 years; 18/20, 90% female) were interviewed. Five major themes emerged: (1) IM@Home alleviated symptom burden and supported symptom self-management; (2) IM@Home facilitated social support and information exchange; (3) IM@Home offered a flexible, tailored program in a group setting; (4) IM@Home facilitated accessible, cost-effective support; and (5) recommendations for program enhancement. IM@Home was perceived as an accessible, flexible, and supportive program that promoted physical and emotional well-being during treatment.
Conclusions: IM@Home demonstrates a promising model for delivering integrative supportive care during cancer treatment. Findings highlight patient-valued features such as real-time guidance, tailored content, and community support. These insights can inform future implementation, integration into clinical care, and efforts to enhance digital mind-body interventions in oncology.
{"title":"Benefits and Challenges of a Digital Exercise and Mind-Body Program During Active Cancer Treatment: Qualitative Study of Patients' Perceptions.","authors":"Karolina L Bryl, Sierra Silverwood, Krupali Desai, Kelsey Schobert, Xiaotong Li, Susan Chimonas, Jun J Mao, Erin F Gillespie","doi":"10.2196/80075","DOIUrl":"10.2196/80075","url":null,"abstract":"<p><strong>Background: </strong>Individuals undergoing cancer treatment often face a high symptom burden that impairs quality of life. Exercise and mind-body therapies have been shown to reduce symptoms but are underused. We developed a digital exercise and mind-body therapy program that effectively reduces symptoms while overcoming in-person delivery barriers. Understanding patient experiences can inform treatment mechanisms and guide digital health interventions in cancer care.</p><p><strong>Objective: </strong>This study aimed to explore patient experiences with Integrative Medicine at Home (IM@Home), a 12-week live digital program delivering exercise and mind-body therapies tailored to the needs of individuals undergoing cancer treatment.</p><p><strong>Methods: </strong>This qualitative study was embedded in a randomized clinical basket trial (NCT05053230) evaluating the effects of IM@Home versus enhanced usual care on symptoms and acute health care utilization in adults with solid tumors undergoing active treatment and experiencing moderate or greater fatigue. Using maximum variation sampling, 20 participants were selected for semistructured interviews. Interviews explored participants' experiences with the program, its impact on outcomes, unmet needs, and suggestions for improvement. Transcripts were analyzed using a combined inductive and deductive thematic analysis.</p><p><strong>Results: </strong>Twenty participants (mean age 63, SD 9.6 years; 18/20, 90% female) were interviewed. Five major themes emerged: (1) IM@Home alleviated symptom burden and supported symptom self-management; (2) IM@Home facilitated social support and information exchange; (3) IM@Home offered a flexible, tailored program in a group setting; (4) IM@Home facilitated accessible, cost-effective support; and (5) recommendations for program enhancement. IM@Home was perceived as an accessible, flexible, and supportive program that promoted physical and emotional well-being during treatment.</p><p><strong>Conclusions: </strong>IM@Home demonstrates a promising model for delivering integrative supportive care during cancer treatment. Findings highlight patient-valued features such as real-time guidance, tailored content, and community support. These insights can inform future implementation, integration into clinical care, and efforts to enhance digital mind-body interventions in oncology.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov NCT05053230; https://www.clinicaltrials.gov/study/NCT05053230.</p><p><strong>International registered report identifier (irrid): </strong>RR2-10.1038/s41746-024-01387-z.</p>","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e80075"},"PeriodicalIF":2.7,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12859541/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145991391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Saif Khairat, Erin E Kent, John Geracitano, Kaushalya Mendis, Zhaoqiang Zhou, Carly Bailey, William A Wood
<p><strong>Background: </strong>Cancer survivors face significant challenges in maintaining adequate physical activity levels, which are essential for overall health and quality of life. Telehealth-based interventions offer promising opportunities to provide accessible support and promote healthier lifestyles throughout the cancer survivorship continuum. HealthScore is a telehealth coaching program designed to optimize the health of cancer survivors.</p><p><strong>Objective: </strong>This study assessed the effectiveness of HealthScore in improving physical activity metrics among cancer survivors compared to controls. We also evaluated participants' qualitative experiences with the program to understand its impact on motivation, accountability, and overall health-related quality of life.</p><p><strong>Methods: </strong>We performed a secondary analysis of a randomized controlled study of cancer survivors who participated in a comprehensive health coaching intervention called HealthScore. Participants in control and intervention groups received a Fitbit activity tracker that collected heart rate, step counts, active minutes, and calories burned. These metrics were analyzed using statistical methods to compare overall averages and temporal trends between intervention and control groups. Eleven exit interviews were conducted with intervention arm participants to ascertain their experiences with HealthScore. Inductive thematic analysis was performed to identify emerging themes. Data were collected between May 2020 and March 2022.