Outcomes of Solid Organ Transplant Recipients With Preexisting Malignancies in Remission: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Solid organ transplant recipients (SOTR) with a pretransplant malignancy (PTM) are at increased risk for cancer recurrence. However, it is unclear whether differences in survival and incidence of posttransplant de novo malignancies exist between recipients with PTM and those without PTM. We designed a systematic review to synthesize all available evidence assessing these outcomes. METHODS: A systematic search was performed in MEDLINE, EMBASE, and Cochrane Library to identify studies comparing the following outcomes in SOTR by PTM status: (1) all-cause mortality, (2) cancer-specific mortality, and (3) incidence of posttransplant de novo malignancy. Risk of bias was assessed using the Newcastle-Ottawa Scale. RESULTS: Thirty-two cohort studies were included. Recipients with PTM were at increased risk of all-cause mortality compared to recipients without PTM (pooled hazard ratio [HR], 1.51; 95% confidence interval [CI], 1.27-1.81). Similarly, recipients with PTM were 3 times more likely to die of cancer (pooled HR, 3.13; 95% CI, 2.29-4.27). The pooled HR for developing posttransplant de novo malignancy was also increased (HR, 1.92; 95% CI, 1.52-2.42). The association of all-cause mortality and SOTR with PTM did not vary by transplanted organ. CONCLUSIONS: Pretransplant malignancy is associated with increased risk of all cause-mortality, cancer-specific mortality and of developing de novo malignancies after transplantation compared with those without PTM. These results reaffirm the need for careful selection of transplant recipients with PTM. Tailored screening and management strategies should be developed for this group of patients.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".