# Predictive value of hemoglobin, serum PAF, and IL-17 in patients with radiation enteritis complicated with intestinal obstruction and construction and validation of predictive model

## TL;DR

This study identifies key biomarkers and builds a predictive model to help identify radiation enteritis patients at high risk of intestinal obstruction.

## Contribution

A novel nomogram prediction model combining hemoglobin, PAF, IL-17, and diabetes for early detection of intestinal obstruction in radiation enteritis patients.

## Key findings

- Diabetes, low hemoglobin, high PAF and IL-17 levels, and elevated CRP are independent risk factors for intestinal obstruction.
- The nomogram model showed good calibration with C-indexes of 0.757 and 0.772 in training and verification sets.
- DCA analysis confirmed the model's clinical utility within a specific probability threshold.

## Abstract

To explore the predictive value of hemoglobin, serum platelet-activating factor (PAF), and interleukin-17 (IL-17) for intestinal obstruction in patients with radiation enteritis, and to construct and validate a related prediction model.

A total of 234 patients who received radiotherapy and were diagnosed with radiation enteritis in our hospital from January 2018 to December 2023 were included in the study. The patients were divided into training set (n = 164) and verification set (n = 70) according to the ratio of 7:3. The hemoglobin, serum PAF and IL-17 levels of the patients were detected, and the above indicators such as age, gender, radiation dose, radiation site, radiation course, basic diseases (such as hypertension and diabetes), intestinal operation history, chemotherapy history, C-reactive protein(CRP), procalcitonin, albumin, globulin, fibrinogen, D-dimer were collected. The risk factors affecting intestinal obstruction in patients with radiation enteritis were screened by univariate analysis and multivariate Logistic regression analysis, a nomogram prediction model was constructed, the receiver operating characteristic curve (ROC) was drawn, and the calibration curve was used to evaluate the effectiveness of the model. The decision curve analysis (DCA) was used to evaluate the value of clinical application.

Multi-factor Logistic regression analysis showed that diabetes, decreased hemoglobin level, increased serum PAF and IL-17 levels, CRP, were the independent risk factors for intestinal obstruction in patients with radiation enteritis (p < 0.05). The constructed nomogram prediction model showed good calibration and fit in the training set and verification set, with C-index of 0.757 and 0.772, respectively, area under ROC curve of 0.759 (95% CI: 0.665–0.853) and 0.775 (95% CI: 0.610–0.939). DCA analysis showed that the model had significant clinical application value within a specific threshold probability range.

The nomogram prediction model constructed by diabetes, hemoglobin, serum PAF, and IL-17 combined with multiple indicators has good prediction efficiency for radiation enteritis patients complicated with intestinal obstruction, which is conducive to identifying high-risk patients in the early clinical stage and taking effective intervention measures.