Prior Event Rate Ratio Research Articles

Two assumptions of the prior event rate ratio approach for controlling confounding can be evaluated by self-controlled case series and dynamic random intercept modeling

ObjectivesThe prior event rate ratio (PERR) is a recently developed approach for controlling confounding by measured and unmeasured covariates in real-world evidence research and observational studies. Despite its rising popularity in studies of safety and effectiveness of biopharmaceutical products, there is no guidance on how to empirically evaluate its model assumptions. We propose two methods to evaluate two of the assumptions required by the PERR, specifically, the assumptions that occurrence of outcome events does not alter the likelihood of receiving treatment, and that earlier event rate does not affect later event rate. Study Design and SettingWe propose using self-controlled case series (SCCS) and dynamic random intercept modeling (DRIM), respectively, to evaluate the two aforementioned assumptions. A nonmathematical introduction of the methods and their application to evaluate the assumptions are provided. We illustrate the evaluation with secondary analysis of deidentified data on pneumococcal vaccination and clinical pneumonia in The Gambia, West Africa. ResultsSCCS analysis of data on 12,901 vaccinated Gambian infants did not reject the assumption of clinical pneumonia episodes had no influence on the likelihood of pneumococcal vaccination. DRIM analysis of 14,325 infants with a total of 1719 episodes of clinical pneumonia did not reject the assumption of earlier episodes of clinical pneumonia had no influence on later incidence of the disease. ConclusionThe SCCS and DRIM methods can facilitate appropriate use of the PERR approach to control confounding. Plain Language SummaryThe prior event rate ratio is a promising approach for analysis of real-world data and observational studies. We propose two statistical methods to evaluate the validity of two assumptions it is based on. They can facilitate appropriate use of the prior even rate ratio.

Association of COVID-19 vaccination with risks of hospitalization due to cardiovascular and other diseases: A study using data from the UK Biobank

ObjectivesTo explore whether COVID-19 vaccination protects against hospital admission by preventing infections and severe disease. MethodsWe leveraged the UK Biobank and studied associations of COVID-19 vaccination (BioNTech-BNT162b2 or Oxford-AstraZeneca-ChAdOx1) with hospitalizations from cardiovascular and other selected diseases (N = 393,544; median follow-up = 54 days among vaccinated individuals). Multivariable Cox, Poisson regression, propensity score matching, and inverse probability treatment weighting analyses were performed. We also performed adjustment using prescription-time distribution matching, and prior event rate ratio. ResultsWe observed that COVID-19 vaccination (at least one dose), compared with no vaccination, was associated with reduced short-term risks of hospitalizations from stroke (hazard ratio [HR] = 0.178, 95% confidence interval [CI]: 0.127-0.250, P = 1.50e-23), venous thromboembolism (HR = 0.426, CI: 0.270-0.673, P = 2.51e-4), dementia (HR = 0.114, CI: 0.060-0.216; P = 2.24e-11), non-COVID-19 pneumonia (HR = 0.108, CI: 0.080-0.145; P = 2.20e-49), coronary artery disease (HR = 0.563, CI: 0.416-0.762; P = 2.05e-4), chronic obstructive pulmonary disease (HR = 0.212, CI: 0.126-0.357; P = 4.92e-9), type 2 diabetes (HR = 0.216, CI: 0.096-0.486, P = 2.12e-4), heart failure (HR = 0.174, CI: 0.118-0.256, P = 1.34e-18), and renal failure (HR = 0.415, CI: 0.255-0.677, P = 4.19e-4), based on standard Cox regression models. Among the previously mentioned results, reduced hospitalizations for stroke, heart failure, non-COVID-19 pneumonia, and dementia were consistently observed across regression, propensity score matching/inverse probability treatment weighting, prescription-time distribution matching, and prior event rate ratio. The results for two-dose vaccination were similar. ConclusionsTaken together, this study provides further support to the safety and benefits of COVID-19 vaccination, and such benefits may extend beyond reduction of infection risk or severity per se. However, causal relationship cannot be concluded and further studies are required.

