Evaluation of the Regulatory Required Post-Authorization Safety Study for Propacetamol: Nested Case-Control and Case-Time-Control Studies

PURPOSE

Following the withdrawal of propacetamol in Europe owing to safety issues, the regulatory authority of South Korea requested a post-marketing surveillance study to investigate its safety profile.

MATERIALS AND METHODS

We conducted nested case-control and case-time-control (CTC) analyses of cases and controls identified for outcomes of interest, including anaphylaxis, thrombosis, and Stevens-Johnson syndrome (SJS), using the claims database of South Korea, 2010-2019. Risk-set sampling was used to match each case with up to 10 controls for age, sex, cohort entry date, and follow-up duration. Exposure to anaphylaxis, thrombosis, and SJS was assessed within 7, 90, and 30 days of the index date, respectively. We calculated odds ratios (OR) with 95% confidence intervals (CIs) using conditional logistic regression to assess the risk of outcomes associated with propacetamol.

RESULTS

We identified cases of anaphylaxis (n=61), thrombosis (n=95), and SJS (n=1) and matched them to controls (173, 268, and 4, respectively). In the nested case-control analysis, the ORs for anaphylaxis and SJS were inestimable given the small number of propacetamol users during the risk period; meanwhile, the OR for thrombosis was 1.60 (95% CI 0.71-3.62). In the CTC design, the effect estimate was only estimated for thrombosis (OR 0.56, 95% CI 0.09-3.47).

CONCLUSION

In both nested case-control and CTC analyses, propacetamol was not associated with an increased risk of anaphylaxis, thrombosis, or SJS. The findings from this study, which used routinely collected clinical data, provide reassuring real-world evidence regarding the safety of propacetamol in a nationwide population to support regulatory decision-making.

Antibiotic-Associated Acute Kidney Injury Among Older Adults: A Case-Crossover Study

BACKGROUND AND OBJECTIVES

Drug-related acute kidney injury is quite common in older adults. The associated drugs, including antibiotics, are often co-prescribed. The objective of this study was to ascertain antibiotic-associated acute kidney injury (AKI) in older adults aged 65 years or above in New Zealand using a case-crossover study design.

METHODS

The International Statistical Classification of Diseases and Related Health Problems, tenth revision, Australian modification code N17.x was used to identify all individuals aged 65 years and above with a diagnosis of incident AKI on admission between 1 January 2005 and 31 December 2020, from the New Zealand National Minimum Data Set. A case-crossover cohort for antibiotic exposures, with a 3 day case period and two 30 day washout periods, summed up to a 66 day study period, was created. Using conditional logistic regression, the changed odds of AKI due to exposure to an antibiotic was calculated as matched odds ratios and their 95% confidence intervals.

RESULTS

A total of 2399 incident cases of AKI were identified between 2005 and 2020 among older adults. The adjusted odds of consuming sulfamethoxazole/trimethoprim antibiotic during the case period was 3.57 times (95% CI 2.86-4.46) higher than the reference period among the incident AKI cases. Fluoroquinolone utilization was also associated with incident AKI (adjusted OR = 2.56; 95% CI 1.90-3.46).

CONCLUSION

The potential of sulfamethoxazole/trimethoprim and fluoroquinolones to be associated with AKI raises the significant need for vigilant prescribing of these antibiotics in older adults.

Bias Due to Within-Subject Exposure Dependency With or Without Bias Due to Lack of Pairwise Exchangeability When Exposure Is Chronic in Case-Crossover and Case-Time-Control Studies: A Simulation Study

The case-crossover study design has been proposed as a suitable design for use when a brief exposure causes a transient change in risk of an acute-onset disease. In pharmacoepidemiology, the condition of "brief exposure" is rarely satisfied because medication use is often chronic or successive, which may result in bias due to within-subject exposure dependency. Here we describe a simulation of a case-crossover study conducted within a cohort, where patients successively used a drug for 60 or more days and the rate ratio for the outcome occurrence was 4.0. Standard conditional logistic regression for the analysis produced overestimated odds ratios ranging up to 7.8. This bias due to within-subject exposure dependency from chronic use can be removed by the Mantel-Haenszel method or by our recently proposed weighting method. We also show that when some patients are censored after switching to another drug, a lack of pairwise exchangeability causes bias which is similar to bias due to an exposure time trend. This bias can be removed by using the case-time-control study design. We show that bias due to within-subject exposure dependency and lack of pairwise exchangeability occur independently and can occur separately or simultaneously, and we demonstrate how to detect and remove them.

Evaluating the use of methods to mitigate bias from non-transient medications in the case-crossover design: A systematic review

PURPOSE

The case-crossover design is a self-controlled study design used to compare exposure immediately preceding an event occurrence with exposure in earlier control periods. The design is most suitable for transient exposures in order to avoid biases that can be problematic when using the case-crossover design for non-transient (i.e., chronic) exposures. Our goal was to conduct a systematic review of case-crossover studies and its variants (case-time-control and case-case-time-control) in order to compare design and analysis choices by medication type.

METHODS

We conducted a systematic search to identify recent case-crossover, case-time-control, and case-case-time-control studies focused on medication exposures. Articles indexed in MEDLINE and EMBASE using these study designs that were published between January 2015 and December 2021 in the English language were identified. Reviews, methodological studies, commentaries, articles without medications as the exposure of interest, and articles with no available full text were excluded. Study characteristics including study design, outcome, risk window, control window, reporting of discordant pairs, and inclusion of sensitivity analyses were summarized overall and by medication type. We further evaluated the implementation of recommended methods to account for biases introduced by non-transient exposures among articles that used the case-crossover design on a non-transient exposure.

