Literature Search

We searched MEDLINE, Embase, and SCOPUS up to December 2022. We used the string “(low skeletal muscle mass OR sarcopenia) AND (cancer)” and supplemented it with tumor-specific searches (e.g., breast cancer, esophageal cancer, pancreatic cancer, etc.). Titles and abstracts underwent screening, followed by full-text evaluation.

Inclusion and Exclusion Criteria

Studies were included if they:

1. Enrolled adult patients with malignant solid tumors.
2. Assessed LSMM or sarcopenia via CT at L3 level, with muscle area normalized by height (SMI).
3. Reported prevalence of LSMM or sarcopenia.
4. Provided data on country or region.

Exclusion criteria were:

• Reviews, case reports, and non-English publications.
• Pediatric cohorts, hematologic malignancies, or primary central nervous system tumors.
• Muscle measurements solely by MRI, bioelectrical impedance, or at other anatomic sites.

Duplicate records were removed. Two radiologists independently selected studies; disagreements were settled by a third reviewer.

Data Extraction and Quality Assessment

From each study, we extracted: sample size, cancer type, country/region, treatment intent (curative/palliative), and the proportion of sarcopenic patients. We used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) to evaluate study risk of bias across four domains (patient selection, index test, reference standard, flow/timing).

We grouped countries into three regions (Europe, North America, Asia). If a study included both curative and palliative patients, we recorded each cohort separately if possible.

Statistical Analysis

We used a DerSimonian and Laird fixed-effects model, weighting effect sizes by inverse variance. Heterogeneity was assessed using the I² statistic. Egger’s test evaluated potential publication bias. Our primary endpoint was overall sarcopenia prevalence. Secondary analyses included tumor-specific prevalence stratified by region and treatment setting.