The State of Use and Utility of Negative Controls in Pharmacoepidemiologic Studies.

Uses of real-world data in drug safety and effectiveness studies are often challenged by various sources of bias. We undertook a systematic search of the published literature through September 2020 to evaluate the state of use and utility of negative controls to address bias in pharmacoepidemiologic studies. Two reviewers independently evaluated study eligibility and abstracted data. Our search identified 184 eligible studies for inclusion. Cohort studies (115, 63%) and administrative data (114, 62%) were, respectively, the most common study design and data type used. Most studies used negative control outcomes (91, 50%), and for most studies the target source of bias was unmeasured confounding (93, 51%). We identified 4 utility domains of negative controls: 1) bias detection (149, 81%), 2) bias correction (16, 9%), 3) P-value calibration (8, 4%), and 4) performance assessment of different methods used in drug safety studies (31, 17%). The most popular methodologies used were the 95% confidence interval and P-value calibration. In addition, we identified 2 reference sets with structured steps to check the causality assumption of the negative control. While negative controls are powerful tools in bias detection, we found many studies lacked checking the underlying assumptions. This article is part of a Special Collection on Pharmacoepidemiology.

Overview of global real-world data sources for pediatric pharmacoepidemiologic research.

PURPOSE: Given limited information available on real-world data (RWD) sources with pediatric populations, this study describes features of globally available RWD sources for pediatric pharmacoepidemiologic research. METHODS: An online questionnaire about pediatric RWD sources and their attributes and capabilities was completed by members and affiliates of the International Society for Pharmacoepidemiology and representatives of nominated databases. All responses were verified by database representatives and summarized. RESULTS: Of 93 RWD sources identified, 55 unique pediatric RWD sources were verified, including data from Europe (47%), United States (38%), multiregion (7%), Asia-Pacific (5%), and South America (2%). Most databases had nationwide coverage (82%), contained electronic health/medical records (47%) and/or administrative claims data (42%) and were linkable to other databases (65%). Most (71%) had limited outside access (e.g., by approval or through local collaborators); only 10 (18%) databases were publicly available. Six databases (11%) reported having >20 million pediatric observations. Most (91%) included children of all ages (birth until 18th birthday) and contained outpatient medication data (93%), while half (49%) contained inpatient medication data. Many databases captured vaccine information for children (71%), and one-third had regularly updated data on pediatric height (31%) and weight (33%). Other pediatric data attributes captured include diagnoses and comorbidities (89%), lab results (58%), vital signs (55%), devices (55%), imaging results (42%), narrative patient histories (35%), and genetic/biomarker data (22%). CONCLUSIONS: This study provides an overview with key details about diverse databases that allow researchers to identify fit-for-purpose RWD sources suitable for pediatric pharmacoepidemiologic research.

The application of lag times in cancer pharmacoepidemiology: a narrative review.

PURPOSE: With the increasing utilization of medications worldwide, coupled with the increasing availability of long-term data, there is a growing opportunity and need for robust studies evaluating drug-cancer associations. One methodology of importance in such studies is the application of lag times. METHODS: In this narrative review, we discuss the main reasons for using lag times. RESULTS: Namely, we discuss the typically long latency period of cancer concerning both tumor promoter and initiator effects and outline why cancer latency is a key consideration when choosing a lag time. We also discuss how the use of lag times can help reduce protopathic and detection bias. Finally, we present practical advice for implementing lag periods. CONCLUSIONS: In general, we recommend that researchers consider the information that generated the hypothesis as well as clinical and biological knowledge to inform lag period selection. In addition, given that latency periods are usually unknown, we also advocate that researchers examine multiple lag periods in sensitivity analyses as well as duration analyses and flexible modeling approaches.

Published registry-based pharmacoepidemiologic associations show limited concordance with agnostic medication-wide analyses.

