Circulating Tumor DNA as a Prognostic Biomarker for Selecting Participants to Early Phase Clinical Trials
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".