IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-19 DOI: 10.2196/75586

Hiroshi Handa, Tadao Ishida, Shuji Ozaki, Shinsuke Iida, Kittima Wattanakamolkul, Chika Sakai, Kenichi Kato, David Bin-Chia Wu, DaeYoung Yu, Shota Nemoto, Yasuho Yamashita, Takuma Shibahara

Background: With the availability of newer therapies, the duration of therapy (DoT) shortens with each increasing line of treatment in Japanese patients with multiple myeloma (MM).Objective: This study aimed to identify factors that shorten DoT in patients with MM using a machine learning (ML) procedure from the Medical Data Vision (MDV) database.Methods: This nationwide, retrospective observational real-world study was conducted using anonymized patient data from the MDV claims database from 2003 to 2022. Patients (≥18 y) with transplant-ineligible newly diagnosed MM (continued first line therapy), or relapsed or refractory MM (continued second or third line therapies) were included. To identify important predictive factors, an explainable deep learning model was created using 647 extracted variables (continuous, binary, and nominal categorical) from the MDV database, and the extracted data were used to train ML algorithms to build point-wise linear (PWL) models for predicting DoT. Predictive performance of the PWL model was compared with the elastic net (regularized logistic regression) and the extreme gradient boosting models, and calculated by area under the curve and evaluated by 10-fold double cross-validation. A clustering analysis (k-means method) of 4848 individual samples assessed the relationship between each sample and DoT (3, 6, and 12 months). The characteristics of clusters and sample features belonging to each cluster during and after treatment were studied.Results: Overall, 2762 (4848 individual samples) patients were evaluated (mean age 69.6, SD 11.8 years; 1450/2762, 52.5% male). The area under the curve score of the PWL model to predict DoT at 3, 6, and 12 months was 0.61, 0.64, and 0.66, respectively. Based on the similarity of coefficients of regression models, samples were categorized into 2 clusters (clusters A and B) at DoT of 3 months, 3 clusters (clusters A, B, and C) at 6 months, and 12 months (clusters A, B, and C). Cluster B versus cluster A (at 3 months) and cluster C versus cluster A and B (at 6 and 12 months) had a significantly (P<.01) higher pretreatment Charlson Comorbidity Index. They also showed a lower median of prediction probability. At 3 months in cluster B and at 6 and 12 months in cluster C, the use of immunomodulatory drugs for MM treatment was significantly higher in patients who met predicted DoT at each threshold versus those who did not. Additionally, the use of aspirin was significantly higher in cluster B and cluster C at 3 and 6 months, respectively.Conclusions: Applying ML techniques using the PWL model yielded efficient results to understand trends associated with treatment and characteristics of Japanese patients with MM whose DoT were shortened. The study demonstrated that patients' disease status and management-related factors, including use of immunomodulatory drugs and manag

背景：随着新疗法的出现，日本多发性骨髓瘤（MM）患者的治疗时间（DoT）随着治疗线的增加而缩短。目的：本研究旨在利用医学数据视觉（MDV）数据库中的机器学习（ML）程序，确定缩短MM患者DoT的因素。方法：这项全国范围内的回顾性观察性现实研究使用了MDV索赔数据库中2003年至2022年的匿名患者数据。新诊断的不适合移植的MM（继续一线治疗）或复发或难治性MM（继续二线或三线治疗）患者（≥18岁）被纳入研究。为了识别重要的预测因素，使用从MDV数据库中提取的647个变量（连续、二元和名义分类）创建了一个可解释的深度学习模型，提取的数据用于训练ML算法，以构建预测DoT的点向线性（PWL）模型。将PWL模型的预测性能与弹性网络（正则化逻辑回归）和极端梯度增强模型进行比较，并通过曲线下面积计算和10次双交叉验证进行评估。对4848个个体样本进行聚类分析（k-均值法），评估每个样本与DoT（3、6和12个月）之间的关系。研究了处理过程和处理后的聚类特征和各聚类的样本特征。结果：总的来说，2762例（4848例个体样本）患者被评估（平均年龄69.6岁，SD 11.8岁；1450/2762例，52.5%为男性）。PWL模型预测3、6、12个月DoT的曲线下面积评分分别为0.61、0.64、0.66。根据回归模型系数的相似性，将样本在3个月时分为2类（A、B类），6个月时分为3类（A、B、C类），12个月时分为A、B、C类。B组与A组（3个月时）和C组与A组和B组（6个月和12个月时）的差异显著（p < 0.05）。结论：使用PWL模型应用ML技术可以有效地了解日本MM患者DoT缩短的治疗趋势和特征。该研究表明，患者的疾病状态和管理相关因素，包括免疫调节药物的使用和血栓预防管理，可能与DoT长度有关。

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引用次数: 0

Co-Ablation System for Pain Management in Bone Metastases: Retrospective Exploratory Study. 骨转移疼痛管理的联合消融系统：回顾性探索性研究。

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-19 DOI: 10.2196/86301

Hang Yuan, Wei-Li Xia, Ho-Young Song, Lin Zheng, Wei-Jun Fan, Hong-Tao Hu

Background: Bone metastasis is a prevalent complication of malignant tumors, often resulting in restricted mobility, severe pain, and diminished quality of life.