RESULTS

Of the 2036 articles initially identified, 114 articles were included. The case-crossover was the most common study design (88%), followed by the case-time-control (17%), and case-case-time-control (3%). Fifty-three percent of the articles included only transient medications, 35% included only non-transient medications, and 12% included both. Across years, the proportion of case-crossover articles evaluating a non-transient medication ranged from 30% in 2018 to 69% in 2017. We found that 41% of the articles that evaluated a non-transient medication did not apply any of the recommended methods to account for biases and more than half of which were conducted by authors with no previous publication history of case-crossover studies.

CONCLUSION

Using the case-crossover design to evaluate a non-transient medication remains common in pharmacoepidemiology. Researchers should apply appropriate design and analysis choices when opting to use a case-crossover design with non-transient medication exposures.

Capturing the variety of clinical pathways in patients with schizophrenic disorders through state sequences analysis

BACKGROUND

Care pathways are increasingly being used to enhance the quality of care and optimize the use of resources for health care. Nevertheless, recommendations regarding the sequence of care are mostly based on consensus-based decisions as there is a lack of evidence on effective treatment sequences. In a real-world setting, classical statistical tools were insufficient to consider a phenomenon with such high variability adequately and have to be integrated with novel data mining techniques suitable for identifying patterns in complex data structures. Data-driven techniques can potentially support empirically identifying effective care sequences by extracting them from data collected routinely. The purpose of this study is to perform a state sequence analysis (SSA) to identify different patterns of treatment and to asses whether sequence analysis may be a useful tool for profiling patients according to the treatment pattern.

METHODS

The clinical application that motivated the study of this method concerns the mental health field. In fact, the care pathways of patients affected by severe mental disorders often do not correspond to the standards required by the guidelines in this field. In particular, we analyzed patients with schizophrenic disorders (i.e., schizophrenia, schizotypal or delusional disorders) using administrative data from 2015 to 2018 from Lombardy Region. This methodology considers the patient's therapeutic path as a conceptual unit, composed of a succession of different states, and we show how SSA can be used to describe longitudinal patient status.

RESULTS

We define the states to be the weekly coverage of different treatments (psychiatric visits, psychosocial interventions, and anti-psychotic drugs), and we use the longest common subsequences (dis)similarity measure to compare and cluster the sequences. We obtained three different clusters with very different patterns of treatments.

CONCLUSIONS

This kind of information, such as common patterns of care that allowed us to risk profile patients, can provide health policymakers an opportunity to plan optimum and individualized patient care by allocating appropriate resources, analyzing trends in the health status of a population, and finding the risk factors that can be leveraged to prevent the decline of mental health status at the population level.

Association between the Use of Suvorexant and Hip Fracture in Older Adults in Japan Using a Nationwide Administrative Claims Database: A Matched Case-Control Study

BACKGROUND AND OBJECTIVE

The use of benzodiazepines and nonbenzodiazepines increases the risk for hip fracture, but the effect of suvorexant, an orexin receptor antagonist, is not clear. The objective of this study was to investigate the association between suvorexant use and hip fractures in older adults.

METHODS

A case-control study was conducted using real-world data (RWD) from Medical Data Vision Co., Ltd. with patients hospitalized between January 2019 and December 2020. Patients were aged 65-84 years and had been prescribed suvorexant at least once. Patients with hip fracture (cases) and those without (controls) were identified by matching up to 1:4 for sex, age (± 2 years), and hospital size category. Suvorexant exposure was identified the day before hospitalization. Hip fracture risk associated with suvorexant was presented as adjusted odds ratios (aOR) with 95% confidence intervals (CI) using conditional logistic regression analysis.

RESULTS

Matching identified 389 cases and 1509 controls. The risk of hip fracture was not increased in patients treated with suvorexant [aOR: 0.86, 95% confidence interval (CI) 0.61-1.20]. Additionally, concomitant use of suvorexant with other hypnotics did not increase the risk. Benzodiazepines (1.01, 0.46-2.22), nonbenzodiazepines (1.16, 0.57-2.34), and melatonin (1.80, 0.82-3.94) were combined with suvorexant. The risk was increased for the use of benzodiazepine without suvorexant (1.88, 1.10-3.21).

CONCLUSIONS

Using RWD in Japanese older adults, we showed that sleep therapy with suvorexant was not associated with an increased risk of hip fracture. The results provide evidence-based drug safety information for the selection of hypnotics for sleep disorders, which increase with age.

Immeasurable Time Bias in Self-controlled Designs: Case-crossover, Case-time-control, and Case-case-time-control Analyses

BACKGROUND

Impact of immeasurable time bias (IMTB) is yet to be examined in self-controlled designs.

METHODS

We conducted case-crossover, case-time-control, and case-case-time-control analyses using Korea's healthcare database. Two empirical examples among elderly patients were used: 1) benzodiazepines-hip fracture; 2) benzodiazepines-mortality. For cases, the date of hip fracture diagnosis or death was defined as the index date, and the inherited date of their matched cases for controls or future cases. Exposure was assessed in the 1-30 day (hazard) and 61-90 day (control) windows preceding the index date. A non-missing exposure setting included in- and outpatient prescriptions and the pseudo-outpatient setting included only the outpatients. Conditional logistic regression was done to estimate odds ratios (ORs) with 95% confidence intervals (CIs), where the relative difference in OR among the two settings was calculated to quantify the IMTB.

RESULTS

The IMTB had negligible impacts in the hip fracture example in the case-crossover (non-missing exposure setting OR 1.27; 95% CI, 1.12-1.44; pseudo-outpatient setting OR 1.21; 95% CI, 1.06-1.39; magnitude 0.05), case-time-control (OR 1.18; 95% CI, 0.98-1.44; OR 1.13; 95% CI, 0.92-1.38; 0.04, respectively), and case-case-time-control analyses (OR 0.99; 95% CI, 0.80-1.23; OR 0.94; 95% CI, 0.75-1.18; 0.05, respectively). In the mortality example, IMTB had significant impacts in the case-crossover (non-missing exposure setting OR 1.44; 95% CI, 1.36-1.52; pseudo-outpatient setting OR 0.72; 95% CI, 0.67-0.78; magnitude 1.00), case-time-control (OR 1.38; 95% CI, 1.26-1.51; OR 0.68; 95% CI, 0.61-0.76; 1.03, respectively), and case-case-time-control analyses (OR 1.27; 95% CI, 1.15-1.40; OR 0.62; 95% CI, 0.55-0.69; 1.05, respectively).

