Burden of de novo malignancy in the liver transplant recipient
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recipients of liver transplantation (LT) have a higher overall risk (2-3 times on average) of developing de novo malignancies than the general population, with standardized incidence ratios ranging from 1.0 for breast and prostate cancers to 3-4 for colon cancer and up to 12 for esophageal and oropharyngeal cancers. Aside from immunosuppression, other identified risk factors for de novo malignancies include the patient's age, a history of alcoholic liver disease or primary sclerosing cholangitis, smoking, and viral infections with oncogenic potential. Despite outcome studies showing that de novo malignancies are major causes of mortality and morbidity after LT, there are no guidelines for cancer surveillance protocols or immunosuppression protocols to lower the incidence of de novo cancers. Patient education, particularly for smoking cessation and excess sun avoidance, and regular clinical follow-up remain the standard of care. Further research in epidemiology, risk factors, and the effectiveness of screening and management protocols is needed to develop evidence-based guidelines for the prevention and treatment of de novo malignancies.
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.
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) | 0.001 | 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 it