Multi-country rapid adverse drug event assessment: the Asian Pharmacoepidemiology Network (AsPEN) antipsychotic and acute hyperglycaemia study

Prescribing Cascades of Loop Diuretics and Anti-vertigo Drugs Following Treatment with Gabapentinoids and Benzodiazepines: Prescription Sequence Symmetry Analysis of a Large-Scale Claims Database Including Japanese Older Adults

BACKGROUND

Gabapentinoids (GBP) and benzodiazepines (BZ) are commonly prescribed in older adults and their package inserts list edema and vertigo as adverse drug reactions. These adverse drug reactions may be treated with symptomatic drug therapies without discontinuing the culprit drugs or decreasing their dose, thereby initiating a prescribing cascade and often resulting in polypharmacy. Whether prescribing cascades occur in the treatment of edema and dizziness among Japanese patients treated with GBP and BZ has not been investigated, including treatment with mirogabalin, a class drug of GBP marketed in Japan.

OBJECTIVE

We aimed to investigate prescribing cascades with GBP-induced and BZ-induced edema and dizziness treated with loop diuretics (LD) and anti-vertigo drugs (AVD), respectively, among older adults.

METHODS

A prescription sequence symmetry analysis design was used to detect signals of prescribing cascades associated with edema and dizziness induced by GBP and BZ (exposure drugs). Loop diuretics and AVD were the outcome drugs used to identify prescribing cascades following the initiation of exposure drugs. The study population consisted of enrollees of a large-scale health claims database provided by DeSC Healthcare, Inc., between April 2014 and March 2021. Subjects eligible for a prescription sequence symmetry analysis were patients aged ≥ 65 years prescribed an outcome drug within 90 days before and after exposure drug initiation. A signal of a prescribing cascade was detected if secular trend-adjusted sequence ratios were statistically significant on comparison of the frequencies of outcome drug initiation before and after exposure drug initiation.

RESULTS

We identified 2671 patients with prescriptions of a GBP-LD combination, 4009 with a GBP-AVD combination, 8675 with a BZ-LD combination, and 9462 with a BZ-AVD combination. The adjusted sequence ratios for GBP-LD and BZ-LD cascades were significantly larger than one (adjusted sequence ratio [95% confidence interval], 1.69 [1.56-1.83]; 1.35 [1.29-1.41], respectively), indicating positive signals of prescribing cascades. No signal was detected for the GBP-AVD or BZ-AVD cascade (0.89 [0.83-0.94]; 0.90 [0.87-0.94], respectively). The adjusted sequence ratio for the mirogabalin cascade was higher than that for pregabalin (2.23 [1.84-2.71] vs 1.59 [1.46-1.73]).

CONCLUSIONS

Our study provides good evidence that LD-prescribing cascades associated with edema would be a class effect of GBP and BZ. Edema emerging around 1 month after GBP initiation should be carefully differentiated from pathological edema, and undue LD prescription as a prescribing cascade should be avoided.

External validity in distributed data networks

PURPOSE

While much has been written about how distributed networks address internal validity, external validity is rarely discussed. We aimed to define key terms related to external validity, discuss how they relate to distributed networks, and identify how three networks (the US Food and Drug Administration's Sentinel System, the Canadian Network for Observational Drug Effect Studies [CNODES], and the National Patient Centered Clinical Research Network [PCORnet]) deal with external validity.

METHODS

We define external validity, target populations, target validity, generalizability, and transportability and describe how each relates to distributed networks. We then describe Sentinel, CNODES, and PCORnet and how each approaches these concepts, including a sample case study.

RESULTS

Each network approaches external validity differently. As its target population is US citizens and it includes only US data, Sentinel primarily worries about lack of external validity by not including some segments of the population. The fact that CNODES includes Canadian, United States, and United Kingdom data forces them to seriously consider whether the United States and United Kingdom data will be transportable to Canadian citizens when they meta-analyze database-specific estimates. PCORnet, with its focus on study-specific cohorts and pragmatic trials, conducts more case-by-case explorations of external validity for each new analytic data set it generates.

CONCLUSIONS

There is no one-size-fits-all approach to external validity within distributed networks. With these networks and comparisons between their findings becoming a key part of pharmacoepidemiology, there is a need to adapt tools for improving external validity to the distributed network setting.

Prescribing Cascades with Recommendations to Prevent or Reverse Them: A Systematic Review

BACKGROUND

To reduce prescribing cascades occurring in clinical practice, healthcare providers require information on the prescribing cascades they can recognize and prevent.

OBJECTIVE

This systematic review aims to provide an overview of prescribing cascades, including dose-dependency information and recommendations that healthcare providers can use to prevent or reverse them.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was followed. Relevant literature was identified through searches in OVID MEDLINE, OVID Embase, OVID CINAHL, and Cochrane. Additionally, Web of Science and Scopus were consulted to analyze reference lists and citations. Publications in English were included if they analyzed the occurrence of prescribing cascades. Prescribing cascades were included if at least one study demonstrated a significant association and were excluded when the adverse drug reaction could not be confirmed in the Summary of Product Characteristics. Two reviewers independently extracted and grouped similar prescribing cascades. Descriptive summaries were provided regarding dose-dependency analyses and recommendations to prevent or reverse these prescribing cascades.

RESULTS

A total of 95 publications were included, resulting in 115 prescribing cascades with confirmed adverse drug reactions for which at least one significant association was found. For 52 of these prescribing cascades, information regarding dose dependency or recommendations to prevent or reverse prescribing cascades was found. Dose dependency was analyzed and confirmed for 12 prescribing cascades. For example, antipsychotics that may cause extrapyramidal syndrome followed by anti-parkinson drugs. Recommendations focused on dosage lowering, discontinuing medication, and medication switching. Explicit recommendations regarding alternative options were given for three prescribing cascades. One example was switching to ondansetron or granisetron when extrapyramidal syndrome is experienced using metoclopramide.

CONCLUSIONS

In total, 115 prescribing cascades were identified and an overview of 52 of them was generated for which recommendations to prevent or reverse them were provided. Nonetheless, information regarding alternative options for managing prescribing cascades was scarce.

