{"title":"Nomograms for Predicting Overall and Cancer-Specific Survival Among Second Primary Endometrial Cancer in Primary Colorectal Carcinoma Patients.","authors":"Linli Liu","doi":"10.2147/RMHP.S481880","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Endometrial cancer (EC) is one of the most frequent gynecologic cancers, approximately 20% of patients are regarded as high-risk with poor prognosis. However, more details of patients with second primary endometrial cancer (SPEC) after colorectal cancer (CRC) remain poorly understood. We therefore proposed to construct two nomograms to predict 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates to facilitate clinical application.</p><p><strong>Methods: </strong>A total of 1631 participants were identified in the SEER database from 1973 to 2020. We constructed and validated the nomograms for predicting OS and CSS. The receiver operating characteristic curves, calibration plot, decision curve analysis, C-index, net reclassification improvement, and integrated discrimination improvement were applied to evaluate the predictive performance. Finally, the Prognostic index was calculated and used for risk stratification of Kaplan-Meier survival analysis based on different treatment options.</p><p><strong>Results: </strong>Nomograms of OS and CSS were formulated based on the independent prognostic factors utilizing the training set. The 3- and 5- years of OS nomogram demonstrated good discrimination (AUC = 0.840 and 0.829, respectively), well-calibrated power, and excellent clinical effectiveness. Our nomograms of predicting OS and CSS had a concordance index of 0.801 and 0.866 compared with 0.676 and 0.746 for the AJCC staging system, and more importantly, demonstrated a better forecast accuracy. Chemoradiotherapy displayed a significant survival benefit in the high-risk groups, but proceeding to surgery plus chemotherapy showed a favorable survival for the low groups based on all patients.</p><p><strong>Conclusion: </strong>We developed and internally validated multivariable models that predict OS and CSS risk of SPEC in patients with a CRC to help clinicians make applicable clinical decisions for patients.</p>","PeriodicalId":56009,"journal":{"name":"Risk Management and Healthcare Policy","volume":"17 ","pages":"2959-2970"},"PeriodicalIF":2.7000,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11625644/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risk Management and Healthcare Policy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/RMHP.S481880","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Endometrial cancer (EC) is one of the most frequent gynecologic cancers, approximately 20% of patients are regarded as high-risk with poor prognosis. However, more details of patients with second primary endometrial cancer (SPEC) after colorectal cancer (CRC) remain poorly understood. We therefore proposed to construct two nomograms to predict 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates to facilitate clinical application.
Methods: A total of 1631 participants were identified in the SEER database from 1973 to 2020. We constructed and validated the nomograms for predicting OS and CSS. The receiver operating characteristic curves, calibration plot, decision curve analysis, C-index, net reclassification improvement, and integrated discrimination improvement were applied to evaluate the predictive performance. Finally, the Prognostic index was calculated and used for risk stratification of Kaplan-Meier survival analysis based on different treatment options.
Results: Nomograms of OS and CSS were formulated based on the independent prognostic factors utilizing the training set. The 3- and 5- years of OS nomogram demonstrated good discrimination (AUC = 0.840 and 0.829, respectively), well-calibrated power, and excellent clinical effectiveness. Our nomograms of predicting OS and CSS had a concordance index of 0.801 and 0.866 compared with 0.676 and 0.746 for the AJCC staging system, and more importantly, demonstrated a better forecast accuracy. Chemoradiotherapy displayed a significant survival benefit in the high-risk groups, but proceeding to surgery plus chemotherapy showed a favorable survival for the low groups based on all patients.
Conclusion: We developed and internally validated multivariable models that predict OS and CSS risk of SPEC in patients with a CRC to help clinicians make applicable clinical decisions for patients.
期刊介绍:
Risk Management and Healthcare Policy is an international, peer-reviewed, open access journal focusing on all aspects of public health, policy and preventative measures to promote good health and improve morbidity and mortality in the population. Specific topics covered in the journal include:
Public and community health
Policy and law
Preventative and predictive healthcare
Risk and hazard management
Epidemiology, detection and screening
Lifestyle and diet modification
Vaccination and disease transmission/modification programs
Health and safety and occupational health
Healthcare services provision
Health literacy and education
Advertising and promotion of health issues
Health economic evaluations and resource management
Risk Management and Healthcare Policy focuses on human interventional and observational research. The journal welcomes submitted papers covering original research, clinical and epidemiological studies, reviews and evaluations, guidelines, expert opinion and commentary, and extended reports. Case reports will only be considered if they make a valuable and original contribution to the literature. The journal does not accept study protocols, animal-based or cell line-based studies.