Integrative model of lifestyle effects on cancer via the HbA1c biomarker

Abstract

Background: Cancer and diabetes are the second and twelfth leading global causes of death, respectively. Cancer incidence is increased in diabetics compared to non-diabetics. Common pathobiological pathways are shared by the two diseases: hyperglycaemia, hyperinsulinaemia, chronic inflammation and altered concentrations of endogenous hormones. These pathways can all directly or indirectly be linked to chronic hyperglycaemia. Lifestyle factors also affect cancer, diabetes and hyperglycaemia. Hypothesis: Chronic hyperglycaemia is the common biological pathway linking cancer, diabetes and lifestyle factors. Chronic hyperglycaemia can be assessed by monitoring glycated haemoglobin (HbA1c) levels. Aim: The first aim is to investigate whether the link between diabetes and increased cancer risk can be explained by increasing HbA1c levels. Secondly, glycaemic and overall models of lifestyle factors should be developed and compared to determine the relative influence of lifestyle factors on blood glucose level and, subsequently, cancer risk. This could clarify whether improved glycaemic control via lifestyle factors is sufficient to significantly reduce cancer risk. Method: Dose-response meta-analyses on cancer risk and HbA1c levels were performed and the results communicated via a research article. Statistical glycaemic and overall models were developed from published studies on colorectal cancer (CRC), lifestyle factors and HbA1c, via meta-analysis. Log-linear and restricted cubic spline models were considered for studies relating CRC risk to lifestyle factors or HbA1c. Linear models were considered for studies relating HbA1c to lifestyle factors. Only statistically significant models were compared. Results: Increased cancer risk with increasing HbA1c levels was present for a number of cancers, with some cancer types also showing increased risk in the pre-diabetic and normal HbA1c ranges. Comparison of the glycaemic and overall models revealed that HbA1c significantly affected cancer risk and was significantly affected by lifestyle factors. However, the overall effects of lifestyle factors were much stronger than their glycaemic effects (between 9% and 25% difference in risk between overall effects and glycaemic effects at the exposure levels analysed). Glycaemic and overall models for cigarette smoking and chronic stress revealed increased cancer risk with increasing exposure, but decreased cancer risk for increased dietary fibre intake. The glycaemic model for alcohol consumption displayed decreased cancer risk, while the overall model revealed increased cancer risk, emphasising the strong effect of carcinogenic substances in alcohol. Conclusions: Risk for a number of cancers increased with HbA1c levels in diabetic and non-diabetic persons. Cancer prevention by improved blood glucose control seems plausible. The overall effects of lifestyle factors on cancer risk are much stronger than their glycaemic effects. Lifestyle factors alone do not provide enough reduction in blood glucose levels. Other therapeutic strategies for reducing blood glucose levels, such as pharmacotherapeutics or fasting, should be investigated. The possible harmful effects of reducing blood glucose levels, such as neuroglycopaenia, should be considered before implementation of therapeutic strategies. Although there seems to be a strong association between HbA1c and cancer risk, this does not imply causality. The possibility of residual confounding cannot be ignored, even though the most adjusted estimates were used to develop the models, where possible.