Circulating tumour DNA kinetics in recurrent/metastatic head and neck squamous cell cancer patients
Bibliographic record
Abstract
PURPOSE: Immune checkpoint blockade (ICB) has become a standard of care in the treatment of recurrent/metastatic head and neck squamous cell cancer (R/M HNSCC). However, only a subset of patients benefit from treatment. Quantification of plasma circulating tumour DNA (ctDNA) levels and on-treatment kinetics may permit real-time assessment of disease burden under selective pressures of treatment. PATIENTS AND METHODS: R/M HNSCC patients treated with systemic therapy, platinum-based chemotherapy (CT) or ICB, underwent serial liquid biopsy sampling. Biomarkers tested included ctDNA measured by CAncer Personalized Profiling by deep Sequencing (CAPP-Seq) and markers of host inflammation measured by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). RESULTS: Among 53 eligible patients, 16 (30%) received CT, 30 (57%) ICB [anti-PD1/L1] monotherapy and 7 (13%) combination immunotherapy (IO). Median progression-free survival (PFS) and overall survival (OS) were 2.8 months (95% CI, 1.3-4.3) and 8.2 months (95% CI, 5.6-10.8), respectively. Seven (13%) patients experienced a partial response and 21 (40%) derived clinical benefit. At baseline, median ctDNA variant allele frequency (VAF) was 4.3%. Baseline ctDNA abundance was not associated with OS (p = 0.56) nor PFS (p = 0.54). However, a change in ctDNA VAF after one cycle of treatment (ΔVAF (T1-2)) was predictive of both PFS (p< 0.01) and OS (p< 0.01). Additionally, decrease in ΔVAF identified patients with longer OS despite early radiological progression, 8.2 vs 4.6 months, hazard ratio 0.44 (95% CI, 0.19-0.87) p = 0.03. After incorporating NLR and PLR into multivariable Cox models, ctDNA ∆VAF retained an association with OS. CONCLUSIONS: Early dynamic changes in ctDNA abundance, after one cycle of treatment, compared to baseline predicted both OS and PFS in R/M HNSCC patients on systemic therapy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".