Prescribing cascades in community-dwelling adults: A systematic review

The misattribution of an adverse drug reaction (ADR) as a symptom or illness can lead to the prescribing of additional medication, referred to as a prescribing cascade. The aim of this systematic review is to identify published prescribing cascades in community-dwelling adults. A systematic review was reported in line with the PRISMA guidelines and pre-registered with PROSPERO. Electronic databases (Medline [Ovid], EMBASE, PsycINFO, CINAHL, Cochrane Library) and grey literature sources were searched. Inclusion criteria: community-dwelling adults; risk-prescription medication; outcomes-initiation of new medicine to "treat" or reduce ADR risk; study type-cohort, cross-sectional, case-control, and case-series studies. Title/abstract screening, full-text screening, data extraction, and methodological quality assessment were conducted independently in duplicate. A narrative synthesis was conducted. A total of 101 studies (reported in 103 publications) were included. Study sample sizes ranged from 126 to 11 593 989 participants and 15 studies examined older adults specifically (≥60 years). Seventy-eight of 101 studies reported a potential prescribing cascade including calcium channel blockers to loop diuretic (n = 5), amiodarone to levothyroxine (n = 5), inhaled corticosteroid to topical antifungal (n = 4), antipsychotic to anti-Parkinson drug (n = 4), and acetylcholinesterase inhibitor to urinary incontinence drugs (n = 4). Identified prescribing cascades occurred within three months to one year following initial medication. Methodological quality varied across included studies. Prescribing cascades occur for a broad range of medications. ADRs should be included in the differential diagnosis for patients presenting with new symptoms, particularly older adults and those who started a new medication in the preceding 12 months.

The Medicines Intelligence Centre of Research Excellence: Co-creating real-world evidence to support the evidentiary needs of Australian medicines regulators and payers

Regulators and payers play a pivotal role in facilitating timely and affordable access to safe and efficacious medicines. They use evidence generated from randomised clinical trials (RCTs) to support decisions to register and subsidise medicines. However, at the time of registration and subsidy approval, regulators and payers face uncertainty about how RCT outcomes will translate to real-world clinical practice. In response to this situation, medicines policy agencies worldwide have endorsed the use of real-world data (RWD) to derive novel insights on the use and outcomes of prescribed medicines. Recent reforms around data availability and use in Australia are creating unparalleled data access and opportunities for Australian researchers to undertake large-scale research to generate evidence on the safety and effectiveness of medicines in the real world. Highlighting the critical importance of research in this area, Quality Use of Medicines and Medicine Safety was announced as Australia's 10th National Health Priority in 2019. The National Health and Medical Research Council, Medicines Intelligence Centre of Research Excellence (MI-CRE) has been formed to take advantage of the renewed focus on quality use of medicines and the changing data landscape in Australia. It will generate timely research supporting the evidentiary needs of Australian medicines regulators and payers by accelerating the development and translation of real-world evidence on medicines use and outcomes. MI-CRE is developing a coordinated approach to identify, triage and respond to priority questions where there are significant uncertainties about medicines use, (cost)-effectiveness, and/or safety and creating a data ecosystem that will streamline access to Australian data to enable researchers to generate robust evidence in a timely manner. This paper outlines how MI-CRE will partner with policy makers, clinicians, and consumer advocates to leverage real-world data to co-create real-world evidence, to improve quality use of medicines and reduce medicine-related harm.

Metabolic events associated with the use of antipsychotics in children, adolescents and young adults: a multinational sequence symmetry study

It is known that younger patients treated with antipsychotics are at increased risk of metabolic events; however, it is unknown how this risk varies according to ethnicity, the class of antipsychotic and the specific product used, and by age group. We conducted a multinational sequence symmetry study in Asian populations (Hong Kong, Japan, Korea, Taiwan and Thailand) and non-Asian populations (Australia and Denmark) to evaluate the metabolic events associated with antipsychotics in both Asian and non-Asian populations, for typical and atypical antipsychotics, and by the subgroups of children and adolescents, and young adults. Patients aged 6-30 years newly initiating oral antipsychotic drugs were included. We defined a composite outcome for metabolic events which included dyslipidemia, hypertension and hyperglycemia. We calculated the sequence ratio (SR) by dividing the number of people for whom a medicine for one of the outcome events was initiated within a 12-month period after antipsychotic initiation by the number before antipsychotic initiation. This study included 346,904 antipsychotic initiators across seven countries. Antipsychotic use was associated with an increased risk of composite metabolic events with a pooled adjusted SR (ASR) of 1.22 (95% CI 1.00-1.50). Pooled ASRs were similar between Asian (ASR, 1.22; 95% CI 0.88-1.70) and non-Asian populations (ASR, 1.22; 95% CI 1.04-1.43). The pooled ASR for typical and atypical antipsychotics was 0.98 (95% CI 0.85-1.12) and 1.24 (95% CI 0.97-1.59), respectively. No difference was observed in the relative effect in children and adolescents compared to young adults. The risk of metabolic events associated with antipsychotics use was similar in magnitude in Asian and non-Asian populations despite the marked difference in drug utilization patterns.

Generating Real-World Evidence on the Quality Use, Benefits and Safety of Medicines in Australia: History, Challenges and a Roadmap for the Future

Australia spends more than $20 billion annually on medicines, delivering significant health benefits for the population. However, inappropriate prescribing and medicine use also result in harm to individuals and populations, and waste of precious health resources. Medication data linked with other routine collections enable evidence generation in pharmacoepidemiology; the science of quantifying the use, effectiveness and safety of medicines in real-world clinical practice. This review details the history of medicines policy and data access in Australia, the strengths of existing data sources, and the infrastructure and governance enabling and impeding evidence generation in the field. Currently, substantial gaps persist with respect to cohesive, contemporary linked data sources supporting quality use of medicines, effectiveness and safety research; exemplified by Australia's limited capacity to contribute to the global effort in real-world studies of vaccine and disease-modifying treatments for COVID-19. We propose a roadmap to bolster the discipline, and population health more broadly, underpinned by a distinct capability governing and streamlining access to linked data assets for accredited researchers. Robust real-world evidence generation requires current data roadblocks to be remedied as a matter of urgency to deliver efficient and equitable health care and improve the health and well-being of all Australians.

Evaluating the use of prescription sequence symmetry analysis as a pharmacovigilance tool: A scoping review

BACKGROUND

The (prescription) sequence symmetry analysis (PSSA) design has been used to identify potential prescribing cascade signals by assessing the prescribing sequence of an index drug relative to a marker drug presumed to treat an adverse drug event provoked by the index drug.

OBJECTIVES

This review aimed to explore the use of the PSSA design as a pharmacovigilance tool with a particular focus on the breadth of identified signals and advances in PSSA methodology.

METHODS

We searched Embase, PubMed/Medline, Google Scholar, Web of Science and grey literature to identify studies that used the PSSA methodology. Two reviewers independently extracted relevant data for each included article. Study characteristics including signals identified, exposure time window, stratified analyses, and use of controls were extracted.

