Prostate
Practice-pattern data, not an efficacy signal: what high-risk pts are actually offered at consult.
MROQC ADT Practice Patterns
ForIntact high-risk M0/N0-1 prostate ca planned for definitive RT
TL;DR67.0% of 553 high-risk pts got guideline-concordant ADT (≥18mo); ARPI use 23.2% among STAMPEDE-eligible post-publication.
The deviation is concentrated where the guideline is weakest-anchored: cN1 (OR 2.94) and GG4-5 (OR 6.23 / 9.45) drove ≥18mo recommendations, so the third of pts NOT getting guideline-concordant ADT are largely single-factor high-risk. Facility remained a predictor after case-mix adjustment (P<.0001), which points at practice culture, not patient selection.
For a man with single-factor high-risk localized disease (GG4-5 or PSA ≥20 alone) heading to definitive RT, this frames how much of the ≥18mo ADT recommendation is guideline versus local habit; it does not address post-prostatectomy salvage or M1 disease.
GC-ADT tracked the features that also define STAMPEDE M0 eligibility (GG4 OR 6.23, GG5 OR 9.45, cN1 OR 2.94), so the non-concordant third is enriched for single-factor high-risk disease. Facility stayed predictive after case-mix adjustment (P<.0001), making department habit, not patient selection, the target.
ARPI intensification reached only 23.2% of STAMPEDE M0-eligible pts after publication, up from 0%. With 27.9% of this high-risk RT population eligible, the referral and co-management pathway for adding an ARPI to definitive RT plus ADT is the bottleneck, not the evidence.
9 details
Prospective observational analysis within the Michigan Radiation Oncology Quality Consortium (MROQC), a statewide quality collaborative. 26 centers, accrual June 2020 to November 2024, N=553. Intended ADT duration and ARPI use were collected prospectively at the treatment decision, not abstracted retrospectively.
Intact (non-postoperative) high-risk M0/N0-1 prostate cancer planned for definitive radiotherapy. Risk features: cT3/4 13.3%, cN1 19.9%, GG 4-5 75.0%, PSA ≥20 ng/mL 40.0%.
Primary outcome was intended guideline-concordant ADT (GC-ADT, ≥18 months) per the 2022 AUA/ASTRO recommendation of 18-36 months. Secondary analyses covered multivariable predictors of GC-ADT, ARPI adoption before versus after STAMPEDE M0 publication, and facility-level variability via a mixed-effects model with treatment site as random intercept.
91.3% were recommended ADT and 67.0% were guideline-concordant. Among the 27.9% meeting STAMPEDE M0 eligibility, ARPI recommendation went from 0% pre-publication to 23.2% after. Site-level variability remained significant on multivariable analysis (P<.0001).
| Factor | OR (95% CI) |
|---|---|
| cN1 | 2.94 (1.44 to 5.99) |
| GG4 | 6.23 (2.85 to 13.62) |
| GG5 | 9.45 (4.46 to 20.06) |
| PSA ≥40 | 3.64 (1.22 to 10.87) |
The 2022 AUA/ASTRO guideline sets 18-36 months, and STAMPEDE M0 supports ARPI intensification for ≥2 of cT3/T4, GG 4-5, PSA ≥40, or cN1. Both benchmarks are met by a minority here, echoing the long-standing gap between the long-course ADT durations tested in EORTC 22863 and RTOG 9202 era trials and what is actually intended in practice.
Intended duration is a proxy for delivered duration, so the true concordance rate could fall further with early discontinuation. STAMPEDE M0 eligibility was applied to a cohort accrued partly before that trial reported, so the 23.2% post-publication figure reflects an adoption curve still in motion rather than a steady state.
The finding that facility explains variance after adjusting for cN1, grade group, and PSA is the load-bearing result: with case mix accounted for, where a man is treated still moves how long he is recommended ADT. That is a quality-improvement target rather than an evidence gap, and it is the kind of signal a consortium is uniquely built to detect and act on.
Prospective practice-pattern survey of intended treatment, no efficacy endpoint. Documents a care-delivery gap rather than testing whether the guideline duration is right.
- Does intended ADT duration match delivered duration?
- Which facility-level factors drive the residual variability?
- Optimal ADT duration for single-factor high-risk disease