Extranodal involvement of the gastrointestinal tract in post transplant lymphoproliferative disorders: Stomach or small bowel involvement increases mortality risk
Notice bibliographique
Résumé
Abstract Post transplant lymphoproliferative disorder (PTLD) is a group of heterogeneous lymphoid disorders that represent a clinically significant complication in patients with a history of solid organ transplant. Most patients (50-80%) present with extranodal involvement, with common involvement of the gastrointestinal (GI) tract, seen in 23-30% of all PTLD cases. Using registry data on PTLD patients in Edmonton, Alberta, Canada, we focused on rates of clinically relevant GI related events including GI obstruction, perforation, GI surgery and severe GI bleeding in those with or without GI tract involvement. We also report an analysis of the impact of demographic, clinical and laboratory parameters on overall survival (OS). Newly diagnosed adult patients with biopsy proven PTLD presenting to our institution from January 2008 to February 2025 were included in the analysis. Primary CNS cases were excluded. Baseline characteristics, survival data and significant GI events were collected. Overall survival (OS) was estimated from the date of diagnosis of the first PTLD diagnosis using the Kaplan Meier method (SPSS version 31.0.0.0). Cox regression analyses were used to predict associations of baseline characteristics with OS. A total of 88 adult patients were identified with newly diagnosed PTLD, 61 males and 27 females. Median age at diagnosis was 59.7y. Transplant types included kidney (45), lung (17), heart (14), liver (9), pancreas (3), islet cell (2) and small bowel (1). Median age at transplantation was 47.1y. Median time from transplant to PTLD diagnosis was 11.25y. At diagnosis, 64/88 (73%) were stage III/IV and ECOG was ≥2 in 56/88 (64%). The majority had monomorphic PTLD (79/88, 90%), and EBER was positive in 35/88 cases (40%). Most patients had GI tract involvement by FDG-PET scan or biopsy (48/88 (55%)). GI events occurred in 21 patients within 60d of diagnosis (44.7%): 24 patients required GI surgery, 15 had GI obstructions, 9 had perforations and 7 had severe GI bleeding events (hemorrhagic shock, ICU admission or requiring urgent intervention). By survival cutoff of July 1, 2025, 53% (47/88) of patients had died. 57% (27/47) of deaths were attributed to PTLD or a complication of PTLD treatment. Of all deaths, six were directly attributable to GI events, four were within 60d of diagnosis. Median overall survival (OS) was 5.5y (95% CI 1.59-9.41y). Increased age at PTLD diagnosis (HR 1.03 per year, 95% CI 1.01-1.06, p=0.005), increased IPI (HR 1.49 per unit increase, 95% CI 1.16-1.91, p=0.002), age >60 (HR 2.36, 95% CI 1.29-4.31, p=0.005) and ECOG ≥2 (HR 2.19, 95% CI 1.11-4.30, p=0.024) predicted mortality. Hemoglobin <120 g/L (12g/dL) (HR 2.78, 95%CI 1.18-6.57, p=0.02) and eGFR <60 mL/min/1.73m2 (HR 3.35, 95%CI 1.49-7.53, p=0.003) predicted OS. Other significant predictors of mortality included lung transplant type (HR 2.39, p=0.006), and peritoneal involvement/ascites (8 cases, HR 2.94, p=0.009). LDH, advanced stage, multiple extranodal sites, monomorphic subtype, EBER positivity and GI tract involvement were not significant predictors of mortality in univariate analysis. However, GI involvement of stomach or esophagus (7 cases, HR 2.75, 95% CI 1.16-6.56, p=0.022) and small bowel (37 cases, HR 1.86, 95% CI 1.04-3.34, p=0.037) were significant, whereas large bowel involvement was not (24 cases, p=56). In conclusion, our registry based analysis demonstrates the significant early and overall mortality in patients with newly diagnosed PTLD. GI tract involvement was common in our cohort and frequently resulted in complications. Although GI involvement did not significantly predict mortality risk, involvement of the stomach, esophagus and small bowel, as opposed to large bowel involvement, did significantly increase mortality risk. In addition, peritoneal involvement of PTLD was a poor prognostic feature. We will include multivariable analyses at the meeting.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».