Predicting prognosis for patients with ESCC before surgery by SVMs ranking with nomogram analyses.

ABSTRACT:

Objective

A SVM predictive model consisting of preoperative tumor markers and inflammatory factors was established to explore its significance in evaluating the prognosis of patients with ESCC.

Methods

Clinical data of 311 patients with ESCC who underwent surgery were collected and followed up until October 2019. Statistical software SPSS version 22.0, and R (version 3.6.1) were used to analyze the data.

Results

In the Test, Val1 and Val2 groups, the sensitivity of preoperative optimal combination (SVM5) to predict the prognosis of patients with ESCC was 88.89%, 76.92%, and 73.68%, respectively. The specificity was 92.00%, 74.42%, and 78.00%, respectively. The sensitivity and specificity were not statistically different from those of SVM9 (P > 0.05), while the sensiti

SUBMITTER: Jiang ZS 

PROVIDER: S-EPMC9452329 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature