A new “Comparative Effectiveness” assessment strategy using the THIN database: comparison of the cardiac complications of pioglitazone and rosiglitazone

Real-world effectiveness of pneumococcal vaccination in older adults: Cohort study using the UK Clinical Practice Research Datalink

Background

The 23-valent pneumococcal polysaccharide vaccine (PPV23) is recommended for UK older adults, but how age moderates effectiveness is unclear.

Methods

Three annual cohorts of primary-care patients aged≥65y from the Clinical Practice Research Datalink selected from 2003–5 created a natural experiment (n = 324,804), reflecting the staged introduction of the vaccine. The outcome was symptoms consistent with community-acquired pneumococcal pneumonia (CAP) requiring antibiotics or hospitalisation. We used the prior event rate ratio (PERR) approach to address bias from unmeasured confounders.

Results

Vaccinated patients had higher rates of CAP in the year before vaccination than their controls, indicating the potential for confounding bias. After adjustment for confounding using the prior event rate ratio (PERR) method, PPV23 was estimated to be effective against CAP for two years after vaccination in all age sub-groups with hazard ratios (95% confidence intervals) of 0.86 (0.80 to 0.93), 0.74 (0.65 to 0.85) and 0.65 (0.57 to 0.74) in patients aged 65–74, 75–79 and 80+ respectively in the 2005 cohort. Age moderated the effect of vaccination with predicted risk reductions of 8% at 65y and 29% at 80y.

Conclusions

PPV23 is moderately effective at reducing CAP among UK patients aged≥65y, in the two years after vaccination. Vaccine effectiveness is maintained, and may increase, in the oldest age groups in step with increasing susceptibility to CAP.

Rosiglitazone Does Not Show Major Hidden Cardiotoxicity in Models of Ischemia/Reperfusion but Abolishes Ischemic Preconditioning-Induced Antiarrhythmic Effects in Rats In Vivo

Clinical observations are highly inconsistent with the use of the antidiabetic rosiglitazone regarding its associated increased risk of myocardial infarction. This may be due to its hidden cardiotoxic properties that have only become evident during post-marketing studies. Therefore, we aimed to investigate the hidden cardiotoxicity of rosiglitazone in ischemia/reperfusion (I/R) injury models. Rats were treated orally with either 0.8 mg/kg/day rosiglitazone or vehicle for 28 days and subjected to I/R with or without cardioprotective ischemic preconditioning (IPC). Rosiglitazone did not affect mortality, arrhythmia score, or infarct size during I/R. However, rosiglitazone abolished the antiarrhythmic effects of IPC. To investigate the direct effect of rosiglitazone on cardiomyocytes, we utilized adult rat cardiomyocytes (ARCMs), AC16, and differentiated AC16 (diffAC16) human cardiac cell lines. These were subjected to simulated I/R in the presence of rosiglitazone. Rosiglitazone improved cell survival of ARCMs at 0.3 μM. At 0.1 and 0.3 μM, rosiglitazone improved cell survival of AC16s but not that of diffAC16s. This is the first demonstration that chronic administration of rosiglitazone does not result in major hidden cardiotoxic effects in myocardial I/R injury models. However, the inhibition of the antiarrhythmic effects of IPC may have some clinical relevance that needs to be further explored.

Provision and Need for Medicine Information in Asia and Africa: A Scoping Review of the Literature

Published reviews of written medicine information (WMI) have mainly drawn on studies published in high-income countries, including very few Asian or African studies. We therefore set out to scope the research literature to determine the extent and type of studies concerning WMI for patients/consumers across these two continents. We sought empirical studies published between January 2004 and December 2019, conducted in any Asian or African country, as defined by the United Nations, in English or with an English abstract. The majority of the 923 papers identified were from high-income countries. We retained 26 papers from Africa and 99 from Asia. Most African studies (n = 20) involved patients in the development of PILs, in the assessment of the effectiveness of PILs or in surveys. In contrast, the highest proportion of Asian studies concerned the content of WMI (n = 42). WMI is desired, but needs to be in local languages, and there needs to be more use made of pre-tested pictograms. Existing WMI frequently does not meet local regulatory requirements, particularly locally manufactured products. A number of studies reported potentially positive impacts of providing WMI on knowledge and medicine use behaviours. Provision of medicine information is essential for safe use of medicines in all countries. Internationally agreed guidelines, incorporating good design principles, are needed to ensure the optimal content and design of WMI. The World Health Organization should support African and Asian regulatory bodies to share best practice in relation to WMI for patients/consumers and to develop and implement pan-continental guidelines that take into account consumer needs and preferences.

