Risk of retinal detachment and exposure to fluoroquinolones, common antibiotics, and febrile illness using a self-controlled case series study design: Retrospective analyses of three large healthcare databases in the US.

OBJECTIVE: The risk of retinal detachment (RD) following exposure to fluoroquinolone (FQ) has been assessed in multiple studies, however, results have been mixed. This study was designed to estimate the risk of RD following exposure to FQ, other common antibiotics, and febrile illness not treated with antibiotics (FINTA) using a self-controlled case series (SCCS) study design to reduce risk of confounding from unreported patient characteristics. DESIGN: Retrospective database analysis-SCCS. SETTING: Primary and Secondary Care. STUDY POPULATION: 40,981 patients across 3 US claims databases (IBM® MarketScan® commercial and Medicare databases, Optum Clinformatics). OUTCOME: RD. METHODS: Exposures included FQ as a class of drugs, amoxicillin, azithromycin, trimethoprim with and without sulfamethoxazole, and FINTA. For the primary analysis, all drug formulations were included. For the post hoc sensitivity analyses, only oral tablets were included. Risk windows were defined as exposure period (or FINTA duration) plus 30 days. Patients of all ages with RD and exposures in 3 US claims databases between 2012 to 2017 were included. Diagnostics included p value calibration and pre-exposure outcome analyses. Incidence rate ratios (IRR) and 95% confidence interval (CI) comparing risk window time with other time were calculated. RESULTS: Our primary analysis showed an increased risk for RD in the 30 days prior to exposure to FQ or trimethoprim without sulfamethoxazole. This risk decreased but remained elevated for 30 days following first exposure. Our post-hoc analysis, which excluded ophthalmic drops, showed no increased risk for RD at any time, with FQ and other antibiotics. CONCLUSION: Our results did not suggest an association between FQ and RD. Oral FQ was not associated with an increased risk for RD during the pre- or post-exposure period. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03479736-March 21, 2018.

Risk of aortic aneurysm and dissection following exposure to fluoroquinolones, common antibiotics, and febrile illness using a self-controlled case series study design: Retrospective analyses of three large healthcare databases in the US.

OBJECTIVE: Recent observational studies suggest increased aortic aneurysm or dissection (AAD) risk following fluoroquinolone (FQ) exposure but acknowledge potential for residual bias from unreported patient characteristics. The objective of our study is to evaluate the potential association between FQ, other common antibiotics and febrile illness with risk of AAD using a self-controlled case series (SCCS) study design. DESIGN: Retrospective database analysis-SCCS. SETTING: Primary and Secondary Care. STUDY POPULATION: 51,898 patients across 3 US claims databases (IBM® MarketScan® commercial and Medicare databases, Optum Clinformatics). EXPOSURE: FQ or other common antibiotics or febrile illness. OUTCOME: AAD. METHODS: We studied patients with exposures and AAD between 2012 and 2017 in 3 databases. Risk windows were defined as exposure period plus 30 days. Diagnostic analyses included p-value calibration to account for residual error using negative control exposures (NCE), and pre-exposure outcome analyses to evaluate exposure-outcome timing. The measure of association was the incidence rate ratio (IRR) comparing exposed and unexposed time. RESULTS: Most NCEs produced effect estimates greater than the hypothetical null, indicating positive residual error; calibrated p (Cp) values were therefore used. The IRR following FQ exposure ranged from 1.13 (95% CI: 1.04-1.22 -Cp: 0.503) to 1.63 (95% CI: 1.45-1.84 -Cp: 0.329). An AAD event peak was identified 60 days before first FQ exposure, with IRR increasing between the 60- to 30- and 29- to 1-day pre-exposure periods. It is uncertain how much this pre-exposure AAD event peak reflects confounding versus increased antibiotic use after a surgical correction of AADs. CONCLUSION: This study does not confirm prior studies. Using Cp values to account for residual error, the observed FQ-AAD association cannot be interpreted as significant. Additionally, an AAD event surge in the 60 days before FQ exposure is consistent with confounding by indication, or increased use of antibiotics post-surgery. REGISTRATION: NCT03479736.

Stroke Risk Among Elderly Users of Haloperidol and Typical Antipsychotics Versus Atypical Antipsychotics: A Real-World Study From a US Health Insurance Claims Database.

