Long-Term Outcomes and Genetic Predictors of Response to Metastasis-Directed Therapy Versus Observation in Oligometastatic Prostate Cancer: Analysis of STOMP and ORIOLE Trials
Bibliographic record
Abstract
Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co‐primary or secondary analyses are not yet available. Clinical Trial Updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported. The initial STOMP and ORIOLE trial reports suggested that metastasis-directed therapy (MDT) in oligometastatic castration-sensitive prostate cancer (omCSPC) was associated with improved treatment outcomes. Here, we present long-term outcomes of MDT in omCSPC by pooling STOMP and ORIOLE and assess the ability of a high-risk mutational signature to risk stratify outcomes after MDT. The primary end point was progression-free survival (PFS) calculated using the Kaplan-Meier method. High-risk mutations were defined as pathogenic somatic mutations within ATM, BRCA1/ 2, Rb1, or TP53. The median follow-up for the whole group was 52.5 months. Median PFS was prolonged with MDT compared with observation (pooled hazard ratio [HR], 0.44; 95% CI, 0.29 to 0.66; P value < .001), with the largest benefit of MDT in patients with a high-risk mutation (HR high-risk, 0.05; HR no high-risk, 0.42; P value for interaction: .12). Within the MDT cohort, the PFS was 13.4 months in those without a high-risk mutation, compared with 7.5 months in those with a high-risk mutation (HR, 0.53; 95% CI, 0.25 to 1.11; P = .09). Long-term outcomes from the only two randomized trials in omCSPC suggest a sustained clinical benefit to MDT over observation. A high-risk mutational signature may help risk stratify treatment outcomes after MDT.
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 | 0.025 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".