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Prognostic impact of bone metastasis in patients with metastatic urothelial carcinoma (mUC) treated with durvalumab (D) with or without tremelimumab (T) in the DANUBE study.

2022· article· en· W4286298149 on OpenAlexaff
Carlos Stecca, Osama Abdeljalil, Cindy Lu, Han Zhang, Erik T. Goluboff, Srikala S. Sridhar

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineDurvalumabInternal medicineMetastatic Urothelial CarcinomaOncologyPost-hoc analysisChemotherapyGastroenterologyCisplatinProportional hazards modelCancerImmunotherapyUrothelial carcinomaBladder cancerNivolumab

Abstract

fetched live from OpenAlex

4564 Background: In mUC, bone metastases (BM) are associated with significant morbidity and mortality, but their independent impact on outcomes is not well established, especially in the current era of immune checkpoint inhibitors (ICIs). This post-hoc analysis assessed the impact of BM, as well as PD-L1 status (within the same BM category) on outcomes of patients with mUC treated with ICIs. Data was derived from the Phase 3 DANUBE study, which compared D, D+T, and standard chemotherapy (SoC). Methods: Patient characteristics, disease characteristics, treatments, and outcomes were collected. Patients were categorized as having BM or no BM. Outcomes included median overall survival (OS) and median progression-free survival (PFS) (in months [mo]), estimated by the Kaplan-Meier method. PD-L1 expression was assessed using the VENTANA PD-L1 (SP263) Assay. Results: Overall, 1032 patients were included; 266 had BM (D, 80; D+T, 97; SoC, 89), and 766 had no BM (D, 262; D+T, 249; SoC, 255). Among all patients, those with BM had a lower OS than those with no BM (HR, 1.67; 95% CI, 1.43-1.92; nominal P< 0.0001) when controlling for cisplatin eligibility, PD-L1 expression, presence of visceral metastases, and treatment. Similarly, patients with BM had lower PFS compared to those without BM (HR, 1.52; 95% CI, 1.30-1.75; nominal P< 0.0001) Within each treatment arm, median OS was lower for patients with BM compared to patients with no BM for all patients, regardless of PD-L1 status (Table). Patients with BM and PD-L1–high expression, treated with either D or D+T, had numerically higher median OS compared to those with PD-L1 low; this difference was also seen in patients with no BM. In contrast, there was no difference in median OS, for BM or no BM, based on PD-L1 expression for patients treated with SoC (Table). Conclusions: In this post-hoc analysis, presence of BM was significantly and consistently associated with worse outcomes in patients with mUC across all treatment arms of the DANUBE study. PD-L1–high expression was associated with higher median OS in patients treated with D or D+T, regardless of presence of BM. These data reinforce the negative prognostic impact of BM in mUC and the role for PD-L1 expression in predicting benefit for patients treated with ICIs. Funding: AstraZeneca. Clinical trial information: NCT02516241. [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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.099
GPT teacher head0.429
Teacher spread0.330 · 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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Citations1
Published2022
Admission routes1
Has abstractyes

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