Body mass index, weight change, and cancer prognosis: a meta-analysis and systematic review of 73 cohort studies.

BACKGROUND: Identifying the association between body mass index (BMI) or weight change and cancer prognosis is essential for the development of effective cancer treatments. We aimed to assess the strength and validity of the evidence of the association between BMI or weight change and cancer prognosis by a systematic evaluation and meta-analysis of relevant cohort studies.

METHODS: We systematically searched the PubMed, Web of Science, EconLit, Embase, Food Sciences and Technology Abstracts, PsycINFO, and Cochrane databases for literature published up to July 2023. Inclusion criteria were cohort studies with BMI or weight change as an exposure factor, cancer as a diagnostic outcome, and data type as an unadjusted hazard ratio (HR) or headcount ratio. Random- or fixed-effects models were used to calculate the pooled HR along with the 95% confidence interval (CI).

RESULTS: Seventy-three cohort studies were included in the meta-analysis. Compared with normal weight, overweight or obesity was a risk factor for overall survival (OS) in patients with breast cancer (HR 1.37, 95% CI 1.22-1.53; P < 0.0001), while obesity was a protective factor for OS in patients with gastrointestinal tumors (HR 0.67, 95% CI 0.56-0.80; P < 0.0001) and lung cancer (HR 0.67, 95% CI 0.48-0.92; P = 0.01) compared with patients without obesity. Compared with normal weight, underweight was a risk factor for OS in patients with breast cancer (HR 1.15, 95% CI 0.98-1.35; P = 0.08), gastrointestinal tumors (HR 1.54, 95% CI 1.32-1.80; P < 0.0001), and lung cancer (HR 1.28, 95% CI 1.22-1.35; P < 0.0001). Compared with nonweight change, weight loss was a risk factor for OS in patients with gastrointestinal cancer.

CONCLUSIONS: Based on the results of the meta-analysis, we concluded that BMI, weight change, and tumor prognosis were significantly correlated. These findings may provide a more reliable argument for the development of more effective oncology treatment protocols.