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Prognostic risk stratification of pathological stage T2N0 bladder cancer after radical cystectomy

2010· article· en· W1537858404 on OpenAlexaff
Guru Sonpavde, Myrna M. Khan, Robert S. Svatek, Richard Lee, Giacomo Novara, Derya Tilki, Seth P. Lerner, Gilad E. Amiel, Eila C. Skinner, Pierre I. Karakiewicz, Patrick J. Bastian, Wassim Kassouf, Hans‐Martin Fritsche, Jonathan I. Izawa, Vincenzo Ficarra, Colin P. Dinney, Yair Lotan, Yves Fradet, Shahrokh F. Shariat

Bibliographic record

VenueBritish Journal of Urology · 2010
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsUniversité LavalWestern UniversityMcGill UniversityMcGill University Health CentreUniversité de Montréal
Fundersnot available
KeywordsCystectomyLymphovascular invasionMedicineBladder cancerProportional hazards modelHazard ratioUrologyInternal medicineOncologyStage (stratigraphy)Lymph nodePathologicalAdjuvant therapySurgeryCancerConfidence intervalMetastasis

Abstract

fetched live from OpenAlex

Study Type – Therapy (individual cohort) Level of Evidence 2b What’s known on the subject? and What does the study add? Patients with urothelial carcinoma of the bladder (UCB) and pathological (p) stage T2N0 disease exhibit a range of clinical outcomes with an overall estimated 10–25% experiencing recurrence and death after radical cystectomy (RC). Nomograms to prognosticate UCB post‐RC have been developed in heterogeneous datasets of patients across different stages and do not address factors unique to pT2N0 disease. A user‐friendly prognostic risk model was devised for patients with pT2N0 UCB undergoing RC based on residual pathological stage at RC (pT2a, pT2b, OBJECTIVE • To stratify risk of pathological (p) T2N0 urothelial carcinoma of the bladder after radical cystectomy (RC) based on pathological factors to facilitate the development of adjuvant therapy trials for high‐risk patients. PATIENTS AND METHODS • The study comprised 707 patients from a database of patients with pT2N0 urothelial carcinoma of the bladder who had undergone RC and not received perioperative chemotherapy. • The effect of residual pT‐stage at RC, age, grade, lymphovascular invasion and number of lymph nodes removed on recurrence‐free survival was evaluated using Cox regression analyses. A weighted prognostic model was devised with significant variables. RESULTS • The median follow up was 60.9 months. In multivariable analyses, residual disease at RC (pT2a: hazard ratio (HR) 1.740, P = 0.03; for pT2b: HR 3.075, P < 0.001; both compared with P = 0.09) and lymphovascular invasion (HR 2.234, P < 0.001) were associated with recurrence‐free survival ( c = 0.70). • Three risk groups were devised based on weighted variables with 5‐year recurrence‐free survival of 95% (95% CI 87–98), 86% (95% CI 81–90) and 62% (95% CI 54–69) in the good‐risk, intermediate‐risk and poor‐risk groups, respectively ( c = 0.68). The primary limitation is the retrospective and multicenter feature. CONCLUSIONS • A prognostic risk model for patients with pT2N0 bladder cancer undergoing RC with generally adequate lymph node dissection was constructed based on residual pathological stage at RC, grade and lymphovascular invasion. • These data warrant validation and may enable the selection of patients with high‐risk pT2N0 urothelial carcinoma of the bladder for adjuvant therapy trials.

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)0.005
metaresearch head score (Gemma)0.011
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 score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
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)0.0020.000

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 head0.012
GPT teacher head0.277
Teacher spread0.266 · 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

Citations35
Published2010
Admission routes1
Has abstractyes

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