Transplantation: Miscellaneous - II (T465-T489)
Bibliographic record
Abstract
The purpose of this study is to evaluate the incidence and the type of malignancies in renal transplant recipients, their clinical course, the efficacy of treatment and the immunosuppression were used.Between March 1983 and Dec 2001, 1055 renal transplantations (611 living and 444 cadaver donor) were performed in our center.Post transplant malignancy developed in 74 pts (7%), (52 M, 22 F).Skin Ca occurred in 22 pts, followed by Kaposi's Sa in 18, LPD in 10 and various types of visceral malignancies in the rest 24 pts (lung Ca in 4, breast Ca in 3, gall bladder, uterus and large bowel Ca in 2 pts of each cause, ovary, thyroid, stomach, prostate, nasal-pharynx, spermatic cord, brain and bile duct Ca, melanoma and chronic myelogenic leukemia in one.Immunosuppression consisted of Aza, CyA and steroids before 1996, followed by MMF, CyA or Tacrolimus and steroids.Anti-IL2 were used the last 3 yrs and Rapamycine recently.All pts with Kaposi's Sa were treated with tapering of Immunosuppression and cessation of CsA or Tcr.Additionally 3 pts received chemotherapy and one local radiation.Patients with solid type of tumors were treated with surgical excision of the lesions and additionally chemotherapy or radiation if it was appropriate.All LPD pts were treated with chemotherapy and radiation in two, apart of severe tapering of immunosuppression including cessation of Cya or Tcr.Disease related mortality was in pts with Kaposi's Sa 11%, in LPD pts 40% and in all other cases 26%.In skin Ca Aza was minimized and in all other malignancies immunosuppression reduced.In conclusion renal transplant recipients are of high risk for malignancy development compared to the general population.Skin Ca, Kaposi's Sa and LPD are the most common malignancies.Significant tapering of immunosuppression is usually adequate treatment for localized KS, while the treatment of other malignancies follows the usual rules.
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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 | 0.000 | 0.000 |
| 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) | 0.033 | 0.012 |
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".