</p><p><strong>Results: </strong>Of the 32 participants enrolled, 20 (62%) were in the intervention group. Compared to the control group, intervention participants had significantly higher average daily steps (mean 3660, SD 3344; 95% CI 3557-3764 vs mean 3408, SD 3288; 95% CI 3299-3518; P=.001) and more moving average daily steps (mean 4813, SD 1723; 95% CI 4680-4946 vs mean 4581, SD 1224; 95% CI 4494-4669; P=.003). Moving average daily step counts in the intervention arm showed an increasing trend, which was significantly higher than that of the control group (regression slope=5.89 vs 2.80; P<.001). Compared to the control group, the intervention participants had significantly higher average daily walking distance (mean 2.6, SD 2.5; 95% CI 2.5-2.7 vs mean 2.4, SD 2.3; 95% CI 2.3-2.5; P<.001) and more moving average daily walking distance (mean 3.5, SD 1.3; 95% CI 3.4-3.6 vs mean 3.2, SD 0.8; 95% CI 3.1-3.3; P<.001). Moving average daily walking distances among intervention participants increased, which was also significantly higher than that of the control group (regression slope=0.0046 vs 0.0017; P<.001). Participants in the intervention group reported a growing sense of accountability and motivation. One barrier was completing weekly monitoring of patient-reported outcome surveys, which focused on symptoms and physical function and did not always align with participants' goals.</p><p><strong>Conclusions: </strong>The Healt
背景：癌症幸存者在保持足够的身体活动水平方面面临着重大挑战，这对整体健康和生活质量至关重要。基于远程保健的干预措施为在整个癌症生存过程中提供可获得的支持和促进更健康的生活方式提供了有希望的机会。HealthScore是一个远程医疗指导项目，旨在优化癌症幸存者的健康状况。目的：本研究评估了与对照组相比，健康评分在改善癌症幸存者身体活动指标方面的有效性。我们还评估了参与者对该计划的定性体验，以了解其对动机、责任和总体健康相关生活质量的影响。方法：我们对一项随机对照研究进行了二次分析，这些研究对象是参加了名为HealthScore的综合健康指导干预的癌症幸存者。对照组和干预组的参与者都收到了Fitbit活动追踪器，可以收集心率、步数、活动时间和卡路里消耗。使用统计方法对这些指标进行分析，以比较干预组和对照组之间的总体平均值和时间趋势。对干预组参与者进行了11次退出访谈，以确定他们对健康评分的体验。进行归纳主题分析以确定新兴主题。数据收集于2020年5月至2022年3月。结果：32名参与者中，20名（62%）在干预组。与对照组相比，干预组参与者的平均每日步数显著增加（平均3660，SD 3344； 95% CI 3557-3764 vs平均3408，SD 3288; 95% CI 3299-3518； P= 0.001），移动平均每日步数更多（平均4813，SD 1723； 95% CI 4680-4946 vs平均4581，SD 1224; 95% CI 4494-4669； P= 0.003）。干预组的移动平均每日步数呈增加趋势，显著高于对照组（回归斜率=5.89 vs 2.80）。结论：HealthScore远程医疗指导项目提高了癌症幸存者的身体活动水平，增强了他们的积极性和责任感。这些发现支持将基于远程保健的健康指导纳入治疗后护理，促进癌症幸存者更健康的生活方式和改善生活质量。试验注册：ClinicalTrials.gov NCT04923997；https://clinicaltrials.gov/study/NCT04923997。
{"title":"Efficacy of Telehealth-Based Coaching to Improve Physical Activity and Overall Experience for Cancer Survivors: Secondary, Mixed Methods Analysis of a Randomized Controlled Trial.","authors":"Saif Khairat, Erin E Kent, John Geracitano, Kaushalya Mendis, Zhaoqiang Zhou, Carly Bailey, William A Wood","doi":"10.2196/78968","DOIUrl":"10.2196/78968","url":null,"abstract":"<p><strong>Background: </strong>Cancer survivors face significant challenges in maintaining adequate physical activity levels, which are essential for overall health and quality of life. Telehealth-based interventions offer promising opportunities to provide accessible support and promote healthier lifestyles throughout the cancer survivorship continuum. HealthScore is a telehealth coaching program designed to optimize the health of cancer survivors.</p><p><strong>Objective: </strong>This study assessed the effectiveness of HealthScore in improving physical activity metrics among cancer survivors compared to controls. We also evaluated participants' qualitative experiences with the program to understand its impact on motivation, accountability, and overall health-related quality of life.</p><p><strong>Methods: </strong>We performed a secondary analysis of a randomized controlled study of cancer survivors who participated in a comprehensive health coaching intervention called HealthScore. Participants in control and intervention groups received a Fitbit activity tracker that collected heart rate, step counts, active minutes, and calories burned. These metrics were analyzed using statistical methods to compare overall averages and temporal trends between intervention and control groups. Eleven exit interviews were conducted with intervention arm participants to ascertain their experiences with HealthScore. Inductive thematic analysis was performed to identify emerging themes. Data were collected between May 2020 and March 2022.</p><p><strong>Results: </strong>Of the 32 participants enrolled, 20 (62%) were in the intervention group. Compared to the control group, intervention participants had significantly higher average daily steps (mean 3660, SD 3344; 95% CI 3557-3764 vs mean 3408, SD 3288; 95% CI 3299-3518; P=.001) and more moving average daily steps (mean 4813, SD 1723; 95% CI 4680-4946 vs mean 4581, SD 1224; 95% CI 4494-4669; P=.003). Moving average daily step counts in the intervention arm showed an increasing trend, which was significantly higher than that of the control group (regression slope=5.89 vs 2.80; P<.001). Compared to the control group, the intervention participants had significantly higher average daily walking distance (mean 2.6, SD 2.5; 95% CI 2.5-2.7 vs mean 2.4, SD 2.3; 95% CI 2.3-2.5; P<.001) and more moving average daily walking distance (mean 3.5, SD 1.3; 95% CI 3.4-3.6 vs mean 3.2, SD 0.8; 95% CI 3.1-3.3; P<.001). Moving average daily walking distances among intervention participants increased, which was also significantly higher than that of the control group (regression slope=0.0046 vs 0.0017; P<.001). Participants in the intervention group reported a growing sense of accountability and motivation. One barrier was completing weekly monitoring of patient-reported outcome surveys, which focused on symptoms and physical function and did not always align with participants' goals.</p><p><strong>Conclusions: </strong>The Healt","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e78968"},"PeriodicalIF":2.7,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12856392/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145985199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Baidong Zhang, Zhichao Kang, Yi Ding, Wang Jing, Alei Feng, Renya Zeng, Jianan Li, Yi Zhao, Yuanliu Nie, Wentao Zhang, Lu Sun, Zhe Yang
