Drug utilization analysis of osteoporosis medications in seven European electronic health databases

We studied the characteristics of patients prescribed osteoporosis medication and patterns of use in European databases. Patients were mostly female, older, had hypertension. There was suboptimal persistence particularly for oral medications. Our findings would be useful to healthcare providers to focus their resources on improving persistence to specific osteoporosis treatments.

PURPOSE

To characterise the patients prescribed osteoporosis therapy and describe the drug utilization patterns.

METHODS

We investigated the treatment patterns of bisphosphonates, denosumab, teriparatide, and selective estrogen receptor modulators (SERMs) in seven European databases in the United Kingdom, Italy, the Netherlands, Denmark, Spain, and Germany. In this cohort study, we included adults aged ≥ 18 years, with ≥ 1 year of registration in the respective databases, who were new users of the osteoporosis medications. The study period was between 01 January 2018 to 31 January 2022.

RESULTS

Overall, patients were most commonly initiated on alendronate. Persistence decreased over time across all medications and databases, ranging from 52-73% at 6 months to 29-53% at 12 months for alendronate. For other oral bisphosphonates, the proportion of persistent users was 50-66% at 6 months and decreased to 30-44% at 12 months. For SERMs, the proportion of persistent users at 6 months was 40-73% and decreased to 25-59% at 12 months. For parenteral treatment groups, the proportions of persistence with denosumab were 50-85% (6 month), 30-63% (12 month) and with teriparatide 40-75% (6 month) decreasing to 21-54% (12 month). Switching occurred most frequently in the alendronate group (2.8-5.8%) and in the teriparatide group (7.1-14%). Switching typically occurred in the first 6 months and decreased over time. Patients in the alendronate group most often switched to other oral or intravenous bisphosphonates and denosumab.

CONCLUSION

Our results show suboptimal persistence to medications that varied across different databases and treatment switching was relatively rare.

Global Epidemiology of Hip Fractures: Secular Trends in Incidence Rate, Post-Fracture Treatment, and All-Cause Mortality

In this international study, we examined the incidence of hip fractures, postfracture treatment, and all-cause mortality following hip fractures, based on demographics, geography, and calendar year. We used patient-level healthcare data from 19 countries and regions to identify patients aged 50 years and older hospitalized with a hip fracture from 2005 to 2018. The age- and sex-standardized incidence rates of hip fractures, post-hip fracture treatment (defined as the proportion of patients receiving anti-osteoporosis medication with various mechanisms of action [bisphosphonates, denosumab, raloxifene, strontium ranelate, or teriparatide] following a hip fracture), and the all-cause mortality rates after hip fractures were estimated using a standardized protocol and common data model. The number of hip fractures in 2050 was projected based on trends in the incidence and estimated future population demographics. In total, 4,115,046 hip fractures were identified from 20 databases. The reported age- and sex-standardized incidence rates of hip fractures ranged from 95.1 (95% confidence interval [CI] 94.8-95.4) in Brazil to 315.9 (95% CI 314.0-317.7) in Denmark per 100,000 population. Incidence rates decreased over the study period in most countries; however, the estimated total annual number of hip fractures nearly doubled from 2018 to 2050. Within 1 year following a hip fracture, post-hip fracture treatment ranged from 11.5% (95% CI 11.1% to 11.9%) in Germany to 50.3% (95% CI 50.0% to 50.7%) in the United Kingdom, and all-cause mortality rates ranged from 14.4% (95% CI 14.0% to 14.8%) in Singapore to 28.3% (95% CI 28.0% to 28.6%) in the United Kingdom. Males had lower use of anti-osteoporosis medication than females, higher rates of all-cause mortality, and a larger increase in the projected number of hip fractures by 2050. Substantial variations exist in the global epidemiology of hip fractures and postfracture outcomes. Our findings inform possible actions to reduce the projected public health burden of osteoporotic fractures among the aging population. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology

BACKGROUND AND OBJECTIVES

Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy.

STUDY DESIGN AND SETTING

Different covariate assessment periods (CAPs) did and did not include the month preceding treatment start were used to compute PS in the French claims database (Sytème National des Données de Santé-SNDS), and 1:1 match patients with metastatic castration resistant prostate cancer initiating abiraterone acetate or docetaxel. The 36-month survival was assessed.

RESULTS

Among 1, 213 docetaxel and 2, 442 abiraterone initiators, the PS distribution resulting from the CAP [-12; 0 months] distinctly separated populations (c = 0.93; 273 matched pairs). The CAPs [-12;-1 months] identified 765 pairs (c = 0.81). Strong docetaxel treatment predictors during the month before treatment start were implantable delivery systems (1% vs. 59%), which fulfilled IV conditions. The 36-month survival was not meaningfully different under the [-12; 0 months] CAP but differed by 10% points (38% vs. 28%) after excluding month -1.

CONCLUSION

In the setting of highly predictive pretreatment procedures, excluding the immediate pre-exposure time from the CAP will reduce the risk of including potential IVs in PS models and may reduce bias.