RESULTS

We identified 53 studies which reported original results obtained using PSSA methodology or quantified the validity of components of the PSSA design. Of those, nine studies provided validation metrics showing reasonable sensitivity and high specificity of PSSA to identify prescribing cascade signals. We identified 340 unique index drug - marker drug signals published in the PSSA literature, representing 281 unique index - marker pharmacological class dyads (i.e., unique fourth-level Anatomical Therapeutic Chemical [ATC] classification dyads). Commonly observed signals were identified for index drugs acting upon the nervous system (34%), cardiovascular system (21%), and blood and blood-forming organs (15%), and many marker drugs were related to the nervous system (25%), alimentary tract and metabolism (23%), cardiovascular system (17%), and genitourinary system and sex hormones (14%). Negative controls and positive controls were utilized in 21% and 13% of studies, respectively.

CONCLUSIONS

The PSSA methodology has been used in 53 studies worldwide to detect and evaluate over 300 unique prescribing cascades signals. Researchers should consider sensitivity analyses incorporating negative and/or positive controls and additional time windows to evaluate time-varying biases when designing PSSA studies.

Suitability of databases in the Asia-Pacific for collaborative monitoring of vaccine safety

INTRODUCTION

Information regarding availability of electronic healthcare databases in the Asia-Pacific region is critical for planning vaccine safety assessments particularly, as COVID-19 vaccines are introduced. This study aimed to identify data sources in the region, potentially suitable for vaccine safety surveillance. This manuscript is endorsed by the International Society for Pharmacoepidemiology (ISPE).

METHODS

Nineteen countries targeted for database reporting were identified using published country lists and review articles. Surveillance capacity was assessed using two surveys: a 9-item introductory survey and a 51-item full survey. Survey questions related to database characteristics, covariate and health outcome variables, vaccine exposure characteristics, access and governance, and dataset linkage capability. Other questions collated research/regulatory applications of the data and local publications detailing database use for research.

RESULTS

Eleven databases containing vaccine-specific information were identified across 8 countries. Databases were largely national in coverage (8/11, 73%), encompassed all ages (9/11, 82%) with population size from 1.4 to 52 million persons. Vaccine exposure information varied particularly for standardized vaccine codes (5/11, 46%), brand (7/11, 64%) and manufacturer (5/11, 46%). Outcome data were integrated with vaccine data in 6 (55%) databases and available via linkage in 5 (46%) databases. Data approval processes varied, impacting on timeliness of data access.

CONCLUSIONS

Variation in vaccine data availability, complexities in data access including, governance and data release approval procedures, together with requirement for data linkage for outcome information, all contribute to the challenges in building a distributed network for vaccine safety assessment in the Asia-Pacific and globally. Common data models (CDMs) may help expedite vaccine safety research across the region.

Real-world evidence of population differences in allopurinol-related severe cutaneous adverse reactions in East Asians: A population-based cohort study

Abstract

Allopurinol‐related severe cutaneous adverse reactions (SCARs) are strongly associated with HLA‐B*58:01, the allele frequency (AF) of which is largely different among East Asians. However, evidence of population differences in SCAR development and relevance of genetic and/or other risk factors in the real‐world remain unelucidated. This study aimed to evaluate population differences in allopurinol‐related SCAR incidence related to genetic and/or other risk factors among East Asians in the real‐world. A population‐based cohort study was conducted using claims databases from Taiwan, Korea, and Japan. New users of allopurinol (311,846; 868,221; and 18,052 in Taiwan, Korea, and Japan, respectively) were followed up to 1 year. As control drugs, phenytoin and carbamazepine were used. The crude incidence rate ratios (IRRs) of SCARs for allopurinol against phenytoin or carbamazepine were the highest in Taiwan (IRR, 0.62 and 1.22; 95% confidence interval [CI], 0.54–0.72 and 1.01–1.47, respectively), followed by Korea (IRR, 0.34 and 0.82; 95% CI, 0.29–0.40 and 0.77–0.87), and the lowest in Japan (IRR, 0.04 and 0.16; 95% CI, 0.02–0.08 and 0.09–0.29). This order was accordant with that of AF ratios (AFRs) reported of HLA‐B*58:01 against alleles responsible for phenytoin‐ or carbamazepine‐related SCARs. The IRRs were higher in patients with chronic kidney disease, females, and elderly. This study demonstrated population differences in the risk of allopurinol‐related SCAR development among East Asians based on genetic and other common risk factors. This finding will help to promote appropriate risk management for allopurinol‐related SCARs based on ethnic origins.

Automation in signal management in pharmacovigilance-an insight

Drugs are the imperial part of modern society, but along with their therapeutic effects, drugs can also cause adverse effects, which can be mild to morbid. Pharmacovigilance is the process of collection, detection, assessment, monitoring and prevention of adverse drug events in both clinical trials as well as in the post-marketing phase. The recent trends in increasing unknown adverse events, known as signals, have raised the need to develop an ideal system for monitoring and detecting the potential signals timely. The process of signal management comprises of techniques to identify individual case safety reports systematically. Automated signal detection is highly based upon the data mining of the spontaneous reporting system such as reports from health care professional, observational studies, medical literature or from social media. If a signal is not managed properly, it can become an identical risk associated with the drug which can be hazardous for the patient safety and may have fatal outcomes which may impact health care system adversely. Once a signal is detected quantitatively, it can be further processed by the signal management team for the qualitative analysis and further evaluations. The main components of automated signal detection are data extraction, data acquisition, data selection, and data analysis and data evaluation. This system must be developed in the correct format and context, which eventually emphasizes the quality of data collected and leads to the optimal decision-making based upon the scientific evaluation.

Incidence, prevalence and prescription patterns of antipsychotic medications use in Asia and US: A cross-nation comparison with common data model

The use of antipsychotic medications (APMs) could be different among countries due to availability, approved indications, characteristics and clinical practice. However, there is limited literature providing comparisons of APMs use among countries. To examine trends in antipsychotic prescribing in Taiwan, Hong Kong, Japan, and the United States, we conducted a cross-national study from 2002 to 2014 b y using the distributed network approach with common data model. We included all patients who had at least a record of antipsychotic prescription in this study, and defined patients without previous exposure of antipsychotics for 6 months before the index date as new users for incidence estimation. We calculated the incidence, prevalence, and prescription rate of each medication by calendar year. Among older patients, sulpiride was the most incident [incidence rate (IR) 11.0-23.3) and prevalent [prevalence rate (PR) 11.9-14.3) APM in Taiwan, and most prevalent (PR 2.5-3.9) in Japan. Quetiapine and haloperidol were most common in the United States (IR 8.1-9.5; PR 18.0-18.4) and Hong Kong (PR 8.8-13.7; PR 10.6-12.7), respectively. The trend of quetiapine use was increasing in Taiwan, Hong Kong and the United States. As compared to older patients, the younger patients had more propensity to be prescribed second-generation APM for treatment in four countries. Trends in antipsychotic prescribing varied among countries. Quetiapine use was most prevalent in the United States and increasing in Taiwan and Hong Kong. The increasing use of quetiapine in the elderly patients might be due to its safety profile compared to other APMs.

