ESMO Real World Data and Digital Oncology最新文献

{"title":"Implementing digital patient-reported outcomes in routine cancer care: barriers and facilitators","authors":"S.G. Aanes ,&nbsp;S. Wiig ,&nbsp;C. Nieder ,&nbsp;E.C. Haukland","doi":"10.1016/j.esmorw.2024.100088","DOIUrl":"10.1016/j.esmorw.2024.100088","url":null,"abstract":"<div><h3>Background</h3><div>In cancer care research, there exists a gap between patient-reported outcomes (PROs) and health care personnel-reported outcomes. PROs have shown significant benefits in terms of symptoms, quality of life, reduced hospital admissions and increased overall survival. However, throughout the past decade, PROS have been used mainly in clinical trials and slowly implemented in routine cancer care. We wanted to review specific published experiences identified as barriers to and facilitators of the implementation of digital PROs in routine cancer care.</div></div><div><h3>Results</h3><div>A literature search was conducted in PubMed and Ovid Medline Evidence-Based Medicine Reviews (EBMRs) from 1 January 2017 to 29 August 2023. A total of 313 records were screened, of which 15 records were included. Facilitators identified were a user-friendly electronic PRO (ePRO) solution routinely used by care providers in a revised workflow that engaged key stakeholders and provided sufficient support and infrastructure. Common barriers were lack of information about benefits, time constraints, literacy or lack of access to text or information technology (IT) together with a negative impact on workflow, inadequate IT infrastructure, not engaging staff and costs.</div></div><div><h3>Conclusions</h3><div>Successful implementation of ePRO systems needs to address identified barriers and leverage facilitators. Using implementation frameworks and guidelines with quality improvement methods can enhance successful implementation as they address both local barriers and facilitators in a system thinking perspective. There is still an unmet need for real-world evidence on how sustainable PROs can be implemented most efficiently over time, thus highlighting the need for a bridge between medical and implementation science.</div></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100088"},"PeriodicalIF":0.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of cabozantinib and sunitinib for the treatment of intermediate/poor risk renal cell carcinoma based upon UK real-world data","authors":"D. Lee ,&nbsp;G.J. Melendez-Torres ,&nbsp;A. Challapalli ,&nbsp;R. Frazer ,&nbsp;J. McGrane ,&nbsp;A. Bahl","doi":"10.1016/j.esmorw.2024.100087","DOIUrl":"10.1016/j.esmorw.2024.100087","url":null,"abstract":"<div><h3>Background</h3><div>The purpose of this study was to explore the effectiveness of cabozantinib versus sunitinib for the treatment of first-line metastatic renal cell carcinoma in intermediate/poor risk patients.</div></div><div><h3>Materials and methods</h3><div>Retrospective review of cases between 1 January 2018 and 30 June 2021 across 17 UK centres. Univariable and multivariable Cox proportional hazards modelling to identify prognostic factors. Inverse probability of treatment weighting, to estimate the causal effect of first-line treatment type.</div></div><div><h3>Results</h3><div>Cabozantinib patients (<em>n</em> = 106) had poorer risk status, less prior nephrectomy, shorter time to therapy, and more clear cell histology than sunitinib patients (<em>n</em> = 218). More sunitinib patients received a second or third line of subsequent treatment (56% and 23% versus 43% and 13%). Though there was no significant difference between treatments in overall survival (OS) or progression-free survival (PFS) across models, the difference in PFS bordered on significant in a multipredictor analysis (benefit in favour of cabozantinib; <em>P</em> = 0.06). When the Kaplan–Meier curves were stratified by risk status (intermediate versus poor), patients had similar OS within the risk groups. PFS appeared to differ with poor risk patients performing better on cabozantinib. Inverse probability of treatment weighting analysis showed little difference from the unadjusted results: OS hazard ratio = 1.119 (95% confidence interval (CI) 0.823-1.521); PFS hazard ratio 0.825 (95% CI 0.636-1.070) for cabozantinib versus sunitinib.