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Enregistrement W3212166614 · doi:10.1182/blood-2021-153045

Propensity Score Matching Analysis Comparing Extracorporeal Photopheresis (ECP) Vs Best Available Therapy in Third Line or Later Treatment of Chronic Graft-Versus-Host Disease (cGVHD)

2021· article· en· W3212166614 sur OpenAlexaff
Swe Mar Linn, Igor Novitzky‐Basso, Elizabeth Shin, Christopher J. Patriquin, Ivan Pašić, Wilson Lam, Arjun Law, Fotios V. Michelis, Armin Gerbitz, Auro Viswabandya, Jeffrey H. Lipton, Rajat Kumar, Jonas Mattsson, David Barth, Dennis Dong Hwan Kim

Notice bibliographique

RevueBlood · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueHematopoietic Stem Cell Transplantation
Établissements canadiensUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicinePrednisoneExtracorporeal PhotopheresisPropensity score matchingRituximabPhotopheresisInternal medicineGraft-versus-host diseaseRandomized controlled trialMaintenance therapyCohortRetrospective cohort studySurgeryTransplantationChemotherapyDiseaseLymphoma

Résumé

récupéré en direct d'OpenAlex

Abstract *DB and DK contributed to the work equally Background Prospective randomized controlled data comparing extracorporeal photopheresis (ECP) to other treatments for chronic graft vs host disease (cGvHD) as third-line or later therapy are limited, despite its clinical benefit observed in patients (pts) who failed ≥ 2 lines of previous therapy. Our single-center experience has reported promising results, including 68.3% failure-free survival (FFS) and 85.9% overall survival (OS) at 12 months in 75 heavily pre-treated cGvHD pts treated with ECP (ASH 2021 Abstract ID 152640). The present study compared outcomes, using propensity-score matching (PSM), between ECP ("ECP group", n=74) and a historical cohort treated with best available therapy (BAT) as third-line or later treatment from 2007 to 2021 ("BAT group", n=132). Statistical endpoints such as FFS and OS, as well as steroid dose reduction were evaluated instead of overall response due to limited response assessment data available from retrospective chart review. Patients and methods The BAT group received MMF (n=71, 53.8%), prednisone (n=37, 28.0%), prednisone/cyclosporine (n=7, 5.3%), rituximab (n=7, 5.3%), and others (n=10, 7.6%). There was an imbalance in characteristics between the two groups, as expected; the ECP group had more pts with severe cGVHD (91.1% vs 20.5%; p<0.001), fewer with a previous history of acute GVHD (aGvHD: 60.8% vs 78.0%; p=0.008), and fewer on a prednisone dose ≥0.5mg/kg/day (37.8% vs. 90.5%; p<0.001). PSM analysis was applied to adjust risk factors imbalanced between groups, including cGVHD grade (mild/moderate vs severe), aGVHD history, and baseline prednisone dose (<0.5 vs. ≥ 0.5 mg/kg/day). A total of 54 pts (27 case-control pairs) were selected via PSM within 0.2 of a calliper difference, resulting in the balancing of risk factors between groups: cGVHD severity (p=0.941), aGVHD history (p=0.75) and prednisone dose ≥ 0.5 mg/kg/day (p=0.788). FFS and OS were calculated from the day of starting ECP or BAT, and were compared using Cox's hazard model. Daily prednisone dose at months 0, 3 and 6 were calculated divided by body weight (kg), and the proportions of pts on prednisone ≤ 0, 0.1, 0.2 and 0.5mg/kg/day were compared. Results In the overall cohort (n=206), with a median 29 months of follow-up, 114 treatment failures (55.3%) occurred. While the non-relapse mortality (NRM) was similar in both groups, the ECP group showed a lower rate of resistance requiring therapy switch. Failure was noted in 27 ECP pts (36.4%) due to causes including resistance/intolerance requiring a switch to other therapy (n=15; 20.3%), NRM (n=11, 14.8%), and relapse (n=1; 1.4%), while 87 failures (65.9%) were noted in BAT pts due to resistance requiring a switch to other therapy (n=63; 47.7%), NRM (n=7; 5.3%), and relapse (n=17; 12.9%). In the overall cohort, the 12-month FFS was 68.3% and 32.0% in ECP and BAT groups (p<0.0001; Fig 1A), while OS was 86.2% and 82.2% in ECP and BAT groups, respectively (p=0.333; Fig 1B). In the PSM cohort (n=54), the ECP group showed a survival benefit at 12 months: FFS was 65.8% in the ECP group vs. 30.5% in the BAT group (p=0.00226; Fig 2A), and OS was 76.6% in the ECP group vs. 67.1% in the BAT group (p=0.0977; Fig 2B). Multivariate analysis in the PSM cohort confirmed that ECP was superior to BAT for FFS (p=0.024, HR 0.317 [0.117-0.859]) when adjusted for other risk factors including cGVHD severity, aGvHD history, age, HCT-CI score and prednisone dose ≤0.5mg/kg/day. Prednisone doses were gradually reduced over time; the median doses of prednisone at months 0, 3, and 6 were 0.35, 0.22 and 0.11 mg/kg/day, respectively, in the ECP group vs. 0.96, 0.24 and 0.19mg/kg/day in the BAT group. ECP also showed better kinetics of steroid dose reduction over time; the proportions of pts who discontinued prednisone at months 0, 3 and 6 were 16.2, 17.6% and 32.4% in ECP group vs. 0.8%, 0% and 2.5% in BAT group (Fig 3). The differences in the proportion of pts (delta) who discontinued prednisone in the ECP vs. BAT groups were 15.4%, 17.6% and 29.9% at 0, 3, and 6 months, respectively. Conclusion In the current study using PSM analysis, use of ECP was associated with a superior FFS to BAT when used as third-line or later therapy in cGVHD patients who failed at least 2 lines of previous therapy. Use of ECP also allowed for better steroid tapering in comparison to BAT. Figure 1 Figure 1. Disclosures Patriquin: Alexion: Consultancy, Honoraria, Speakers Bureau; BioCryst Pharmaceuticals: Honoraria; AstraZeneca: Consultancy, Honoraria, Speakers Bureau; Apellis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria. Law: Novartis: Consultancy; Actinium Pharmaceuticals: Research Funding. Lipton: Bristol Myers Squibb, Ariad, Pfizer, Novartis: Consultancy, Research Funding. Mattsson: MattssonAB medical: Current Employment, Current holder of individual stocks in a privately-held company. Kim: Novartis: Consultancy, Honoraria, Research Funding; Paladin: Consultancy, Honoraria, Research Funding; Bristol-Meier Squibb: Research Funding; Pfizer: Honoraria.

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)0,006
score de la tête « metaresearch » (Gemma)0,008
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai non randomisé · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,006
Score d'incertitude au seuil0,032

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,008
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,081
Tête enseignante GPT0,291
Écart entre enseignants0,210 · 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'étudeEssai non randomisé
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

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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