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Introduction <p>Sarcopenia negatively impacts surgical outcomes in gastrointestinal cancer patients, yet practical preoperative screening tools are lacking. The CRP/ALB ratio, a novel biomarker of systemic inflammation and nutritional status, may enhance sarcopenia prediction but remains underexplored in surgical oncology. This study aims to identify the predictors for preoperative sarcopenia prediction in gastric and colorectal cancer patients.</p> Methods <p>This retrospective study analyzed 145 patients undergoing curative surgery (2019–2021). Sarcopenia was defined by sex-specific CT-measured L3 skeletal muscle index (cutoffs, male ≤ 40.8 cm<sup>2</sup>/m<sup>2</sup>; female ≤ 34.9 cm<sup>2</sup>/m<sup>2</sup>). Multivariable logistic regression identified predictors, with model performance assessed via ROC analysis and Cohen’s Kappa.</p> Results <p>The cohort (median age 64&#xa0;years; 73.8% male) comprised 66 gastric (45.5%) and 79 colorectal (54.5%) cancer patients, with 29 (20%) diagnosed with sarcopenia. Sarcopenic patients exhibited a higher NRS 2002 score (<i>P</i> &lt; 0.001), lower PNI score (<i>P</i> &lt; 0.05), and higher CRP/ALB ratio (<i>P</i> &lt; 0.05). Multivariate logistic regression analysis results showed that CRP/ALB ratio (OR = 3.084, 95% CI 1.071–8.882, <i>P</i> = 0.037), age (OR = 1.074, 95% CI 1.021–1.130, <i>P</i> = 0.006), and BMI (OR = 0.667, 95% CI 0.542–0.820, <i>P</i> = 0.000) were associated with the increased risk of sarcopenia. The combined model achieved superior discrimination (AUC = 0.854, 95% CI 0.770–0.937), yielding 75.86% sensitivity and 84.82% specificity at optimal cutoff value − 1.0340, and a Cohen’s Kappa coefficient of 0.542 when compared to CT results.</p> Conclusion <p>The CRP/ALB ratio combined with BMI and age is utilized as a convenient and effective tool for preoperative sarcopenia screening. This model-driven approach provides robust strategies to facilitate preoperative interventions, optimize perioperative care, and enhance long-term oncological outcomes for patients undergoing gastric and colorectal cancer surgery.</p>

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Preoperative Prediction of Sarcopenia in Patients Scheduled for Gastric and Colorectal Cancer Surgery

  • 期刊论文

  • 发表日期：

    2025年3月21日

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  • Beijia Zhou,
  • Yanjun Song,
  • Chen Chen,
  • Xiaotian Chen,
  • Tingting Tao

摘要

Introduction

Sarcopenia negatively impacts surgical outcomes in gastrointestinal cancer patients, yet practical preoperative screening tools are lacking. The CRP/ALB ratio, a novel biomarker of systemic inflammation and nutritional status, may enhance sarcopenia prediction but remains underexplored in surgical oncology. This study aims to identify the predictors for preoperative sarcopenia prediction in gastric and colorectal cancer patients.

Methods

This retrospective study analyzed 145 patients undergoing curative surgery (2019–2021). Sarcopenia was defined by sex-specific CT-measured L3 skeletal muscle index (cutoffs, male ≤ 40.8 cm2/m2; female ≤ 34.9 cm2/m2). Multivariable logistic regression identified predictors, with model performance assessed via ROC analysis and Cohen’s Kappa.

Results

The cohort (median age 64 years; 73.8% male) comprised 66 gastric (45.5%) and 79 colorectal (54.5%) cancer patients, with 29 (20%) diagnosed with sarcopenia. Sarcopenic patients exhibited a higher NRS 2002 score (P < 0.001), lower PNI score (P < 0.05), and higher CRP/ALB ratio (P < 0.05). Multivariate logistic regression analysis results showed that CRP/ALB ratio (OR = 3.084, 95% CI 1.071–8.882, P = 0.037), age (OR = 1.074, 95% CI 1.021–1.130, P = 0.006), and BMI (OR = 0.667, 95% CI 0.542–0.820, P = 0.000) were associated with the increased risk of sarcopenia. The combined model achieved superior discrimination (AUC = 0.854, 95% CI 0.770–0.937), yielding 75.86% sensitivity and 84.82% specificity at optimal cutoff value − 1.0340, and a Cohen’s Kappa coefficient of 0.542 when compared to CT results.

Conclusion

The CRP/ALB ratio combined with BMI and age is utilized as a convenient and effective tool for preoperative sarcopenia screening. This model-driven approach provides robust strategies to facilitate preoperative interventions, optimize perioperative care, and enhance long-term oncological outcomes for patients undergoing gastric and colorectal cancer surgery.