Objective: This study aimed to assess the analgesic effect and safety of a co-ablation system that combines elements of hyperthermic ablation and cryoablation in patients with bone metastases.

Methods: This retrospective study included patients with histologically confirmed painful bone metastases treated with the co-ablation system between January and October 2024. Pain intensity was assessed using the numerical rating scale (NRS), and functional status was evaluated using the Karnofsky Performance Status score at baseline and during a 12-week follow-up. Technical success, adverse events, analgesic use, and pain response (defined as a ≥2-point reduction in NRS) were analyzed.

Results: Nine patients were included. Technical success was achieved in all procedures, with no procedure-related adverse events observed. Median NRS scores decreased progressively from 5 (IQR 4-6) at baseline to 2 (IQR 1-3) at 12 weeks. By the fourth week, 8 (88.9%) patients achieved a clinically meaningful pain reduction. Karnofsky Performance Status scores showed gradual improvement during follow-up. No patients required escalation of analgesic therapy, and some experienced dose reductions.

Conclusions: The co-ablation system appeared to be feasible and was associated with short-term pain reduction in patients with bone metastases, with no ablation-related adverse events observed.

背景：骨转移是恶性肿瘤的常见并发症，常导致活动受限、剧烈疼痛和生活质量下降。目的：本研究旨在评估一种结合热消融和冷冻消融的联合消融系统在骨转移患者中的镇痛效果和安全性。方法：本回顾性研究纳入2024年1月至10月间接受联合消融系统治疗的组织学证实的疼痛性骨转移患者。采用数值评定量表（NRS）评估疼痛强度，并在基线和12周随访期间使用Karnofsky性能状态评分评估功能状态。分析技术成功、不良事件、止痛药使用和疼痛反应（定义为NRS降低≥2分）。结果：纳入9例患者。所有手术均取得了技术上的成功，未观察到与手术相关的不良事件。NRS评分中位数从基线时的5分（IQR 4-6）逐渐下降到12周时的2分（IQR 1-3）。到第四周，8例（88.9%）患者实现了临床意义上的疼痛减轻。Karnofsky Performance Status评分在随访中逐渐改善。没有患者需要增加镇痛治疗，一些患者经历了剂量减少。结论：联合消融系统似乎是可行的，并且与骨转移患者的短期疼痛减轻有关，未观察到消融相关的不良事件。

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引用次数: 0

Correction: Social Media as a Platform for Cancer Care Decision-Making Among Women: Internet Survey-Based Study on Trust, Engagement, and Preferences. 更正：社交媒体作为女性癌症治疗决策的平台：基于互联网调查的信任、参与和偏好研究。

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-13 DOI: 10.2196/87683

Anna Rose Johnson, Grace Anne Longfellow, Clara N Lee, Benjamin Ormseth, Gary B Skolnick, Mary C Politi, Yonaira M Rivera, Terence Myckatyn

[This corrects the article DOI: 10.2196/64724.].

[更正文章DOI: 10.2196/64724]。

引用次数: 0

Remote Patient Monitoring Use Among Commercially Insured Adults With Cancer. 商业保险成年癌症患者远程监护的使用。

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-12 DOI: 10.2196/84788

Joseph H Joo, Changchuan Jiang, Jessica I Billig, Nadia Lieu, Shining Yang, Yujia Jin, Arthur S Hong, Joshua M Liao

Our study describes the characteristics of remote patient monitoring use among commercially insured patients with cancer from 2019 to 2023.

我们的研究描述了2019年至2023年商业保险癌症患者远程患者监测使用的特征。

引用次数: 0

Evaluation of the ALIBIRD mHealth Platform for Care of Patients With Lung Cancer: Prospective Pilot Study. ALIBIRD移动健康平台对肺癌患者护理的评估：前瞻性试点研究

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-11 DOI: 10.2196/69525

Jose M Iniesta-Chamorro, Maria Sereno, Beatriz Garrido-Rubiales, Marta Villarino Sanz, Isabel Espinosa-Salinas, Sandra Falagán Martínez, Gustavo Rubio Romero, Juan Moreno-Rubio, Beatriz Tabarés, Yolanda Martín, Irene Hernández de Córdoba, Maria Morales Parga, Natalia Molinero, M Victoria Moreno-Arribas, Guillermo Reglero Rada, Ana Ramírez de Molina, Enrique J Gómez, Enrique Casado

