Cancer Medicine最新文献

{"title":"Multi-Center Evaluation of Opioid Administration or Prescription in Pediatric Oncology Patients Using the OMOP CDM","authors":"Yuqing Feng,&nbsp;Martin Yi,&nbsp;Catherine C. Aftandilian,&nbsp;Melissa P. Beauchemin,&nbsp;Christine Cunningham,&nbsp;David DeStephano,&nbsp;Rhea K. Khurana,&nbsp;Emily Larimer,&nbsp;Jennifer Oberg,&nbsp;Benjamin L. May,&nbsp;Keith Morse,&nbsp;Karthik Natarajan,&nbsp;David Noyd,&nbsp;Victoria Soucek,&nbsp;Yujie Chen,&nbsp;Adam Yan,&nbsp;Lin Lawrence Guo,&nbsp;Lillian Sung","doi":"10.1002/cam4.72310","DOIUrl":"10.1002/cam4.72310","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Purpose</h3>\u0000 \u0000 <p>Opioid use in pediatric oncology is poorly characterized. The primary objective was to describe opioid administration or prescription patterns in pediatric oncology patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In this multi-center retrospective study conducted across three sites, we included patients aged 0–19 years with a malignant neoplastic disease who received their first chemotherapy between January 2019 and March 2024. Data were extracted from each site's Observational Medical Outcomes Partnership Common Data Model. We described patient characteristics based on: (1) first opioid administration or prescription, overall and for each specific opioid; and (2) all opioid administrations or prescriptions, overall and for each specific opioid. We also evaluated variability in opioid and naloxone use.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Of 2903 pediatric patients with cancer, 2707 (93.2%) were administered or prescribed at least one opioid. Among these patients, fentanyl was the most common (92.4%), followed by morphine (68.7%), hydromorphone (55.3%), and oxycodone (38.6%). Across centers, the proportion of patients receiving fentanyl ranged from 90.9% to 94.9%, morphine from 34.0% to 89.2%, oxycodone from 0.9% to 76.1%, and naloxone from 2.4% to 29.5%. Overall, 10.9% were administered or prescribed naloxone, but among 169 methadone patients, 43.5% were administered or prescribed it. Of the 153,849 total opioid administrations or prescriptions, 22.4% occurred more than 12 months after initiating chemotherapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Among pediatric patients with cancer who receive chemotherapy, 93.2% were administered or prescribed at least one opioid; fentanyl was the most common. There was heterogeneity in opioid choice and naloxone use across sites. These findings lay preliminary groundwork for understanding opioid use patterns and identifying potential areas for practice improvement in pediatric oncology.</p>\u0000 </section>\u0000 </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620299/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149072820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CCNE1: A Cell Cycle Regulator That Influences Tumor Progression","authors":"Liang Yan,&nbsp;Siyi Liu,&nbsp;Yanling Li,&nbsp;Qian He,&nbsp;Chen Long,&nbsp;Ning Tang,&nbsp;Yanhong Zhou","doi":"10.1002/cam4.72336","DOIUrl":"10.1002/cam4.72336","url":null,"abstract":"<p>Cyclin E1 (CCNE1), a pivotal member of the cyclin family, governs the G1/S phase transition of the cell cycle by binding to and activating cyclin-dependent kinase 2 (CDK2), thereby initiating DNA replication and driving S-phase entry. In a broad spectrum of human malignancies—including breast, ovarian, gastric, and non-small cell lung cancers—amplification or overexpression of CCNE1 disrupts the orderly regulation of cell cycle progression, leading to uncontrolled proliferation, impaired DNA damage repair, and genomic instability. These oncogenic consequences are intimately associated with increased tumor aggressiveness, poor patient prognosis, and diminished therapeutic efficacy. This review provides an integrated examination of CCNE1 biology, spanning its physiological regulation in the cell cycle, the molecular mechanisms by which its dysregulation drives tumorigenesis and drug resistance, the clinical implications of CCNE1 amplification as both a prognostic biomarker and a predictor of therapeutic response, and the emerging strategies to target CCNE1-driven vulnerabilities. By synthesizing findings across diverse cancer types and regulatory layers, we evaluate the translational potential of CCNE1 as a diagnostic marker and therapeutic target, and highlight key challenges and opportunities for future investigation.