Empowering knowledge generation through international data network: the IMeCCHI-DATANETWORK

Introduction

The International Methodology Consortium for Coded Health Information (IMeCCHI) is a collaboration of health services researchers who promote methodological advances in coded health information. The IMeCCHI-DATANETWORK initiative focuses on developing a multi-purpose distributed data infrastructure and common data model (CDM) to enable cross-border data sharing and international comparisons.

Methods

IMeCCHI consortium partners from six different countries – Canada, Denmark, Italy, New Zealand, South Korea, and Switzerland – used a questionnaire to describe their original databases which differ in size, structure, content and coding systems. To standardize these data, they agreed on a CDM and mapped their population-based databases to meet the CDM specifications. At the end of this process, local data had a more homogenous content and structure, which made them syntactically and semantically interoperable. Data transformation was performed using a common data management software called TheMatrix.

Results

The CDM encompasses four tables of structured data (person characteristics, hospitalizations, outpatient prescription medication and death), linked at the individual level through a person identifier. It can be used to answer research questions across countries using locally converted databases, which facilitates study replication in a distributed fashion. As a proof-of-concept study, an initial research question was addressed using an agreed protocol. Local data were transformed in csv files in the CDM structure and TheMatrix was tested to transform the standardized data from each partner into local analytical datasets. This allowed results to be shared between countries, whilst maintaining local control over each region’s data.

Conclusion

The IMeCCHI-DATANETWORK, a model of a distributed data network, demonstrated that it is feasible to analyze international data using standardized analytical methods that enable independent analyses by regions, without relocating datasets thereby protecting local confidentiality obligations. The distributed data infrastructure can produce results that can be generalized to several countries, while facilitating cross-border data sharing and international comparisons.

Keywords

Common data model, international comparison, cross-border data sharing, interoperability, observational data

Sequence symmetry analysis graphic adjustment for prescribing trends

BACKGROUND

Sequence symmetry analysis (SSA) is a signal detection method that can be used to assist with adverse drug event detection. It provides both a risk estimate and a data visualisation. Published methods provide results in the form of an adjusted sequence ratio, which adjusts for underlying market trends of medicine use, however no method for adjusting the visualisation is available. We aimed to develop and evaluate another method of adjustment for prescribing trends and apply it to the SSA visualisation.

METHODS

The SSA method relies on incident prescriptions for pairs of medicines of interest. Smoothing curves were fitted to the frequency distributions of incident medicine use. When divided and normalised, these curves yielded a set of proportions related to differences in prescribing trends over follow-up. These were then used to adjust the unit counts for incident prescriptions in the SAA visualisation and to calculate the sequence ratio. Curve fitting was also used to identify the proportional relationship between sequences over time for SSA and is presented as a supplementary visualisation to the SSA. We compared the sensitivity and specificity of our method with that from the SSA method of Tsiropolous et al. RESULTS: Curve-fit adjusted SSA visualisations yielded adjusted sequence ratios very close to those of Tsiropolous, with a p-value of 0.999 for the two sample Kolmogorov-Smirnov test. Results for sensitivity and specificity derived from adjusted sequence ratios were also practically the same. The curve-fit method graphically indicates the proportionality of the sequence and provides a useful supplement of net differences between the two sides of the SSA visualisation. Additionally, we found that incident prescriptions for patients common to both distributions are best precluded from adjustment calculations, leaving only incident prescriptions for patients unique to one or other distribution. This improved the accuracy of SSA in some atypical instances with negligible affect on accuracy elsewhere.

CONCLUSIONS

Our curve-fit method is equivalent to current methods in the literature for adjusting prescribing trends in SAA, with the advantage of providing adjustment incorporated in the SAA visualisation.

Taiwan's National Health Insurance Research Database: past and future

Taiwan's National Health Insurance Research Database (NHIRD) exemplifies a population-level data source for generating real-world evidence to support clinical decisions and health care policy-making. Like with all claims databases, there have been some validity concerns of studies using the NHIRD, such as the accuracy of diagnosis codes and issues around unmeasured confounders. Endeavors to validate diagnosed codes or to develop methodologic approaches to address unmeasured confounders have largely increased the reliability of NHIRD studies. Recently, Taiwan's Ministry of Health and Welfare (MOHW) established a Health and Welfare Data Center (HWDC), a data repository site that centralizes the NHIRD and about 70 other health-related databases for data management and analyses. To strengthen the protection of data privacy, investigators are required to conduct on-site analysis at an HWDC through remote connection to MOHW servers. Although the tight regulation of this on-site analysis has led to inconvenience for analysts and has increased time and costs required for research, the HWDC has created opportunities for enriched dimensions of study by linking across the NHIRD and other databases. In the near future, researchers will have greater opportunity to distill knowledge from the NHIRD linked to hospital-based electronic medical records databases containing unstructured patient-level information by using artificial intelligence techniques, including machine learning and natural language processes. We believe that NHIRD with multiple data sources could represent a powerful research engine with enriched dimensions and could serve as a guiding light for real-world evidence-based medicine in Taiwan.

Taiwan's National Health Insurance Research Database: past and future

Taiwan’s National Health Insurance Research Database (NHIRD) exemplifies a population-level data source for generating real-world evidence to support clinical decisions and health care policy-making. Like with all claims databases, there have been some validity concerns of studies using the NHIRD, such as the accuracy of diagnosis codes and issues around unmeasured confounders. Endeavors to validate diagnosed codes or to develop methodologic approaches to address unmeasured confounders have largely increased the reliability of NHIRD studies. Recently, Taiwan’s Ministry of Health and Welfare (MOHW) established a Health and Welfare Data Center (HWDC), a data repository site that centralizes the NHIRD and about 70 other health-related databases for data management and analyses. To strengthen the protection of data privacy, investigators are required to conduct on-site analysis at an HWDC through remote connection to MOHW servers. Although the tight regulation of this on-site analysis has led to inconvenience for analysts and has increased time and costs required for research, the HWDC has created opportunities for enriched dimensions of study by linking across the NHIRD and other databases. In the near future, researchers will have greater opportunity to distill knowledge from the NHIRD linked to hospital-based electronic medical records databases containing unstructured patient-level information by using artificial intelligence techniques, including machine learning and natural language processes. We believe that NHIRD with multiple data sources could represent a powerful research engine with enriched dimensions and could serve as a guiding light for real-world evidence-based medicine in Taiwan.

