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Allogeneic stem cell transplantation for renal cell carcinoma

2001· review· en· W1985342059 on OpenAlexaff
Richard Childs, Darrel Drachenberg

Bibliographic record

VenueCurrent Opinion in Urology · 2001
Typereview
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsLeukemia & Lymphoma Society of Canada
Fundersnot available
KeywordsMedicineTransplantationRenal cell carcinomaImmunotherapyStem cellImmune systemOncologyImmunologyDiseaseCancer researchInternal medicineBiology

Abstract

fetched live from OpenAlex

Although the prognosis for patients with metastatic kidney cancer remains poor, a number of promising immunotherapeutic approaches for the treatment of metastatic disease have been developed over the past decade. The response of some patients to cytokines such as interleukin-2 and interferon-alpha, and more recently, vaccination with dendritic cell/tumor fusions has laid the ground work for ongoing immune-based investigational approaches. Allogeneic stem cell transplantation is a potent form of immunotherapy capable of delivering potentially curative immune-mediated anti-tumor effects against a number of different hematological malignancies. Knowledge of renal cell carcinoma's unusual susceptibility to immune attack has led to the hypothesis that tumor rejection, mediated through immunocompetent donor T-cells, might be generated against this solid tumor following the transplantation of an allogeneic immune system. Although clinical trials are early and ongoing, the recent observation of metastatic disease regression following non-myeloablative stem cell transplantation has identified renal cell carcinoma as being susceptible to a graft-versus-tumor effect. Disease responses following such therapy have ranged from partial to complete and have been observed even in patients who have failed conventional cytokine based strategies. This article reviews the design, methodology and early clinical results of studies investigating the use of allogeneic stem cell transplantation in metastatic renal cell carcinoma.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.107
GPT teacher head0.372
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations15
Published2001
Admission routes1
Has abstractyes

Explore more

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