The Impact of Vaccination against SARS-CoV-2 on Health Outcomes and Hospital Visits after Omicron Infection in Children and Adolescents Aged 5-18 Years: A Danish Nation-Wide Cohort Study.

This study investigates the impact of vaccination against SARS-CoV-2 on health outcomes and hospital contacts in children and adolescents aged 5-18 years infected with the SARS-CoV-2 Omicron variant, comparing previously vaccinated with unvaccinated. Using national register data, vaccinated and unvaccinated Danish children and adolescents with a positive SARS-CoV-2 test between 1 January and 31 March 2022 (Omicron dominance period) were included. The Prior Event Rate Ratio (PERR) was used to explore differences in hospital contacts (hospitalizations and emergency room (ER) visits), while Inverse Treatment Probability Weighted (IPW) risk ratios were used to explore the risk of severe health outcomes within six weeks following SARS-CoV-2 infection. Vaccinated 5-11-year-old girls had fewer visits to the ER compared to unvaccinated ones, PERR 0.92 (95% CI 0.84-1.00). Vaccinated 5-11-year-old boys had fewer hospitalizations (PERR 0.79 (0.64-0.99)) and more ER visits (PERR 1.13 (1.04-1.22)) compared to unvaccinated ones. An unadjusted and significant lower risk of febrile seizure among vaccinated 5-11-year-olds compared to unvaccinated ones was found (risk ratio 0.12 (0.04-0.39), p ≤ 0.01. No significant differences were found for severe conditions or for croup or pneumonia in either age group. The results indicate a modest protective effect of the vaccine in terms of hospital contacts, but no protective effect on health outcomes after SARS-CoV-2 Omicron infection in this population of Danish children and adolescents.

Use of Bisphosphonates and the Risk of Skin Ulcer: A National Cohort Study Using Data from the French Health Care Claims Database.

Previous pre-clinical and pharmacovigilance disproportionality analyses highlighted a safety signal of cutaneous ulcer with bisphosphonate use. Therefore, our objective is to evaluate this risk and assess whether unmeasured confounding factors could explain this association. This study is a population-based cohort study from a representative sample (1/97th) of the French health insurance claims database: Echantillon Généraliste des Bénéficiaires (EGB) from 2006 to 2019. To limit the impact of our study design and methodological choices on any association between skin ulceration and exposure to bisphosphonates, we used several methods: a Cox proportional hazards analysis and a prior event rate ratio (PERR) analysis, using two propensity matched control groups, and either the first episode of incident ulceration or multiple event-time outcomes. There were 7402 individuals newly exposed to bisphosphonates matched to 29,605 unexposed individuals on propensity score. The primary outcome was skin ulcer occurrence assessed by at least 2 deliveries of wound dressing during the period of one month. Among 6911 individuals newly exposed to bisphosphonates and 28,072 unexposed individuals with no previous skin ulcer, the Cox regression yielded a hazard ratio (HR) of 1.40 (95% CI 1.26-1.56) for newly exposed individuals. Among 7402 exposed and 29,605 unexposed individuals, the PERR analysis found a non-significant HR of 1.03 (95% CI 0.87-1.24). Results were similar on the different sensitivity analyses. No association between bisphosphonate and skin ulcers was found in the French population. The association observed in previous pharmacovigilance studies and in the Cox regression analysis is likely due to unmeasured confounding factors.

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

BackgroundThe 23-valent pneumococcal polysaccharide vaccine (PPV23) is recommended for UK older adults, but how age moderates effectiveness is unclear.MethodsThree 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.ResultsVaccinated 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.ConclusionsPPV23 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.