Background: Mobile health (mHealth) represents a promising instrument for optimizing symptom management and important lifestyle strategies that enhance self-care and the quality of health care for patients with cancer. The ALIBIRD mHealth platform is a digital health solution specifically designed for the telemonitoring of oncology patients, fostering patient empowerment and supporting clinical decision-making.Objective: The primary objective of this study was to evaluate the patient experience with the ALIBIRD platform. In addition, the study aimed to assess clinical outcomes, particularly in symptom management, nutritional status, and lifestyle, using patient-reported outcome measures (PROMs).Methods: The evaluation was conducted over a 30-week period in patients with advanced lung cancer receiving active treatment. Outcome variables included usability, patient experience, symptom burden, lifestyle behaviors (diet, physical activity, and sleep), nutritional status, PROMs, and system-generated clinical alerts. Through the mobile app, patients reported symptoms and completed integrated REDCap (Research Electronic Data Capture) questionnaires assessing lifestyle behaviors and PROMs, while receiving personalized recommendations informed by nutrigenetic and gut microbiota assessments. Daily activity and sleep data were automatically captured using the Fitbit Inspire wearable. Clinicians remotely monitored patient data using a web-based dashboard and performed clinical actions when required, including phone calls, therapeutic adjustments, referrals, and appointment rescheduling. Statistical analysis included descriptive summaries and pre-post comparisons of clinical and patient-reported outcomes.Results: Out of 20 patients recruited for the study, 14 completed the intervention. The System Usability Scale yielded a score of 90, indicating high usability. Among the 14 completers, adherence to scheduled questionnaires ranged from 94% to 100% for several instruments, and wearable-based monitoring ranged from 66% to 96% across visits. Overall, the ALIBIRD platform collected and processed 3589 patient-reported outcomes related to physical activity, 3468 related to sleep, 679 on-demand symptom entries, and 1524 completed questionnaires. Clinically, 143 alerts were resolved within an average of 2.05 days, resulting in 2 referrals to emergency rooms and 2 early detections of disease progressions. Furthermore, more than 2100 personalized recommendations contributed to a 21% (3/14 patients) increase in adherence to the Mediterranean diet and a 14% (2/14 patients) increase in moderate physical activity.Conclusions: The evaluation of the ALIBIRD implementation yielded promising results in that it facilitated the adoption of healthier lifestyle habits while enhancing health self-management among oncology patients. The ALIBIRD mHealth platform emerges

背景：移动医疗（mHealth）是一种很有前途的工具，可以优化症状管理和重要的生活方式策略，增强癌症患者的自我保健和医疗保健质量。ALIBIRD移动健康平台是一个专门为肿瘤患者远程监测设计的数字健康解决方案，促进患者赋权并支持临床决策。目的：本研究的主要目的是评估ALIBIRD平台的患者体验。此外，该研究旨在评估临床结果，特别是在症状管理、营养状况和生活方式方面，使用患者报告的结果测量（PROMs）。方法：对接受积极治疗的晚期肺癌患者进行为期30周的评估。结果变量包括可用性、患者体验、症状负担、生活方式行为（饮食、身体活动和睡眠）、营养状况、PROMs和系统生成的临床警报。通过移动应用程序，患者报告症状并完成评估生活方式行为和PROMs的综合REDCap（研究电子数据采集）问卷，同时接受营养和肠道微生物群评估的个性化建议。Fitbit Inspire可穿戴设备会自动捕捉日常活动和睡眠数据。临床医生使用基于网络的仪表板远程监控患者数据，并在需要时执行临床操作，包括电话、治疗调整、转诊和重新安排预约。统计分析包括描述性总结和临床和患者报告结果的前后比较。结果：在研究招募的20例患者中，有14例完成了干预。系统可用性量表得分为90分，表示高可用性。在14名完成者中，对于几种仪器，计划问卷的依从性从94%到100%不等，基于可穿戴设备的监测在访问期间从66%到96%不等。总体而言，ALIBIRD平台收集并处理了3589例患者报告的与身体活动相关的结果，3468例与睡眠相关的结果，679例按需症状条目和1524份完成的问卷。在临床上，143个警报在平均2.05天内得到解决，导致2例转诊到急诊室，2例早期发现疾病进展。此外，2100多项个性化建议使地中海饮食依从性增加了21%(3/14)，适度体育活动增加了14%（2/14）。结论：ALIBIRD实施的评估取得了可喜的结果，因为它促进了肿瘤患者采用更健康的生活习惯，同时增强了健康自我管理。ALIBIRD移动健康平台是一种有效的数字健康工具，可以更密切地监测患者，从而更明智地做出临床决策。

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引用次数: 0

User Experiences of a Chatbot for Supporting the Self-Management of Peripherally Inserted Central Catheter for Chemotherapy: Mixed Methods Study. 支持化疗外周置管中心导管自我管理的聊天机器人用户体验：混合方法研究。

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-11 DOI: 10.2196/81026

Bokyung Jo, Su Jin Kim, Min Jeong Kim, Nayeon Kim, Ayoung Lee, Hoyoung Kim, Mangyeong Lee, Juhee Cho

