The Challenges and Opportunities of Pharmacoepidemiology in Bone Diseases

Altres ajuts: This work was supported by the National Health Medical Research Council Australia (NHMRC project ID; DA 1114676, DB 1073430, and JRC 1008219). This work was partially supported by the NIHR Biomedical Research Centre, Oxford. DPA is funded by a National Institute for Health Research Clinician Scientist award (CS-2013-13-012). This article presents independent research funded by the National Institute for Health Research (NIHR). Other funding bodies were the Bupa Health Foundation (formerly MBF Foundation) and the Mrs Gibson and Ernst Heine Family Foundation. The views expressed are those of the authors and not necessarily those of the NHMRC and the NIHR.Pharmacoepidemiology is used extensively in osteoporosis research and involves the study of the use and effects of drugs in large numbers of people. Randomized controlled trials are considered the gold standard in assessing treatment efficacy and safety. However, their results can have limited external validity when applied to day-to-day patients. Pharmacoepidemiological studies aim to assess the effect/s of treatments in actual practice conditions, but they are limited by the quality, completeness, and inherent bias due to confounding. Sources of information include prospectively collected (primary) as well as readily available routinely collected (secondary) (eg, electronic medical records, administrative/claims databases) data. Although the former enable the collection of ad hoc measurements, the latter provide a unique opportunity for the study of large representative populations and for the assessment of rare events at relatively low cost. Observational cohort and case-control studies, the most commonly implemented study designs in pharmacoepidemiology, each have their strengths and limitations. However, the choice of the study design depends on the research question that needs to be answered. Despite the many advantages of observational studies, they also have limitations. First, missing data is a common issue in routine data, frequently dealt with using multiple imputation. Second, confounding by indication arises because of the lack of randomization; multivariable regression and more specific techniques such as propensity scores (adjustment, matching, stratification, trimming, or weighting) are used to minimize such biases. In addition, immortal time bias (time period during which a subject is artefactually event-free by study design) and time-varying confounding (patient characteristics changing over time) are other types of biases usually accounted for using time-dependent modeling. Finally, residual "uncontrolled" confounding is difficult to assess, and hence to account for it, sensitivity analyses and specific methods (eg, instrumental variables) should be considered. © 2018 The Authors JBMR Plus published by Wiley Periodicals, Inc. on behalf of American Society for Bone and Mineral Research

Sample size and power considerations for ordinary least squares interrupted time series analysis: a simulation study.

Interrupted time series (ITS) analysis is being increasingly used in epidemiology. Despite its growing popularity, there is a scarcity of guidance on power and sample size considerations within the ITS framework. Our aim of this study was to assess the statistical power to detect an intervention effect under various real-life ITS scenarios. ITS datasets were created using Monte Carlo simulations to generate cumulative incidence (outcome) values over time. We generated 1,000 datasets per scenario, varying the number of time points, average sample size per time point, average relative reduction post intervention, location of intervention in the time series, and reduction mediated via a 1) slope change and 2) step change. Performance measures included power and percentage bias. We found that sample size per time point had a large impact on power. Even in scenarios with 12 pre-intervention and 12 post-intervention time points with moderate intervention effect sizes, most analyses were underpowered if the sample size per time point was low. We conclude that various factors need to be collectively considered to ensure adequate power for an ITS study. We demonstrate a means of providing insight into underlying sample size requirements in ordinary least squares (OLS) ITS analysis of cumulative incidence measures, based on prespecified parameters and have developed Stata code to estimate this

Assessment of channeling bias among initiators of glucose-lowering drugs: A UK cohort study

Background: Channeling bias may occur when a newly marketed drug and an established drug, despite similar indications, are prescribed to patients with different prognostic characteristics (ie, confounding). Aim: To investigate channeling bias and its impact on relative effectiveness of glucagon-like peptide-1 (GLP-1) analogs versus basal insulin and dipeptidyl peptidase-4 inhibitors (DPP-4i) versus sulfonylurea. Methods: In the UK Clinical Practice Research Datalink, patients with type 2 diabetes initiating treatment between 2006 and 2015 were included. Analyses were stratified by years since first prescription of GLP-1 and DPP-4i, respectively. The characteristics of GLP-1 versus insulin and DPP-4i versus sulfonylurea initiators were compared over time. After propensity score matching, the relative effectiveness regarding 6-month changes in glycated hemoglobin (HbA1c) and body weight was estimated. Results: In total, 8,398 GLP-1, 14,807 insulin, 24,481 DPP-4i, and 33,505 sulfonylurea initiators were identified. No major channeling was observed. Considerable overlap in distributions of characteristics allowed for propensity score-matched analyses. Relative effectiveness was similar across time. The overall relative effect of GLP-1 versus insulin showed no difference for HbA1c and relative increase in body weight (3.57 kg [95% confidence interval {CI}: 3.21, 3.92]) for insulin. The overall relative effect of DPP-4i versus sulfonylurea showed relative decrease in HbA1c (–0.34% [95% CI: –0.38, –0.30]) and increase in body weight (1.58 kg [95% CI: 1.38, 1.78]) for sulfonylurea. Conclusion: No major channeling was identified in the investigated glucose-lowering drugs. Relative effectiveness could be estimated already in the first year after launch and was consistent in the years thereafter

