Immeasurable time bias due to hospitalization in medico-administrative databases: which impact for pharmacoepidemiological studies?

[Performing pharmacoepidemiological studies using the French health insurance data warehouse (SNDS): How to translate guidelines into practice]

The French health insurance data warehouse named SNDS is one of the largest medico-administrative in the world allowing for powerful pharmacoepidemiological studies, based on real-life data collected prospectively. In addition to the absolute necessity of a strong pharmacological rationale, recommendations have been thought to improve the quality of pharmacoepidemiological studies. These guidelines emphasize the importance of an accurate definition of the study population, outcome and exposure, especially for studies performed on medico-administrative databases. Compliance with certain guidelines, particularly those concerning the identification of a specific population or an outcome and the definition of risk periods or exposure periods, may be difficult when performing studies on the SNDS because of its structure and the nature of the data recorded. The objective of this article is to provide advice for the conduct of pharmacoepidemiological studies according to the recommendationswhen using the SNDS, given its specificities. The performing of reliable studies from this rich but complex data warehouse requires the expertise of researchers with deep knowledge both in the SNDS and in pharmacological reasoning.

Performing pharmacoepidemiological studies using the French health insurance data warehouse (SNDS): How to translate guidelines into practice

The French health insurance data warehouse named SNDS is one of the largest medico-administrative in the world allowing for powerful pharmacoepidemiological studies, based on real-life data collected prospectively. In addition to the absolute necessity of a strong pharmacological rationale, recommendations have been thought to improve the quality of pharmacoepidemiological studies. These guidelines emphasize the importance of an accurate definition of the study population, outcome and exposure, especially for studies performed on medico-administrative databases. Compliance with certain guidelines, particularly those concerning the identification of a specific population or an outcome and the definition of risk periods or exposure periods, may be difficult when performing studies on the SNDS because of its structure and the nature of the data recorded. The objective of this article is to provide advice for the conduct of pharmacoepidemiological studies according to the recommendations when using the SNDS, given its specificities. The performing of reliable studies from this rich but complex data warehouse requires the expertise of researchers with deep knowledge both in the SNDS and in pharmacological reasoning.

Validating an approach to overcome the immeasurable time bias in cohort studies: a real-world example and Monte Carlo simulation study

BACKGROUND

Immeasurable time bias arises from the lack of in-hospital medication information. It has been suggested that time-varying adjustment for hospitalization may minimize this potential bias. However, whereas we examined this issue in one case study, there remains a need to assess the validity of this approach in other settings.

METHODS

Using a Monte Carlo simulation, we generated synthetic immeasurable time-varying hospitalization-related factors of duration, frequency and timing. Nine scenarios were created by combining three frequency scenarios and three duration scenarios, where the empirical cohort distribution of hospitalization was used to simulate the 'timing'. We used Korea's healthcare database and a case example of β-blocker use and mortality among patients with heart failure. We estimated the gold-standard hazard ratio (HR) with 95% CI using inpatient and outpatient drug data, and that of the pseudo-outpatient setting using outpatient data only. We assessed the validity of adjusting for time-varying hospitalization in nine different scenarios, using relative bias, confidence limit ratio (CLR) and mean squared error (MSE) compared with the empirical gold-standard estimate across bootstrap resamples.

RESULTS

With the real-world gold standard (HR 0.73; 95% CI 0.67-0.80) as the reference estimate, adjusting for time-varying hospitalization (0.71; 0.63-0.80) effectively reduced the immeasurable time bias and had the following performance metrics across the nine scenarios: relative bias (range: -7.08% to 0.61%), CLR (1.28 to 1.36) and MSE (0.0005 to 0.0031).

CONCLUSIONS

The approach of adjusting for time-varying hospitalization consistently reduced the immeasurable time bias in Monte Carlo simulated data.

