Cancer survivorship, excess body fatness and weight-loss intervention-where are we in 2020?

Abstract

Earlier diagnosis and more effective treatments mean that the estimated number of cancer survivors in the United Kingdom is expected to reach 4 million by 2030. However, there is an increasing realisation that excess body fatness (EBF) is likely to influence the quality of cancer survivorship and disease-free survival. For decades, the discussion of weight management in patients with cancer has been dominated by concerns about unintentional weight loss, low body weight and interventions to increase weight, often re-enforced by the existence of the obesity paradox, which indicates that high body weight is associated with survival benefits for some types of cancer. However, observational evidence provides strong grounds for testing the hypothesis that interventions for promoting intentional loss of body fat and maintaining skeletal muscle in overweight and obese cancer survivors would bring important health benefits in terms of survival outcomes and long-term impact on treatment-related side effects. In this paper, we outline the need for studies to improve our understanding of the health benefits of weight-loss interventions, such as hypocaloric healthy-eating plans combined with physical activity. In particular, complex intervention trials that are pragmatically designed are urgently needed to develop effective, clinically practical, evidence-based strategies for reducing EBF and optimising body composition in people living with and beyond common cancers.

Fig. 1. Possible explanations for the obesity paradox.

Despite significant evidence that excess body fat (EBF) is associated with reduced cancer survival, data from a number of studies indicate that overweight and early obese cancer patients exhibit improved survival—this is known as the so-called ‘obesity paradox’. Although there are potential clinical and biological explanations for this in specific patient groups many of these reports can be explained by methodological mechanisms, including the inadequacy of BMI as a measure of adiposity.

Fig. 2. Two-step Mendelian Randomisation procedure: integration of feasibility randomised controlled trial (RCT) results with MR to predict the long-term effect of interventions.

Introduction to Mendelian randomisation: Mendelian randomisation is a form of instrumental variable analysis that uses genetic variants as instruments to examine the causal effects of modifiable exposures on outcomes of interest. This method depends on the existence of genetic variants that are robustly associated with metabolite levels. In the example outlined here, the results of a feasibility RCT of dietary interventions for the prevention of prostate cancer were carried forward to a large-scale Mendelian randomisation analysis to infer the causal effect of the interventions on prostate cancer risk via intermediate metabolites. Step 1 assessed the randomised effects of lycopene and green-tea consumption for 6 months versus placebo on 159 serum metabolic traits, quantified by nuclear magnetic resonance (NMR), amongst 133 men enrolled in the ProDiet randomised controlled trial. Step 2 used Mendelian randomisation to assess the effects of those metabolic traits altered by the intervention on prostate cancer risk, using genome-wide association studies (GWAS) summary statistics from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. The lycopene intervention lowered circulating levels of pyruvate, a change that the Mendelian randomisation analysis suggested was associated with decreases in prostate cancer risk (a genetically instrumented SD increase in pyruvate increased the odds of prostate cancer by 1.29 (1.03, 1.62, P = 0.027)). Lycopene lowered the levels of pyruvate, which our Mendelian randomisation analysis suggests may be causally related to reduced prostate cancer risk. By combining the results of a feasibility study with Mendelian randomisation, it has been possible to identify potential intermediate mechanisms through which interventions might be influencing cancer risk (see 767,68 (step 2)).