OBJECTIVES: To assess how the results of published national registry-based pharmacoepidemiology studies (where select associations are of interest) compare with an agnostic medication-wide approach (where all possible drug associations are tested). STUDY DESIGN AND SETTING: We systematically searched for publications that reported drug associations with any, breast, colon/colorectal, or prostate cancer in the Swedish Prescribed Drug Registry. Results were compared against a previously performed agnostic medication-wide study on the same registry. PROTOCOL: https://osf.io/kqj8n. RESULTS: Most published studies (25/32) investigated previously reported associations. 421/913 (46%) associations had statistically significant results. 134 of the 162 unique drug-cancer associations could be paired with 70 associations in the agnostic study (corresponding drug categories and cancer types). Published studies reported smaller effect sizes and absolute effect sizes than the agnostic study, and generally used more adjustments. Agnostic analyses were less likely to report statistically significant protective associations (based on a multiplicity-corrected threshold) than their paired associations in published studies (McNemar odds ratio 0.13, P = 0.0022). Among 162 published associations, 36 (22%) showed increased risk signal and 25 (15%) protective signal at P < 0.05, while for agnostic associations, 237 (11%) showed increased risk signal and 108 (5%) protective signal at a multiplicity-corrected threshold. Associations belonging to drug categories targeted by individual published studies vs. nontargeted had smaller average effect sizes; smaller P values; and more frequent risk signals. CONCLUSION: Published pharmacoepidemiology studies using a national registry addressed mostly previously proposed associations, were mostly "negative", and showed only modest concordance with their respective agnostic analyses in the same registry.

Bias amplification of unobserved confounding in pharmacoepidemiological studies using indication-based sampling.

PURPOSE: Estimating causal effects in observational pharmacoepidemiology is a challenging task, as it is often plagued by confounding by indication. Restricting the sample to those with an indication for drug use is a commonly performed procedure; indication-based sampling ensures that the exposed and unexposed are exchangeable on the indication-limiting the potential for confounding by indication. However, indication-based sampling has received little scrutiny, despite the hazards of exposure-related covariate control. METHODS: Using simulations of varying levels of confounding and applied examples we describe bias amplification under indication-based sampling. RESULTS: We demonstrate that indication-based sampling in the presence of unobserved confounding can give rise to bias amplification, a self-inflicted phenomenon where one inflates pre-existing bias through inappropriate covariate control. Additionally, we show that indication-based sampling generally leads to a greater net bias than alternative approaches, such as regression adjustment. Finally, we expand on how bias amplification should be reasoned about when distinct clinically relevant effects on the outcome among those with an indication exist (effect-heterogeneity). CONCLUSION: We conclude that studies using indication-based sampling should have robust justification - and that it should by no means be considered unbiased to adopt such approaches. As such, we suggest that future observational studies stay wary of bias amplification when considering drug indications.

Pragmatic considerations for negative control outcome studies to guide non-randomized comparative analyses: A narrative review.

PURPOSE: This narrative review describes the application of negative control outcome (NCO) methods to assess potential bias due to unmeasured or mismeasured confounders in non-randomized comparisons of drug effectiveness and safety. An NCO is assumed to have no causal relationship with a treatment under study while subject to the same confounding structure as the treatment and outcome of interest; an association between treatment and NCO then reflects the potential for uncontrolled confounding between treatment and outcome. METHODS: We focus on two recently completed NCO studies that assessed the comparability of outcome risk for patients initiating different osteoporosis medications and lipid-lowering therapies, illustrating several ways in which confounding may result. In these studies, NCO methods were implemented in claims-based data sources, with the results used to guide the decision to proceed with comparative effectiveness or safety analyses. RESULTS: Based on this research, we provide recommendations for future NCO studies, including considerations for the identification of confounding mechanisms in the target patient population, the selection of NCOs expected to satisfy required assumptions, the interpretation of NCO effect estimates, and the mitigation of uncontrolled confounding detected in NCO analyses. We propose the use of NCO studies prior to initiating comparative effectiveness or safety research, providing information on the potential presence of uncontrolled confounding in those comparative analyses. CONCLUSIONS: Given the increasing use of non-randomized designs for regulatory decision-making, the application of NCO methods will strengthen study design, analysis, and interpretation of real-world data and the credibility of the resulting real-world evidence.