CONCLUSION

Although IMTB had negligible impacts on the drug's effect on acute events, as these are unlikely to be accompanied with hospitalizations, it negatively biased the drug's effect on mortality, an outcome with prodromal phases, in the three self-controlled designs.

Risk of parkinsonism and related movement disorders with gabapentinoids or tramadol: A case-crossover study

INTRODUCTION

A safety signal concerning parkinsonism and related movement disorders with gabapentinoids (gabapentin and pregabalin) or tramadol was detected by reviewing individual case reports and data mining in spontaneous report databases. Well-designed pharmacoepidemiological studies are needed to assess the signal.

OBJECTIVE

This study aimed to investigate the association of exposure to gabapentinoids or tramadol with the risk of parkinsonism and related movement disorders.

METHODS

We conducted a case-crossover study using a Japanese electronic medical records database. Patients with newly diagnosed parkinsonism or related movement disorders between January 1, 2007, and April 14, 2019, were identified. The diagnosis date of outcomes was defined as the index date. We assessed the exposure of each patient to gabapentinoids or tramadol during a 90-day hazard period ending 1 day before the index date and in three 90-day reference periods. Multivariable conditional logistic regression models were employed to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs). To confirm the robustness of the primary findings, we also performed sensitivity analyses using a case-case-time-control design, a different time window for hazard and reference periods, a different definition of outcome, and different number of reference periods.

RESULTS

A total of 28,972 eligible cases were included in the primary analysis. Exposure to gabapentinoids (aOR, 2.12; 95% CI, 1.73-2.61) and tramadol (aOR, 2.04; 95% CI, 1.57-2.64) was associated with increased risk. Results were consistent across sensitivity analyses.

CONCLUSION

Our findings serve as a caution to physicians who prescribe gabapentinoids or tramadol in routine clinical practice.

Recent tapering from long-term opioid therapy and odds of opioid-related hospital use

PURPOSE

The number of patients tapered from long-term opioid therapy (LTOT) has increased in recent years in the United States. Some patients tapered from LTOT report improved quality of life, while others face increased risks of opioid-related hospital use. Research has not yet established how the risk of opioid-related hospital use changes across LTOT dose and subsequent tapering. Our objective was to examine associations between recent tapering from LTOT with odds of opioid-related hospital use.

METHODS

Case-crossover design using 2014-2018 health information exchange data from Indiana. We defined opioid-related hospital use as hospitalizations, and emergency department (ED) visits for a drug overdose, opioid abuse, and dependence. We defined tapering as a 15% or greater dose reduction following at least 3 months of continuous opioid therapy of 50 morphine milligram equivalents (MME)/day or more. We used conditional logistic regression to estimate odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

Recent tapering from LTOT was associated with increased odds of opioid-related hospital use (OR: 1.50, 95%CI: 1.34-1.63), ED visit (OR: 1.52; 95%CI: 1.35-1.72), and inpatient hospitalization (OR: 1.40; 95%CI: 1.20-1.65). We found no evidence of heterogeneity of the effect of tapering on opioid-related hospital use by gender, age, and race. Recent tapering among patients on a high baseline dose (>300 MME) was associated with increased odds of opioid-related hospital use (OR: 2.95, 95% CI: 2.12-4.11, p < 0.001) compared to patients on a lower baseline doses.

CONCLUSIONS

Recent tapering from LTOT is associated with increased odds of opioid-related hospital use.

Oral Janus kinase inhibitors and venous thromboembolic events in atopic dermatitis: protocols for a case-time control study and a nested case-control study based on the French national health insurance (SNDS) cohort

INTRODUCTION

Atopic dermatitis (AD) is a highly prevalent, chronic, inflammatory skin disease. Several orally administered Janus kinase inhibitors (JAKis, including baricitinib, upadacitinib and abrocitinib) have received a marketing authorisation for AD.Clinical trials in rheumatoid arthritis (RA) have flagged up a potential risk of JAKi-induced venous thromboembolic events (VTEs). Accordingly, the summary of product characteristics for a JAKi must mention VTEs as potential adverse drug reactions. In contrast to RA, AD per se is not associated with an elevated risk of VTEs. Assessing this potential risk among patients with AD would shed further light on the putative underlying relationship between JAKis and VTEs.Our research question is to investigate whether JAKi administration increases the risk of VTEs in adults with AD. Our primary objective is to assess the risk of VTEs in adults with AD exposed to JAKis compared to AD adults not exposed to JAKis, and our secondary objective is to evaluate whether JAKi initiation acts as a trigger of VTEs in adults with AD within 3 months.

METHODS AND ANALYSIS

Hence, we have designed (1) a nested case-control study and (2) a case-time control study in a cohort of adults with AD with data from the French national health insurance system (2017-2025).Here, we describe the study protocol, our methodological choices and certain novel aspects, including the combined value of the two assumptions and the use of an exhaustive national health insurance database with potentially greater statistical power for studying rare events in the population of patients with AD at a low risk of VTEs (thus limiting the influence of confounding factors).

ETHICS AND DISSEMINATION

The protocol has been approved by an independent ethics committee and registered with the French National Data Protection Commission. The study's findings will be published in peer-reviewed scientific journals and presented at international conferences.