On the Causal Interpretation of Rate-Change Methods: The Prior Event Rate Ratio and Rate Difference

A growing number of studies use data before and after treatment initiation in groups exposed to different treatment strategies to estimate “causal effects” using a ratio measure called the prior event rate ratio (PERR). Here, we offer a causal interpretation for PERR and its additive scale analog, the prior event rate difference (PERD). We show that causal interpretation of these measures requires untestable rate-change assumptions about the relationship between 1) the change of the counterfactual rate before and after treatment initiation in the treated group under hypothetical intervention to implement the control strategy; and 2) the change of the factual rate before and after treatment initiation in the control group. The rate-change assumption is on the multiplicative scale for PERR but on the additive scale for PERD; the 2 assumptions hold simultaneously under testable, but unlikely, conditions. Even if investigators can pick the most appropriate scale, the relevant rate-change assumption might not hold exactly, so we describe sensitivity analysis methods to examine how assumption violations of different magnitudes would affect study results. We illustrate the methods using data from a published study of proton pump inhibitors and pneumonia.

The Changing Landscape of Pharmacotherapy for Diabetes Mellitus: A Review of Cardiovascular Outcomes

The prevention of cardiovascular morbidity and mortality has always been a primary concern in patients with type 2 diabetes. Modern trials of glucose-lowering therapies now assess major adverse cardiac events as an endpoint in addition to the effects on glycaemic control. Whilst the data on the efficacy of intensive glucose lowering on reducing cardiovascular risk are limited, there are now increasing numbers of glucose-lowering therapies that have proven cardiovascular benefit independent of glucose lowering. This review will summarise the available literature on cardiovascular outcomes in relation to metformin, sulphonylureas, di-peptidyl peptidase-4 inhibitors, glucagon-like peptide receptor agonists, sodium-glucose co-transporter 2 inhibitors, thiazolidinediones, acarbose and insulin. In addition, new paradigms in diabetes management and the importance of treatment selection based on considerations including but not limited to glycaemic control will be discussed.

Risk prediction for heterogeneous populations with application to hospital admission prediction

This article is motivated by the increasing need to model risk for large hospital and health care systems that provide services to diverse and complex patients. Often, heterogeneity across a population is determined by a set of factors such as chronic conditions. When these stratifying factors result in overlapping subpopulations, it is likely that the covariate effects for the overlapping groups have some similarity. We exploit this similarity by imposing structural constraints on the importance of variables in predicting outcomes such as hospital admission. Our basic assumption is that if a variable is important for a subpopulation with one of the chronic conditions, then it should be important for the subpopulation with both conditions. However, a variable can be important for the subpopulation with two particular chronic conditions but not for the subpopulations of people with just one of those two conditions. This assumption and its generalization to more conditions are reasonable and aid greatly in borrowing strength across the subpopulations. We prove an oracle property for our estimation method and show that even when the structural assumptions are misspecified, our method will still include all of the truly nonzero variables in large samples. We demonstrate impressive performance of our method in extensive numerical studies and on an application in hospital admission prediction and validation for the Medicare population of a large health care provider.

