Clinical oncology最新文献

{"title":"Paid MBP advert CO_Journals_AI_Conference_280x210_180925_SEB_01","authors":"","doi":"10.1016/S0936-6555(25)00195-5","DOIUrl":"10.1016/S0936-6555(25)00195-5","url":null,"abstract":"","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"46 ","pages":"Article 103940"},"PeriodicalIF":3.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RCR Meetings","authors":"","doi":"10.1016/S0936-6555(25)00194-3","DOIUrl":"10.1016/S0936-6555(25)00194-3","url":null,"abstract":"","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"46 ","pages":"Article 103939"},"PeriodicalIF":3.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145095640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Oncoflash—Research Updates in a Flash!","authors":"D. Shor , K. Thippu Jayaprakash","doi":"10.1016/j.clon.2025.103932","DOIUrl":"10.1016/j.clon.2025.103932","url":null,"abstract":"","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"46 ","pages":"Article 103932"},"PeriodicalIF":3.0,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145085348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Magnetic Resonance Imaging Based Delineation in Head and Neck Cancers: Balancing Coverage and Toxicity","authors":"S. Haider","doi":"10.1016/j.clon.2025.103941","DOIUrl":"10.1016/j.clon.2025.103941","url":null,"abstract":"","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"47 ","pages":"Article 103941"},"PeriodicalIF":3.0,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RT-HaND_C: A Multi-Source, Validated Real-world Head and Neck Cancer Dataset for Research","authors":"T. Young ,&nbsp;H. Drake ,&nbsp;V. Butterworth ,&nbsp;W. Wulaningsih ,&nbsp;B. Dann ,&nbsp;A. Giemza ,&nbsp;E. Ivy ,&nbsp;D. Adjogatse ,&nbsp;K. Sambasivan ,&nbsp;I. Petkar ,&nbsp;M. Reis Ferreira ,&nbsp;A. Kong ,&nbsp;M. Lei ,&nbsp;L. Collins ,&nbsp;A. King ,&nbsp;D. Vilic ,&nbsp;T.G. Urbano","doi":"10.1016/j.clon.2025.103935","DOIUrl":"10.1016/j.clon.2025.103935","url":null,"abstract":"<div><h3>Aims</h3><div>Real-world data (RWD) are a valuable resource for head and neck cancer (HNC) research, offering insights into outcomes among diverse, comorbid patients who are often underrepresented in clinical trials. However, RWD pose challenges, including data quality and requires rigorous evaluation before being used to generate real-world evidence. We aimed to develop a large HNC oncology dataset containing comprehensive clinical data.</div></div><div><h3>Methods</h3><div>We developed RT-HaND_C, a multi-source clinical dataset integrating structured Electronic Health Record (EHR) data, unstructured EHR data extracted using a previously validated AI-driven Natural Language Processing tool, and manually curated datasets. RT-HaND_C incorporates extensive demographic, disease, laboratory, treatment, outcome (disease and toxicity) and radiotherapy dosimetry data for all HNC oncology patients seen at our centre (2010–2023). The dataset underwent rigorous evaluation for accuracy, completeness and consistency. We evaluated usability by addressing the unanswered question of long-term weight trends post-radical HNC radiotherapy.</div></div><div><h3>Results</h3><div>The retrospective cohort comprises 2,895 HNC patients with over 1.9 million data points across over 2000 data categories. Accuracy assessments exceeded 98% for most variables. High data completeness and consistency were observed for all key data categories. Dataset usability testing showed rapidly extractable and analysable data, with data demonstrating that HNC patients experienced statistically significant weight loss persisting at 5 years post-radical radiotherapy (even when accounting for disease recurrence), with peak weight loss observed at 6 months post-radiotherapy.</div></div><div><h3>Conclusions</h3><div>RT-HaND_C represents a novel, high-quality RWD resource and evaluation framework. RT-HaND_C is virtually linked to corresponding diagnostic and radiotherapy imaging data to facilitate multi-modal research. The dataset is available for research and collaboration, with ongoing work focused on enhancing completeness and incorporating prospective updates.