Body shape phenotypes of multiple anthropometric traits and cancer risk: a multi-national cohort study

Anthropometrics and cancer prognosis: a multicenter cohort study

BACKGROUND

Anthropometric indicators have been shown to be associated with the prognosis of patients with cancer. However, any single anthropometric index has limitation in predicting the prognosis.

OBJECTIVES

This study aimed to observe the predictive role of 7 anthropometric indicators based on body size on the prognosis of patients with cancer.

METHODS

A principal component analysis (PCA) on 7 anthropometric measurements: height, weight, BMI, hand grip strength (HGS), triceps skinfold thickness (TSF), mid-upper arm circumference (MAC), and calf circumference (CAC) was conducted. Principal components (PCs) were derived from this analysis. Cox regression analysis was used to investigate the association between the prognosis of patients with cancer and the PCs. Subgroups and sensitivity analyses were also conducted.

RESULTS

Through PCA, 4 distinct PCs were identified, collectively explaining 88.3% of the variance. PC1, primarily characterized by general obesity, exhibited a significant inverse association with risk of cancer-related death (adjusted hazard ratio [HR]: 0.86; 95% confidence interval [CI]: 0.83, 0.88). PC2 (short stature with high TSF) was not significantly associated with cancer prognosis. PC3 (high BMI coupled with low HGS) demonstrated a significant increase with risk of cancer-related death (adjusted HR: 1.08; 95% CI: 1.05, 1.11). PC4 (tall stature with high TSF) exhibited a significant association with increased cancer risk (adjusted HR: 1.05; 95% CI: 1.02, 1.07). These associations varied across different cancer stages. The stability of the results was confirmed through sensitivity analyses.

CONCLUSIONS

Different body sizes are associated with distinct prognostic outcomes in patients with cancer. The impact of BMI on prognosis is influenced by both HGS and subcutaneous fat. This finding may influence the clinical care of cancer and improve the survival of cancer patients.

Multi-Trait Body Shape Phenotypes and Breast Cancer Risk in Postmenopausal Women: A Causal Mediation Analysis in the UK Biobank Cohort

Body shape phenotypes combining multiple anthropometric traits have been linked to postmenopausal breast cancer (BC). However, underlying biological pathways remain poorly understood. This study investigated to what extent the associations of body shapes with postmenopausal BC risk is mediated by biochemical markers. The study included 176,686 postmenopausal women from UK Biobank. Four body shape phenotypes were derived from principal component (PC) analysis of height, weight, body mass index, waist and hip circumferences, and waist-to-hip ratio (WHR). The four-way decomposition of the total effect was used to estimate mediation and interaction effects simultaneously as well as the mediated proportions. After 10.9 years median follow-up, 6,396 incident postmenopausal BC were diagnosed. There was strong evidence of positive associations between PC1 (general obesity) and PC2 (tall, low WHR), and BC risk. The association of PC1 with BC risk was positively mediated by testosterone and negatively by insulin-like growth factor-1 (IGF-1), with the overall proportion mediated (sum of the mediated interaction and pure indirect effect (PIE)) accounting for 11.4% (95% confidence intervals: 5.1 to 17.8%) and -12.2% (-20.5% to -4.0%) of the total effect, respectively. Small proportions of the association between PC2 and BC were mediated by IGF-1 (PIE: 2.8% (0.6 to 4.9%)), and sex hormone-binding globulin (SHBG) (PIE: -6.1% (-10.9% to -1.3%)). Our findings are consistent with differential pathways linking different body shapes with BC risk, with a suggestive mediation through testosterone and IGF-1 in the relationship of a generally obese body shape and BC risk, while IGF-1 and SHBG may mediate a tall/lean body shape-BC risk association.