Thiazolidinedione drugs in the treatment of type 2 diabetes mellitus: past, present and future

Thiazolidinedione (TZD) drugs used in the treatment of type 2 diabetes mellitus (T2DM) have proven effective in improving insulin sensitivity, hyperglycemia, and lipid metabolism. Though well tolerated by some patients, their mechanism of action as ligands of peroxisome proliferator-activated receptors (PPARs) results in the activation of several pathways in addition to those responsible for glycemic control and lipid homeostasis. These pathways, which include those related to inflammation, bone formation, and cell proliferation, may lead to adverse health outcomes. As treatment with TZDs has been associated with adverse hepatic, cardiovascular, osteological, and carcinogenic events in some studies, the role of TZDs in the treatment of T2DM continues to be debated. At the same time, new therapeutic roles for TZDs are being investigated, with new forms and isoforms currently in the pre-clinical phase for use in the prevention and treatment of some cancers, inflammatory diseases, and other conditions. The aims of this review are to provide an overview of the mechanism(s) of action of TZDs, a review of their safety for use in the treatment of T2DM, and a perspective on their current and future therapeutic roles.

A new method to address unmeasured confounding of mortality in observational studies

INTRODUCTION

The prior event rate ratio (PERR) overcomes "unmeasured confounding" by adjusting study outcomes for all confounding (measured and unmeasured) by comparing exposed to unexposed cohort outcomes prior to study entry when neither group is receiving treatment. However, PERR cannot address "unmeasured confounding" of death since prior events cannot occur.

METHODS

This study's goal is to determine whether a new method, built on the concepts that led to the PERR development, reliably overcomes unmeasured confounding for death. In contrast to the PERR, which precedes study onset, the new mortality analysis uses exposed and unexposed cohorts, not taking the treatment medication, at the end of the study. It is called the post-treated event rate ratio (PTERR).

RESULTS

Theoretical and simulation studies were used to evaluate the likelihood for reliable results using of this new analytic strategy. Also, prior empiric studies, which used both the UK GPRD and THIN databases to examine and validate the PERR method, were used to ascertain the validity of the PTERR method.

CONCLUSION

In the aggregate the results provide strong evidence that the PTERR method to evaluate unmeasured confounding will be a valuable analytic tool.

Prior event rate ratio adjustment for hidden confounding in observational studies of treatment effectiveness: a pairwise Cox likelihood approach

Observational studies provide a rich source of information for assessing effectiveness of treatment interventions in many situations where it is not ethical or practical to perform randomized controlled trials. However, such studies are prone to bias from hidden (unmeasured) confounding. A promising approach to identifying and reducing the impact of unmeasured confounding is prior event rate ratio (PERR) adjustment, a quasi-experimental analytic method proposed in the context of electronic medical record database studies. In this paper, we present a statistical framework for using a pairwise approach to PERR adjustment that removes bias inherent in the original PERR method. A flexible pairwise Cox likelihood function is derived and used to demonstrate the consistency of the simple and convenient alternative PERR (PERR-ALT) estimator. We show how to estimate standard errors and confidence intervals for treatment effect estimates based on the observed information and provide R code to illustrate how to implement the method. Assumptions required for the pairwise approach (as well as PERR) are clarified, and the consequences of model misspecification are explored. Our results confirm the need for researchers to consider carefully the suitability of the method in the context of each problem. Extensions of the pairwise likelihood to more complex designs involving time-varying covariates or more than two periods are considered. We illustrate the application of the method using data from a longitudinal cohort study of enzyme replacement therapy for lysosomal storage disorders. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Methods to control for unmeasured confounding in pharmacoepidemiology: an overview

Background Unmeasured confounding is one of the principal problems in pharmacoepidemiologic studies. Several methods have been proposed to detect or control for unmeasured confounding either at the study design phase or the data analysis phase. Aim of the Review To provide an overview of commonly used methods to detect or control for unmeasured confounding and to provide recommendations for proper application in pharmacoepidemiology. Methods/Results Methods to control for unmeasured confounding in the design phase of a study are case only designs (e.g., case-crossover, case-time control, self-controlled case series) and the prior event rate ratio adjustment method. Methods that can be applied in the data analysis phase include, negative control method, perturbation variable method, instrumental variable methods, sensitivity analysis, and ecological analysis. A separate group of methods are those in which additional information on confounders is collected from a substudy. The latter group includes external adjustment, propensity score calibration, two-stage sampling, and multiple imputation. Conclusion As the performance and application of the methods to handle unmeasured confounding may differ across studies and across databases, we stress the importance of using both statistical evidence and substantial clinical knowledge for interpretation of the study results.

