Mary C. Playdon

Obesity is a well‐established risk factor for numerous cancers, with body habitus, especially central adiposity, contributing to increased cancer incidence and worse prognosis. Glucagon‐like peptide‐1 receptor agonists (GLP‐1 RAs), initially developed to treat Type 2 diabetes, have rapidly gained prominence as powerful anti‐obesity agents due to their ability to induce significant weight loss and potential to improve metabolic health. These medications act by reducing appetite, enhancing insulin sensitivity, lowering systemic inflammation, and preferentially targeting fat mass for reduction. This review explores the growing body of evidence linking GLP‐1 RA therapy to potential changes in cancer risk among individuals with obesity. To date, data suggest that GLP‐1 RAs do not increase overall cancer risk and may reduce the risk of certain obesity‐related cancers, likely by interrupting obesity‐driven metabolic dysregulation. Still, questions remain about the beneficial effects of weight loss and the sustainability of health benefits if weight is regained after stopping treatment. We examine how GLP‐1 RAs' anti‐inflammatory and metabolic effects might mediate reductions in cancer risk, review emerging data regarding both protective signals and specific safety concerns (e.g., increased risk of medullary thyroid carcinoma), and emphasize the critical role of combining pharmacotherapy with lifestyle interventions to maintain muscle mass and long‐term weight loss. Ultimately, given the strong link between obesity and cancer, GLP‐1 RAs represent a promising new class of agents that may not only help to manage obesity but also serve as effective chemopreventive tools against obesity‐associated cancers.

Composite dietary and lifestyle indices capture the combined effects of multiple health-related behaviours and may better reflect real-world cancer risk and survivorship than single exposures. This umbrella review aimed to evaluate and grade the strength of evidence for associations between adherence to composite dietary and lifestyle quality indices and endometrial cancer (EC) outcomes, including risk, EC-specific survival, overall survival, disease recurrence, quality of life, and new-onset cardiometabolic diseases. PubMed, Embase, Scopus, Web of Science, CINAHL, and Cochrane Library databases were systematically searched for relevant systematic reviews. Evidence was graded using prespecified umbrella review criteria. A total of 21 systematic reviews were included. Nine investigated diet quality (7 meta-analyses) and 12 investigated lifestyle exposure or interventions (8 meta-analyses). The outcomes assessed were EC risk (N = 14), all-cause or cancer-specific mortality (N = 5), recurrence (N = 4), overall or cancer-specific survival (N = 3), QoL (N = 5), and cardiometabolic events (N = 1). Following a Mediterranean diet was associated with 29% lower odds of EC (pooled OR = 0.71, 95% CI 0.51–0.98; class IV), whereas Western dietary patterns were associated with 20% higher odds of EC (pooled OR = 1.20, 95% CI 1.03–1.39; class IV). A combined healthy diet and lifestyle approach was associated with a 46% lower hazard of EC incidence (pooled HR = 0.54, 95% CI 0.42–0.71; class III), although heterogeneity was high. No significant associations were observed between lifestyle interventions and global or domain-specific quality of life (QoL) across follow-up durations ranging from 9 weeks to 12 months, irrespective of the validated assessment instruments used. Evidence remains limited regarding the associations between diet and lifestyle factors and EC recurrence, survival, mortality, and cardiometabolic outcomes. Our umbrella review identified suggestive (class III–IV) evidence for associations between healthy dietary patterns, particularly the Mediterranean diet, and combined healthy lifestyle approaches with lower EC incidence. Evidence remains insufficient or non‐significant for post-diagnosis outcomes, underscoring the need for further high-quality research.

Supplemental Table 5. Association between metabolic phenotypes defined by high sensitivity C-Reactive Protein (hs-CRP) ≥ 10 mg/L with obesity-related cancer risk in the Women’s Health Initiative cohort (N= 21,245).

Supplemental Figure 7. Hazard ratios and 95% confidence intervals for the association of metabolic phenotype defined by Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) with obesity-related cancer risk, stratified by cancer type among postmenopausal women in the Women’s Health Initiative. Model adjusted for demographics (age, education, race/ethnicity, marital status), lifestyle (smoking status, physical activity, alcohol use, fruits and vegetable intake, fiber intake, read meat intake), hormonal factors for female cancers (parity, hormone therapy use), family history of ORC and study ID. MUNW=metabolically unhealthy normal weight; MHO=metabolically healthy overweight/obese; MUO= metabolically unhealthy overweight/obese. Metabolically healthy normal weight (MHNW) is the comparison group.

Supplemental Figure 1. Study Schematic of Women’s Health Initiative Participant Selection. Flowchart detailing the selection process of study participants, and the final cohort size for the study.

Supplemental Figure 4. Hazard ratios and 95% confidence intervals for the association of metabolic phenotype defined by the Wildman criteria with obesity-related cancer risk, stratified by cancer type among postmenopausal women in the Women’s Health Initiative. Model adjusted for demographics (age, education, race/ethnicity, marital status), lifestyle (smoking status, physical activity, alcohol use, fruits and vegetable intake, fiber intake, read meat intake), hormonal factors for female cancers (parity, hormone therapy use), family history of ORC and study ID. MUNW=metabolically unhealthy normal weight; MHO=metabolically healthy overweight/obese; MUO= metabolically unhealthy overweight/obese. Metabolically healthy normal weight (MHNW) is the comparison group.

Supplemental Table 6. Association between metabolic phenotypes defined by Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) with obesity-related cancer risk in the Women’s Health Initiative cohort (N= 23,232).

Supplemental Figure 2. Directed Acyclic Graph (DAG). Directed Acyclic Graph (DAG) illustrating potential causal relationships among covariates, exposure, and outcome measures in this study.

Supplemental Table 4. Association between metabolic phenotypes defined by high sensitivity C-Reactive Protein (hs-CRP) ≥ 3 mg/L with obesity-related cancer risk in the Women’s Health Initiative cohort (N= 21,245).

Supplemental Table 7. Association between metabolic phenotypes defined by Wildman criteria with obesity-related cancer (ORC) risk after excluding participants diagnosed with ORC within the first three years of follow-up in the Women’s Health Initiative cohort (N= 20,320).