</p>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13620288/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149072766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic Predictions in Non-Small Cell Lung Cancer Using Joint Modeling of Longitudinal and Time-To-Event Outcomes Data","authors":"Christopher R. Pretz,&nbsp;Sara Wienke,&nbsp;Carin R. Espenschied,&nbsp;Samantha I. Liang,&nbsp;Jiemin Liao,&nbsp;Christopher R. Cabanski,&nbsp;Jim Hayes,&nbsp;Victoria Ngo,&nbsp;Enjun Yang,&nbsp;Amar K. Das","doi":"10.1002/cam4.72308","DOIUrl":"10.1002/cam4.72308","url":null,"abstract":"<p>Joint modeling (JM) of longitudinal and time-to-event (TTE) data is a powerful statistical technique that elucidates how temporal changes in a biomarker relate to TTE outcomes while accounting for study confounders. The growing use of next-generation sequencing (NGS) in precision oncology, particularly in capturing circulating tumor DNA (ctDNA) methylation via liquid biopsy, offers new opportunities to apply JM for patient prognostication. In this study, we used JM to analyze a prospective cohort of 251 non-small cell lung cancer patients receiving standard-of-care immune checkpoint inhibitor treatment regimens. The JM is comprised of two sub-models—a hierarchical cubic spline random effects model for the longitudinal biomarker component and a Cox proportional hazards model for the TTE outcome component. Each sub-model incorporated baseline factors of age, gender, smoking status, and cancer stage. The main objective was to establish whether the evolution of a methylation-derived tumor fraction (TF) is associated with patient outcomes. Our investigation revealed that TF is strongly associated with both real-world overall survival and real-world progression-free survival. These results enable the generation of various patient-level predictions that capture the dynamic interplay between TF and patient outcomes, offering a path toward real-time, personalized prognostication. Although validation in larger, multi-center cohorts is needed before routine adoption, this work represents an important step toward integrating dynamic predictions into serial liquid biopsy monitoring. This approach demonstrates the potential of JM to provide more nuanced and adaptive disease evolution monitoring, offering better clinical decision guidance compared to static models or imaging alone.</p>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13616821/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149069000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cancer and Hypertension: Shared Mechanisms, Treatment Interactions, and Clinical Management","authors":"Peizhi Jia,&nbsp;Daxin Chen,&nbsp;Jingting Wang,&nbsp;Yupei Guo,&nbsp;Jinhong Liu,&nbsp;Jiumao Lin","doi":"10.1002/cam4.72319","DOIUrl":"10.1002/cam4.72319","url":null,"abstract":"<p>Cancer and hypertension (HTN) frequently coexist, and their relationship is increasingly recognized as a clinically relevant intersection between oncology and cardiovascular medicine. However, the extent to which this association reflects shared risk factors, common biological mechanisms, or treatment-related effects remains incompletely understood. In this narrative review, we focus specifically on the cancer–HTN interface and summarize epidemiological evidence while considering the potential influence of age, obesity, metabolic syndrome, dietary patterns, and psychosocial factors. We further discuss overlapping mechanisms, including chronic inflammation, renin–angiotensin–aldosterone system activation, calcium signaling abnormalities, activation of the sympathetic nervous system, metabolic dysregulation, dysbiosis of the gut microbiota and genetic and epigenetic alterations. Particular attention is given to the bidirectional interactions between cancer therapies and HTN, as well as the heterogeneous evidence concerning potential associations between antihypertensive medications and cancer outcomes. We also summarize the clinical assessment and management of cancer therapy-related HTN, including Common Terminology Criteria for Adverse Events grading, blood pressure monitoring, cardiovascular risk assessment, and current recommendations from the European Society of Hypertension (ESH) and American Heart Association. Emerging issues, including immune checkpoint inhibitor-associated cardiovascular toxicity, the potential role of cardiac biomarkers such as troponin and natriuretic peptides, and the prognostic significance of treatment-induced HTN across different tumor types, are also discussed. Overall, the available evidence supports an important clinical interplay between cancer and HTN but does not establish a uniform causal relationship. Future prospective studies integrating tumor biology, cardiovascular risk factors, treatment exposure, and longitudinal blood pressure (BP) assessment are needed to clarify these interactions and improve individualized cardio-oncology care.</p>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13616819/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149068910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pan-Cancer Analysis of the Immunomodulatory Roles and Prognostic Value of PDXP and Experimental Verification in SKCM","authors":"Yingjian Hu,&nbsp;Xinzhu Zeng,&nbsp;Wei Cao,&nbsp;Jianhao Jiao,&nbsp;Yuan Zhao,&nbsp;Jun Wang","doi":"10.1002/cam4.72311","DOIUrl":"10.1002/cam4.72311","url":null,"abstract":"<p>Multiple public databases, including TCGA, GEO, and TARGET, were utilized to comprehensively analyze pyridoxal phosphatase (PDXP) expression profiles across 34 cancer types. We further explored the associations of PDXP expression with clinicopathological features, tumor immune microenvironment, genomic heterogeneity, functional signaling pathways, and therapeutic response. In addition, in vitro