Epidemiology Of Post-Transplant Lymphoproliferative Disorders Following Solid Organ Transplant In a Major Canadian Transplant Centre
Bibliographic record
Abstract
Abstract Post-transplant lymphoproliferative disorder (PTLD) is a consequence of organ transplantation with a high risk of mortality. We analyzed records of all patients who received a solid organ transplant at the University of Alberta between 1984 and 2011 (n=4525). 133 patients developed PTLD over the follow up period of January 1984 to November 2012, including 61 cases that occurred less than 2 years after transplant ( early), 33 cases between 2 and 7 years after transplant (late), and 39 cases more than 7 years after transplant (very late). We calculated the cumulative incidence rate for PTLD. We also used Cox regression analysis to determine whether variables year of transplant, age at transplant, organ, and EBV serology mismatch influenced the risk of development of any PTLD, early and very late PTLD, and central nervous system (CNS) PTLD (any PTLD and early PTLD shown in Table 1). The cumulative incidence of any PTLD occurrence was 1.4% at 1 year, 2.6% at 5 years, 4.3% at 10 years, 6.6% at 15 years, and 7.9% at 20 years. Univariate analyses showed that year of transplant (1984-92 vs. 1993-2001 vs. 2002-2011) was not predictive of PTLD development (p=0.27, HR 0.88, CI 0.68-1.12). Patients aged 0-5 years at transplant had significantly higher risk of PTLD development (mean freedom from disease (FFD) 18.90 yrs, 95% CI 17.52-20.28) followed by patients over 60 (mean FFD 25.49 yrs, 95% CI 24.97-26.0; p value 0.000, hazard ratio (HR) 0.57, 95% CI 0.49-0.68). Among organs transplanted, multivisceral transplant conferred the highest risk (mean FFD 5.94, 95% CI 4.19-7.69, n=12) followed by lung transplant (mean FFD 15.45 yrs, 95% CI 17.76-19.83), whereas kidney transplant conferred the lowest risk (mean FFD 27.52 yrs, 95% CI 27.15-27.88; p=0.000, HR 0.57, 95% CI 0.49-0.68). Patients with EBV serology recipient to donor mismatch (ie. recipient negative, donor positive) also had a higher risk of PTLD development (mean FFD 22.9 yrs, 95% CI 21.2-24.6 vs. mean FFD 27.2 yrs, 95% CI 26.90-27.54, p=0.000, HR 8.79, 95% CI 5.83-13.24). Variables associated with increased risk of early PTLD development were year of transplant, with the highest risk in patients transplanted between 1984-1991 (mean FFD 27.88 yrs, 95% CI 27.51-28.24) and the lowest risk in those transplanted in 2002-2011 (mean FFD 10.7 yrs, 95% CI 10.69-10.79, p=0.002, HR 0.68, 95% CI 0.49-0.94); age, with the highest risk in patients 0-5 yrs (mean FFD 20.66, 95% CI 19.68-21.63), followed by over 60 yrs (mean FFD 26.17 yrs, 95% CI 25.98-26.36, p=0.000, HR 0.55, 95% CI 0.45-0.68); organ, with the highest risk in lung transplant (mean FFD 16.50 yrs, 95% CI 16.21-16.80), and the lowest risk in kidney transplant (mean FFD 28.40 yrs, 95% CI 28.30-28.96; p=0.000, HR 0.58, 95% CI 0.46-0.74), and EBV serologic mismatch (p=0.000, HR 18.62, 95% CI 10.45-33.20). In contrast, only organ significantly predicted development of late PTLD, with lung conferring the highest risk (mean FFD 16.27 yrs, 95% CI 15.6-16.94; p= 0.002, HR 0.53, 95% CI 0.39-0.73). Risk of development of CNS PTLD (n=10, either primary or secondary) was greater in patients with EBV serology mismatch (p=0.000, HR 19.95, CI 4.98-79.92), but no other variables significantly predicted its development. In conclusion, the risk of PTLD after solid organ transplant is increased even 20 years after transplant, but the risk of early PTLD is declining over time. The risk of PTLD is highest in patients 0-5 years of age at transplant, patients receiving lung transplant, and patients with EBV serologic mismatch.Total n (%)PTLD Cases (n=133) (%)p valueHazard ratio95% CIEARLY PTLD Cases (n=61) (%)p valueHazard ratio95% CIYear of transplant0.270.880.68-1.120.020.680.49-0.941984-92655 (14.5)33 (24.8)14 (23.0)1993-20011558 (34.4)55 (41.3)24 (39.3)2002-20112312 (51.1)45 (33.8)23 (37.7)Age category0.0000.6450.55-0.750.0000.550.45-0.680-5231 (5.1)23 (17.3)13 (21.3)5-18225 (5.0)9 (6.8)7 (11.5)18-603242 (71.6)31 (23.3)34 (55.7)Over 60827 (18.3)16 (12.0)7 (11.5)Organ0.0000.570.49-0.680.0000.580.46-0.74Heart701 (15.5)35 (26.3)17 (26.9)Lung(18 Heart/Lung)512 (11.3)28 (21.0)16 (26.2)Kidney1983 (43.8)41 (30.8)12 (19.7)Liver1219 (26.9)28 (21.0)16 (26.2)Multivisceral (6 small bowel)12 (0.3)1 (0.75)0Pancreas98 (2.2)00EBV Serology Mismatch0.0008.795.83-13.240.00018.6210.45-33.20No3832 (84.7)75 (56.3)23 (37.7)Yes231 (5.1)33 (24.8)23 (37.7)Unknown460 (10.2)25 (18.8)15 (24.6) Disclosures: Peters: Lundbeck Canada: Honoraria; Hoffman LaRoche: Research Funding.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".