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Circulating tumor DNA fraction (ctDNA%) to independently predict for clinical outcomes in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC).

2021· article· en· W3172178421 on OpenAlexafffund
Corinne Maurice‐Dror, Nicolette M. Fonseca, Cameron Herberts, William R. S. Fan, Alexander W. Wyatt, Kim N.

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity of British Columbia
FundersBC Cancer Foundation
KeywordsMedicineInternal medicineProstate cancerOncologyProportional hazards modelUnivariate analysisCancerMultivariate analysis

Abstract

fetched live from OpenAlex

5049 Background: CtDNA% (the tumour-derived proportion of cell-free DNA (cfDNA)) is abundant in >60% of mCRPC pts and associates with adverse clinical prognostic factors. However, prognostic associations have not been comprehensively tested across clinical contexts. We evaluated the utility of ctDNA% as an independent prognostic biomarker in patients with mCRPC prior to first-line (1L) therapy. Methods: 410 treatment-naïve mCRPC pts had blood samples drawn prior to 1L therapy and followed prospectively for outcomes. Plasma cfDNA was subjected to deep targeted sequencing and ctDNA% was calculated using validated methods ( Annala, Cancer Discov, 2018 ). Overall survival (OS), PSA progression free survival (PSA PFS) and PSA declines ≥50% from baseline (PSA50 response rate (RR)) were stratified by ctDNA% and compared using Kaplan-Meier and Cox proportional hazards analysis. Results: Median age was 73 yrs. (range 45-98), the majority of pts had ECOG PS 0-1 (78%) and 9.5% had liver metastases at baseline. The most common 1L therapy employed was androgen receptor pathway inhibitors (90%). Median follow-up was 21 mo. (range 1-75) and median ctDNA% was 4.9% (range: 0-89%). Stratifying patients into high ctDNA (>30%) and Low ctDNA (≤2%) groups showed stronger association with OS and PSA PFS than grouping by median (Table). In a univariate comparison to pts with low ctDNA (≤2%), pts with high ctDNA% (>30%) had significantly shorter median PSA PFS, median OS and a lower PSA50 RR (Table). In a multivariable adjustment for clinical prognostic factors and cfDNA concentration, high ctDNA% remained strongly associated with OS (HR= 3.3, 95%CI: 2.1-5.3, p<0.001) and PSA PFS (HR: 3.7, 95%CI: 2.4-5.9, p<0.001). Although ctDNA% and total cfDNA concentration were correlated (R2=0.55), association with OS was stronger for ctDNA% than cfDNA concentration (stratified at median; HR: 2.9 (2.3-3.7), p<0.001 vs HR: 2.1 (1.7-2.6), p<0.001). Conclusions: In a large cohort of treatment-naïve mCRPC pts, ctDNA% prior to 1L treatment provided strong prognostic information independent of known clinical factors. These data further demonstrate the multipronged clinical utility of ctDNA-based profiling for actionable genomic alterations.[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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.439
Teacher spread0.367 · 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".

Quick stats

Citations7
Published2021
Admission routes2
Has abstractyes

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