Effect estimate comparison between the prescription sequence symmetry analysis (PSSA) and parallel group study designs: A systematic review

Prescription sequence symmetry analysis (PSSA), a case-only design introduced in 1996, has been increasingly used to identify unintentional drug effects, and has potential applications as a hypothesis-testing and a hypothesis-generating method, due to its easy application and effective control of time-invariant confounders. The aim of this study is to systematically compare effect estimates from the PSSA to effect estimates from conventional observational parallel group study designs, to assess the validity and constraints of the PSSA study design. We reviewed the MEDLINE, EMBASE, and Web of Science databases until February 2016 to identify studies that compared PSSA to a parallel group design. Data from the eligible articles was extracted and analyzed, including making a Bland-Altman plot and calculating the number of discrepancies between the designs. 63 comparisons (from two studies) were included in the review. There was a significant correlation (p < 0.001) between the effect estimates of the PSSA and the parallel group designs, but the bias indicated by the Bland-Altman plot (0.20) and the percentage of discrepancies (70–80%) showed that this correlation was not accompanied by a considerable similarity of the effect estimates. Overall, the effect estimates of the parallel group designs were higher than those of the PSSA, not necessarily further away from 1, and the parallel group designs also generated more significant signals. However, these results should be approached with caution, as the effect estimates were only retrieved from two separate studies. This review indicates that, even though PSSA has a lot of potential, the effect estimates generated by the PSSA are usually lower than the effect estimates generated by parallel group designs, and PSSA mostly has a lower power than the conventional study designs, but this is based on limited comparisons, and more comparisons are needed to make a proper conclusion.

Lessons from meta-analyses of randomized clinical trials for analysis of distributed networks of observational databases

Networks of constellations of longitudinal observational databases, often electronic medical records or transactional insurance claims or both, are increasingly being used for studying the effects of medicinal products in real-world use. Such databases are frequently configured as distributed networks. That is, patient-level data are kept behind firewalls and not communicated outside of the data vendor other than in aggregate form. Instead, data are standardized across the network, and queries of the network are executed locally by data partners, and summary results provided to a central research partner(s) for amalgamation, aggregation, and summarization. Such networks can be huge covering years of data on upwards of 100 million patients. Examples of such networks include the FDA Sentinel Network, ASPEN, CNODES, and EU-ADR. As this is a new emerging field, we note in this paper the conceptual similarities and differences between the analysis of distributed networks and the now well-established field of meta-analysis of randomized clinical trials (RCTs). We recommend, wherever appropriate, to apply learnings from meta-analysis to help guide the development of distributed network analyses of longitudinal observational databases.

From Big Data to Smart Data for Pharmacovigilance: The Role of Healthcare Databases and Other Emerging Sources

In the last decade 'big data' has become a buzzword used in several industrial sectors, including but not limited to telephony, finance and healthcare. Despite its popularity, it is not always clear what big data refers to exactly. Big data has become a very popular topic in healthcare, where the term primarily refers to the vast and growing volumes of computerized medical information available in the form of electronic health records, administrative or health claims data, disease and drug monitoring registries and so on. This kind of data is generally collected routinely during administrative processes and clinical practice by different healthcare professionals: from doctors recording their patients' medical history, drug prescriptions or medical claims to pharmacists registering dispensed prescriptions. For a long time, this data accumulated without its value being fully recognized and leveraged. Today big data has an important place in healthcare, including in pharmacovigilance. The expanding role of big data in pharmacovigilance includes signal detection, substantiation and validation of drug or vaccine safety signals, and increasingly new sources of information such as social media are also being considered. The aim of the present paper is to discuss the uses of big data for drug safety post-marketing assessment.

Assessment of Medication Safety Using Only Dispensing Data

PURPOSE OF REVIEW

The purpose of this review is to provide an overview of the published studies that have been used to generate evidence on the safety of medicine use when only medication dispensing data are available.

RECENT FINDINGS

Medication dispensing databases are increasingly available for research on large populations, particularly in countries that provide universal coverage for medicines. These data are often used for drug utilisation studies to identify inappropriate medicine use at the population level that may be associated with known safety issues. Lack of coded diagnoses, to identify outcomes, and lack of data on confounders can limit use of these data in practice for medication safety assessment. To overcome these issues, studies have exploited the fact that symptoms of adverse effects of medications can be treated with other medications, for example antidepressants to treat depression or oxybutynin to treat urinary incontinence. The challenge of unmeasured confounding has been addressed by implementing self-controlled study designs that use within-person comparisons and provide inherent control for confounding. Prescription sequence symmetry analysis (SSA) is a within-person study design that has been demonstrated as a useful tool for safety signal generation in dispensing data.

SUMMARY

Using medicine initiation as a proxy for the development of adverse events can help to generate evidence of the safety of medicines when only medication dispensing data are available. Careful consideration, however, should be given to the sensitivity and specificity of the proxy medicine for the adverse event and potential for time-varying confounding due to trends in medicine utilisation. Data-mining approaches using dispensing data have the potential to improve safety assessments; however, the challenge of unmeasured confounding with these methods remains to be investigated.

Comparative safety of NSAIDs for gastrointestinal events in Asia-Pacific populations: A multi-database, international cohort study

PURPOSE

The safety of nonsteroidal anti-inflammatory drugs (NSAIDs) commonly used in Asia-Pacific countries has had limited study. We assessed the risk of hospitalization for gastrointestinal events with loxoprofen and mefenamic acid compared with other NSAIDs in Asia-Pacific populations.

METHODS

We conducted a cohort study using a distributed network with a common data model in Australia, Hong Kong, Japan, Korea, and Taiwan. We included patients who initiated diclofenac, loxoprofen, mefenamic acid, or celecoxib and followed them until their first gastrointestinal hospitalization, switch or discontinuation of medication, disenrollment, or end of database coverage. We used Cox proportional hazards models to assess hospitalization risk.

RESULTS

We identified 9879 patients in Japan, 70 492 in Taiwan, 263 741 in Korea, and 246 in Hong Kong who initiated an NSAID, and 44 013 patients in Australia, a predominantly Caucasian population. The incidence of gastrointestinal hospitalization was 25.6 per 1000 person-years in Japan, 32.8 in Taiwan, 11.5 in Korea, 484.5 in Hong Kong, and 35.6 in Australia. Compared with diclofenac, the risk of gastrointestinal events with loxoprofen was significantly lower in Korea (hazards ratio, 0.37; 95% CI, 0.25-0.54) but not in Japan (1.65; 95% CI, 0.47-5.78). The risk of gastrointestinal events with mefenamic acid was significantly lower in Taiwan (0.45; 95% CI, 0.26-0.78) and Korea (0.11; 95% CI, 0.05-0.27) but not Hong Kong (2.16; 95% CI, 0.28-16.87), compared with diclofenac.