Budget Impact of Tyrosine Kinase Inhibitor Discontinuation in Chronic Myeloid Leukemia With Sustained Deep Molecular Response

OBJECTIVES

Tyrosine kinase inhibitors (TKIs) account for the vast majority of healthcare expenditure on patients with chronic myeloid leukemia (CML), and it has been demonstrated that TKI discontinuation in patients in long-term deep molecular remission (DMR) is safe and improves quality of life. Our objective was to estimate the budget impact of TKI discontinuation in CML patients in long-term DMR from the perspective of the French healthcare system.

METHODS

This analysis was conducted over a 5-year time horizon using a Markov model with cycles of 6 months. Transition probabilities were estimated through systematic reviews and meta-analyses. Costs were estimated from the French National Claims Database. Monte Carlo simulations were performed to take into account the uncertainty surrounding model parameters. Sensitivity analyses were carried out by varying the size of the target population and the cost of TKIs.

RESULTS

Over a 5-year period and for a target population of 100 patients each year eligible and agreeing to stop TKI, the TKI discontinuation strategy would save €25.5 million (95% confidence interval -39.3 to 70.0). In this model, the probability that TKI discontinuation would be more expensive than TKI continuation was 12.0%. In sensitivity analyses, mean savings ranged from €14.9 million to €62.9 million.

CONCLUSIONS

This study provides transparent, reproducible, and interpretable results for healthcare professionals and policy makers. Our results clearly show that innovative healthcare strategies can benefit both the healthcare system and patients. Savings from generalizing TKI discontinuation in CML patients in sustained DMR should yield health gains for other patients.

Intra-database validation of case-identifying algorithms using reconstituted electronic health records from healthcare claims data

BACKGROUND

Diagnosis performances of case-identifying algorithms developed in healthcare database are usually assessed by comparing identified cases with an external data source. When this is not feasible, intra-database validation can present an appropriate alternative.

OBJECTIVES

To illustrate through two practical examples how to perform intra-database validations of case-identifying algorithms using reconstituted Electronic Health Records (rEHRs).

METHODS

Patients with 1) multiple sclerosis (MS) relapses and 2) metastatic castration-resistant prostate cancer (mCRPC) were identified in the French nationwide healthcare database (SNDS) using two case-identifying algorithms. A validation study was then conducted to estimate diagnostic performances of these algorithms through the calculation of their positive predictive value (PPV) and negative predictive value (NPV). To that end, anonymized rEHRs were generated based on the overall information captured in the SNDS over time (e.g. procedure, hospital stays, drug dispensing, medical visits) for a random selection of patients identified as cases or non-cases according to the predefined algorithms. For each disease, an independent validation committee reviewed the rEHRs of 100 cases and 100 non-cases in order to adjudicate on the status of the selected patients (true case/ true non-case), blinded with respect to the result of the corresponding algorithm.

RESULTS

Algorithm for relapses identification in MS showed a 95% PPV and 100% NPV. Algorithm for mCRPC identification showed a 97% PPV and 99% NPV.

CONCLUSION

The use of rEHRs to conduct an intra-database validation appears to be a valuable tool to estimate the performances of a case-identifying algorithm and assess its validity, in the absence of alternative.

P1664Pharmacological treatment patterns in heart failure: a real world cohort study

Background

Although the efficacy and safety of existing therapies of heart failure (HF) have been demonstrated in clinical trials in the last 35 years, little is known about the treatment patterns of HF in clinical practice, especially in France.

Objectives

To describe the treatment initiation patterns and the subsequent treatment changes among HF patients, in the first year following an incident hospitalisation for HF, in a French real-world setting.

Methods

A cohort of patients aged 40 years old and older, with an incident hospitalisation for HF between January 1, 2008 and December 31, 2013, was identified in the EGB, a 1/97 permanent random sample of the French nationwide claims database. All patients who died during the index hospitalization or with a period of at least 3 consecutive months with no healthcare dispensing recorded were excluded. All included patients were followed one year. HF drugs of interest were: beta blockers (BB), angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARBs), aldosterone antagonists (AA), diuretics, digoxin or ivabradine. Drug exposure was assessed quarterly using a Proportion of Days Covered >66% (>60 days out of the 90 days of the quarter covered by the treatment of interest), by considering HF drugs individually or in combination. Drug changes were assessed between each quarter over the first year of follow-up.

Results

Between 2008 and 2013, 7,387 from the EGB were included in the cohort study. The mean age at baseline was 77.7 years (±12.0 years) and 51.6% were women. During the follow-up, 24.4% of patients died and 20% did not receive any HF treatment. During the first quarter following initial hospitalisation, 42.7% of patients had diuretics, 26.0% had BB, 25.7% had ACEI, 7.4% had ARB, 7.6% had AA, 4.7% had digoxin and 1.3% had ivabradine. the most frequent combination was BB/ACE/ARB (23.4%). These proportions remained globally constant in each quarter of the follow-up. The main change occurred between thee first and the second quarter and concerned 53.1% of the initially untreated patients; by the second quarter, 22.2% of them initiated a BB/ACI/ARB combination, 13% a diuretic alone, 7.4% a BB and 4.9% a BB/ACI/ARB/AA combination.

