JMIR Cancer最新文献

Background: Electronic health records (EHRs) are a cornerstone of modern health care delivery, but their current configuration often fragments information across systems, impeding timely and effective clinical decision-making. In gynecological oncology, where care involves complex, multidisciplinary coordination, these limitations can significantly impact the quality and efficiency of patient management. Few studies have examined how EHR systems support clinical decision-making from the perspective of end users. This study aimed to explore multiprofessional experiences of EHR use in gynecological oncology and to develop a co-designed informatics platform to improve decision-making for ovarian cancer care.

Objective: This study aims to evaluate the perspectives of health care professionals on retrieving routine clinical data from EHRs in the management of ovarian cancer and to design an integrated informatics platform that supports clinical decision-making.

Methods: We conducted a national cross-sectional survey of 92 UK-based professionals working in gynecological oncology, including oncologists, nurses, radiologists, and other specialists in ovarian cancer. The web-based questionnaire, combining quantitative and free-text responses, assessed their experiences with EHR use, focusing on information retrieval, usability challenges, perceived risks, and benefits. In parallel, a human-centered design approach involving health care professionals, data engineers, and informatics experts codeveloped a digital informatics platform that integrates structured and unstructured data from multiple clinical systems into a unified patient summary view for clinical decision-making. Natural language processing was applied to extract genomic and surgical information from free-text records, with data pipelines validated by clinicians against original clinical system sources.

Results: Among 92 respondents, 84 out of 91 (92%) routinely accessed multiple EHR systems, with 26 out of 91 (29%) using 5 or more. Notably, 16 out of 92 respondents (17%) reported spending more than 50% of their clinical time searching for patient information. Key challenges included lack of interoperability (35/141 reported challenges, 24.8%), difficulty locating critical data such as genetic results (57/85 respondents, 67%), and poor organization of information. Only 10 out of 92 professionals (11%) strongly agreed that their systems provided well-organized data for clinical use. While ease of access to patient data was a key benefit, 54 out of 90 respondents (60%) reported lacking access to comprehensive patient summaries. To address these issues, our co-designed informatics platform consolidates disparate patients' data from different EHR systems into a single visual display to support clinical decision-making and audit.

Conclusions: Current EHR systems are suboptimal for support

Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative. However, its acceptance, reliability, and impact on the screening experience remain underexplored.

Objective: This study aimed to explore women's perceptions of AI-enhanced thermography (ThermoBreast) as an alternative to mammography. It aims to identify barriers and motivators related to breast cancer screening and assess how ThermoBreast might improve the screening experience.

Methods: A mixed methods approach was adopted, combining an online survey with follow-up focus groups. The survey captured women's knowledge, attitudes, and experiences related to breast cancer screening and was used to recruit participants for qualitative exploration. After the focus groups, the survey was relaunched to include additional respondents. Quantitative data were analyzed using SPSS (IBM Corp), and qualitative data were analyzed in MAXQDA (VERBI software). Findings from both strands were synthesized to redesign the breast cancer screening journey.

Results: A total of 228 valid survey responses were analyzed. Of 228, 154 women (68%) had previously undergone mammography, while 74 (32%) had not. The most reported motivators were belief in prevention (69/154, 45%), invitations from screening programs (68/154, 44%), and doctor recommendations (45/154, 29%). Among nonscreeners, key barriers included no recommendation from a doctor (39/74, 53%), absence of symptoms (27/74, 36%), and perceived age ineligibility (17/74, 23%). Pain, long appointment waits, and fear of radiation were also mentioned. In total, 18 women (mean age 45.3 years, SD 13.6) participated in 6 focus groups. Participants emphasized the importance of respectful and empathetic interactions with medical staff, clear communication, and emotional comfort-factors they perceived as more influential than the screening technology itself. ThermoBreast was positively received for being contactless, radiation-free, and potentially more comfortable. Participants described it as "less traumatic," "easier," and "a game changer." However, concerns were raised regarding its novelty, lack of clinical validation, and data privacy. Some participants expressed the need for human oversight in AI-supported procedures and requested more information on how AI is used. Based on these insights, an updated screening journey was developed, highlighting improvements in preparation, appointment booking, privacy, and communication of results.