Influenza vaccination reduced myocardial infarctions in United Kingdom older adults: a prior event rate ratio study

ObjectivesWe aimed to estimate the real-world effectiveness of the influenza vaccine against myocardial infarction (MI) and influenza in the decade since adults aged ≥ 65 years were first recommended the vaccine. Study Design and SettingWe identified annual cohorts, 1997 to 2011, of adults aged ≥ 65 years, without previous influenza vaccination, from UK general practices, registered with the Clinical Practice Research Datalink. Using a quasi-experimental study design to control for confounding bias, we estimated influenza vaccine effectiveness on hospitalization for MI, influenza, and antibiotic prescriptions for lower respiratory tract infections. ResultsVaccination was moderately effective against influenza, the prior event rate ratio–adjusted hazard ratios ranging from 0.70 in 1999 to 0.99 in 2001. Prior event rate ratio–adjusted hazard ratios demonstrated a protective effect against MIs, varying between 0.40 in 2010 and 0.89 in 2001. Aggregated across the cohorts, influenza vaccination reduced the risk of MIs by 39% (95% confidence interval: 34%, 44%). ConclusionEffectiveness of the flu vaccine in preventing MIs in older UK adults is consistent with the limited evidence from clinical trials. Similar trends in effectiveness against influenza and against MIs suggest the risk of influenza mediates the effectiveness against MIs, although divergence in some years implies the mechanism may be complex.

The Effect of Buprenorphine on Human Immunodeficiency Virus Viral Suppression.

Opioid use is prevalent among people living with human immunodeficiency virus (HIV; PLWH) and adversely affects HIV outcomes. We assessed the effect of buprenorphine (BUP) initiation on subsequent HIV viral loads. We identified PLWH from the Johns Hopkins HIV Clinical Cohort who initiated BUP between 2002 and 2017. Poisson regression with robust variance was used to estimate the prevalence of viral suppression (<200 copies/mL) before and after BUP initiation. We matched individuals who initiated BUP with controls based on viral load measurement dates and used prior event rate ratio (PERR) methods to estimate the effect of BUP initiation on viral suppression. PERR methods account for unmeasured confounders. We identified 279 PLWH who initiated BUP. After BUP initiation, PLWH were more likely to be virally suppressed (prevalence ratio [PR], 1.19; 95% confidence interval [CI], 1.03-1.37). After matching PLWH who initiated BUP to controls and accounting for measured and unmeasured confounders, BUP initiation increased viral suppression for both those on antiretroviral therapy (ART) at baseline (PERR PR, 1.08; 95% CI, 1.00-1.18) and those not on ART at baseline (PR, 1.31; 95% CI, 1.10-1.61). Our results indicate that the initiation of BUP results in an increase in the probability of being virally suppressed after accounting for both measured and unmeasured confounders. Persons with opioid use disorder should initiate BUP to not only treat substance use but also to increase viral suppression allowing for treatment as prevention.

Methods for evaluating the benefit and harms of deprescribing in observational research using routinely collected data.

Deprescribing is defined as "the planned and supervised process of dose reduction or stopping of medication that might be causing harm, or no longer be of benefit". Barriers to deprescribing include healthcare professional fear and lack of guidance. These may stem from limited available evidence on benefits and harms of deprescribing medications commonly used among older persons. Advances in pharmacoepidemiology and causal inference methods to evaluate comparative effectiveness and safety of prescribing medications have yet to be considered for deprescribing medication. This paper discusses select methods and how they can be applied to deprescribing research, using case studies of benzodiazepines and low-dose acetylsalicylic acid (aspirin). Target trial emulation involves the explicit application of design principles from randomised controlled trials to observational studies. Several design aspects, including defining eligibility criteria and time zero, require additional considerations for deprescribing studies. The active comparator new user design also presents challenges, including selection of an appropriate comparator. This paper discusses these aspects, and others, in relation to deprescribing studies. Furthermore, methods proposed to control for confounding, in particular, the prior event rate ratio and propensity scores, are discussed. Introduction of billing codes or mechanisms for accurately determining when deprescribing has occurred would enhance the ability to conduct research using routinely collected data. Although the approaches discussed in this paper may strengthen observational studies of deprescribing, their use may be best suited to certain scenarios or research questions, where randomised controlled trials may be less feasible.

Impact of influenza vaccination on amoxicillin prescriptions in older adults: A retrospective cohort study using primary care data.

