A pooled analysis evaluating prognostic significance of Residual Cancer Burden in invasive lobular breast cancer
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
Residual Cancer Burden (RCB) after neoadjuvant chemotherapy (NAC) is validated to predict event-free survival (EFS) in breast cancer but has not been studied for invasive lobular carcinoma (ILC). We studied patient-level data from a pooled cohort across 12 institutions. Associations between RCB index, class, and EFS were assessed in ILC and non-ILC with mixed effect Cox models and multivariable analyses. Recursive partitioning was used in an exploratory model to stratify prognosis by RCB components. Of 5106 patients, the diagnosis was ILC in 216 and non-ILC in 4890. Increased RCB index was associated with worse EFS in both ILC and non-ILC (p = 0.002 and p < 0.001, respectively) and remained prognostic when stratified by receptor subtype and adjusted for age, grade, T category, and nodal status. Recursive partitioning demonstrated residual invasive cancer cellularity as most prognostic in ILC. These results underscore the utility of RCB for evaluating NAC response in those with ILC.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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