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

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

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.

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

Survivorship Data in Prostate Cancer: Where Are We and Where Do We Need To Be?

Cancer survivorship was recently identified as a prostate cancer (PCa) research priority by PIONEER, a European network of excellence for big data in PCa. Despite being a research priority, cancer survivorship lacks a clear and agreed definition, and there is a distinct paucity of patient-reported outcome (PRO) data available on the subject. Data collection on cancer survivorship depends on the availability and implementation of (validated) routinely collected patient-reported outcome measures (PROMs). There have been recent advances in the availability of such PROMs. For instance, the European Organisation for Research and Treatment of Cancer Quality of Life Group (EORTC QLG) is developing survivorship questionnaires. This provides an excellent first step in improving the data available on cancer survivorship. However, we propose that an agreed, standardised definition of (prostate) cancer survivorship must first be established. Only then can real-world data on survivorship be collected to strengthen our knowledge base. With more men than ever surviving PCa, this type of research is imperative to ensure that the quality of life of these men is considered as much as their quantity of life. Patient summary: As there are more prostate cancer survivors than ever before, research into cancer survivorship is crucial. We highlight the importance of such research and provide recommendations on how to carry it out. The first step should be establishing agreement on a standardised definition of survivorship. From this, patient-reported outcome measures can then be used to collect important survivorship data