</div></div><div><h3>Conclusions</h3><div>Our results showed no significant difference in either OS or PFS between treatments. Cabozantinib trended towards improved PFS and reduced OS. Decision-making for tyrosine kinase inhibitor monotherapy should consider later-line treatment options. This analysis is of particular relevance as sunitinib is now off-patent meaning that the cost of a course of treatment has considerably reduced.</div></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100087"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human-centered AI as a framework guiding the development of image-based diagnostic tools in oncology: a systematic review","authors":"K. Allen ,&nbsp;A.K. Yawson ,&nbsp;S. Haggenmüller ,&nbsp;J.N. Kather ,&nbsp;T.J. Brinker","doi":"10.1016/j.esmorw.2024.100077","DOIUrl":"10.1016/j.esmorw.2024.100077","url":null,"abstract":"<div><h3>Background</h3><div>Artificial intelligence diagnostic tools (AIDTs) in oncology show high image classification accuracy but limited clinical adoption. Their adoption could be enhanced by (i) using user feedback during the software design, (ii) demonstrating that AIDTs improve the user’s decisions, and (iii) providing explanations of AI decisions tailored to the user, three aspects central to human-centered AI (HCAI). This review assesses these three aspects in AIDTs for oncology in general, exemplifying its concepts in the established field of skin cancer diagnostics as a specific use case.</div></div><div><h3>Materials and methods</h3><div>We carried out three Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) searches using PubMed and ScienceDirect, limiting the results to articles published from 2019 to 2024. The first search focused on articles that used user feedback to develop AIDTs. The second search addressed whether AIDT improves dermatologists’ decisions. The third search targeted explainable AI in skin cancer.</div></div><div><h3>Results</h3><div>Five studies incorporated user feedback in AIDT design for cancer. Zooming in on AIDT for skin cancer, nine studies (3/37 in 2019, 3/93 in 2023) indicated that AIDTs improve dermatologists’ decisions in experimental (<em>n</em> = 5) and clinical settings (<em>n</em> = 1). Explainable AI was common in skin cancer diagnostics (<em>n</em> = 26), with papers assessing the user’s preference for explainable AI (XAI) methods or the impact of XAI on the user’s trust in AI diagnosis.</div></div><div><h3>Conclusions</h3><div>User feedback has been used to develop AIDTs tailored to clinicians’ needs. Evidence shows that AIDTs can improve clinicians’ decisions. This, combined with XAI, increases clinicians’ trust in AIDTs, potentially favoring their widespread usage.</div></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100077"},"PeriodicalIF":0.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using real world data to bridge the evidence gap left by prostate cancer screening trials","authors":"N. Norori ,&nbsp;N. Burns-Cox ,&nbsp;L. Blaney ,&nbsp;N. Mayor ,&nbsp;A. Rylance ,&nbsp;T.T. Shah ,&nbsp;A. Naranjo ,&nbsp;M.D. Hobbs","doi":"10.1016/j.esmorw.2024.100073","DOIUrl":"10.1016/j.esmorw.2024.100073","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Population-based prostate cancer screening is currently not recommended in the UK because harms may outweigh benefits. Recent changes to the diagnostic pathway have improved safety and accuracy, but uncertainty remains as to how much they have shifted the screening harm to benefit ratio. Our work uses modelling and real-world data (RWD) to bridge this evidence gap.</div></div><div><h3>Materials and methods</h3><div>We analysed outcomes of men entering the current prostate cancer diagnostic pathway using RWD from two NHS registries covering 16 hospitals. To assess improvements, we compared current UK clinical practice outcomes with those reported in the Cluster Randomised Trial of PSA Testing for Prostate Cancer (CAP)/ProtecT trial and past UK clinical practice, and to a model built to represent expected outcomes from the UK current diagnostic pathway.</div></div><div><h3>Results</h3><div>Out of 10 000 men who underwent a prostate specific antigen (PSA) test, we estimated that the proportion of men with no cancer after a biopsy following a PSA test decreased from 9.46% in the pre-magnetic resonance imaging CAP/ProtecT pathway to 2.33% and 1.52% in the Rapid Assessment for Prostate Imaging and Diagnosis (RAPID) and South West of England RWD pathways, respectively. Clinically insignificant prostate cancer diagnoses decreased to 0.73% in RAPID and 0.83% in South West, while the proportion of men experiencing sepsis reduced from a historic 0.10% to 0.02% in RAPID. We estimated an increase in clinically significant prostate cancer diagnoses in the RWD pathways.