Conclusion

This study provides precious information on treatment patterns after an initial hospital admission for HF at a time when new treatments for HF are emerging.

Acknowledgement/Funding

None

[Pharmacoepidemiology: how to assess medicines in real-life setting?]

Pharmacoepidemiology : how to assess use and effects of medicines in real-life setting ? Pharmacoepidemiology is a recently developed field of pharmacology defined as « the study of drug uses, benefits, and adverse effects in population, with the aim of improving public health ». In drugs post-marketing assessment, its objectives are to study drugs real patterns of use, and to identify and quantify the risks associated to their use and the benefit they provide in settings that hugely differ from those of clinical trials. The methods employed are mostly common with that used in classical epidemiology, even specific biases led to the development of particular techniques. If pharmacoepidemiology has been strongly developed and sustained over the past decades in Anglo- Saxon and Northern Europe countries, its concrete emergence is much more recent in France. Indeed, it is only in the past years that it was effectively integrated to French post-marketing drug monitoring and promoted as a research field, essentially under the impetus of the French drug agency.

False-positive results in pharmacoepidemiology and pharmacovigilance

False-positive constitute an important issue in scientific research. In the domain of drug evaluation, it affects all phases of drug development and assessment, from the very early preclinical studies to the late post-marketing evaluations. The core concern associated with this false-positive is the lack of replicability of the results. Aside from fraud or misconducts, false-positive is often envisioned from the statistical angle, which considers them as a price to pay for type I error in statistical testing, and its inflation in the context of multiple testing. If envisioning this problematic in the context of pharmacoepidemiology and pharmacovigilance however, that both evaluate drugs in an observational settings, information brought by statistical testing and the significance of such should only be considered as additional to the estimates provided and their confidence interval, in a context where differences have to be a clinically meaningful upon everything, and the results appear robust to the biases likely to have affected the studies. In the following article, we consequently illustrate these biases and their consequences in generating false-positive results, through studies and associations between drug use and health outcomes that have been widely disputed.

Risk of mortality with concomitant use of tamoxifen and selective serotonin reuptake inhibitors: multi-database cohort study

OBJECTIVE

 To compare differences in mortality between women concomitantly treated with tamoxifen and selective serotonin reuptake inhibitors (SSRIs) that are potent inhibitors of the cytochrome-P450 2D6 enzyme (CYP2D6) versus tamoxifen and other SSRIs.

DESIGN

 Population based cohort study.

SETTING

 Five US databases covering individuals enrolled in private and public health insurance programs from 1995 to 2013.

PARTICIPANTS

 Two cohorts of women who started taking tamoxifen. In cohort 1, women started taking an SSRI during tamoxifen treatment. In cohort 2, women were already taking an SSRI when they started taking tamoxifen.

MAIN OUTCOME MEASURES

 All cause mortality in each cohort in women taking SSRIs that are potent inhibitors of CYP2D6 (paroxetine, fluoxetine) versus other SSRIs. Propensity scores were used to match exposure groups in a variable ratio fashion. Results were measured separately for each cohort and combined hazard ratios calculated from Cox regression models across the two cohorts with random effects meta-analysis.

RESULTS

 There were 6067 and 8465 new users of tamoxifen in cohorts 1 and 2, respectively. Mean age was 55. A total of 991 and 1014 deaths occurred in cohorts 1 and 2 during a median follow-up of 2.2 (interquartile range 0.9-4.5) and 2.0 (0.8-3.9) years, respectively. The pooled hazard ratio for death for potent inhibitors (rate 58.6/1000 person years) compared with other SSRIs (rate 57.9/1000 person years) across cohorts 1 and 2 was 0.96 (95% confidence interval 0.88 to 1.06). Results were consistent across sensitivity analyses.

CONCLUSION

 Concomitant use of tamoxifen and potent CYP2D6 inhibiting SSRIs versus other SSRIs was not associated with an increased risk of death.

Pharmacological treatments of cardiovascular diseases: Evidence from real-life studies

The management of chronic cardiovascular diseases has evolved greatly in the last decades. Over the last thirty years, the management of acute coronary syndrome has improved, leading to an important lowering of the mortality in the acute phase of the event. Consequently, the optimal management of the secondary prevention of acute coronary syndrome has greatly evolved. Moreover, the increased number of pharmacological alternatives for patients affected by chronic heart failure and by non-valvular atrial fibrillation reserves a number of challenges for their correct management. Moreover, these diseases are without any reasonable doubt the largest contributor to global mortality in the present and will continue to be it in the future. The aim of this study was to provide the most updated information of the real-life drug use and their effectiveness. This review was performed to assess the potential knowledge gaps in the treatments of these diseases and to indicate potential perspective of pharmaco-epidemiological research in this area.