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Record W2154540012 · doi:10.5489/cuaj.10017

Cost analysis of two follow-up strategies for localized kidney cancer: A Canadian cohort comparison

2010· article· en· W2154540012 on OpenAlexaffvenueabout
Marie Dion, Andrew K. Williams, Venu Chalasani, Linda Nott, Stephen E. Pautler

Bibliographic record

VenueCanadian Urological Association Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicRenal cell carcinoma treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineNephrectomyRenal cell carcinomaCohortKidney cancerAcademic institutionSurgeryInternal medicineKidney

Abstract

fetched live from OpenAlex

INTRODUCTION: The cost of surveillance strategies in patients after radical nephrectomy for localized primary renal cell carcinoma (RCC) has not been evaluated. We compared the costs of 2 different surveillance strategies, the new Canadian Urological Association (CUA) guidelines and the old strategy implemented in our institution. METHODS: Seventy-five patients who underwent radical nephrectomy for primary non-metastatic renal cancer were retrospectively reviewed. The direct cost of surveillance was determined and compared with the theoretical cost which would have been accrued using the CUA guidelines. RESULTS: Our mean follow-up was 31.1 (SD ± 20.4) months. The overall and disease-free survival endpoints were 87.7% and 85.2%, respectively. Total medical costs were higher for our old institutional surveillance strategy than the CUA guidelines ($181 861 vs. $135 054). For the complete follow-up of 75 patients, a cost-savings of $46 806 could have been achieved following the CUA guidelines (p = 0.002). Of recurrences, 7 of 8 were detected by routine screening, only 1 recurrence was identified by symptoms. The cost per recurrence detected in our old protocol was $9 812.92. The increased cost of our institution was due to more visits with basic testing, symptomatic investigation, and follow-up of imaging tests. The median percent cost attributable to these extra tests was 15% (range 0 to 59). CONCLUSION: Based on our results, we endorse the new CUA surveillance strategy in RCC follow-up as appropriate and cost effective in comparison with previous follow-up strategies used at our institution.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.156
Threshold uncertainty score0.315

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.306
Teacher spread0.274 · 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

Citations9
Published2010
Admission routes3
Has abstractyes

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