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Record W4414011763 · doi:10.36401/jipo-25-11

Circulating Tumor DNA as a Prognostic Biomarker for Selecting Participants to Early Phase Clinical Trials

2025· article· en· W4414011763 on OpenAlexfundno aff
Sammy Shaya, Okezie Uche–Ikonne, Bedirhan Kilerci, Julie Stevenson, Alastair Greystoke, Natalie Cook, Fiona Thistlethwaite, Louise Carter, Donna M. Graham, Matthew Krebs

Bibliographic record

VenueJournal of Immunotherapy and Precision Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsnot available
FundersLoxo OncologyChugai PharmaceuticalFoundation MedicineSierra OncologyServierMinistry of Minority AffairsEuropean Society for Medical OncologyAstellas PharmaEisaiCancer Research UKSeagenActuate TherapeuticsPfizerIncyteNuCanaModernaTarveda TherapeuticsTaiho PharmaceuticalChristie CharityMacroGenicsSarcoma UKSanofiGlaxoSmithKlineAmgenCarrick TherapeuticsAstraZenecaIgnytaEli Lilly and CompanyBristol-Myers Squibb
KeywordsBiomarkerOncologyClinical trialMedicineCirculating tumor DNAInternal medicineComputational biologyCancerBiologyGenetics

Abstract

fetched live from OpenAlex

Introduction Patients with advanced solid tumors may be considered for early phase clinical trials investigating the safety, tolerability, and dosing of experimental therapies. Optimizing participant selection is critical to maximize clinical benefit and meet trial endpoints with fewer participants. One in six participants does not meet routine life expectancy requirements (>3 months), highlighting the need for improved prognostication. Variant allele frequency (VAF) in circulating tumor DNA (ctDNA) correlates with overall survival (OS) in advanced solid tumors. We aimed to derive an optimal VAF threshold as a prognostic biomarker to enhance participant selection. Methods ctDNA testing was performed as part of the TARGET (NIHR Clinical Research Network CPMS ID 39172) and TARGET National (NCT04723316) prospective cohort studies, in patients with advanced solid tumors referred for early phase clinical trials. Maximum (maxVAF) and mean VAF (meanVAF) were compared in their association with OS and ability to delineate favorable and poor outcomes at set threshold points using hazard ratios (HRs). Optimal thresholds of VAF were explored using receiver operating characteristic curve analysis to predict 3-month landmark OS. Univariable and multivariable analysis was performed to determine whether VAF was an independent prognostic marker. Results Of 631 patients, 587 had evaluable ctDNA results. MeanVAF and maxVAF exhibited similar correlation with OS (r s = −0.32 vs −0.35, respectively) and similar prognostic utility at matched threshold points. A maxVAF value of 4% was selected as optimal for prognostic subgrouping (area under curve 0.77). OS was 5.9 versus 12.1 months ( p < 0.0001) for patients with more than 4% and 4% or less maxVAF, respectively. Multivariable analysis confirmed more than 4% maxVAF as independently associated with reduced 3-month landmark OS (HR 2.17 [1.76–2.70], p < 0.001). Conclusion VAF is an independent prognostic marker in patients with advanced solid tumors, with 4% maxVAF deemed optimal for delineating favorable and poorer prognostic subgroups in this patient cohort. Further validation and integration into existing prognostic scores are warranted.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.118
GPT teacher head0.498
Teacher spread0.380 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2025
Admission routes1
Has abstractyes

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