Performance of international phenotypic criteria for prenatal exome sequencing: systematic review and comparative diagnostic accuracy study using historical individual participant data
Bibliographic record
Abstract
OBJECTIVES: To evaluate: (i) the performance of the National Health Service (NHS) phenotypic eligibility criteria for prenatal exome sequencing (pES); (ii) the diagnostic yield of individual NHS criteria; (iii) the diagnostic yield when one or multiple NHS criteria were met; and (iv) the performance of the NHS criteria compared with that of phenotypic eligibility criteria used in other countries/regions. METHODS: An online survey was circulated to healthcare professionals in 120 countries to gather information on whether pES is offered in their country and how case selection is performed. Five predefined sets of phenotypic eligibility criteria from England, Greece, Canada (British Columbia and Ontario) and Spain were tested on a virtual historical cohort of 1054 'unselected' structurally abnormal fetuses undergoing pES, derived from a published systematic review. The performance of the current and previous gene panels used in the NHS pES service was assessed in the unselected cohort. The sensitivity and specificity with 95% CI for each set of criteria in relation to diagnostic yield for pathogenic and likely pathogenic variants were calculated, along with the area under the summary receiver-operating-characteristics curve (AUC). RESULTS: The electronic survey received 261 responses from 63/120 countries. Where deducible, 81.8% (45/55) of the countries surveyed offered pES. Where stated, most (90.3% (28/31)) cases were selected for pES on a case-by-case basis, according to fetal phenotype and the likelihood of an association with a monogenic condition, rather than on the basis of predetermined phenotypic criteria. The total diagnostic yield of the NHS criteria when applied to all relevant cases for pES was 27.8% (69/248), with pooled sensitivity, pooled specificity and AUC of 49.8% (95% CI, 31.7-67.9%), 80.7% (95% CI, 59.6-92.2%) and 0.66 (95% CI, 0.53-0.74), respectively. The diagnostic yield was highest for isolated short long bones (58.3% (7/12)). The likelihood of a monogenic diagnosis did not increase significantly as the number of NHS criteria met increased. There was a significant increase in the diagnostic yield of the current (2024) vs original (2020) gene panel adopted by the NHS (129/135 (95.6%) vs 118/135 (87.4%); P = 0.017). The four other sets of phenotypic criteria used in other countries/regions performed moderately well, with the best performance seen for the British Columbia criteria, which had a pooled sensitivity of 70.5% (95% CI, 43.7-88.1%), pooled specificity of 68.9% (95% CI, 37.5-89.1%) and AUC of 0.73 (95% CI, 0.58-0.79). CONCLUSIONS: In the majority of countries for which there was a survey response, pES was offered on a case-by-case basis, according to fetal phenotype and the likelihood of an underlying monogenic condition. Existing phenotypic eligibility criteria for pES performed modestly. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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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 | 0.057 | 0.214 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".