Brief family history questionnaire for identification of Lynch syndrome in women with newly diagnosed endometrial cancer.
Bibliographic record
Abstract
5026 Background: Endometrial cancer (EC) is often the sentinel cancer for women with Lynch syndrome (LS); however, it is underappreciated in this population. The Brief Family History Questionnaire (bFHQ) was developed to identify women with EC who have family histories suggestive of LS. The objective of our study was to evaluate the bFHQ compared to an extended family history (eFHQ) and medical record in identifying women with EC who may benefit from genetic cancer risk assessment. Methods: All women with newly diagnosed EC from July 2010 to June 2011 were asked to participate in a prospective screening protocol for LS which included completing two family history questionnaires; the bFHQ which is a 4-item self-report measure and the 37-item eFHQ administered by a research assistant. Family history was also extracted from the medical record. Using the bFHQ women were flagged as requiring additional investigation for LS based on predetermined criteria and the predictive ability of the flag was evaluated treating eFHQ as the gold standard. Comparisons were made between the bFHQ, eFHQ and medical record for families meeting Amsterdam II, Society Gynecologic Oncologist (SGO) 20-25% or the Ontario Ministry of Health (MOH) testing criteria for LS, using generalized estimating equation logistic regression models. Results: 119 (N = 182, 65%) consented to the study and 106 (89%) completed the bFHQ. The median age was 61 (26-91). The number of women who met testing criteria by the eFHQ was 17 (16%) and 33 (31%) were flagged by the bFHQ. The sensitivity, specificity, PPV and NPV of the bFHQ was 88.2%, 79.8%, 45.5% and 97.3%. There was no significant difference in the number of women who met Amsterdam II or SGO 20-25% testing criteria between the bFHQ, eFHQ and medical record (P > 0.05). The numbers of women meeting MOH criteria using the bFHQ (N=16, 15%) and the eFHQ were similar (N=17, 16%) (P = 0.7); however, more women met MOH criteria using the bFHQ and the eFHQ compared to the medical record (N=8, 7.6%) (P = 0.011; P = 0.006). Conclusions: The patient-administered bFHQ is a highly effective tool in identifying women who meet MOH testing criteria for LS and is a good screening tool to identify women with EC for further genetic assessment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".