Development and validation of a nomogram involving immunohistochemical markers for prediction of recurrence in early low-risk endometrial cancer.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2022-12-01 Epub Date: 2022-10-16 DOI:10.1177/03936155221132292

Wei Kong, Yuan Tu, Peng Jiang, Yuzhen Huang, Jingni Zhang, Shan Jiang, Ning Li, Rui Yuan

{"title":"Development and validation of a nomogram involving immunohistochemical markers for prediction of recurrence in early low-risk endometrial cancer.","authors":"Wei Kong, Yuan Tu, Peng Jiang, Yuzhen Huang, Jingni Zhang, Shan Jiang, Ning Li, Rui Yuan","doi":"10.1177/03936155221132292","DOIUrl":null,"url":null,"abstract":"Background: The purpose of this study was to construct a nomogram based on classical parameters and immunohistochemical markers to predict the recurrence of early low-risk endometrial cancer patients.Methods: A total of 998 patients with early low-risk endometrial cancer who underwent primary surgical treatment were enrolled (668 in the training cohort, 330 in the validation cohort). Prognostic factors identified by univariate and multivariate analysis in the training cohort were used to construct the nomogram. Prediction performance of the nomogram was evaluated using the calibration curve, concordance index (C-index), and the time-dependent receiver operating characteristic curve. The cumulative incidence curve was used to describe the prognosis of patients in high-risk and low-risk groups divided by the optimal risk threshold of the model.Results: In the training cohort, grade (P = 0.040), estrogen receptor (P < 0.001), progesterone receptor (P = 0.001), P53 (P = 0.004), and Ki67 (P = 0.002) were identified as independent risk factors of recurrence of early low-risk endometrial cancer, and were used to establish the nomogram. The calibration curve showed that the fitting degree of the model was good. The C-indexes of training and validation cohorts were 0.862 and 0. 827, respectively. Based on the optimal risk threshold of the nomogram, patients were split into a high-risk group and a low-risk group. The cumulative incidence curves showed that the prognosis of the high-risk group was far worse than that of the low-risk group (P < 0.001).Conclusion: This nomogram, with a combination of classical parameters and immunohistochemical markers, can effectively predict recurrence in early low-risk endometrial cancer patients.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":" ","pages":"395-403"},"PeriodicalIF":4.6000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/03936155221132292","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/10/16 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}

引用次数: 1

Abstract

Background: The purpose of this study was to construct a nomogram based on classical parameters and immunohistochemical markers to predict the recurrence of early low-risk endometrial cancer patients.

Methods: A total of 998 patients with early low-risk endometrial cancer who underwent primary surgical treatment were enrolled (668 in the training cohort, 330 in the validation cohort). Prognostic factors identified by univariate and multivariate analysis in the training cohort were used to construct the nomogram. Prediction performance of the nomogram was evaluated using the calibration curve, concordance index (C-index), and the time-dependent receiver operating characteristic curve. The cumulative incidence curve was used to describe the prognosis of patients in high-risk and low-risk groups divided by the optimal risk threshold of the model.

Results: In the training cohort, grade (P = 0.040), estrogen receptor (P < 0.001), progesterone receptor (P = 0.001), P53 (P = 0.004), and Ki67 (P = 0.002) were identified as independent risk factors of recurrence of early low-risk endometrial cancer, and were used to establish the nomogram. The calibration curve showed that the fitting degree of the model was good. The C-indexes of training and validation cohorts were 0.862 and 0. 827, respectively. Based on the optimal risk threshold of the nomogram, patients were split into a high-risk group and a low-risk group. The cumulative incidence curves showed that the prognosis of the high-risk group was far worse than that of the low-risk group (P < 0.001).

Conclusion: This nomogram, with a combination of classical parameters and immunohistochemical markers, can effectively predict recurrence in early low-risk endometrial cancer patients.

查看原文本刊更多论文

用于预测早期低风险子宫内膜癌复发的免疫组织化学标记物的nomogram发展和验证。

背景:本研究的目的是基于经典参数和免疫组织化学标志物构建预测早期低危子宫内膜癌患者复发的nomogram。方法:共纳入998例接受初级手术治疗的早期低危子宫内膜癌患者(培训组668例，验证组330例)。在训练队列中通过单因素和多因素分析确定的预后因素被用来构建nomogram。采用校准曲线、一致性指数(C-index)和随时间变化的受者工作特征曲线来评价nomogram预测性能。用累积发生率曲线描述高、低危组患者的预后除以模型的最优风险阈值。结果:在训练队列中，分级(P = 0.040)、雌激素受体(P < 0.001)、孕激素受体(P = 0.001)、P53 (P = 0.004)、Ki67 (P = 0.002)被确定为早期低危子宫内膜癌复发的独立危险因素，并用于建立nomogram。标定曲线表明，模型拟合程度较好。训练队列和验证队列的c指数分别为0.862和0。827年,分别。根据nomogram最佳风险阈值，将患者分为高危组和低危组。累积发病率曲线显示，高危组预后远差于低危组(P < 0.001)。结论:该nomogram结合经典参数和免疫组化标志物，可有效预测早期低危子宫内膜癌患者的复发。

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分钟内获得全文求助全文

来源期刊

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464

期刊介绍： ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.