</div></div><div><h3>Conclusions</h3><div>This analysis of high-quality RWD estimates a 79% decrease in harm from the diagnostic process when comparing the previous pathway to actual outcomes from current UK clinical practice. This confirms and quantifies the harm reduction delivered by new diagnostic techniques.</div></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100073"},"PeriodicalIF":0.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Oncology education in the age of artificial intelligence","authors":"A. Prelaj ,&nbsp;G. Scoazec ,&nbsp;D. Ferber ,&nbsp;J.N. Kather","doi":"10.1016/j.esmorw.2024.100079","DOIUrl":"10.1016/j.esmorw.2024.100079","url":null,"abstract":"<div><div>The rapid advancements in artificial intelligence (AI) technology have broad implications for the clinical practice of oncology. AI methods enable us to analyze unstructured patient data in a quantitative way, at scale. AI can also help to manage the exponentially growing amount of specialist knowledge, for example, by parsing information from medical guidelines. As oncologists, we will increasingly interact with AI systems in clinical routine and research. These technical developments will require a reshaping of oncology education, which needs to include the development of ‘AI literacy’ as a core aim. Henceforth, oncologists require an understanding of the principles of AI, and the capabilities to adapt and use AI for clinical and research tasks. They should also be able to interpret AI-generated data effectively, especially when communicating with patients who will increasingly use AI tools. Oncologists who understand the fundamental concepts of AI, its limitations, and capabilities will be able to come up with new ideas and use cases, for example, in designing clinical trials. Currently, postgraduate oncology education lacks comprehensive curricula addressing AI integration. We propose that the scientific community, in particular academic institutions, professional societies, and policymakers, should prioritize implementing AI literacy within oncology curricula.</div></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100079"},"PeriodicalIF":0.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Superhuman performance on urology board questions using an explainable language model enhanced with European Association of Urology guidelines","authors":"M.J. Hetz ,&nbsp;N. Carl ,&nbsp;S. Haggenmüller ,&nbsp;C. Wies ,&nbsp;J.N. Kather ,&nbsp;M.S. Michel ,&nbsp;F. Wessels ,&nbsp;T.J. Brinker","doi":"10.1016/j.esmorw.2024.100078","DOIUrl":"10.1016/j.esmorw.2024.100078","url":null,"abstract":"<div><h3>Background</h3><div>Large language models encode clinical knowledge and can answer medical expert questions out-of-the-box without further training. However, this zero-shot performance is limited by outdated training data and lack of explainability impeding clinical translation. We aimed to develop a urology-specialized chatbot (UroBot) and evaluate it against state-of-the-art models as well as historical urologists’ performance in answering urological board questions in a fully clinician-verifiable manner.</div></div><div><h3>Materials and methods</h3><div>We developed UroBot, a software pipeline based on the GPT-3.5, GPT-4, and GPT-4o models by OpenAI, utilizing retrieval augmented generation and the 2023 European Association of Urology guidelines. UroBot was benchmarked against the zero-shot performance of GPT-3.5, GPT-4, GPT-4o, and Uro_Chat. The evaluation involved 10 runs with 200 European Board of Urology in-service assessment questions, with the performance measured by the mean rate of correct answers (RoCA).</div></div><div><h3>Results</h3><div>UroBot-4o achieved the highest RoCA, with an average of 88.4%, outperforming GPT-4o (77.6%) by 10.8%. Besides, it is clinician-verifiable and demonstrated the highest level of agreement between runs as measured by Fleiss’ kappa (κ = 0.979). In comparison, the average performance of urologists on urological board questions is 68.7% as reported by the literature.</div></div><div><h3>Conclusions</h3><div>UroBot is a clinician-verifiable and accurate software pipeline and outperforms published models and urologists in answering urology board questions. We provide code and instructions to use and extend UroBot for further development.