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Outcomes of partial nephrectomy for non-metastatic cT2 renal tumors: Results from a Canadian multi-institutional collaborative.

2023· article· en· W4324136259 on OpenAlexaffabout
Rahul Bansal, Raees Cassim, Ryan Sun, Ranjeeta Mallick, Antonio Finelli, Simon Tanguay, Darrel Drachenberg, Frédéric Pouliot, Luke T. Lavallée, Alan So, Ricardo Rendon, Lori Wood, Anil Kapoor, Aly‐Khan A. Lalani, Naveen S. Basappa, Bimal Bhindi, Lucas Dean, Georg A. Bjarnason, Rodney H. Breau

Bibliographic record

VenueJournal of Clinical Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsUniversity of AlbertaQueen Elizabeth II Health Sciences CentreMcGill University Health CentreUniversity of OttawaUniversité LavalSunnybrook Health Science CentreSt. Boniface HospitalOttawa HospitalSt. Joseph’s Healthcare HamiltonUniversity of ManitobaDalhousie UniversityUniversity of TorontoMcMaster UniversityUniversity of British Columbia
Fundersnot available
KeywordsMedicineChromophobe cellNephrectomyRenal cell carcinomaClear cellHistologyInternal medicineUrologyCancerKidney cancerPathologicalGastroenterologySurgeryKidney

Abstract

fetched live from OpenAlex

690 Background: The role of partial nephrectomy (PN) is not well defined for cT2 renal cell carcinoma (RCC) as compared to radical nephrectomy (RN). The aim of this study was to examine oncological outcomes of PN as compared to RN for non-metastatic cT2 RCC. Methods: The Canadian Kidney Cancer information system was used to define patients who underwent surgery for non-metastatic cT2 RCC from January 2011 to October 2022. Patients with clear-cell, papillary, and chromophobe RCC were included. Other histology, multiple tumours, and hereditary RCC syndrome patients were excluded. Each PN patient was individually matched to RN up to 1:4 depending on availability of patients based on tumor size (+/- 1cm), histology, grade (clear cell and papillary), and necrosis (clear cell). Matched patients were analyzed as clusters. Results: A total of 1523 patients were identified, and 50 PN patients met study criteria who were then matched to 185 RN patients. Both groups had similar age, gender, smoking status, BMI, Charlson comorbidity index score, symptoms at presentation, baseline eGFR, hemoglobin and pathological characteristics. PN patients had smaller tumors (7.6 cm [IQR 2] vs 8.4 [IQR 2.4], p=0.05), had higher likelihood of undergoing open surgery (72.9% vs 31.8%, p<0.0001) and less likely received adrenalectomy (2% vs 24.3%, p=0.0004). Positive surgical margin rates were similar in both groups (8.2% in PN vs 3.4% in RN, p=0.2). Median follow up was not significantly different in either group (3.6 yrs [IQR 4.7] in PN vs 3.3 [4.7] yrs in RN, p=0.9). During the follow up period, PN patients had higher risk of local recurrence (HR 3.0, 95%CI 1.08-8.37), lower risk of distant metastasis (HR 0.36, 95%CI 0.15-0.88), better cancer specific survival (HR 0.56, 95%CI 0.18-1.78) and overall survival (HR 0.36, 95%CI 0.11-1.19) and as compared to RN. At 6 months and beyond after surgery, PN patients had less decline in eGFR than RN patients (-16.6 [SD 21.1] vs -24.4[SD 16.2], p=0.0002). Complications rates between PN and RN were (18% vs 9%, p=0.057). Conclusions: In this multi-institutional Canadian cohort of patients with non-metastatic cT2 RCC undergoing surgery, PN compared to RN was associated with slightly higher risk of peri-operative complications, better preservation of renal function, and higher risk of local recurrence. The lower risk of distant metastasis and death was likely from residual confounding unaccounted for in the individual patient match. [Table: see text]

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)0.002
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 score0.901
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.171
GPT teacher head0.459
Teacher spread0.288 · 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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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