Performance of international phenotypic criteria for prenatal exome sequencing: systematic review and comparative diagnostic accuracy study using historical individual participant data
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,057 | 0,214 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,008 |
| Bibliométrie | 0,012 | 0,012 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».