BACKGROUND: We estimated stroke risk associated with new exposure to haloperidol, or any typical antipsychotic, versus atypical antipsychotic among patients aged ≥65 years regardless of dementia status. METHODS: IBM MarketScan Medicare Supplemental Database data (January 1, 2001 to December 31, 2017) were used. Stroke risk for new users of typical antipsychotics (T1 cohort) or haloperidol (T2 cohort) was compared with new users of atypical antipsychotics (C1 cohort) aged ≥65 years. Crude incidence rate (IR) and incidence proportion of stroke were estimated within each cohort and gender subgroup. Three propensity score (PS) matching strategies were employed: Unadjusted (crude), Sentinel PS replication, and a large-scale regularized regression model (adapted PS). RESULTS: Overall, 36,734 (T1), 24,074 (T2), and 226,990 (C1) patients were included. Crude IRs for stroke per 1000 person-years were 17.67 (T1), 23.74 (T2), and 14.17 (C1). In preplanned analyses, PS-matched calibrated hazard ratio (cHR) for stroke T1 versus C1 cohort was 1.08 (95% calibrated confidence interval [cCI] = 0.75, 1.55) with Sentinel PS strategy and 1.31 (95% cCI = 1.07, 1.60) with adapted PS strategy. The cHR for stroke in patients of T2 versus C1 was 1.69 (95% cCI = 1.08, 2.75) with Sentinel PS strategy and 1.45 (95% cCI = 1.17, 1.80) with adapted PS strategy. CONCLUSION: Stroke risk in elderly new users of haloperidol was elevated compared to new users of atypical antipsychotics and was elevated for typical antipsychotics using the adapted PS strategy.

Quantification of missing prescriptions in commercial claims databases: results of a cohort study.

PURPOSE: This study aims to quantify the magnitude of missed dispensings in commercial claims databases. METHODS: A retrospective cohort study has been used linking PharMetrics, a commercial claims database, to a prescription database (LRx) that captures pharmacy dispensings independently of payment method, including cash transactions. We included adults with dispensings for opioids, diuretics, antiplatelet medications, or anticoagulants. To determine the degree of capture of dispensings, we calculated the number of subjects with the following: (1) same number of dispensings in both databases; (2) at least one dispensing, but not all dispensings, missed in PharMetrics; and (3) all dispensings missing in PharMetrics. Similar analyses were conducted using dispensings as the unit of analysis. To assess whether a dispensing in LRx was in PharMetrics, the dispensing in PharMetrics had to be for the same medication class and within ±7 days in LRx. RESULTS: A total of 1 426 498 subjects were included. Overall, 68% of subjects had the same number of dispensings in both databases. In 13% of subjects, PharMetrics identified ≥1 dispensing but also missed ≥1 dispensing. In 19% of the subjects, PharMetrics missed all the dispensings. Taking dispensings as the unit of analysis, 25% of the dispensings present in LRx were not captured in PharMetrics. These patterns were similar across all four classes of medications. Of the dispensings missing in PharMetrics, 48% involved a subject who had >1 health insurance plan. CONCLUSIONS: Commercial claims databases provide an incomplete picture of all prescriptions dispensed to patients. The lack of capture goes beyond cash transactions and potentially introduces substantial misclassification bias. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Fidelity assessment of a clinical practice research datalink conversion to the OMOP common data model.

BACKGROUND: The unique structure and coding of the Clinical Practice Research Datalink (CPRD) presents challenges for epidemiologic analysis and for comparisons with other databases. To address this limitation we sought to transform CPRD into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). METHODS: An extraction, transformation and loading process was developed, which detailed source code mappings, Read code domain classification, an imputation algorithm for drug duration and special handling of lifestyle/clinical data. Completeness and accuracy of the above elements were assessed. A final validation exercise involved replication of a published case-control study that examined use of nonsteroidal anti-inflammatory drugs (NSAIDs) and the risk of first-time acute myocardial infarction (AMI) in raw CPRD data and the CPRD CDM. FINDINGS: All elements of the CPRD CDM transformation were assessed to be of high quality. 99.9 % of database condition records and 89.7 % of database drug records were mapped (majority unmapped drugs were devices and over-the-counter products); 3.1 % of duration imputations were deemed possibly erroneous and prevalences for selected conditions and drugs across CPRD raw and CDM data were equivalent. Results between the replication raw data and CDM study agreed for conditions, demographics and lifestyle data with slight NSAID exposure data loss owing to unmapped drugs. CONCLUSION: CPRD can be accurately transformed into the OMOP CDM with acceptable information loss across drugs, conditions and observations. We determined that for a particular use, case CDM structure was adequate and mappings could be improved but did not substantially change the results of our analysis.

Opioid shopping behavior: how often, how soon, which drugs, and what payment method.

Doctor shopping (obtaining opioid prescriptions from multiple prescribers) is one example of opioid abuse and diversion. The authors assessed how soon shopping behavior was observed after opioid exposure, number of events per shopper, preferred opioids, and method of payment. This was a cohort study. Individuals with ≤1 dispensing for any opioid in 2008 were followed for 18 months. Shopping behavior was defined as ≤2 prescriptions by different prescribers with ≤1 day of overlap and filled at ≤3 pharmacies. Of 25,161,024 subjects, 0.30% exhibited shopping behavior. Opioid-experienced subjects were 13.7 times more likely to exhibit shopping behavior and had more shopping episodes than opioid-naive subjects. Time to first shopping event was 246.90 ± 163.61 days. Number of episodes was 2.74 ± 4.66. Most subjects with shopping behavior (55.27%) had 1 shopping episode, whereas 9.52% had ≤6 episodes; 88.99% had ≤4 prescribers. Subjects with shopping behavior filled schedule II opioids more often than subjects without shopping behavior (19.51% vs 10.89%) and more often paid in cash (44.85% vs 18.54%). Three of 1000 people exposed to opioids exhibit shopping behavior, on average, 8 months after exposure. Opioid shoppers seek strong opioids, avoid combination products, often pay cash, and obtain prescriptions from few prescribers.