The association between exposure to clozapine, olanzapine, and quetiapine and the outcomes perimyocarditis and heart failure: A population-based cohort study

The risk of cardiac adverse events following clozapine use is debated and is unknown for the chemically related and widely used antipsychotics olanzapine and quetiapine. National Swedish registers were used to identify all patients 16-75 years old with antipsychotic dispensations between 2005 and 2018. The short-term outcome was a diagnosis of perimyocarditis (pericarditis and/or myocarditis) within two months of first dispensation, and the long-term outcome was heart failure (including cardiomyopathy) within three years. Cox regressions with time varying exposure were used to estimate hazard rates (HR) and their 95% confidence intervals (CI). A total of 201,045 individuals were included in the cohort. The risk of developing perimyocarditis during clozapine treatment tripled compared to no antipsychotic treatment (HR 3.4, CI 1.6-7.3), although the absolute rate remained comparably low. The long-term risk of heart failure during clozapine treatment was also elevated (HR 1.3, CI 1.1-1.7). Treatment with either or both olanzapine or quetiapine was not associated with an increased relative risk of perimyocarditis, or heart failure compared to no antipsychotic treatment. Clozapine use is therefore associated with a substantially elevated short-term risk of perimyocarditis and an increased risk of heart failure within three years.

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.

Patterns of opioid analgesic prescribing in cancer outpatients during the last year of life in France: A pharmacoepidemiological cohort study based on the French health insurance database

Cancer pain management with adequate analgesics for cancer outpatients can be particularly challenging. This representative retrospective cohort study aimed to investigate the prevalence and timing of weak and strong opioid analgesic prescriptions in cancer outpatients during their last year of life, with a focus on factors associated to potential late strong opioid initiation. Factors associated with late strong opioid initiation were investigated through multivariate logistic regression analyses stratified by place of death. A retrospective cohort of cancer outpatients, who died between 2014 and 2016, was identified from the general sample of beneficiaries. Among N=4704 cancer patients (median age 76 years, 42.7% women), 3002 (63.8%) were prescribed and dispensed ≥1 weak or strong opioid analgesic during their last year of life; of whom, 2458 (52.3%) received ≥1 weak opioid analgesic (tramadol as single-ingredient accounting for 25.9%) and 1733 (36.8%) ≥1 strong opioid analgesic dispensation (fentanyl 21.6%). Median interval between the first prescription for any strong opioid and death was 18 weeks (interquartile range: 8-38), and for weak opioids 33 weeks (interquartile range: 20-47). Among weak opioid users, 1229 (50.0%) patients had received ≥1 weak opioid analgesic dispensation during the year n-2 before death. Among strong opioid users, 986 (56.9%) patients had received ≥1 weak opioid analgesic dispensation during the year n-2 before death and 381 (21.9%) patients ≥1 strong opioid analgesic dispensation. Patients with an outpatient death were more likely to have a late strong opioid initiation compared to patients with an inpatient death. Late strong opioid initiation (<18 weeks before death) was significantly associated with a lower number of hospitalization days and prior weak opioid exposure for patients with an inpatient death and, with older age, social, prior weak opioid exposure, and a prescription initiation by general practitioner for patients with an outpatient death. Our gained knowledge of opioid prescribing patterns in cancer patients during the last year of life might help to progress opioid analgesic treatment and to improve patient outcomes.

Risk of long-term benzodiazepine and Z-drug use following the first prescription among community-dwelling adults with anxiety/mood and sleep disorders: a retrospective cohort study

OBJECTIVE

To measure the incidence of long-term benzodiazepine receptor agonist (BZRA) use among individuals with anxiety, mood and/or sleep disorders. To identify factors associated with long-term use following the first prescription.

METHODS

This was a population-based retrospective cohort study using administrative databases in Manitoba, Canada. Individuals with anxiety/mood or sleep disorder who received their first BZRA between 1 April 2001 and 31 March 2015 were included. Long-term use was defined as ≥180 days. Logistic regression modelling was used to examine predictors of long-term use.

RESULTS

Among 206 933 individuals included, long-term BZRA use in the first episode of use was 4.5% (≥180 days) following their first prescription. Factors associated with ≥180 days of use included male sex (adjusted OR (aOR) 1.33, 95% CI 1.27 to 1.39), age ≥65 (aOR 5.15, 95% CI 4.81 to 5.52), income assistance (aOR 1.68, 95% CI 1.55 to 1.81), previous non-BZRA psychotropic (aOR 1.93, 95% CI 1.83 to 2.02) or opioid use (aOR 1.16, 95% CI 1.11 to 1.22), high comorbidity (aOR 1.43, 95% CI 1.32 to 1.55), high healthcare use (aOR 1.46, 95% CI 1.33 to 1.60) and psychiatrist prescriber (aOR 2.11, 95% CI 1.93 to 2.32).

