Post renal transplantation <scp>K</scp>aposi's sarcoma: a review of its epidemiology, pathogenesis, diagnosis, clinical aspects, and therapy
Bibliographic record
Abstract
BACKGROUND: Kaposi's sarcoma (KS) is a vascular malignancy primarily involving the skin. This neoplasm occurs commonly in acquired immunodeficiency syndrome (AIDS) and post solid organ transplantation. Human herpesvirus type 8 (HHV-8) has been shown to play a causative role in AIDS-associated KS and in post renal transplantation KS. METHODS: Based on a MEDLINE search, we present a review of the current information on the epidemiology, pathogenesis, diagnosis and treatment of post-transplantation KS (PT-KS) with an emphasis on renal transplantation. RESULT: The different frequencies of PT-KS in different parts of the world seem to be related to seroprevalence of HHV-8 infection. Following renal transplantation and the administration of immunosuppressive therapy, HHV-8 may reactivate. The renal tubular epithelium is a site for HHV-8 latency. Rates of PT-KS in seropositive recipients and anti-HHV-8 mismatched recipients (donor+/recipient-) are approximately 13% and 4.6%, respectively. Additional risk factors for the development of PT-KS include skin color, country of birth, age at the time of transplantation, and different induction regimens including anti-thymocyte globulin, steroid, or anti-interleukin 2-receptor antagonists. Skin is the major site of involvement. Surprisingly, involvement of the transplanted organ has been reported to be extremely rare. Reduction in immunosuppressive therapy and switching to mammalian targets of rapamycin inhibitors, such as sirolimus, are effective treatments for PT-KS. In patients with no response to reduction in immunosuppressive therapy, systemic chemotherapy with different regimens has been reported to be successful. CONCLUSION: PT-KS in renal transplant patients is an important problem specifically in southern Europe and the Middle East. In the majority of patients, the diagnosis based on clinical suspicion is always essential. Clinicians should bear in mind that PT-KS may threaten graft function and hence result in rejection complications. Appropriate management increases patient survival.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".