and in vivo experiments were performed to preliminarily validate the potential mechanism linking PDXP expression to melanoma progression. PDXP exhibited aberrant differential expression in most cancer types and tended to be highly expressed in malignant tumor cells. PDXP expression was correlated with overall survival outcomes in 14 cancer types. In most investigated tumors, PDXP expression was significantly associated with the expression of immunoregulatory and immune checkpoint genes, as well as the general landscape of the tumor immune microenvironment. Correlation analysis of genomic characteristics indicated that PDXP may serve as a potential immune-related biomarker in skin cutaneous melanoma (SKCM). Functional enrichment and signaling pathway analysis showed that elevated PDXP expression in SKCM was correlated with enhanced tumor cell proliferative activity. In vitro and in vivo functional experiments demonstrated that PDXP knockdown significantly suppressed colony formation and migration of melanoma cells, induced G2/M phase cell cycle arrest, and increased cell apoptosis. These findings suggest that PDXP is associated with malignant phenotypes of melanoma cells, which are accompanied by changes in protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling activity. Moreover, we established a prognostic model with moderate predictive performance for melanoma using least absolute shrinkage and selection operator (LASSO)-Cox regression, providing a preliminary prognostic reference for SKCM patients.</p>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13616823/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149068916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pragmatic Screening for Sarcopenia in Non-Small Cell Lung Cancer: Development and Internal Validation of a Prospective Risk Model Integrating T12 CT Indices and Routine Clinical Variables","authors":"Zhuorui You,&nbsp;Wei Dai,&nbsp;Hechen Shen,&nbsp;Xing Wei,&nbsp;Cheng Lei,&nbsp;Jia Liao,&nbsp;Jieming Cao,&nbsp;Minxian Li,&nbsp;Jia Wang,&nbsp;Mengqi Shao,&nbsp;Gang Li","doi":"10.1002/cam4.72230","DOIUrl":"https://doi.org/10.1002/cam4.72230","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Sarcopenia or low muscle mass is common in non-small cell lung cancer and predicts poorer outcomes, but its assessment typically relies on CT-based skeletal muscle index at the L3 vertebral level. Standard chest CTs often omit the L3 level, leaving many patients without a straightforward muscle mass measure, so sarcopenia frequently goes undetected. We therefore evaluated whether thoracic CT measurements could reliably substitute for L3 SMI and developed a simple, accurate clinical tool to identify patients at risk of CT-defined low muscle mass.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In retrospective (<i>n</i> = 192) and prospective (<i>n</i> = 177) cohorts of NSCLC patients, cross-sectional muscle area was quantified on CT at L3, T12, and T4. Deming regression and Bland–Altman analysis were used to assess correlations and agreement between T4- or T12-derived SMI and reference L3 SMI. Candidate clinical predictors were selected based on univariate associations and clinical plausibility, and machine-learning methods identified five routine variables, which were combined into the Lung Cancer Patients' Sarcopenia Risk Model (LSRM). Model performance was evaluated in terms of discrimination, calibration, and risk stratification and compared with established clinical indices like BMI and the advanced lung cancer inflammation index (ALI).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>T12-derived SMI showed a strong correlation and minimal bias versus L3, outperforming T4-derived SMI. A conversion equation was established to estimate L3 SMI from T12. The LSRM, incorporating age, body mass index, carcinoembryonic antigen, C-reactive protein, and lymphocyte count, demonstrated good discrimination, satisfactory calibration, and clear three-tier risk stratification. It outperformed BMI and ALI in identifying CT-defined low muscle mass.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>T12 measurements on routine chest CT can replace L3 for muscle assessment. The LSRM provides a practical bedside tool for screening patients at risk of CT-defined low muscle mass in NSCLC without additional imaging, supporting earlier risk identification and integration into routine care.