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

Design and validation of algorithms to identify venous thromboembolism in the French National Healthcare Database

PURPOSE

This paper aims to introduce an algorithm designed to identify Venous Thromboembolism (VTE) in the French National Healthcare Database (SNDS) and to estimate its positive predictive value.

METHODS

A case-identifying algorithm was designed using SNDS inpatient and outpatient encounters, including hospital stays with discharge diagnoses, imaging procedures and drugs dispensed, of French patients aged at least 18 years old to whom baricitinib or Tumor Necrosis Factor Inhibitors (TNFi) were dispensed between September 1, 2017, and December 31, 2018. An intra-database validation study was then conducted, drawing 150 cases identified as VTE by the algorithm and requesting four vascular specialists to assess them. Patient profiles used to conduct the case adjudication were reconstituted from de-identified pooled and formatted SNDS data (i.e., reconstituted electronic health records-rEHR) with a 6-month look-back period prior to the supposed VTE onset and a 12-month follow-up period after. The positive predictive value (PPV) with its 95% confidence interval (95% CI) was calculated as the number of expert-confirmed VTE divided by the number of algorithm-identified VTE. The PPV and its 95% CI were then recomputed among the same patient set initially drawn, once the VTE-identifying algorithm was updated based on expert recommendation.

RESULTS

For the 150 patients identified with the first VTE-identifying algorithm, the adjudication committee confirmed 92 cases, resulting in a PPV of 61% (95% CI = [54-69]). The final VTE-identifying algorithm including expert suggestions showed a PPV of 92% (95% CI = [86-98]) with a total of 87 algorithm-identified cases, including 80 retrieved from the 92 confirmed by experts.

CONCLUSION

The identification of VTE in the SNDS is possible with a good PPV.

Clustering of prostate cancer healthcare pathways in the French National Healthcare database

BACKGROUND

Healthcare pathways of patients with prostate cancer are heterogeneous and complex to apprehend using traditional descriptive statistics. Clustering and visualization methods can enhance their characterization.

METHODS

Patients with prostate cancer in 2014 were identified in the French National Healthcare database (Système National des Données de Santé-SNDS) and their data were extracted with up to 5 years of history and 4 years of follow-up. Fifty-one-specific encounters constitutive of prostate cancer management were synthesized into four macro-variables using a clustering approach. Their values over patient follow-ups constituted healthcare pathways. Optimal matching was applied to calculate distances between pathways. Partitioning around medoids was then used to define consistent groups across four exclusive cohorts of incident prostate cancer patients: Hormone-sensitive (HSPC), metastatic hormone-sensitive (mHSPC), castration-resistant (CRPC), and metastatic castration-resistant (mCRPC). Index plots were used to represent pathways clusters.

RESULTS

The repartition of macro-variables values-surveillance, local treatment, androgenic deprivation, and advanced treatment-appeared to be consistent with prostate cancer status. Two to five clusters of healthcare pathways were observed in each of the different cohorts, corresponding for most of them to relevant clinical patterns, although some heterogeneity remained. For instance, clustering allowed to distinguish patients undergoing active surveillance, or treated according to cancer progression risk in HSPC, and patients receiving treatment for potentially curative or palliative purposes in mHSPC and mCRPC.

CONCLUSION

Visualization methods combined with a clustering approach enabled the identification of clinically relevant patterns of prostate cancer management. Characterization of these care pathways is an essential element for the comprehension and the robust assessment of healthcare technology effectiveness.

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.

Evaluation of VTE, MACE, and Serious Infections Among Patients with RA Treated with Baricitinib Compared to TNFi: A Multi-Database Study of Patients in Routine Care Using Disease Registries and Claims Databases

INTRODUCTION

The aim of this work is to evaluate baricitinib safety with respect to venous thromboembolism (VTE), major adverse cardiovascular events (MACE), and serious infection relative to tumor necrosis factor inhibitors (TNFi) in patients with rheumatoid arthritis (RA).

METHODS

Patients with RA from 14 real-world data sources (three disease registries, eight commercial and three government health insurance claims databases) in the United States (n = 9), Europe (n = 3), and Japan (n = 2) were analyzed using a new user active comparator design. Propensity score matching (1:1) controlled for potential confounding. Meta-analysis of incidence rate ratios (IRR) and incidence rate differences (IRD) for each outcome, from each data source was executed using modified Poisson regression and Cochran-Mantel-Haenszel analysis.

RESULTS

Of 9013 eligible baricitinib-treated patients, 7606 were propensity score-matched with TNFi-treated patients, contributing 5879 and 6512 person-years of baricitinib and TNFi exposure, respectively. Across data sources, 97 patients (56 baricitinib) experienced VTE during follow-up, 93 experienced MACE (54 baricitinib), and 321 experienced serious infection (176 baricitinib). Overall IRRs comparing baricitinib with TNFi treatment were 1.51 (95% CI 1.10, 2.08) for VTE, 1.54 (95% CI 0.93, 2.54) for MACE, and 1.36 (95% CI 0.86, 2.13) for serious infection. IRDs for VTE, MACE, and serious infection, respectively, were 0.26 (95% CI -0.04, 0.57), 0.22 (95% CI -0.07, 0.52), and 0.57 (95% CI -0.07, 1.21) per 100 person-years greater for baricitinib than TNFi.

CONCLUSIONS

Overall results suggest increased risk of VTE with baricitinib versus TNFi, with consistent point estimates from the two largest data sources. A numerically greater risk was observed for MACE and serious infection when comparing baricitinib versus TNFi, with different point estimates from the two largest data sources. Findings from this study and their impact on clinical practice should be considered in context of limitations and other evidence regarding the safety and efficacy of baricitinib and other Janus kinase inhibitors.