Core concepts in pharmacoepidemiology: Key biases arising in pharmacoepidemiologic studies.

Pharmacoepidemiology has an increasingly important role in informing and improving clinical practice, drug regulation, and health policy. Therefore, unrecognized biases in pharmacoepidemiologic studies can have major implications when study findings are translated to the real world. We propose a simple taxonomy for researchers to use as a starting point when thinking through some of the most pervasive biases in pharmacoepidemiology. We organize this discussion according to biases best assessed with respect to the study population (including confounding by indication, channeling bias, healthy user bias, and protopathic bias), the study design (including prevalent user bias and immortal time bias), and the data source (including misclassification bias and missing data/loss to follow up). This tutorial defines, provides a curated list of recommended references, and illustrates through relevant case examples these key biases to consider when planning, conducting, or evaluating pharmacoepidemiologic studies.

Real-World Trends in the Evaluation of Medical Products.

There is a compelling need to evaluate the real-world health effects of medical products outside of tightly controlled preapproval clinical trials. This is done through pharmacoepidemiology, which is the study of the health effects of medical products (including drugs, biologicals, and medical devices and diagnostics) in populations, often using nonrandomized designs. Recent developments in pharmacoepidemiology span changes in the focus of research questions, research designs, data used, and statistical analysis methods. Developments in these areas are thought to improve the value of the evidence produced by such studies, and are prompting greater use of real-world evidence to inform clinical, regulatory, and reimbursement decisions.

A data-informed approach using individualised dispensing patterns to estimate medicine exposure periods and dose from pharmaceutical claims data.

Pharmaceutical claims data are often used as the primary information source to define medicine exposure periods in pharmacoepidemiological studies. However, often critical information on directions for use and the intended duration of medicine supply are not available. In the absence of this information, alternative approaches are needed to support the assignment of exposure periods. This study summarises the key methods commonly used to estimate medicine exposure periods and dose from pharmaceutical claims data; and describes a method using individualised dispensing patterns to define time-dependent estimates of medicine exposure and dose. This method extends on important features of existing methods and also accounts for recent changes in an individual's medicine use. Specifically, this method constructs medicine exposure periods and estimates the dose used by considering characteristics from an individual's prior dispensings, accounting for the time between prior dispensings and the amount supplied at prior dispensings. Guidance on the practical applications of this method is also provided. Although developed primarily for application to databases, which do not contain duration of supply or dose information, use of this method may also facilitate investigations when such information is available and there is a need to consider individualised and/or changing dosing regimens. By shifting the reliance on prescribed duration and dose to determine exposure and dose estimates, individualised dispensing information is used to estimate patterns of exposure and dose for an individual. Reflecting real-world individualised use of medicines with complex and variable dosing regimens, this method offers a pragmatic approach that can be applied to all medicine classes.

Sex differences in adverse drug reactions: Are women more impacted?

Pharmacovigilance and pharmacoepidemiology studies regarding the sex difference in adverse drug reactions are numerous, and it is now a challenge to take them into account in order to increase drug safety. Here, we present an overview of this topic through data on epidemiology, mechanisms, and methods used for assessing sex differences in drug safety. Because the literature is extensive, we choose to expose a few examples of studies for cardiovascular drugs, anti-infectious, psychotropics, antidiabetics, anticancer drugs and some specific drugs to illustrate our purpose. Many studies show a higher risk in women for most of drugs involving in sex differences. However, physiological, methodological and subjective points have to be taken into account to interpret these results. Clinical trials must also enroll more women to better evaluate sex differences both in efficacy and pharmacovigilance. Nevertheless, when there is a pharmacological rationale underlying the observed association between sex and drug safety profile, it is now unavoidable to think about its consideration for a personalized prescription.

