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First-line pembrolizumab in advanced urothelial carcinoma: Clinical parameters associated with efficacy in the phase 2 KEYNOTE-052 and phase 3 KEYNOTE-361 trials.

2022· article· en· W4212936557 on OpenAlexaff
Tibor Csőszi, Thomas Powles, Ajjai Alva, Daniel Castellano, Mustafa Özgüroğlu, Peter H. O’Donnell, Yohann Loriot, Noah M. Hahn, Aude Fléchon, Alejo Rodríguez‐Vida, Ronald de Wit, Susanna Y. Cheng, Stéphane Oudard, Christof Vulsteke, Evan Y. Yu, Jianxin Lin, Kentaro Imai, Blanca Homet Moreno, Arjun Vasant Balar, Petros Grivas

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineInternal medicineOncologyUrothelial carcinomaPembrolizumabPopulationClinical trialMultivariate analysisLogistic regressionUnivariate analysisCisplatinProportional hazards modelExploratory analysisCancerChemotherapyBladder cancerImmunotherapy

Abstract

fetched live from OpenAlex

521 Background: First-line treatment with pembrolizumab (pembro) monotherapy has shown durable clinical activity in selected patients (pts) with advanced/unresectable or metastatic urothelial carcinoma (UC). In a pooled population of pts with advanced UC from the single-arm phase 2 KEYNOTE-052 (NCT02335424) and the randomized, open-label, phase 3 KEYNOTE-361 (NCT02853305) studies, this exploratory analysis evaluated the relationship between baseline characteristics and clinical outcomes of first-line pembro monotherapy. Methods: Cisplatin-ineligible pts with advanced UC were enrolled in KEYNOTE-052 and chemotherapy-naive pts with advanced UC were enrolled in KEYNOTE-361. For analysis of predictive factors for ORR and OS in pembro-treated pts, the purposeful selection method was used to build the multivariable logistic regression model (ORR) and multivariable Cox model (OS), beginning with a univariable analysis of each independent variable. Any variable in the univariate model with P < 0.10 was a candidate for the multivariate model. The stepwise selection method was used to select the variables in the final model. Significance of the final model was set at P < 0.05. Data cutoff dates were September 26, 2020 (KEYNOTE-052) and April 29, 2020 (KEYNOTE-361). Results: This pooled analysis included 681 pts treated with pembro monotherapy (KEYNOTE-052, N = 374; KEYNOTE-361, N = 307 [170 were cisplatin ineligible]). Median follow-up was 51.9 mo (range, 22.0-65.3). ORR was 29.4% (95% CI, 26.0-32.9; 69 CRs, 131 PRs), and median DOR was 33.2 mo (range, 1.4+ to 60.7+). Median OS was 12.5 mo (95% CI, 11.0-14.6). By multivariate analysis, independent factors significantly associated with higher ORR were PD-L1 status (combined positive score [CPS] ≥10 vs CPS < 10; odds ratio [OR], 1.90 [95% CI, 1.33-2.71]; P = 0.0004), site of metastasis (lymph node only vs visceral disease; OR, 1.66 [95% CI, 1.06-2.59]; P = 0.0265), liver involvement (absent vs present; OR, 1.75 [95% CI, 1.06-2.89]; P = 0.0294), and baseline hemoglobin level ≥10 vs < 10 g/dL; OR, 2.17 [95% CI, 1.09-4.31]; P = 0.0276). Multivariate analysis of OS is displayed in the Table. Conclusions: This exploratory multivariate analysis identified numerous factors, including PD-L1–positive status (CPS ≥10), lymph node only metastasis, and lower ECOG PS score, associated with improved clinical outcomes in pts with advanced UC treated with first-line pembro monotherapy. Clinical trial information: NCT02335424 and NCT02853305. [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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.214
GPT teacher head0.508
Teacher spread0.294 · 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 designNon-randomized trial
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

Citations1
Published2022
Admission routes1
Has abstractyes

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