</div></div>","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"47 ","pages":"Article 103935"},"PeriodicalIF":3.0,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimisation of Margin Adaptation for Respiratory Motion in Lung Cancer Stereotactic Body Radiation Therapy Using Virtual Four-dimensional Volumetric Modulated Arc Therapy System Radiotherapy","authors":"D. Kawahara ,&nbsp;H. Masuda ,&nbsp;T. Wada ,&nbsp;M. Kishi ,&nbsp;T. Katsuta ,&nbsp;N. Imano ,&nbsp;Y. Murakami","doi":"10.1016/j.clon.2025.103934","DOIUrl":"10.1016/j.clon.2025.103934","url":null,"abstract":"<div><h3>Aim</h3><div>This study applies a previously developed four-dimensional (4D) dose calculation method using virtual four-dimensional computed tomography (v4DCT) to evaluate and optimise the use of an optimal margin (OM) in lung stereotactic body radiation therapy (SBRT). Specifically, we assess the clinical feasibility of an OM derived from different prescription isodose levels and its impact on target coverage and normal tissue sparing.</div></div><div><h3>Materials and Methods</h3><div>Volumetric modulated arc therapy (VMAT) plans were created using a whole-body phantom with a virtual lung tumour. Treatment planning ensured that 95% of the planning target volume (PTV) was covered by the prescription isodose lines for 70%, 75%, and 80%. v4DCT images were generated assuming free breathing. The four-dimensional radiotherapy (v4DRT) dose represented the accumulated dose across all respiratory phases. The dosimetric internal margin (DIM) was defined as the maximum amplitude ensuring D_100% and D_99% coverage of the gross tumour volume (GTV). The OM was determined based on the average dose to the GTV and the dose to organs at risk (OARs) for the 70% to 80% isodose plans.</div></div><div><h3>Results</h3><div>The DIM was determined to be 2.0 to 2.6 times larger than the conventional margin accounting for respiratory motion. Implementation of the optimised margin resulted in a significant reduction of the V_20Gy for normal lung tissue under respiratory motion conditions. Additionally, the maximum dose at distances of 0.5 to 2.0 cm from the PTV showed a reduction with larger amplitudes. The OM with 70% and 75% isodose plan achieved a 55% to 62% reduction compared to the conventional PTV margin with 80% isodose plan.</div></div><div><h3>Conclusion</h3><div>This study proposes an OM for lung SBRT with marginal prescription. This approach reduced the respiratory motion margin by 55% to 62% while maintaining target dose coverage and lowering OAR exposure.</div></div>","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"47 ","pages":"Article 103934"},"PeriodicalIF":3.0,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radiating Excellence: A Decade of Pioneering Radiotherapy Trials and Collaborative Leadership at Leeds Cancer Research UK Clinical Trials Unit","authors":"F. Slevin ,&nbsp;E.M. Hudson ,&nbsp;A. Hockaday ,&nbsp;J. Kendall ,&nbsp;S. Noutch ,&nbsp;J.B. Oughton ,&nbsp;A. Smith ,&nbsp;J.C. Webster ,&nbsp;D. Sebag-Montefiore ,&nbsp;S.R. Brown","doi":"10.1016/j.clon.2025.103937","DOIUrl":"10.1016/j.clon.2025.103937","url":null,"abstract":"<div><div>Recently, there has been considerable development in radiotherapy technologies and novel drug-radiotherapy combinations, with the potential to develop more effective and less toxic treatments for patients. There is a need to evaluate these approaches through clinical trials, and clinical trials units (CTUs) are ideally positioned to design and deliver these studies. Over the past 10 years, the Leeds Cancer Research UK CTU has developed a flagship portfolio of radiotherapy clinical trials, which encompass novel drug-radiotherapy combinations, radiotherapy technologies and optimising radiotherapy dose. Key to the success of the portfolio has been an emphasis on multidisciplinary collaborations, career development of future leaders in clinical trials, understanding the funding landscape, engagement with discovery and translational scientists, and keeping patients at the heart of our research. Moving forward, the priorities of the CTU are to build on this strong foundation with a pipeline of impactful and scientifically rich clinical trials, which will continue to shape the radiotherapy research landscape.