Clinical epidemiology and pharmacoepidemiology studies with real-world databases

Hospital-based registry data, including patients' information collected by academic societies or government based research groups, were previously used for clinical research in Japan. Now, real-world data routinely obtained in healthcare settings are being used in clinical epidemiology and pharmacoepidemiology. Real-world data include a database of claims originating from health insurance associations for reimbursement of medical fees, diagnosis procedure combinations databases for acute inpatient care in hospitals, a drug prescription database, and electronic medical records, including patients' medical information obtained by doctors, derived from electronic records of hospitals. In the past ten years, much evidence of clinical epidemiology and pharmacoepidemiology studies using real-world data has been accumulated. The purpose of this review was to introduce clinical epidemiology and pharmacoepidemiology approaches and studies using real-world data in Japan.

Use of State Sequence Analysis in Pharmacoepidemiology: A Tutorial

While state sequence analysis (SSA) has been long used in social sciences, its use in pharmacoepidemiology is still in its infancy. Indeed, this technique is relatively easy to use, and its intrinsic visual nature may help investigators to untangle the latent information within prescription data, facilitating the individuation of specific patterns and possible inappropriate use of medications. In this paper, we provide an educational primer of the most important learning concepts and methods of SSA, including measurement of dissimilarities between sequences, the application of clustering methods to identify sequence patterns, the use of complexity measures for sequence patterns, the graphical visualization of sequences, and the use of SSA in predictive models. As a worked example, we present an application of SSA to opioid prescription patterns in patients with non-cancer pain, using real-world data from Italy. We show how SSA allows the identification of patterns in prescriptions in these data that might not be evident using standard statistical approaches and how these patterns are associated with future discontinuation of opioid therapy.

A novel weighting method to remove bias from within-subject exposure dependency in case-crossover studies

BACKGROUND

Case-crossover studies have been widely used in various fields including pharmacoepidemiology. Vines and Farrington indicated in 2001 that when within-subject exposure dependency exists, conditional logistic regression can be biased. However, this bias has not been well studied.

METHODS

We have extended findings by Vines and Farrington to develop a weighting method for the case-crossover study which removes bias from within-subject exposure dependency. Our method calculates the exposure probability at the case period in the case-crossover study which is used to weight the likelihood formulae presented by Greenland in 1999. We simulated data for the population with a disease where most patients receive a cyclic treatment pattern with within-subject exposure dependency but no time trends while some patients stop and start treatment. Finally, the method was applied to real-world data from Japan to study the association between celecoxib and peripheral edema and to study the association between selective serotonin reuptake inhibitor (SSRI) and hip fracture in Australia.

RESULTS

When the simulated rate ratio of the outcome was 4.0 in a case-crossover study with no time-varying confounder, the proposed weighting method and the Mantel-Haenszel odds ratio reproduced the true rate ratio. When a time-varying confounder existed, the Mantel-Haenszel method was biased but the weighting method was not. When more than one control period was used, standard conditional logistic regression was biased either with or without time-varying confounding and the bias increased (up to 8.7) when the study period was extended. In real-world analysis with a binary exposure variable in Japan and Australia, the point estimate of the odds ratio (around 2.5 for the association between celecoxib and peripheral edema and around 1.6 between SSRI and hip fracture) by our weighting method was equal to the Mantel-Haenszel odds ratio and stable compared with standard conditional logistic regression.

CONCLUSION

Case-crossover studies may be biased from within-subject exposure dependency, even without exposure time trends. This bias can be identified by comparing the odds ratio by the Mantel-Haenszel method and that by standard conditional logistic regression. We recommend using our proposed method which removes bias from within-subject exposure dependency and can account for time-varying confounders.

The Use of Active Comparators in Self-Controlled Designs

For self-controlled studies of medication-related effects, time-varying confounding by indication can occur if the indication varies over time. We describe how active comparators might mitigate such bias, using an empirical example. Approaches to using active comparators are described for case-crossover design, case-time-control design, self-controlled case-series, and sequence symmetry analyses. In the empirical example, we used Danish data from 1996-2018 to study the association between penicillin and venous thromboembolism (VTE), using roxithromycin, a macrolide antibiotic, as comparator. Upper respiratory infection is a transient risk factor for VTE, thus representing time-dependent confounding by indication. Odds ratios for case-crossover analysis were 3.35 (95% confidence interval: 3.23, 3.49) for penicillin and 3.56 (95% confidence interval: 3.30, 3.83) for roxithromycin. We used a Wald-based method or an interaction term to estimate the odds ratio for penicillin with roxithromycin as comparator. These 2 estimates were 0.94 (95% confidence interval: 0.87, 1.03) and 1.03 (95% confidence interval: 0.95, 1.13). Results were similar for the case-time-control analysis, but both the self-controlled case-series and sequence symmetry analysis suggested a weak protective effect of penicillin, seemingly explained by VTE affecting future exposure exclusively for penicillin. The strong association of antibiotics with VTE suggests presence of confounding by indication. Such confounding can be mitigated by using an active comparator.

Association between opioid-related deaths and prescribed opioid dose and psychotropic medicines in England: a case-crossover study

BACKGROUND

Opioid-overdose deaths are associated with poisoning with prescription and illicit opioids in the USA. In contrast, opioid-related deaths (ORDs) in the UK often involve drugs and substances of misuse, and may not be associated with a high dose of prescribed opioids. This study aimed to investigate the association between prescribed opioid dose and ORDs in UK primary care.

METHODS

This case-crossover study used the Clinical Practice Research Datalink and death registration between 2000 and 2015 to identify ORDs. Daily oral morphine equivalent (OMEQ) dose was measured within a 90 day focal window before ORD and three earlier reference windows. Conditional logistic regression models assessed the adjusted odds ratio (aOR) and 95% confidence interval (95% CI) comparing daily OMEQ dose greater than 120 mg in the focal window against the reference windows.

