Use of mammalian target of rapamycin inhibitors after failure of tyrosine kinase inhibitors in patients with metastatic renal cell carcinoma undergoing hemodialysis: A single‐center experience with four cases
Bibliographic record
Abstract
We retrospectively identified patients with end-stage renal disease undergoing hemodialysis treated with the mammalian target of rapamycin inhibitors as a second- and/or third-line targeted therapy after treatment failure with the tyrosine kinase inhibitors for metastatic renal cell carcinoma. Patient medical records were reviewed to evaluate the response to therapies and treatment-related toxicities. Four patients were identified. All patients had undergone nephrectomy, and one had received immunotherapy before targeted therapy. Two patients had clear cell histology, and the other two had papillary histology. All patients were classified into the intermediate risk group according to the Memorial Sloan-Kettering Cancer Center risk model. All patients were treated with everolimus as a second- or third-line therapy, and two patients were treated with temsirolimus as a second- or third-line therapy after treatment failure with sorafenib or sunitinib. The median duration of everolimus therapy was 6.7 months, whereas that of temsirolimus was 9.5 months. All patients had stable disease as the best response during each period of therapy. There were no severe adverse events. The use of mammalian target of rapamycin inhibitors in patients who previously failed to respond to tyrosine kinase inhibitors appears to be feasible in patients with end-stage renal disease requiring hemodialysis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".