Construction and validation of the perioral moisture-related skin damage (PMASD) risk prediction model in patients with colorectal cancer

构建和验证结直肠癌患者口周皮肤水分相关损伤(PMASD)风险预测模型

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Abstract

This study aims to analyse the risk factors of Peristomal Moisture-Associated Skin Damage (PMASD) in colorectal cancer patients, construct a prediction model, and verify its effect. A total of 375 patients who underwent rectal cancer stoma surgery at the Liaoning Cancer Hospital between January and December 2020 were selected according to the inclusion and exclusion criteria. The clinical data were retrospectively analysed for modelling and internal validation (modelling group). According to the same criteria, the clinical data of 242 patients from January and June 2021 were retrospectively analysed for external validation (validation group). Baseline patient data were recorded. Patients in the modelling group were divided into those with and without PMASD based on the occurrence of PMASD during hospitalisation. Logistic regression analysis was used to examine the factors of PMASD and the PMASD nomogram model of colorectal cancer. Internal model validation was performed with the Bootstrap method, using the ROC and H-L goodness of fit test to evaluate the differentiation and calibration of the model. Last, external validation of the model was performed. In the modelling group, 212 patients with colorectal cancer developed PMASD. According to the results of the logistic regression analysis, high fasting plasma glucose and fasting blood glucose (FPG), a history of radiotherapy, the height of the stoma opening (i.e., flat or lower than the skin surface), and skin folds around the stoma are risk factors for PMASD (OR > 1, P < 0.05). The stool shaping and colostomy are protective factors for PMASD in patients with colorectal cancer (OR < 1, P < 0.05). To establish the prediction of colorectal cancer, patient development of PMASD line, graph model, and internal verification was carried out using the Bootstrap method: H-L test P = 0.846, area under curve, area under the ROC curve (0 > 0.75, 95% CI: 0.778-0, AUC = 0.820). The external validation included the H-L test (P = 0.137, AUC [0.862] > 0.75, 95% CI: 0.815-0.909), with the maximum value of the Youden index as the best cut-off value for the model. The ROC curve had a Youden index of 0.559, a sensitivity of 0.877, and a specificity of 0.657. The prompt model area showed good calibration and discrimination. The PMASD in patients with colorectal cancer is affected by defecation traits, the stoma opening height, stoma type, FPG, skin folds around the stoma, and previous radiotherapy history. The nomogram model can provide an effective means to reasonably predict the risk of PMASD in patients with colorectal cancer.

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