Measuring the Effect of Newborn Screening on Survival After Hematopoietic Cell Transplantation for Severe Combined Immunodeficiency: A 36-Year Longitudinal Study From the Primary Immune Deficiency Treatment Consortium
Notice bibliographique
Résumé
To explore the effects of the implementation of population-based newborn screening for Severe Combined Immunodeficiency (SCID) on overall survival in patients with SCID after hematopoietic cell transplantation (HCT).After exclusions, the study included 902 children with SCID from 34 Primary Immune Deficiency Treatment Consortium sites in the United States and Canada who underwent allogeneic HCT between January 1, 1982 and December 31, 2018.Data such as sex, race and ethnicity, SCID type and genotype, trigger for diagnosis (newborn screening, family history, or clinical illness), age at HCT, time interval of HCT, infection status at HCT, transplant-related data, and date of death were collected. The Kaplan-Meier method was used to estimate overall survival. A risk adjustment model using Cox proportional hazards regression was used to analyze risk factors for HCT outcomes.Before 2010, the 5-year overall survival rate for children with SCID was 72% to 73%, with 32% to 33% of SCID diagnoses made because of preventative testing by family history, and 65% to 67% of diagnoses resulting from presenting clinical illness. Between 2010 and 2018, the 5-year overall survival rate significantly increased to 87%. Forty-nine percent of these diagnoses were made because of positive SCID newborn screening, whereas 33% of diagnoses resulted from presenting clinical illness. Since 2010, the 5-year overall survival rate was significantly higher in children diagnosed with SCID via newborn screening (92.5%) compared with children whose diagnosis resulted from presenting clinical illness (79.9%) or family history (85.4%). Risk factors for increased mortality, including active infection, age 3.5 months or older at HCT, Black or African American race, and specific SCID genotypes, were identified using multivariable analysis.There is marked benefit in population-based newborn SCID screening on overall survival of patients by facilitating early HCT and preventing infection.To our knowledge, this is the largest longitudinal multi-institutional study that has demonstrated the positive impact of population-based newborn SCID screening on the survival of patients with SCID who underwent HCT. This has led to a paradigm shift in the declining number of presenting infections and a higher frequency of HCT being performed before 3.5 months of age. Delayed SCID diagnosis can be a significant public health cost burden as these children will experience repeat hospitalizations, morbidity, and mortality. Newborn screening not only alleviates cost but also effectively treats these patients. Interestingly, African American children with SCID had the highest risk of death. Further studies are warranted to investigate factors contributing to disparities in care for this patient population.
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 | 0,003 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».