Incidence and prognosis of cancer following heart transplantation using RATG induction therapy
Bibliographic record
Abstract
Cancer limits survival following heart transplantation. The study's objectives were to evaluate the incidence and risk factors for cancers after heart transplantation and to assess the association between i.v. thymoglobuline induction therapy [rabbit antithymocyte immunoglobulin, (RATG)] and neoplasia. From 1982 to 2002, prospective data were gathered for 207 heart transplant recipients. Except from 1982 to 1987, all patients received a 3-day course of i.v. RATG following transplantation. Forty-three malignant neoplasms (21%) were diagnosed. The most common were: skin (42%), lung (12%), prostate (9%), genitourinary (9%) and lymphoma (5%). Mean length of follow-up after transplantation was 99 +/- 57 months. Mean survival after diagnosis was 52 +/- 44 months. Multivariate analysis showed no significant increase in the incidence of cancer with recipient age, sex, number of rejection episodes, the type of immunosuppression or the use of RATG. Patients receiving RATG developed their malignancies significantly earlier after transplantation (P =0.007) and succumbed faster after the diagnosis (P = 0.06). Cancer is a limiting event for long-term survival after heart transplantation. No individual risk factors allow predicting its development. In the present cohort, RATG does not have carcinogenic effects following transplantation, but is associated with a more precocious development of malignancies.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".