Background: A peripherally inserted central catheter (PICC) for vesicant or long-term chemotherapy is recommended for safe and sustainable drug delivery. However, maintaining its benefits requires regular and careful self-management. Although medical staff provide education and telephone consultation, proactive support accessible at any time or location remains limited. Therefore, we developed a rule-based chatbot to support PICC self-management.Objective: This study aimed to evaluate the feasibility of a chatbot designed to support PICC self-management by examining chatbot use rate, usability, and user experience.Methods: A mixed methods study was conducted from September to December 2022, adhering to the GRAMMS (Good Reporting of a Mixed Methods Study) guideline. Patients with cancer scheduled for PICC insertion and their caregivers were recruited, as PICC care is commonly performed by patients or cohabiting caregivers. All participants provided written informed consent. The chatbot was designed to provide structured responses based on prespecified dialog trees and to recognize users' intent using natural language processing. It was delivered through KakaoTalk and accessed on participants' personal mobile phones without requiring a separate app installation. Participants received face-to-face training at enrollment and were asked to voluntarily use the chatbot for 1 month. Baseline and postintervention surveys assessing usability were administered using paper-based questionnaires. Usage logs were collected from a secure researcher dashboard and analyzed for inquiry topics, free-text inputs, and fallback situations. Semistructured interviews were conducted approximately 1 month after the intervention during outpatient visits, with invitations by telephone, to explore participants' experiences regarding chatbot use. Quantitative data were analyzed descriptively to summarize participant characteristics, chatbot use, and usability outcomes, while qualitative interview data were analyzed using thematic analysis.Results: A total of 56 participants were included in the final analysis (mean age 55.4 years, SD 13.7; female: n=39, 70%). Among them, 28 (50%) used the chatbot at least once. Chatbot users were younger than nonusers (51.1 vs 59.6 y; P=.02). Of the 25 users who agreed to log analysis, 347 inquiries were recorded; frequent topics included catheter care (126 observations), managing daily life (85 observations), symptoms (72 observations), and heparin use (55 observations). Among the 23 users who completed the usability survey, 20 (87%) reported that the chatbot was helpful for PICC-related issues. Qualitative interviews (N=56) identified 3 major benefits-information accessibility, effective guidance, and psychosocial support-while also revealing unmet needs related to conversational issues, user experience issues, and lack of personalization.<stro

背景：为了安全、可持续的给药，建议在泡状或长期化疗中使用外周插入中心导管（PICC）。然而，要保持它的好处，就需要定期和仔细的自我管理。虽然医务人员提供教育和电话咨询，但在任何时间或地点可获得的主动支持仍然有限。因此，我们开发了一个基于规则的聊天机器人来支持人保的自我管理。目的：本研究旨在通过考察聊天机器人的使用率、可用性和用户体验来评估支持PICC自我管理的聊天机器人的可行性。方法：一项混合方法研究于2022年9月至12月进行，遵循GRAMMS（混合方法研究的良好报告）指南。由于PICC护理通常由患者或同居护理人员进行，因此招募了计划进行PICC插入的癌症患者及其护理人员。所有参与者均提供书面知情同意书。该聊天机器人被设计为基于预先指定的对话树提供结构化的响应，并使用自然语言处理来识别用户的意图。它通过KakaoTalk提供，无需单独安装应用程序就可以在参与者的个人手机上访问。参与者在注册时接受了面对面的培训，并被要求自愿使用聊天机器人一个月。评估可用性的基线和干预后调查使用纸质问卷进行。从安全的研究员仪表板收集使用日志，并分析查询主题、自由文本输入和回退情况。半结构化访谈在干预后大约1个月的门诊访问期间进行，通过电话邀请，探索参与者关于聊天机器人使用的经验。定量数据通过描述性分析来总结参与者特征、聊天机器人使用情况和可用性结果，而定性访谈数据则通过主题分析来分析。结果：最终分析共纳入56例受试者（平均年龄55.4岁，SD 13.7；女性：n=39, 70%）。其中28人（50%）至少使用过一次聊天机器人。聊天机器人用户比非用户年轻（51.1 vs 59.6； P= 0.02）。在同意记录分析的25个用户中，347个查询被记录下来；常见的主题包括导管护理（126例观察）、日常生活管理（85例观察）、症状（72例观察）和肝素使用（55例观察）。在完成可用性调查的23名用户中，20人（87%）表示聊天机器人对人保相关问题有帮助。定性访谈（N=56）确定了3个主要的好处——信息可访问性、有效的指导和社会心理支持——同时也揭示了与对话问题、用户体验问题和缺乏个性化相关的未满足需求。结论：基于规则的聊天机器人设计支持PICC自我管理显示出增强信息可及性、提供实用指导和提供社会心理支持的潜力。然而，与会话灵活性、界面可用性和个性化相关的限制突出表明，未来开发需要结合大型语言模型。有必要进行纵向和多地点研究，以评估持续的用户参与度和临床结果。

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引用次数: 0

The Longevity of Mobile Apps for Cancer Recovery: Scoping Review. 癌症康复的移动应用程序的寿命：范围审查。

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-11 DOI: 10.2196/82448

Kenneth Färnqvist, Luisa Thiele, Sophie Johnsson, Pernilla Lagergren, Anna Schandl

Background: The number of cancer survivors is steadily increasing worldwide, leading to an increased demand for long-term follow-up and supportive care. Many survivors face ongoing physical and psychosocial issues that highlight the need for innovative management approaches. Mobile health apps offer potential benefits by facilitating patient-led follow-up, self-management, and more efficient use of health care resources. Although the market for cancer-related mobile apps has grown rapidly, their sustainability and scientific basis remain unclear. In the European Union, the Medical Device Regulation (MDR), in effect since May 2021, introduced stricter criteria for classifying medical devices, including certain software apps. While aiming to improve patient safety, the MDR could pose challenges for small companies and academic developers, potentially limiting the availability of such apps. No scoping review has delineated changes in active apps before and after implementation of the legislation regulating medical devices.