Bacterial infections of the upper and lower respiratory tract are a frequent complication of influenza and contribute to the widespread use of antibiotics. Influenza vaccination may help reduce both appropriate and inappropriate prescribing of antibiotics. Electronic health records provide a rich source of information for assessing secondary effects of influenza vaccination. We conducted a retrospective study to estimate effects of influenza vaccine on antibiotic (amoxicillin) prescription in the elderly based on data from the Clinical Practice Research Datalink. The introduction of UK policy to recommend the influenza vaccine to older adults in 2000 led to a substantial increase in uptake, creating a natural experiment. Of 259,753 eligible patients that were unvaccinated in 1999 and aged≥65y by January 2000, 88,519 patients received influenza vaccination in 2000. These were propensity score matched 1:1 to unvaccinated patients. Time-to-amoxicillin was analysed using the Prior Event Rate Ratio (PERR) Pairwise method to address bias from time-invariant measured and unmeasured confounders. A simulation study and negative control outcome were used to help strengthen the validity of results. Compared to unvaccinated patients, those from the vaccinated group were more likely to be prescribed amoxicillin in the year prior to vaccination: hazard ratio (HR) 1.90 (95% confidence interval 1.83, 1.98). Following vaccination, the vaccinated group were again more likely to be prescribed amoxicillin, HR 1.64 (1.58,1.71). After adjusting for prior differences between the two groups using PERR Pairwise, overall vaccine effectiveness was 0.86 (0.81, 0.92). Additional analyses suggested that provided data meet the PERR assumptions, these estimates were robust. Once differences between groups were taken into account, influenza vaccine had a beneficial effect, lowering the frequency of amoxicillin prescribing in the vaccinated group. Ensuring successful implementation of national programmes of vaccinating older adults against influenza may help contribute to reducing antibiotic resistance.

Aspirin reduces cardiovascular events in patients with pneumonia: a prior event rate ratio analysis in a large primary care database.

Ischaemic stroke and myocardial infarction (MI) are common after pneumonia and are associated with long-term mortality. Aspirin may attenuate this risk and should be explored as a therapeutic option. We extracted all patients with pneumonia (aged over 50 years) from the Clinical Practice Research Datalink (CPRD), a large UK primary care database, from inception until January 2019. We then performed a prior event rate ratio (PERR) analysis with propensity score matching (PSM), an approach that allows for control of measured and unmeasured confounding, with aspirin usage as the exposure and ischaemic events as the outcome. The primary outcome was the combined outcome of ischaemic stroke and MI. Secondary outcomes were ischaemic stroke and MI individually. Relevant confounders (smoking, comorbidities, age and gender) were included in the analysis. 48 743 patients were eligible for matching. Of these, 9864 were aspirin users who were matched to 9864 non-users. Aspirin users had a reduced risk of the primary outcome (adjusted hazard ratio 0.64, 95% CI 0.52-0.79) in the PERR analysis. For both secondary outcomes, aspirin use was also associated with a reduced risk for MI (hazard ratio 0.46, 95% CI 0.30-0.72) and stroke (hazard ratio 0.70, 95% CI 0.55-0.91), respectively. This study provides supporting evidence that aspirin use is associated with reduced ischaemic events after pneumonia in a primary care setting. This drug may have a future clinical role in preventing this important complication.

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.

Prior event rate ratio adjustment produced estimates consistent with randomized trial: a diabetes case study