Conclusions: While AI-driven thermography shows promise as

Background: Effective prevention and treatment are urgently needed, since gastric cancer (GC) poses a grave threat to the health and well-being of patients. The 5 East Asian countries (China, Japan, North Korea, South Korea, and Mongolia) represent one of the most significant regions globally in terms of GC burden.

Objective: The goal of this study is to examine the patterns and trends of GC across 5 East Asian countries between 1990 and 2021.

Methods: We retrieved data from the Global Burden of Disease Study (GBD) 2021 regarding the prevalence, incidence, mortality, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life years (DALYs) associated with GC in 5 East Asian countries from 1990 to 2021. We further assessed the burden of GC according to age and sex. We used decomposition analysis to examine the changes in the number of new cases, patients, and deaths related to GC. We also used Joinpoint (Joinpoint Regression Program, Version 5.1.0) and age-period-cohort analysis methods to interpret the epidemiological characteristics of GC. Autoregressive integrated moving average model (ARIMA) and Bayesian age-period-cohort (BAPC) prediction models were used to forecast the GC burden by 2036.

Results: Among the 5 East Asian countries, China recorded the highest incidence, prevalence, death, YLLs, YLDs, and DALYs in both 1990 and 2021. From 1990 to 2021, the age-standardized rates for prevalence, mortality, incidence, YLDs, YLLs, and DALYs across the 5 East Asian countries showed an overall decline, though they remained higher than the global average. In all 5 East Asian countries, individuals aged 65 years and older consistently exhibited the highest rates for prevalence, incidence, mortality, YLDs, YLLs, and DALYs. The prevalence rate in South Korea, the incidence rate in North Korea and Mongolia, and the mortality rate in China are influenced by aging, surpassing the global aging average.

Conclusions: The disease burden of GC in the 5 East Asian countries has consistently ranked high over the past 3 decades, particularly among the older individuals. The burden of GC in the 5 East Asian countries is expected to present a major public health challenge, primarily driven by the large population size and the aging demographic.

Background: Patients with hepatocellular carcinoma (HCC) exhibit a high rate of recurrence and poor prognosis after surgery, and effective prognostic indicators and stratification strategies are currently lacking. Hence, this study proposes new prognostic markers to provide a theoretical basis for patients with HCC.

Objective: We aim to build and evaluate a model estimating the effect of alpha-fetoprotein-tumor size ratio (ATR) on the prognosis of patients undergoing hepatectomy for HCC.

Methods: We retrospectively reviewed hospital records to identify patients who underwent hepatectomy for HCC at the First Affiliated Hospital of Guangxi Medical University from January 2013 to December 2018. Outcomes (recurrence events and mortality) not available in the outpatient medical records were determined through telephone interviews until February 2022. The optimal cutoff value was determined using X-tile (Yale School of Medicine). Independent risk factors for prognosis were investigated by Cox regression modeling, and between-group differences were reduced through propensity score matching. A predictive model for HCC prognosis was constructed using a nomogram, and the predictive performance of the model was evaluated using the C-index.

Results: Of the 1628 eligible patients, 1204 patients were included in the analysis. Patients were stratified into low, medium, and high ATR groups with X-tile. Before propensity score matching, ATR was identified as an independent risk factor for overall survival (low vs medium: HR 1.41, 95% CI 1.03-1.94; P=.03; medium versus high: HR 1.59, 95% CI 1.02-2.47; P=.04) and relapse-free survival (low vs medium: HR 1.33, 95% CI 1.03-1.70; P=.03; medium versus high: HR 2.10, 95% CI 1.40-3.15; P<.001) of patients with HCC following hepatectomy. A nomogram incorporating ATR, China Clinic Liver Cancer staging, bleeding, and postoperative transcatheter arterial chemoembolization was developed to predict moderate predictive efficacy for overall survival (C-index: 0.73) and relapse-free survival (C-index: 0.73). ATR was found to be associated with microvascular, macroinvasion, and poor tumor differentiation.

Conclusions: ATR is an independent prognostic risk factor in patients with HCC after hepatectomy and is associated with microvascular, macroinvasion, and poor tumor differentiation.

Background: In Manitoba, Canada, the impact of the COVID-19 pandemic on cancer care delivery included, but was not limited to, disruption of many routine health care services, and the rapid introduction of both social distancing and virtual care. Little was known about how COVID-19-related changes to cancer care delivery would impact patient satisfaction with care and care coordination.

