Antiepileptic drug use and mortality among community-dwelling persons with Alzheimer disease

Study design and participants

This study was conducted on the nationwide register-based MEDALZ (Medication Use and Alzheimer Disease) cohort. The MEDALZ cohort includes all community-dwelling people who received diagnoses of AD in Finland in 2005–2011 (n = 70,718).²³

People with AD diagnosis were identified from the Special Reimbursement Register, which contains records of people who are entitled to higher medication reimbursement due to chronic diseases, including AD. All citizens and long-term residents of Finland are covered under the Finnish National Health Insurance scheme and are thus eligible for reimbursement of medical expenses under the Health Insurance Act.

To be entitled to special reimbursement due to a chronic disease, a patient must meet predefined criteria and a diagnosis statement must be submitted to the Social Insurance Institution of Finland (SII) for approval. For AD, the SII requires that the medical statement verifies that the patient has (1) symptoms consistent with AD; (2) experienced a decrease in social capacity over a period of at least 3 months; (3) received a CT or MRI scan; (4) had possible alternative diagnoses excluded; and (5) received confirmation of the diagnosis by a registered geriatrician or neurologist. The diagnosis of AD is based on the National Institute of Neurologic and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association and DSM-IV criteria for AD. The accuracy of AD diagnosis in the register has been validated previously.²⁴ For a diagnosis of epilepsy to be verified and recorded in the Special Reimbursement Register, a neurologist provides a medical statement to the SII indicating that the person has (1) been examined by a neurologist or at a neurology clinic; (2) received relevant examinations including EEG, a CT or MRI scan, and relevant laboratory tests for diagnosis according to the ICD-10; and (3) has a care plan in accordance with good clinical practice.

People who initiated AED use after AD diagnosis were considered for this study. Incident users were identified with 1-year washout period to avoid prevalent user bias.²⁵ People hospitalized or institutionalized for more than 182 days during the washout period, or >90 days at the end of the washout period, were excluded. Dates of long-term institutionalization were obtained from the SII and durations of hospital stays from the Care Register for Health Care. People with a history of any cancer (ICD-10, C00-C97) as a main or auxiliary diagnosis in the Care Register for Health Care or purchases of antineoplastic or immunomodulating agents during the 12 months preceding the AED initiation were also excluded (table e-1, doi.org/10.5061/dryad.q3b38p9).

For each AED user, a matched nonuser was identified based on the same inclusion and exclusion criteria (figure 1) applying incidence density sampling without replacement. The matching criteria were age (±730 days), sex, and time since AD diagnosis (±90 days). People without a match (n = 360) were excluded from further analyses.

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Figure 1 Flowchart of exclusion criteria of the study cohort with Alzheimer disease diagnoses

AED = antiepileptic drug.

The follow-up started on the index date, which was the date of AED initiation or the corresponding matching date for nonusers. People were followed until death, AED use discontinuation (for users) or AED initiation (for nonusers), continuous hospitalization or institutionalization more than 90 days, after 3 years of follow-up, or the end of the study (December 31, 2015). In drug–drug comparisons, the follow-up also ended if there were switches between AEDs or polytherapy was initiated.

The maximum follow-up was restricted to 3 years based on our previous data²⁰ showing that a high proportion of users discontinued AED use within this period.

Standard protocol approvals, registrations, and patient consents

According to Finnish legislation, no ethics committee approval was required for this study because only deidentified register-based data were used and the study participants were not contacted.

AED use exposure

Data on purchased drugs since 1995 were extracted from the prescription register maintained by the SII. This register contains all reimbursed prescription drug purchases made by Finnish community-dwellers and includes dispensing date of each prescription, the WHO Anatomical Therapeutic Chemical (ATC) code, and such information as the quantity, strength, and formulation of dispensed drugs. In this study, antiepileptics were defined as ATC code N03A and categorized to older and newer according to previous classifications.²⁶ Older AEDs included valproic acid, carbamazepine, clonazepam, and phenytoin; newer AEDs included pregabalin, gabapentin, lamotrigine, oxcarbazepine, topiramate, and levetiracetam.

AED purchases were modeled to use periods for each person and for each ATC code during the follow-up with a validated PRE2DUP (from prescription drug purchase to drug use periods) method.²⁷ In brief, based on each person's purchase history for each ATC code, this method constructs continuous drug use periods, calculates sliding average of daily dose in defined daily doses, and combines purchases of the same drug by taking into account stockpiling, purchases regularity, dose changes, and periods of hospitalization or institutionalization.²⁸ After modeling for each drug substance, overlapping periods of AEDs were combined to retrieve time when any AED was used for use vs nonuse comparisons and similarly time on old vs new AED use.