Objective: This scoping review aimed to evaluate the current availability and longevity of English-language mobile apps supporting cancer recovery, with a specific focus on changes before and after the implementation of the European Union MDR, and to assess the extent to which these apps are supported by clinical evidence.

Methods: Searches were conducted in mobile app stores (Apple's App Store and Google Play) and literature databases (MEDLINE, Embase, Cochrane Library, and Web of Science), using predefined terms. Mobile apps targeting cancer recovery and published articles on their effectiveness were included. Two reviewers independently extracted data. A descriptive analysis was conducted to report trends in mobile device app availability and updates over time.

Results: A total of 151 mobile apps were identified in 2018. However, by 2024, only 45 of 151 (30%) were still available. Among these, 25 of 151 (17%) were updated within the past 2 years. During the search in December 2024, 1 new mobile app supported by scientific evidence was discovered. This mobile app was developed to assist cancer survivors in managing insomnia through cognitive behavioral therapy. Rapid turnover and a potential lack of sustainability in the mobile health app market for cancer survivors were evident, with most mobile apps identified in 2018 no longer available by 2024.

Conclusions: This review revealed a limited number of publicly available mobile apps that support cancer recovery. The longevity of existing mobile apps is limited, potentially because of regulatory and financial barriers. Prioritizing rigorous effectiveness trials, addressing implementation barriers, and developing sustainable business models are essential to ensure the long-term availability and success of mobile health apps in cancer survivorship care.

背景：世界范围内癌症幸存者的数量正在稳步增加，导致对长期随访和支持性护理的需求增加。许多幸存者面临着持续的身体和心理问题，这突出了创新管理方法的必要性。移动医疗应用程序通过促进患者主导的随访、自我管理和更有效地利用医疗资源，提供了潜在的好处。尽管与癌症相关的移动应用市场增长迅速，但它们的可持续性和科学基础仍不清楚。在欧盟，自2021年5月起生效的医疗器械法规（MDR）引入了更严格的医疗器械分类标准，包括某些软件应用程序。虽然旨在提高患者安全，但MDR可能会给小公司和学术开发者带来挑战，可能会限制此类应用程序的可用性。没有范围审查描述在实施医疗器械监管立法之前和之后活跃应用程序的变化。目的：本综述旨在评估目前支持癌症康复的英语移动应用程序的可用性和寿命，特别关注欧盟MDR实施前后的变化，并评估这些应用程序在多大程度上得到临床证据的支持。方法：在移动应用商店（Apple’s app Store和谷歌Play）和文献数据库（MEDLINE、Embase、Cochrane Library和Web of Science）中使用预定义的术语进行检索。针对癌症康复的移动应用程序和发表的关于其有效性的文章被纳入其中。两名审稿人独立提取数据。一项描述性分析报告了移动设备应用的可用性和更新趋势。结果：2018年共识别了151个移动应用程序。然而，到2024年，151个中只有45个（30%）仍然可用。其中，151个中有25个（17%）是在过去两年内更新的。在2024年12月的搜索中，发现了一个有科学证据支持的新移动应用程序。开发这款手机应用程序是为了帮助癌症幸存者通过认知行为疗法来控制失眠。针对癌症幸存者的移动健康应用市场的快速更替和潜在的缺乏可持续性是显而易见的，2018年确定的大多数移动应用程序到2024年将不再可用。结论：本综述揭示了支持癌症康复的公开可用移动应用程序数量有限。现有手机应用的寿命有限，可能是因为监管和财务障碍。优先进行严格的有效性试验，解决实施障碍，开发可持续的商业模式，对于确保移动健康应用程序在癌症幸存者护理中的长期可用性和成功至关重要。

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引用次数: 0

Generative AI Chatbots as Digital Adjuncts for Sexual Health Information After Prostate Cancer in Men Who Have Sex With Men: Auto-Netnographic Study. 生成人工智能聊天机器人作为与男性发生性关系的男性前列腺癌后性健康信息的数字辅助工具：自动网络研究。

