Low RNA disruption during neoadjuvant chemotherapy predicts pathologic complete response absence in patients with breast cancer
Bibliographic record
Abstract
In previously reported retrospective studies, high tumor RNA disruption during neoadjuvant chemotherapy predicted for post-treatment pathologic complete response (pCR) and improved disease-free survival at definitive surgery for primary early breast cancer. The BREVITY (Breast Cancer Response Evaluation for Individualized Therapy) prospective clinical trial (NCT03524430) seeks to validate these prior findings. Here we report training set (Phase I) findings, including determination of RNA disruption index (RDI) cut points for outcome prediction in the subsequent validation set (Phase II; 454 patients). In 80 patients of the training set, maximum tumor RDI values for biopsies obtained during neoadjuvant chemotherapy were significantly higher in pCR responders than in patients without pCR post-treatment (P = .008). Moreover, maximum tumor RDI values ≤3.7 during treatment predicted for a lack of pCR at surgery (negative predictive value = 93.3%). These findings support the prospect that on-treatment tumor RNA disruption assessments may effectively predict post-surgery outcome, possibly permitting treatment optimization.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".