RESULTS

Of the 232 ORDs, 62 (26.7%) were not prescribed opioids in the year before death. Of the remaining 170 cases, 50 (29.4%) were never prescribed a daily OMEQ dose greater than 50 mg. Daily OMEQ doses over 120 mg (aOR 2.20; 95% CI: 1.06-4.56), co-prescribing gabapentinoids (aOR 2.32; 95% CI: 1.01-5.33), or some antidepressants (aOR 3.03; 95% CI: 1.02-9.04) significantly increased the risk of ORD.

CONCLUSIONS

Daily OMEQ dose greater than 120 mg and the concomitant use of psychotropic medicines were related to ORDs in the UK. Prescribers should cautiously avoid prescribing opioids with a daily OMEQ dose greater than 120 mg day^-1 and the combination of opioids and gabapentinoids, even with low opioid doses.

Risk of fall-related injury and all-cause hospitalization of select concomitant central nervous system medication prescribing in older adult persistent opioid users: A case-time-control analysis

BACKGROUND

Concomitant use of central nervous system (CNS) medications frequently occurs in older adults with persistent opioid use. The risks of adverse outcomes associated with combinations of opioids, sedative hypnotics, or skeletal muscle relaxants have not been sufficiently described in this population.

OBJECTIVE

To compare the overall and incremental risk of (1) fall-related injury and (2) all-cause hospitalization associated with sedative hypnotics and skeletal muscle relaxants among older persistent opioid users.

METHODS

A case-time-control study was conducted using administrative claims of adults ages ≥66 years with a history of persistent (≥90 days) opioid use. Cases included those with first (1) emergency department, hospital, or outpatient visit for a fall-related injury, or (2) all-cause hospitalization. Exposure to CNS medications prior to the case event versus earlier periods, and the risk associated with CNS drug class combinations and sequence of use, was estimated using conditional logistic regression, adjusted for time trends and time-varying covariates.

RESULTS

Among 140,101 older persistent opioid users, 20,723 experienced fall-related injury and 39,444 were hospitalized during follow-up. Skeletal muscle relaxant use was associated with an increased risk of fall-related injury (Odds ratio [OR] 1.28) and all-cause hospitalization (OR 1.11). Statistically significant associations were observed for the joint effects of interactions involving skeletal muscle relaxants on fall-related injury (with opioid: OR 1.25; with sedative hypnotic: OR 1.24), and interactions involving opioids on all-cause hospitalization (with sedative hypnotic: OR 1.10; with skeletal muscle relaxant: OR 1.17). The addition of a skeletal muscle relaxant to an opioid regimen was associated with a 25% increased risk of fall-related injury. Additions of other CNS medications did not have apparent incremental effects on the risk of all-cause hospitalization.

CONCLUSION

The excess risks of fall-related injury and hospitalization associated with various combinations of CNS medications among older persistent opioid users should be considered in therapeutic decision making. Further research is needed to confirm these findings.

Association Between Early Severe Cardiovascular Events and the Initiation of Treatment With the Anti-Interleukin 12/23p40 Antibody Ustekinumab

Importance

Ustekinumab, a monoclonal antibody targeting interleukin 12/23p40 (IL-12/23p40), is effective in the treatment of moderate to severe psoriasis, psoriatic arthritis, and Crohn disease. In 2011, a meta-analysis of randomized clinical trials reported a potential risk of severe cardiovascular events (SCEs) within the first few months after the initiation of anti-IL-12/23p40 antibodies.

Objective

To assess whether the initiation of ustekinumab treatment is associated with increased risk of SCEs.

Design, Setting, and Participants

This case-time-control study used data from the French national health insurance database, covering 66 million individuals, on all patients exposed to ustekinumab between April 1, 2010, and December 31, 2016, classified according to their cardiovascular risk level (high- and low-risk strata). The risk period was the 6 months before the SCE, defined as acute coronary syndrome or stroke, and the reference period was the 6 months before the risk period. Statistical analysis was performed from September 20, 2017, to July 6, 2018.

Exposure

The initiation of ustekinumab treatment was screened during the risk and reference periods.

Main Outcomes and Measures

Odds ratios for the risk of SCE after the initiation of ustekinumab treatment were calculated.

Results

Of the 9290 patients exposed to ustekinumab (4847 men [52%]; mean [SD] age, 43 [14] years), 179 experienced SCEs (65 cases of acute coronary syndrome, 68 cases of unstable angina, and 46 cases of stroke). Among patients with a high cardiovascular risk, a statisically significant association between initiaton of ustekinumab treatment and SCE occurrence was identified (odds ratio, 4.17; 95% CI, 1.19-14.59). Conversely, no statistically significant association was found among patients with a low cardiovascular risk (odds ratio, 0.30; 95% CI, 0.03-3.13).

Conclusions and Relevance

This study suggests that the initiation of ustekinumab treatment may trigger SCEs among patients at high cardiovascular risk. In line with the current mechanistic models for atherosclerotic disease, the period after the initiation of anti-IL-12/23p40 may be associated with atherosclerotic plaque destabilization via the inhibition of helper T cell subtype 17. Although the study interpretation is limited by its observational design, these results suggest that caution may be needed in the prescription of ustekinumab to patients at high cardiovascular risk.

