Lung cancer is one of the most commonly diagnosed cancers worldwide and the leading cause of cancer-related mortality. Global studies have highlighted the importance of awareness of lung cancer signs and symptoms, as it influences health care seeking, diagnosis timing, and treatment outcomes. Despite the high prevalence of both lung cancer and smoking in Jordan, no studies have assessed lung cancer awareness among the Jordanian population. This study is the first in Jordan to reveal the levels of awareness of lung cancer signs and symptoms, risk factors, and screening and to identify factors associated with the awareness level. This study aimed to explore the awareness of lung cancer risk factors, signs and symptoms, and screening in the Jordanian population and the factors determining the levels of awareness. A cross-sectional survey was conducted across all 12 governorates of Jordan, including 498 adult participants. Data were collected using a structured questionnaire covering sociodemographic characteristics and awareness about lung cancer signs, symptoms, risk factors, and screening. Items were derived from the Lung Cancer Awareness Measure Toolkit, version 2.1, 2011. Awareness scores for lung cancer risk factors, signs and symptoms, and overall lung cancer awareness were calculated. Multivariate linear regression was used to identify significant predictors of awareness scores. Multivariate logistic regression was used to determine significant predictors of lung cancer screening awareness. The mean lung cancer signs and symptoms awareness score was 5.4 (SD 4.9) out of 14, while the mean risk factor awareness score was 33.0 (SD 5.6) out of 45. The most recognized symptoms were coughing up blood (n=297, 59.6%) and pain upon breathing (n=237, 47.6%), while cigarette smoking (n=403, 80.9%) and exposure to air pollution (n=339, 68.1%) were the most recognized risk factors. Only 41.6% (n=207) of the participants had heard of lung cancer screening, while 79.3% (n=395) believed that screening improves survival. Being a smoker was predictive of lower awareness of lung cancer signs, symptoms, and risk factors, while a higher educational level and having a friend or relative previously diagnosed with lung cancer were associated with higher levels of awareness. This study revealed a low level of awareness of lung cancer signs and symptoms, risk factors, and screening in the Jordanian population. Further studies are needed to identify effective strategies for improving awareness, especially among high-risk populations.

Electronic medical record (EMR) systems have been associated with better clinical workflows and fewer documentation errors. However, evidence regarding their effect on time-sensitive leukemia care in public hospitals in Latin America remains limited. This study aimed to compare 60-day mortality and urgent supportive-care processes between 2 tertiary public hospitals in Mexico with different documentation models (integrated EMR vs traditional physical records [TPR]), under the hypothesis that digital workflows may facilitate more timely treatment. We conducted a retrospective natural experiment including 274 patients with newly diagnosed acute leukemia treated between February 2023 and April 2025. Clinical characteristics, treatment intensity, complications during induction, antibiotic administration times, and survival outcomes were abstracted from finalized institutional records that are routinely reviewed at discharge by the institutional medical record committee as part of standard quality-assurance procedures. The primary outcome was 60-day mortality. Secondary outcomes included time to first antibiotic dose after recognition of febrile neutropenia, treatment-related complications, and the number of operational steps required for urgent care processes. A subgroup analysis of 70 patients with complete timing documentation was performed for antibiotic administration. Comparisons between hospitals were performed using univariate tests, Kaplan-Meier 60-day survival curves, and multivariable logistic regression. Of the 274 included patients, 104 (38%) were treated at the hospital using an integrated EMR, and 170 (62%) at the hospital using TPR. Sixty-day mortality was lower in the EMR hospital (6/104, 5.8%) than in the TPR hospital (61/170, 35.9%; P<.001). In the subgroup with complete timing data, the mean time from febrile episode recognition to first antibiotic administration was shorter in the hospital using EMR than in the hospital using TPR (54, SD 18.4 minutes; P<.001). Although the EMR hospital used a higher proportion of high-intensity regimens, patients in that hospital had better 60-day outcomes. In multivariable analysis, hospital type remained independently associated with 60-day mortality (odds ratio 0.11, 95% CI 0.05-0.26; P<.001), whereas kidney injury and hepatotoxicity were associated with worse outcomes. In this natural experiment, the hospital using an integrated EMR had a lower 60-day mortality and shorter time to antibiotic administration than the hospital using TPR. These findings are hypothesis-generating and suggest that digital workflows may contribute to more timely urgent supportive care, but they should be interpreted with caution, given the retrospective 2-center design and the potential for residual confounding.

