Predictive models of long-term survival outcomes following radical cystectomy

IF 2.9 2区医学 Q2 ONCOLOGY Cancer Medicine Pub Date : 2023-10-30 DOI:10.1002/cam4.6670

Akira Ohtsu, Seiji Arai, Yuji Fujizuka, Yoshiyuki Miyazawa, Masashi Nomura, Yoshitaka Sekine, Hidekazu Koike, Hiroshi Matsui, Yasuhiro Shibata, Kazuto Ito, Kazuhiro Suzuki

{"title":"Predictive models of long-term survival outcomes following radical cystectomy","authors":"Akira Ohtsu, Seiji Arai, Yuji Fujizuka, Yoshiyuki Miyazawa, Masashi Nomura, Yoshitaka Sekine, Hidekazu Koike, Hiroshi Matsui, Yasuhiro Shibata, Kazuto Ito, Kazuhiro Suzuki","doi":"10.1002/cam4.6670","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Identifying the likelihood of life-threatening recurrence after radical cystectomy by reliable and user-friendly predictive models remains an unmet need in the clinical management of invasive bladder cancer.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>A total of 204 consecutive patients undergoing open radical cystectomy (ORC) for bladder cancer were retrospectively enrolled between May 2005 and August 2020. Clinicopathological and peri-ORC therapeutic data were extracted from clinical records. We explored predictive factors that significantly affected the primary endpoint of overall survival (OS) and secondary endpoints of cancer-specific survival (CSS) and recurrence-free survival (RFS).</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>During a median follow-up of 3.9 years, 42 (20.6%) and 10 (4.9%) patients died due to bladder cancer and other causes, respectively. Five-year RFS, CSS, and OS were 66.5%, 77.6%, and 75.4%, respectively. Pathological T and N categories and lymphovascular invasion (LVI) significantly affected RFS by Cox regression analysis. Accordingly, clinical T and pathological N categories and LVI significantly affected CSS. Clinical T and pathological N categories, LVI, age, and ORC tumor grade significantly affected OS. Based on the assessment score for each independent risk factor, we developed the Gunma University Oncology Study Group (GUOSG) score, which predicts RFS, CSS, and OS. The GUOSG score classified four groups for RFS, three for CSS, and five for OS, with statistically significant distribution for nearly all comparisons.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>The GUOSG model is helpful to show individualized prognosis and functions as a risk-stratified historical cohort for assessing the lifelong efficacy of new salvage treatment regimens.</p>\n </section>\n </div>","PeriodicalId":139,"journal":{"name":"Cancer Medicine","volume":"12 23","pages":"21118-21128"},"PeriodicalIF":2.9000,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cam4.6670","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Medicine","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cam4.6670","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Background

Identifying the likelihood of life-threatening recurrence after radical cystectomy by reliable and user-friendly predictive models remains an unmet need in the clinical management of invasive bladder cancer.

Methods

A total of 204 consecutive patients undergoing open radical cystectomy (ORC) for bladder cancer were retrospectively enrolled between May 2005 and August 2020. Clinicopathological and peri-ORC therapeutic data were extracted from clinical records. We explored predictive factors that significantly affected the primary endpoint of overall survival (OS) and secondary endpoints of cancer-specific survival (CSS) and recurrence-free survival (RFS).

Results

During a median follow-up of 3.9 years, 42 (20.6%) and 10 (4.9%) patients died due to bladder cancer and other causes, respectively. Five-year RFS, CSS, and OS were 66.5%, 77.6%, and 75.4%, respectively. Pathological T and N categories and lymphovascular invasion (LVI) significantly affected RFS by Cox regression analysis. Accordingly, clinical T and pathological N categories and LVI significantly affected CSS. Clinical T and pathological N categories, LVI, age, and ORC tumor grade significantly affected OS. Based on the assessment score for each independent risk factor, we developed the Gunma University Oncology Study Group (GUOSG) score, which predicts RFS, CSS, and OS. The GUOSG score classified four groups for RFS, three for CSS, and five for OS, with statistically significant distribution for nearly all comparisons.

Conclusions

The GUOSG model is helpful to show individualized prognosis and functions as a risk-stratified historical cohort for assessing the lifelong efficacy of new salvage treatment regimens.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

根治性膀胱切除术后长期生存结果的预测模型。

背景：在侵袭性膀胱癌症的临床管理中，通过可靠和用户友好的预测模型来识别根治性膀胱切除术后危及生命的复发的可能性仍然是一个未满足的需求。方法：回顾性纳入2005年5月至2020年8月期间连续204例接受癌症开放性根治性膀胱切除术（ORC）的患者。从临床记录中提取临床病理学和ORC周围的治疗数据。我们探讨了显著影响总生存率（OS）主要终点和癌症特异性生存率（CSS）和无复发生存率（RFS）次要终点的预测因素年，42例（20.6%）和10例（4.9%）患者分别死于膀胱癌症和其他原因。5年RFS、CSS和OS分别为66.5%、77.6%和75.4%。Cox回归分析显示，病理性T和N分类以及淋巴血管浸润（LVI）显著影响RFS。因此，临床T和病理N类以及LVI显著影响CSS。临床T和病理N分类、LVI、年龄和ORC肿瘤分级显著影响OS。基于每个独立风险因素的评估得分，我们制定了群马大学肿瘤研究小组（GUOSG）评分，该评分预测RFS、CSS和OS。GUOSG评分将RFS分为四组，CSS分为三组，OS分为五组，几乎所有比较的分布都具有统计学意义。结论：GUOSG模型有助于显示个体化预后，并作为一个风险分层的历史队列来评估新的挽救治疗方案的终身疗效。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.