Preoperative Albumin to Alkaline Phosphatase Ratio and Inflammatory Burden Index for Rectal Cancer Prognostic Nomogram-Construction: Based on Multiple Machine Learning

Autor: Li X, Zhou Z, Zhou C, Xiong M, Xing C, Wu Y
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Journal of Inflammation Research, Vol Volume 17, Pp 11161-11174 (2024)
Druh dokumentu: article
ISSN: 1178-7031
Popis: Xiangyong Li,1 Zeyang Zhou,1 Chenxi Zhou,1 Mengya Xiong,2 Chungen Xing,1 Yong Wu1 1Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People’s Republic of China; 2Operating Room, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People’s Republic of ChinaCorrespondence: Yong Wu; Chungen Xing, Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Soochow University, Suzhou City, Jiangsu Province, People’s Republic of China, Email wuyong6302@163.com; xingcg@suda.edu.cnPurpose: Preoperative albumin to alkaline phosphatase ratio (AAPR) and inflammatory burden index (IBI) are prognostic indicators for a multitude of cancers, and our study focuses on evaluating the prognostic significance of the AAPR and the IBI on rectal cancer (RC) patients to provide a more accurate guideline for patient prognosis.Patients and Methods: This study enrolled patients who underwent laparoscopic rectal cancer surgery from January 2016 to January 2021. We utilized three machine learning approaches to select variables most relevant to prognosis in the training cohort. Finally, based on the screened variables, a nomogram was established to predict RC patients’ overall survival (OS). The improvement in predictive ability and clinical benefit was assessed through the concordance index (C-index), receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA).Results: A total of 356 patients were enrolled and they were randomly divided into a training cohort (60%, n=214) and a validation cohort (40%, n=143). Overall survival (OS) was worse for patients in either the low AAPR or the high AAPR group, whereas patients in the low AAPR with both high IBI group had the lowest OS (P< 0.001). Finally, five variables were obtained after screening the best variables by three machine learning, and the nomogram was constructed. In both the development and validation cohorts, the C-index values exceeded 0.85, indicating that the predictive model has a strong predictive performance in terms of overall survival. The calibration curves and the decision curve analysis (DCA) showed that the nomogram demonstrated a superior benefit.Conclusion: Preoperative AAPR and IBI can serve as effective indicators for predicting the OS of RC patients. We have developed a nomogram for predicting the OS of patients who underwent laparoscopic rectal cancer surgery.Keywords: albumin to alkaline phosphatase ratio, inflammatory burden index, rectal cancer, overall survival, prediction nomogram
Databáze: Directory of Open Access Journals