High-risk pregnancy: characterization of medication use profile and association with clinical and sociodemographic factors / Gestação de alto risco: caracterização do perfil de utilização de medicamentos e associação com fatores clínicos e sociodemográficos

Abstract Objectives: describe the profile of medication use and adherence, and the association with clinical and sociodemographic characteristics of high-risk pregnant women attended at a university hospital. Methods: cross-sectional study with data collected through a questionnaire applied on 386 pregnant women. Results: most participants were seen only by the gynecologist (75.1%), started prenatal in the first gestational trimester (86.8%), did not plan the pregnancy (61.9%), and performed an average of 8.2 (SD=4.4) prenatal consultations. The most frequent diagnoses were arterial hypertension (20.5%) and diabetes mellitus (19.7%). Prevalence of medication use was 99.7%, with an average of 5.1 (SD=2.1) medication per woman and 12.7% self-medication. Antianemics (88.9%) and analgesics (63.2%) were the most prevalent classes and 17.9% of the women reported the use of medication with significant gestational risk. Only 36.5% were considered adherent, 32.9% declared they were unaware of the indication of the medication in use and 42% did not receive guidance on the use of the medication during pregnancy. There is no evidence of association between the number of the medication used and clinical and sociodemographic aspects. Conclusions: there is a need to develop strategies to improve the care of this population, with emphasis on strengthening multi-professional care.

Resumo Objetivos: descrever o perfil de utilização de medicamentos e de adesão, e a associação com as características clínicas e sociodemográficas de gestantes de alto risco atendidas em um hospital universitário. Métodos: trata-se de um estudo transversal com dados coletados mediante um questionário estruturado aplicado à 386 gestantes. Resultados: a maior parte das participantes era acompanhada apenas pelo ginecologista (75,1%), iniciou o pré-natal no primeiro trimestre gestacional (86,8%), não planejou a gravidez (61,9%) e realizou em média 8,2 (DP=4,4) consultas de pré-natal. Os diagnósticos mais frequentes foram hipertensão arterial (20,5%) e diabetes mellitus (19,7%). A prevalência de uso de medicamentos foi 99,7%, com média de 5,1 (DP=2,1) medicamentos por mulher e 12,7% de automedicação. Os antianêmicos (88,9%) e analgésicos (63,2%) foram as classes farmacológicas mais prevalentes e 17,9% das gestantes referiram uso de fármacos com risco gestacional relevante. Apenas 36,5% das gestantes foram consideradas aderentes ao tratamento, 32,9% declararam desconhecer a indicação dos medicamentos em uso e 42% não receberam orientações sobre o uso de medicamentos durante a gestação. Não há evidências de associação entre o número de medicamentos utilizados e os aspectos clínicos e sociodemográficos. Conclusão: é necessário desenvolver estratégias para melhorar o atendimento desta população e o uso racional de medicamentos, com ênfase no fortalecimento do cuidado multiprofssional.

Comparative effectiveness research considered methodological insights from simulation studies in physician's prescribing preference.

OBJECTIVES: To review comparative effectiveness research (CER) using physician's prescribing preference as an instrumental variable (PPP IV) in pharmacoepidemiology and to review methodological studies that use simulation to evaluate the performance of PPP IV in CER. STUDY DESIGN AND SETTING: We conducted a review of CER using PPP IV and studies evaluating the use of PPP IV by using simulation methods. We searched Ovid, PubMed, and Google Scholar databases from 2005 to 2020. RESULTS: We identified six simulation studies and 18 CER studies. The simulation studies explored the most suitable ways for using PPP IV in different settings (outcome types, sample size, and the prevalence of outcomes) which can be useful guidance for using PPP IV in CER. The CER studies identified show heterogeneity in terms of validation assumptions, estimation methods, and sample size. Not all applied studies used the methodological insights from the simulation studies. However, they all concluded that PPP is a valid IV. CONCLUSION: Future CER should consider a range of methodological issues to improve the validity of findings when using PPP IV. Specifically, studies should consider the impact of a different choice of statistical methods, forms of proxy for measuring preference, time-varying exposures, and the type of outcome.

Incidence in pharmacoepidemiology-Basic definitions and types of misclassification.