Objective: This report aims to present and interpret findings of an online survey of people with oncology-related conditions in Manitoba, Canada, during the COVID-19 pandemic, exploring patient satisfaction and care coordination.

Methods: A link to an online survey was made available to patients receiving cancer treatment in Manitoba, Canada, between July 31, 2020, and February 28, 2022. The survey included validated patient-reported experience measures (PREMs) for patient satisfaction and care coordination. Analysis included the generation of descriptive statistics and logistic regression, including univariate and multivariate analysis using stepwise model building. The survey results were interpreted using fit theory as a theoretical lens.

Results: A total of 203 responses were collected, of which 154 had completed responses for all PREM measures and were included in the analysis. Response rate is estimated at 3.3%-2.0%. The average age was 65 (SD 11.7) years. Most respondents were male (n=79, 52.7%). Most respondents were being treated with curative intent (n=81, 53.6%). The most common type of cancer was breast (n=41, 26.6%). Univariate analysis demonstrated that ages 60-69 years were associated with above average patient satisfaction (OR 2.205, 95% CI 1.045-4.624; P=.04). Age <60 years (OR 0.437, 95% CI 0.204-0.934; P=.03) and European Cooperative Group functional status (ECOG) ≥2 (OR 0.327, 95% CI 0.137-0.782; P=.01) were associated with below average patient satisfaction. Age <60 years, ECOG ≥2, and hematological cancer were selected through stepwise multivariate model building, resulting in an explanatory model (R2=0.129) of patient satisfaction. ECOG ≥2 was associated with below-average care coordination (OR 0.357, 95% CI 0.145-0.880; P=.03), and was the only identified predictor of care coordination, with no explanatory multivariate model generated. Fit theory supports that the level of patient satisfaction and care coordination in each population subset inversely reflects a relative level of unmet supportive care need.

Conclusions: Survey respondents with poor functional status, those outside the 60-69 years age range, and those with nonhematological malignancies likely experience increased unmet supportive care needs compared with their counterparts. Further research is needed to determine whether these findings reflect transient phenomena related to the COVID-19 pandemic, selection biases associated with the survey method used, or underlying

Background: Artificial intelligence is reshaping cancer care, but little is known about how people with cancer perceive its integration into their care. Understanding these perspectives is essential to ensuring artificial intelligence adoption aligns with patient needs and preferences while supporting a patient-centered approach.

Objective: The aim of this study is to synthesize existing literature on patient attitudes toward artificial intelligence in cancer care and identify knowledge gaps that can inform future research and clinical implementation.

Methods: A scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. MEDLINE, Embase, PsycINFO, and CINAHL were searched for peer-reviewed primary research studies published until February 1, 2025. The Population-Concept-Context framework guided study selection, focusing on adult patients with cancer and their attitudes toward artificial intelligence. Studies with quantitative or qualitative data were included. Two independent reviewers screened studies, with a third resolving disagreements. Data were synthesized into tabular and narrative summaries.

Results: Our search yielded 1240 citations, of which 19 studies met the inclusion criteria, representing 2114 patients with cancer across 15 countries. Most studies used quantitative methods (9/19, 47%) such as questionnaires or surveys. The most studied cancers were melanoma (375/2114, 17.7%), prostate (n=323, 15.3%), breast (n=263, 12.4%), and colorectal cancer (n=251, 11.9%). Although patients with cancer generally supported artificial intelligence when used as a physician-guided tool (9/19, 47%), concerns about depersonalization, treatment bias, and data security highlighted challenges in implementation. Trust in artificial intelligence (10/19, 53%) was shaped by physician endorsement and patient familiarity, with greater trust when artificial intelligence was physician-guided. Geographic differences were observed, with greater artificial intelligence acceptance in Asia, while skepticism was more prevalent in North America and Europe. Additionally, patients with metastatic cancer (99/2114, 5%) were underrepresented, limiting insights into artificial intelligence perceptions in this population.

Conclusions: This scoping review provides the first synthesis of patient attitudes toward artificial intelligence across all cancer types and highlights concerns unique to patients with cancer. Clinicians can use these findings to enhance patient acceptance of artificial intelligence by positioning it as a physician-guided tool and ensuring its integration aligns with patient values and expectations.

