{"title":"新辅助治疗后进行食管切除术的原发性食管癌患者中,有病理完全反应和无病理完全反应患者的个体化生存率预测在线工具:两个独立提名图的开发和外部验证。","authors":"Yuqin Cao, Binhao Huang, Han Tang, Dong Dong, Tianzheng Shen, Xiang Chen, Xijia Feng, Jiahao Zhang, Liqiang Shi, Chengqiang Li, Heng Jiao, Lijie Tan, Jie Zhang, Hecheng Li, Yajie Zhang","doi":"10.1136/bmjgast-2023-001253","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to develop and validate robust predictive models for patients with oesophageal cancer who achieved a pathological complete response (pCR) and those who did not (non-pCR) after neoadjuvant therapy and oesophagectomy.</p><p><strong>Design: </strong>Clinicopathological data of 6517 primary oesophageal cancer patients who underwent neoadjuvant therapy and oesophagectomy were obtained from the National Cancer Database for the training cohort. An independent cohort of 444 Chinese patients served as the validation set. Two distinct multivariable Cox models of overall survival (OS) were constructed for pCR and non-pCR patients, respectively, and were presented using web-based dynamic nomograms (graphical representation of predicted OS based on the clinical characteristics that a patient could input into the website). The calibration plot, concordance index and decision curve analysis were employed to assess calibration, discrimination and clinical usefulness of the predictive models.</p><p><strong>Results: </strong>In total, 13 and 15 variables were used to predict OS for pCR and non-pCR patients undergoing neoadjuvant therapy followed by oesophagectomy, respectively. Key predictors included demographic characteristics, pretreatment clinical stage, surgical approach, pathological information and postoperative treatments. The predictive models for pCR and non-pCR patients demonstrated good calibration and clinical utility, with acceptable discrimination that surpassed that of the current tumour, node, metastases staging system.</p><p><strong>Conclusions: </strong>The web-based dynamic nomograms for pCR (https://predict-survival.shinyapps.io/pCR-eso/) and non-pCR patients (https://predict-survival.shinyapps.io/non-pCR-eso/) developed in this study can facilitate the calculation of OS probability for individual patients undergoing neoadjuvant therapy and radical oesophagectomy, aiding clinicians and patients in making personalised treatment decisions.</p>","PeriodicalId":9235,"journal":{"name":"BMJ Open Gastroenterology","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10982901/pdf/","citationCount":"0","resultStr":"{\"title\":\"Online tools to predict individualised survival for primary oesophageal cancer patients with and without pathological complete response after neoadjuvant therapy followed by oesophagectomy: development and external validation of two independent nomograms.\",\"authors\":\"Yuqin Cao, Binhao Huang, Han Tang, Dong Dong, Tianzheng Shen, Xiang Chen, Xijia Feng, Jiahao Zhang, Liqiang Shi, Chengqiang Li, Heng Jiao, Lijie Tan, Jie Zhang, Hecheng Li, Yajie Zhang\",\"doi\":\"10.1136/bmjgast-2023-001253\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>This study aimed to develop and validate robust predictive models for patients with oesophageal cancer who achieved a pathological complete response (pCR) and those who did not (non-pCR) after neoadjuvant therapy and oesophagectomy.</p><p><strong>Design: </strong>Clinicopathological data of 6517 primary oesophageal cancer patients who underwent neoadjuvant therapy and oesophagectomy were obtained from the National Cancer Database for the training cohort. An independent cohort of 444 Chinese patients served as the validation set. Two distinct multivariable Cox models of overall survival (OS) were constructed for pCR and non-pCR patients, respectively, and were presented using web-based dynamic nomograms (graphical representation of predicted OS based on the clinical characteristics that a patient could input into the website). The calibration plot, concordance index and decision curve analysis were employed to assess calibration, discrimination and clinical usefulness of the predictive models.</p><p><strong>Results: </strong>In total, 13 and 15 variables were used to predict OS for pCR and non-pCR patients undergoing neoadjuvant therapy followed by oesophagectomy, respectively. Key predictors included demographic characteristics, pretreatment clinical stage, surgical approach, pathological information and postoperative treatments. The predictive models for pCR and non-pCR patients demonstrated good calibration and clinical utility, with acceptable discrimination that surpassed that of the current tumour, node, metastases staging system.</p><p><strong>Conclusions: </strong>The web-based dynamic nomograms for pCR (https://predict-survival.shinyapps.io/pCR-eso/) and non-pCR patients (https://predict-survival.shinyapps.io/non-pCR-eso/) developed in this study can facilitate the calculation of OS probability for individual patients undergoing neoadjuvant therapy and radical oesophagectomy, aiding clinicians and patients in making personalised treatment decisions.</p>\",\"PeriodicalId\":9235,\"journal\":{\"name\":\"BMJ Open Gastroenterology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10982901/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMJ Open Gastroenterology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1136/bmjgast-2023-001253\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GASTROENTEROLOGY & HEPATOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Open Gastroenterology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjgast-2023-001253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GASTROENTEROLOGY & HEPATOLOGY","Score":null,"Total":0}
Online tools to predict individualised survival for primary oesophageal cancer patients with and without pathological complete response after neoadjuvant therapy followed by oesophagectomy: development and external validation of two independent nomograms.
Objective: This study aimed to develop and validate robust predictive models for patients with oesophageal cancer who achieved a pathological complete response (pCR) and those who did not (non-pCR) after neoadjuvant therapy and oesophagectomy.
Design: Clinicopathological data of 6517 primary oesophageal cancer patients who underwent neoadjuvant therapy and oesophagectomy were obtained from the National Cancer Database for the training cohort. An independent cohort of 444 Chinese patients served as the validation set. Two distinct multivariable Cox models of overall survival (OS) were constructed for pCR and non-pCR patients, respectively, and were presented using web-based dynamic nomograms (graphical representation of predicted OS based on the clinical characteristics that a patient could input into the website). The calibration plot, concordance index and decision curve analysis were employed to assess calibration, discrimination and clinical usefulness of the predictive models.
Results: In total, 13 and 15 variables were used to predict OS for pCR and non-pCR patients undergoing neoadjuvant therapy followed by oesophagectomy, respectively. Key predictors included demographic characteristics, pretreatment clinical stage, surgical approach, pathological information and postoperative treatments. The predictive models for pCR and non-pCR patients demonstrated good calibration and clinical utility, with acceptable discrimination that surpassed that of the current tumour, node, metastases staging system.
Conclusions: The web-based dynamic nomograms for pCR (https://predict-survival.shinyapps.io/pCR-eso/) and non-pCR patients (https://predict-survival.shinyapps.io/non-pCR-eso/) developed in this study can facilitate the calculation of OS probability for individual patients undergoing neoadjuvant therapy and radical oesophagectomy, aiding clinicians and patients in making personalised treatment decisions.
期刊介绍:
BMJ Open Gastroenterology is an online-only, peer-reviewed, open access gastroenterology journal, dedicated to publishing high-quality medical research from all disciplines and therapeutic areas of gastroenterology. It is the open access companion journal of Gut and is co-owned by the British Society of Gastroenterology. The journal publishes all research study types, from study protocols to phase I trials to meta-analyses, including small or specialist studies. Publishing procedures are built around continuous publication, publishing research online as soon as the article is ready.