CYP2D6-inhibiting drugs and risk of fall injuries after newly initiated antidepressant and antipsychotic therapy in a Swedish, register-based case-crossover study

Drug-drug interactions have been shown to affect the risk of fall injuries when opioids are used concomitantly with drugs inhibiting the cytochrome P450 2D6 (CYP2D6) enzyme in a previous pharmacoepidemiological study. The aim of this study was to determine whether CYP2D6-inhibiting drugs reinforce the risk of fall injuries when used concomitantly with antidepressants or antipsychotics. We identified all 252,704 adults with a first fall injury leading to hospitalisation from the National Patient Register in Sweden 2006–2013. Data on dispensed drugs was linked from the Swedish Prescribed Drug Register. We applied a case-crossover design to analyse newly dispensed (28 days preceding the fall injury, preceded by a 12-week washout period) antidepressants and antipsychotics, respectively, in relation to risk of a fall injury and according to concomitant use of CYP2D6-inhibiting drugs. Newly dispensed drugs were assessed correspondingly in a control period of equal length, 28 days prior to the 12-week washout period. Overall, the risk of fall injury was increased after newly initiated antidepressant and antipsychotic treatment. For antidepressants, concomitant CYP2D6 inhibitor use further elevated the risk estimates compared to non-use, most pronounced for the groups selective serotonin reuptake inhibitors (sertraline excluded) [OR = 1.47 (95% CI 1.19–1.80) vs. OR = 1.19 (95% CI 1.13–1.26)], and tricyclic antidepressants [OR = 1.71 (95% CI 1.17–2.51) vs. 1.27 (95% CI 1.11–1.47)] as well as for sertraline [OR = 1.61 (95% CI 1.05–2.38) vs. 1.12 (95% CI 1.00–1.26)]. For antipsychotics, the risk of fall injury was not altered by concomitant use of CYP2D6-inhibiting drugs. In conclusion, concomitant use of CYP2D6 inhibiting drugs tends to further increase the risk of fall injury in newly initiated antidepressant treatment, but not in antipsychotic treatment.

A data visualisation method for assessing exposure misclassification in case-crossover studies: the example of tricyclic antidepressants and the risk of hip fracture in older people

Background

The case-crossover design is suited to medication safety studies but is vulnerable to exposure misclassification. Using the example of tricyclic antidepressants and the risk of hip fracture, we present a data visualisation tool for observing exposure misclassification in case-crossover studies.

Methods

A case-crossover study was conducted using Australian Government Department of Veterans’ Affairs claims data. Beneficiaries aged over 65 years who were hospitalised for hip fracture between 2009 and 2012 were included. The case window was defined as 1–50 days pre fracture. Control window one and control window two were defined as 101–150 and 151–200 days pre fracture, respectively. Patients were stratified by whether exposure status changed when control window two was specified instead of control window one. To visualise potential misclassification, each subject’s tricyclic antidepressant dispensings were plotted over the 200 days pre fracture.

Results

The study population comprised 8828 patients with a median age of 88 years. Of these subjects, 348 contributed data to the analyses with either control window. The data visualisation suggested that 14% of subjects were potentially misclassified with control window one while 45% were misclassified with control window two. The odds ratio for the association between tricyclic antidepressants and hip fracture was 1.18 (95% confidence interval = 0.91–1.52) using control window one, whereas risk was significantly increased (odds ratio = 1.43, 95% confidence interval = 1.11–1.83) using control window two.

Conclusions

Exposure misclassification was less likely to be present with control window one than with an earlier control window, control window two. When specifying different control windows in a case-crossover study, data visualisation can help to assess the extent to which exposure misclassification may contribute to variable results.

New methodological approaches were able to effectively reduce immeasurable time bias in case-only designs

OBJECTIVES

The objective of this study was to assess approaches to reduce immeasurable time bias in case-crossover (CCO), case-time-control (CTC), and case-case-time-control (CCTC) designs.

STUDY DESIGN AND SETTING

We used Korea's health care database that has inpatient and outpatient prescriptions and an empirical example of benzodiazepines and mortality among the elderly. We defined our unbiased exposure setting using all prescriptions and a pseudo-outpatient setting using outpatient records only. In the pseudo-outpatient setting, we assessed 10 approaches of restricting, adjusting, stratifying, or weighting on hospitalization-related factors. We conducted conditional logistic regression to estimate odds ratio (OR) with 95% confidence intervals (CI), where an approach was considered effective when its OR was within the unbiased exposure setting OR's 95% CI.

RESULTS

Immeasurable time bias negatively biased the unbiased exposure setting's OR in all three case-only designs, overestimating the protective effect of benzodiazepines on mortality. Of the 10 approaches examined, stratifying the proportion of hospitalized time in 0.01 intervals most effectively repaired the bias in the CCO (OR 1.25, 95% CI 1.10-1.43) and CTC analyses (1.11, 0.95-1.30); no approach was effective in the CCTC analysis.

CONCLUSION

Stratifying the proportion of hospitalized time in 0.01 intervals best approximated the unbiased exposure setting estimate by overcoming the significant impact of immeasurable time bias in CCO and CTC designs.

Medication as a risk factor for hospitalization due to heart failure and shock: a series of case-crossover studies in Swiss claims data

Purpose

Heart failure is among the leading causes for hospitalization in Europe. In this study, we evaluate potential precipitating factors for hospitalization for heart failure and shock.

Methods

Using Swiss claims data (2014–2015), we evaluated the association between hospitalization for heart failure and shock, and prescription of oral potassium supplements, non-steroidal anti-inflammatory drugs (NSAIDs), and amoxicillin/clavulanic acid. We conducted case-crossover analyses, where exposure was compared for the hazard period and the primary control period (e.g., 1–30 days before hospitalization vs. 31–60 days, respectively). Conditional logistic regression was applied and subsequently adjusted for addressing potential confounding by disease progression. Sensitivity analyses were conducted and stratification for co-medication was performed.

