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Record W4386348930 · doi:10.3390/curroncol30090591

A Real-World Evidence Study Using Alberta-Population-Based Data to Describe Treatment Patterns for Metastatic Castration-Sensitive Prostate Cancer Patients (AWARENESS)

2023· article· en· W4386348930 on OpenAlexafffundvenueabout
Safiya Karim, Jennifer Lowther, Gabriel Gyulay, Dylan E. O’Sullivan, Christopher J.D. Wallis, Steven Yip, Darren R. Brenner, Devon J. Boyne, Winson Y. Cheung

Bibliographic record

VenueCurrent Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai HospitalBayer (Canada)University of Calgary
FundersBayer Canada
KeywordsMedicineEnzalutamideProstate cancerAndrogen deprivation therapyCohortPopulationInternal medicineAbiraterone acetateDocetaxelRetrospective cohort studyCancer registryOncologyCohort studyCancerAndrogen receptor

Abstract

fetched live from OpenAlex

INTRODUCTION: Over the past decade, the treatment of metastatic castration-sensitive prostate cancer (mCSPC) has changed significantly. Current guidelines suggest the use of androgen deprivation therapy (ADT) plus an additional systemic therapy, regardless of disease burden and risk, based on phase 1 evidence showing improved overall survival. We sought to describe treatment patterns of patients with mCSPC in the province of Alberta. METHODS: This was a retrospective, population-based, cohort study of male patients aged ≥18 with mCSPC at the time of diagnosis and who initiated ADT between 1 January 2016 and 31 December 2020. Data were obtained from the Alberta Cancer Registry. Patients were assigned to an ADT-alone cohort or a treatment intensification cohort (cohorts 2-5). The primary objectives of this study were to describe baseline characteristics and the treatment of mCSPC patients who initiated ADT with or without treatment intensification. Overall survival between cohorts was a secondary objective. Descriptive statistics were used to describe differences in baseline characteristics of each cohort. Overall survival was calculated using the Kaplan-Meier method. All statistical tests were two-sided and are used to call out likely cohort differences descriptively. RESULTS: Between 1 January 2016 and 31 December 2020, we identified a total of 960 patients with mCSPC (median age 74 years, IQR 66-82). Most patients received ADT alone (67%), followed by ADT plus abiraterone (18%), ADT plus docetaxel (12%), and ADT plus enzalutamide or apalutamide (3%). Over the study period, we observed an increase in the utilization of treatment intensification over time, in particular, the increased use of androgen-receptor-axis-targeted (ARAT) therapies. Patients who received ADT alone were older, were more likely to have more than one comorbid condition, had fewer sites of metastatic disease, and were less likely to be on opioid medications. CONCLUSIONS: In this study, we show that patients who received ADT alone as treatment for mCSPC are older, have more comorbidities, and have less extensive disease. While there has been a decline over time in the number of patients treated with ADT alone, over 50% of all patients with mCSPC continue to receive ADT alone. Further work is needed to understand barriers to treatment intensification and for knowledge translation initiatives to improve the treatment of patients with mCSPC.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.794

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.041
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.017
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.515
GPT teacher head0.551
Teacher spread0.036 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2023
Admission routes4
Has abstractyes

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