Background: An increasing number of early-stage breast cancer (EBC) survivors and limited health care resources have raised interest in developing digital methods for communication between patients and health care personnel. In 2015, Helsinki University Hospital (HUS) Comprehensive Cancer Center (CCC) launched a digital solution called Noona (Helsinki University Hospital; Noona Healthcare) for patients with cancer, which allows patients to report their symptoms or side effects and ask questions with a computer or smart mobile device.

Objective: In this study, we compare the cost and contacts of surveillance of EBC by 2 follow-up methods: digital solution and phone calls during their first year of follow-up outside preplanned visits.

Methods: This was a prospective, open-label, randomized crossover study. After postoperative radiotherapy, patients with EBC were randomized to surveillance with either a digital solution or phone calls in addition to routine follow-up visits. After 6 months, the patient switched to the alternative follow-up method. All patients were thus exposed to both follow-up methods, and the order was determined by randomization. Hospital contacts and the costs of specialized health care were extracted from the Ecomed database of the Helsinki and Uusimaa Hospital District. The Ecomed database records all hospital costs. The costs of follow-up visits and diagnostics at the HUS CCC were analyzed in a repeated measurements general linear model analysis.

Results: The study extended from July 2015 to January 2017. Of 765 patients, 734 were included in the final analyses. For the digital solution group, the mean number of contacts per patient was 1.06 (SD 1.57) during the first 6-month period and 1.22 (SD 1.04) in the second period, with associated costs of €269 (US $313.21) and €311 (US $362.11). Similarly, in the phone call group, the mean number of contacts increased from 0.95 (SD 1.39) to 1.24 (SD 1.14) with the costs of €236 (US $274.78) and €344 (US $400.53), respectively. There were no statistically significant differences in the number of outpatient contacts (P=.46 and P=.35) or total costs (P=.80 and P=.12) between the 2 follow-up methods or randomization groups.

Conclusions: We did not find any statistically significant differences in the total cost of follow-up of EBC by digital solution or phone calls. The number of visits and costs were higher during the latter follow-up period, probably due to the scheduled routine 1-year visit. There were more visits and higher costs in the digital solution group during the first 6 months, but these were higher in the phone call group during the latter 6-month period. This shows that the digital solution may enable faster access to outpatient services than conventional follow-up.

Background: Advances in research and modes of information delivery provide new opportunities to access medical information. Despite this, patient information needs on head and neck cancer (HNC) treatment are not sufficiently met.

Objective: The aim is to investigate (1) information content required for patients with HNC and their caregivers to support confident decisions about their treatment, (2) information needs by role (eg, patient and caregiver), and (3) the preferred format or mode of information delivery. Results will be used to inform the development and testing of a decision aid for this patient population.

Methods: A scoping review was conducted using the Arksey and O'Malley and Levac et al frameworks. The search was carried out in CINAHL, MEDLINE, Embase, and Cochrane Central Register of Controlled Trials and limited to the English language between 2012 and the search date of September 20, 2022. Studies were dual-screened against inclusion and exclusion criteria, central to which was a focus on information needs within the context of decision-making. Data were extracted from the articles using prespecified criteria into a data extraction sheet that was pilot-tested and refined prior to its application. Reporting followed the research questions and was guided by PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews).

Results: A total of 10,495 publications were identified, with 30 articles suitable for data extraction. High information needs included details of the diagnosis (3/30, 10%), purpose (6/30, 20%), and risks (10/30, 33%) of medical procedures; strategies for eating and speaking during and after treatment (6/30, 20%); lifestyle guidelines for survivorship (4/30, 13%); and facts about the human papillomavirus (2/30, 7%). Moderate information needs included the physical (10/30, 33%) and psychological (17/30, 57%) domains of posttreatment, treatment options (6/30, 20%), strategies to improve communication with health care providers (8/30, 27%), and nutrition (8/30, 27%). Information needs of patients with HNC and their caregivers evolved through the phases of treatment, highlighting the need for relevant information to support collaborative decision-making with their health care providers. Caregiver needs were underrepresented (5/30, 17%), but more information on stress reduction strategies for the patient, how to play a role in treatment decisions, and where to obtain the best medical care for the patient was identified. The preferred mode of delivery for information varied and reflected the age, gender, and country of the sample populations.

Conclusions: Information needs of patients with HNC and their caregivers are not being met to a satisfactory level, evidenced by the breadth of outstanding needs. Health care providers must consider evolving patient and caregiv