Differentiated prevention and care to reduce the risk of HIV acquisition and transmission among female sex workers in Zimbabwe: study protocol for the 'AMETHIST' cluster randomised trial

BACKGROUND: Female sex workers (FSW) in sub-Saharan Africa are disproportionately affected by HIV and are critical to engage in HIV prevention, testing and care services. We describe the design of our evaluation of the 'AMETHIST' intervention, nested within a nationally-scaled programme for FSW in Zimbabwe. We hypothesise that the implementation of this intervention will result in a reduction in the risk of HIV transmission within sex work. METHODS: The AMETHIST intervention (Adapted Microplanning to Eliminate Transmission of HIV in Sex Transactions) is a risk-differentiated intervention for FSW, centred around the implementation of microplanning and self-help groups. It is designed to support uptake of, and adherence to, HIV prevention, testing and treatment behaviours among FSW. Twenty-two towns in Zimbabwe were randomised to receive either the Sisters programme (usual care) or the Sisters programme plus AMETHIST. The composite primary outcome is defined as the proportion of all FSW who are at risk of either HIV acquisition (HIV-negative and not fully protected by prevention interventions) or of HIV transmission (HIV-positive, not virally suppressed and not practicing consistent condom use). The outcome will be assessed after 2 years of intervention delivery in a respondent-driven sampling survey (total n = 4400; n = 200 FSW recruited at each site). Primary analysis will use the 'RDS-II' method to estimate cluster summaries and will adapt Hayes and Moulton's '2-step' method produce adjusted effect estimates. An in-depth process evaluation guided by our project trajectory will be undertaken. DISCUSSION: Innovative pragmatic trials are needed to generate evidence on effectiveness of combination interventions in HIV prevention and treatment in different contexts. We describe the design and analysis of such a study. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR202007818077777 . Registered on 2 July 2020

Differentiated prevention and care to reduce the risk of HIV acquisition and transmission among female sex workers in Zimbabwe:study protocol for the ‘AMETHIST’ cluster randomised trial

Background: Female sex workers (FSW) in sub-Saharan Africa are disproportionately affected by HIV and are critical to engage in HIV prevention, testing and care services. We describe the design of our evaluation of the ‘AMETHIST’ intervention, nested within a nationally-scaled programme for FSW in Zimbabwe. We hypothesise that the implementation of this intervention will result in a reduction in the risk of HIV transmission within sex work. Methods: The AMETHIST intervention (Adapted Microplanning to Eliminate Transmission of HIV in Sex Transactions) is a risk-differentiated intervention for FSW, centred around the implementation of microplanning and self-help groups. It is designed to support uptake of, and adherence to, HIV prevention, testing and treatment behaviours among FSW. Twenty-two towns in Zimbabwe were randomised to receive either the Sisters programme (usual care) or the Sisters programme plus AMETHIST. The composite primary outcome is defined as the proportion of all FSW who are at risk of either HIV acquisition (HIV-negative and not fully protected by prevention interventions) or of HIV transmission (HIV-positive, not virally suppressed and not practicing consistent condom use). The outcome will be assessed after 2 years of intervention delivery in a respondent-driven sampling survey (total n = 4400; n = 200 FSW recruited at each site). Primary analysis will use the ‘RDS-II’ method to estimate cluster summaries and will adapt Hayes and Moulton’s ‘2-step’ method produce adjusted effect estimates. An in-depth process evaluation guided by our project trajectory will be undertaken. Discussion: Innovative pragmatic trials are needed to generate evidence on effectiveness of combination interventions in HIV prevention and treatment in different contexts. We describe the design and analysis of such a study. Trial registration: Pan African Clinical Trials Registry PACTR202007818077777. Registered on 2 July 2020.</p

Framework for the Synthesis of Non-Randomised Studies and Randomised Controlled Trials: A Guidance on Conducting a Systematic Review and Meta-Analysis for Healthcare Decision Making