</div></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100078"},"PeriodicalIF":0.0,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-world occurrence, therapy, and outcome of patients with class 2 or 3 BRAF compared with class 1 BRAF-mutated cancers","authors":"S. Pradervand ,&nbsp;N. Freundler ,&nbsp;B. Gosztonyi ,&nbsp;L. Roncoroni ,&nbsp;R. Achermann ,&nbsp;T. Schwenk ,&nbsp;G. de Fraipont ,&nbsp;J. Garessus ,&nbsp;S. Haefliger ,&nbsp;A.B. Leichtle ,&nbsp;M.K. Kiessling ,&nbsp;T. Mueller-Focke ,&nbsp;F.S. Krebs ,&nbsp;V. Zoete ,&nbsp;P. Tsantoulis ,&nbsp;O. Michielin ,&nbsp;C. Britschgi ,&nbsp;A. Wicki","doi":"10.1016/j.esmorw.2024.100075","DOIUrl":"10.1016/j.esmorw.2024.100075","url":null,"abstract":"<div><h3>Background</h3><div><em>BRAF</em> V600 mutations are the epitome of targeted therapy. However, not much is known about non-V600 mutations. Using the new data infrastructure of the Swiss Personalized Oncology project of the Swiss Personalized Health Network (SPHN), we evaluated the fate of patients with cancer with non-V600 <em>BRAF</em> mutations in comparison to patients with class 1 mutations.</div></div><div><h3>Patients and methods</h3><div>In this retrospective observational multicenter study, we have assembled a cohort of 392 patients with class 1 and 154 patients with nonclass 1 <em>BRAF</em> mutations (76 colorectal cancers, 96 lung cancers, 297 melanomas, and 77 other cancers). We carried out outcome analyses between mutational classes and therapeutic subgroups.</div></div><div><h3>Results</h3><div>Overall survival (OS) did not differ significantly between patients with class 1 and nonclass 1 mutations. Upon treatment with BRAF/MEK inhibitors, patients with class 1 mutant melanoma showed numerically longer progression-free survival (PFS; 217 days) than patients with nonclass 1 mutant disease (73 days). Overall, in patients with class 2 or 3 mutations, BRAF and MEK inhibitors showed no benefit over other systemic therapies. However, specific class 2 mutations such as K601E may confer sensitivity to BRAF/MEK inhibitors, with two out of five patients achieving a PFS &gt;400 days.</div></div><div><h3>Conclusions</h3><div>The diversity of <em>BRAF</em> mutations presents significant treatment challenges. Despite similar OS, nonclass 1 mutant tumors showed a trend toward lower PFS with BRAF/MEK blockade. Selected class 2 mutations may confer sensitivity to BRAF/MEK inhibitors. This highlights the rationale for a mutation, rather than class-specific, clinical approach against nonclass 1 BRAF-mutant tumors.</div></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100075"},"PeriodicalIF":0.0,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142317828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical trial and real-world evidence of circulating tumor DNA monitoring to predict recurrence in patients with resected colorectal cancer","authors":"H.T. Nguyen ,&nbsp;V.-A. Nguyen Hoang ,&nbsp;T.V. Nguyen ,&nbsp;N.A.L. Trinh ,&nbsp;T.H. Pham ,&nbsp;D.N. Le ,&nbsp;H.H. Ho ,&nbsp;T.D. Nguyen ,&nbsp;H.D. Nguyen ,&nbsp;T.S.L. Thi ,&nbsp;N. Nguyen ,&nbsp;D.H. Tran ,&nbsp;M.T. Le ,&nbsp;T.C. Dinh ,&nbsp;T.S. Nguyen ,&nbsp;K.C.N. The ,&nbsp;H. Mai ,&nbsp;M.T. Chu ,&nbsp;D.H. Pham ,&nbsp;N.H.T. Phuc ,&nbsp;L.N. Tu","doi":"10.1016/j.esmorw.2024.100076","DOIUrl":"10.1016/j.esmorw.2024.100076","url":null,"abstract":"<div><h3>Background</h3><div>Circulating tumor DNA (ctDNA) is a novel biomarker to predict recurrence in colorectal cancer (CRC). However, clinical validation data in underrepresented patient populations like Southeast Asians are lacking.</div></div><div><h3>Materials and methods</h3><div>In our prospective clinical trial, 92 patients with stage I-IVA CRC and eligible for curative-intent surgery were recruited. Blood samples were collected before surgery, after surgery and during surveillance. ctDNA analysis was carried out using a personalized tumor-informed approach. Performance of ctDNA monitoring was further evaluated in a retrospective analysis of 32 patients who had commercial ctDNA testing.</div></div><div><h3>Results</h3><div>Before surgery, the ctDNA detection rate was 91.2%, significantly higher than the carcinoembryonic antigen (CEA) elevation rate at 42.9%. At 2-4 weeks after surgery, ctDNA detection, not CEA, was significantly associated with shorter disease-free survival (DFS) [hazard ratio (HR) = 30.3, 95% confidence interval (CI) 3.3-278.9, <em>P</em> = 0.002]. Longitudinally, ctDNA positivity showed the strongest prognostic value with 100% sensitivity and specificity to detect recurrence (HR = 173.6, 95% CI 19.7 to &gt;1000, <em>P</em> = 0.001); the median lead time was 8.0 months. In the real-world data analysis, post-operative ctDNA remained the only significant prognostic biomarker for DFS (HR = 44.2, 95% CI 9.2-212.0, <em>P</em> &lt; 0.0001). Among relapsed patients, the most common mutations found in ctDNA were in <em>TP53</em> (58.8%), <em>APC</em> (52.9%) and <em>KRAS</em> (41.2%), with high frequency of co-mutations.