<p><strong>Background: </strong>Immune checkpoint inhibitors (ICIs) have emerged as a pivotal treatment for advanced esophageal squamous cell carcinoma (ESCC). However, their efficacy can significantly differ among patients, highlighting the need for reliable prognostic markers to enhance treatment outcomes. Lactate dehydrogenase (LDH) plays a key regulatory role in the complex relationship between cancer metabolism and the immune system, suggesting that monitoring LDH levels may provide valuable insights into treatment efficacy and inform personalized therapeutic strategies for advanced ESCC.</p><p><strong>Objective: </strong>This study aimed to explore the prognostic significance of dynamic changes in LDH levels during ICI therapy in predicting treatment outcomes.</p><p><strong>Methods: </strong>We retrospectively analyzed the clinical data of 126 patients with advanced ESCC who received first-line ICI therapy at the Department of Radiation Oncology, Cancer Center, Shandong Provincial Hospital, between April 2018 and November 2022. Serum LDH levels were measured after every 3 cycles of combined immunotherapy and chemotherapy. Receiver operating characteristic curve analysis determined the optimal LDH reduction threshold. Kaplan-Meier survival curves and Cox regression models assessed progression-free survival (PFS) and overall survival.</p><p><strong>Results: </strong>Among the 126 patients, 55 (43.6%) were classified into the LDH-increased group, while 71 (56.4%) belonged to the LDH-decreased group. Within the LDH-increased group, 78.2% (43/55) of the patients were male, compared to 90.1% (64/71) in the LDH-decreased group. The median age of patients in the LDH-increased group was 59 (range 55-68) years, whereas the median age in the LDH-decreased group was 65 (range 58-65) years. LDH decrease following first-line ICI therapy was associated with improved outcomes compared to LDH increases (median PFS 13.4, IQR 8.1-24.3 mo vs median 10.8, IQR 4.8-20.6 mo; P= .03). Patients with a posttreatment LDH decrease of more than 14.4% had a median PFS of 11.1 (IQR 7.2-24.3) months, whereas those with an LDH decrease between 0% and 14.4% had a median PFS of 21.7 (IQR 9.4-34.5) months. Conversely, an increase in LDH resulted in a median PFS of 10.8 (IQR 4.8-20.6) months. Patients with tumor reduction exhibited a significantly greater decrease in LDH levels compared with those without tumor reduction (P<.001). Multivariate analysis identified LDH decrease as an independent predictor of a 41% lower mortality risk (hazard ratio 0.59, 95% CI 0.36-0.96; P=.04).</p><p><strong>Conclusions: </strong>In patients with advanced ESCC, a decrease in serum LDH levels ranging from 0% to 14.4% after treatment initiation was significantly associated with prolonged PFS. Notably, an early decrease in LDH levels observed after 3 cycles of immunotherapy further correlated with improved clinical outcomes. These results highlight the potential of LDH as a valuable biomarker for
{"title":"Prognostic Value of Dynamic Lactate Dehydrogenase Trends in Immunotherapy for Advanced Esophageal Squamous Cell Carcinoma: Retrospective Cohort Study.","authors":"Baidong Zhang, Zhichao Kang, Yi Ding, Wang Jing, Alei Feng, Renya Zeng, Jianan Li, Yi Zhao, Yuanliu Nie, Wentao Zhang, Lu Sun, Zhe Yang","doi":"10.2196/73576","DOIUrl":"10.2196/73576","url":null,"abstract":"<p><strong>Background: </strong>Immune checkpoint inhibitors (ICIs) have emerged as a pivotal treatment for advanced esophageal squamous cell carcinoma (ESCC). However, their efficacy can significantly differ among patients, highlighting the need for reliable prognostic markers to enhance treatment outcomes. Lactate dehydrogenase (LDH) plays a key regulatory role in the complex relationship between cancer metabolism and the immune system, suggesting that monitoring LDH levels may provide valuable insights into treatment efficacy and inform personalized therapeutic strategies for advanced ESCC.</p><p><strong>Objective: </strong>This study aimed to explore the prognostic significance of dynamic changes in LDH levels during ICI therapy in predicting treatment outcomes.</p><p><strong>Methods: </strong>We retrospectively analyzed the clinical data of 126 patients with advanced ESCC who received first-line ICI therapy at the Department of Radiation Oncology, Cancer Center, Shandong Provincial Hospital, between April 2018 and November 2022. Serum LDH levels were measured after every 3 cycles of combined immunotherapy and chemotherapy. Receiver operating characteristic curve analysis determined the optimal LDH reduction threshold. Kaplan-Meier survival curves and Cox regression models assessed progression-free survival (PFS) and overall survival.</p><p><strong>Results: </strong>Among the 126 patients, 55 (43.6%) were classified into the LDH-increased group, while 71 (56.4%) belonged to the LDH-decreased group. Within the LDH-increased group, 78.2% (43/55) of the patients were male, compared to 90.1% (64/71) in the LDH-decreased group. The median age of patients in the LDH-increased group was 59 (range 55-68) years, whereas the median age in the LDH-decreased group was 65 (range 58-65) years. LDH decrease following first-line ICI therapy was associated with improved outcomes compared to LDH increases (median PFS 13.4, IQR 8.1-24.3 mo vs median 10.8, IQR 4.8-20.6 mo; P= .03). Patients with a posttreatment LDH decrease of more than 14.4% had a median PFS of 11.1 (IQR 7.2-24.3) months, whereas those with an LDH decrease between 0% and 14.4% had a median PFS of 21.7 (IQR 9.4-34.5) months. Conversely, an increase in LDH resulted in a median PFS of 10.8 (IQR 4.8-20.6) months. Patients with tumor reduction exhibited a significantly greater decrease in LDH levels compared with those without tumor reduction (P<.001). Multivariate analysis identified LDH decrease as an independent predictor of a 41% lower mortality risk (hazard ratio 0.59, 95% CI 0.36-0.96; P=.04).