The Changing Epidemiology of Posttransplant Lymphoproliferative Disorder in Adult Solid Organ Transplant Recipients Over 30 Years
Bibliographic record
Abstract
BACKGROUND: Posttransplant lymphoproliferative disorders (PTLD) are a complication of solid organ transplantation (SOT) associated with Epstein-Barr virus (EBV). METHODS: We analyzed the incidence of and risk factors for PTLD among adult SOT recipients at our center over 30 years (1984-2013). We also compared PTLD incidence before and after a prevention strategy of EBV viral load monitoring in EBV serology mismatched patients was adapted in 2001 (ie, transplant era 1 [1983-2001] vs era 2 [2002-2013]). RESULTS: Among 4171 SOT patients, 109 developed PTLD. Cumulative incidence at 1, 10, and 20 years posttransplant was 0.95, 2.3, and 3.5 per 100 person-years, respectively. Beyond the first year peak of almost exclusively EBV-positive PTLD, a lower incidence of PTLD, predominantly EBV negative, persisted for 20 years. Thoracic transplant (hazard ratio [HR], 2.1; P = 0.007) and negative EBV serology (HR, 7.7; P < 0.001) were independent risk factors for PTLD on multivariate Cox regression analysis. EBV seronegativity significantly increased risk of early (HR, 18.5) and EBV-positive PTLD (HR, 14.2), as well as late (HR, 4.9) and EBV-negative PTLD (HR, 3.6) on univariate analyses. Risk of early PTLD was significantly reduced in the recent transplant era (0.8% era 2 vs 1.9% era 1 at 5 years, P = 0.002); this reduction was seen in recent era EBV seropositive (P = 0.035 at 5 years) but not seronegative recipients (P = 0.90 year 5), suggesting lack of impact of viral load monitoring. CONCLUSIONS: Adult SOT recipients face a prolonged risk of late PTLD, whereas risk of early PTLD may have declined in recent years.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".