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Record W4387393316 · doi:10.1097/spc.0000000000000675

Perioperative systemic therapy in renal cell carcinoma

2023· review· en· W4387393316 on OpenAlexaff
Ceilidh MacPhail, Lori Wood, Myuran Thana

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2023
Typereview
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsNova Scotia Cancer CentreDalhousie University
Fundersnot available
KeywordsMedicinePembrolizumabRenal cell carcinomaPerioperativeNephrectomyOncologyInternal medicineAdjuvantKidney cancerAdjuvant therapySystemic therapyDiseaseImmunotherapyIntensive care medicineSurgeryCancerKidney

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Renal cell carcinoma (RCC) is the most common kidney neoplasm. Localized RCC can be cured with nephrectomy. However, a proportion of patients will recur with incurable distant metastatic disease. There is a clear need for treatments to reduce the risk of RCC recurrence and thus improve survival. This review describes the landscape of perioperative therapy for RCC, focusing on more recent trials involving immune checkpoint inhibitors (ICIs). RECENT FINDINGS: ICIs have significantly changed outcomes in advanced RCC. Four trials investigating the role of perioperative ICI for RCC are now reported. Only one trial utilizing adjuvant pembrolizumab (Keynote-564) has shown a disease-free survival benefit in resected RCC. SUMMARY: Patients with resected RCC should be counselled on their risk of recurrence and the potential option of adjuvant pembrolizumab, recognizing that overall survival data are not yet available.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.223
GPT teacher head0.426
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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