</div></div><div><h3>Conclusion</h3><div>Our analysis from both clinical trial and real-world data indicated that ctDNA was an independent and strong prognostic biomarker to predict recurrence in CRC. ctDNA testing could be helpful for clinical decision making by enabling personalized intervention and surveillance strategies.</div></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100076"},"PeriodicalIF":0.0,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949820124000547/pdfft?md5=669e201a99dd4cf1572edc157b3e2fb7&pid=1-s2.0-S2949820124000547-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142316063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sequencing the anti-EGFR-TKIs; route to the longest survival","authors":"H.G. Güzel ,&nbsp;Y. İlhan ,&nbsp;A.H. Önder","doi":"10.1016/j.esmorw.2024.100074","DOIUrl":"10.1016/j.esmorw.2024.100074","url":null,"abstract":"","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100074"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949820124000523/pdfft?md5=b66ee1a5b7980fb8a0b0ec87a0612745&pid=1-s2.0-S2949820124000523-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142243101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EBANO study: real-world data from patients with locally advanced/metastatic urothelial carcinoma (la/mUC) in Northern Spain","authors":"R. Fernández Rodríguez ,&nbsp;N. Sagastibeltza ,&nbsp;E. Pujol Obis ,&nbsp;N. Lainez Milagro ,&nbsp;R. Sánchez-Escribano ,&nbsp;M. Martínez Kareaga ,&nbsp;J.A. Verdún Aguilar ,&nbsp;M. Arruti Ibarbia ,&nbsp;M. Pumares González ,&nbsp;T. de Portugal Fernández del Rivero ,&nbsp;A. Lacalle Emborujo ,&nbsp;I. Gil Arnaiz ,&nbsp;A. Pereira-Elorrieta ,&nbsp;C. Álvarez Fernández ,&nbsp;I. Duran ,&nbsp;GONORTE Collaborative Group","doi":"10.1016/j.esmorw.2024.100063","DOIUrl":"10.1016/j.esmorw.2024.100063","url":null,"abstract":"<div><h3>Background</h3><p>Limited real-world data exist on managing locally advanced/metastatic urothelial carcinoma (la/mUC), crucial for predicting outcomes and integrating new treatments. This study explores la/mUC in Northern Spain.</p></div><div><h3>Methods</h3><p>Retrospective observational analysis from 16 hospitals across 12 provinces. The study population included adult patients diagnosed with la/mUC (1 January 2007-31 December 2019). Median overall survival and progression-free survival were determined using the Kaplan–Meier method.</p></div><div><h3>Results</h3><p>A total of 1230 patients were included, 83% were males, median age was 68, and 70% had a smoking history. The most common primary tumor was bladder (89.2%) followed by renal pelvis (6.4%), ureter (4.3%), and urethra (0.1%) and most of them (91%) were pure urothelial tumors. Cystectomy was the predominant treatment of localized disease (69%) and 30% received perioperative chemotherapy. Twenty-four percent of la/mUC patients never received systemic therapy and out of 934 patients treated with first-line (1L) therapy, 55% were fit for cisplatin. Progression to further lines of treatment was poor, only 53% (<em>n</em> = 492) progressed to receive a second line and 22% (<em>n</em> = 209) to a third line. Median overall survival (95% confidence interval) was 12.2 (11.3-12.9) months for the entire cohort and 14.5 and 10.8 months for patients who received first-line cisplatin or carboplatin-based chemotherapy, respectively. No unexpected toxicity was reported.</p></div><div><h3>Conclusions</h3><p>This Spanish real-world data analysis echoes previous findings and highlights unmet needs, including the proportion of patients not receiving systemic treatment and the limited progression to subsequent lines of therapy, hampering access to new effective treatments.</p></div>","PeriodicalId":100491,"journal":{"name":"ESMO Real World Data and Digital Oncology","volume":"6 ","pages":"Article 100063"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949820124000419/pdfft?md5=6518ef0344086f222997c2c513b5b982&pid=1-s2.0-S2949820124000419-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}