ArticleCancer imaging : the official publication of the International Cancer Imaging Society2026
Temporal change in skeletal muscle index as a predictor of recurrence for patients with locally advanced colorectal malignancy: a retrospective cohort study.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundColorectal cancer remains a leading cause of cancer-related morbidity and mortality with stage III disease carrying a substantial risk of recurrence despite curative resection. Accurate risk stratification is essential to optimize surveillance and guide adjuvant therapy. Traditional risk models rely heavily on pathologic features, but recent studies suggest that body composition metrics, particularly imaging-based assessments of skeletal muscle mass, may offer additional prognostic value. The skeletal muscle index (SMI), derived from routine CT imaging, has emerged as a promising surrogate marker of frailty. However, the relationship between temporal changes in SMI and cancer recurrence remains poorly understood.
methodsA retrospective cohort study was performed using single-institution data from over 500 patients who underwent resection for stage III colorectal malignancy. SMI at diagnosis (SMI
resultsA decrease in SMI was independently associated with increased risk of disease recurrence with an odds ratio of 2.23 per 10% decline (95% CI: 1.15-4.35, p = 0.018). Baseline muscle status was not associated with recurrence (OR 1.01 per cm
conclusionsPostoperative decline in skeletal muscle index is a significant, independent predictor of colorectal cancer recurrence. Clinically relevant risk stratification thresholds have been proposed and support the conclusion that longitudinal monitoring of SMI may have value to escalate surveillance intensity rather than being a passive prognostic marker. Future studies should focus on validating these thresholds in large, multi-center cohorts.
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