Posttransplant lymphoproliferative disorder in pediatric patients: Survival rates according to primary sites of occurrence and a proposed clinical categorization
Bibliographic record
Abstract
Posttransplant lymphoproliferative disorder (PTLD) is a devastating complication of organ transplant. In a hospital-based registry, we identified biopsy-proven cases of PTLD among children during a 15-year period and reviewed trends in PTLD rates, the sites of involvement, and the associated survival rates. Cases that were included had at least 1 year of follow-up after the diagnosis of PTLD. We studied 82 patients with first-episode PTLD. Median age at diagnosis was 6.4 years (IQR 3.2-12.3 years). The most frequent PTLD sites were tonsillar/adenoidal (T/A [34%]) and gastrointestinal (32%), followed by miscellaneous (defined as less common sites including central nervous system, kidney, lung, and soft tissue [12%]), lymph node (11%), and multisite (11%). Kaplan-Meier survival curves showed that T/A PTLD was associated with decreased all-cause mortality compared with PTLD at other sites (log-rank 0.004), even after adjustment for histological subtype (P = .047). PTLD-related mortality was also decreased among T/A PTLD (log-rank 0.012) but showed a trend toward significance only after adjustment for histological subtype (P = .09). Among first episodes of PTLD, T/A PTLD was associated with a survival advantage compared with PTLD at other sites, even after adjustment for potential confounders. Based on our observations, we propose a clinical categorization of PTLD according to anatomical site of occurrence.
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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 | 0.002 | 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".