TRIAL REGISTRATION

EU PAS Register ( http://encepp.eu ), identifier #32271.

Validation of Algorithms to Identify Acute Myocardial Infarction, Stroke, and Cardiovascular Death in German Health Insurance Data

Purpose

Validation of outcomes allows measurement of and correction for potential misclassification and targeted adjustment of algorithms for case definition. The purpose of our study was to validate algorithms for identifying cases of acute myocardial infarction (AMI), stroke, and cardiovascular (CV) death using patient profiles, ie, chronological tabular summaries of relevant available information on a patient, extracted from pseudonymized German claims data.

Patients and Methods

Based on the German Pharmacoepidemiological Research Database (GePaRD), 250 cases were randomly selected (50% males) for each outcome between 2016 and 2017 based on the inclusion criteria age ≥50 years and continuous insurance ≥1 year and applying the following algorithms: hospitalization with a main diagnosis of AMI (ICD-10-GM codes I21.- and I22.-) or stroke (I63, I61, I64) or death with a hospitalization in the 60 days before with a main diagnosis of CV disease. Patient profiles were built including (i) age and sex, (ii) hospitalizations incl. diagnoses, procedures, discharge reasons, (iii) outpatient diagnoses incl. diagnostic certainty, physician specialty, (iv) outpatient encounters, and (v) outpatient dispensings. Using adjudication criteria based on clinical guidelines and risk factors, two trained physicians independently classified cases as “certain”, “probable”, “unlikely” or “not assessable”. Positive predictive values (PPVs) were calculated as percentage of confirmed cases among all assessable cases.

Results

For AMI, the overall PPV was 97.6% [95% confidence interval 94.8–99.1]. The PPV for any stroke was 94.8% [91.3–97.2] and higher for ischemic (98.3% [95.0–99.6]) than for hemorrhagic stroke (86.5% [76.5–93.3]). The PPV for CV death was 79.9% [74.4–84.4]. It increased to 91.7% [87.2–95.0] after excluding 32 cases with data insufficient for a decision.

Conclusion

Algorithms based on hospital diagnoses can identify AMI, stroke, and CV death from German claims data with high PPV. This was the first study to show that German claims data contain information suitable for outcome validation.

Assessing the Risk of Relapse Requiring Corticosteroids After In Vitro Fertilization in Women With Multiple Sclerosis

BACKGROUND AND OBJECTIVES

Several studies have shown an increased risk of relapse after in vitro fertilization (IVF) in women with multiple sclerosis (MS), especially when a gonadotrophin-releasing hormone (GnRH) agonist stimulation protocol was used. Our objective was to investigate the risk of relapse after IVF in women with MS, overall and according to stimulation protocol (GnRH agonists vs antagonists), using data from the French national health insurance database.

METHODS

This retrospective cohort study included all women with MS who have benefited from IVF between January 1, 2010, and December 31, 2015, in France. Three-month exposed periods after IVF were compared with unexposed periods before IVF, each woman being her own control. Four outcomes were considered: annualized relapse rate (ARR), proportion of IVF with relapse, difference in the number of relapses "after-before," and the delay from IVF to the first relapse. Relapses were identified by an algorithm based on MS-related hospital admissions and the use of corticosteroid therapy. Stimulation protocols and disease-modifying therapies (DMTs) were identified using drug claims. Zero-inflated Poisson regression models adjusted for age at IVF and the presence of DMT were used. A random effect on women was included because women may undergo multiple IVF procedures. Subgroup analyses by stimulation protocol and IVF outcome (pregnancy or failure) were conducted.

RESULTS

A total of 225 women accounting for 338 IVF procedures were included (the mean age at the first IVF 34.6 ± 4.5 years; 36% of women underwent at least 2 IVF procedures during the period). No increase in the risk of relapse after IVF was found overall (before vs after IVF: 0.20 vs 0.18 relapse per patient-year; 7.7% vs 7.1% of IVF with women having at least one relapse) and in subgroups. A lower ARR before and after IVF was observed among women who remained treated until IVF.

DISCUSSION

The maintenance of DMT until IVF seemed to be a determining factor in reducing the risk of relapse. Women with MS should be reassured because we did not show an increased risk of relapse requiring the use of corticosteroid therapy after IVF neither with GnRH agonists nor with GnRH antagonists.

Abiraterone acetate versus docetaxel for metastatic castration-resistant prostate cancer: a cohort study within the French Nationwide Claims Database

OBJECTIVES

To conduct the direct comparison of abiraterone acetate and docetaxel for first-line treatment of metastatic castration-resistant prostate cancer (mCRPC) in real-life settings.

METHODS

Data were extracted from the French nationwide claims database (SNDS) on all men aged ≥40 years starting first-line treatment with abiraterone acetate or docetaxel for mCRPC in 2014. A high-dimensional propensity score including 100 baseline characteristics was used to match patients of both groups and form two comparative cohorts. Three-year overall survival and treatment discontinuation-free survival were determined using Kaplan-Meier analysis.

RESULTS

In 2014, 2,444 patients started abiraterone for treatment of mCRPC and 1,214 started docetaxel. After trimming and matching, 716 patients were available in each group. Median overall survival tended to be longer in the abiraterone acetate cohort (23.8 months, 95% confidence interval = [21.5; 26.0]) than in the docetaxel cohort (20.3 [18.4; 21.6] months). Survival at 36 months was 34.6% for abiraterone acetate and 27.9% for docetaxel (p = 0.0027). Treatment discontinuation-free median was longer in the abiraterone acetate cohort compared to the docetaxel cohort (10.8 [10.1; 11.7] versus 7.4 [7.0; 8.0] months).

CONCLUSION

The findings underline the interest of oral abiraterone acetate over intravenous docetaxel as the first-line treatment option in mCRPC.