CONCLUSIONS

Compared with diclofenac, loxoprofen was associated with a lower risk of gastrointestinal hospitalizations in Korea and mefenamic acid with a lower risk in Taiwan and Korea.

Applying a common data model to Asian databases for multinational pharmacoepidemiologic studies: opportunities and challenges

Objective

The goal of the Asian Pharmacoepidemiology Network is to study the effectiveness and safety of medications commonly used in Asia using databases from individual Asian countries. An efficient infrastructure to support multinational pharmacoepidemiologic studies is critical to this effort.

Study design and setting

We converted data from the Japan Medical Data Center database, Taiwan’s National Health Insurance Research Database, Hong Kong’s Clinical Data Analysis and Reporting System, South Korea’s Ajou University School of Medicine database, and the US Medicare 5% sample to the Observational Medical Outcome Partnership common data model (CDM).

Results

We completed and documented the process for the CDM conversion. The coordinating center and participating sites reviewed the documents and refined the conversions based on the comments. The time required to convert data to the CDM varied widely across sites and included conversion to standard terminology codes and refinements of the conversion based on reviews. We mapped 97.2%, 86.7%, 92.6%, and 80.1% of domestic drug codes from the USA, Taiwan, Hong Kong, and Korea to RxNorm, respectively. The mapping rate from Japanese domestic drug codes to RxNorm (70.7%) was lower than from other countries, and we mapped remaining unmapped drugs to Anatomical Therapeutic Chemical Classification System codes. Because the native databases used international procedure coding systems for which mapping tables have been established, we were able to map >90% of diagnosis and procedure codes to standard terminology codes.

Conclusion

The CDM established the foundation and reinforced collaboration for multinational pharmacoepidemiologic studies in Asia. Mapping of terminology codes was the greatest challenge, because of differences in health systems, cultures, and coding systems.

Antipsychotic polypharmacy in older Australians

ABSTRACTBackground:Antipsychotics are commonly used, and the rate of use is highest, among those aged 65 years or over, where the risk of adverse events is also high. Up to 20% of younger adults use more than one antipsychotic concurrently; however there are few studies on the prevalence of antipsychotic polypharmacy in older people. We aimed to analyze antipsychotic use in elderly Australians, focusing on the prevalence of antipsychotic polypharmacy and the use of medicines to manage adverse events associated with antipsychotics.

METHODS

A cross-sectional study was conducted using Australian Department of Veterans' Affairs (DVA) administrative claims data for the period 1 March 2014 to 30 June 2014. Veterans dispensed at least one antipsychotic medicine during the study period was included. We determined the number of participants dispensed antipsychotic polypharmacy and the number of participants dispensed medicines to manage antipsychotic side effects.

RESULTS

There were 7,412 participants with a median age of 86 years. Fifty-one percent (n=3,784) were women and 48% (n=3,569) lived in residential aged-care. Fifty one participants (0.7%) were dispensed anticholinergic medicines indicated for the management of antipsychotic-associated extrapyramidal movement disorders and eight (0.1%) were dispensed medicines for the management of hyperprolactinemia. Five percent of participants (n=365) received dual antipsychotics. Dual antipsychotic users were more likely to be under the care of a psychiatrist or to have had a mental health hospitalization than those using a single antipsychotic.

CONCLUSIONS

Antipsychotic polypharmacy occurred in one in 20 elderly persons, indicating that there is room for improvement in antipsychotic use in elderly patients.

Proton pump inhibitors and risk of Clostridium difficile infection: a multi-country study using sequence symmetry analysis

OBJECTIVE

To determine the association between incident proton pump inhibitor (PPI) use and Clostridium difficile infections across multiple countries Method: National data covering the total population in Australia and Korea, the Canadian population over 65 years and a 3 million person random sample data set from Taiwan were assessed, as were data from a worker insurance population and a hospital inpatient/outpatient population in Japan. Sequence symmetry analysis was used to assess the association with oral vancomycin dispensing as the outcome of interest.

RESULTS

54,957 patients were included. Positive associations were observed in Australia; adjusted sequence ratio (ASR) 2.48 (95% CI 1.90, 3.12), Korea ASR 2.15 (95%CI 2.11, 2.19), Canada ASR 1.45 (95% CI 1.16, 1.79), Japan hospital dataset ASR 3.21 (95%CI 2.12, 4.55) and Japan worker insurance dataset ASR 5.40 (95% CI 2.73, 8.75). The pooled result was ASR 2.40 (95%CI 1.88, 3.05) and 3.16 (95%CI 1.95, 5.10) when limited to Japan, Korean and Taiwan. Results did not vary by individual PPI. The temporal analysis showed effects within the first two weeks of PPI initiation.

CONCLUSION

Our study confirms the association between PPI initiation and C. difficile infections across countries in the Asia-Pacific region.

Impact on Drug Safety of Variation in Adherence: The Need for Routinely Reporting Measures of Dose Intensity in Medication Safety Studies Using Electronic Health Data

Randomized controlled trials always report the dose assessed and usually include a measure of adherence. By comparison, observational studies assessing medication safety often fail to report the dose used and rarely report any measure of adherence to therapy. This limits the ability to control for differences in doses used when undertaking meta-analyses. Non-adherence with therapy is common in the practice setting and varies across countries and settings. Inter-country differences in the registration of medicines may also result in different product strengths being available in different countries. These two factors combined means that observational studies undertaken for the same medicine in different settings may be assessing the same medicine but in circumstances where quite different dosages are used. Given that many adverse drug effects are dose dependent, differences in dosages used could be a factor explaining differences in risk estimates observed across studies. We argue that dose intensity, which can be defined as a product of the dose prescribed and adherence to the dose prescribed over the course of treatment, should be routinely reported in observational studies of medication safety. We illustrate the issue with the example of dabigatran. The randomized controlled trial evidence underpinning dabigatran’s marketing authorization resulted in uncertainty about the appropriate dose for efficacy versus safety. As a result, different dosages of dabigatran were registered in the USA and Europe. The USA registered the 150- and 75-mg dabigatran products, while the 150- and 110-mg dabigatran products were registered in Europe. Among five observational studies subsequently undertaken to resolve the safety question concerning dabigatran and risk of bleeding, only one stratified results by dose. None of the US studies stratified results by the 75-mg dabigatran dose, despite this dose not being assessed in the original trial. None of the five studies reported adherence measures, despite three separate observational studies finding between 25 and 40 % of patients were non-adherent to dabigatran. The STROBE and RECORD statements should consider adding the requirement for reporting measures of dose intensity and its component products to improve observational study reports.