Introduction: High-quality randomised controlled trials (RCTs) provide the most reliable evidence on the comparative efficacy of new medicines. However, non-randomised studies (NRS) are increasingly recognised as a source of insights into the real-world performance of novel therapeutic products, particularly when traditional RCTs are impractical or lack generalisability. This means there is a growing need for synthesising evidence from RCTs and NRS in healthcare decision making, particularly given recent developments such as innovative study designs, digital technologies and linked databases across countries. Crucially, however, no formal framework exists to guide the integration of these data types. Objectives and Methods: To address this gap, we used a mixed methods approach (review of existing guidance, methodological papers, Delphi survey) to develop guidance for researchers and healthcare decision-makers on when and how to best combine evidence from NRS and RCTs to improve transparency and build confidence in the resulting summary effect estimates. Results: Our framework comprises seven steps on guiding the integration and interpretation of evidence from NRS and RCTs and we offer recommendations on the most appropriate statistical approaches based on three main analytical scenarios in healthcare decision making (specifically, ‘high-bar evidence’ when RCTs are the preferred source of evidence, ‘medium,’ and ‘low’ when NRS is the main source of inference). Conclusion: Our framework augments existing guidance on assessing the quality of NRS and their compatibility with RCTs for evidence synthesis, while also highlighting potential challenges in implementing it. This manuscript received endorsement from the International Society for Pharmacoepidemiology

CIDACS-RL: a novel indexing search and scoring-based record linkage system for huge datasets with high accuracy and scalability

Background: Record linkage is the process of identifying and combining records about the same individual from two or more different datasets. While there are many open source and commercial data linkage tools, the volume and complexity of currently available datasets for linkage pose a huge challenge; hence, designing an efficient linkage tool with reasonable accuracy and scalability is required. Methods: We developed CIDACS-RL (Centre for Data and Knowledge Integration for Health – Record Linkage), a novel iterative deterministic record linkage algorithm based on a combination of indexing search and scoring algorithms (provided by Apache Lucene). We described how the algorithm works and compared its performance with four open source linkage tools (AtyImo, Febrl, FRIL and RecLink) in terms of sensitivity and positive predictive value using gold standard dataset. We also evaluated its accuracy and scalability using a case-study and its scalability and execution time using a simulated cohort in serial (single core) and multi-core (eight core) computation settings. Results: Overall, CIDACS-RL algorithm had a superior performance: positive predictive value (99.93% versus AtyImo 99.30%, RecLink 99.5%, Febrl 98.86%, and FRIL 96.17%) and sensitivity (99.87% versus AtyImo 98.91%, RecLink 73.75%, Febrl 90.58%, and FRIL 74.66%). In the case study, using a ROC curve to choose the most appropriate cut-off value (0.896), the obtained metrics were: sensitivity = 92.5% (95% CI 92.07–92.99), specificity = 93.5% (95% CI 93.08–93.8) and area under the curve (AUC) = 97% (95% CI 96.97–97.35). The multi-core computation was about four times faster (150 seconds) than the serial setting (550 seconds) when using a dataset of 20 million records. Conclusion: CIDACS-RL algorithm is an innovative linkage tool for huge datasets, with higher accuracy, improved scalability, and substantially shorter execution time compared to other existing linkage tools. In addition, CIDACS-RL can be deployed on standard computers without the need for high-speed processors and distributed infrastructures

Alendronate use and bone mineral density gains in women with moderate-severe (stages 3B-5) chronic kidney disease:an open cohort multivariable and propensity score analysis from Funen, Denmark

Funding: This project was funded by the NIHR HTA (project number or 14/36/02) and supported by the NIHR Biomedical Research Centre, Oxford.Bisphosphonates are contraindicated in moderate-to-severe chronic kidney disease patients. However, they are used to prevent fragility fractures in patients with impaired kidney function, despite a lack of evidence on their effects on bone density in these patients. We demonstrated that Alendronate had a positive effect on bone in these patients. This study aimed to assess the association between alendronate use and bone mineral density (BMD) change in subjects with moderate-severe chronic kidney disease (CKD). We created a cohort of CKD stage 3B-5 patients by linking all DXA-based measurements in the Funen area, Denmark, to biochemistry, national health registries and filled prescriptions. Exposure was dispensation of alendronate and the outcome was annualized percentage change in BMD at the femoral neck, total hip and lumbar spine. Individuals were followed from first BMD to the latest of subsequent DXA measurements. Alendronate non-users were identified using incidence density sampling and matched groups were created using propensity scores. Linear regression was used to estimate average differences in the annualized BMD. Use of alendronate was rare in this group of patients: propensity score matching (PSM) resulted in 71 alendronate users and 142 non-users with stage 3B-5 CKD (as in the 1 year before DXA). Whilst alendronate users gained an average 1.07% femoral neck BMD per year, non-users lost an average of 1.59% per annum. The PSM mean differences in annualized BMD were + 2.65% (1.32%, 3.99%), + 3.01% (1.74%, 4.28%) and + 2.12% (0.98%, 3.25%) at the femoral neck, total hip and spine BMD, respectively, all in favour of alendronate users. In a real-world cohort of women with stage 3B-5 CKD, use of alendronate appears associated with a significant improvement of 2-3% per year in the femoral neck, total hip and spine BMD. More data are needed on the anti-fracture effectiveness and safety of bisphosphonate therapy in moderate-severe CKD