</p><p><strong>Conclusions: </strong>In patients with advanced ESCC, a decrease in serum LDH levels ranging from 0% to 14.4% after treatment initiation was significantly associated with prolonged PFS. Notably, an early decrease in LDH levels observed after 3 cycles of immunotherapy further correlated with improved clinical outcomes. These results highlight the potential of LDH as a valuable biomarker for ","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e73576"},"PeriodicalIF":2.7,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12808870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145991352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mahtab Azhdar, Adalberto Loyola-Sanchez, Amber Wardrop, Martin Ferguson-Pell
<p><strong>Background: </strong>People surviving breast cancer often face long-term impairments in physical function, significantly impacting their quality of life. In recent years, a variety of technologies have been developed to monitor and assess these functions; however, there is no consolidated synthesis linking specific technologies to targeted functional domains and real-world clinical contexts, limiting comparability and translation into practice.</p><p><strong>Objective: </strong>This scoping review aimed to systematically explore and map the use of advanced clinic-based technologies for assessing and monitoring key physical functions, such as balance, muscle strength, and range of motion, among individuals surviving breast cancer. The purpose of this review was not only to identify which technologies have been applied but also to clarify how they are being used, the clinical settings, target physical functions, assessment protocols, and types of outcomes measured. It further summarized the current patterns of use to inform and enhance clinical assessment practices.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted across MEDLINE, Scopus, CINAHL, and Web of Science databases, with no publication date restrictions. Eligible studies included adults with breast cancer assessed using advanced clinic-based technologies to monitor physical function. Screening and selection followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The data extraction captured study characteristics, participant demographics, technologies applied, and related outcomes. The extracted data were organized in Covidence and synthesized descriptively to map the types of technologies, assessed functional domains, and application settings across studies.</p><p><strong>Results: </strong>Across the 17 included studies, the participants (N=719; age range between 30 and 75 years) were predominantly female and largely drawn from stage 0 to III breast cancer cohorts; 1 (5.9%) study reported a single male participant, and 2 (11.8%) studies did not specify participant sex. Among the 17 included studies, 11 (64.7%) were published from 2017 onward. Technologies spanned balance platforms (force plates, Technobody-PK 200 WL, Sensory Organization Test; 5/17, 29.4%), isokinetic dynamometry (Biodex systems; 4/17, 23.5%), and range of motion assessment via motion capture (3/17, 17.6%) or digital inclinometers (5/17, 29.4%). Sample sizes per study ranged from 20 to 100 participants (median 43), and follow-up durations varied from 1 session to 6 months.</p><p><strong>Conclusions: </strong>Advanced clinic-based technologies for assessing balance, muscle strength, and range of motion in breast cancer survivors were identified across the literature, including balance platforms, isokinetic dynamometry, digital inclinometers, and markerless motion capture systems. Considerable heterogeneity in devices, outcome reporting, and
背景：乳腺癌患者经常面临身体功能的长期损伤，严重影响其生活质量。近年来，已经开发了各种技术来监测和评估这些功能；然而，目前还没有将特定技术与目标功能域和现实世界临床环境联系起来的综合研究，限制了可比性和转化为实践。目的：本综述旨在系统地探索和绘制先进的临床技术用于评估和监测乳腺癌存活个体的关键身体功能，如平衡、肌肉力量和活动范围。本综述的目的不仅是确定哪些技术已经被应用，而且要澄清它们是如何被使用的、临床环境、目标身体功能、评估方案和测量结果的类型。它进一步总结了目前的使用模式，以告知和加强临床评估实践。方法：在MEDLINE、Scopus、CINAHL和Web of Science数据库中进行全面的文献检索，无发表日期限制。合格的研究包括患有乳腺癌的成年人，使用先进的临床技术来监测身体功能。筛选和选择遵循PRISMA（系统评价和荟萃分析首选报告项目）指南。数据提取包括研究特征、参与者人口统计、应用的技术和相关结果。提取的数据在covid中进行组织，并进行描述性综合，以绘制技术类型、评估的功能领域和跨研究的应用设置。结果：在纳入的17项研究中，参与者（N=719，年龄在30至75岁之间）主要是女性，大部分来自0期至III期乳腺癌队列；1项（5.9%）研究报告了单个男性参与者，2项（11.8%）研究没有明确参与者的性别。在纳入的17项研究中，11项（64.7%）发表于2017年以后。技术跨越平衡平台（力板，Technobody-PK 200 WL，感官组织测试；5/17,29.4%），等速动力学测量（Biodex系统；4/17,23.5%），以及通过运动捕捉（3/17,17.6%）或数字倾斜仪（5/17,29.4%）进行运动范围评估。每项研究的样本量从20到100名参与者（中位数43），随访时间从1个月到6个月不等。结论：在文献中发现了用于评估乳腺癌幸存者平衡、肌肉力量和活动范围的先进临床技术，包括平衡平台、等速动力学测量、数字倾角计和无标记运动捕捉系统。设备、结果报告和研究设计的巨大异质性限制了研究间的直接比较，并阻碍了对任何单一技术的优越性或临床准备性的明确结论。