BackgroundCancer survivors frequently face persistent nutrition-related challenges after treatment. Mobile health tools may extend access to dietary self-management support beyond clinic settings, but feasibility and preliminary effects remain insufficiently characterized in this population.ObjectiveThis study aims to evaluate the feasibility, user engagement, and preliminary effects of a 4-week mobile nutrition app on dietary behavior and quality of life (QoL) among cancer survivors, and to explore whether higher engagement is associated with greater improvements.MethodsA single-arm, prospective pilot feasibility study was conducted at a tertiary cancer center in Korea. Participants used a mobile nutrition app that provided dietary feedback and self-monitoring features. In-app log data were analyzed to determine engagement metrics (session frequency, duration, and gap regularity) using an elbow-based 10-minute session threshold. Primary outcomes included the Nutrition Quotient for Adults (NQ-2021) and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) scores, measured before and after 4 weeks. Nonparametric paired analyses assessed changes, and exploratory correlations examined relationships between engagement and outcomes.ResultsAmong 27 enrolled participants, 24 cancer survivors (88.9%) completed the intervention and postassessment; the majority were female (17/24, 70.8%), with a mean age of 58.5 (SD 8.7) years. Breast cancer was the most common diagnosis (11/24, 45.8%), and most participants reported no diet-related adverse effects (20/24, 83.3%) and stable body weight during the study period. Participants averaged 2.3 app sessions per day and a median cumulative use of 177.5 minutes. Retention was 88.9%, and median adherence to daily self-monitoring exceeded 85%. The NQ Moderation domain improved significantly (mean 76.6, SD 17.5 → mean 81.0, SD 13.7; P=.02), while Balance and Dietary Behavior showed positive trends (mean 63.7, SD 16.1 → mean 65.5, SD 13.3, P=.14; mean 64.9, SD 17.3 → mean 67.1, SD 15.9, P=.10). In QoL outcomes, appetite loss decreased (mean 17.9, SD 22.0 → mean 7.7, SD 14.6; P=.03) and global health status increased modestly (mean 68.5, SD 21.4 → mean 72.9, SD 20.1; P=.08). Higher engagement correlated with improved moderation (r=0.46; P=.02) and reduced appetite loss (r=–0.42; P=.04). Exploratory subgroup analyses suggested stronger effects among participants aged 60 years and older (ΔNQ Moderation +7.9; P=.04) and those with longer cancer survivorship (>3 years; P=.047). No adverse events were reported.ConclusionsThis pilot feasibility study demonstrates high user engagement, satisfactory retention, and preliminary improvements in nutritional behavior and QoL among cancer survivors using a mobile nutrition app. These findings indicate the feasibility of a larger controlled trial to confirm the app’s effectiveness and explore long-term adherence strategies.

BackgroundPatients with metastatic breast cancer (MBC) experience significant quality-of-life decrements, but there are few supportive care interventions specifically designed for this group that significantly improve quality of life. Ecological momentary assessment (EMA) and related ecological momentary interventions (EMIs) may be particularly beneficial for patients with MBC. However, no studies have previously examined the use of EMIs in the context of metastatic cancer.ObjectiveThe purpose of this study was to qualitatively assess experiences with EMA and preferences for intervention content and mode among patients living with MBC, with an emphasis on EMIs.MethodsWomen with MBC (n=29) were recruited from a longitudinal, observational study of quality of life using an EMA design. In-depth qualitative interviews assessed participants’ perspectives on the EMA design, including its feasibility, acceptability, and relevance to participants’ MBC experiences. Guided by participants’ EMA data, the interviews also examined the impact of self-monitoring and possible interventions when patients reported high symptom burden and/or low quality of life. Interviews were audio-recorded, transcribed verbatim, and analyzed using open coding, axial coding, and selective coding. The codebook was developed by reviewing a randomly selected subset of transcripts (n=5) and creating inductive, data-driven codes using the raw data, which were deductively organized into overarching themes.ResultsParticipants were mainly White (17/29, 59%), heterosexual (23/29, 79%), currently working (17/29, 59%), and held at least a bachelor’s degree (17/29, 59%). Participants had been living with MBC for a median of 2.5 years (range 0.2‐16.6 years). Most were diagnosed with hormone receptor-positive (23/29, 79%) and HER2-negative (21/29, 72%) breast cancer. Qualitative analysis identified 5 major themes. The participants reflected on their reasons for enrolling in the study, including interest in study activities and giving back to the MBC community (theme 1: participant engagement). Most participants found the EMA format easy to complete, and they provided recommendations for improving the design of future studies, including altering the timing and frequency of questionnaires (theme 2: feedback on study design). While less common, some participants discussed how engaging with the EMA protocol altered their experiences or behaviors (theme 3: impact of self-monitoring). Participants also discussed their reactions to seeing their EMA data, including their mixed thoughts on real-time data sharing (theme 4: responses to data). Finally, participants suggested programs and resources to improve their overall quality of life, reflecting on their interest in real-time interventions and peer-to-peer support (theme 5: recommendations for future interventions).ConclusionsPatients with MBC are willing to use EMA methodologies for data collection on quality of life and are open to EMIs with varying content and formats. Given variations in daily functioning between and within patients, a just-in-time adaptive intervention framework may be well suited for this population.