'Big data' in mental health research: current status and emerging possibilities

PURPOSE

'Big data' are accumulating in a multitude of domains and offer novel opportunities for research. The role of these resources in mental health investigations remains relatively unexplored, although a number of datasets are in use and supporting a range of projects. We sought to review big data resources and their use in mental health research to characterise applications to date and consider directions for innovation in future.

METHODS

A narrative review.

RESULTS

Clear disparities were evident in geographic regions covered and in the disorders and interventions receiving most attention.

DISCUSSION

We discuss the strengths and weaknesses of the use of different types of data and the challenges of big data in general. Current research output from big data is still predominantly determined by the information and resources available and there is a need to reverse the situation so that big data platforms are more driven by the needs of clinical services and service users.

Variation in Association Between Thiazolidinediones and Heart Failure Across Ethnic Groups: Retrospective analysis of Large Healthcare Claims Databases in Six Countries

INTRODUCTION

The prevalence of polymorphisms among the metabolising enzymes and pharmacodynamic receptors relevant for the thiazolidinediones differs by ethnic group, a factor that may modify risk of adverse drug events.

OBJECTIVE

The aim of the study was to determine if the risk of oedema or heart failure associated with the thiazolidinediones varies in populations in Australia, Canada, Hong Kong, Japan, Korea and Taiwan.

METHODS

Sequence symmetry analyses were undertaken to investigate the risk of peripheral oedema, as measured by incident furosemide dispensing, and risk of hospitalisations for heart failure. Results were pooled, with Australia and Canada representing predominantly Caucasian population and all other countries contributing to Asian population estimates.

RESULTS

Pooled estimates of risk for furosemide initiation in the Caucasian populations were significantly increased for pioglitazone [adjusted sequence ratio (ASR) 1.47; 95 % confidence interval (CI) 1.14-1.91] and rosiglitazone (ASR 1.65; 95 % CI 1.58-1.72), while in the Asian populations, the pooled risk estimates were lower (ASR 1.11; 95 % CI 0.93-1.32 and ASR 1.21; 95 % CI 1.01-1.45 for pioglitazone and rosiglitazone, respectively). Results for hospitalisation for heart failure showed a similar trend, with elevated risk in the Australian data (ASR 1.88; 95 % CI 1.01-3.5 and ASR 1.25; 95 % CI 0.76-2.05 for pioglitazone and rosiglitazone, respectively), while no increased risk was found in the pooled results for the Asian populations.

CONCLUSION

The risk of both oedema and heart failure with thiazolidinediones was higher in predominantly Caucasian countries than in the Asian countries assessed. Assessment of adverse events by ethnicity may support safer medicine use.

Prescription sequence symmetry analysis: assessing risk, temporality, and consistency for adverse drug reactions across datasets in five countries

Background

Prescription sequence symmetry analysis (PSSA) is a signal detection method for adverse drug events. Its capacity to consistently detect adverse drug events across different settings has not been tested. We aimed to determine the consistency of PSSA results for detecting positive and negative control adverse drug events across different settings.

Methods

Using a distributed network model, we analyzed prescription dispensing data using PSSA in Australia, Hong Kong, Japan, Korea, and Taiwan. Positive control was amiodarone and thyroxine, as a marker of amiodarone-induced hypothyroidism, a known adverse event with a clear temporal relationship to amiodarone initiation. Negative controls were amiodarone and allopurinol, as a marker of amiodarone-induced gout and thyroxine and allopurinol, as a marker of thyroxine-induced gout. Gout is not recorded as an adverse event in product information for either medicine. Adjusted sequence ratios (ASR) were calculated for each country. Pooled estimates were obtained by using the generic inverse variance method.

Results

A positive association was identified between amiodarone and thyroxine in all settings with a pooled ASR 2.63 (95% confidence interval (CI) 1.47–4.72). Temporal analysis showed the effect occurred within the first few weeks of treatment. No significant associations were found for the negative controls in any setting; pooled ASR were 0.76 (95%CI 0.62–0.93) and 0.98 (95%CI 0.85–1.12) for amiodarone-allopurinol and thyroxine-allopurinol, respectively.

Conclusion

Despite different health settings, different populations, and different patterns of medicine utilization, PSSA gave consistent estimates across countries for a well-known positive association and two negative control adverse events. © 2015 The Authors Pharmacoepidemiology and Drug Safety Published by John Wiley & Sons Ltd.

A comparison of active adverse event surveillance systems worldwide

Post-marketing drug surveillance for adverse drug events (ADEs) has typically relied on spontaneous reporting. Recently, regulatory agencies have turned their attention to more preemptive approaches that use existing data for surveillance. We conducted an environmental scan to identify active surveillance systems worldwide that use existing data for the detection of ADEs. We extracted data about the systems' structures, data, and functions. We synthesized the information across systems to identify common features of these systems. We identified nine active surveillance systems. Two systems are US based-the FDA Sentinel Initiative (including both the Mini-Sentinel Initiative and the Federal Partner Collaboration) and the Vaccine Safety Datalink (VSD); two are Canadian-the Canadian Network for Observational Drug Effect Studies (CNODES) and the Vaccine and Immunization Surveillance in Ontario (VISION); and two are European-the Exploring and Understanding Adverse Drug Reactions by Integrative Mining of Clinical Records and Biomedical Knowledge (EU-ADR) Alliance and the Vaccine Adverse Event Surveillance and Communication (VAESCO). Additionally, there is the Asian Pharmacoepidemiology Network (AsPEN) and the Shanghai Drug Monitoring and Evaluative System (SDMES). We identified two systems in the UK-the Vigilance and Risk Management of Medicines (VRMM) Division and the Drug Safety Research Unit (DSRU), an independent academic unit. These surveillance systems mostly use administrative claims or electronic medical records; most conduct pharmacovigilance on behalf of a regulatory agency. Either a common data model or a centralized model is used to access existing data. The systems have been built using national data alone or via partnership with other countries. However, active surveillance systems using existing data remain rare. North America and Europe have the most population coverage; with Asian countries making good advances.

Studies using Australia's Pharmaceutical Benefits Scheme data for pharmacoepidemiological research: a systematic review of the published literature (1987-2013)

PURPOSE

Research using dispensing claims is used increasingly to study post-market medicines use and outcomes. The purpose of this review is to catalogue more than 25 years of published literature using Australia's Pharmaceutical Benefits Scheme (PBS) dispensing records.

