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Enregistrement W2911926938 · doi:10.1182/blood-2018-99-119472

Comprehensive Analysis of Systemic Immunosuppression (SIS) Duration after Allogeneic Hematopoietic Stem Cell Transplant: Risk Score Model Provides Stratification of Patients According to Probability of SIS Discontinuation

2018· article· en· W2911926938 sur OpenAlexaff
Maria Rhida Bautista, Arjun Law, Wilson Lam, Fotios V. Michelis, Santhosh Thyagu, Auro Viswabandya, Rajat Kumar, Jeff H. Lipton, Hans A. Messner, Dennis Dong Hwan Kim

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueHematopoietic Stem Cell Transplantation
Établissements canadiensPrincess Margaret Cancer CentreUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineDiscontinuationCumulative incidenceInternal medicineHazard ratioImmunosuppressionTransplantationHematopoietic stem cell transplantationUnivariate analysisRetrospective cohort studyProportional hazards modelMultivariate analysisGraft-versus-host diseaseConfidence intervalOncology

Résumé

récupéré en direct d'OpenAlex

Abstract BACKGROUND: Systemic immunosuppression (SIS) is the standard treatment for significant acute and chronic graft versus host disease (GVHD) after allogeneic hematopoietic cell transplantation (HCT). Previous studies have shown that 30-70% of patients require immunosuppressive treatment for GVHD for more than 2 years. Prolonged SIS increases the risk of infections, recurrence of malignancy and multi-organ complications including endocrine dysfunction, hypertension, myopathy and ocular complications. This study aimed to evaluate the predictive factors associated with increased likelihood of SIS discontinuation from 3 different time points: from the day of transplant in all patients, from the day of treatment of acute GVHD (aGVHD) and from the day of treatment of chronic GVHD (cGVHD). METHODS: A retrospective review was conducted in 674 consecutive patients who underwent allogeneic HCT at Princess Margaret Cancer Centre from 2004 to 2013. Analyses were done using cumulative incidence method considering competing risks for SIS discontinuation. The incidence of SIS discontinuation was calculated from 3 time points: from the day of transplant in all patients, from the day of treatment of aGVHD and from the day of treatment of cGVHD. Univariate and multivariate analyses were conducted to identify the predictive factors for SIS discontinuation and hazard ratio (HR) with 95% confidence interval (CI) was calculated using Fine-Gray model. Risk score models were generated based on the results from the multivariate analysis with respect to the 3 time points. Each predictive factor was weighted according to the HR. Risk score models are presented in the Table below: for each risk score model, the patients were divided into 3 risk groups based on the scores. The cumulative incidence of SIS discontinuation was compared according to the risk group for each risk score model as shown in the Figure below. RESULTS: With a median follow-up duration of 3.5 years, the probability of SIS cessation at 3 years was 30.7% (27.0-34.5%) in all patients (n=674), 25.4% (21.2-29.8%) in patients treated for aGVHD (n=457) and 34.6% (29.1-40.3%) in patients treated for cGVHD (n=347). Multivariate analysis confirmed the following predictive factors associated with increased likelihood of SIS discontinuation. In all patients (n=654): age >50 years (vs ≤ 50 yrs; p<0.001, HR 1.83), bone marrow (BM) as a source of stem cells (vs peripheral blood [PBSC]; p=0.002, HR 1.78), T-cell depletion (vs no T-cell depletion; p<0.001, HR 1.98), matched related donor (vs others; p<0.001, HR 1.81) and HLA match (vs partially mismatched HLA; p=0.026, HR 2.58). In patients treated for aGVHD (n=457): age>50 (vs ≤ 50 yrs; p<0.001, HR 1.77), BM (vs PBSC; p<0.001, HR 2.38), matched related donor (vs others; p=0.025, HR 1.55) and aGVHD grade 0-2 (vs grade 3/4 aGVHD; p<0.001, HR 1.77). In patients treated for cGVHD (n=347): age >50 (vs ≤ 50 yrs; p=0.002, HR 1.83), BM (vs PBSC; p=0.004, HR 2.13), Grade 0-2 aGVHD (vs grade 3/4 aGVHD; p=0.003, HR 2.32), cGVHD grade (mild vs moderate vs severe; p<0.001, HR 2.02) and classical subtype (vs overlap syndrome; p=0.028, HR 1.52). The risk score model stratified the patients into low, intermediate and high risk groups: for all patients, SIS discontinuation at 3 years was 52.5% (37.9-65.2%), 30.7% (26.5-35.0%) and 17% (8.6-27.7%) respectively (p<0.0001); in patients treated for aGVHD, SIS discontinuation at 3 years was 70.6% (39.0-87.9%), 29.2% (24.0-34.5%) and 2.7% (0.5-8.6%) respectively (p<0.001); in patients treated for cGVHD, SIS discontinuation at 3 years was 62.8% (48.4-74.3%), 36.4% (29.8-43.0%) and 5.7% (1.0-17.1%) respectively (p<0.001). CONCLUSIONS: Older age, bone marrow as a source of stem cells, T-cell depletion, matched related donor and a full matched donor increase the likelihood of discontinuation of SIS after allogeneic HCT. In addition, the severity of aGVHD and cGVHD significantly affects the chance of SIS discontinuation. The proposed risk score stratifies patients into well-defined groups according to the chance of SIS discontinuation. Further studies in a larger number of patients are strongly recommended to validate this finding. Prospective validation is also warranted to confirm the utility of the risk score as a clinical tool for estimation of likelihood of SIS discontinuation in patients after allogeneic HCT. Figure. Figure. Disclosures Lipton: Pfizer: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding.

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)0,003
score de la tête « metaresearch » (Gemma)0,007
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 enseignants0,003
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,007
Méta-épidémiologie (sens strict)0,0010,000
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 recherche0,0000,001
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 Opus0,019
Tête enseignante GPT0,249
Écart entre enseignants0,230 · 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

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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