CONCLUSIONS

Less than 1 in 20 patients use BZRAs ≥180 days in their first treatment episode. Several factors were associated with long-term use following the first prescription and further investigation into whether these factors need to be considered at the point of prescribing is warranted. In light of these findings, future research should examine the predictors of cumulative repeat episodes of BZRA exposure.

Analytical approaches to minimizing immeasurable time bias in cohort studies

BACKGROUND

Immeasurable time bias exaggerates drug benefits in pharmacoepidemiological studies due to exposure misclassification arising from the inability to measure in-hospital medications in many health care databases.

METHODS

To compare the ability of different methodological approaches to minimize immeasurable time bias, we conducted a cohort study of β-blocker use and all-cause mortality among patients with heart failure (HF), using a nationwide health care database which contains both in- and outpatient prescriptions. In our gold-standard analysis, we assessed exposure using a time-varying approach involving both in- and outpatient prescriptions. Cox proportional hazard models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) of mortality, with exposure to β-blockers defined as a time-varying variable. To estimate the magnitude of the immeasurable time bias, we repeated the analyses using outpatient prescriptions only and compared 10 approaches to minimize the bias, which are categorized as restriction, adjustment, assumption and weighting.

RESULTS

The HR for β-blocker use versus non-use was 0.76 (95% CI: 0.71 to 0.80) in our gold-standard analysis. When exposure assessment was restricted to outpatient prescriptions only, β-blocker use was substantially more protective (HR 0.43, 95% CI: 0.40 to 0.46). Of the 10 approaches examined, adjusting for hospitalization as a time-varying variable successfully minimized the bias (HR 0.75, 95% CI: 0.68 to 0.82).

CONCLUSIONS

The immeasurable time bias can result in substantial bias in pharmacoepidemiological studies. Time-varying adjustment for hospitalization appears to reduce the immeasurable time bias in the absence of inpatient medication data.

Potential inappropriate use of strong opioid analgesics in cancer outpatients during the last year of life in France and associated factors

AIMS

A better knowledge of opioid prescribing patterns would help to identify areas of potential improvement in cancer pain management. This study aimed to identify potential inappropriate use (PIU) of strong opioid analgesics in cancer outpatients in their last year of life.

METHODS

A retrospective cohort of cancer patients who died between 2011 and 2014 and were exposed as outpatient to a strong opioid analgesic in the last year of life was identified in the Echantillon Généraliste de Bénéficiaires (a 1/97th random sample of the French general population). Prescribing patterns of strong opioids were analysed and PIU was defined by at least 1 of these criteria: overlapping prescriptions; contraindicated prescriptions; lack of laxatives; potential drug interactions; prescription in patients hospitalized for opioid-related disorders. Factors associated with PIU were investigated through a multiple logistic regression model.

RESULTS

One third of the 2236 patients (median age 72 years [interquartile range: 61-82], 44.1% women) presented a PIU (insufficient laxative prescription [19.6% of patients], insufficient background treatment with transmucosal fentanyl [14.8%], overlapping prescriptions [2.6%]). The rate of PIU significantly decreased from 37.6% (2011) to 29.8% (2014). For patients with a duration of opioid use ≥3 months, factors associated with PIU were fentanyl prescription (adjusted odds ratio = 2.36; 95% confidence interval [1.86-3.00]) and previous use of strong opioid (adjusted odds ratio = 1.88; [1.50-2.36]).

CONCLUSION

In France, 1/3 of cancer patients exposed to strong opioids experienced PIU and this proportion tended to decrease over time. There is still room for progress in cancer pain management at the end of life.

Use of the French national health insurance information system for research in the field of mental health: Systematic review and perspectives

PURPOSE

This systematic review registered in PROSPERO (CRD42021225296) aimed to describe the use of the French national health insurance information system, which covers the entire French population (67 million inhabitants), for research in the field of mental health.

METHODS

Three electronic databases and a journal hand-search identified 15 265 articles from January 1, 2003 (year of creation of the database) to October 31, 2020. Studies of any design were eligible for inclusion provided that they (i) made use of at least one component of the French health insurance database and (ii) focused on a topic in near and far connection with the field of mental health in France. Database used, design and methods, study period, population, key findings, and type of use for medical research were described.