</div></div>","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"47 ","pages":"Article 103937"},"PeriodicalIF":3.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization and Quality Assurance of VMAT-Driven Lattice Radiotherapy in Large Tumors Across Anatomical Sites","authors":"A.K. Singh ,&nbsp;S. Singh ,&nbsp;S. Sen ,&nbsp;A. Vijay ,&nbsp;Dipesh ,&nbsp;M. Bhushan ,&nbsp;Mahipal ,&nbsp;M. Omar","doi":"10.1016/j.clon.2025.103936","DOIUrl":"10.1016/j.clon.2025.103936","url":null,"abstract":"<div><h3>Aims</h3><div>This study investigates the feasibility, dosimetric optimization, and validation of VMAT-based Lattice Radiotherapy (LRT) across head and neck, thoracic, and abdominal tumors using TrueBeam STx(Varian Medical Systems).</div></div><div><h3>Materials and methods</h3><div>60 patients with gross tumor volumes (GTVs) &gt;550 cc and ≥10 lattice vertices were included. Planning CTs were acquired using a Siemens Somatom go.Sim. VMAT plans were generated in Eclipse (v15.1) with 6 MV FFF beams, using HD120 MLCs. Each spherical high-dose vertex received 20 Gy in 5 fractions. Optimization incorporated concentric dose rings (C1–C3) for valley dose control. Dosimetric parameters evaluated included D_95%, Dmean, D_50%, Homogeneity Index (HI), and Peak-to-Valley Dose Ratio (PVDR). Validation was performed using OSLDs in a Rando phantom and ArcCHECK gamma analysis (3%/3 mm).</div></div><div><h3>Results</h3><div>Abdominal tumors showed the highest spatial modulation, with axial VPDR reaching 0.62, compared to 0.47 in head and neck and thoracic sites. Abdominal sphere doses exhibited the lowest standard deviation (Dmean = 2113.8 ± 47.1 cGy). Head and neck cases required higher modulation intensity (MU/deg = 3.8) due to OAR proximity, while abdominal cases required reduced gantry speeds (1.2°/sec) for sharper dose gradients. Gamma pass rates exceeded 96% across all sites, confirming delivery accuracy.</div></div><div><h3>Conclusion</h3><div>VMAT-guided LRT provides robust peak-to-valley dose modulation and reproducible high-dose vertex delivery for large tumors. Anatomical location significantly affects vertex geometry, modulation requirements, and dosimetric outcomes. Abdominal plans demonstrated superior uniformity and spatial separation, whereas head and neck cases demanded more complex optimization. Standardized planning protocols and rigorous QA are essential for safe clinical translation of LRT.</div></div>","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"47 ","pages":"Article 103936"},"PeriodicalIF":3.0,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145156358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Evaluation of Stereotactic Ablative Radiotherapy for Oligometastases From Rare Primary Cancers","authors":"R. Talwar ,&nbsp;J. Duong ,&nbsp;P. Nariyangadu ,&nbsp;P. Hoskin ,&nbsp;A. Stewart-Lord ,&nbsp;N. Shah ,&nbsp;P. Ostler ,&nbsp;M. Harrison ,&nbsp;A. Vinayan ,&nbsp;S. Dubash ,&nbsp;Y. Tsang","doi":"10.1016/j.clon.2025.103931","DOIUrl":"10.1016/j.clon.2025.103931","url":null,"abstract":"<div><h3>Aims</h3><div>Stereotactic ablative body radiotherapy (SABR) has emerged as a promising treatment modality for oligometastatic disease from primary breast, prostate, lung, and colorectal cancers. However, there is a paucity of information on clinical outcomes of SABR to oligometastases from rare primary cancers (RPCs). This study aimed to report the treatment outcomes and to investigate what factors are prognostic in terms of overall survival (OS) and progression-free survival (PFS) in patients receiving SABR for oligometastases from RPCs.</div></div><div><h3>Methods and materials</h3><div>All patients with oligometastases from any RPCs were included in this retrospective review of patients treated with SABR at one single institution. This cohort excluded breast, prostate, lung, colon, and rectum primary cancer. OS and PFS were calculated using Kaplan-Meier statistics and post-SABR toxicities were scored following the Common Terminology Criteria for Adverse Events (CTCAE) v. 4.0. An analysis of prognostic factors for OS and PFS was performed based on log-rank tests which were used for the analysis of prognostic factors for OS and PFS based on the site of primary cancer, previous radiotherapy status, previous systemic therapy status, the number of oligometastases, SABR treatment site, biological equivalent dose, total size of gross tumour volume, and planning target volume (PTV).