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-09 DOI: 10.2196/81745

Mats Christiansen, Henrik Eriksson, Lisbeth Fagerström

Background: Sexual health concerns following prostate cancer treatment are common yet often insufficiently addressed in clinical practice, particularly among men who have sex with men. These individuals may face additional barriers stemming from heteronormative assumptions, limited disclosure, and a lack of culturally tailored information. As generative artificial intelligence (GenAI) chatbots become increasingly accessible, patients are using these systems to seek sensitive health information outside traditional care settings. While prior research has focused on the accuracy and safety of chatbot-generated health advice, less attention has been paid to how responses are framed and experienced in sexual minority contexts.Objective: This study aimed to describe and compare how 4 GenAI chatbots respond to questions about sexual health following prostate cancer treatment, with a focus on the needs of a gay man, and to interpret these responses using netnographic and actor-network theory perspectives.Methods: A qualitative exploratory study using auto-netnography was conducted. In February-March 2025, the first author interacted once with 4 widely used GenAI chatbots-ChatGPT (GPT-4o; Open AI), Claude (3.5 Sonnet; Anthropic), Copilot (GPT-4 Turbo; Microsoft), and Gemini (2.0 Flash; Google)-while assuming the role of a simulated "mock patient." Two standardized prompts were used verbatim across all platforms: an initial prompt addressing sexual health concerns after prostate cancer treatment and a supplementary prompt focusing on sexual minority-specific issues, including same-sex practices. Chatbot outputs were treated as system-generated data and analyzed qualitatively, integrating system-generated text with reflexive experiential engagement and attention to interactional framing, emotional attunement, specificity, and performative features. The analysis did not assess clinical effectiveness, safety, or generalizability.Results: Across platforms, chatbot responses addressed treatment-related sexual health concerns using generally inclusive language, with variation in emotional tone, specificity, and cultural sensitivity. Interactional features included the scope and framing of clinical information, encouragement of dialogue, self-care advice, and explicit discussion of same-sex sexual practices. No obvious fabricated claims were identified; however, contextual inaccuracies were observed. Responses were mapped along 2 intersecting continua-logical-to-empathetic orientation and general-to-specific framing-yielding 4 interactional styles: structured overview, rational clarity, compassionate perspective, and compassionate precision. This 4-quadrant framework served as an interpretive heuristic and does not constitute an evaluation of quality or effectiveness.Conclusions: The findings indicate that contemporary GenAI chatbots, when used as d

背景：前列腺癌治疗后的性健康问题很常见，但在临床实践中往往没有得到充分解决，特别是在男男性行为者中。这些人可能会面临来自异性恋假设、有限的信息披露和缺乏文化定制信息的额外障碍。随着生成式人工智能（GenAI）聊天机器人变得越来越容易获得，患者正在使用这些系统在传统护理环境之外寻求敏感的健康信息。虽然之前的研究主要集中在聊天机器人产生的健康建议的准确性和安全性上，但很少有人关注性少数群体的回应是如何构建和体验的。目的：本研究旨在描述和比较4个GenAI聊天机器人对前列腺癌治疗后性健康问题的反应，重点关注男同性恋者的需求，并从网络学和行动者网络理论的角度解释这些反应。方法：采用自动网络图进行定性探索性研究。在2025年2 - 3月，第一作者与4个广泛使用的GenAI聊天机器人——chatgpt （gpt - 40; Open AI）、Claude （3.5 Sonnet; Anthropic）、Copilot （GPT-4 Turbo; Microsoft）和Gemini （2.0 Flash；谷歌）——进行了一次互动，同时扮演了一个模拟的“模拟病人”。两个标准化提示在所有平台上逐字逐句使用：一个初始提示解决前列腺癌治疗后的性健康问题，一个补充提示侧重于性少数群体特有的问题，包括同性行为。聊天机器人输出被视为系统生成的数据，并进行定性分析，将系统生成的文本与反身性体验参与和对互动框架、情感调节、特异性和表演特征的关注相结合。该分析没有评估临床有效性、安全性或普遍性。结果：在各个平台上，聊天机器人的回应使用普遍包容的语言来解决与治疗相关的性健康问题，在情感语气、特异性和文化敏感性方面有所不同。互动特征包括临床信息的范围和框架，鼓励对话，自我护理建议，以及对同性性行为的明确讨论。没有发现明显捏造的说法；然而，语境的不准确性被观察到。反应沿着两个相交的连续方向——逻辑到移情取向和一般到特定框架——绘制，产生4种互动风格：结构化概述、理性清晰、同情视角和同情精确。这个四象限框架作为解释性启发式，并不构成质量或有效性的评估。结论：研究结果表明，当代GenAI聊天机器人，当被用作数字辅助工具时，可能会制定出在特定性健康互动中可被视为支持性，文化敏感性和LGBTQI+（女同性恋，男同性恋，双性恋，变性人，酷儿和双性人）包容性的沟通风格。虽然这些系统缺乏道德意识，不能取代专业护理，但它们的行为反应可以通过促进反思和获取敏感信息来补充临床实践。该研究强调，通过用户和人工智能系统之间的社会物质互动，而不是展示普遍的性能或临床可靠性，可能会出现类似护理的意义。

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引用次数: 0

Patient and Clinician Perspectives on Expanding Telehealth Use for Older Adults Across the Cancer Control Continuum: Mixed Methods Study. 扩大远程医疗在老年人癌症控制连续统中的应用：混合方法研究的患者和临床医生的观点。

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-09 DOI: 10.2196/73058

Robin T Higashi, Bella Etingen, Jessica Lee, Suzanne Cole, John C Mansour, Alice Zhao, Timothy P Hogan

