构建胰腺癌患者化疗相关性恶心呕吐（CINV）的风险因素模型，并验证其应用效果。

回顾性收集2022年2月至2024年2月中国人民解放军空军军医大学第一附属医院收治的138例胰腺癌患者，根据是否出现CINV，将患者分为CINV组（n=57）和无CINV组（n=81），分析两组患者临床资料差异，通过单因素分析筛选有统计学意义的变量，进一步通过多因素Logistic回归验证。按3∶1分为训练组（n=104）和验证组（n=34），构建列线图（Nomogram）预测模型，并以受试者操作特征曲线（ROC）及决策曲线分析（DCA）验证模型预测效能与校准度。

CINV组和无CINV组在年龄、既往晕动病、妊娠期恶心呕吐史、匹兹堡睡眠质量指数（PSQI）评分、焦虑自评量表（SAS）评分、化疗次数、胃肠道疾病、预期性CINV、低钾血症、低镁血症、营养不良等方面具有明显差异（P<0.05）。Logistic多因素分析显示，年龄18~50岁、既往晕动病、妊娠期恶心呕吐史、PSQI评分≥8分、SAS评分≥50分、化疗次数<3次、合并胃肠道疾病、预期性CINV、低钾血症、低镁血症、营养不良均为影响胰腺癌CINV发生的独立危险因素（P<0.05）。模型应用于训练组、验证组的曲线下面积分别为0.843、0.838，应用于验证组的灵敏度、特异性分别为82.70%、83.19%，DCA分析示模型临床净收益率较高。通过校准曲线分析和Hosmer-Lemeshow检验（P=0.372）验证，模型预测概率与实际观察概率高度一致，提示良好的校准度。

胰腺癌患者CINV发生的风险较高，且与年龄、既往晕动病、妊娠期恶心呕吐史、PSQI评分、SAS评分、化疗次数、胃肠道疾病、预期性CINV、低钾血症、低镁血症、营养不良等因素有关，基于上述因素建立的预测模型能够为胰腺癌患者CINV发生减少风险评估提供可靠参考。

To construct a risk factor model of chemotherapy-induced nausea and vomiting (CINV) in patients with pancreatic cancer and verify its application effect.

A retrospective collection was made of 138 patients with pancreatic cancer admitted to First Affiliated Hospital of Air Force Medical University of the People's Liberation Army from February 2022 to February 2024. The patients were divided into the CINV group (n=57) and the non-CINV group (n=81) based on whether CINV occurred, the differences in clinical data between the two groups were analyzed, and statistically significant variables were screened through univariate analysis, it was further verified through multivariate Logistic regression. The patients were divided into a training group (n=104) and a validation group (n=34) at a 3∶1 ratio. A nomogram prediction model was constructed, and the receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to verify the predictive efficacy and calibration degree of the model.

The terms of age, history of motion sickness, history of nausea and vomiting during pregnancy, sleep status (Pittsburgh Sleep Quality Index, PSQI score), anxiety level (Self-Rating Anxiety Scale, SAS score), number of chemotherapy cycles, gastrointestinal diseases, psychological anticipation of CINV, hypokalemia, hypomagnesemia, and malnutrition between the CINV group and the non-CINV group were significantly different (P<0.05). Logistic multivariate analysis showed that age 18-50 years old, previous motion sickness, history of nausea and vomiting during pregnancy, PSQI score ≥8 points, SAS score ≥50 points, chemotherapy frequency <3 times, combined gastrointestinal diseases, psychological anticipation of CINV, hypokalemia, hypomagnesemia, and malnutrition were all independent risk factors affecting the occurrence of CINV in pancreatic cancer (P<0.05). The areas under the curve of the model applied in the training group and the verification group were 0.843 and 0.838 respectively, and the sensitivity and specificity applied in the verification group were 82.70% and 83.19% respectively, and DCA analysis showed that the clinical net rate of return of the model was relatively high. Through calibration curve analysis and Hosmer-Lemeshow test (P=0.372) verification, the predicted probability of the model was highly consistent with the actual observed probability, suggesting a good calibration degree.

Patients with pancreatic cancer have a relatively high risk of CINV occurrence, and it is related to factors such as age, previous motion sickness, history of nausea and vomiting during pregnancy, PSQI score, SAS score, number of chemotherapy sessions, gastrointestinal diseases, psychological anticipation of CINV occurrence, hypokalemia, hypomagnesemia, and malnutrition, and the prediction model established based on the above factors can provide a reliable reference for the risk assessment of reducing the occurrence of CINV in patients with pancreatic cancer.