Cardiovascular risk associated with the use of glitazones, metformin and sufonylureas: meta-analysis of published observational studies

BACKGROUND

The results of observational studies evaluating and comparing the cardiovascular safety of glitazones, metformin and sufonylureas are inconsistent.To conduct and evaluate heterogeneity in a meta-analysis of observational studies on the risk of acute myocardial infarction (AMI) or stroke in patients with type 2 diabetes using non-insulin blood glucose-lowering drugs (NIBGLD).

METHODS

We systematically identified and reviewed studies evaluating NIBGLD in patients with type 2 diabetes indexed in Medline, Embase, or the Cochrane Library that met prespecified criteria. The quality of included studies was assessed with the RTI item bank. Results were combined using fixed- and random-effects models, and the Higgins I(2) statistic was used to evaluate heterogeneity. Sensitivity analyses by study quality were conducted.

RESULTS

The summary relative risk (sRR) (95% CI) of AMI for rosiglitazone versus pioglitazone was 1.13 (1.04-1.24) [I(2) = 55%]. In the sensitivity analysis, heterogeneity was reduced [I(2) = 16%]. The sRR (95% CI) of stroke for rosiglitazone versus pioglitazone was 1.18 (1.02-1.36) [I(2)  = 42%]. There was strong evidence of heterogeneity related to study quality in the comparisons of rosiglitazone versus metformin and rosiglitazone versus sulfonylureas (I (2) ≥ 70%). The sRR (95% CI) of AMI for sulfonylurea versus metformin was 1.24 (1.14-1.34) [I(2) = 41%] and for pioglitazone versus metformin was 1.02 (0.75-1.38) [I(2) = 17%]. Sensitivity analyses decreased heterogeneity in most comparisons.

CONCLUSION/INTERPRETATION

Sulfonylureas increased the risk of AMI by 24% compared with metformin; an imprecise point estimate indicated no difference in risk of AMI when comparing pioglitazone with metformin. The presence of heterogeneity precluded any conclusions on the other comparisons. The quality assessment was valuable in identifying methodological problems in the individual studies and for analysing potential sources of heterogeneity.

Pharmacokinetics and clinical evaluation of the alogliptin plus pioglitazone combination for type 2 diabetes

INTRODUCTION

Type 2 diabetes is a complex disease with multiple defects, which generally requires a combination of several pharmacological approaches to reach glucose control targets. A unique fixed-dose combination combines a thiazolidinedione (pioglitazone) and a dipeptidyl peptidase-4 inhibitor (alogliptin).

AREA COVERED

An extensive literature search was performed to analyze the pharmacokinetics of pioglitazone and alogliptin when used separately and in combination as well as to summarize clinical and toxicological considerations about the combined therapy.

EXPERT OPINION

Pioglitazone, a potent insulin sensitizer, and alogliptin, an incretin-based agent that potentiates post-meal insulin secretion and reduces glucagon secretion, have complementary mechanisms of action. The clinical efficacy of a combined therapy is superior to any single therapy in patients treated with diet or with metformin (with or without sulphonylurea). These two drugs can be administered once daily, with or without a meal. No clinically relevant pharmacokinetic interactions between the two agents have been described and the fixed-dose combination has shown bioequivalence with alogliptin and pioglitazone given separately. Combining alogliptin with pioglitazone does not alter the safety profile of each compound. Weight gain observed with pioglitazone may be limited with the addition of alogliptin. The concern of an increased risk of heart failure remains to be better investigated.

