Impact of Obesity on Outcomes of Operable Breast Cancer: A Retrospective Cohort Study

Associations between body mass index and all-cause mortality: A systematic review and meta-analysis

Fasting insulin and c-reactive protein confound the association between mortality and body mass index. An increase in fat mass may mediate the associations between hyperinsulinemia, hyperinflammation, and mortality. The objective of this study was to describe the "average" associations between body mass index and the risk of mortality and to explore how adjusting for fasting insulin and markers of inflammation might modify the association of BMI with mortality. MEDLINE and EMBASE were searched for studies published in 2020. Studies with adult participants where BMI and vital status was assessed were included. BMI was required to be categorized into groups or parametrized as non-first order polynomials or splines. All-cause mortality was regressed against mean BMI squared within seven broad clinical populations. Study was modeled as a random intercept. β coefficients and 95% confidence intervals are reported along with estimates of mortality risk by BMIs of 20, 30, and 40 kg/m2 . Bubble plots with regression lines are drawn, showing the associations between mortality and BMI. Splines results were summarized. There were 154 included studies with 6,685,979 participants. Only five (3.2%) studies adjusted for a marker of inflammation, and no studies adjusted for fasting insulin. There were significant associations between higher BMIs and lower mortality risk in cardiovascular (unadjusted β -0.829 [95% CI -1.313, -0.345] and adjusted β -0.746 [95% CI -1.471, -0.021]), Covid-19 (unadjusted β -0.333 [95% CI -0.650, -0.015]), critically ill (adjusted β -0.550 [95% CI -1.091, -0.010]), and surgical (unadjusted β -0.415 [95% CI -0.824, -0.006]) populations. The associations for general, cancer, and non-communicable disease populations were not significant. Heterogeneity was very large (I2  ≥ 97%). The role of obesity as a driver of excess mortality should be critically re-examined, in parallel with increased efforts to determine the harms of hyperinsulinemia and chronic inflammation.

Postdiagnosis body fatness, weight change and breast cancer prognosis: Global Cancer Update Program (CUP global) systematic literature review and meta-analysis

Previous evidence on postdiagnosis body fatness and mortality after breast cancer was graded as limited-suggestive. To evaluate the evidence on body mass index (BMI), waist circumference, waist-hip-ratio and weight change in relation to breast cancer prognosis, an updated systematic review was conducted. PubMed and Embase were searched for relevant studies published up to 31 October, 2021. Random-effects meta-analyses were conducted to estimate summary relative risks (RRs). The evidence was judged by an independent Expert Panel using pre-defined grading criteria. One randomized controlled trial and 225 observational studies were reviewed (220 publications). There was strong evidence (likelihood of causality: probable) that higher postdiagnosis BMI was associated with increased all-cause mortality (64 studies, 32 507 deaths), breast cancer-specific mortality (39 studies, 14 106 deaths) and second primary breast cancer (11 studies, 5248 events). The respective summary RRs and 95% confidence intervals per 5 kg/m2 BMI were 1.07 (1.05-1.10), 1.10 (1.06-1.14) and 1.14 (1.04-1.26), with high between-study heterogeneity (I2  = 56%, 60%, 66%), but generally consistent positive associations. Positive associations were also observed for waist circumference, waist-hip-ratio and all-cause and breast cancer-specific mortality. There was limited-suggestive evidence that postdiagnosis BMI was associated with higher risk of recurrence, nonbreast cancer deaths and cardiovascular deaths. The evidence for postdiagnosis (unexplained) weight or BMI change and all outcomes was graded as limited-no conclusion. The RCT showed potential beneficial effect of intentional weight loss on disease-free-survival, but more intervention trials and well-designed observational studies in diverse populations are needed to elucidate the impact of body composition and their changes on breast cancer outcomes.

Low Fat-Free Mass Index Measured by Bioelectrical Impedance Analysis Correlates With Hematologic Adverse Events in Early-Stage Breast Cancer Patients Receiving Chemotherapy: A Prospective Observational Cohort Study

Background: Low muscle mass is associated with worse cancer treatment outcomes. Although dual-energy X-ray absorptiometry or computerized tomography-based analysis have both been widely studied in this clinical setting, studies in the use of bioelectrical impedance analysis (BIA) remain limited. The aim of this prospective study was to investigate for association between body composition estimated by BIA and hematologic adverse events in early-stage breast cancer patients receiving chemotherapy. Methods: A total of 144 female patients were enrolled. Before the first cycle of chemotherapy, body weight and fat-free mass were measured by a BIA device and then those values were converted into body mass index and fat-free mass index. Association between fat-free mass index and composite adverse events (CAEs), including grade 4 neutropenia, febrile neutropenia, or relative dose intensity <85%, was explored. Results: CAEs occurred in 85 patients (59%), and point biserial correlation showed an inverse correlation between the fat-free mass index and CAE. No included patients were sarcopenic (fat-free mass index <11.4 kg/m²). Receiver operating characteristic curve analysis revealed <14.85 kg/m² as the cutoff value indicating a low fat-free mass index. Using this cutoff, 85 patients were classified as having a low fat-free mass index, and 62 of those patients (72.9%) had CAE (relative risk: 1.86, P < .001). After adjusting for other factors, a low fat-free mass index was found to be independently associated with a high CAE (adjusted odds ratio: 4.562, 95% CI: 2.162-9.627, P < .001). Conclusion: Low fat-free mass index is an independent predictor of increased risk of hematologic adverse events in early-stage breast cancer patients receiving chemotherapy. Estimation of fat-free mass index by BIA may identify at-risk patients so that interventions can be considered to improve treatment outcomes.