| 朱仔雯,罗鑫婷,项蓉蓉,等.基于营养－免疫－炎症评分构建晚期胰腺癌化疗患者预后模型[J].肿瘤学杂志,2026,32(7):573-580. |
| 基于营养－免疫－炎症评分构建晚期胰腺癌化疗患者预后模型 |
| Development and Validation of a Prognostic Model Based on Nutritional-Immune-Inflammatory Score for Advanced Pancreatic Cancer Patients Undergoing Chemotherapy |
| 投稿时间：2025-11-06 |
| DOI：10.11735/j.issn.1671-170X.2026.07.B008 |
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| 中文关键词: 胰腺肿瘤 预后 炎症 免疫 营养 列线图 生存 |
| 英文关键词:pancreatic neoplasms prognosis inflammation immunity nutrition Nomogram survival |
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| 中文摘要: |
| 摘 要：［目的］ 构建基于营养－免疫－炎症相关生物标志物的风险评分，并建立列线图模型预测晚期胰腺癌化疗患者生存情况。 ［方法］ 回顾性收集2019年1月至2024年10月徐州医科大学附属医院179例晚期胰腺癌化疗患者的临床资料，男性110例，女性69例，中位年龄63岁，单部位转移124例，多部位转移55例。采用R语言4.4.3及SPSS 27.0软件按照7∶3比例随机划分为训练集（n=125）和验证集（n=54）。通过LASSO-Cox回归模型筛选最具预测价值的变量并构建风险评分。根据多因素Cox回归分析筛选独立预后因素，并建立列线图，采用一致性指数、校准曲线和决策曲线对列线图可信性进行评估。［结果］ 训练集和验证集在年龄、性别、糖尿病病史、首次化疗方案、体质指数及主要实验室指标等基线特征差异均无统计学意义（均P>0.05）。全组患者中位生存时间为7个月［95%置信区间（confidence interval，CI）：5.8~8.2个月］。LASSO-Cox回归模型筛选最具预测价值的变量结果显示，中性粒细胞-淋巴细胞比值（neutrophil-to-lymphocyte ratio，NLR）、预后营养指数（prognostic nutritional index，PNI）、白蛋白-胆红素评分（albumin-bilirubin score，ALBI）和白蛋白-碱性磷酸酶比值（albumin-alkaline phosphatase ratio，AAPR）与生存期相关，风险评分=（0.068 6×NLR）+（-0.013 2×PNI）+（0.484 6×ALBI）+（-0.422 9×AAPR）。Cox多因素分析结果显示，风险评分［风险比（hazard ratio，HR）=4.113，95%CI：2.284~7.408］、CA19-9（HR=1.997，95%CI：1.099~3.629）和CA125（HR=1.979，95%CI：1.194~3.279）是影响总生存时间的独立危险因素，基于此构建列线图。训练集与验证集的一致性指数C分别为0.746和0.716，校准曲线及决策曲线均提示列线图具有良好的准确性和有效性。［结论］ 构建基于营养－免疫－炎症相关生物标志物的风险评分可作为晚期胰腺癌化疗患者个体化预后评估有效预测工具，为临床风险分层及治疗方案选择提供参考依据。 |
| 英文摘要: |
| Abstract： ［Objective］ To develop a risk score based on nutritional-immune-inflammatory biomarkers and to construct a Nomogram for predicting survival outcomes for patients with advanced pancreatic cancer undergoing chemotherapy. ［Methods］ Clinical data of 179 patients with advanced pancreatic cancer treated with chemotherapy between January 2019 and October 2024 were retrospectively reviewed. The study included 110 men and 69 women with a median age of 63 years， 124 patients had single-site metastasis and 55 had multi-site metastasis. Patients were randomly divided into a training set (n=125) and a validation set (n=54) in a 7∶3 ratio using R version 4.4.3 and SPSS version 27.0. Predictive variables were selected via LASSO-Cox regression to construct the risk score. Independent prognostic factors were identified by multivariate Cox proportional hazards regression， and a Nomogram was subsequently developed. The performance of the Nomogram was evaluated using the concordance index (C-index)， calibration curves， and decision curve analysis (DCA). ［Results］ There was no significant difference between the training and validation sets in baseline characteristics， including age， sex， history of diabetes， first-line chemotherapy regimen， body mass index， and major laboratory indicators (all P>0.05). The median overall survival of the entire cohort was 7 months (95%CI： 5.8-8.2 months). LASSO-Cox regression identified neutrophil-to-lymphocyte ratio (NLR)， prognostic nutritional index (PNI)， albumin-bilirubin score (ALBI)， and albumin-to-alkaline phosphatase ratio (AAPR) as variables associated with survival. The risk score was calculated as follows： risk score= (0.068 6 × NLR) + (-0.013 2×PNI) + (0.484 6×ALBI) + (-0.422 9×AAPR). Multivariate Cox regression analysis showed that the risk score ［hazard ratio(HR)=4.113， 95%CI： 2.284-7.408］， CA19-9(HR=1.997， 95%CI： 1.099-3.629)， and CA125(HR=1.979， 95%CI： 1.194-3.279) were independent predictors of overall survival. A Nomogram was constructed based on these factors. The C-index values in the training and validation sets were 0.746 and 0.716， respectively. Both the calibration curves and DCA indicated favorable accuracy and clinical utility of the Nomogram. ［Conclusions］ The risk score based on nutritional-immune-inflammatory biomarkers may serve as an effective tool for individualized survival prediction in patients with advanced pancreatic cancer undergoing chemotherapy， thereby facilitating clinical risk strati-fication and treatment decision-making. |
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