First look at the baseline characteristics of participants in IRONMAN, the international registry for men with advanced prostate cancer.
Bibliographic record
Abstract
85 Background: Patients with advanced prostate cancer (APC) experience high mortality and increasingly deteriorating quality of life due to the disease itself and the therapies they are treated with. Despite recent advances in the treatment landscape, disparities in outcomes have only worsened. There is an urgent need to identify disparities in treatment patterns and outcomes in advanced disease in diverse populations. The International Registry for Men with Advanced Prostate Cancer (IRONMAN) is uniquely equipped to address these needs. Methods: IRONMAN is a prospective registry initiated in 2017 with a planned accrual of 5000 patients with newly diagnosed metastatic hormone-sensitive (mHSPC) and castration-resistant (CRPC) prostate cancer. As of 10/11/2022, 2890 patients have enrolled from 14 countries at 113 sites, with 2 more countries pending activation. Sites were selected to create a diverse cohort across race/ethnicity, geography and socioeconomic factors. Patients are followed for survival, clinically significant adverse events, changes in cancer treatments, biomarkers, and Patient-Reported Outcome Measures (PROMs). This analysis includes patients with treatment data reported from Baseline through Month 3 as of October 2021 (n=1931, 9 countries). Results: Patients were recruited across the USA (N=799), Australia (146), Canada (282), Spain (238), England (205), and all other countries (261). 61% had mHSPC, and 39% had CRPC at enrollment with little variation in these proportions across countries. Based on self-report, 87% of patients were White, 9% Black, 4% reported other races/ethnicities, and 353 did not report race. In the US, 18% of patients were Black. Globally, 22% of respondents reported current or former military service. The most common first systemic therapy on study was androgen receptor signaling inhibitors (ARSI) +/- ADT in 1039 (54%), ranging between 12% and 66% of patients by country. 19% received chemotherapy +/- ADT and 18% received ADT alone. ARSI use varied by age, race, and metastatic disease site. Conclusions: Our preliminary results highlight our ability to successfully enroll and follow APC patients from 113 sites across 14 countries, with 2890 of 5000 planned patients enrolled. Accrual is greater in de novo mHSPC patients than anticipated. Differences in treatment patterns are already emerging, with more ARSI use in the mHSPC setting in North America than other regions. Our data demonstrates that IRONMAN participating sites are rapidly adopting new treatment recommendations into clinical practice of real-world patients.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".