METHODS

We searched MEDLINE, PreMEDLINE and Embase and conducted author searches for studies published from 1987 to 2013. Independent reviewers screened abstracts of 3209 articles and reviewed 264 full-text manuscripts. Included studies used PBS dispensing data to measure patterns and/or outcomes of prescribed medicines use or dispensing claims to derive a proxy for a specific disease cohort or health outcome.

RESULTS

Of the 228 studies identified, 106 used PBS claims only (56 using claims-level data and 50 using individual-level data) and 63 studies linked individual-level PBS claims to other health data. Most commonly, studies examined trends in drug utilisation (33%), clinician and patient practices (26%), drug use and outcomes (18%) and evaluations of intervention impacts (17%). Sixty-two percent of studies using individual-level data were based on a subset of elderly Australians. Most studies focused on drug classes acting on the nervous system (36%), cardiovascular system (15%) and alimentary tract (11%). Few studies examined prescribed medicines use in children and pregnant women.

CONCLUSIONS

Pharmaceutical Benefits Scheme claims represent a significant resource to examine Australia's billion-dollar annual investment in prescribed medicines. The body of research is growing and has increased in complexity over time. Australia has great potential to undertake world-class, whole-of-population pharmacoepidemiological studies. Recent investment in data linkage infrastructure will significantly enhance these opportunities.

Prescription patterns of psychotropic medications for the treatment of psychotic disorders in the largest mental health institutions of Uganda

The study describes prescription patterns of psychotropic medications for patients treated for psychosis in psychiatric hospitals of Uganda. A cross-sectional quantitative survey of age, sex, diagnoses, and psychotropic medication of 682 psychiatric inpatients of the 2 national referral hospitals in Uganda was conducted on 1 day in March 2012. The percentage of patients treated with the same substance within the diagnostic categories schizophrenia, bipolar affective disorder, unspecified psychosis, and depressive disorder was calculated. Close to 90% of the patients with conditions diagnosed with any psychotic disorder were treated with first-generation antipsychotic drugs (eg, chlorpromazine, haloperidol, trifluoperazine, and depot fluphenazine). Carbamazepine in combination with first-generation antipsychotics was prescribed frequently (45%) for the treatment of bipolar affective disorder. The use of second-generation antipsychotics, lithium, and valproic acid was exceptional. Patients with depression usually received a combination (63%) of first-generation antipsychotics and antidepressants (fluoxetine or amitriptyline). Benzodiazepines were only infrequently used for patients diagnosed with psychoses. First-generation antipsychotics, antidepressants, and carbamazepine were the most frequently used medications for treatment of psychosis in Uganda. Although lithium and valproic acid were on the essential drug list in Uganda, their use was still infrequent. There is a need to ensure the practical availability of the drugs listed on the essential drug list and to support the implementation of their use in clinical practice.

Olanzapine in Chinese patients with schizophrenia or bipolar disorder: a systematic literature review

BACKGROUND

Despite the burden of schizophrenia and bipolar disorder in the Chinese population, country-specific data to guide practitioners regarding antipsychotic therapy are lacking. The primary aim of this systematic review was to examine evidence of the efficacy, effectiveness, and safety of olanzapine in Chinese populations.

METHODS

A systematic literature search was conducted using databases covering international and Chinese core journals using search terms related to schizophrenia and bipolar disorder, specified countries (People's Republic of China, Hong Kong, Taiwan), and olanzapine treatment. Following initial screening, inclusion and exclusion criteria were applied to the search results to identify relevant studies from which data were extracted.

RESULTS

A total of 489 publications were retrieved and 61 studies were identified for inclusion. Most studies were related to schizophrenia (n=54), with six studies related to bipolar disorder and one study related to both conditions. The quality of study methods and reporting in international journals was noticeably better than in Chinese language journals. Most studies included relatively small patient populations and were of short duration. The efficacy of olanzapine in Chinese populations was confirmed by multiple comparative and noncomparative studies that found statistically significant reductions in symptom measures in studies conducted for ≥6 weeks (schizophrenia) or ≥3 weeks (bipolar disorder). Findings related to effectiveness (treatment discontinuation, quality of life, and neurocognitive improvements) were generally consistent with those observed in non-Chinese populations. No new safety signals specific for Chinese populations were raised for olanzapine.

CONCLUSION

Chinese and non-Chinese populations with schizophrenia or bipolar disorder treated with olanzapine display broadly similar responses. Differences between these populations, especially in relation to the relative efficacy of olanzapine versus other antipsychotics, may warrant further investigation via studies incorporating both populations. Use of local data to provide evidence for practice guidelines should be encouraged, and may promote ongoing improvements in the quality of research and study reporting.

The performance of sequence symmetry analysis as a tool for post-market surveillance of newly marketed medicines: a simulation study

Background

Sequence symmetry analysis (SSA) is a potential tool for rapid detection of adverse drug events (ADRs) associated with newly marketed medicines utilizing computerized claims data. SSA is robust to patient specific confounders but it is sensitive to the underlying utilization trends in the medicines of interest. Methods to adjust for utilisation trends have been developed, however, there has been no systematic investigation to assess the performance of SSA when variable prescribing trends occur. The objective of this study was to evaluate the validity of SSA as a signal detection tool for newly marketed medicines.

Methods

Randomly simulated prescription supplies for a population of 1 million were generated for two medicines, DrugA (medicine of interest) and DrugB (medicine indicative of an adverse event). Scenarios were created by varying medicine utilization trends for a newly marketed medicine (DrugA). In addition, the magnitude of association between DrugA and DrugB was varied. For each scenario 1000 simulations were generated. Average Adjusted Sequence Ratios (ASR), bootstrapped 95% confidence intervals (CIs), percentage of CI's which covered the expected ASR and percent relative bias were calculated.

Results

When no association was simulated between DrugA and DrugB, over 95% of SSA CI's covered the expected ASR (ASR = 1) and relative bias was 1% or less irrespective of medicine utilization trends. In scenarios where DrugA and DrugB were associated (ASR = 2), unadjusted SR's were underestimated by between 11.7 and 15.3%. After adjustment for trend, ASR estimates were close to expected with relative bias less than 1%. Power was over 80% in all scenarios except for one scenario in which medicine uptake was gradual and the effect of interest was weak (ASR = 1.2).

Conclusions

Adjustment for underlying medicine utilization patterns effectively overcomes potential under-ascertainment bias in SSA analyses. SSA may be effectively applied as a safety signal detection tool for newly marketed medicines where sufficiently large health claim data are available.