Outcome

The primary outcome was all-cause mortality. Dates and causes of death were obtained from the causes of death register maintained by Statistics Finland. The register is compiled on the basis of death certificates, which are issued by physicians and if an autopsy is required, the death certificate is issued by a medicolegal officer after autopsy completion. Death certificates are delivered to the regional unit of the National Institute for Health and Welfare of the region where the decedent resided. A provincial medical officer confirms the correctness of the certificates before they are sent to Statistics Finland for registration. Causes of death are reported according to ICD-10 codes. In this study, cause-specific mortality was based on underlying causes of death, which are determined according to the selection and application rules of ICD-10 maintained by the WHO.

Confounders

Data on hospitalization-based confounders since 1996 until the index date were retrieved from the Care Register for Health Care on the basis of ICD-10 codes, whereas those based on entitlements to higher special reimbursements were defined as occurring ever after establishment of the Special Reimbursement register in 1972 until the index date.

From these registers, we identified the following comorbidities: stroke, ischemic heart disease, cardiac arrhythmias, hypertension, chronic heart failure, and peripheral arterial disease; and diabetes, chronic renal failure, asthma or chronic obstructive pulmonary disease, rheumatoid arthritis, epilepsy, head injuries, and hip fracture.

In addition, we considered mental comorbidities, such as schizophrenia, depression, or bipolar disorders, and substance abuse as confounders. Schizophrenia diagnoses were restricted to those that were diagnosed at least 5 years before AD. Substance abuse was defined as alcohol-induced chronic pancreatitis, mental and behavioral disorders due to psychoactive substance abuse, or substance abuse as a reason for admission.

Use of acetylcholinesterase inhibitors, memantine, antipsychotics, benzodiazepines and related drugs, antidepressants, nonsteroidal anti-inflammatory drugs (NSAIDs), statins, proton pump inhibitors, and antithrombotic agents within a 1-year period prior to the index date were identified from the PRE2DUP modeled drug use data.

Detailed definitions and classifications of confounders are provided in table e-2 (doi.org/10.5061/dryad.q3b38p9).

Statistical analyses

All analyses were performed with Stata (version 14; StataCorp, College Station, TX). Descriptive statistics are presented as means with SDs or frequencies with proportions.

The risk of death between AED users and nonusers was compared by Cox proportional hazards regression models. We used robust variance estimator in the models for AED user and nonuser comparisons to account for the matching. Proportional hazards assumptions were confirmed by exploring parallelism of log negative and log estimated survival curves for each covariate (figures e-1 through e-4, doi.org/10.5061/dryad.q3b38p9). Hazard ratios (HRs) with their corresponding 95% confidence intervals (CIs) were estimated by crude and confounder-adjusted models.

For control of confounding by indication and balance potential confounders between the comparison groups, the Cox models were weighted with inverse probability of treatment (IPT) weights based on propensity score. Selection of variables (table e-2, doi.org/10.5061/dryad.q3b38p9) for the IPT weights was based on their potential association with the outcome and the exposure. We estimated propensity score with logistic regression model as the conditional probability of AED use conditioned on the covariates measured at the baseline. Balancing properties of the IPT weighting (IPTW) between the AED users and matched nonusers were ascertained by comparing covariate distributions before and after IPTW using the standardized difference. Standardized difference >10% was considered as an indication of a meaningful difference.²⁹

In addition to all-cause mortality, we investigated cause-specific mortality. These analyses were restricted to diseases of the circulatory system (ICD10 codes I*), dementia and Alzheimer disease (ICD10 codes F01–F03 and G30–G31), and other diseases due to small proportion of causes of deaths due to other diseases.

All-cause mortality, according to the duration of AED use, was studied by dividing the duration of AED use into 4 periods: 1–90 days, 91–180 days, 181–365 days, and 366–1,095 days.

In drug–drug comparison (user only design), risk of death was compared between most frequently used AEDs, where users of multiple AEDs were excluded (n = 38). Valproic acid was chosen as a reference AED.

The main analyses included people with and without epilepsy. In order to exclude potential influence of epilepsy on mortality risk, we conducted sensitivity analyses after excluding people with epilepsy.

Data availability

The data used to conduct the research are available from the corresponding author but restrictions by the register maintainers and Finnish legislation apply to the availability of these data. Therefore the data are not publicly available. However, data are available from the authors upon reasonable request and with permission of the register maintainers.