{"title":"Advanced Clinical-Based Technologies for Monitoring Physical Function in Breast Cancer Survivors: Scoping Review.","authors":"Mahtab Azhdar, Adalberto Loyola-Sanchez, Amber Wardrop, Martin Ferguson-Pell","doi":"10.2196/77894","DOIUrl":"10.2196/77894","url":null,"abstract":"<p><strong>Background: </strong>People surviving breast cancer often face long-term impairments in physical function, significantly impacting their quality of life. In recent years, a variety of technologies have been developed to monitor and assess these functions; however, there is no consolidated synthesis linking specific technologies to targeted functional domains and real-world clinical contexts, limiting comparability and translation into practice.</p><p><strong>Objective: </strong>This scoping review aimed to systematically explore and map the use of advanced clinic-based technologies for assessing and monitoring key physical functions, such as balance, muscle strength, and range of motion, among individuals surviving breast cancer. The purpose of this review was not only to identify which technologies have been applied but also to clarify how they are being used, the clinical settings, target physical functions, assessment protocols, and types of outcomes measured. It further summarized the current patterns of use to inform and enhance clinical assessment practices.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted across MEDLINE, Scopus, CINAHL, and Web of Science databases, with no publication date restrictions. Eligible studies included adults with breast cancer assessed using advanced clinic-based technologies to monitor physical function. Screening and selection followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The data extraction captured study characteristics, participant demographics, technologies applied, and related outcomes. The extracted data were organized in Covidence and synthesized descriptively to map the types of technologies, assessed functional domains, and application settings across studies.</p><p><strong>Results: </strong>Across the 17 included studies, the participants (N=719; age range between 30 and 75 years) were predominantly female and largely drawn from stage 0 to III breast cancer cohorts; 1 (5.9%) study reported a single male participant, and 2 (11.8%) studies did not specify participant sex. Among the 17 included studies, 11 (64.7%) were published from 2017 onward. Technologies spanned balance platforms (force plates, Technobody-PK 200 WL, Sensory Organization Test; 5/17, 29.4%), isokinetic dynamometry (Biodex systems; 4/17, 23.5%), and range of motion assessment via motion capture (3/17, 17.6%) or digital inclinometers (5/17, 29.4%). Sample sizes per study ranged from 20 to 100 participants (median 43), and follow-up durations varied from 1 session to 6 months.</p><p><strong>Conclusions: </strong>Advanced clinic-based technologies for assessing balance, muscle strength, and range of motion in breast cancer survivors were identified across the literature, including balance platforms, isokinetic dynamometry, digital inclinometers, and markerless motion capture systems. Considerable heterogeneity in devices, outcome reporting, and ","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e77894"},"PeriodicalIF":2.7,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12853085/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145985170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adapting Interventions for Home Hospice Caregivers Using Digital Health Innovation.","authors":"Qing Huang","doi":"10.2196/81589","DOIUrl":"10.2196/81589","url":null,"abstract":"","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e81589"},"PeriodicalIF":2.7,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12853088/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145985196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><strong>Background: </strong>Metastatic cancer remains one of the leading causes of cancer-related mortality worldwide. Yet, the prediction of survivability in this population remains limited by heterogeneous clinical presentations and high-dimensional molecular features. Advances in machine learning (ML) provide an opportunity to integrate diverse patient- and tumor-level factors into explainable predictive ML models. Leveraging large real-world datasets and modern ML techniques can enable improved risk stratification and precision oncology.</p><p><strong>Objective: </strong>This study aimed to develop and interpret ML models for predicting overall survival in patients with metastatic cancer using the Memorial Sloan Kettering-Metastatic (MSK-MET) dataset and to identify key prognostic biomarkers through explainable artificial intelligence techniques.</p><p><strong>Methods: </strong>We performed a retrospective analysis of the MSK-MET cohort, comprising 25,775 patients across 27 tumor types. After data cleaning and balancing, 20,338 patients were included. Overall survival was defined as deceased versus living at last follow-up. Five classifiers (extreme gradient boosting [XGBoost], logistic regression, random forest, decision tree, and naive Bayes) were trained using an 80/20 stratified split and optimized via grid search with 5-fold cross-validation. Model performance was assessed using accuracy, area under the curve (AUC), precision, recall, and F<sub>1</sub>-score. Model explainability was achieved using Shapley additive explanations (SHAP). Survival analyses included Kaplan-Meier estimates, Cox proportional hazards models, and an XGBoost-Cox model for time-to-event prediction. The positive predictive value and negative predictive value were calculated at the Youden index-optimal threshold.</p><p><strong>Results: </strong>XGBoost achieved the highest performance (accuracy=0.74; AUC=0.82), outperforming other classifiers. In survival analyses, the XGBoost-Cox model with a concordance index (C-index) of 0.70 exceeded the traditional Cox model (C-index=0.66). SHAP analysis and Cox models consistently identified metastatic site count, tumor mutational burden, fraction of genome altered, and the presence of distant liver and bone metastases as among the strongest prognostic factors, a pattern that held at both the pan-cancer level and recurrently across cancer-specific models. At the cancer-specific level, performance varied; prostate cancer achieved the highest predictive accuracy (AUC=0.88), while pancreatic cancer was notably more challenging (AUC=0.68). Kaplan-Meier analyses demonstrated marked survival separation between patients with and without metastases (80-month survival: approximately 0.80 vs 0.30). At the Youden-optimal threshold, positive predictive value and negative predictive value were approximately 70% and 80%, respectively, supporting clinical use for risk stratification.</p><p><strong>Conclusions: </strong>Explainable ML mod
