Randomized Clinical Trial of<scp>First‐Line</scp>Genome Sequencing in Pediatric White Matter Disorders
Bibliographic record
Abstract
OBJECTIVE: Genome sequencing (GS) is promising for unsolved leukodystrophies, but its efficacy has not been prospectively studied. METHODS: A prospective time-delayed crossover design trial of GS to assess the efficacy of GS as a first-line diagnostic tool for genetic white matter disorders took place between December 1, 2015 and September 27, 2017. Patients were randomized to receive GS immediately with concurrent standard of care (SoC) testing, or to receive SoC testing for 4 months followed by GS. RESULTS: Thirty-four individuals were assessed at interim review. The genetic origin of 2 patient's leukoencephalopathy was resolved before randomization. Nine patients were stratified to the immediate intervention group and 23 patients to the delayed-GS arm. The efficacy of GS was significant relative to SoC in the immediate (5/9 [56%] vs 0/9 [0%]; Wild-Seber, p < 0.005) and delayed (control) arms (14/23 [61%] vs 5/23 [22%]; Wild-Seber, p < 0.005). The time to diagnosis was significantly shorter in the immediate-GS group (log-rank test, p = 0.04). The overall diagnostic efficacy of combined GS and SoC approaches was 26 of 34 (76.5%, 95% confidence interval = 58.8-89.3%) in <4 months, greater than historical norms of <50% over 5 years. Owing to loss of clinical equipoise, the trial design was altered to a single-arm observational study. INTERPRETATION: In this study, first-line GS provided earlier and greater diagnostic efficacy in white matter disorders. We provide an evidence-based diagnostic testing algorithm to enable appropriate clinical GS utilization in this population. ANN NEUROL 2020;88:264-273.
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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 | 0.001 |
| 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".