RESULTS

A total of 152 studies were included in the review analysis. There was an increase in the number of published articles over time throughout the studied period. Studies focusing on adults (n = 139) largely outnumbered those focusing on children and adolescents (n = 11). Pharmacoepidemiological studies were by far the most frequent (n = 123), followed by methodological studies (n = 23), epidemiological studies (n = 17), and health economics studies (n = 3). The most studied psychotropic drugs were antidepressants (n = 27), anxiolytics (n = 27), and opioids (n = 25) while fewer studies focused on methylphenidate (n = 6) and on mood stabilizers (n = 5). Few studies specifically focused on psychiatric disorders, mainly depression (n = 4), suicide (n = 4), and psychotic disorders (n = 3).

CONCLUSION

This systematic review highlighted a relatively poor exploitation of the Système national des données de santé database in the field of psychiatric research with regard to the great possibilities it offers, with a clear lag in certain fields such as epidemiological or health economics studies and in specific populations, in particular children and adolescents.

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.

Outpatient healthcare utilization 30 days before and after hospitalization for heart failure in France: Contribution of the national healthcare database (Systèmenationaldesdonnéesdesanté)

BACKGROUND

Guidelines have been published concerning patient management after hospitalization for heart failure. The French national healthcare database (Systèmenationaldesdonnéesdesanté; SNDS) can be used to compare these guidelines with real-life practice.

AIMS

To study healthcare utilization 30 days before and after hospitalization for heart failure, and the variations induced by the exclusion of institutionalized patients, who are less exposed to outpatient healthcare utilization.

METHODS

We identified the first hospitalization for heart failure in 2015 of adult beneficiaries of the health insurance schemes covering 88% of the French population, who were alive 30 days after hospitalization. Outpatient healthcare utilization rates during the 30 days after hospitalization and the median times to outpatient care, together with their interquartile ranges, were described for all patients, and for a subgroup excluding institutionalized patients.

RESULTS

Among the 104,984 patients included (mean age 79 years; 52% women), 74% were non-institutionalized (mean age 78 years; 47% women). The frequencies of at least one consultation after hospitalization and the median times to consultation were 69% (total sample) vs. 78% (subgroup excluding institutionalized patients) and 8 days (interquartile range 3; 16) vs. 7 days (3; 15) for general practitioners, 20% vs. 21% and 14 days (7; 23) vs. 16 days (9; 24) for cardiologists and 58% vs. 69% and 3 days (1; 9) vs. 2 days (1; 7) for nurses, with reimbursement of diuretics in 77% vs. 86%, angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers in 48% vs. 55% and beta-blockers in 55% vs. 63%. Departmental variations, excluding institutionalized patients, were large: general practice consultations (interquartile range 74%; 83%), cardiology consultations (11%; 23%) and nursing care (68%; 77%).

CONCLUSIONS

Low outpatient healthcare utilization rates, long intervals to first healthcare utilization and departmental variations indicate a mismatch between guidelines and real-life practice, which is accentuated when including institutionalized patients.

Capture of biologic and biosimilar dispensings in a consortium of U.S.-based claims databases: Utilization of national drug codes and Healthcare Common Procedure Coding System modifiers in medical claims

PURPOSE

To assess the capture of biologics (originator and biosimilar) in the Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) Distributed Research Network (DRN), with a focus on medical claim National Drug Code (NDC), a new data field, and Healthcare Common Procedure Coding System (HCPCS) modifier.

METHODS

We conducted a repeated cross-sectional study among patients with medical and pharmacy benefits enrolled in insurance plans participating in the BBCIC DRN between 1 January 2013 and 30 September 2017. We calculated the proportion of medical claims with ≥1 NDC and identified select biologics using four different approaches: (a) specific HCPCS alone, (b) specific HCPCS and NDC, (c) non-specific HCPCS with NDC, and (d) HCPCS with modifiers (applicable to biosimilars). Numbers of dispensings were calculated for each biologic by approach and select patient and claim characteristics.