背景：转移性癌症仍然是世界范围内癌症相关死亡的主要原因之一。然而，该人群的存活率预测仍然受到异质性临床表现和高维分子特征的限制。机器学习（ML）的进步为将不同的患者和肿瘤水平的因素整合到可解释的预测ML模型中提供了机会。利用大型真实世界数据集和现代ML技术可以改进风险分层和精确肿瘤学。目的：本研究旨在利用纪念斯隆-凯特林-转移（MSK-MET）数据集开发和解释预测转移性癌症患者总生存的ML模型，并通过可解释的人工智能技术确定关键的预后生物标志物。方法：我们对MSK-MET队列进行了回顾性分析，包括27种肿瘤类型的25,775例患者。经过数据清理和平衡，纳入了20338例患者。总生存率定义为最后随访时的死亡vs存活。五个分类器（极端梯度增强[XGBoost]，逻辑回归，随机森林，决策树和朴素贝叶斯）使用80/20分层分割进行训练，并通过网格搜索进行优化，并进行5倍交叉验证。通过准确性、曲线下面积（AUC）、精度、召回率和f1评分来评估模型的性能。采用Shapley加性解释（SHAP）实现模型的可解释性。生存分析包括Kaplan-Meier估计、Cox比例风险模型和用于事件时间预测的XGBoost-Cox模型。在优登指数-最优阈值下计算阳性预测值和阴性预测值。结果：XGBoost获得了最高的性能（准确率=0.74；AUC=0.82），优于其他分类器。在生存分析中，XGBoost-Cox模型的一致性指数（C-index）为0.70，优于传统Cox模型（C-index=0.66）。SHAP分析和Cox模型一致认为转移部位计数、肿瘤突变负担、基因组改变的部分以及远处肝脏和骨转移的存在是最强的预后因素，这种模式在泛癌症水平和癌症特异性模型中都存在。在癌症特异性水平上，表现各不相同；前列腺癌的预测准确率最高（AUC=0.88），而胰腺癌的预测准确率更高（AUC=0.68）。Kaplan-Meier分析显示，有和没有转移的患者之间存在明显的生存差异（80个月生存率：约0.80 vs 0.30）。在约登最优阈值下，阳性预测值和阴性预测值分别约为70%和80%，支持临床应用于风险分层。结论：可解释的ML模型，特别是XGBoost联合SHAP，可以强烈预测转移性癌症的生存能力，同时突出临床有意义的特征。这些发现支持使用基于ml的工具进行患者咨询、治疗计划和整合到精确的肿瘤学工作流程中。未来的工作应包括对独立队列进行外部验证，通过基于快速医疗互操作性资源的仪表板与电子健康记录集成，以及对临床医生进行前瞻性循环评估以评估实际使用情况。
{"title":"Explainable AI for Predicting Mortality Risk in Metastatic Cancer: Retrospective Cohort Study Using the Memorial Sloan Kettering-Metastatic Dataset.","authors":"Polycarp Nalela, Deepthi Rao, Praveen Rao","doi":"10.2196/74196","DOIUrl":"10.2196/74196","url":null,"abstract":"<p><strong>Background: </strong>Metastatic cancer remains one of the leading causes of cancer-related mortality worldwide. Yet, the prediction of survivability in this population remains limited by heterogeneous clinical presentations and high-dimensional molecular features. Advances in machine learning (ML) provide an opportunity to integrate diverse patient- and tumor-level factors into explainable predictive ML models. Leveraging large real-world datasets and modern ML techniques can enable improved risk stratification and precision oncology.</p><p><strong>Objective: </strong>This study aimed to develop and interpret ML models for predicting overall survival in patients with metastatic cancer using the Memorial Sloan Kettering-Metastatic (MSK-MET) dataset and to identify key prognostic biomarkers through explainable artificial intelligence techniques.</p><p><strong>Methods: </strong>We performed a retrospective analysis of the MSK-MET cohort, comprising 25,775 patients across 27 tumor types. After data cleaning and balancing, 20,338 patients were included. Overall survival was defined as deceased versus living at last follow-up. Five classifiers (extreme gradient boosting [XGBoost], logistic regression, random forest, decision tree, and naive Bayes) were trained using an 80/20 stratified split and optimized via grid search with 5-fold cross-validation. Model performance was assessed using accuracy, area under the curve (AUC), precision, recall, and F<sub>1</sub>-score. Model explainability was achieved using Shapley additive explanations (SHAP). Survival analyses included Kaplan-Meier estimates, Cox proportional hazards models, and an XGBoost-Cox model for time-to-event prediction. The positive predictive value and negative predictive value were calculated at the Youden index-optimal threshold.</p><p><strong>Results: </strong>XGBoost achieved the highest performance (accuracy=0.74; AUC=0.82), outperforming other classifiers. In survival analyses, the XGBoost-Cox model with a concordance index (C-index) of 0.70 exceeded the traditional Cox model (C-index=0.66). SHAP analysis and Cox models consistently identified metastatic site count, tumor mutational burden, fraction of genome altered, and the presence of distant liver and bone metastases as among the strongest prognostic factors, a pattern that held at both the pan-cancer level and recurrently across cancer-specific models. At the cancer-specific level, performance varied; prostate cancer achieved the highest predictive accuracy (AUC=0.88), while pancreatic cancer was notably more challenging (AUC=0.68). Kaplan-Meier analyses demonstrated marked survival separation between patients with and without metastases (80-month survival: approximately 0.80 vs 0.30). At the Youden-optimal threshold, positive predictive value and negative predictive value were approximately 70% and 80%, respectively, supporting clinical use for risk stratification.</p><p><strong>Conclusions: </strong>Explainable ML mod","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e74196"},"PeriodicalIF":2.7,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12848487/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145967424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alberto Lopez-Garcia, Carola Diaz-Aizpun, Beatriz Gallego-Diaz, Carolina Miranda-Castillo, Maria Yuste-Platero, Pilar Beltran-Alvarez, Cristina Carames-Sanchez, Jesus Garcia-Foncillas, Pilar Llamas-Sillero, Marta Del Olmo-Rodriguez, Jorge Short-Apellaniz, Bernadette Pfang, Javier Arcos-Campillo, Raul Cordoba
Background: Barriers to eHealth use include lack of technological infrastructure, resistance to change, and inequities in access. However, patterns of access to and use of eHealth tools in people being treated for cancer have not been fully described in the literature.
Objective: Our aim was to describe the patterns of access to and use of eHealth tools among outpatients receiving treatment for hematological malignancies and solid tumors.