</p>\u0000 </section>\u0000 </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.72230","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lanreotide, a Somatostatin Analogue, in Advanced Merkel Cell Carcinoma: A Prospective Single-Arm Phase II Study","authors":"Julie Charles,&nbsp;Aude Belbezier,&nbsp;Stéphane Mouret,&nbsp;Brigitte Dreno,&nbsp;Stéphane Dalle,&nbsp;Céleste Lebbe,&nbsp;Ewa Hainaut-Wierzbicka,&nbsp;Andreea Stefan,&nbsp;Julie de Quatrebarbes,&nbsp;Olivier Dereure,&nbsp;Ouidad Zehou,&nbsp;Sandrine Mansard,&nbsp;Alain Dupuy,&nbsp;Caroline Dutriaux,&nbsp;Florent Grange,&nbsp;Caroline Gaudy-Marqueste,&nbsp;Henri Montaudié,&nbsp;Jean-Philippe Arnault,&nbsp;Yannick Le Corre,&nbsp;Thibault Kervarrec,&nbsp;Jean-Louis Quesada,&nbsp;Mahtab Samimi,&nbsp;Marie-Thérèse Leccia,&nbsp;The Group of Cutaneous Oncology of the French Society of Dermatology","doi":"10.1002/cam4.72295","DOIUrl":"https://doi.org/10.1002/cam4.72295","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Merkel Cell Carcinoma (MCC) is a rare, aggressive neuroendocrine and epithelial skin cancer. Somatostatin analogues, such as lanreotide, have shown efficacy in managing other neuroendocrine tumors. Retrospective studies suggest that lanreotide may induce partial response or disease stabilization in patients with advanced MCC. To test this hypothesis, we conducted a Phase II, non-randomized, open trial investigating lanreotide in MCC patients with advanced disease (ClinicalTrials.gov identifier: NCT02351128).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Patients with Stage IIIB-IV MCC received lanreotide monotherapy (120 mg every 28 days) at any line of systemic therapy, until disease progression or unacceptable toxicity. The primary endpoint was disease control rate (DCR) (defined as the proportion of patients with complete response, partial response, and stable disease) at 3 months. Secondary endpoints included progression-free survival (PFS), overall survival (OS), somatostatin receptor (SSTR) tumor expression, and treatment safety.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Between April, 2015, and November, 2016, 35 patients received lanreotide, with 12 evaluable at 3 months. The DCR at 3 months was 33.3% (4) among evaluable patients (all with stable disease) and 11.4% for the full cohort. Statistical analyses showed no significant difference from the expected 20% response rate (<i>p</i> = 0.205 for intention-to-treat; <i>p</i> = 0.939 for per-protocol). Kaplan–Meier analysis revealed median OS and PFS of 3.1 months (95% CI, 2–5.5) and 3.5 months (95% CI, 2.3–5.5), respectively. SSTR tumor expression did not correlate with treatment response.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Although limited by its implementation before the era of immunotherapy, this non-randomized study shows the limited effectiveness of lanreotide as monotherapy in treating patients with advanced MCC.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Trial Registration</h3>\u0000 \u0000 <p>Identifier: NCT02351128</p>\u0000 </section>\u0000 </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.72295","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevention of Venous Thromboembolism in Patients With Pancreatic Cancer: A Nationwide Survey","authors":"Ruth A. L. Willems,&nbsp;Merlijn U. J. E. Graus,&nbsp;Eline H. E. van Gansewinkel,&nbsp;Aniek E. van Diepen,&nbsp;Geert A. Cirkel,&nbsp;Hanneke W. M. van Laarhoven,&nbsp;Miriam L. Wumkes,&nbsp;Marjolein Y. V. Homs,&nbsp;Johanna W. Wilmink,&nbsp;F. A. Klok,&nbsp;Nick van Es,&nbsp;Hugo ten Cate,&nbsp;Judith de Vos-Geelen,&nbsp;for the Dutch Pancreatic Cancer Group (DPCG)","doi":"10.1002/cam4.72306","DOIUrl":"https://doi.org/10.1002/cam4.72306","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Pancreatic cancer is associated with a high risk of venous thromboembolism (VTE), with approximately one in five patients developing VTE. Randomized controlled trials have demonstrated that primary thromboprophylaxis is effective and safe in ambulatory patients with pancreatic cancer treated with chemotherapy. Despite international guideline recommendations, thromboprophylaxis appears underused in clinical practice.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>To assess clinical practice regarding VTE prevention in ambulatory patients with pancreatic cancer among medical oncologists in the Netherlands.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A nationwide online survey was conducted between March and June 2025 among Dutch medical oncologists involved in pancreatic cancer care. The questionnaire assessed VTE risk perception, use of risk assessment tools, use of thromboprophylaxis, and patient education regarding thrombosis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Thirty-eight medical oncologists completed the survey. Most respondents (79%) classified the VTE risk in patients with pancreatic cancer as high or very high, yet 63% never prescribed thromboprophylaxis to ambulatory patients receiving chemotherapy. Lack of a national guideline recommendation was the most frequently reported reason for not prescribing thromboprophylaxis (74%). Only 11% of medical oncologists reported using the Khorana score, and only 3% always discussed VTE risk with patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Although medical oncologists recognize the high risk of VTE in patients with pancreatic cancer, thromboprophylaxis remains substantially underused in clinical practice in the Netherlands. Limited awareness of risk assessment tools and national guidance were prominent findings that may inform future implementation efforts. These findings provide a benchmark for assessing the impact of the recently updated Dutch guideline on thromboprophylaxis in this high-risk population.