Validation study of the <scp>lambda</scp> model for predicting the <i>BRCA1</i> or <i>BRCA2</i> mutation carrier status of North American Ashkenazi Jewish women
Bibliographic record
Abstract
LAMBDA is a model that estimates the probability an Ashkenazi Jewish (AJ) woman carries an ancestral BRCA1 or BRCA2 mutation from her personal and family cancer history. LAMBDA is relevant to clinical practice, and its implementation does not require a computer. It was developed principally from Australian and UK data. We conducted a validation study using 1286 North American AJ women tested for the mutations 185delAG and 5382insC in BRCA1 and 6174delT in BRCA2. Most had a personal or family history of breast cancer. We observed 197 carriers. The area under the receiver operator characteristic (ROC) curve (a measure of ranking) was 0.79 [95% confidence interval (CI) = 0.77-0.81], similar to that for the model-generating data (0.78; 95% CI = 0.75-0.82). LAMBDA predicted 232 carriers (18% more than observed; p = 0.002) and was overdispersed (p = 0.009). The Bayesian computer program BRCAPRO gave a similar area under the ROC curve (0.78; 95% CI = 0.76-0.80), but predicted 367 carriers (86% more than observed; p < 0.0001), and was substantially overdispersed (p < 0.0001). Therefore, LAMBDA is comparable to BRCAPRO for ranking AJ women according to their probability of being a BRCA1 or BRCA2 mutation carrier and is more accurate than brcapro which substantially overpredicts carriers in this population.
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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 | 0.001 | 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) | 0.000 | 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".