Methods: We conducted a cross-sectional multicenter study using a survey offered to patients aged over 18 years receiving outpatient treatment for hematological malignancies or solid tumors at 4 teaching hospitals in Madrid, Spain, between February 1, 2021, and November 30, 2021. The survey instrument featured questions about patients' demographic and social characteristics, cancer diagnosis, use of information and communication technology (ICT), use and opinions of the Patient Portal, and changes in ICT use during the COVID-19 pandemic. To study the relationship between the different variables, 2-tailed Student t tests or ANOVA were used for variables with normal distribution, and the Mann-Whitney or Kruskal-Wallis tests were used for variables with nonnormal distribution. Statistical analyses were performed using SPSS (version 25; IBM Corp) for Windows.
Results: In total, 200 patients were included in our study. Median age was 60 (range 21-87) years. A total of 130 (65%) patients presented with hematological malignancies. Most (n=181, 90.5%) patients considered that eHealth tools might help to improve communication with the medical team during their treatment. Retired participants (28.6% vs 71.4%; P<.001), those older than 60 years (26% vs 74%; P<.001), and those without higher education (2.6% vs 97.4%; P<.001) showed significantly lower rates of internet use, with no observed sex-related differences. A total of 177 (88.5%) patients found the Patient Portal useful, and 140 (70%) reported increased use of ICT due to the COVID-19 pandemic.
Conclusions: Most (177/200, 88.5%) patients viewed eHealth tools as useful and believed that it was helpful to improve communication with their care team. However, notable gaps in the use of eHealth were observed in certain groups of patients, with significant differences in use due to age, education, and employment status. Strategies to identify subgroups at risk for unequal access to digital health, as well as to facilitate access and use, are warranted.
背景：电子卫生使用的障碍包括缺乏技术基础设施、抗拒变革和获取不公平。然而，文献中并未充分描述正在接受癌症治疗的患者获取和使用电子卫生工具的模式。目的：我们的目的是描述在接受血液恶性肿瘤和实体肿瘤治疗的门诊患者中获取和使用电子健康工具的模式。方法：我们在2021年2月1日至2021年11月30日期间，对西班牙马德里4家教学医院接受血液恶性肿瘤或实体瘤门诊治疗的18岁以上患者进行了一项横断面多中心研究。该调查工具的问题包括患者的人口统计学和社会特征、癌症诊断、信息通信技术（ICT）的使用、患者门户网站的使用和意见，以及COVID-19大流行期间信息通信技术使用的变化。为研究不同变量之间的关系，正态分布的变量采用双尾Student t检验或方差分析，非正态分布的变量采用Mann-Whitney或Kruskal-Wallis检验。统计分析使用SPSS (version 25; IBM Corp) for Windows进行。结果：本研究共纳入200例患者。中位年龄为60岁（21-87岁）。共有130例（65%）患者表现为血液系统恶性肿瘤。大多数（n=181, 90.5%）患者认为电子健康工具可能有助于改善他们在治疗期间与医疗团队的沟通。结论：大多数（177/200,88.5%）患者认为电子健康工具是有用的，并认为有助于改善与护理团队的沟通。然而，在某些患者群体中，由于年龄、教育程度和就业状况的不同，在使用电子健康方面存在显著差异。有必要制定战略，确定有不平等获取数字卫生服务风险的亚群体，并促进获取和使用。
{"title":"New Technologies and Digital Health Tools in Patients With Solid Tumors and Hematological Malignancies: Cross-Sectional Multicenter Survey Study.","authors":"Alberto Lopez-Garcia, Carola Diaz-Aizpun, Beatriz Gallego-Diaz, Carolina Miranda-Castillo, Maria Yuste-Platero, Pilar Beltran-Alvarez, Cristina Carames-Sanchez, Jesus Garcia-Foncillas, Pilar Llamas-Sillero, Marta Del Olmo-Rodriguez, Jorge Short-Apellaniz, Bernadette Pfang, Javier Arcos-Campillo, Raul Cordoba","doi":"10.2196/58823","DOIUrl":"10.2196/58823","url":null,"abstract":"<p><strong>Background: </strong>Barriers to eHealth use include lack of technological infrastructure, resistance to change, and inequities in access. However, patterns of access to and use of eHealth tools in people being treated for cancer have not been fully described in the literature.</p><p><strong>Objective: </strong>Our aim was to describe the patterns of access to and use of eHealth tools among outpatients receiving treatment for hematological malignancies and solid tumors.</p><p><strong>Methods: </strong>We conducted a cross-sectional multicenter study using a survey offered to patients aged over 18 years receiving outpatient treatment for hematological malignancies or solid tumors at 4 teaching hospitals in Madrid, Spain, between February 1, 2021, and November 30, 2021. The survey instrument featured questions about patients' demographic and social characteristics, cancer diagnosis, use of information and communication technology (ICT), use and opinions of the Patient Portal, and changes in ICT use during the COVID-19 pandemic. To study the relationship between the different variables, 2-tailed Student t tests or ANOVA were used for variables with normal distribution, and the Mann-Whitney or Kruskal-Wallis tests were used for variables with nonnormal distribution. Statistical analyses were performed using SPSS (version 25; IBM Corp) for Windows.</p><p><strong>Results: </strong>In total, 200 patients were included in our study. Median age was 60 (range 21-87) years. A total of 130 (65%) patients presented with hematological malignancies. Most (n=181, 90.5%) patients considered that eHealth tools might help to improve communication with the medical team during their treatment. Retired participants (28.6% vs 71.4%; P<.001), those older than 60 years (26% vs 74%; P<.001), and those without higher education (2.6% vs 97.4%; P<.001) showed significantly lower rates of internet use, with no observed sex-related differences. A total of 177 (88.5%) patients found the Patient Portal useful, and 140 (70%) reported increased use of ICT due to the COVID-19 pandemic.</p><p><strong>Conclusions: </strong>Most (177/200, 88.5%) patients viewed eHealth tools as useful and believed that it was helpful to improve communication with their care team. However, notable gaps in the use of eHealth were observed in certain groups of patients, with significant differences in use due to age, education, and employment status. Strategies to identify subgroups at risk for unequal access to digital health, as well as to facilitate access and use, are warranted.</p>","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e58823"},"PeriodicalIF":2.7,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12798843/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145967427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qi Chen, Erin Donovan, Leyi Zhou, Lailea Noel, Barbara Jones
