A Targeted Methylation–Based Multicancer Early Detection Blood Test Preferentially Detects High-Grade Prostate Cancer While Minimizing Overdiagnosis of Indolent Disease
Bibliographic record
Abstract
PURPOSE Indolent prostate cancer (PCa) is prevalent in the intended use population (adults age 50-79 years) for blood-based multicancer early detection (MCED) tests. We examined the detectability of PCa by a clinically validated, targeted methylation–based MCED test. METHODS Detectability by Gleason grade group (GG), clinical stage, association of detection status with tumor methylated fraction (TMeF), and overall survival (OS) were assessed in substudy 3 of Circulating Cell-Free Genome Atlas (CCGA; ClinicalTrials.gov identifier: NCT02889978 ) and PATHFINDER (ClinicalTrials.gov identifier: NCT04241796 ) studies. RESULTS Test sensitivity for PCa in substudy 3 of CCGA was 11.2% (47/420). The test detected 0 (0%) of 58 low-grade (GG1), 3 (1.9%) of 157 favorable intermediate-grade (GG2), 4 (5.1%) of 78 unfavorable intermediate-grade (GG3), and 36 (31.9%) of 113 high-grade (GG4 and 5) cancers and 3 (3.2%) of 95 stage I, 11 (4.7%) of 235 stage II, 7 (14.9%) of 47 stage III, and 22 (81.5%) of 27 stage IV cases. The median TMeF was higher for detected than nondetected cases (2,106.0 parts per million [PPM]; IQR, 349.8-24,376.3 v 24.4 PPM; IQR, 17.8-38.5; P < .05). Nondetected cases had better OS ( P < .05; hazard ratio [HR], 0.263 [95% CI, 0.104 to 0.533]) and detected cases had similar survival ( P = .2; HR, 0.672 [95% CI, 0.323 to 1.21]) compared with SEER adjusted for age, GG, and stage. Performance was similar in PATHFINDER, with no detected GG1/2 (0/13) or stage I/II (0/16) cases. CONCLUSION This MCED test preferentially detects high-grade, clinically significant PCa. Use in population-based screening programs in addition to standard-of-care screening is unlikely to exacerbate overdiagnosis of indolent PCa.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".