BackgroundRandomized controlled trials (RCTs) are the gold standard for evaluating interventions in oncology, but reporting can be subject to “spin”—presenting results in ways that mislead readers about true efficacy.ObjectiveThis study aimed to investigate whether large language models (LLMs) could provide a standardized approach to detect spin, particularly in the conclusions, where it most commonly occurs.MethodsWe randomly sampled 250 two-arm, single–primary end point oncology RCTs from 7 major medical journals published between 2005 and 2023. Two authors independently annotated trials as positive or negative based on whether they met their primary end point. Three commercial LLMs (GPT-3.5 Turbo, GPT-4o, and GPT-o1) were tasked with classifying trials as positive or negative when provided with (1) conclusions only; (2) methods and conclusions; (3) methods, results, and conclusions; or (4) title and full abstract. LLM performance was evaluated against human annotations. Afterward, trials incorrectly classified as positive when the model was provided only with the conclusions but correctly classified as negative when provided with the whole abstract were analyzed for patterns that may indicate the presence of spin. Model performance was assessed using accuracy, precision, recall, and F1-score calculated from confusion matrices.ResultsOf the 250 trials, 146 (58.4%) were positive, and 104 (41.6%) were negative. The GPT-o1 model demonstrated the highest performance across all conditions, with F1-scores of 0.932 (conclusions only; 95% CI 0.90-0.96), 0.96 (methods and conclusions; 95% CI 0.93-0.98), 0.98 (methods, results, and conclusions; 95% CI 0.96-0.99), and 0.97 (title and abstract; 95% CI 0.95-0.99). Analysis of trials incorrectly classified as positive when the model was provided only with the conclusions revealed shared patterns, including absence of primary end point results, emphasis on subgroup improvements, or unclear distinction between primary and secondary end points. These patterns were almost never found in trials correctly classified as negative.ConclusionsLLMs can effectively detect potential spin in oncology RCT reporting by identifying discrepancies between how trials are presented in the conclusions vs the full abstracts. This approach could serve as a supplementary tool for improving transparency in scientific reporting, although further development is needed to address more complex trial designs beyond those examined in this feasibility study.

BackgroundIndividuals 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.ObjectiveThis 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.MethodsThis 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.ResultsTwenty 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.ConclusionsIM@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.Trial RegistrationClinicalTrials.gov NCT05053230; https://www.clinicaltrials.gov/study/NCT05053230International Registered Report Identifier (IRRID)RR2-10.1038/s41746-024-01387-z

BackgroundImmune 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.ObjectiveThis study aimed to explore the prognostic significance of dynamic changes in LDH levels during ICI therapy in predicting treatment outcomes.MethodsWe 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.ResultsAmong 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).ConclusionsIn 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 risk stratification and personalized treatment optimization in advanced ESCC.

BackgroundIn recent years, the global incidence of thyroid cancer has been increasing.ObjectiveThis study aimed to examine the association between Hashimoto thyroiditis (HT) and papillary thyroid cancer (PTC) progression under active surveillance (AS).MethodsOur retrospective study was conducted at Peking University Third Hospital and included 203 patients with PTC who underwent AS for ≥6 months before surgery. Patients were first categorized into 2 groups: the HT group (n=90) and the non-HT group (n=113). Cox proportional hazards models were then used to evaluate the association between HT and PTC progression during AS, adjusting for age, sex, baseline tumor size, BMI, pregnancy status, number of tumor foci, and thyroid-stimulating hormone level. Subgroup analyses stratified by the 6 covariates mentioned above were also applied to explore the potential effect modification.ResultsNo significant difference was observed between the HT and non-HT groups in PTC progression-free survival (hazard ratio [HR] 1.11, 95% CI 0.61‐1.99; P=.74), tumor enlargement-free survival (HR 1.02, 95% CI 0.56‐1.86; P=.95), or lymph node metastasis-free survival (HR 1.76, 95% CI 0.31‐10.12; P=.52). Subgroup analyses revealed a potential interaction between HT and BMI. Among patients who were overweight or obese (BMI >24 kg/m²), HT was significantly associated with an increased risk of disease progression (HR 6.32, 95% CI 1.84‐21.69; P=.003), while among patients with BMI ≤24 kg/m2, no association between HT and progression risk was observed (P=.01).ConclusionsWe found no evidence of association between HT and PTC progression during AS. However, the relationship between HT and PTC progression may be modified by overweight or obesity status.

Over the past decade, Fast Healthcare Interoperability Resources (FHIR) have become increasingly relevant in health care data standardization. However, the complex structure of FHIR makes cohort analytics with many-to-many relations extremely time-consuming, and, impossible in many cases. To support exploratory cohort building and data visualization in oncology, especially for nontechnical users, we developed the DermaDashboard, an interactive dashboard built on top of a relational FHIR-compliant PostgreSQL database. Relevant oncology data was preaggregated with a materialized view, and the subsequent visualization layer was implemented using an open-source visualization tool, enabling clinicians to filter and analyze data without requiring familiarity with FHIR or SQL. The database encompassed data from 3949 patients with melanoma and included 82,783 health records. Core FHIR resources were Patient, DiagnosticReport, and QuestionnaireResponse, with 54 mapped attributes spanning demographics, stagings, mutations, and treatments. The resulting dashboard allowed filtering across 29 variables to construct subcohorts and generate aggregation analyses. This implementation shows how open interoperability data standards, such as FHIR, can be used in the development of modular, user-friendly clinical dashboards for cohort analysis, and the architecture demonstrates a feasible path toward democratizing access to structured health care data.