ObjectivesElectronic health records (EHR) provide a valuable resource for assessing drug side-effects, but treatments are not randomly allocated in routine care creating the potential for bias. We conduct a case study using the Prior Event Rate Ratio (PERR) Pairwise method to reduce unmeasured confounding bias in side-effect estimates for two second-line therapies for type 2 diabetes, thiazolidinediones, and sulfonylureas. Study Design and SettingsPrimary care data were extracted from the Clinical Practice Research Datalink (n = 41,871). We utilized outcomes from the period when patients took first-line metformin to adjust for unmeasured confounding. Estimates for known side-effects and a negative control outcome were compared with the A Diabetes Outcome Progression Trial (ADOPT) trial (n = 2,545). ResultsWhen on metformin, patients later prescribed thiazolidinediones had greater risks of edema, HR 95% CI 1.38 (1.13, 1.68) and gastrointestinal side-effects (GI) 1.47 (1.28, 1.68), suggesting the presence of unmeasured confounding. Conventional Cox regression overestimated the risk of edema on thiazolidinediones and identified a false association with GI. The PERR Pairwise estimates were consistent with ADOPT: 1.43 (1.10, 1.83) vs. 1.39 (1.04, 1.86), respectively, for edema, and 0.91 (0.79, 1.05) vs. 0.94 (0.80, 1.10) for GI. ConclusionThe PERR Pairwise approach offers potential for enhancing postmarketing surveillance of side-effects from EHRs but requires careful consideration of assumptions.

Assessing the prior event rate ratio method via probabilistic bias analysis on a Bayesian network.

Background: Unmeasured confounders are commonplace in observational studies conducted using real‐world data. Prior event rate ratio (PERR) adjustment is a technique shown to perform well in addressing such confounding. However, it has been demonstrated that, in some circumstances, the PERR method actually increases rather than decreases bias. In this work, we seek to better understand the robustness of PERR adjustment. Methods: We begin with a Bayesian network representation of a generalized observational study, which is subject to unmeasured confounding. Previous work evaluating PERR performance used Monte Carlo simulation to calculate joint probabilities of interest within the study population. Here, we instead use a Bayesian networks framework. Results: Using this streamlined analytic approach, we are able to conduct probabilistic bias analysis (PBA) using large numbers of combinations of parameters and thus obtain a comprehensive picture of PERR performance. We apply our methodology to a recent study that used the PERR in evaluating elderly‐specific high‐dose (HD) influenza vaccine in the US Veterans Affairs population. That study obtained an HD relative effectiveness of 25% (95% CI: 2%‐43%) against influenza‐ and pneumonia‐associated hospitalization, relative to standard‐dose influenza vaccine. In this instance, we find that the PERR‐adjusted result is more like to underestimate rather than to overestimate the relative effectiveness of the intervention. Conclusions: Although the PERR is a powerful tool for mitigating the effects of unmeasured confounders, it is not infallible. Here, we develop some general guidance for when a PERR approach is appropriate and when PBA is a safer option.

Estimating the risk of acute kidney injury associated with use of diuretics and renin angiotensin aldosterone system inhibitors: A population based cohort study using the clinical practice research datalink

BackgroundThe risk of acute kidney injury (AKI) attributable to renin angiotensin aldosterone (RAAS) inhibitors and diuretics remains unclear.MethodsWe conducted a prospective cohort study using the Clinical Practice Research Datalink (2008–2015) linked to Hospital Episode Statistics – Admitted Patient Care and Office for National Statistics mortality data. Patients were included if they had one or more chronic diagnoses requiring medication. Exposed patients had a first ever prescription for RAAS inhibitors/diuretics during the study period. AKI risk associated with exposure was determined by multivariable Cox regression, propensity score-adjusted Cox regression and a prior event rate ratio (PERR) analysis.ResultsOne hundred forty thousand nine hundred fifty-two individuals were included. Increased AKI risk in the exposed group was demonstrated in both the multivariable and propensity score-adjusted cox regressions (HR 1.23 (95% CI 1.04–1.45) and HR 1.24 (1.05–1.47) respectively). The PERR analysis provided a similar overall hazard ratio with a wider confidence interval (HR 1.29 (0.94–1.63)). The increased AKI risk in the exposed group was present only in those receiving two or more antihypertensives. Absolute AKI risk was small.ConclusionsRAAS inhibitors/diuretics result in an increased risk of AKI. The absolute increase in AKI risk is small, however, and needs to be considered in the context of any potential benefits.

