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Enregistrement W4386209370

Carrier Screening Programs for Cystic Fibrosis, Fragile X Syndrome, Hemoglobinopathies and Thalassemia, and Spinal Muscular Atrophy: A Health Technology Assessment.

2023· article· en· W4386209370 sur OpenAlexaboutno aff

Notice bibliographique

RevuePubMed · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueCystic Fibrosis Research Advances
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineCarrier testingNewborn screeningSpinal muscular atrophyFragile X syndromeSMA*Systematic reviewCost effectivenessPediatricsPhysical therapyPrenatal diagnosisMEDLINEPregnancyInternal medicineDiseasePsychiatryRisk analysis (engineering)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background: We conducted a health technology assessment to evaluate the safety, effectiveness, and cost-effectiveness of carrier screening programs for cystic fibrosis (CF), fragile X syndrome (FXS), hemoglobinopathies and thalassemia, and spinal muscular atrophy (SMA) in people who are considering a pregnancy or who are pregnant. We also evaluated the budget impact of publicly funding carrier screening programs, and patient preferences and values. Methods: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using the Cochrane Risk of Bias tool and the Risk of Bias Assessment tool for Non-randomized Studies (RoBANS), and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature search and conducted cost-effectiveness analyses comparing preconception or prenatal carrier screening programs to no screening. We considered four carrier screening strategies: 1) universal screening with standard panels; 2) universal screening with a hypothetical expanded panel; 3) risk-based screening with standard panels; and 4) risk-based screening with a hypothetical expanded panel. We also estimated the 5-year budget impact of publicly funding preconception or prenatal carrier screening programs for the given conditions in Ontario. To contextualize the potential value of carrier screening, we spoke with 22 people who had sought out carrier screening. Results: We included 107 studies in the clinical evidence review. Carrier screening for CF, hemoglobinopathies and thalassemia, FXS, and SMA likely results in the identification of couples with an increased chance of having an affected pregnancy (GRADE: Moderate). Screening likely impacts reproductive decision-making (GRADE: Moderate) and may result in lower anxiety among pregnant people, although the evidence is uncertain (GRADE: Very low).We included 21 studies in the economic evidence review, but none of the study findings were directly applicable to the Ontario context. Our cost-effectiveness analyses showed that in the short term, preconception or prenatal carrier screening programs identified more at-risk pregnancies (i.e., couples that tested positive) and provided more reproductive choice options compared with no screening, but were associated with higher costs. While all screening strategies had similar values for health outcomes, when comparing all strategies together, universal screening with standard panels was the most cost-effective strategy for both preconception and prenatal periods. The incremental cost-effectiveness ratios (ICERs) of universal screening with standard panels compared with no screening in the preconception period were $29,106 per additional at-risk pregnancy detected and $367,731 per affected birth averted; the corresponding ICERs in the prenatal period were about $29,759 per additional at-risk pregnancy detected and $431,807 per affected birth averted.We estimated that publicly funding a universal carrier screening program in the preconception period over the next 5 years would require between $208 million and $491 million. Publicly funding a risk-based screening program in the preconception period over the next 5 years would require between $1.3 million and $2.7 million. Publicly funding a universal carrier screening program in the prenatal period over the next 5 years would require between $128 million and $305 million. Publicly funding a risk-based screening program in the prenatal period over the next 5 years would require between $0.8 million and $1.7 million. Accounting for treatment costs of the screened health conditions resulted in a decrease in the budget impact of universally provided carrier screening programs or cost savings for risk-based programs.Participants value the perceived potential positive impact of carrier screening programs such as medical benefits from early detection and treatment, information for reproductive decision-making, and the social benefit of awareness and preparation. There was a strong preference expressed for thorough, timely, unbiased information to allow for informed reproductive decision-making. Conclusions: Carrier screening for CF, FXS, hemoglobinopathies and thalassemia, and SMA is effective at identifying at-risk couples, and test results may impact preconception and reproductive decision-making.The cost-effectiveness and budget impact of carrier screening programs are uncertain for Ontario. Over the short term, carrier screening programs are associated with higher costs, and also higher chances of detecting at-risk pregnancies compared with no screening. The 5-year budget impact of publicly funding universal carrier screening programs is larger than that of risk-based programs. However, accounting for treatment costs of the screened health conditions results in a decrease in the total additional costs for universal carrier screening programs or in cost savings for risk-based programs.The people we spoke with who had sought out carrier screening valued the potential medical benefits of early detection and treatment, particularly the support and preparation for having a child with a potential genetic condition.

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)0,056
score de la tête « metaresearch » (Gemma)0,196
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,056
Score d'incertitude au seuil0,298

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0560,196
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0060,020
Bibliométrie0,0180,013
Études des sciences et des technologies0,0010,001
Communication savante0,0040,003
Science ouverte0,0020,003
Intégrité de la recherche0,0040,003
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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 Opus0,026
Tête enseignante GPT0,319
Écart entre enseignants0,293 · 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'étudeRevue systématique
Domainenon disponible
GenreSynthèse

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

En bref

Citations5
Publié2023
Routes d'admission1
Résumé présentoui

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