Registration of Observational Studies: perspectives from an industry-based epidemiology group.

Registration of randomized clinical trials has become standard practice and is enforced through publication policies and governmental regulations. However, the registration of observational studies remains controversial. In this commentary, we propose that a compromise can be reached on which observation should be registered based on study design and study intent.

Estimating post-marketing exposure to pharmaceutical products using ex-factory distribution data.

The pharmaceutical industry has an obligation to identify adverse reactions to drug products during all phases of drug development, including the post-marketing period. Estimates of population exposure to pharmaceutical products are important to the post-marketing surveillance of drugs, and provide a context for assessing the various risks and benefits, including drug safety, associated with drug treatment. This paper describes a systematic approach to estimating post-marketing drug exposure using ex-factory shipment data to estimate the quantity of medication available, and dosage information (stratified by indication or other factors as appropriate) to convert the quantity of medication to person time of exposure. Unlike the non-standardized methods often used to estimate exposure, this approach provides estimates whose calculations are explicit, documented, and consistent across products and over time. The methods can readily be carried out by an individual or small group specializing in this function, and lend themselves to automation. The present estimation approach is practical and relatively uncomplicated to implement. We believe it is a useful innovation.

Achilles tendon rupture and its association with fluoroquinolone antibiotics and other potential risk factors in a managed care population.

BACKGROUND: Case reports and observational studies have implicated fluoroquinolone antibiotic exposure as a risk factor for Achilles tendon rupture (ATR), an uncommon condition for which there are few formal studies. We sought to quantify the strength of association between exposure to fluoroquinolone antibiotics and the occurrence of ATR, accounting for other risk factors. METHODS: This was a case-control study nested within a health insurer cohort. Cases of ATR were identified and confirmed using patterns of health insurance claims that were validated through sampled medical record review. Information on risk factors, including fluoroquinolone exposure, came from health insurance claims. RESULTS: There were 947 cases of ATR and 18 940 controls. A dispensing of a fluoroquinolone antibiotic in the past 6 months was more common among ATR cases than controls, although not significantly so (odds ratio (OR) = 1.2; 95% confidence interval (CI) = 0.9-1.7), and exposure to a higher cumulative fluoroquinolone dose was more strongly associated (OR = 1.5, 95%CI = 1.0-2.3). Other risk factors for ATR were trauma (OR = 17.2, 95%CI = 14.0-20.2), male sex (OR = 3.0, 95%CI = 2.6-3.5), injected corticosteroid administration (OR = 2.2, 95%CI = 1.6-2.9), obesity (OR = 2.0, 95%CI = 1.2-3.1), rheumatoid arthritis (OR = 1.9, 95%CI = 1.0-3.7), skin or soft tissue infections (OR = 1.5, 95%CI = 0.9-2.3), oral corticosteroids (OR = 1.4, 95%CI = 1.0-1.8), and non-fluoroquinolone antibiotics (OR = 1.2, 95%CI = 1.1-1.5). CONCLUSIONS: The elevation in ATR risk associated with fluoroquinolones was similar in magnitude to that associated with oral corticosteroids or non-fluoroquinolone antibiotics. Trauma and male sex were more strongly associated with ATR, as were obesity and injected corticosteroids.

The impact of wording in "Dear doctor" letters and in black box labels.

OBJECTIVES: The Food and Drug Administration and pharmaceutical manufacturers use "Dear doctor" letters to alert physicians about drug safety. To determine how such warnings may be improved, we retrospectively examined how variations in the wording of one series of "Dear doctor" letters affected their impact on concomitant dispensing of cisapride (Propulsid; Janssen Pharmaceutica, Titusville, NJ) and several medications contraindicated for concomitant use. METHODS: Concomitant dispensing was defined as dispensing cisapride and a contraindicated medication on dates when the intended duration of the two dispensings overlapped on at least 1 day. Using outpatient pharmacy claims from a New England health insurer, we calculated a concomitant dispensing rate for each calendar month as the number of concomitant cisapride dispensings divided by the total number of cisapride dispensings. We grouped drugs contraindicated for concomitant use with cisapride as (1) explicitly named in the warnings, (2) only mentioned as examples of a drug class, or (3) only implied as drug class members. We used multivariate analysis to relate temporal changes in concomitant dispensing rates to type of warning (explicit, example, or implied), patient demographic characteristics, season, calendar year, and temporal relationship to the "Dear doctor" warnings. RESULTS: A highly publicized letter sent in June 1998 was associated with a notable decline (58%) in the concomitant dispensing rate with explicitly contraindicated drugs but not in the concomitant dispensing of cisapride with the example or implied drugs. An earlier letter, which had been explicit but was accompanied by less publicity, had no measurable effect on this study's measure of coprescription, nor did a later letter that emphasized comorbidities. CONCLUSIONS: Explicit, well-publicized drug warnings can change prescriber behavior.