<p><strong>Background: </strong>Online cancer communities provide young adult (YA) cancer survivors with access to informational and emotional support that may not be available in traditional care settings. While these platforms offer vital connection opportunities, the unique pathways YA survivors take to find online communities and the challenges they encounter remain underexplored.</p><p><strong>Objectives: </strong>This study aimed to (1) examine how YA cancer survivors locate and access online cancer communities and (2) identify barriers that impede their participation or sustained engagement.</p><p><strong>Methods: </strong>The first author conducted semistructured interviews with 12 YA cancer survivors aged 18 to 39 years who had experience using online resources after their diagnosis. Participants were recruited through purposive and snowball sampling from YA cancer-focused nonprofit organizations and through social media. Interviews were conducted via Zoom and analyzed using thematic analysis. The analytic process followed Braun and Clarke's 6-phase framework and was supported by MAXQDA software. Codes and themes were generated inductively and refined iteratively.</p><p><strong>Results: </strong>Participants ranged in age from 24 to 39 years (mean 32, SD 5.08 years), with an average of 3 (SD 2.98) years since diagnosis. Most identified as female (n=9, 75%) and non-Hispanic White (n=7, 58%). Over half held a graduate degree (n=7, 58%), half were employed full time (n=6, 50%), and most resided in suburban areas (n=8, 67%). Cancer diagnoses included leukemia (n=3, 25%), lymphoma (n=4, 33%), and other solid tumors such as testicular, colon, and uterine cancers. At the time of the interview, 3 (25%) participants were in active treatment and 9 (75%) had completed treatment. Participants described five primary pathways to discovering online cancer communities: (1) direct searching using hashtags or keywords, (2) community hubs on public accounts, (3) referrals from health providers or social networks, (4) algorithm-recommended content, and (5) connections formed within preexisting online interest-based groups. Despite the promise of digital tools, participants encountered five roadblocks: (1) platform fragmentation and digital literacy complicated initial discovery; (2) lack of representation made it difficult for some to find communities where they felt seen; (3) emotional overload and engagement fatigue, along with shifting group hierarchies and boundaries, further hindered sustained participation; and (5) lastly, concerns about cyberbullying discouraged open engagement, prompting some to withdraw or limit their presence in online communities.</p><p><strong>Conclusions: </strong>YA cancer survivors navigated a fragmented and emotionally complex digital landscape in search of social support. Their ability to access and engage with online communities was shaped not only by individual agency and digital literacy but also by structural and relati
{"title":"Pathways and Roadblocks in Navigating Online Cancer Communities: Qualitative Study Among Young Adult Cancer Survivors.","authors":"Qi Chen, Erin Donovan, Leyi Zhou, Lailea Noel, Barbara Jones","doi":"10.2196/79893","DOIUrl":"10.2196/79893","url":null,"abstract":"<p><strong>Background: </strong>Online cancer communities provide young adult (YA) cancer survivors with access to informational and emotional support that may not be available in traditional care settings. While these platforms offer vital connection opportunities, the unique pathways YA survivors take to find online communities and the challenges they encounter remain underexplored.</p><p><strong>Objectives: </strong>This study aimed to (1) examine how YA cancer survivors locate and access online cancer communities and (2) identify barriers that impede their participation or sustained engagement.</p><p><strong>Methods: </strong>The first author conducted semistructured interviews with 12 YA cancer survivors aged 18 to 39 years who had experience using online resources after their diagnosis. Participants were recruited through purposive and snowball sampling from YA cancer-focused nonprofit organizations and through social media. Interviews were conducted via Zoom and analyzed using thematic analysis. The analytic process followed Braun and Clarke's 6-phase framework and was supported by MAXQDA software. Codes and themes were generated inductively and refined iteratively.</p><p><strong>Results: </strong>Participants ranged in age from 24 to 39 years (mean 32, SD 5.08 years), with an average of 3 (SD 2.98) years since diagnosis. Most identified as female (n=9, 75%) and non-Hispanic White (n=7, 58%). Over half held a graduate degree (n=7, 58%), half were employed full time (n=6, 50%), and most resided in suburban areas (n=8, 67%). Cancer diagnoses included leukemia (n=3, 25%), lymphoma (n=4, 33%), and other solid tumors such as testicular, colon, and uterine cancers. At the time of the interview, 3 (25%) participants were in active treatment and 9 (75%) had completed treatment. Participants described five primary pathways to discovering online cancer communities: (1) direct searching using hashtags or keywords, (2) community hubs on public accounts, (3) referrals from health providers or social networks, (4) algorithm-recommended content, and (5) connections formed within preexisting online interest-based groups. Despite the promise of digital tools, participants encountered five roadblocks: (1) platform fragmentation and digital literacy complicated initial discovery; (2) lack of representation made it difficult for some to find communities where they felt seen; (3) emotional overload and engagement fatigue, along with shifting group hierarchies and boundaries, further hindered sustained participation; and (5) lastly, concerns about cyberbullying discouraged open engagement, prompting some to withdraw or limit their presence in online communities.</p><p><strong>Conclusions: </strong>YA cancer survivors navigated a fragmented and emotionally complex digital landscape in search of social support. Their ability to access and engage with online communities was shaped not only by individual agency and digital literacy but also by structural and relati","PeriodicalId":45538,"journal":{"name":"JMIR Cancer","volume":"12 ","pages":"e79893"},"PeriodicalIF":2.7,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12795408/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145960630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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