RESUMEN
Background: Metastatic prostate cancer (PCa) constitutes ~5% of all new PCa diagnoses in Western countries. For most cases, primary consideration should be given to systemic therapies as the first-line approach based on evidence from randomized controlled trials (RCTs). Despite the importance of RCTs as the pinnacle of evidence in modern medicine, concerns have been raised about their applicability to real-life scenarios. These trials often feature participants who are younger with better performance statuses and prognoses compared to their real-world counterparts. The PIONEER project falls under the Innovative Medicine Initiative's (IMI) "Big Data for Better Outcomes" initiative, aimed at revolutionizing PCa care in Europe. The central focus lies in improving cancer-related outcomes, enhancing health system efficiency, and elevating the quality of health and social care. This study endeavours to evaluate the generalizability of RCT findings concerning newly diagnosed metastatic PCa. Methods: A systematic review of the literature will be conducted to compile patient characteristics from RCTs addressing this subject within the past decade. To create a real-world benchmark, patients with recently diagnosed metastatic PCa from a network of population-based databases will serve as a comparison group. The objective is to assess the applicability of RCT results in two ways. First, a comparison will be made between the characteristics of patients with newly diagnosed metastatic PCa enroled in RCTs and those with the same condition included in our databases which might represent the real-world setting. Second, an evaluation will be undertaken to determine the proportion of real-world patients with newly diagnosed metastatic PCa who meet the criteria for RCT enrolment. This study will rely on extensive observational data, primarily sourced from population-based registries, electronic health records, and insurance claims data. The study cohort is established upon routinely gathered healthcare data, meticulously mapped to the Observational Medical Outcomes Partnership Common Data Model.
RESUMEN
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.
RESUMEN
BACKGROUND: Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics. OBJECTIVE: To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data. DESIGN, SETTING, AND PARTICIPANTS: From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data. RESULTS AND LIMITATIONS: The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent. CONCLUSIONS: Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data. PATIENT SUMMARY: Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.