RESULTS

More than 1.5 million eligible participants contributed approximately 4 million person-years of data, including 1.2 billion medical claims. The proportion of medical claims with ≥1 NDC increased from 1.2% in 2013 to 3.0% in 2017. Medical claim NDCs identified 39% and 28% of vedolizumab dispensed in 2014 and 2015 and 30% of Epogen/Procrit dispensed overall. Out of 26,381 filgrastim biosimilar dispensings identified, 51% had a HCPCS modifier and 12% had a medical claim NDC for Zarxio. HCPCS modifiers and medical claim NDCs were present for 38% and 3% of all infliximab biosimilars dispensed (total n = 1,244).

CONCLUSIONS

Medical claim NDC and HCPCS modifier improves identification of select biologics without product-specific HCPCS code, thereby facilitating product-specific biologic research.

Bias in pharmacoepidemiologic studies using secondary health care databases: a scoping review

BACKGROUND

The availability of clinical and therapeutic data drawn from medical records and administrative databases has entailed new opportunities for clinical and epidemiologic research. However, these databases present inherent limitations which may render them prone to new biases. We aimed to conduct a structured review of biases specific to observational clinical studies based on secondary databases, and to propose strategies for the mitigation of those biases.

METHODS

Scoping review of the scientific literature published during the period 2000-2018 through an automated search of MEDLINE, EMBASE and Web of Science, supplemented with manually cross-checking of reference lists. We included opinion essays, methodological reviews, analyses or simulation studies, as well as letters to the editor or retractions, the principal objective of which was to highlight the existence of some type of bias in pharmacoepidemiologic studies using secondary databases.

RESULTS

A total of 117 articles were included. An increasing trend in the number of publications concerning the potential limitations of secondary databases was observed over time and across medical research disciplines. Confounding was the most reported category of bias (63.2% of articles), followed by selection and measurement biases (47.0% and 46.2% respectively). Confounding by indication (32.5%), unmeasured/residual confounding (28.2%), outcome misclassification (28.2%) and "immortal time" bias (25.6%) were the subcategories most frequently mentioned.

CONCLUSIONS

Suboptimal use of secondary databases in pharmacoepidemiologic studies has introduced biases in the studies, which may have led to erroneous conclusions. Methods to mitigate biases are available and must be considered in the design, analysis and interpretation phases of studies using these data sources.

Discontinuation and Nonadherence to Medications for Chronic Conditions after Hematopoietic Cell Transplantation: A 6-Year Propensity Score-Matched Cohort Study

INTRODUCTION

Hematopoietic cell transplantation (HCT) is an established curative option for patients with hematological malignancies and other life-threatening conditions. Evidence on nonpersistence and nonadherence to oral medications for chronic conditions among patients following HCT is lacking.

OBJECTIVES

This study aims to examine patterns of oral medication use for chronic conditions following HCT in the U.S.

POPULATION

METHODS

Nonpersistence and nonadherence to oral medications for diabetes, hypertension, and dyslipidemia among HCT recipients were assessed in a cohort that included 1382 autologous and 650 allogeneic HCT recipients with hematological malignancies using the Truven Health MarketScan Research Database between 2009 and 2014. Recipients of HCT were compared to propensity score-matched cancer patients receiving chemotherapy without transplantation. Multivariable Cox proportional hazards models and generalized estimating equations were used to determine characteristics associated with nonpersistence and nonadherence to oral chronic medications, respectively.

RESULTS

Recipients of HCT had higher risks of discontinuing medication for diabetes mellitus (allogeneic HCT hazard ratio [HR] = 1.93, 95% confidence interval [CI] 1.10-3.39; autologous HCT HR = 1.49, 95% CI 1.04-2.15); hypertension (allogeneic HCT HR = 1.75, 95% CI 1.21-2.53; autologous HCT HR = 1.32, 95% CI 1.07-1.62), and dyslipidemia (allogeneic HCT HR = 2.02, 95% CI 1.39-2.93; autologous HCT, HR = 1.26, 95% CI 0.98-1.61) compared to patients treated with only chemotherapy. Lower odds of adherence to antihypertensive medications (odds ratio [OR] = 0.58, 95% CI 0.38-0.89) and to lipid-lowering medications (OR = 0.38, 95% CI 0.22-0.65) were observed in allogeneic HCT recipients compared with propensity score-matched patients who underwent chemotherapy only.

CONCLUSIONS

Poor medication persistence and adherence to chronic disease medications are common after HCT. Further research to improve long-term outcomes following HCT should include management of medication therapy for chronic comorbid conditions.