The definition of a new case is a vital step in incidence studies in both epidemiology and pharmacoepidemiology, although with significant differences in methodology between the fields. We define and apply a framework for two different types of new cases of drug use, first-ever and recurrent, and show how the associated misclassifications related to length of run-in period can be expressed by the positive predictive value (PPV). In the study, we consider individual-level dispensations of statins 2006-2019 for 1,017,058 individuals with at least one dispensation in 2019 in Sweden. The incidence proportion for statins for both sexes of all ages in Sweden 2019 varied from 17.4/1000 with a run-in of 8 months, 9.45/1000 with 5 years and 8.4/1000 with 10 years. The PPV was 49% with 8 months and 89% for 5 years using 10 years as gold standard. We conclude that the interpretation of incidence and thus the selection of an appropriate run-in period, in pharmacoepidemiology, depends on whether first-ever use, recurrent treatment or both together (new cases) is the focus of the research question studied. At least five different misclassifications can be introduced depending on how incidence is defined.

Pharmacoepidemiology for oncology clinical practice: Foundations, state of the art and perspectives.

Since the early 2000s, the arrival of the so-called targeted therapies and immunotherapies have prolonged survival rates in many cancers. In parallel, post-marketing surveillance of anticancer drugs through pharmacoepidemiology has gradually developed. This paper provides (i) a detailed argumentation of the foundations for pharmacoepidemiology of anticancer drugs, (ii) an overview of pharmacoepidemiological studies currently available in this field, and (iii) some perspectives to improve pharmacoepidemiology for oncology practice. First of all, according to the existing literature, the development of pharmacoepidemiological studies for the clinical evaluation of anticancer drugs appears particularly justified based on common limitations of clinical trials in oncology regarding essential methodological principles such as adequate control groups, randomisation or double blinding. Many descriptive field cohort studies have investigated together treatment patterns, effectiveness, and safety to compare results from clinical trials with those of everyday practice. The utilisation of anticancer drugs has also been extensively described through cross-sectional or cohort studies by often using medico-administrative or medical databases. Such studies are useful to quantify and characterise use over time in the population, including clinically unvalidated use, and to evaluate adherence and persistence to increasingly available oral anticancer drugs. Despite their importance to increase knowledge, comparative effectiveness or safety studies remain uncommon. In a context of rapidly emerging therapies and personalised treatments, this may be due to methodological challenges especially related to the choice of a comparator or the consideration of confounding by indication. In the future, efforts must be pursued to provide real-time access to high-quality, large-scale clinical, biological and treatment data, and to improve record-linkage between hospital and outpatient databases. More research is also needed to better evaluate all medications, not only anticancer, as part of an overall cancer care pathway and to bring the evaluation of anticancer drugs closer to patients and society (social pharmacology).

Core concepts in pharmacoepidemiology: Confounding by indication and the role of active comparators.

Confounding by indication poses a significant threat to the validity of nonexperimental studies assessing effectiveness and safety of medical interventions. While no different from other forms of confounding in theory, confounding by indication often requires specific methods to address the bias it creates in addition to common epidemiological adjustment or restriction methods. Clinical indication influencing treatment prescription is patient-specific and complex, making it challenging to measure within nonexperimental research. Restriction of the study population to patients with the indication for treatment would effectively mitigate confounding by indication and bring about comparability between exposure and comparator populations with respect to probability of the exposure. Active comparators are often an effective practical solution to restrict the study population in this manner when indication cannot be measured accurately. This article discusses various forms of confounding by indication, the utility of active comparators for nonexperimental studies of treatment effects, and the active comparator, new user (ACNU) study design to implicitly condition on indication. Considerations for selecting active comparators and conducting an ACNU study design are discussed to enable increased adoption of these methods, improve quality of nonexperimental studies, and ultimately strengthen our evidence base for intended and unintended treatment effects in relevant target populations.

