Efficacy of apalutamide (APA) plus ongoing androgen deprivation therapy (ADT) in patients (pts) with nonmetastatic castration-resistant prostate cancer (nmCRPC) and baseline (BL) comorbidities (CM).
Bibliographic record
Abstract
5023 Background: The addition of APA to ongoing ADT in pts with nmCRPC significantly prolonged metastasis-free survival (MFS), time to symptomatic progression (SymProg), and second progression-free survival (PFS2) in SPARTAN. We assessed the impact of APA on these end points in pts with or without BL CM. Methods: Using Cox proportional hazards models, treatment effect of APA was evaluated in SPARTAN pts with CM at BL, stratifying by the presence of BL diabetes/hyperglycemia (D/H), cardiovascular disease (CVD), hypertension (HTN), and renal insufficiency (RI). Results: Of 1207 SPARTAN pts, 1062 (88%) had ≥ 1 BL CM, including 703/806 (87%) APA pts and 359/401 (90%) PBO pts. A total of 226 (19%), 398 (33%), 798 (66%), and 774 (64%) pts had D/H, CVD, HTN, and RI, respectively; 323 (27%), 412 (34%), 259 (21%), and 68 (6%) pts had 1, 2, 3, and 4 CM, respectively. Incidence of CM was balanced between arms. Pts with CM were older than pts with no CM (median age, 75 vs 69 yrs, APA; 74 vs 69 yrs, PBO). MFS, SymProg, and PFS2 benefit with APA was significant in all CM subgroups, except PFS2 for pts with D/H (Table) and regardless of the number of CM. The incidence of any treatment-emergent AE was balanced between pts with and without CM. AEs with APA were not affected by any CM. Clinical trial information: NCT01946204. Conclusions: The benefit of APA + ongoing ADT in pts with nmCRPC was maintained in pts with D/H, CVD, HTN, and RI. The safety profile of APA was not affected by any CM.[Table: see text]
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".