Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform

Pawel Rajwa, Angelika Borkowetz, Thomas Abbott, Andrea Alberti, Anders Bjartell, James T. Brash, Riccardo Campi, Andrew Chilelli, Mitchell Conover, Niculae Constantinovici, Eleanor Davies, Bertrand De Meulder, Sherrine Eid, Mauro Gacci, Asieh Golozar, Haroon Hafeez, Samiul Haque, Ayman Hijazy, Tim Hulsen, Andreas JosefssonSara Khalid, Raivo Kolde, Daniel Kotik, Samu Kurki, Mark Lambrecht, Chi Ho Leung, Julia Moreno, Rossella Nicoletti, Daan Nieboer, Marek Oja, Soundarya Palanisamy, Peter Prinsen, Christian Reich, Giulio Raffaele Resta, Maria J. Ribal, Juan Gómez Rivas, Emma Smith, Robert Snijder, Carl Steinbeisser, Frederik Vandenberghe, Philip Cornford, Susan Evans-Axelsson, James N'Dow, Peter Paul M. Willemse*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in “real-life” patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Original languageEnglish
Pages (from-to)81-88
Number of pages8
JournalEuropean Urology Open Science
Volume63
DOIs
Publication statusPublished - May 2024

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