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Circulating tumor DNA (ctDNA) in patients with muscle-invasive bladder cancer (MIBC) who received perioperative durvalumab (D) in NIAGARA.

2025· article· en· W4410821726 on OpenAlexaff
Thomas Powles, Michiel Simon Van Der Heijden, Ying Wang, James W.F. Catto, Joshua J. Meeks, Hikmat Al‐Ahmadie, Hiroyuki Nishiyama, Toan Quang Vu, Lorenzo Antonuzzo, Tae‐Hwan Kim, Vagif Atduev, Hiroaki Kikukawa, Bernhard J. Eigl, Yousef Zakharia, Kazuo Nishimura, Svetlana Ho, Wenjing Xin, Yashaswi Shrestha, Matthew D. Galsky

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineDurvalumabUrothelial cancerBladder cancerPerioperativeCancerCirculating tumor DNAUrologyInternal medicineOncologySurgeryImmunotherapyPembrolizumab

Abstract

fetched live from OpenAlex

4503 Background: In the phase 3 NIAGARA trial (NCT03732677) of patients (pts) with cisplatin-eligible MIBC, addition of perioperative D to neoadjuvant chemotherapy (NAC) demonstrated a statistically significant and clinically meaningful improvement in event-free survival (EFS) and overall survival compared with NAC alone, and a 10% higher pathological complete response (pCR) rate, with a manageable safety profile and no impact on the feasibility of surgery. Here, we report a planned exploratory analysis of ctDNA and association with clinical outcomes from NIAGARA. Methods: NIAGARA enrolled cisplatin-eligible pts with MIBC (cT2-T4aN0/1M0) planned for radical cystectomy (RC). Pts were randomized 1:1 to receive either neoadjuvant D (1500 mg IV Q3W) and NAC (cisplatin + gemcitabine IV Q3W) for 4 cycles followed by RC, then adjuvant D monotherapy (1500 mg IV Q4W) for 8 cycles (D arm), or NAC followed by RC alone (comparator [C] arm). Dual primary endpoints were pCR and EFS. Disease-free survival (DFS) was a secondary endpoint. Plasma ctDNA was assessed using the Signatera personalized, tumor-informed molecular residual disease (MRD) assay (Natera, Inc, Austin, TX, USA). ctDNA was assessed at baseline (screening or neoadjuvant C1D1, n = 460), after neoadjuvant treatment prior to RC (pre-RC, n = 422), and at C1D1 of the adjuvant phase (post-RC, n = 345). Results: Of 1063 randomized pts, 462 comprised the biomarker-evaluable population (237 D arm; 225 C arm). Patient characteristics were similar to the ITT population. Overall, the ctDNA+ rate at baseline was 57% (260/460) and decreased to 22% (94/422) after neoadjuvant treatment at pre-RC. ctDNA clearance rates from baseline to pre-RC were 41% in the D arm and 31% in the C arm. The non-pCR rate was 97% (86/89) among pts with pre-RC ctDNA+ status. Overall ctDNA+ rate post-RC was 9% (31/345). EFS benefit in the D arm vs the C arm was observed in both the baseline ctDNA+ and ctDNA− groups (Table). DFS benefit with perioperative D was observed in post-RC ctDNA+ and ctDNA− groups (Table). Conclusions: In this exploratory analysis, ctDNA+ status at pre-RC was associated with non-pCR. Higher ctDNA clearance from baseline to pre-RC in the D arm indicated the additional benefit of D plus NAC vs NAC alone. Perioperative D provided an EFS benefit to both pts with ctDNA+ and ctDNA− status at baseline; a similar trend was observed with DFS based on ctDNA status post-RC. These results further support the perioperative D regimen for pts with MIBC. Funding : AstraZeneca. Clinical trial information: NCT03732677 . EFS DFS Baseline ctDNA+ Baseline ctDNA- Post-RC ctDNA+ Post-RC ctDNA- D C D C D C D C n 137 123 99 101 9 8 129 126 Median (95% CI), months NR (NR–NR) 32.3(24.3–NR) NR(NR–NR) NR(NR–NR) 9.5(2.8–NR) 6.2(2.9–NR) NR(NR–NR) NR(NR–NR) Hazard ratio(95% CI) 0.73(0.51–1.06) 0.45(0.25–0.84) NC* 0.49(0.28–0.84) CI, confidence interval; NC, not calculable; NR, not reached. *NC due to <20 events between arms.

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)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.028
GPT teacher head0.372
Teacher spread0.344 · 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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Citations35
Published2025
Admission routes1
Has abstractyes

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