Evidence‐based consensus guidelines for <scp>ALS</scp> genetic testing and counseling
Bibliographic record
Abstract
OBJECTIVE: Advances in amyotrophic lateral sclerosis (ALS) gene discovery, ongoing gene therapy trials, and patient demand have driven increased use of ALS genetic testing. Despite this progress, the offer of genetic testing to persons with ALS is not yet "standard of care." Our primary goal is to develop clinical ALS genetic counseling and testing guidelines to improve and standardize genetic counseling and testing practice among neurologists, genetic counselors or any provider caring for persons with ALS. METHODS: Core clinical questions were identified and a rapid review performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-P) 2015 method. Guideline recommendations were drafted and the strength of evidence for each recommendation was assessed by combining two systems: the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) System and the Evaluation of Genomic Applications in Practice and Prevention (EGAPP). A modified Delphi approach was used to reach consensus among a group of content experts for each guideline statement. RESULTS: A total of 35 guideline statements were developed. In summary, all persons with ALS should be offered single-step genetic testing, consisting of a C9orf72 assay, along with sequencing of SOD1, FUS, and TARDBP, at a minimum. The key education and genetic risk assessments that should be provided before and after testing are delineated. Specific guidance regarding testing methods and reporting for C9orf72 and other genes is provided for commercial laboratories. INTERPRETATION: These evidence-based, consensus guidelines will support all stakeholders in the ALS community in navigating benefits and challenges of genetic testing.
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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 | 0.069 | 0.189 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.016 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.009 | 0.005 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".