Risk Factors and Outcomes for the Development of Malignancy in Lung and Heart‐Lung Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Many factors may limit survival from lung and heartlung transplantation, including malignancy. OBJECTIVE: To investigate factors associated with the development of malignancy following transplantation and its effect on survival by retrospectively reviewing a population of lung transplant recipients. METHODS: Data from 342 consecutive lung transplant patients were collected. Results were analyzed by fitting variables into a multivariate logistic regression model predicting the development of post-transplant malignancies. Covariates were selected based on crude associations that reached a level of significance at P ≤ 0.10. Length of survival was analyzed using the Kaplan-Meier method. RESULTS: Fifty-eight subjects developed post-transplant malignancies, which were the cause of death of 14 patients. Twenty-one patients had a pretransplant malignancy, of whom six developed a malignancy posttransplant--of these, two were fatal recurrences. No risk factors were significantly associated with all forms of post-transplant malignancy. When adjusted for age at transplantation and donor smoking history, Epstein-Barr virus seropositivity at the time of transplant was significantly associated with a reduced risk of a post-transplant lymphoproliferative disorder (OR 0.17; 95% CI 0.05 to 0.59). The median survival time in individuals without a post-transplant malignancy was significantly shorter than in those with a post-transplant malignancy (P = 0.018 Wilcoxon [Breslow]). This may be secondary to the length of time required to develop malignancy and the fact that not all malignancies that developed were fatal. The median time to develop malignancy was greater than two years. In addition, the 14 patients who died as a result of their malignancy had a significantly shorter survival time than the 44 who died because of nonmalignant causes (P < 0.001). CONCLUSIONS: Malignancy was not associated with an overall decrease in survival time when compared with those who did not develop a malignancy. Risk factors specific for the development of malignancies remain difficult to specify.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".