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Enregistrement W2989166112 · doi:10.1182/blood-2019-125344

Epidemiology of Post-Transplant Lymphoproliferative Disorders in Children with Solid Organ Transplant over 34 Years of a Single Center Experience

2019· article· en· W2989166112 sur OpenAlexaffabout
Marta Rojas Vasquez, Anthea Peters, Raymond Lai, Curtis Mabilangan, Burton Catherine, Jutta K. Preiksaitis

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueViral-associated cancers and disorders
Établissements canadiensUniversity of AlbertaStollery Children's Hospital
Organismes subventionnairesnon disponible
Mots-clésImmunosuppressionMedicineLymphoproliferative disordersTransplantationSerostatusSingle CenterPopulationPediatricsInternal medicineEpidemiologyIncidence (geometry)ImmunologyViral loadLymphomaHuman immunodeficiency virus (HIV)

Résumé

récupéré en direct d'OpenAlex

Background Post-Transplant lymphoproliferative disorders (PTLD) are a heterogeneous group of lymphoid neoplasms following solid organ transplantation (SOT) caused by uncontrolled lymphoproliferation often induced by Epstein Barr Virus (EBV) due to the lack of cytotoxic T cell response resulting from immunosuppression. A pre-emptive intervention strategy for PTLD prevention was implemented in our center in 2002 for all EBV-mismatched SOT recipients consisting in close monitoring of the viral load and consideration for early intervention (Ex; reduction of immunosuppression) in addition to universal antiviral prophylaxis (implemented in 1990). We aim to describe the incidence and risk factors for PTLD in children with SOT, including all transplant types, at a single center over 34 years. We also aim to analyze the impact of a pre-emptive PTLD prevention program. Material and methods All patients younger than 18 years of age who received SOT at the University of Alberta Hospital/Stollery Children's Hospital from January 1st, 1984 to December 31st, 2018 were included. Donor and recipient baseline data (age, sex, donor living status, date and type of transplant, EBV and cytomegalovirus serostatus) were extracted from a prospective database. Retrospective chart review was performed for PTLD cases along with expert pathology review (when tissue available). Local Ethics Board was obtained. Statistical analyses were performed using SPSS software version 25 and R version 3.3.3. Results Characteristics of the study population, immunosuppression regimen used by transplant program and specific immunosuppression for PTLD cases are summarized in table 1, 2 and 3 respectively. PTLD characteristics were compared based on the time of presentation of PTLD ≤1 year, 1 to 5 years and >5 years (table 4). Most of the cases with PTLD presented with primary involvement in multiple sites followed by lymph nodes, gastro-intestinal tract, allograft, tonsils/adenoids and other sites. Advance staging (III-IV) was present in 71% of cases. The incidence rate of PTLD for the whole group was 0.82/100 Person-year (Figure 1 A). The incidence rate peaked at 1-year post-transplant and had a decreasing trend in the following years post-transplant, with no cases beyond 12 years post-transplant (Figure 1 B). The cumulative incidence was the highest for the multi-visceral transplants followed by thoracic, liver and kidney transplants (Figure 1C). Univariate analysis showed children younger than 5 years at transplant had 5-fold higher risk of PTLD compared to children ≥ 10 years of age at transplant. Donors ≤ 5 years of age at transplant, showed 3-fold higher risk PTLD comparing to older donors. Liver transplant had 2.8-fold and thoracic transplants had 5-fold higher risk of PTLD comparing to kidney transplants, no significant risk was associated with multi-visceral group (only 1 case in the cohort). EBV seronegative recipient was associated with 2.6-fold higher risk of PTLD comparing to EBV seropositive recipient. Era prior to implementation of pre-emptive intervention had 3-fold risk of PTLD comparing to era post implementation. Patients transplanted at 1.1 - 5 years of age was an independent risk factor associated with PTLD in multivariate analysis (table 3) SOT recipients showed EBV seroconversion with age (Figure 3A). PTLD based on EBV Donor Recipient (DR) serostatus showed more cases D positive R negative (D+R-) in the first-year comparing to D negative Recipient negative (D-R-), D-R- cases increased between 1-5 years equivalent to D+R-, beyond 5 years D+R- decreased with no D-R- cases (Figure 3B). D-R- serostatus had the highest probability of PTLD followed by D+R- (Figure 3 C). Eleven (24%) out of 45 patients with PTLD presented with PTLD relapse. Seven (5.6%) out of 125 deaths of SOT were secondary to PTLD. PTLD was the most common cause of death in the PTLD group (50%) followed by graft failure/rejection. Conclusions Incidence of PTLD peaked in the first-year post-transplant and decreased overtime with increase incidence in thoracic and multi-visceral transplants. Risk factors for PTLD included patients transplanted at younger age, younger donors, thoracic and liver transplants and EBV seronegativity in the recipient. A pre-emptive intervention strategy for PTLD prevention implemented in 2002 decreased the risk of PTLD. Disclosures No relevant conflicts of interest to declare.

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)0,001
score de la tête « metaresearch » (Gemma)0,002
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 enseignants0,009
Score d'incertitude au seuil0,017

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
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 Opus0,007
Tête enseignante GPT0,243
Écart entre enseignants0,236 · 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

Citations1
Publié2019
Routes d'admission2
Résumé présentoui

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