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Record W2315224281 · doi:10.1097/spc.0000000000000074

The emerging roles of stereotactic ablative radiotherapy for metastatic renal cell carcinoma

2014· review· en· W2315224281 on OpenAlexaff
Patrick Cheung, Isabelle Thibault, Georg A. Bjarnason

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2014
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsSABR volatility modelMedicineRenal cell carcinomaAbscopal effectRadiation therapyAblative caseOncologyRadiosurgeryRadiologyInternal medicineImmunotherapyCancer

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To discuss the emerging roles of stereotactic ablative radiotherapy (SABR) in patients with metastatic renal cell carcinoma (RCC). RECENT FINDINGS: RCC tumours are not as radio-resistant as previously thought, as local control rates of tumours treated with SABR are high. Therefore, SABR is an attractive treatment option for RCC tumours in which effective long-term palliation of symptoms or local control is desired. Like surgical resection of metastatic tumours, SABR can also be used as a method of eradicating oligometastases to potentially 'cure' or offer prolonged disease-free survival in patients with low-volume metastatic disease. In patients who develop progression of a solitary or few tumours (termed oligoprogression), SABR to the progressing 'rogue' tumours may delay the need to start or change systemic therapy. Finally, there is the potential for SABR to improve the efficacy of immunotherapy for metastatic RCC, given the known immune-modulated abscopal effect of radiotherapy. SUMMARY: SABR is increasingly being used in metastatic RCC patients, given the great potential to improve various outcomes. More prospective clinical trials are needed to identify and quantify the clinical benefits.

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 score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.130
GPT teacher head0.422
Teacher spread0.292 · 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

Citations21
Published2014
Admission routes1
Has abstractyes

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