Construction and validation of a risk prediction model for sarcopenia in patients after pancreaticoduodenectomy

Zhang Xiaojiao; Zhang Dan; Wang Feitong; Zhao Huiling; Ding Ling; Mao Ping

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Construction and validation of a risk prediction model for sarcopenia in patients after pancreaticoduodenectomy

更新时间：2026-06-10

- Construction and validation of a risk prediction model for sarcopenia in patients after pancreaticoduodenectomy
- Journal of Chongqing Medical University Pages: 1-9(2026)
- 作者机构：
  
  徐州医科大学附属医院肝胆胰疝外科，徐州 221000
- 作者简介：
- 基金信息：
- DOI：
  CLC： R656.6
- Received：20 February 2026，
  
  Revised：2026-04-10，
  
  Accepted：08 May 2026，
  
  Online First：10 June 2026，
- 稿件说明：
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Zhang Xiaojiao,Zhang Dan,Wang Feitong,et al.Construction and validation of a risk prediction model for sarcopenia in patients after pancreaticoduodenectomy[J].Journal of Chongqing Medical University,
DOI：

Zhang Xiaojiao,Zhang Dan,Wang Feitong,et al.Construction and validation of a risk prediction model for sarcopenia in patients after pancreaticoduodenectomy[J].Journal of Chongqing Medical University, DOI：10.13406/j.cnki.cyxb..

摘要

目的

构建并验证胰十二指肠切除术（pancreaticoduodenectomy，PD）后患者肌少症发生风险预测模型，为临床早期识别高危人群、制定个体化干预策略提供依据

。

方法

选取2023年1月至2024年12月于徐州医科大学附属医院接受PD的365例患者为研究对象，按7∶3比例分为建模组（255例）和内部验证组（110例），另选取2025年1~12月接受PD的120例患者作为外部验证组。建模组于术后30 d判定肌少症发生情况，采用单因素分析和二元Logistic回归筛选独立危险因素，构建风险预测模型并绘制列线图。验证组采用受试者工作特征曲线（receiver operating characteristic curve，ROC）、Hosmer-Lemeshow检验及决策曲线分析（decision curve analysis，DCA）评估模型的区分度、校准度和临床实用性。

结果

建模组肌少症发生率为38.8%（99/255）。Logistic回归分析显示，体质指数（body mass index，BMI）、患者主观整体营养评估量表（patient-generated subjective global assessment，PG-SGA）评分、年

龄校正查尔森合并症指数（age-adjusted Charlson comorbidity index，aCCI）及术后2周体脂率（body fat percentage，BF%）是PD术后肌少症发生的独立危险因素（

0.05）。基于上述因素构建的列线图模型，建模组、内部验证组、外部验证组的曲线下面积（area under the curve，AUC）分别为0.878［95%置信区间（95% confidence interval，95%CI）：0.835~0.921］、0.890（95%CI=0.845~0.936）、0.930（95%CI=0.883~0.977），Hosmer-Lemeshow检验P值分别为0.743、0.728、0.689，DCA显示模型在广泛风险阈值范围内具有良好的临床净获益。

结论

基于BMI、PG-SGA评分、aCCI及BF%构建的风险预测模型具有良好的预测性能，可有效评估PD术后患者肌少症发生风险，为临床精准防控提供参考。

Abstract

Objective

To construct and validate a risk prediction model for sarcopenia in patients after pancreaticoduodenectomy （PD），and to provide a basis for early identification of high-risk populations and formulation of individualized intervention strategies in clinical practice.

Methods

A total of 365 patients who underwent PD in The Affiliated Hospital of Xuzhou Medical University from January 2023 to December 2024 were enrolled as subjects，and they were divided into modeling group with 255 patients and internal validation group with 110 patients at a ratio of 7∶3. Another 120 patients who underwent PD from January to December 2025 were enrolled as the external validation group. The onset of sarcopenia was determined for the modeling group on day 30 after surgery. The univariate analysis and the binary logistic regression analysis were used to identify independent risk factors，a risk prediction model was constructed，and a nomogram was plotted. For the validation groups，the receiver operating characteristic（ROC） curve，the Hosmer-Lemeshow test，and decision curve analysis（DCA） were used to assess the discriminatory ability，calibration，and clinical practicability of the model.

Results

The incidence rate of sarcopenia was 38.8%（99/255） in the modeling group. The logistic regression analysis showed that body mass index（BMI），Patient-Generated Subjective Global Assessment（PG-SGA） score，age-

adjusted Charlson Comorbidity Index（aCCI），and body fat percentage（BF%） at 2 weeks after surgery were independent risk factors for sarcopenia after PD （all

0.05）. The nomogram model constructed based on the above factors had an area under the ROC curve of 0.878（95%CI=0.835-0.921） in the modeling group，0.890（95%CI=0.845-0.936） in the internal validation group，and 0.930（95%CI=0.883-0.977） in the external validation group，and the Hosmer-Lemeshow test showed a P value of 0.743，0.728，and 0.689，respectively. The DCA showed that the model had good net clinical benefits within a wide range of risk thresholds.

Conclusion

The risk prediction model constructed based on BMI，PG-SGA score，aCCI，and BF% has good predictive performance and can effectively assess the risk of sarcopenia in patients after PD，thereby providing a reference for precise prevention and control in clinical practice.

关键词

Keywords

references

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