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Enregistrement W4389220987 · doi:10.1182/blood-2023-182013

Impact of Publicly Reported Center Specific Analysis on Patient Selection Practices for Hematopoietic Stem Cell Transplantation

2023· article· en· W4389220987 sur OpenAlexaff
Christopher Strouse, Mark Juckett, Brent R. Logan, Noel Estrada‐Merly, Jaime M. Preussler, Tony H. Truong, Jesse D. Troy, Nandita Khera, William A. Wood, Hemalatha G. Rangarajan, Luke P. Akard, Neel S. Bhatt, Akshay Sharma, Wael Saber

Notice bibliographique

RevueBlood · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueGlobal Cancer Incidence and Screening
Établissements canadiensAlberta Children's Hospital
Organismes subventionnairesnon disponible
Mots-clésMedicineTransplantationPopulationHematopoietic cellConfidence intervalHematopoietic stem cell transplantationMultivariate analysisInternal medicineStem cellHaematopoiesisBiologyEnvironmental health

Résumé

récupéré en direct d'OpenAlex

Introduction Public reporting of outcomes drives healthcare improvement in many fields, including hematopoietic cell transplantation (HCT), although with possible unintended consequences. The Center for International Blood & Marrow Transplant Research (CIBMTR) publishes an annual Center-Specific Survival Analysis (CSA), which compares HCT centers' observed 1-year overall survival (OS) with their statistically modeled expected 1-year OS, with 95% confidence intervals (CI). Centers with OS within their 95% CI receive a 0 score, indicating as expected outcomes. Those with OS below / above their 95% CI receive a -1 / +1 score, indicating below / above expected OS, respectively. After a -1 report, centers may change their patient selection criteria, causing unintentional systematic exclusion of patient populations who could benefit from HCT. We analyzed how the CSA report influences patient selection practices among centers receiving a -1 score. Methods Centers receiving a -1 report between 2012 and 2016 that had ‘as expected’ survival in the preceding 2 years were classified as newly below expected OS centers (NBCs). The year of their -1 report was used as the index year. Centers with ‘as expected’ OS in the 3 years before and after each index year were identified as control centers, reflecting expected evolution of patient selection in the HCT field. The patient population variables analyzed are shown in Table 1. The difference in patient population characteristics in the 3 years before vs the 3 years after the index years defined the change in patient selection behavior at the NBCs and the controls. A multivariate model adjusting for baseline patient population characteristics and center size was used to compare the change in patient population from before and after the index year in the NBCs and that of the controls. The difference in differences (ΔinΔ) were calculated as ΔNBC - ΔControl. A significance threshold of p<0.01 was used to account for multiple testing. Results After adjusting for overall trends, center size, and baseline patient population characteristics, no differences in patient selection behavior meeting the pre-specified threshold for statistical significance were identified when comparing the NBCs (n=24 centers) with the controls (n=195 centers). In the 3 years following the index years, 4,150 and 25,013 patients were transplanted at NBCs and controls, respectively. The proportion of patients receiving reduced intensity or non-myeloablative conditioning regimens decreased 4.1% in NBCs and increased 5.0% in controls, for a net difference of -9.1% (95% CI: -16.7% to -1.6%, p=0.02). All other patient characteristic proportions changed in the same direction at NBCs and controls, albeit to varying degrees (Table 1). In some high-risk characteristics, (e.g. HCT-CI > 3), a greater increase was seen at NBCs vs controls (ΔinΔ 2.1% 95% CI: -2.8% to 6.9%, p=0.40). In others, (e.g. age 60+ years), a greater increase was seen at controls vs NBCs (ΔinΔ -2.6% 95% CI: -5.9% to 0.7%, p=0.12). To capture a holistic measure of centers' patient population risk, the predicted 1-year survival was compared in the NBCs vs controls using the logistic regression model generated for each year's CSA. The predicted OS increased by 3.08% and 3.30% in the NBCs and controls respectively, with no statistically significant difference (-0.23%, 95% CI: -1.4% to 0.9%, p=0.70, Figure 1). The observed overall survival (adjusted for predicted 1 year OS) also increased in both BECs and controls by 0.9% and 4.5% respectively, without statistically significant difference (-3.6%, 95% CI: -6.7% to -0.7%, p=0.02). Discussion For centers receiving a -1 report, no statistically significant changes were seen in patient population characteristics in the following 3 years when compared to centers with OS was as expected. There was variability in the changes in high-risk patient characteristics at the NBCs relative to the controls, and in some cases more patients with high-risk characteristics were selected at these centers compared to those at controls. The change in predicted overall survival at 1 year, a summary indicator of survival risk, was similar between BECs and control centers. Although the number of patients in centers with below expected OS was small, these findings suggest the public reporting of outcomes in HCT in the US does not unintentionally affect access to HCT for high-risk patients at NBCs.

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)0,025
score de la tête « metaresearch » (Gemma)0,080
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Évaluation · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,975
Score d'incertitude au seuil0,130

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0250,080
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0020,005
Études des sciences et des technologies0,0010,001
Communication savante0,0020,001
Science ouverte0,0010,002
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,092
Tête enseignante GPT0,361
Écart entre enseignants0,269 · 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.

Devis d'étudeObservationnel
DomaineÉvaluation
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

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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