Development and validation of a prognostic model for the occurrence of parastomal hernia in patients undergoing...

Parastomal hernia (PSH) is the most common long-term complication of stoma creation during rectal resection, impacting the patients' quality of life to some degree. However, current clinical practice lacks accurate tools for predicting the occurrence of PSH. The present study aimed to develop a nomogram that could predict the occurrence of PSH in patients undergoing permanent colostomy during surgery for rectal cancer.

This study retrospectively enrolled a total of 430 eligible patients. The preliminary selection of predictive factors was performed using the Least Absolute Shrinkage and Selection Operator analysis. Subsequently, a predictive model was constructed using multivariable logistic regression and presented in the form of a nomogram. The nomogram's value was evaluated using receiver-operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Internal validation was conducted by evaluating the model's performance on a validation cohort.

Altogether, 133 cases (30.9%) were diagnosed with PSH. The diagnostic model incorporated seven factors, including elderly patients (age ≥ 65 years, odds ratio [OR]: 2.51; 95% confidence interval [CI]: 1.52-4.11), Female (OR: 2.43; 95% CI: 1.36-3.69), body mass index (BMI ≥ 25 kg/m²;OR: 2.52; 95% CI: 1.52-4.15), visceral fat area (VFA) (≥ 100 cm²; OR: 2.13; 95% CI: 1.18-3.85), subcutaneous fat area (SFA) (≥ 100 cm²;OR: 2.07; 95% CI: 1.14-3.73), surrounding parastomal fat tissue (SPFT) (≥ 43.2 ml; OR: 2.07; 95% CI: 1.14-3.73), and maximum abdominal wall defect diameter (≥ 4 cm; OR: 4.12; 95% CI: 2.46-6.89). The values of the area under the ROC curve for the training and validation sets were 0.826 (95% CI: 0.776-0.877) and 0.867 (95% CI: 0.804-0.933), respectively. The calibration curve showed a high degree of agreement between the predicted and observed outcomes. DCA indicated that the nomogram holds a substantial clinical value in predicting PSH in patients undergoing permanent colostomy during rectal cancer surgery.

We developed a model to predict the occurrence of PSH in patients with rectal cancer after permanent colostomy. This nomogram can help clinicians in assessing the risk of PSH occurrence in postoperative patients, thereby enabling personalized management of high-risk patients and guiding their lifestyle to improve their quality of life.