Additive effects of blood glucose lowering drugs, statins and renin-angiotensin system blockers on all-site cancer risk in patients with type 2 diabetes

Abstract

BackgroundHyperglycemia is associated with increased risk of all-site cancer that may be mediated through activation of the renin-angiotensin-system (RAS) and 3-hydroxy-3-methyl-glutaryl-coenzyme-A-reductase (HMGCR) pathways. We examined the joint associations of optimal glycemic control (HbA1c <7%), RAS inhibitors and HMGCR inhibitors on cancer incidence in patients with type 2 diabetes.MethodsPatients with type 2 diabetes, with or without a history of cancer or prior exposure to RAS or HMGCR inhibitors at baseline were observed between 1996 and 2005. All patients underwent a comprehensive assessment at baseline and were followed until the censored date at 2005 or their death.ResultsAfter a median follow-up period of 4.91 years (interquartile range, 2.81 to 6.98), 271 out of 6,103 patients developed all-site cancer. At baseline, patients with incident cancers were older, had longer disease duration of diabetes, higher alcohol and tobacco use, and higher systolic blood pressure and albuminuria, but lower triglyceride levels and estimated glomerular filtration rate (P <0.05). Patients who developed cancers during follow-up were less likely to have started using statins (22.5% versus 38.6%, P <0.001), fibrates (5.9% versus 10.2%, P = 0.02), metformin (63.8% versus 74.5%, P <0.001) or thiazolidinedione (0.7% versus 6.8%, P <0.001) than those who remained cancer-free. After adjusting for co-variables, new treatment with metformin (hazard ratio: 0.39; 95% confidence interval: 0.25, 0.61; P <0.001), thiazolidinedione (0.18; 0.04, 0.72; P = 0.015), sulphonylurea (0.44; 0.27, 0.73; P = 0.014), insulin (0.58; 0.38, 0.89; P = 0.01), statins (0.47; 0.31, 0.70; P <0.001) and RAS inhibitors (0.55; 0.39, 0.78; P <0.001) were associated with reduced cancer risk. Patients with all three risk factors of HbA1c ≥7%, non-use of RAS inhibitors and non-use of statins had four-fold adjusted higher risk of cancer than those without any risk factors (incidence per 1,000-person-years for no risk factors: 3.40 (0.07, 6.72); one risk factor: 6.34 (4.19, 8.50); two risk factors: 8.40 (6.60, 10.20); three risk factors: 13.08 (9.82, 16.34); P <0.001).ConclusionsHyperglycemia may promote cancer growth that can be attenuated by optimal glycemic control and inhibition of the RAS and HMGCR pathways.

Relationship between sleep duration and cause-specific mortality in diabetic men and women based on self-reports

“…Previous studies showed that sleep duration in diabetic people had a U‐shaped relationship with glucose intolerance represented by hemoglobin A1c and homeostasis model assessment of insulin resistance, metabolic syndrome and levels of lipid, which are well known risk factors of cardiovascular disease. In addition, diabetic people with uncontrolled glycemia are shown to have higher risks of the incidence of cancer, the promotion of cancer growth, and the aggregation of infection than those with controlled glycemia . Nevertheless, in this study, we did not find any significant associations of ≤5 h or ≥9 h sleep with mortality except that listed above.…”

Dose-related neuropathic and anti-neuropathic effects of simvastatin in vincristine-induced neuropathic pain in rats

“…However, statins exhibit umpteen pleiotropic cholesterol independent effects including anti-oxidants by reducing superoxide formation (Uekawa et al, 2014), anti-inflammatory by reducing macrophage migration , anti-microbial effect in staphylococcus blood infections (López-Cortés et al, 2013), modulation of the neurotrophic levels (Wu et al, 2008) and up-regulation of L-type Ca 2+ channel affecting smooth muscle contraction (Clunn et al, 2010). Due to these multiple activities, preclinical studies have suggested the potential beneficial role of statins in a number of other diseased states like cancer (Khurana et al, 2007;Kong et al, 2014;Mondul et al, 2011), arthritis (Gottschalk et al, 2014), chronic obstructive pulmonary disease (Criner et al, 2014), Alzheimer's disease and Parkinson's disease (Barone et al, 2014;Wolozin et al, 2007) and chronic kidney disease (Dasari et al, 2014).…”

Methodological challenges to control for immortal time bias in addressing drug effects in type 2 diabetes

“…We tested various combinations of exclusion/inclusion of immortal time and adjustment for drug indications at baseline or at the end of immortal time when drug was commenced Consistently, timedependent drug-exposure Cox models severely inflated the HR of these two drugs for CVD risk [5,6] , despite their proven cardioprotective effects in RCTs. In the statin-CVD validation [6] , compared to a HR of 0.63 (95%CI: 0.48 to 0.83) in a RCT [21] , exclusion of immortal time and adjustment for estimated covariables at the end of the immortal time when statins were commenced, resulted in a 52.3% inflation in the HR of statins for CVD (0.96, 0.72 to 1.27), which was above the higher bound of the 95%CI. On the other hand, inclusion of immortal time, i.e., ignoring immortal time bias, and adjustment for covariables at baseline generated the least inflated HR of 0.64 (0.48 to 0.84) which was within the HR estimates in clinical trial and inflated by 1.59% compared to the absolute HR of 0.63.…”

“…In order to test the validity of these methods [3,4] , we used a referent drug with proven benefits [e.g., statin or renin angiotensin system (RAS) inhibitors] and applied the methods to the Hong Kong Diabetes Registry [5,6] to find out if the estimated effect size fell within the bounds of that reported in RCTs with regard to their associations with CVD. We tested various combinations of exclusion/inclusion of immortal time and adjustment for drug indications at baseline or at the end of immortal time when drug was commenced Consistently, timedependent drug-exposure Cox models severely inflated the HR of these two drugs for CVD risk [5,6] , despite their proven cardioprotective effects in RCTs.…”

“…Several methods have been proposed to control for immortal bias but it is uncertain whether these methods can adequately remove these biases [2][3][4] . Our recent work has shed light on these important issues [5,6] .…”