Development and validation of a web-based predictive model for preoperative diagnosis of localized colorectal cancer and colorectal adenoma

ABSTRACT:

Background

Localized colorectal cancer (LCC) has obscure clinical signs, which are difficult to distinguish from colorectal adenoma (CA). This study aimed to develop and validate a web-based predictive model for preoperative diagnosis of LCC and CA.

Methods

We conducted a retrospective study that included data from 500 patients with LCC and 980 patients with CA who were admitted to Dongyang People’s Hospital between November 2012 and June 2022. Patients were randomly divided into the training (n=1036) and validation (n=444) cohorts. Univariate logistic regression, least absolute shrinkage and selection operator regression, and multivariate logistic regression were used to select the variables for predictive models. The area under the curve (AUC), calibration curve, decisi

SUBMITTER:  

PROVIDER: S-EPMC10470828 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature