Pharmacoepidemiological methods for computing the duration of pharmacological prescriptions using secondary data sources

Association between long-term statin use and cataract surgery: a nationwide study on 505 105 cataract surgery patients

AIMS

To assess the association between statin use and cataract surgery according to different statin treatment durations in patients with different cardiovascular risk profiles.

METHODS AND RESULTS

We performed a nested case-control study using Danish registries, covering the period from 1 January 1996 to 31 December 2020. We defined cases as surgically treated cataract patients, matched in a 1:1 ratio by sex and age with controls not undergoing cataract surgery. The exposure of interest was statin use in different durations (1, 5 and 10 years) compared with never use of statins. Conditional logistic regression provided adjusted HRs and corresponding 95% CIs in subgroups defined by established atherosclerotic cardiovascular disease, diabetes, hypertension and individuals without these comorbidities. We identified 505 150 cataract surgery cases and found no increased HR of cataract surgery with statin treatment at any duration in any of the subgroups with established atherosclerotic cardiovascular disease, diabetes or hypertension.

CONCLUSION

Our findings do not support a possible association between long-term statin use and cataract in patients with established atherosclerotic cardiovascular disease, diabetes or hypertension. Although we found an association between statin use and cataract in individuals without these comorbidities, increasing durations of statin use did not yield higher cataract surgery rates.

Smaller Differences in the Comparative Effectiveness of Biologics in Reducing Asthma-Related Hospitalizations Compared With Overall Exacerbations

BACKGROUND

Evidence on the comparative effectiveness of respiratory biologics remains sparse.

OBJECTIVE

We sought to evaluate the comparative effectiveness of omalizumab, mepolizumab, benralizumab, and dupilumab in a matched retrospective cohort of patients with asthma.

METHODS

We identified patients with asthma aged ≥18 years who were incident users of these biologics between November 1, 2018, and June 30, 2023, in administrative claims data from the Food and Drug Administration's Sentinel System and Merative MarketScan Commercial Database. We compared asthma-related exacerbations and hospitalizations in the 12 months since biologic prescription in pairwise comparisons of propensity score-matched cohorts. Covariates used in matching included age, sex, allergic comorbidities, baseline asthma medications use, and the Charlson Comorbidity Index. Incidence rate ratios (IRR) and 95% confidence intervals (CI) were estimated using negative binomial regression models.

RESULTS

A total of 893 patients on mepolizumab, 1300 on benralizumab, 1170 on omalizumab, and 1863 on dupilumab were identified. The average age was 55 years, and two-thirds of the participants were female. At baseline, over 80% of these individuals had an active prescription for an inhaled corticosteroid. Almost half of patients on dupilumab had concomitant nasal polyposis compared with 6% to 13% of patients on the other biologics. Covariates were balanced after matching. In matched analyses, dupilumab was associated with the lowest incidence of exacerbations over the follow-up period (vs dupilumab): mepolizumab (IRR: 1.36; 95% CI: 1.12, 1.64), omalizumab (IRR: 1.33; 95% CI: 1.13, 1.58), benralizumab (IRR: 1.19; 95% CI: 1.00, 1.41). For exacerbations leading to hospitalizations, benralizumab and mepolizumab were associated with the lowest incidence of hospitalizations, and the greatest difference was between mepolizumab versus dupilumab (IRR: 0.76; 95% CI: 0.56, 1.03).

CONCLUSIONS

Dupilumab was associated with the lowest incidence of overall exacerbations, and mepolizumab with the lowest incidence of asthma hospitalizations in this administrative claims-based cohort of individuals with asthma. Despite matching propensity scores, residual confounding, such as baseline eosinophil count, may explain some of these findings.

Comparing major and mild cognitive impairment risks in older type-2 diabetic patients: a Danish register-based study on dipeptidyl peptidase-4 inhibitors vs. glucagon-like peptide-1 analogues

INTRODUCTION

The prevalence of major and mild cognitive impairment (CI) in type-2 diabetes older patients is 15-25% and 30-60%, respectively, thus affecting quality of life and health outcomes. There is, therefore, the need of head-to-head studies aiming at identifying the optimal treatment for individuals with type-2 diabetes at increased risk of mild and major CI. This study focuses on the risk of developing mild and major CI in Danish patients treated with dipeptidyl peptidase-4 inhibitors (DPP-4i) and glucagon-like peptide-1 analogues (GLP-1a) using administrative and healthcare registers.

METHODS

An active comparator design with a 3-year follow-up period was used. The main outcome was the hospital admission with a diagnosis of mild CI or major CI. Multivariate Cox Regression analysis was performed using the high-dimensional propensity score to obtain adjusted Hazard Ratio (HR) estimates. Inverse probability of treatment weighting (IPTW) and marginal structured model were used to calculate risk differences while accounting for the variations of confounders throughout the follow-up period.

RESULTS

Our results show a significant higher risk of major CI between DPP-4i and GLP-1a in unadjusted [HR (95% CI) = 3.13 (2.45-4.00), p < 0.001] and adjusted analyses [HR (95% CI) = 1.58 (1.22-2.06), p = 0.001]. No statistically significant differences were observed for mild CI. IPTW resulted stable throughout the follow-up period. Marginal structure modeling (β (95% CI) = 0.022 (0.020-0.024), p < 0.001) resulted in a higher risk of major CI for DPP-4i when compared to GLP-1a.

DISCUSSION

DPP-4i was associated with an increased risk of developing major CI when compared to GLP-1a among older individuals with type-2 diabetes.

Persistence and adherence with Latanoprost: A Danish register-based cohort study in older patients with glaucoma

PURPOSE

This study aims to assess the association between switching patterns and adherence/persistence in Danish patients over the age of 65, who started their first-ever glaucoma treatment with latanoprost eye drops.

METHODS

Patients were assigned to three different cohorts: (1) switchers, (2) non-switchers, and (3) preservative-free latanoprost (Monoprost®) users. Patients were followed for 1 year until the end of data coverage or censoring. Study covariates were used to compute the propensity score. In the adjusted analysis, the propensity score was added to the model as an independent variable. The Cox regression model was used to calculate the hazard ratio (HR) of discontinuation for the three cohorts (the non-switchers cohort was the reference level) in both adjusted and unadjusted analyses.

RESULTS

Non-switchers had a statistically significant lower adherence (proportion of days covered, PDC 92%) than switchers (PDC 96%; p < 0.001) and users of Monoprost® (PDC 99%; p < 0.001). Switchers had a 53% lower risk of treatment discontinuation compared to the reference group within 1 year after the first redemption of latanoprost in both unadjusted (HR 0.47; 95% Confidence interval, 95% CI: 0.41-0.53; p < 0.001) and adjusted (HR 0.47; 95% CI: 0.42-0.53; p < 0.001) analyses. In comparison to the non-switchers, Monoprost® users had a 78% lower risk for the above result in both unadjusted (HR 0.22; 95% CI: 0.17-0.28; p < 0.001) and adjusted (HR 0.22; 95% CI: 0.17-0.29; p < 0.001) analyses.

CONCLUSION

This study found increased adherence and persistence in latanoprost users among those who redeemed preservative-free latanoprost (Monoprost®) and among those who switched between different latanoprost formulations.

Menopausal hormone therapy and central nervous system tumors: Danish nested case-control study

BACKGROUND

Use of estrogen-containing menopausal hormone therapy has been shown to influence the risk of central nervous system (CNS) tumors. However, it is unknown how the progestin-component affects the risk and whether continuous versus cyclic treatment regimens influence the risk differently.

METHODS AND FINDINGS

Nested case-control studies within a nationwide cohort of Danish women followed for 19 years from 2000 to 2018. The cohort comprised 789,901 women aged 50 to 60 years during follow-up, without prior CNS tumor diagnosis, cancer, or contraindication for treatment with menopausal hormone therapy. Information on cumulative exposure to female hormonal drugs was based on filled prescriptions. Statistical analysis included educational level, use of antihistamines, and use of anti-asthma drugs as covariates. During follow-up, 1,595 women were diagnosed with meningioma and 1,167 with glioma. The median (first-third quartile) follow-up time of individuals in the full cohort was 10.8 years (5.0 years to 17.5 years). Compared to never-use, exposure to estrogen-progestin or progestin-only were both associated with increased risk of meningioma, hazard ratio (HR) 1.21; (95% confidence interval (CI) [1.06, 1.37] p = 0.005) and HR 1.28; (95% CI [1.05, 1.54] p = 0.012), respectively. Corresponding HRs for glioma were HR 1.00; (95% CI [0.86, 1.16] p = 0.982) and HR 1.20; (95% CI [0.95, 1.51] p = 0.117). Continuous estrogen-progestin exhibited higher HR of meningioma 1.34; (95% CI [1.08, 1.66] p = 0.008) than cyclic treatment 1.13; (95% CI [0.94, 1.34] p = 0.185). Previous use of estrogen-progestin 5 to 10 years prior to diagnosis yielded the strongest association with meningioma, HR 1.26; (95% CI [1.01, 1.57] p = 0.044), whereas current/recent use of progestin-only yielded the highest HRs for both meningioma 1.64; (95% CI [0.90, 2.98] p = 0.104) and glioma 1.83; (95% CI [0.98, 3.41] p = 0.057). Being an observational study, residual confounding could occur.

CONCLUSIONS

Use of continuous, but not cyclic estrogen-progestin was associated with increased meningioma risk. There was no evidence of increased glioma risk with estrogen-progestin use. Use of progestin-only was associated with increased risk of meningioma and potentially glioma. Further studies are warranted to evaluate our findings and investigate the influence of long-term progestin-only regimens on CNS tumor risk.

Central nervous system tumours among users of vaginal oestradiol tablets: A nationwide population-based study

BACKGROUND AND PURPOSE

It is currently unknown whether vaginal oestradiol is associated with development of meningioma and glioma. The aim of this study was to examine associations between cumulative use and treatment intensity of vaginally administered oestradiol tablets and incidence of meningioma and glioma in a nationwide, population-based study.

METHODS

We conducted a nested case-control study within a nationwide cohort of Danish women followed from 2000 to 2018. The cohort consisted of 590,676 women aged 50-60 years at study start, without prior cancer diagnosis or use of systemic hormone therapy. Information on cumulative dose, duration, and intensity of vaginal oestradiol tablet use was assessed from filled prescriptions. Conditional logistic regression provided adjusted hazard ratios (HRs) for the association between vaginal oestradiol use and diagnosis of meningioma or glioma.

RESULTS

We identified 1108 women with meningioma and 835 with glioma. Of these, 19.8% and 14.0% used vaginal oestradiol tablets, respectively. The HRs in those with ever-use of vaginal oestradiol tablets was 1.14 (95% confidence interval [CI] 0.97-1.34) for meningioma and 0.90 (95% CI 0.73-1.11) for glioma. The corresponding HRs for new users exclusively were 1.18 (95% CI 0.99-1.40) for meningioma and 0.89 (95% CI 0.71-1.13) for glioma. Intensity of vaginal oestradiol tablet use according to duration and user status yielded slightly elevated HRs for meningioma without an apparent dose-response pattern, while the HRs for glioma were generally below unity. Among new users, the HR with high intensity of current or recent vaginal oestradiol tablet use for 2+ years was 1.66 (95% CI 1.09-2.55) for meningioma and 0.77 (95% CI 0.41-1.44) for glioma.

CONCLUSION

Use of vaginal oestradiol tablets was associated with a slightly increased incidence of meningioma but not of glioma. Owing to the observational nature of the study, residual bias cannot be ruled out.

Asthma and COPD: Comparison with International Guidelines and Medication Adherence in Belgium

Asthma and chronic obstructive pulmonary disease (COPD) are major chronic conditions. It is possible to limit their impact by controlling symptoms, which limits exacerbations and worsening of the disease, by choosing the appropriate treatment and ensuring that the patient adheres to it. The main purpose of this study was to assess medication adherence and persistence with inhaled medications for chronic treatment of asthma and COPD, as well as to evaluate the factors influencing this adherence. Medication adherence was measured from January 2013 to December 2016 using continuous multiple-interval measures of medication availability (CMA). Persistence was evaluated by treatment episodes (TE). We analyzed the influence of different factors on CMA such as sex, age, type of device, and the realization of the "new medicines service" (NMS), introduced in Belgium in October 2013 to support patients in adhering to their treatment. We also analyzed the consumption of these inhaled medications within the Belgian population and compared them with the Global Initiative for Asthma (GINA) and the Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations. Medication adherence varied greatly between the different pharmacological classes: inhaled corticosteroids (ICS) alone or in combination with long-acting beta agonists (LABA) had the lowest medication adherence and persistence, while adherence was highest for the long-acting muscarinic antagonists (LAMA) and LABA/LAMA associations. The NMS seemed to have a positive impact on medication adherence, although few patients completed the two guidance interviews offered by the service. In addition, only a minority of the targeted patients took advantage of this new service.

Prenatal Antidepressant Exposure and the Risk of Attention-Deficit/Hyperactivity Disorder in Childhood: Accounting for Misclassification of Exposure

BACKGROUND

Many studies of prenatal antidepressant exposure and the risk of attention-deficit/hyperactivity disorder (ADHD) have done little to reduce bias from exposure misclassification. We assessed the prenatal antidepressant-ADHD effect by incorporating information on repeatedly redeemed prescriptions and redemptions of drug classes commonly used in pregnancy in the analyses to reduce bias from exposure misclassification.

METHODS

Using population-based registries, we conducted a nationwide cohort study of all children born in Denmark from 1997 to 2017. In a former-user analysis, we compared children prenatally exposed, defined by a redeemed prescription by the mother during pregnancy, to a comparison cohort consisting of prenatally unexposed children whose mothers had redeemed a prescription before pregnancy. We incorporated information on repeatedly redeemed prescriptions and redemptions of drug classes commonly used in pregnancy in the analyses to reduce bias from exposure misclassification. We used incidence rate ratios (IRRs) and incidence rate differences (IRDs) as effect measures.

RESULTS

The cohort included 1,253,362 children, among whom 24,937 were prenatally exposed to antidepressants. The comparison cohort consisted of 25,698 children. During follow-up, 1,183 exposed children and 1,291 children in the comparison cohort developed ADHD yielding an IRR of 1.05 (95% confidence interval [CI] = 0.96, 1.15) and an IRD of 0.28 (95% CI = -0.20, 0.80) pr. 1,000 person-years. IRRs from analyses attempting to reduce exposure misclassification varied from 1.03 to 1.07.

CONCLUSIONS

Our results were not consistent with the hypothesized effect of prenatal antidepressant exposure on the risk of ADHD. Attempts to reduce exposure misclassification did not alter this finding.

Menopausal hormone therapy and dementia: nationwide, nested case-control study

OBJECTIVES

To assess the association between use of menopausal hormone therapy and development of dementia according to type of hormone treatment, duration of use, and age at usage.

DESIGN

Nationwide, nested case-control study.

SETTING

Denmark through national registries.

PARTICIPANTS

5589 incident cases of dementia and 55 890 age matched controls were identified between 2000 and 2018 from a population of all Danish women aged 50-60 years in 2000 with no history of dementia or contraindications for use of menopausal hormone therapy.

MAIN OUTCOME MEASURES

Adjusted hazard ratios with 95% confidence intervals for all cause dementia defined by a first time diagnosis or first time use of dementia specific medication.

RESULTS

Compared with people who had never used treatment, people who had received oestrogen-progestogen therapy had an increased rate of all cause dementia (hazard ratio 1.24 (95% confidence interval 1.17 to 1.33)). Increasing durations of use yielded higher hazard ratios, ranging from 1.21 (1.09 to 1.35) for one year or less of use to 1.74 (1.45 to 2.10) for more than 12 years of use. Oestrogen-progestogen therapy was positively associated with development of dementia for both continuous (1.31 (1.18 to 1.46)) and cyclic (1.24 (1.13 to 1.35)) regimens. Associations persisted in women who received treatment at the age 55 years or younger (1.24 (1.11 to 1.40)). Findings persisted when restricted to late onset dementia (1.21 (1.12 to 1.30)) and Alzheimer's disease (1.22 (1.07 to 1.39)).

CONCLUSIONS

Menopausal hormone therapy was positively associated with development of all cause dementia and Alzheimer's disease, even in women who received treatment at the age of 55 years or younger. The increased rate of dementia was similar between continuous and cyclic treatment. Further studies are warranted to determine whether these findings represent an actual effect of menopausal hormone therapy on dementia risk, or whether they reflect an underlying predisposition in women in need of these treatments.

A novel approach for pharmacological substantiation of safety signals using plasma concentrations of medication and administrative/healthcare databases: a case study using Danish registries for an FDA warning on lamotrigine

PHARMACOM-EPI is a novel framework to predict plasma concentrations of drugs at the time of occurrence of clinical outcomes. In early 2021, the U.S. Food and Drug Administration (FDA) issued a warning on the antiseizure drug lamotrigine claiming that it has the potential to increase the risk of arrhythmias and related sudden cardiac death due to a pharmacological sodium channel-blocking effect. We hypothesized that the risk of arrhythmias and related death is due to toxicity. We used the PHARMACOM-EPI framework to investigate the relationship between lamotrigine's plasma concentrations and the risk of death in older patients using real-world data. Danish nationwide administrative and healthcare registers were used as data sources and individuals aged 65 years or older during the period 1996 - 2018 were included in the study. According to the PHARMACOM-EPI framework, plasma concentrations of lamotrigine were predicted at the time of death and patients were categorized into non-toxic and toxic groups based on the therapeutic range of lamotrigine (3-15mg/L). Over 1 year of treatment, the incidence rate ratio (IRR) of all-cause mortality was calculated between the propensities score matched toxic and non-toxic groups. In total, 7286 individuals were diagnosed with epilepsy and were exposed to lamotrigine, 432 of which had at least one plasma concentration measurement The pharmacometric model by Chavez et al. was used to predict lamotrigine's plasma concentrations considering the lowest absolute percentage error among identified models (14.25%, 95% CI: 11.68-16.23). The majority of lamotrigine associated deaths were cardiovascular-related and occurred among individuals with plasma concentrations in the toxic range. The IRR of mortality between the toxic group and non-toxic group was 3.37 [95% CI: 1.44-8.32] and the cumulative incidence of all-cause mortality exponentially increased in the toxic range. Application of our novel framework PHARMACOM-EPI provided strong evidence to support our hypothesis that the increased risk of all-cause and cardiovascular death was associated with a toxic plasma concentration level of lamotrigine among older lamotrigine users.

β-blocker adherence among patients with congenital long QT syndrome: a nationwide study

AIM

β-blockers are the first line of treatment in patients with congenital long QT syndrome (cLQTS) (class I or II recommendation) in order to prevent malignant arrhythmias. Hence, we examined long-term β-blocker adherence and associated risk factors among patients with cLQTS.

METHODS AND RESULTS

Danish patients with cLQTS claiming a prescription for any β-blocker after their cLQTS diagnosis were identified using data from nationwide registries and specialized inherited cardiac disease clinics (1995-2017). Patients were followed for up to 5 years. Treatment breaks >60 days were assessed (i.e. proxy for reduced adherence). Multivariable Cox regression was used to identify risk factors associated with breaks of >60 days in β-blocker treatment. Overall, 500 out of 633 (79%) patients with cLQTS claimed at least one prescription for any β-blocker after cLQTS diagnosis. During follow-up, 38.4% had a treatment break. Risk factors significantly associated with treatment breaks were implantable cardioverter defibrillator (ICD) [hazard ratio (HR) = 1.65, 95% confidence interval (CI): 1.08-2.53], β-blocker side effects (HR = 2.69, 95% CI: 1.75-4.13), and psychiatric disease (HR = 1.63, 95% CI: 1.04-2.57). In contrast, patients presenting with ventricular tachycardia/syncope as cLQTS disease manifestation were less likely to have a treatment break compared with asymptomatic patients (HR = 0.55, 95% CI: 0.33-0.92).

CONCLUSION

Reduced β-blocker adherence was common with more than a third of patients having a treatment break >60 days after cLQTS diagnosis. Patients with psychiatric disease, self-reported β-blocker side effects, and an ICD were more likely to display reduced adherence, whereas a severe cLQTS disease manifestation was associated with optimal β-blocker adherence.

A machine-learning guided method for predicting add-on and switch in secondary data sources: A case study on anti-seizure medications in Danish registries

Purpose: There is a lack of available evidence regarding the treatment pattern of switches and add-ons for individuals aged 65 years or older with epilepsy during the first years from the time they received their first anti-seizure medication because of the lack of valid methods. Therefore, this study aimed to develop an algorithm for identifying switches and add-ons using secondary data sources for anti-seizure medication users. Methods: Danish nationwide databases were used as data sources. Residents in Denmark between 1996 and 2018 who were diagnosed with epilepsy and redeemed their first prescription for anti-seizure medication after epilepsy diagnosis were followed up for 730 days until the end of the follow-up period, death, or emigration to assess switches and add-ons occurred during the follow-up period. The study outcomes were the overall accuracy of the classification of switch or add-on of the newly developed algorithm. Results: In total, 15870 individuals were included in the study population with a median age of 72.9 years, of whom 52.0% were male and 48.0% were female. A total of 988 of the 15879 patients from the study population were present during the 730-day follow-up period, and 988 individuals (6.2%) underwent a total of 1485 medication events with co-exposure to two or more anti-seizure medications. The newly developed algorithmic method correctly identified 9 out of 10 add-ons (overall accuracy 92%) and 9 out of 10 switches (overall accuracy 88%). Conclusion: The majority of switches and add-ons occurred early during the first 2 years of disease and according to clinical recommendations. The newly developed algorithm correctly identified 9 out of 10 switches/add-ons.

