Preexisting melanoma and hematological malignancies, prognosis, and timing to solid organ transplantation: A consensus expert opinion statement
Bibliographic record
Abstract
Patients undergoing evaluation for solid organ transplantation (SOT) frequently have a history of malignancy. Only patients with treated cancer are considered for SOT but the benefits of transplantation need to be balanced against the risk of tumor recurrence, taking into consideration the potential effects of immunosuppression. Prior guidelines on timing to transplant in patients with a prior treated malignancy do not account for current staging, disease biology, or advances in cancer treatments. To update these recommendations, the American Society of Transplantation (AST) facilitated a consensus workshop to comprehensively review contemporary literature regarding cancer therapies, cancer stage specific prognosis, the kinetics of cancer recurrence, as well as the limited data on the effects of immunosuppression on cancer-specific outcomes. This document contains prognosis, treatment, and transplant recommendations for melanoma and hematological malignancies. Given the limited data regarding the risk of cancer recurrence in transplant recipients, the goal of the AST-sponsored conference and the consensus documents produced are to provide expert opinion recommendations that help in the evaluation of patients with a history of a pretransplant malignancy for transplant candidacy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.031 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".