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Relapse-free survival (RFS) of clinical T2-4N0 urothelial bladder carcinoma (UBC) after radical cystectomy (RC), with or without perioperative chemotherapy (POC): Endpoints for clinical trial design.

2018· article· en· W2891338044 on OpenAlexaffabout
Marco Bandini, Alberto Briganti, Elizabeth R. Plimack, Günter Niegisch, Evan Y. Yu, Aristotelis Bamias, Neeraj Agarwal, Srikala S. Sridhar, Cora N. Sternberg, Ulka N. Vaishampayan, Christine Théodore, Jonathan E. Rosenberg, Joaquim Bellmunt, Matt D. Galsky, Francesco Montorsi, Andrea Necchi

Bibliographic record

VenueJournal of Clinical Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsMedicineNomogramOncologyCystectomyInternal medicineBladder cancerUrologyAdjuvantCisplatinProportional hazards modelOverall survivalChemotherapyCancer

Abstract

fetched live from OpenAlex

4535 Background: Recent data suggests that the full benefit of neoadjuvant therapy may not be captured via pathologic complete response rates. Improved relapse-free survival (RFS) may identify active agents acting though novel mechanisms. Methods: Within RISC and San Raffaele databases (1990-2016), we identified 973 cT2-4N0 UBC patients (pts), from 27 centers in the U.S., Europe, Israel, and Canada. A Cox-based nomogram predicting 12-m RFS was built including pt (gender, race), tumor characteristics (histology, pT, pN and surgical margin status [SMS]), and administration of neoadjuvant or adjuvant chemotherapy (CT). Multiple imputation was performed to handle missing data. Validation (2000 bootstrap resamples) was internally tested. Calibration and prognostic ability was assessed comparing estimated versus observed 12-m RFS. Results: Overall, 577 (59.3%) and 236 (24.3%) pts had cT2 and cT3-T4, respectively (T unknown and imputated in 160, 16.4%). 125 (12.8%) had mixed UC+other histologies. 275 pts (28.3%) received neoadjuvant CT, 165 (17%) adjuvant CT. On multivariable analyses, pT (p < 0.002), pN (p < 0.001) and SMS (p = 0.005) were associated with higher rate of recurrence. Conversely, use of adjuvant CT (HR = 0.63, p < 0.001) was associated with lower rate of recurrence. Results were confirmed in sensitivity analyses after removing 61 (6.2%) non-cisplatin POC. Overall, 405 (41.6%) pts relapsed and 375 (38.5%) died. Median RFS and overall survival were 44 months (95%CI, 36-65) and 57 months (95%CI, 50-90), respectively. In POC-treated pts, nomogram-predicted 12-m RFS rates were 91.6% (95%CI, 87-96), 79.7% (95%CI, 73-88) and 53.0% (95%CI, 44-63), across the nomogram-derived tertiles. In pts who did not receive POC, these estimates were 89.8%, 74.8%, and 47.0%, respectively. The bootstrapped c-index of the nomogram was 78% (95%CI: 74-81). Conclusions: Nomogram-predicted 12-m RFS may provide data to base future clinical trial designs of novel agents in the perioperative setting.

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)0.015
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.235
GPT teacher head0.502
Teacher spread0.267 · 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
Published2018
Admission routes2
Has abstractyes

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