Sociodemographic and pharmacoepidemiological profile of people on antiretroviral therapy in the coast of the state of Paraná

The aim of this study was to investigate possible factors related to antiretroviral therapy (ART) that contribute to the understanding of the highest rate of Aids detection on the coast of the state of Paraná, a port region identified administratively as the 1stRegional Health Division (1stHD) in the state of Paraná. Data on the sociodemographic profile of the population undergoing antiretroviral treatment (ART), medication changes, dropout of therapy, proportion of the population undergoing treatment and viral load were obtained through computerized systems. Between July 1, 2018 and June 31, 2019, 1,393 people were on ART in the 1stRS. Of these, 57.6% were male. During this period, 110 people started ART with a predominance of the age group between 30 and 39 years old. ART was switched for169 people and 211 patient dropouts were detected. The proportion of people diagnosed with HIV without treatment (gap) is still high, however 92.7% people on ART have suppressed viral load. It can be concluded that the lower educational level of the population undergoing treatment, the late diagnosis of those infected and the treatment gapprobably contribute to the highest rate of Aids detection in the 1stRS.

Triangulation of pharmacoepidemiology and laboratory science to tackle otic quinolone safety.

BACKGROUND: The scientific method requires studies with high internal and external validity. Though both are necessary, they do not go hand-in-hand: The more controlled a study is to enhance internal validity, the less applicable to real-world clinical care, and vice versa. In the many instances where evidence from clinical trials is not available, scientific inference must rely on more extreme approaches on this spectrum, such as mechanistic (limited generalizability/strong bias control) and real-world evidence (RWE) studies (higher generalizability/lesser bias control). OBJECTIVES: Illustrate how triangulating mechanistic and RWE studies can enhance scientific inference by delivering the supporting evidence for both. METHODS: We describe our research on an unexpected and highly unlikely drug safety issue: the risk of tympanic membrane (TM) perforations resulting from otic quinolone therapy. Tightly controlled laboratory studies using cell culture and rodent models were complemented with pharmacoepidemiological studies of real-world data to translate mechanistic findings and corroborate RWE. RESULTS: We present a cascade of mechanistic and RWE studies investigating fibroblast cytotoxicity, delayed healing of perforated TMs, and spontaneous TM perforations after otic quinolone exposure, all suggesting local tissue toxicity. CONCLUSION: Triangulation of mechanistic and RWE studies allowed incremental progress toward robust evidence on otic quinolone toxicity.

Pharmacoepidemiological methods for computing the duration of pharmacological prescriptions using secondary data sources.

PURPOSE: In pharmacoepidemiology, correctly defining the exposure period of pharmacological treatment is a challenging step when information on the time in treatment is missing or incomplete. METHODS: In this review, we describe several methods for defining exposure to pharmacological treatments using secondary data sources that lack such information. RESULTS AND CONCLUSION: Several methods for assessing the duration of redeemed prescriptions and combining them into temporal sequences are available. We present a set of considerations to make researchers aware of the potentials and pitfalls of these methods that may aid in minimizing biases in research using these methods. Additionally, we highlight that, to date, there is no one-size-fits-all solution. Thus, the choice of method should be based on their area of applicability combined with a careful mapping to the research scenario under investigation.

The Role of the Contextual Cohort to Resolve Some Challenges and Limitations of Comparisons in Pharmacoepidemiology.

In pharmacoepidemiology, comparison studies can provide a useful estimate of the level of increased or decreased risk of specific events with a medication (through a measure of effect). A key focus of pharmacoepidemiological studies is the safety and effectiveness of medicines in their real-world use, and adequate comparisons of effect estimates are critical. However, consideration of guidelines, pharmacoeconomic assessments, and policies for reimbursement have made comparisons in pharmacoepidemiological studies far more difficult to conduct in recent years. Where certain subject characteristics influence the probability of being exposed to a treatment, this can introduce issues of selection bias and confounding. Methodologies are available to minimise selection bias (through case-only and randomised study designs) and deal with confounding (such as regression modelling or propensity score matching methods), however these each have their own limitations. Where prescribing guidelines are present, conducting comparisons in pharmacoepidemiology produces many challenges and not all of these can be easily overcome. Patient channelling can be more frequent with adherence to clinical guidelines compared with when prescribing decisions by doctors are based predominantly on their clinical judgement. Use of a contextual cohort could be considered as an option to characterise the adoption of new medications into clinical practice and describe the prevalence of clinical characteristics and risk factors in the two cohorts, rather than compare event rates and produce an estimate of effect.