</p>\u0000 </section>\u0000 </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 10","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.72306","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149048334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Validation of an Interpretable Machine Learning Model for Predicting Early Pulmonary Metastasis Risk in Osteosarcoma","authors":"Jianhua Mu,&nbsp;Yitian Wang,&nbsp;Han Liu,&nbsp;Xuanhong He,&nbsp;Zhuangzhuang Li,&nbsp;Yi Luo,&nbsp;Yong Zhou,&nbsp;Minxun Lu,&nbsp;Fan Tang,&nbsp;Li Min,&nbsp;Chongqi Tu","doi":"10.1002/cam4.72209","DOIUrl":"10.1002/cam4.72209","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Pulmonary metastasis in high-grade conventional osteosarcoma remains a leading cause of treatment failure and mortality. Traditional monitoring methods are insufficient for early detection. This study aims to develop and validate an interpretable machine learning (ML) model using multi-dimensional data from electronic medical records (EMR) to predict the early risk of pulmonary metastasis in high-grade conventional osteosarcoma patients.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective study included data from 522 high-grade conventional osteosarcoma patients. After rigorous feature selection, 12 independent predictive factors were identified: prothrombin time (PT), international normalized ratio (INR), fibrinogen, globulin, prognostic nutritional index (PNI), eosinophil percentage, monocyte percentage, neutrophil percentage, monocyte count, maximum tumor diameter, gender, and amputation status. Eleven ML models were constructed and compared, with Shapley Additive Explanations (SHAP) analysis applied to enhance model interpretability and clinical transparency.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The gradient boosting model exhibited superior performance, achieving an area under the curve (AUC) of 0.891 in the training set and 0.742 in the independent test set. SHAP analysis revealed that tumor maximum diameter was the most influential predictor of pulmonary metastasis risk, while inflammation and coagulation-related indicators also demonstrated significant contributions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>The gradient boosting model effectively predicts the early risk of pulmonary metastasis in high-grade conventional osteosarcoma and provides interpretable risk factors. This model shows potential as a clinical decision support tool, facilitating personalized risk management and precision medicine, aiming to improve patient outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13590279/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149011662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Why Do Cancer Patients Decide to Withdraw Their Treatment? A Systematic Review and Meta-Synthesis","authors":"Faezeh Abadi,&nbsp;Esmat Nouhi,&nbsp;Mostafa Bijani,&nbsp;Camelia Rohani","doi":"10.1002/cam4.72219","DOIUrl":"https://doi.org/10.1002/cam4.72219","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Discontinuation of treatment by cancer patients is a complex decision driven by many factors that are not yet fully understood. Using a qualitative approach is the best way to explore this complexity in greater depth. Therefore, this study aimed to explore and synthesize the factors that influence the decision-making of cancer patients regarding withdrawal from treatment.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This is a qualitative systematic review and meta-synthesis, conducted using the six-step meta-synthesis method developed by Sandelowski and Barroso in 2007. Initially, a comprehensive systematic search was conducted in PubMed, Web of Science, Scopus, and CINAHL to identify relevant studies published between 2000 and 2024 according to our inclusion criteria. Subsequently, conventional content analysis was used to analyze the data extracted from qualitative studies. Initially, 348 studies were retrieved, and after screening, 18 studies were included in the meta-synthesis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>From 177 primary codes, one main theme, two categories (endogenous and exogenous factors), and eight sub-categories were extracted through the meta-synthesis process. The factors affecting withdrawal from treatment were: “financial and insurance challenges,” “the communication role of the healthcare team,” “cultural and social factors,” “spiritual and religious beliefs,” “family functioning,” “personal attributes,” “the role of emotions,” and “medication side effects.”</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The decision to withdraw from treatment is a multifaceted process influenced by personal values, clinical considerations, and social dynamics. A deeper understanding of these factors enables healthcare providers, especially nurses, to design better support programs.</p>\u0000 </section>\u0000 </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"15 9","pages":""},"PeriodicalIF":3.5,"publicationDate":"2026-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.72219","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148994530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}