Confounder adjustment in observational comparative effectiveness researches: (2) statistical adjustment approaches for unmeasured confounders

Observational study of therapy efficacy comparison has been widely conducted to provide the additional efficacy evidence to support randomized control study. Statistical adjustment for unmeasured confounders is a major challenge in observational study of therapy efficacy comparison. This paper summarizes and evaluates the relative statistical methods. Currently, the most commonly used methods include instrumental variable, difference-in-differences (DiD) model and prior event rate ratio (PERR) adjustment. The instrumental variable method skill fully escapes unmeasured confounders through model structure, but it is not easy to obtain satisfied instrumental variables. Both PERR and DiD require the data prior to exposure which are not always collected in observational studies. Unmeasured confounders could result in new requirements and pose new challenges for statistical methods, which needs further study and improvement.

Advantages of large medical record database for outcomes research: Insights into post-menopausal hormone therapy.

Approximately 25 years ago, our team initiated studies to determine whether outcome results from a large medical record database would yield valid results. We utilized the data in the United Kingdom (UK) General Practice Research Database (GPRD) to replicate the randomized controlled trial (RCT) study result and compared them to confirm the database results. The initial studies compared favorably, but some subsequent studies did not. This prompted development of a new strategy to determine and correct for unrecognized confounding in the database. This strategy divided outcome rates prior to initiation of therapy in the database study (which should include both identified and unidentified confounders) into the outcome rates during the treatment interval. When they differed from Cox‐adjusted results, it reflected unrecognized confounding. We called this strategy Prior Event Rate Ratio (PERR)–adjusted outcome.One of our previously published observational studies replicated the Women's Health Initiative (WHI) RCT study of hormone therapy in post‐menopausal women. Our study results replicated the WHI RCT results except it did not exhibit an increase in heart attack in contrast to the RCT. Furthermore, we could not evaluate death reliably since our analytic approach to overcome unrecognized confounding does not work for this outcome. In Volume 1, Issue 1 of the Learning Health Systems open access journal, we published a new study (titled “A new method to address unmeasured confounding of mortality in observational studies”) that reported a novel death method, based on our prior methodology, that could analyze unrecognized confounding of the death outcome. This new methodology, termed Post Treatment Event Rate Ratio (PTERR), permitted a reliable examination of mortality in post‐menopausal women undergoing hormone therapy. These results are reported in this manuscript. The study used the data from our previous observational study. It demonstrates that estrogen therapy markedly reduced death in post‐menopausal women.This work also illuminates principles of database construction and correspondingly demonstrates the use of novel methodologies for obtaining valid results, which can be applied to enable learning from such databases. Work to advance such methodologies is essential to advancing the scientific integrity Core Value underpinning learning health systems (LHSs). Indeed, in the absence of such efforts to develop and refine methodologies for learning trustworthy lessons from real‐world data, we risk inadvertently creating mis‐learning systems.

Proton-Pump Inhibitors and Long-Term Risk of Community-Acquired Pneumonia in Older Adults.

ObjectivesTo estimate associations between long‐term use of proton pump inhibitors (PPIs) and pneumonia incidence in older adults in primary care.DesignLongitudinal analyses of electronic medical records.SettingEnglandParticipantsIndividuals aged 60 and older in primary care receiving PPIs for 1 year or longer (N=75,050) and age‐ and sex‐matched controls (N=75,050).MeasurementsNet hazard ratios for pneumonia incidence in Year 2 of treatment were estimated using the prior event rate ratio (PERR), which adjusts for pneumonia incidence differences before initiation of treatment. Inverse probability weighted models adjusted for 78 demographic, disease, medication, and healthcare usage measures.ResultsDuring the second year after initiating treatment, PPIs were associated with greater hazard of incident pneumonia (PERR‐adjusted hazard ratio=1.82, 95% confidence interval=1.27–2.54), accounting for pretreatment pneumonia rates. Estimates were similar across age and comorbidity subgroups. Similar results were also obtained from propensity score– and inverse probability–weighted models.ConclusionIn a large cohort of older adults in primary care, PPI prescription was associated with greater risk of pneumonia in the second year of treatment. Results were robust across alternative analysis approaches. Controversies about the validity of reported short‐term harms of PPIs should not divert attention from potential long‐term effects of PPI prescriptions on older adults.