New Horizons: Epidemiology of Obesity, Diabetes Mellitus, and Cancer Prognosis

The global prevalence of obesity and diabetes mellitus has increased in parallel with increasing cancer incidence, due to environmental and lifestyle factors and population aging. Metabolic diseases are associated with increased cancer risk, so a growing number of patients with cancer have coexistent obesity and/or diabetes mellitus. In this narrative review, we highlight recent evidence on the clinical impact of obesity and diabetes mellitus on the prognosis of prostate, breast, and colorectal cancer, and provide an overview of the underlying mechanisms. There is evidence that obesity is associated with increased risk of recurrence, and all-cause and cancer-specific mortality among adults with prostate, breast, and colorectal cancer. Diabetes mellitus is associated with increased all-cause and cancer-specific mortality for these 3 cancers, beyond any impact of obesity. Evidence also suggests increased risk of colorectal cancer recurrence in patients with diabetes mellitus. The underlying mechanisms are multifactorial and likely include hormonal imbalances and chronic inflammation that promote cancer cell growth. Obesity and diabetes mellitus are associated with increased risk of complications and side effects of cancer treatment. Associated comorbidities such as impaired kidney function, cardiovascular disease, and neuropathies may preclude the use of guideline cancer treatment and are competing causes of death. Cancer patients with metabolic diseases require a designated clinical program and a multidisciplinary approach involving oncologists, endocrinologists, surgeons, nutritionists, and physiotherapists, to ensure coordinated and optimized patient care.

Association between Metabolically Healthy Status and Risk of Gastrointestinal Cancer

PURPOSE

Although obesity is associated with numerous diseases, the risks of disease may depend on metabolically healthy status. Nevertheless, it is unclear to whether metabolically healthy status affects risk of gastrointestinal (GI) cancer in general Chinese population.

MATERIALS AND METHODS

A total of 114,995 participants who met the criteria were included from the Kailuan Study. The study participants were divided into four groups according to body mass index (BMI)/waist circumference (WC) and metabolic status. Incident of GI cancer (esophageal cancer, gastric cancer, liver cancer, biliary cancer, pancreatic cancer, and colorectal cancer) during 2006-2020 were confirmed by review of medical records. The Cox proportional hazard regression models were used to assess the association metabolically healthy status with the risk of GI cancer by calculating the hazard ratios (HR) and 95% confidence interval (CI).

RESULTS

During a mean 13.76 years of follow-up, we documented 2,311 GI cancers. Multivariate Cox regression analysis showed that compared with the metabolically healthy normal-weight group, metabolically healthy obese (MHO) participants demonstrated an increased risk of developing GI cancer (HR, 1.54; 95% CI, 1.11 to 2.13) by BMI categories. However, such associations were not found for WC category. These associations were moderated by age, sex, and anatomical site of the tumor. Individuals with metabolic unhealthy normal-weight or metabolic unhealthy obesity phenotype also have an increased risk of GI cancer.

CONCLUSION

MHO phenotype was associated with increased risk of GI cancer. Moreover, individuals who complicated by metabolic unhealthy status have an increased risk of developing GI cancer. Hence, clinicians should consider the risk of incident GI cancer in people with abnormal metabolically healthy status and counsel them about metabolic fitness and weight control.

Body Shape Phenotypes and Breast Cancer Risk: A Mendelian Randomization Analysis

Observational and genetic studies have linked different anthropometric traits to breast cancer (BC) risk, with inconsistent results. We aimed to investigate the association between body shape defined by a principal component (PC) analysis of anthropometric traits (body mass index [BMI], height, weight, waist-to-hip ratio [WHR], and waist and hip circumference) and overall BC risk and by tumor sub-type (luminal A, luminal B, HER2+, triple negative, and luminal B/HER2 negative). We performed two-sample Mendelian randomization analyses to assess the association between 188 genetic variants robustly linked to the first three PCs and BC (133,384 cases/113,789 controls from the Breast Cancer Association Consortium (BCAC)). PC1 (general adiposity) was inversely associated with overall BC risk (0.89 per 1 SD [95% CI: 0.81-0.98]; p-value = 0.016). PC2 (tall women with low WHR) was weakly positively associated with overall BC risk (1.05 [95% CI: 0.98-1.12]; p-value = 0.135), but with a confidence interval including the null. PC3 (tall women with large WHR) was not associated with overall BC risk. Some of these associations differed by BC sub-types. For instance, PC2 was positively associated with a risk of luminal A BC sub-type (1.09 [95% CI: 1.01-1.18]; p-value = 0.02). To clarify the inverse association of PC1 with breast cancer risk, future studies should examine independent risk associations of this body shape during childhood/adolescence and adulthood.