Pathways targeted by antidiabetes drugs are enriched for multiple genes associated with type 2 diabetes risk

Genome-wide association studies (GWAS) have uncovered >65 common variants associated with type 2 diabetes (T2D); however, their relevance for drug development is not yet clear. Of note, the first two T2D-associated loci (PPARG and KCNJ11/ABCC8) encode known targets of antidiabetes medications. We therefore tested whether other genes/pathways targeted by antidiabetes drugs are associated with T2D. We compiled a list of 102 genes in pathways targeted by marketed antidiabetic medications and applied Gene Set Enrichment Analysis (MAGENTA [Meta-Analysis Gene-set Enrichment of variaNT Associations]) to this gene set, using available GWAS meta-analyses for T2D and seven quantitative glycemic traits. We detected a strong enrichment of drug target genes associated with T2D (P = 2 × 10(-5); 14 potential new associations), primarily driven by insulin and thiazolidinedione (TZD) targets, which was replicated in an independent meta-analysis (Metabochip). The glycemic traits yielded no enrichment. The T2D enrichment signal was largely due to multiple genes of modest effects (P = 4 × 10(-4), after removing known loci), highlighting new associations for follow-up (ACSL1, NFKB1, SLC2A2, incretin targets). Furthermore, we found that TZD targets were enriched for LDL cholesterol associations, illustrating the utility of this approach in identifying potential side effects. These results highlight the potential biomedical relevance of genes revealed by GWAS and may provide new avenues for tailored therapy and T2D treatment design.

Performance of prior event rate ratio adjustment method in pharmacoepidemiology: a simulation study

PURPOSE

Prior event rate ratio (PERR) adjustment method has been proposed to control for unmeasured confounding. We aimed to assess the performance of the PERR method in realistic pharmacoepidemiological settings.

METHODS

Simulation studies were performed with varying effects of prior events on the probability of subsequent exposure and post-events, incidence rates, effects of confounders, and rate of mortality/dropout. Exposure effects were estimated using conventional rate ratio (RR) and PERR adjustment method (i.e. ratio of RR post-exposure initiation and RR prior to initiation of exposure).

RESULTS

In the presence of unmeasured confounding, both conventional and the PERR method may yield biased estimates, but PERR estimates appear generally less biased estimates than the conventional method. However, when prior events strongly influence the probability of subsequent exposure, the exposure effect from the PERR method was more biased than the conventional method. For instance, when the effect of prior events on the exposure was RR = 1.60, the effect estimate from the PERR method was RR = 1.13 and from the conventional method was RR = 2.48 (true exposure effect, RR = 2). In all settings, the variation of the estimates was larger for the PERR method than for the conventional method.

CONCLUSION

The PERR adjustment method can be applied to reduce bias as a result of unmeasured confounding. However, only in particular situations, it can completely remove the bias as a result of unmeasured confounding. When applying this method, theoretical justification using available clinical knowledge for assumptions of the PERR method should be provided.

The risk of heart failure associated with the use of noninsulin blood glucose-lowering drugs: systematic review and meta-analysis of published observational studies

Background

Patients with type 2 diabetes mellitus (T2DM) are at high risk of heart failure. A summary of the effects of blood glucose-lowering drugs other than glitazones on the risk of heart failure in routine clinical practice is lacking. The objective of this study was to conduct a systematic review and meta-analysis of observational studies on the risk of heart failure when using blood glucose-lowering drugs.

Methods

We systematically identified and reviewed cohort and case–control studies in which the main exposure of interest was noninsulin blood glucose-lowering medications in patients with T2DM. We searched Medline, Embase, and the Cochrane Library to identify publications meeting prespecified eligibility criteria. The quality of included studies was assessed with the Newcastle-Ottawa Scale and the RTI item bank. Results were combined using fixed and random-effects models when at least 3 independent data points were available for a drug-drug comparison.

Results

The summary relative risk of heart failure in rosiglitazone users versus pioglitazone users (95% CI) was 1.16 (1.05-1.28) (5 cohort studies). Heterogeneity was present (I² = 66%). For new users (n = 4) the summary relative risk was 1.21 (1.14-1.30) and the heterogeneity was reduced (I² = 31%);. The summary relative risk for rosiglitazone versus metformin was 1.36 (95% CI, 1.17-1.59) (n = 3). The summary relative risk (95% CI) of heart failure in sulfonylureas users versus metformin users was 1.17 (95% CI, 1.06-1.29) (5 cohort studies; I² = 24%) and 1.22 (1.02-1.46) when restricted to new users (2 studies).