</div></div><div><h3>Results</h3><div>A total of 114 patients with 126 metachronous oligometastatic lesions from RPC receiving SABR were included. The median patient age when they received SABR was 66.7 years (range: 22.3-91.8 years), with the median follow-up of the cohort being 21.7 months (range: 2.8-75.8 months). The estimated median OS was 40.1 months (95% confidence interval [CI]: 27.5-52.6 months), and the estimated median PFS was 14.2 months (95% CI: 11.0-17.5 months). The treatment was well tolerated, with the majority of patients experiencing only grade 1 fatigue as the most common acute toxicity. The previous radiotherapy status (<em>P =</em> 0.04) and cumulative PTV (<em>P</em> = 0.01) were identified as statistically significant independent predictors of OS. For PFS, SABR treatment site (<em>P</em> = 0.03) was the only statistically significant independent predictor.</div></div><div><h3>Conclusion</h3><div>There are limited studies published on the efficacy and post-treatment toxicities of using SABR in the management of oligometastases from RPC. This study confirmed that SABR was a safe, noninvasive treatment option for patients with extracranial oligometastases originated from RPC in terms of the favourable post-treatment toxicities.</div></div>","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"47 ","pages":"Article 103931"},"PeriodicalIF":3.0,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145085288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Treatment Decisions on Survival Outcomes in Elderly Patients With Non–Small Cell Lung Cancer: A Retrospective Real-World Study","authors":"V. Paappanen ,&nbsp;H. Järvenpää ,&nbsp;A. Jukkola ,&nbsp;P. Päkkilä ,&nbsp;S. Sahlström ,&nbsp;T. Klaavuniemi ,&nbsp;L. Sailas ,&nbsp;J. Ahvonen ,&nbsp;H. Kuitunen ,&nbsp;J. Kopra ,&nbsp;O. Kuittinen ,&nbsp;M. Tengström ,&nbsp;S. Tiainen","doi":"10.1016/j.clon.2025.103930","DOIUrl":"10.1016/j.clon.2025.103930","url":null,"abstract":"<div><h3>Aims</h3><div>Lung cancer (LC) is a leading cause of cancer-related mortality, particularly in elderly patients, who often receive less curative treatment and have poorer prognoses than younger individuals. The reasons for these disparities remain unclear. This study aimed to identify clinical factors influencing treatment decisions and survival outcomes in elderly patients with non–small cell lung cancer (NSCLC).</div></div><div><h3>Materials and methods</h3><div>This retrospective study included 395 NSCLC patients diagnosed in 2018 at five Finnish hospitals. Patients were divided into four age cohorts: &lt;61, 61 to 70, 71 to 80, and &gt;80 years. Overall survival (OS) was analysed across age groups, stratified by treatment methods.</div></div><div><h3>Results</h3><div>Stage distribution was similar across age groups; however, older patients had worse performance status and higher Charlson Comorbidity Index (CCI) scores (<em>P ≤</em> 0.008). Elderly patients were less likely to receive surgery, chemoradiotherapy, or chemotherapy and were more frequently offered best supportive care (BSC) (<em>P</em> &lt; 0.013). OS decreased with increasing age (<em>P</em> = 0.006), with 1-year survival rates of 60% and 32% and 2-year survival rates of 41% and 15% in the youngest and oldest cohorts, respectively. LC was the leading cause of death across all age groups.</div></div><div><h3>Conclusion</h3><div>Elderly NSCLC patients had poorer survival outcomes despite similar disease stage at diagnosis, possibly due to lower rates of curative treatment. These findings highlight the need for further investigation into optimising treatment strategies for elderly patients with NSCLC.</div></div>","PeriodicalId":10403,"journal":{"name":"Clinical oncology","volume":"47 ","pages":"Article 103930"},"PeriodicalIF":3.0,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145198607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}