How should genetic tests be evaluated? Preliminary results of a systematic review
Bibliographic record
Abstract
Background Genetic tests are becoming increasingly available for clinical decision making, ushering in the era of personalized medicine. However, their implementation in clinical practice must be underpinned by a rigorous evaluation of their actual benefits. For this purpose, several evaluation tools have been developed. The aim of this study is to identify and compare the existing tools for assessments of genetic tests, taking into account their methodology and evaluation criteria. Methods A systematic review of the literature has been carried out through PUBMED, SCOPUS, ISI Web of Knowledge, Google and grey literature sources using the following inclusion criteria: research articles, systematic reviews, documents of eminent scientific societies, government agencies and research organizations focused on evaluation tools for genetic test. A DELPHI survey, undertaken with international experts in Public Health Genomics, will be performed to reach consensus on data extraction. Results Preliminary results consist of 19 tools published between 2000 and 2012 (10 in USA, three in Canada, six in Europe), mostly based on the ACCE model (n.10 tools) and on the HTA model (n.5 tools). Sixteen tools address all types of genetic test, while the others take into account a specific type of genetic test (newborn screening, predictive genetic tests, genetic susceptibility tests). The evaluation criteria adopted by the vast majority of the tools (n.16 tools) are analytic and clinical validity, clinical utility, ethical legal and social issues. At a glance, the evaluation of the economic aspects seems insufficient. Conclusions The comparative analysis of the strengths and weaknesses of the retrieved evaluation tools will be the basis for the choice of the most appropriate process of genetic test evaluation that should take into account national and local contexts. Key messages Our preliminary search has retrieved 19 tools for the evaluation of genetic tests, developed in the last fifteen years This systematic review will provide the basis for adapting comprehensive and appropriate processes of genetic test evaluation to the different national and local contexts
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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 | 0.208 | 0.472 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.024 | 0.030 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".