Artificial Neural Network vs. Pharmacometric Model for Population Prediction of Plasma Concentration in Real-World Data: A Case Study on Valproic Acid

We compared the predictive performance of an artificial neural network to traditional pharmacometric modeling for population prediction of plasma concentrations of valproate in real-world data. We included individuals aged 65 years or older with epilepsy who redeemed their first prescription of valproate after the diagnosis of epilepsy and had at least one valproate plasma concentration measured. A long short-term memory neural network (LSTM) was developed using the training data set to fit the LSTM and the test data set to validate the model. Predictions from the LSTM were compared with those obtained from the population predictions from a pharmacometric model by Birnbaum et al. which had the best predictive performance for population predictions of valproate concentrations in Danish databases. We used the cutoff of ± 20 mg/L of prediction error to define good predictions. A total of 1,252 individuals were included in the study. The LSTM fitted using the training data set had poor predictive performance in the test data set, but better than that of the pharmacometric model. The proportion of individuals with at least one predicted concentration within ± 20 mg/L of observed concentration was largest in case of the LSTM (64.4%, 95% confidence interval (CI): 58.4-70.2%) compared with the pharmacometric model by Birnbaum et al. (49.8%, 95% CI: 47.0-52.6%). LSTM shows better predictive performance to predict valproate plasma concentrations compared with a traditional pharmacometric model in the investigated setting with real-world data in older patients with epilepsy where information on exact timepoints for both dosing and plasma concentration measurement are missing.

Rationale and performances of a data-driven method for computing the duration of pharmacological prescriptions using secondary data sources

The assessment of the duration of pharmacological prescriptions is an important phase in pharmacoepidemiologic studies aiming to investigate persistence, effectiveness or safety of treatments. The Sessa Empirical Estimator (SEE) is a new data-driven method which uses k-means algorithm for computing the duration of pharmacological prescriptions in secondary data sources when this information is missing or incomplete. The SEE was used to compute durations of exposure to pharmacological treatments where simulated and real-world data were used to assess its properties comparing the exposure status extrapolated with the method with the “true” exposure status available in the simulated and real-world data. Finally, the SEE was also compared to a Researcher-Defined Duration (RDD) method. When using simulated data, the SEE showed accuracy of 96% and sensitivity of 96%, while when using real-world data, the method showed sensitivity ranging from 78.0 (nortriptyline) to 95.1% (propafenone). When compared to the RDD, the method had a lower median sensitivity of 2.29% (interquartile range 1.21–4.11%). The SEE showed good properties and may represent a promising tool to assess exposure status when information on treatment duration is not available.

The PHARMACOM-EPI Framework for Integrating Pharmacometric Modelling Into Pharmacoepidemiological Research Using Real-World Data: Application to Assess Death Associated With Valproate

In pharmacoepidemiology, it is usually expected that the observed association should be directly or indirectly related to the pharmacological effects of the drug/s under investigation. Pharmacological effects are, in turn, strongly connected to the pharmacokinetic and pharmacodynamic properties of a drug, which can be characterized and investigated using pharmacometric models. Recently, the use of pharmacometrics has been proposed to provide pharmacological substantiation of pharmacoepidemiological findings derived from real-world data. However, validated frameworks suggesting how to combine these two disciplines for the aforementioned purpose are missing. Therefore, we propose PHARMACOM-EPI, a framework that provides a structured approach on how to identify, characterize, and apply pharmacometric models with practical details on how to choose software, format dataset, handle missing covariates/dosing data, how to perform the external evaluation of pharmacometric models in real-world data, and how to provide pharmacological substantiation of pharmacoepidemiological findings. PHARMACOM-EPI was tested in a proof-of-concept study to pharmacologically substantiate death associated with valproate use in the Danish population aged ≥ 65 years. Pharmacological substantiation of death during a follow-up period of 1 year showed that in all individuals who died (n = 169) individual predictions were within the subtherapeutic range compared with 52.8% of those who did not die (n = 1,084). Of individuals who died, 66.3% (n = 112) had a cause of death possibly related to valproate and 33.7% (n = 57) with well-defined cause of death unlikely related to valproate. This proof-of-concept study showed that PHARMACOM-EPI was able to provide pharmacological substantiation for death associated with valproate use in the study population.