After adjustment for baseline and time varying confounders, diuretic use and statin use were significantly associated with new onset diabetes. For β blockers, a non-significant difference in the development of new onset diabetes was observed. Our findings provide further evidence that in high risk people with impaired glucose tolerance, use of diuretics and statins may be associated with an increased risk of new onset diabetes.
Before studying the effect of each drug on development of new onset diabetes, we first examined the concomitant use of those drugs in the NAVIGATOR (Nateglinide and Valsartan in Impaired Glucose Tolerance Outcomes Research) trial. We found that in this high risk population, as expected, statins were used as a concomitant therapy with β blockers as often as with diuretics and calcium channel blockers. Although we did not analyse drug-drug and drug-disease interactions, by accounting for concomitant treatment usage, we limited the confounding of multiple drugs on new onset diabetes. Given this methodology, our study further supports the independent effect of statins on new onset diabetes and emphasises the substantial net effect in a high risk population with impaired glucose tolerance.
In the past decade, studies have found varying associations between diabetes risk and use of β blockers, diuretics, and statins.18
Compared with previous studies using investigator reported or patient reported data on new onset diabetes or administrative claims, the NAVIGATOR trial used serial glucose measurements that enhanced detection of risk for new onset diabetes in a high risk population with impaired glucose tolerance. We found that the increased risk of new onset diabetes associated with diuretic use was similar to that of previous studies.20
Some observational studies have shown a 20% to 40% increased risk of developing new onset diabetes in patients taking compared with not taking diuretics,13
whereas other studies have shown similar risks of development for new onset diabetes in patients treated with diuretics compared with angiotensin converting enzyme inhibitors.22
In several major antihypertensive studies, among non-diabetic patients with hypertension, the number needed to harm with respect to new onset diabetes ranged from 125 to 167 over four to six years of follow-up.8
In The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial, among patients with hypertension and a high risk of cardiovascular disease, the incidence of diabetes at four years was 11.6% for chlorthalidone and 9.8% for amlodipine (number needed to harm for chlorthalidone=167 at four years of follow-up).20
For the Captopril Prevention Project study among hypertensive, non-diabetic patients, the number needed to harm for diuretic or β blocker therapy, or both was 125 at six years of follow-up.23
However, the effect of diuretics had not yet been examined in an impaired glucose tolerance population. In our study, one additional case of diabetes occurred within five years for every 17 patients treated with diuretics. This lower number needed to harm can be attributed to our population of patients with impaired glucose tolerance having a high propensity for new onset diabetes and serial glucose measurement.
Among patients taking β blockers, previous studies have reported up to a sixfold increased risk of new onset diabetes.24
In the Losartan Intervention For Endpoint reduction in hypertension study, among non-diabetic hypertensive patients with left ventricular hypertrophy, the incidence of diabetes was 6% compared with 8% for patients taking losartan versus atenolol (adjusted hazard ratio 0.75, 95% confidence interval 0.63 to 0.88).25
In another large prospective trial with new onset diabetes as a primary endpoint among non-diabetic hypertensive patients, those taking β blockers compared with not taking β blockers had a 28% increased risk of developing subsequent diabetes (adjusted hazard ratio 1.28, 95% confidence interval 1.04 to 1.57).26
The mechanism of β blocker induced new onset diabetes has been postulated to result from a combination of changes in lipoprotein lipase activity, attenuation of the release of insulin by pancreatic β cells, weight gain where increased adiposity constrains the distribution of insulin, and peripheral vasoconstriction from unopposed α adrenergic activity.5
In our analysis, we did not find a statistically significant association between use of β blockers and new onset diabetes. However, the estimated hazard ratio of 1.10 and confidence interval (0.92 to 1.31) were not inconsistent with previous studies. Thus, an important detrimental effect cannot be excluded, and a large sample size would be required to detect a moderate effect. Furthermore, the lack of significant association may also be attributed to the mixed receptor specificity, dosage, and duration of β blocker treatment in our study, as other studies of β blockers have yielded varying results based on the categories and dosages used.27
Initial data linking statin use and diabetes suggested a protective effect of these drugs. The West of Scotland Coronary Prevention Study reported a 30% reduction in the hazard of developing diabetes with pravastatin.28
However, more recent studies examining higher potency statins have suggested a link between statin potency and risk of new onset diabetes. One study reported that statin use resulted in a 48% increased risk of new onset diabetes in postmenopausal women.29
Likewise, results from the Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) showed a 25% higher proportion in investigator reported diabetes in patients treated with rosuvastatin versus placebo.3
A meta-analysis of 13 trials involving 91
140 patients showed a 9% increased risk of diabetes among statin treated patients,7
leading the Food and Drug Administration in 2012 to add a warning label to statin drugs marketed and sold in the United States.9
The relative effect of statins on new onset diabetes was similar in our study, with a 32% increased risk of new onset diabetes in patients receiving statins. Compared with previous studies, our population with impaired glucose tolerance has a smaller number needed to harm, with one case of new onset diabetes for every 12 patients treated over five years; whereas in a population with non-impaired glucose tolerance, the number needed to harm has been as high as 255 over four years.7
Although the relative risk was similar, we saw a greater net impact of statin therapy on new onset diabetes than in previous studies, in our population of high risk patients with impaired glucose tolerance.
