Utility of ctDNA burden as a prognostic biomarker for efficacy in TALAPRO-2: A phase 3 study of talazoparib (TALA) + enzalutamide (ENZA) vs placebo (PBO) + ENZA as first-line (1L) treatment in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC).
Bibliographic record
Abstract
5020 Background: TALAPRO-2 (NCT03395197) demonstrated that 1L TALA + ENZA significantly improved radiographic progression-free survival (rPFS) vs PBO + ENZA for pts with mCRPC. ctDNA burden is a candidate prognostic biomarker with potentially broad utility across treatments and tumor types. We assessed the potential prognostic utility of baseline (BL) ctDNA burden and changes in ctDNA burden at Week 9 (WK 9) in TALAPRO-2 pts. Methods: Retrospectively analyzed serial ctDNA samples from BL and WK 9 were assessed using FoundationOneLiquid CDx. Plasma tumor fraction was calculated based on aneuploidy (Husain et al. JCO Precis Oncol. 2022. PMID: 36265119). We categorized ctDNA burden as high (ctDNA burden quantifiable) vs low (unknown ctDNA burden). Data cutoff date was August 16, 2022. Results: In the all-comers intent-to-treat population, 678 pts were evaluable for ctDNA burden at BL: 26% (89/337) of TALA + ENZA pts were ctDNA-high and 74% (248/337) were ctDNA-low; 29% (98/341) of PBO + ENZA pts were ctDNA-high and 71% (243/341) were ctDNA-low. High ctDNA burden at BL was prognostic of inferior rPFS in the TALA + ENZA and PBO + ENZA arms (Table). A relatively favorable median rPFS was observed for pts with low ctDNA at BL and WK 9 for TALA + ENZA (n=206) and PBO + ENZA (n=207), as reported in the Table. At WK 9, 72 pts in the TALA + ENZA and 77 pts in the PBO + ENZA arms were evaluable for ctDNA conversion from high to low. In both treatment arms, conversion from high to low ctDNA was prognostic of improved rPFS vs pts who remained ctDNA-high (Table). Pts who remained ctDNA-low had a more favorable rPFS vs conversion from high to low ctDNA: TALA + ENZA, hazard ratio (HR) 95% confidence interval (CI), 0.45 (0.29–0.71), P=0.0003; PBO + ENZA, 0.34 (0.23–0.52), P<0.0001). Conclusions: High ctDNA burden at BL was negatively prognostic, and ctDNA conversion from high to low at WK 9 was prognostic of improved rPFS in TALAPRO-2. Limitations included not all clinical trial sites were able to perform ctDNA collection and most samples were below the limit of quantification. These results support the broad prognostic utility of ctDNA burden in mCRPC. Clinical trial information: NCT03395197 . [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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".