Results

We identified 2185 patients hospitalized with heart failure or shock. Prescription of potassium supplements, NSAIDs, and amoxicillin/clavulanic acid was significantly associated with an increased risk for hospitalization for heart failure and shock with crude odds ratios (OR) of 2.04 for potassium (95% CI 1.24–3.36, p = 0.005, 30 days), OR 1.8 for NSAIDs (95% CI 1.39–2.33, p < 0.0001, 30 days), and OR 3.25 for amoxicillin/clavulanic acid (95% CI 2.06–5.14, p < 0.0001, 15 days), respectively. Adjustment attenuated odds ratios, while the significant positive association remained (potassium OR 1.70 (95% CI 1.01–2.86, p = 0.046), NSAIDs OR 1.50 (95% CI 1.14–1.97, p = 0.003), and amoxicillin/clavulanic acid OR 2.26 (95% CI 1.41–3.62, p = 0.001).

Conclusion

Prescription of potassium supplements, NSAIDs, and amoxicillin/clavulanic acid is associated with increased risk for hospitalization. Underlying conditions such as pain, electrolyte imbalances, and infections are likely contributing risk factors. Physicians may use this knowledge to better identify patients at risk and adapt patient management.

Electronic supplementary material

The online version of this article (10.1007/s00228-020-02835-x) contains supplementary material, which is available to authorized users.

Treatment With Bupropion and Varenicline for Smoking Cessation and the Risk of Acute Cardiovascular Events and Injuries: a Swedish Case-Crossover Study

Introduction

Bupropion and varenicline are non-nicotine medications used for smoking cessation that mitigate craving and withdrawal symptoms. We aim to investigate whether these drugs increase the risk of selected acute adverse outcomes when used in medical practice.

Methods

Population-based case-crossover design using data from Swedish health and administrative registers. Adult individuals diagnosed with acute myocardial infarction, stroke, suicide, suicide attempt, fall injury, or that suffered a road traffic crash from 01.10.2006 for bupropion, or from 01.03.2008 for varenicline, until 31.12.2013 were included. Different lengths of exposure periods were analyzed within the 12-week hazard period prior to the adverse outcome (1-14, 15-28, and 29-84 days). The control period was matched using the interval preceding the hazard period (85-168 days), and breaking it up into equivalent periods (85-98, 99-112, and 113-168 days). Conditional logistic regression with each case considered as one stratum was used to estimate adjusted odds ratios (OR) and confidence intervals (CI).

Results

Neither medication was associated with consistent higher risks for any of the adverse outcomes. For bupropion and varenicline, respectively, in the 1-14 days hazard period, OR (95% CI) were: myocardial infarction 1.14 (0.55 to 2.34) and 1.06 (0.70 to 1.62); stroke 1.16 (0.39 to 3.47) and 1.26 (0.72 to 2.17), and traffic crashes 0.85 (0.39 to 1.85) and 1.48 (0.90 to 2.41). In the other periods, ORs were similar or even lower. For falls and suicidal events ORs were generally below one for both drugs.

Conclusion

The available evidence suggests that if prescription guidelines are properly followed regarding potential contraindications both of these medications could be considered relatively safe.

Implications

The reliable exposure and diagnosis assessment used in this nationwide register-based study, along with the number of cases gathered makes this sample one of the largest of its type to assess potential side effects associated with the use of these drugs. Neither medication was associated with consistent higher risks for any of the adverse outcomes studied.

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.

Sample size estimation for case-crossover studies

Case-crossover study designs are observational studies used to assess postmarket safety of medical products (eg, vaccines or drugs). As a case-crossover study is self-controlled, its advantages include better control for confounding because the design controls for any time-invariant measured and unmeasured confounding and potentially greater feasibility as only data from those experiencing an event (or cases) are required. However, self-matching also introduces correlation between case and control periods within a subject or matched unit. To estimate sample size in a case-crossover study, investigators currently use Dupont's formula (Biometrics 1988; 43:1157-1168), which was originally developed for a matched case-control study. This formula is relevant as it takes into account correlation in exposure between controls and cases, which are expected to be high in self-controlled studies. However, in our study, we show that Dupont's formula and other currently used methods to determine sample size for case-crossover studies may be inadequate. Specifically, these formulas tend to underestimate the true required sample size, determined through simulations, for a range of values in the parameter space. We present mathematical derivations to explain where some currently used methods fail and propose two new sample size estimation methods that provide a more accurate estimate of the true required sample size.

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.

Changes in drinking as predictors of changes in sickness absence: a case-crossover study

Background

We investigated whether changes in alcohol use predict changes in the risk of sickness absence in a case-crossover design.

Methods

Finnish public sector employees were surveyed in 2000, 2004 and 2008 on alcohol use and covariates. Heavy drinking was defined as either a weekly intake that exceeded recommendations (12 units for women; 23 for men) or having an extreme drinking session. The responses were linked to national sickness absence registers. We analysed the within-person relative risk of change in the risk of sickness absence in relation to change in drinking. Case period refers to being sickness absent within 1 year of the survey and control period refers to not being sickness absent within 1 year of the survey.

Results

Periods of heavy drinking were associated with increased odds of self-certified short-term (1–3 days) sickness absence (multivariable-adjusted OR 1.21, 95% CI 1.07 to 1.38 for all participants; 1.62, 95% CI 1.19 to 2.21 for men and 1.15, 95% CI 1.00 to 1.33 for women). A higher risk of short-term sickness absence was also observed after increase in drinking (OR=1.27, 95% CI 1.07 to 1.52) and a lower risk was observed after decrease in drinking (OR=0.83, 95% CI 0.69 to 1.00). Both increase (OR=1.38, 95% CI 1.21 to 1.57) and decrease (OR=1.27, 95% CI 1.19 to 1.43) in drinking were associated with increased risk of long-term (>9 days) medically certified all-cause sickness absence.

Conclusion

Increase in drinking was related to increases in short-term and long-term sickness absences. Men and employees with a low socioeconomic position in particular seemed to be at risk.