Another study of patients at high risk of new onset diabetes included a subgroup of patients from the JUPITER trial, which examined patients with major risk factors for diabetes, including metabolic syndrome, impaired fasting glucose, and high body mass index or HbA1c
levels, and showed a hazard ratio for statin therapy similar to that in our study (1.28, 95% confidence interval 1.07 to 1.54).8
However, this study had a lower event rate than in our study (treated versus untreated, 2.12% v
1.65%, and 41% v
33%, respectively) over a similar follow-up period. Therefore, we found a much higher net risk towards new onset diabetes compared with other high risk populations with diabetes. Again, this difference may be due to the patients with impaired glucose tolerance in our study being closer to the threshold for overt new onset diabetes than the patients with metabolic syndrome from JUPITER, as well as the use of serial glucose measurements with laboratory confirmation, allowing for a more accurate and thus higher detection rate of diabetes.
The potential for unmeasured confounding remains a concern in this observational study. To the extent that these treatments are used in similar populations, the magnitude of unmeasured bias may be reflected in the hazard ratio estimate for calcium channel blockers. Other hazard ratios can be compared with calcium channel blockers (hazard ratio 0.95) rather than to a hazard ratio of 1. We observed that the confidence intervals for statins and diuretics did not contain 0.95, strengthening the case against them. The confidence interval for β blockers did contain 0.95 and is therefore not convincingly different from our metabolically neutral control.
The marginal results for the structural model are consistent with a reduction in treatment selection bias, whereby higher risk patients are more likely to receive treatment. The hazard ratios from the unadjusted and baseline adjusted Cox models are generally higher than those from the marginal structural model. Interestingly, the baseline adjusted Cox model provides nearly identical results to that of the unadjusted model. This likely reflects the fact that the population was treatment naïve at baseline and post-baseline factors play a role in post-baseline treatment use. This emphasises the important role of adjustment for post-baseline factors.
Strengths and limitations of this study
Our study has three major strengths compared with previous studies. Firstly, our study is large; the largest of its kind to date. Secondly, our study used standard methods for diagnosing diabetes, with prespecified serial glucose assessments and laboratory confirmation for all patients, whereas other studies have relied on billing data8
or pooled results data in meta-analyses.6
Thirdly, we began with a treatment naïve population and used marginal structural models to account for the time varying confounders for the use of drug therapy and its association with new onset diabetes. This allowed pseudorandomisation of treatment strategies in which, at each visit, patients who had not yet progressed to diabetes were re-examined for use of the drugs of interest according to their full covariate history. By only including a treatment naïve population, we estimated the effect of first time initiation of drugs on new onset diabetes.
Firstly, this was a reanalysis of a clinical trial that was not prospectively designed to examine the association between new onset diabetes and β blocker, statin, and diuretic use. Biases due to the observational nature of treatment assignment are possible. Documentation of the reason for initiation of new non-trial study treatment was not collected as part of the trial protocol. Although the NAVIGATOR dataset captured strong predictors of new onset diabetes and all known factors expected to be associated with treatment use, these measured confounders were not measured perfectly. For example, glucose tolerance and blood pressure are known to be measured with error, which could lead to imperfect adjustment. The interval nature of data collection implied that covariates could only be updated to their most recent value, six months before treatment decisions, but not immediately before. Given the potential for residual treatment selection bias, we emphasised the comparison with calcium channel blocker. Secondly, we were unable to examine the effects of treatment stratified by duration of drug use—that is, we did not explore differential effects according to the duration of use but estimated the effect averaged over duration. Because we did not collect information on dosage or category, we cannot determine whether there was a dose or category response for these drugs, especially when previous studies have showed that diuretic and β blocker effect can vary within these classes of drugs, and intensive dose (versus lower dose) statins may be associated with an increased risk of new onset diabetes.7
Thirdly, we fit proportional hazards models and did not attempt to investigate time varying effects of treatment, as a more complex model would have trade-offs in precision and interpretability. Finally, we did not examine the effect of new onset diabetes on cardiovascular disease outcomes, so we cannot determine the effect of increased rate of diabetes on major outcomes in this population at high risk for cardiovascular disease.
We found that in high risk patients with impaired glucose tolerance and established cardiac risk factors, statins and diuretics increased the risk of new onset diabetes. Our findings suggest that glycaemia should be better monitored when these drugs are initiated in high risk patients. However, these findings should be confirmed in subsequent studies where those agents are prospectively prescribed in a randomised manner among patients at high risk of diabetes.
What is already known on this topic
- β blockers and diuretics may increase the risk of new onset diabetes
- Recent evidence suggests that statins also increase this risk
- The degree to which use of these drugs in patients with impaired glucose tolerance and other cardiovascular risk factors is associated with new onset diabetes is unknown
What this study adds
- Among people with impaired glucose tolerance and other cardiovascular risk factors and with serial glucose measurements, diuretics and statins were associated with an increased risk of new onset diabetes
- The effect of β blockers was, however, indeterminate