Background: Reliance on telehealth increased dramatically during the COVID-19 pandemic, introducing new opportunities to consider the use of telehealth across the cancer control continuum. However, patient, clinician, and staff perspectives about the types of cancer care appointments that are considered appropriate and the clinical care needs to support expanded remote care services are limited. Understanding older adults' diverse technology needs and perspectives is especially important given that they comprise a large and growing proportion of patients with cancer.Objective: This study aimed to describe the perceptions and experiences of older patients with cancer and their clinical care team members regarding the expansion of telehealth use across the cancer control continuum and to solicit suggestions about how to support telehealth use for cancer care delivery.Methods: Using a convergent mixed methods design, we surveyed and interviewed patients aged ≥60 years, clinicians, and staff at a comprehensive cancer center in the southern United States between December 2020 and November 2021. Interview questions were rooted in the sociotechnical model, which proposes 8 interrelated dimensions representing factors influencing the design, use, and outcomes associated with health information technologies. Patient survey domains included telehealth experience and satisfaction and factors affecting telehealth perceptions and use; clinician survey domains included contexts of telehealth appropriateness, training, and barriers and facilitators to telehealth service provision. Survey data were analyzed using descriptive statistics. Qualitative data were thematically analyzed using a combined deductive and inductive approach.Results: We received completed surveys from 128 patients (567 invited) and 106 clinicians and staff (146 invited). We completed 14 patient (29 invited) and 20 clinician and staff (22 invited) interviews. Across all participants, most agreed or strongly agreed that multiple cancer care appointment types should be offered via telehealth, including discussing treatment side effects (75/102, 73.5% of patients and 66/94, 70.2% of clinicians and staff), results communication (71/102, 69.6% of patients and 65/94, 69.1% of clinicians and staff), and treatment follow-up (67/102, 65.7% of patients and 52/93, 55.9% of clinicians and staff). In interviews, participants elaborated on factors influencing the appropriateness of telehealth versus in-person appointments, including symptom severity, type of cancer, and purpose of the appointment. Many patient and staff suggestions focused on ways to address digital literacy gaps, while clinicians recommended improving clinic workflows, infrastructure, and training.Conclusions: Overall, clinicians, staff, and older patients with cancer all responded positively toward expanding telehealth use

背景：在2019冠状病毒病大流行期间，对远程医疗的依赖急剧增加，这为考虑在整个癌症控制连续体中使用远程医疗提供了新的机会。然而，患者、临床医生和工作人员对癌症护理预约的类型以及支持扩展远程护理服务的临床护理需求的看法是有限的。考虑到老年人在癌症患者中所占的比例越来越大，了解老年人不同的技术需求和观点尤为重要。目的：本研究旨在描述老年癌症患者及其临床护理团队成员对在癌症控制连续体中扩大远程医疗使用的看法和经验，并就如何支持远程医疗用于癌症护理提供征求建议。方法：采用融合混合方法设计，我们在2020年12月至2021年11月期间对美国南部一家综合癌症中心的年龄≥60岁的患者、临床医生和工作人员进行了调查和访谈。访谈问题植根于社会技术模型，该模型提出了8个相互关联的维度，代表影响与卫生信息技术相关的设计、使用和结果的因素。患者调查领域包括远程医疗体验和满意度以及影响远程医疗认知和使用的因素；临床医生调查领域包括远程医疗适宜性背景、培训以及远程医疗服务提供的障碍和促进因素。调查数据采用描述性统计进行分析。定性数据的主题分析使用结合演绎和归纳的方法。结果：我们收到了来自128名患者（567名受邀）和106名临床医生和工作人员（146名受邀）的完整调查。我们完成了14名患者（29名被邀请）和20名临床医生和工作人员（22名被邀请）的访谈。在所有参与者中，大多数人同意或强烈同意应通过远程医疗提供多种癌症护理预约类型，包括讨论治疗副作用（75/102,73.5%的患者和66/94,70.2%的临床医生和工作人员），结果沟通（71/102,69.6%的患者和65/94,69.1%的临床医生和工作人员），以及治疗随访（67/102,65.7%的患者和52/93,55.9%的临床医生和工作人员）。在访谈中，参与者详细阐述了影响远程保健与面对面预约是否适当的因素，包括症状严重程度、癌症类型和预约目的。许多患者和工作人员的建议侧重于解决数字素养差距的方法，而临床医生则建议改善诊所工作流程、基础设施和培训。结论：总体而言，临床医生、工作人员和老年癌症患者都积极响应在多种癌症和癌症控制连续体的预约类型中扩大远程医疗的使用。患有癌症的老年人通常对癌症护理的远程医疗感兴趣，特别是如果将解决数字素养差距的战略纳入其中。临床医生和工作人员表示需要专门培训和基础设施，以优化远程保健的吸收和服务的提供。

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引用次数: 0

Reinforcement Learning-Based Digital Therapeutic Intervention for Postprostatectomy Incontinence: Development and Pilot Feasibility Study. 基于强化学习的数字治疗干预前列腺切除术后尿失禁：发展和试点可行性研究。

IF 2.7 Q2 ONCOLOGY

JMIR Cancer

Pub Date : 2026-02-06 DOI: 10.2196/83375

Fan Fan, Hao Huang, Jingwen Yan, Chao-Yue Xu, Xiuhua Wu, Chunmei Zhou, Dandan Wen, Hai Huang, Ho Cheung Li, Yihong Qiu

