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Record W4391580550

Temporal Trends in Selecting Patients for Partial Nephrectomy for Small Renal Cell Carcinomas in Alberta, Canada

2020· article· en· W4391580550 on OpenAlexaboutno aff
Taylor Remondini, Van Tuyl J, Pak W, Geoffrey Gotto

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsnot available
Fundersnot available
KeywordsNephrectomyRenal cell carcinomaMedicineUrologyGeneral surgeryOncologyInternal medicineKidney
DOInot available

Abstract

fetched live from OpenAlex

Derek Tilley,1 Taylor Remondini,2 John Van Tuyl,2 Wendy Pak,1 Geoffrey T Gotto3 1Alberta Health Services, Cancer Control, Holy Cross Centre, Calgary, AB, Canada; 2Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; 3Department of Surgery, University of Calgary, Calgary, AB, CanadaCorrespondence: Geoffrey T GottoDepartment of Surgery, University of Calgary, Suite 6625 - 7007 14th Street SW Calgary, Calgary, AB T2V 1P9, CanadaTel +1 403 943-8921Fax +1 403 943-8667Email drgotto@gmail.comBackground: When technically feasible, partial nephrectomy (pN) is preferred over radical nephrectomy (rN) due to similar oncological control with preservation of renal function. Here, we evaluate the incorporation of pN into practice for small renal masses and examine the associated outcomes.Methods: We included patients who had undergone either a partial or radical nephrectomy in Alberta, Canada for renal cell carcinomas with pathology tumor stage T1a between 2002 and 2014 (N=1449). Patients were excluded if they had multiple tumors or if they were on dialysis prior to nephrectomy.Results: pN use increased over the duration of the study period. Patients treated after the introduction of guidelines (2007) recommending the use of pN were significantly more likely to receive a pN (OR: 2.709, 95% CI: 1.944– 3.775; p< 0.001) after adjusting for baseline estimated glomerular filtration rate (GFR), age, and sex. Patients who received rN were at significantly increased risk of death (HR: 1.528, 95% CI: 1.029– 2.270; p=0.036) after controlling for baseline GFR, age, and sex. Baseline GFR significantly affected odds of receiving pN (p< 0.050) in the entire cohort, but subgroup analysis of more recently diagnosed patients (2011– 2014) showed that only patients with kidney failure (GFR < 15) were less likely to have received pN.Discussion: The utilization of pN for patients with pT1a renal cell carcinoma has increased significantly over time and has been accelerated by the introduction of guideline recommendations. Patients treated with pN over the study period had superior overall survival.Keywords: nephrectomy, T1a, renal cell carcinoma, guideline, survival, adherence

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.006
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.212
GPT teacher head0.464
Teacher spread0.252 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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