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

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.