Background: Postprostatectomy incontinence (PPI) is a common complication after robot-assisted radical prostatectomy and significantly impairs patients' quality of life. Although behavioral interventions such as pelvic floor muscle training and bladder diaries are evidence-based, their effectiveness is often limited by poor adherence and lack of personalization.Objective: This study aimed to develop and evaluate a reinforcement learning (RL)-driven clinical behavioral intervention-supporting system (CBISs) for adaptive, personalized rehabilitation in patients with PPI.Methods: The study comprised 2 sequential stages. First, the CBISs was developed through (1) construction of a medical record database from a prospective cohort of PPI patients using standardized 3-day bladder diaries, (2) design of functional modules and user interfaces based on clinical rehabilitation needs, and (3) development of an RL model using XGBoost (extreme gradient boosting) and Bayesian optimization to generate individualized training plans. Second, a separate cohort of 16 patients participated in a single-arm, pre-post pilot study to evaluate feasibility and preliminary outcome trends over a 3-month intervention period, with assessments based on bladder diary parameters and system usage metrics.Results: The CBISs successfully implemented an adaptive, closed-loop behavioral rehabilitation framework that dynamically tailored training recommendations according to individual voiding patterns, fluid intake behaviors, and adherence signals. Feasibility outcomes were favorable, with high system engagement observed throughout the intervention (mean usage frequency 5.2, SD 1.1 times per day). In exploratory pre-post analyses (n=16), consistent directional improvements were observed across multiple outcomes. Mean daytime urinary frequency decreased from 5.74 (SD 1.21) episodes per day to 4.69 (SD 1.08) episodes per day, while median nighttime urinary frequency declined from 1.8 (IQR 1.6-2.2) episodes per night to 1.0 (IQR 1.0-1.6) episodes per night. Median incontinence episodes were reduced from 7.0 (IQR 6.0-11.0) episodes per day to 4.0 (IQR 2.0-6.0) episodes per day. Objective urine leakage measured by the 1-hour pad test decreased from a median of 8.5 (IQR 4.0-19.0) g to 3.5 (IQR 2.0-9.0) g. Patient-reported symptom burden, assessed using the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-UI SF), showed a median reduction from 14.0 (IQR 12.0-20.0) points to 9.0 (IQR 6.0-16.0) points. Although several within-participant changes were statistically detectable, effect magnitudes varied across individuals. Given the single-arm design, small sample size, and lack of a control group, findings are presented as exploratory and hypothesis-generating rather than confirmatory of clinical efficacy.Conclusions: The CBISs represents the first RL-powe

背景：前列腺切除术后尿失禁（PPI）是机器人辅助根治性前列腺切除术后常见的并发症，严重影响患者的生活质量。尽管骨盆底肌肉训练和膀胱日记等行为干预是基于证据的，但其有效性往往受到依从性差和缺乏个性化的限制。目的：本研究旨在开发和评估强化学习（RL）驱动的临床行为干预支持系统（cbis），用于PPI患者的适应性、个性化康复。方法：研究分为2个连续阶段。首先，cbis通过(1)使用标准化的3天膀胱日记构建PPI前瞻性队列患者的病历数据库，(2)根据临床康复需求设计功能模块和用户界面，(3)使用XGBoost（极端梯度提升）和贝叶斯优化开发RL模型来生成个性化训练计划。其次，一个单独的队列，16名患者参加了一项单臂，前后试点研究，评估可行性和初步结果趋势，为期3个月的干预期，评估基于膀胱日记参数和系统使用指标。结果：ciss成功地实施了一个自适应的闭环行为康复框架，该框架根据个人排尿模式、液体摄入行为和依从性信号动态定制训练建议。可行性结果是有利的，在整个干预过程中观察到较高的系统参与度（平均使用频率5.2次，SD每天1.1次）。在探索性的前后分析（n=16）中，在多个结果中观察到一致的方向性改善。平均白天尿频从5.74 （SD 1.21）次/天下降到4.69 （SD 1.08）次/天，而夜间尿频中位数从1.8 （IQR 1.6-2.2）次/天下降到1.0 （IQR 1.0-1.6）次/天。平均尿失禁次数从每天7.0 （IQR 6.0-11.0）次减少到每天4.0 （IQR 2.0-6.0）次。通过1小时尿垫试验测量的尿漏从中位数8.5 (IQR 4.0-19.0) g降至3.5 (IQR 2.0-9.0) g。使用国际失禁问卷短表咨询（ICIQ-UI SF）评估患者报告的症状负担，中位数从14.0 （IQR 12.0-20.0）分降至9.0 （IQR 6.0-16.0）分。虽然在统计上可以检测到一些参与者内部的变化，但影响程度在个体之间是不同的。考虑到单臂设计、小样本量和缺乏对照组，研究结果是探索性的和假设生成的，而不是临床疗效的证实。结论：cbis代表了首个rl驱动的PPI数字治疗系统，实现了适应性、循证行为优化。通过解决静态康复方案的局限性和依从性下降，它为个性化PPI管理提供了一种可扩展的方法。需要未来的多中心试验来证实其临床有效性。

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引用次数: 0

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