Preoperative abnormal bone mineral density as a prognostic indicator in patients undergoing gastrectomy for gastric cancer: A cohort study

Abstract

Predicting postgastrectomy relapse and mortality in patients with gastric cancer (GC) remains challenging, with limitations to traditional staging systems such as the tumor–node–metastasis (TNM) system. This study aimed to investigate the impact of preoperative Hounsfield unit (HU) values, which serve as a surrogate marker for bone mineral density (BMD), in predicting survival outcomes in patients with GC. A retrospective analysis was conducted on data from patients with GC who underwent curative-intent gastrectomy. Opportunistic abdominopelvic computed tomography images were used to assess HU values at the 3rd lumbar vertebra (L3). These values were then categorized using a cutoff value of 110 HU, which has been established in previous studies as a determinant for abnormal versus normal BMD. Cox regression analysis established predictor models for overall survival (OS). Among 501 initial patients, 478 met the inclusion criteria. Multivariate analyses revealed HU values (hazard ratio, 1.51), along with other factors (the 5-factor modified frailty index, type of gastrectomy, TNM stage, anemia, and serum albumin level), as significant predictors of OS. The full model (FM) incorporating these variables demonstrated superior discrimination ability compared to the baseline model (BM), which is based solely on the TNM stage (concordance index: 0.807 vs 0.709; P < .001). Furthermore, the FM outperformed the BM in predicting OS risks at 36- and 60-months post-surgery. In conclusion, among patients undergoing gastrectomy for GC, those with HU values ≤ 110 (indicating abnormal BMD) at the L3 level, as determined through opportunistic CT scans, exhibited a poorer prognosis than those with HU values > 110 (indicating normal BMD). Integrating HU with other clinicopathological parameters enhances predictive accuracy, facilitating individualized risk stratification and treatment decision-making, which could potentially lead to improved survival outcomes.