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ABSTRACT Introduction Pancreatic cancer has a high mortality rate due to late diagnosis and presentation with non‐specific symptoms like weight loss. Quantifying weight loss more precisely could enhance its utility as a diagnostic marker. Methods In March 2025, we systematically searched PubMed, Embase, Web of Science, The Cochrane Library, and Scopus for studies reporting quantitative pre‐diagnosis weight loss in pancreatic cancer, with no date restrictions. The protocol was registered with PROSPERO (CRD42022302985). Primary outcomes were weight loss (kg) and BMI change (kg/m 2 ). Meta‐analyses provided pooled estimates with 95% confidence intervals, displayed in forest plots. We conducted stratified analyses at the study level by diabetes status, cancer type, self‐reported weight change, and timing of weight loss. Subgroup analyses considered publication year, country, study design, mean age, and percentage of male participants. Study quality and bias were assessed using the ROBINS‐I framework. Results The analysis included 25 studies (25,971 participants). In random‐effects meta‐analysis, we found that on average participants lost 5.9 kg 95% CI 4.7 to 7.1 of body weight. The average BMI change was −2.5 kg/m 2 95% CI −3.0 to −2.1. There was significant heterogeneity between studies for both weight loss (I 2 = 99.2%) and BMI change (I 2 = 82.6%). For weight loss in kg, heterogeneity was partially explained ( p < 0.001) by diabetes status (0.15%), weight loss timing (15.5%), whether weight loss was self‐reported (11.4%) and publication year (13.1%). For BMI change heterogeneity was partially explained ( p < 0.001) by pancreatic cancer type (1.3%), whether BMI change was self‐reported (49.6%) and publication year (49.5%). Post hoc pairwise comparisons of moderators for stratified analysis were not significant ( p < 0.0125). The certainty of evidence was moderate due to high heterogeneity between studies. Conclusions This meta‐analysis provides a reference for expected weight loss in pancreatic cancer, aiding clinical practice and improving early detection models.
Price et al. (Sun,) studied this question.