Estimating Adherence Based on Prescription or Dispensation Information: Impact on Thresholds and Outcomes. A Real-World Study With Atrial Fibrillation Patients Treated With Oral Anticoagulants in Spain

Objective: To estimate drug exposure, Proportion of Days Covered (PDC) and percentage of patients with PDC ≥ 80% from a cohort of atrial fibrillation patients initiating oral anticoagulant (OAC) treatment. We employed three different approaches to estimate PDC, using either data from prescription and dispensing (PD cohort) or two common designs based on dispensing information only, requiring at least one (D1) or at least two (D2) refills for inclusion in the cohorts. Finally, we assessed the impact of adherence on health outcomes according to each method. Methods: Population-based retrospective cohort of all patients with Non Valvular Atrial Fibrillation (NVAF), who were newly prescribed acenocoumarol, apixaban, dabigatran or rivaroxaban from November 2011 to December 2015 in the region of Valencia (Spain). Patients were followed for 12 months to assess adherence using three different approaches (PD, D1 and D2 cohorts). To analyze the relationship between adherence (PDC ≥ 80) defined according to each method of calculation and health outcomes (death for any cause, stroke or bleeding) Cox regression models were used. For the identification of clinical events patients were followed from the end of the adherence assessment period to the end of the available follow-up period. Results: PD cohort included all patients with an OAC prescription (n = 38,802), D1 cohort excluded fully non-adherent patients (n = 265) and D2 cohort also excluded patients without two refills separated by 180 days (n = 2,614). PDC ≥ 80% ranged from 94% in the PD cohort to 75% in the D1 cohort. Drug exposure among adherent (PDC ≥ 80%) and non-adherent (PDC < 80%) patients was different between cohorts. In adjusted analysis, high adherence was associated with a reduced risk of death [Hazard Ratio (HR): from 0.82 to 0.86] and (except in the PD cohort) the risk for ischemic stroke (HR: from 0.61 to 0.64) without increasing the risk of bleeding. Conclusion: Common approaches to assess adherence using measures based on days' supply exclude groups of non-adherent patients and, also, misattribute periods of doctors' discontinuation to patient non-adherence, misestimating adherence overall. Physician-initiated discontinuation is a major contributor to reduced OAC exposure. When using the PDC80 threshold, very different groups of patients may be classified as adherent or non-adherent depending on the method used for the calculation of days' supply measures. High adherence and high exposure to OAC treatment in NVAF patients is associated with better health outcomes.

Risk of death associated with new benzodiazepine use among persons with Alzheimer disease: A matched cohort study

OBJECTIVE

To investigate the risk of death associated with new benzodiazepine and related drug (BZDR) use in a nationwide cohort of persons with Alzheimer disease (AD).

METHODS

The register-based MEDALZ cohort, including all community-dwelling Finns diagnosed with AD during 2005 to 2011 (n = 70 718), was used. Clinically verified AD diagnoses were obtained from the Special Reimbursement Register. Drug use periods were modeled from BZDR purchases, derived from the Prescription Register. To study new users, persons who had any BZDR use during the year preceding the AD diagnosis were excluded. For each person initiating BZDR use (n = 10 380), 2 nonusers (n = 20 760) were matched on age, gender, and time since AD diagnosis. The outcome was 180-day mortality, and BZDR use was compared with nonuse with Cox regression. Multivariable analyses were adjusted for Charlson comorbidity index, socioeconomic position, hip fractures, psychiatric disorders, substance abuse, stroke, and other psychotropic drug use.

RESULTS

During the follow-up, 5 excess deaths per 100 person-years occurred during BZDR use in comparison to nonuse, and mortality rates were 13.4 (95% confidence interval [CI], 12.2-14.5) and 8.5 (95% CI, 7.9-9.1), respectively. Benzodiazepine and related drug use was associated with an increased risk of death (adjusted hazard ratio = 1.4 [95% CI, 1.2-1.6]), and the association was significant from the initiation of use. Benzodiazepine use was associated with an increased risk of death, whereas benzodiazepine-related drug use was not.

CONCLUSIONS

Benzodiazepine and related drug use was associated with an increased risk of death in persons with AD. Our results support treatment guidelines stating that nonpharmacological approaches should be the first-line option for symptomatic treatment of AD.