Information on other comparisons was very scarce. Information on dose and duration of treatment effects was lacking for most comparisons. Few studies accounted for disease severity; therefore, confounding by indication might be present in the majority of the within-study comparisons of this meta-analysis.

Conclusions

Use of glitazones and sulfonylureas was associated with an increased risk of heart failure compared with metformin use. However, indication bias cannot be ruled out. Ongoing large multidatabase studies will help to evaluate the risk of heart failure in treated patients with diabetes, including those using newer blood glucose-lowering therapies.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2261-14-129) contains supplementary material, which is available to authorized users.

Can analyses of electronic patient records be independently and externally validated? The effect of statins on the mortality of patients with ischaemic heart disease: a cohort study with nested case-control analysis

OBJECTIVE

To conduct a fully independent and external validation of a research study based on one electronic health record database, using a different electronic database sampling the same population.

DESIGN

Using the Clinical Practice Research Datalink (CPRD), we replicated a published investigation into the effects of statins in patients with ischaemic heart disease (IHD) by a different research team using QResearch. We replicated the original methods and analysed all-cause mortality using: (1) a cohort analysis and (2) a case-control analysis nested within the full cohort.

SETTING

Electronic health record databases containing longitudinal patient consultation data from large numbers of general practices distributed throughout the UK.

PARTICIPANTS

CPRD data for 34 925 patients with IHD from 224 general practices, compared to previously published results from QResearch for 13 029 patients from 89 general practices. The study period was from January 1996 to December 2003.

RESULTS

We successfully replicated the methods of the original study very closely. In a cohort analysis, risk of death was lower by 55% for patients on statins, compared with 53% for QResearch (adjusted HR 0.45, 95% CI 0.40 to 0.50; vs 0.47, 95% CI 0.41 to 0.53). In case-control analyses, patients on statins had a 31% lower odds of death, compared with 39% for QResearch (adjusted OR 0.69, 95% CI 0.63 to 0.75; vs OR 0.61, 95% CI 0.52 to 0.72). Results were also close for individual statins.

CONCLUSIONS

Database differences in population characteristics and in data definitions, recording, quality and completeness had a minimal impact on key statistical outputs. The results uphold the validity of research using CPRD and QResearch by providing independent evidence that both datasets produce very similar estimates of treatment effect, leading to the same clinical and policy decisions. Together with other non-independent replication studies, there is a nascent body of evidence for wider validity.

Current clinical evidence on pioglitazone pharmacogenomics

Pioglitazone is the most widely used thiazolidinedione and acts as an insulin-sensitizer through activation of the Peroxisome Proliferator-Activated Receptor-γ (PPARγ). Pioglitazone is approved for use in the management of type 2 diabetes mellitus (T2DM), but its use in other therapeutic areas is increasing due to pleiotropic effects. In this hypothesis article, the current clinical evidence on pioglitazone pharmacogenomics is summarized and related to variability in pioglitazone response. How genetic variation in the human genome affects the pharmacokinetics and pharmacodynamics of pioglitazone was examined. For pharmacodynamic effects, hypoglycemic and anti-atherosclerotic effects, risks of fracture or edema, and the increase in body mass index in response to pioglitazone based on genotype were examined. The genes CYP2C8 and PPARG are the most extensively studied to date and selected polymorphisms contribute to respective variability in pioglitazone pharmacokinetics and pharmacodynamics. We hypothesized that genetic variation in pioglitazone pathway genes contributes meaningfully to the clinically observed variability in drug response. To test the hypothesis that genetic variation in PPARG associates with variability in pioglitazone response, we conducted a meta-analysis to synthesize the currently available data on the PPARG p.Pro12Ala polymorphism. The results showed that PPARG 12Ala carriers had a more favorable change in fasting blood glucose from baseline as compared to patients with the wild-type Pro12Pro genotype (p = 0.018). Unfortunately, findings for many other genes lack replication in independent cohorts to confirm association; further studies are needed. Also, the biological functionality of these polymorphisms is unknown. Based on current evidence, we propose that pharmacogenomics may provide an important tool to individualize pioglitazone therapy and better optimize therapy in patients with T2DM or other conditions for which pioglitazone is being used.