Valuing gene testing in children with possible neurofibromatosis 1
Bibliographic record
Abstract
With the growing number of clinical guidelines recommending genetics tests in routine clinical care, the value of these tests should be evaluated. We examined the economic value of offering genetic testing to children with possible neurofibromatosis 1 (NF1) in British Columbia. Diagnosis of NF1 is usually made based on diagnostic clinical criteria, but molecular diagnostic testing, currently offered on a case-by-case basis in BC, now reliably diagnoses NF1 in 95% of cases. Children who present with some clinical features but whose findings are insufficient to meet the diagnostic criteria are labelled as having 'possible NF1'. Current guidelines call for these children to be followed as they have NF1, leading to annual ophthalmologic examinations and screening for complications; thus, there are increased costs to health care system. We created a model to account for these costs to the health care system, comparing the current protocol with one that would offer all children diagnosed with possible NF1 with genetic testing. Focusing on the incremental cost allowed us to determine that genetic testing provides good value, and patient interviews provided insight into the qualitative benefits of an earlier firm diagnosis. These findings may be helpful in guiding health policy decision-making.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".