Multimodal detection of molecular residual disease in high-risk locally advanced squamous cell carcinoma of the head and neck
Bibliographic record
Abstract
Up to 30% of patients with locally advanced head and neck squamous cell carcinoma (LA-HNSCC) relapse. Molecular residual disease (MRD) detection using multiple assays after definitive therapy has not been reported. In this study, we included patients with LA-HNSCC (stage III Human Papilloma virus (HPV)-positive, III-IVB HPV-negative) treated with curative intent. Plasma was collected pre-treatment, at 4-6 weeks (FU1) and 8-12 weeks (FU2) post-treatment. Circulating tumor DNA (ctDNA) was analyzed using a tumor-informed (RaDaR®) and a tumor-naïve (CAPP-seq) assay. HPV DNA was measured using HPV-sequencing (HPV-seq) and digital PCR (dPCR). A total of 86 plasma samples from 32 patients were analyzed; all patients with at least 1 follow-up sample. Most patients were stage III HPV-positive (50%) and received chemoradiation (78%). No patients had radiological residual disease at FU2. With a median follow-up of 25 months, there were 7 clinical relapses. ctDNA at baseline was detected in 15/17 (88%) by RaDaR and was not associated with recurrence free survival (RFS). Two patients relapsed within a year after definitive therapy and showed MRD at FU2 using RaDaR; detection of ctDNA during follow-up was associated with shorter RFS (p < 0.001). ctDNA detection by CAPP-seq pre-treatment and during follow-up was not associated with RFS (p = 0.09). HPV DNA using HPV-seq or dPCR during follow-up was associated with shorter RFS (p < 0.001). Sensitivity and specificity for MRD at FU2 using RaDaR was 40% and 100% versus 20 and 90.5% using CAPP-seq. Sensitivity and specificity for MRD during follow-up using HPV-seq was 100% and 91.7% versus 50% and 100% using dPCR. In conclusion, HPV DNA and ctDNA can be detected in LA-HNSCC before definitive therapy. The RaDaR assay but not CAPP-seq may detect MRD in patients who relapse within 1 year. HPV-seq may be more sensitive than dPCR for MRD detection.
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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".