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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).

2024· article· en· W4399394934 on OpenAlexaff
Arun Azad, Karim Fizazi, Douglas Laird, Nobuaki Matsubara, Ugo De Giorgi, Consuelo Buttigliero, Lawrence I. Karsh, Jae Young Joung, Steven Yip, Stefanie Zschaebitz, Lee A. Albacker, Cynthia G. Healy, Xun Lin, Jijumon Chelliserry, Neeraj Agarwal

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicPARP inhibition in cancer therapy
Canadian institutionsBaker Hughes (Canada)
FundersPfizer
KeywordsMedicineEnzalutamidePlaceboOncologyInternal medicineCancerAlternative medicineProstate cancerPathologyAndrogen receptor

Abstract

fetched live from OpenAlex

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]

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.143
GPT teacher head0.503
Teacher spread0.360 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations3
Published2024
Admission routes1
Has abstractyes

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