Bespoke ctDNA for longitudinal detection of molecular residual disease in high-risk melanoma patients
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Locally advanced melanoma has a variable prognosis. Currently, there are no reliable criteria to stratify the risk of disease relapse and identify those patients who will benefit the most from adjuvant therapies. Circulating tumor DNA (ctDNA) is an emerging biomarker measuring the presence of tumor-derived DNA in blood. PATIENTS AND METHODS: We used a bespoke, tumor-informed assay (RaDaR®, NeoGenomics, Inc.) to detect ctDNA in 276 prospectively collected plasma samples from 66 melanoma patients receiving definitive treatment. Collection time points included landmark (after completion of local treatment) and every 3-6 months for up to 2 years. RESULTS: ctDNA was detected in at least one plasma sample in 19 patients (29%), including 6/65 (9%) at landmark (post-surgical sample). Positive ctDNA at landmark was associated with shorter overall survival (OS; median OS 22.7 months versus not reached, log-rank P value = 0.01) and a trend towards a shorter relapse-free survival (RFS; median RFS 15.7 months versus not reached, log-rank P value = 0.07). In 10 patients, ctDNA detection preceded disease relapse by a median of 128 days (range 8-406 days). CONCLUSIONS: Our data indicate that ctDNA detection after surgery can identify patients with worse prognosis, and serial ctDNA measurements may enable earlier identification of disease recurrence.
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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 it