Obesity, diabetes, and cancer: epidemiology, pathophysiology, and potential interventions.

The proportion of deaths attributable to cancer is rising, and malignant neoplasms have become the leading cause of death in high-income countries. Obesity and diabetes are now recognized as risk factors for several types of malignancies, especially endometrial, colorectal, and postmenopausal breast cancers. Mechanisms implicated include disturbances in lipid-derived hormone secretion, sex steroids biosynthesis, hyperinsulinemia, and chronic inflammation. Intentional weight loss is associated with a mitigation of risk for obesity-related cancers, a phenomenon observed specially with bariatric surgery. The impact of pharmacological interventions for obesity and diabetes is not uniform: while metformin seems to protect against cancer, other agents such as lorcaserin may increase the risk of malignancies. However, these interpretations must be carefully considered, since most data stem from bias-prone observational studies, and high-quality randomized controlled trials with appropriate sample size and duration are needed to achieve definite conclusions. In this review, we outline epidemiological and pathophysiological aspects of the relationship between obesity, diabetes, and malignancies. We also highlight pieces of evidence regarding treatment effects on cancer incidence in these populations.

Is lorcaserin really associated with increased risk of cancer? A systematic review and meta-analysis.

The US Food and Drug Administration (FDA) reported in February 2020 an increased risk of cancer with lorcaserin in the follow-up of the CAMELLIA-TIMI 61 trial. This systematic review and meta-analysis addresses whether lorcaserin is associated with higher incidence of cancer compared with other interventions or no treatment. We searched MEDLINE, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) for randomized controlled trials that compared lorcaserin with other interventions or no treatment in adults. We performed descriptive synthesis of all included studies and conducted meta-analysis of trials that reported new cases of cancer. From 11 trials, comprising 21,299 individuals, four studies were included in the meta-analysis and reported 476 cases of cancer in 10,342 subjects in the lorcaserin group and 438 among 9429 individuals randomized to placebo (relative risk [RR]: 1.08; 95% confidence interval [95% CI]: 0.96-1.23). The result was heavily influenced by the CAMELLIA-TIMI 61 trial. In this study, the lorcaserin group had a higher risk of lung and pancreatic but not colon cancer. Overall risk of bias was low, and quality of evidence was moderate. The current evidence does not confirm the increased risk of cancer with lorcaserin but suggests a trend in this direction, with a greater incidence of some subtypes such as lung and pancreas.

Distinct metabolic profile according to the shape of the oral glucose tolerance test curve is related to whole glucose excursion: a cross-sectional study.

BACKGROUND: The shapes of the plasma glucose concentration curve during the oral glucose tolerance test are related to different metabolic risk profiles and future risk of type 2 DM. We sought to further analyze the relationship between the specific shapes and hyperglycemic states, the metabolic syndrome and hormones involved in carbohydrate and lipid metabolism, and to isolate the effect of the shape by adjusting for the area under the glucose curve. METHODS: One hundred twenty one adult participants underwent a 2-h oral glucose tolerance test and were assigned to either the monophasic (n = 97) or the biphasic (n = 24) group based upon the rise and fall of their plasma glucose concentration. We evaluated anthropometric measures, blood pressure, lipid profile, high-sensitivity C-reactive protein, glycated hemoglobin, insulin sensitivity, beta-cell function, C-peptide, glucagon, adiponectin and pancreatic polypeptide. RESULTS: Subjects with monophasic curves had higher fasting and 2-h plasma glucose levels, while presenting lower insulin sensitivity, beta-cell function, HDL cholesterol, adiponectin and pancreatic polypeptide levels. Prediabetes and metabolic syndrome had a higher prevalence in this group. Glycated hemoglobin, total cholesterol, triglycerides, high-sensitivity C-reactive protein and glucagon were not significantly different between groups. After adjusting for the area under the glucose curve, only the differences in the 1-h and 2-h plasma glucose concentrations and HDL cholesterol levels between the monophasic and biphasic groups remained statistically significant. CONCLUSIONS: Rates and intensity of metabolic dysfunction are higher in subjects with monophasic curves, who have lower insulin sensitivity and beta-cell function and a higher prevalence of prediabetes and metabolic syndrome. These differences, however, seem to be dependent on the area under the glucose curve.

Accuracy of insulin resistance indices for metabolic syndrome: a cross-sectional study in adults.

BACKGROUND: This study aimed to determine the ability of commonly used insulin resistance indices to identify the metabolic syndrome. METHODS: 183 people referred for outpatient care at the Metabolism Unit of Hospital de Clínicas de Porto Alegre were evaluated with anthropometric, blood pressure, lipid profile, and adiponectin measurements. Glucose tolerance status was determined by 2-h 75-g oral glucose tolerance test and glycosylated hemoglobin. Definition of metabolic syndrome was based on the Joint Interim Statement of different medical associations. Twenty-one indices of insulin resistance were estimated from published equations. The accuracy of these indices was determined by area under the ROC curve (AUC) analysis. In addition, we determined an optimal cut point for each index and its performance as a diagnostic test. RESULTS: The study population was comprised of 183 people (73.2% women; 78.7% white; age 52.6 ± 12.0 years, mean ± standard deviation), of whom 140 (76.5%) had metabolic syndrome. The reciprocal of the Gutt index provided the greatest AUC for identification of metabolic syndrome, but there were no statistical differences between Gutt and 11 AUC indices. Gutt presented 86.4% sensitivity and 76.7% specificity to identify metabolic syndrome. CONCLUSIONS: A number of commonly employed indices of insulin resistance are capable of identifying individuals with the metabolic syndrome.