Uncertain Associations of Major Bleeding and Concurrent Use of Antiplatelet Agents and Chinese Medications: A Nested Case-Crossover Study

Despite the evidence that some commonly used Chinese medications (CMs) have antiplatelet/anticoagulant effects, many patients still used antiplatelets combined with CMs. We conducted a nested case-crossover study to examine the associations between the concomitant use of antiplatelets and CMs and major bleeding using population-based health database in Taiwan. Among the cohort of 79,463 outpatients prescribed antiplatelets (e.g., aspirin and clopidogrel) continuously, 1,209 patients hospitalized with new occurring bleeding in 2012 and 2013 were included. Those recruited patients served as their own controls to compare different times of exposure to prespecified CMs (e.g., Asian ginseng and dong quai) and antiplatelet agents. The periods of case, control 1, and control 2 were defined as 1–4 weeks, 6–9 weeks, and 13–16 weeks before hospitalization, respectively. Conditional logistic regression analyses found that concurrent use of antiplatelet drugs with any of the prespecified CMs in the case period might not significantly increase the risks of bleeding over that in the control periods (OR = 1.00, 95% CI 0.51 to 1.95 and OR = 1.13, 95% CI 0.65 to 1.97). The study showed no strong relationships between hospitalization for major bleeding events and concurrent use of antiplatelet drugs with the prespecified CMs.

Evaluation of the Case-Crossover (CCO) Study Design for Adverse Drug Event Detection

INTRODUCTION

The case-crossover (CCO) design was originally intended to study exposures characterized as intermittent with acute effects. The performance of the CCO design is not well characterized under alternative exposure and outcome relationships.

OBJECTIVE

The purpose of this study was to evaluate the ability of the CCO to identify simulated treatment effects under different drug exposures and outcomes relationships while varying the duration of the 1:1 matched risk and control windows.

METHODS

The simulated data were obtained from the Observational Medical Dataset Simulator, version 2 (OSIM2). The area under the receiver operator characteristic curve (AUC) was calculated to compare CCO performance across outcome types, simulated relative risk (RR), and duration of risk and control windows.

RESULTS

The AUC for acute outcomes was higher for shorter risk and control windows and improved with higher simulated RR. For example, the AUC for the simulated RR of 4 was 0.95 for a 30-day window length and 0.78 for a 360-day window length. The AUC for the accumulative outcomes increased with longer risk and control windows and stronger simulated RR. For example, the AUC for the simulated RR of 4 was 0.85 for a 360-day window length and 0.23 for a 30-day window length. Risk and control window lengths did not appear to sufficiently alter the AUC for insidious onset outcomes.

CONCLUSIONS

The CCO performed best for acute-onset outcomes, but may be useful for exploring adverse outcomes with accumulative effects. Careful consideration must be given to the hypothesized drug exposure and outcome distribution because specification of risk and control window duration affects CCO performance.

Self-controlled designs in pharmacoepidemiology involving electronic healthcare databases: a systematic review

Background

Observational studies are widely used in pharmacoepidemiology. Several designs can be used, in particular self-controlled designs (case-crossover and self-controlled case series). These designs offer the advantage of controlling for time-invariant confounders, which may not be collected in electronic healthcare databases. They are particularly useful in pharmacoepidemiology involving healthcare database. To be valid, they require the presence of some characteristics (key validity assumptions), and in such situations, these designs should be preferred. We aimed at describing the appropriate use and reporting of the key validity assumptions in self-controlled design studies.

Methods

Articles published between January 2011 and December 2014, and describing a self-controlled study design involving electronic healthcare databases were retrieved. The appropriate use (fulfilment of key assumptions) was studied in terms of major (abrupt onset event, rare or recurrent event, and intermittent exposure) and minor assumptions (those for which the design can be adapted).

Results

Among the 107 articles describing a self-controlled design, 35/53 (66%) case-crossover studies, and 48/55 (87%) self-controlled case series fulfilled the major validity assumptions for use of the design; 4/35 and 14/48 respectively did not fulfill the minor assumptions. Overall, 31/53 (58%) case-crossover studies and 34/55 (62%) self-controlled case series fulfilled both major and minor assumptions. The reporting of the methodology or the results was appropriate, except for power calculation.

Conclusions

Self-controlled designs were not appropriately used in34% and 13% of the articles we reviewed that described a case-crossover or a self-controlled case series design, respectively. We encourage better use of these designs in situations in which major validity assumptions are fulfilled (i.e., for which they are recommended), accounting for situations for which the design can be adapted.

Electronic supplementary material

The online version of this article (doi:10.1186/s12874-016-0278-0) contains supplementary material, which is available to authorized users.

Diffusion of Innovations model helps interpret the comparative uptake of two methodological innovations: co-authorship network analysis and recommendations for the integration of novel methods in practice

OBJECTIVE

The objective of this study was to characterize the diffusion of methodological innovation.

STUDY DESIGN AND SETTING

Comparative case study analysis of the diffusion of two methods that summarize confounder information into a single score: disease risk score (DRS) and high-dimensional propensity score (hdPS). We completed systematic searches to identify DRS and hdPS papers in the field of pharmacoepidemiology through to the end of 2013, plotted the number of papers and unique authors over time, and created sociograms and animations to visualize co-authorship networks. First and last author affiliations were used to ascribe institutional contributions to each paper and network.

RESULTS

We identified 43 DRS papers by 153 authors since 1981, reflecting slow uptake during initial periods of uncertainty and broader diffusion since 2001 linked to early adopters from Vanderbilt. We identified 44 hdPS papers by 147 authors since 2009, reflecting rapid and integrated diffusion, likely facilitated by opinion leaders, early presentation at conferences, easily accessible statistical code, and improvement in funding. Most contributions (87% DRS, 96% hdPS) were from North America.

CONCLUSION

When proposing new methods, authors are encouraged to consider innovation attributes and early evaluation to improve knowledge translation of their innovations for integration into practice, and we provide recommendations for consideration.