Characteristics of Children Prescribed Antipsychotics: Analysis of Routinely Collected Data.

Objective: Antipsychotics are licensed for psychosis and are also prescribed for behavior control. This study aims to examine characteristics and outcomes of children prescribed antipsychotics.Methods: A cohort study using general practice and hospital records linked with education records for 1,488,936 children living in Wales between 1999 and 2015. The characteristics of the children who were prescribed antipsychotics are presented using descriptive statistics and outcomes such as respiratory illness, diabetes, and injury were analyzed using multilevel logistic regression and the prior event rate ratio (PERR).Results: Children with intellectual difficulty/autism were more likely to be prescribed antipsychotics (2.8% have been prescribed an antipsychotic [75% with autism] compared with 0.15% of children without intellectual difficulty). Those with intellectual disabilities/autism were prescribed antipsychotics at a younger age and for a longer period. Antipsychotic use was associated with a higher rate of respiratory illness for all (PERR of hospital admission: 1.55 [95% CI: 1.51–1.598] or increase in rate of 2 per 100 per year in those treated), and for those with intellectual difficulty/autism, there was a higher rate of injury and hospitalized depression. However, among those without intellectual difficulty/autism, there were lower rates of depression (PERR: 0.55 [95% CI: 0.51–0.59]).Conclusions: This work shows real-world use of antipsychotics and provides information on the rate of possible adverse events in children treated. Antipsychotics are predominantly used for those with intellectual difficulty/autism rather than those with a psychotic diagnosis. There is evidence that rates of respiratory disease, epilepsy, and diabetes are also higher postantipsychotic use for all. In those with intellectual difficulty/autism, hospital-admitted depression and injury are higher postantipsychotic use. The use of antipsychotics for behavioral management is likely to have increased cost implications to the healthcare system.

Risk of Adverse Outcomes for Older People with Dementia Prescribed Antipsychotic Medication: A Population Based e-Cohort Study

IntroductionOver recent years there has been growing evidence of increased risk of mortality associated with antipsychotic use in older people with dementia. Although this concern combined with limited evidence of efficacy has informed guidelines restricting antipsychotic prescription in this population, the use of antipsycotics remains common. Many published studies only report short-term outcomes, are restricted to examining mortality and stroke risk or have other limitations. The aim of this study was to assess adverse outcomes associated with the use of antipsychotics in older people living with dementia in Wales (UK).MethodsThis was a retrospective study of a population-based dementia cohort using the Welsh Secure Anonymised Information Linkage databank. The prior event rate ratio (PERR) was used to estimate the influence of exposure to antipsychotic medication on acute cardiac events, venous thromboembolism, stroke and hip fracture, and adjusted Cox proportional hazard models were used to compare all-cause mortality.ResultsA total of 10,339 people aged ≥65 years were identified with newly diagnosed dementia. After excluding those who did not meet the inclusion criteria, 9674 people remained in the main cohort of whom 3735 were exposed to antipsychotic medication. An increased risk of a venous thromboembolic episode [PERR 1.95, 95% confidence interval (CI) 1.83–2.0], stroke (PERR 1.41, 95% CI 1.4–1.46) and hip fracture (PERR 1.62, 95% CI 1.59–1.65) was associated with antipsychotic use. However, there was no long-term increased mortality in people exposed to antipsychotics (adjusted hazard ratio 1.06, 95% CI 0.99–1.13).ConclusionsThe increase in adverse medical events supports guidelines restricting antipsychotic use in this population.Electronic supplementary materialThe online version of this article (doi:10.1007/s40120-016-0060-6) contains supplementary material, which is available to authorized users.

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

IntroductionThe 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.MethodsThis 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).ResultsTheoretical 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.ConclusionIn the aggregate the results provide strong evidence that the PTERR method to evaluate unmeasured confounding will be a valuable analytic tool.