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Enregistrement W1900171141 · doi:10.1093/clinchem/48.4.653

Accuracy of Expected Risk of Down Syndrome Using the Second-Trimester Triple Test

2002· article· en· W1900171141 sur OpenAlexaffabout
Chris Meier, Tianhua Huang, Philip Wyatt, Anne Summers

Notice bibliographique

RevueClinical Chemistry · 2002
Typearticle
Langueen
DomaineMedicine
ThématiquePrenatal Screening and Diagnostics
Établissements canadiensNorth York General Hospital
Organismes subventionnairesnon disponible
Mots-clésDown syndromeMedicineTriple testEstriolPregnancyObstetricsHuman chorionic gonadotropinRisk assessmentPrenatal screeningCutoffGynecologyPrenatal diagnosisInternal medicineFetusBiologyHormone

Résumé

récupéré en direct d'OpenAlex

Second-trimester maternal serum screening (MSS) for Down syndrome has been widely used in routine prenatal care in developed countries. The screening combines maternal age-specific risk of Down syndrome with risk estimation obtained by measuring maternal serum markers to assign women an expected risk of having a term Down syndrome pregnancy. Diagnostic tests were offered to women whose risk exceeded the risk cutoff determined by the screening program. The commonly used triple test, which involves the use of maternal age, serum α-fetoprotein, unconjugated estriol, and human chorionic gonadotropin, was expected to have a Down syndrome detection rate of 60–65% and false-positive rate of 5% (1). Although the expected screening performance has been achieved in many screening programs, the accuracy of individual risk calculated by a relatively complex computation based on a statistical model was not immediately obvious. Good agreement between the expected risk of Down syndrome and observed prevalence has been reported previously in several screening programs (2)(3)(4)(5). We evaluated the accuracy of expected risk of Down syndrome in a large provincial, multiple test center, MSS program in Ontario, Canada. MSS has been coordinated at the provincial level in Ontario since 1993. Triple maker screening (α-fetoprotein, unconjugated estriol, and β-human chorionic gonadotropin) was carried out in seven regional laboratory centers. Information including screen utilization, results, follow-up data, and the pregnancy outcomes of all women screened in the seven centers was collected in the Ontario MSS database. Data on outcomes for all pregnancies screened were obtained through the Canadian Institute of Health Information, which records every hospital admission in Canada. Where necessary, information was verified through provincial genetic-counseling centers and cytogenetic laboratories. Using this protocol, we obtained 94.4% of outcomes. The study was based on 311 256 women screened in the Ontario MSS program between October 1993 and September 1998. Of the 311 256 women screened, a Down syndrome risk level was recorded for 301 700, and 284 804 (94.4%) of them had outcome data from Canadian Institute of Health Information, including 506 pregnancies associated with Down syndrome. The expected risks of a term Down syndrome pregnancy were calculated with AFP Expert (Benetech). The risk cutoff used in the Ontario MSS program was 1 in 385. Using a technique described by Wald et al. (2), we ranked the women screened according to their individual expected risk of Down syndrome. They were divided into 10 groups, each group containing 44–59 cases of Down syndrome pregnancies. Two factors were considered when grouping the cases: (a) that each risk group covered an appropriate risk range; and (b) that there was a similar number of cases in each group. The mean expected term risks of an affected pregnancy were calculated for each group. The risks were then compared with the observed risks (prevalence) of that particular group (2). Because it was estimated that 23% of Down syndrome pregnancies will abort spontaneously after 16 weeks of gestation, cases with positive screening results (risk, ≥1 in 385 in our program) and diagnosed prenatally were multiplied by 77% to allow for the spontaneous fetal losses (6). Table 1 compares the expected risk of Down syndrome with its observed prevalence; it gives the risk category, the mean expected risk, number of Down syndrome cases, adjusted number of Down syndrome cases, and observed birth prevalence of Down syndrome for each group of women. The mean expected risks were close to the observed prevalence across all the risk groups, particularly for women with very high expected risks (women in risk groups 1 in 8 or greater, 1 in 9 to 1 in 25, and 1 in 26 to 1 in 45). Expected risk at term and observed birth prevalence of Down syndrome (triple test; Ontario, October 1993 to September 1998). Number of Down syndrome pregnancies with positive MSS results and diagnosed prenatally multiplied by 0.77 to adjust for spontaneous loss subsequent to amniocentesis. Expected risk at term and observed birth prevalence of Down syndrome (triple test; Ontario, October 1993 to September 1998). Number of Down syndrome pregnancies with positive MSS results and diagnosed prenatally multiplied by 0.77 to adjust for spontaneous loss subsequent to amniocentesis. The logarithmic transformed mean expected risks of Down syndrome are plotted against the logarithmic transformed observed prevalence in Fig. 1. The plot shows that the mean expected risk of Down syndrome was close to the observed prevalence (R2 = 0.9901). Association between mean expected risk and observed birth prevalence of Down syndrome (triple test; Ontario, October 1993 to September 1998). The diagonal line represents perfect agreement between observed and predicted rates. Results from regression analysis: y = 0.97x − 0.06 (R2 = 0.988). Good agreement between the expected and observed risks of Down syndrome has been reported in several studies. Wald and colleagues (2)(4) described a technique that can be used to validate the expected risk of Down syndrome. Using this method, they compared expected risk of Down syndrome with the prevalence observed in their screening program. The studies consisted of approximately 120 000 women screened, including 153 cases of Down syndrome screened with the triple test and 86 cases of Down syndrome screened with the quadruple test. The results showed that the estimated risks were accurate across the entire range of risks (2)(4). Similar results were reported by Canick and Rish (3), who detected in their program 66 cases of Down syndrome among the 49 139 women screened with the triple test. The agreement between expected and observed risks of Down syndrome was also assessed by Onda et al. (5) based on 9350 Japanese women screened using triple test and 24 Down syndrome cases. To our knowledge, our data set is the largest for assessing agreement between expected and observed risks of Down syndrome. Our results showed that the expected risks of Down syndrome assigned to individual women were close to the observed risks across all the risk ranges. The expected risks and observed risks for women in high risk groups (risk ≥1 in 45) were almost identical. We examined the completeness of the ascertainment of Down syndrome in our study population by comparing the expected number of Down syndrome cases with the number identified through the screening program. The expected number of Down syndrome births was estimated by applying the age-specific Down syndrome risk to the age distribution of women screened with an available outcome. In our study population, we would have expected 444 Down syndrome births in the absence of prenatal diagnosis and selective termination. After adjusting for spontaneous fetal losses, we would have expected 424 term Down syndrome pregnancies. The rate of ascertainment was consistent with that reported by Canick and Rish (3) in a similar, but small-scale, study. We have also estimated the completeness of this ascertainment by adding the actual observed number of Down syndrome births to the number terminated or lost spontaneously, multiplying by 0.77 to adjust for the spontaneous fetal losses. Using this adjustment, we identified 439 cases of term Down syndrome, a number very close to the expected 444 cases. In conclusion, the expected risk assigned to the individual woman in the Down syndrome serum screening program is accurate, reflecting the term risk of having a fetus with Down syndrome. We thank all members of the Ontario MSS consultative committee and participating MSS centers for their contributions to the Ontario MSS program. We also thank the women of Ontario for supporting the MSS program.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,007
score de la tête « metaresearch » (Gemma)0,043
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,172
Score d'incertitude au seuil0,343

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0070,043
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,067
Tête enseignante GPT0,347
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations20
Publié2002
Routes d'admission2
Résumé présentoui

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