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Intravesical sacituzumab tirumotecan in participants with intermediate-risk non–muscle-invasive bladder cancer: The phase 1/2 TroFuse-027 study.

2025· article· en· W4410816990 on OpenAlexaff
Joshua J. Meeks, Roger Li, Ashish M. Kamat, Girish S. Kulkarni, Noah M. Hahn, Ekta Kapadia, Qing Zhao, Hema Kishore Dave, Max Kates

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicBladder and Urothelial Cancer Treatments
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineBladder cancerUrothelial cancerCancerOncologyUrologyInternal medicine

Abstract

fetched live from OpenAlex

TPS4627 Background: Standard treatment for patients with intermediate-risk (IR) non–muscle-invasive bladder cancer (NMIBC) is transurethral resection of bladder tumor (TURBT) with or without adjuvant intravesical chemotherapy or bacillus Calmette-Guérin. However, 30% to 50% of patients experience disease recurrence, which leads to repeated endoscopic resections and intravesical therapies that contribute to patient morbidity and decreased urinary quality of life. Therefore, novel therapies with favorable efficacy and safety profiles are needed. Trophoblast cell-surface antigen 2 (TROP2) is a transmembrane glycoprotein expressed broadly in several tumors, including all stages of bladder cancer, making it a viable therapeutic target. Sacituzumab tirumotecan (sac-TMT; MK-2870) is an antibody-drug conjugate consisting of a humanized anti-TROP2 monoclonal antibody, a linker, and a cytotoxic belotecan-derivative topoisomerase I inhibitor. In in vivo mouse models, intravesical sac-TMT demonstrated antitumor activity, tolerability, and minimal systemic exposure. TroFuse-027 (NCT06637423) is a nonrandomized, open-label, phase 1/2 study designed to evaluate the safety and efficacy of intravesical sac-TMT as ablative therapy in participants with IR NMIBC. Methods: Eligible participants are adults with prior history of pathologically confirmed low-grade Ta diagnosed with recurrence by visual inspection on cystoscopy who have not yet undergone TURBT and have urine cytology negative for high-grade urothelial carcinoma. In the phase 1 dose-escalation part, approximately 32 participants will be sequentially enrolled into 4 escalating sac-TMT dose groups using the Bayesian optimal interval design with a target dose-limiting toxicity rate of 30%; 3 to 14 participants are planned for each dose group. Sac-TMT will be administered by intravesical instillation weekly for 6 weeks unless there is unacceptable toxicity or withdrawal of consent. Disease assessments (per local urine cytology, cystoscopy, and biopsy as indicated for visible tumors) will occur at week 12 in all participants, then every 12 weeks for the first year and every 24 weeks thereafter for up to 2 years unless progression to high-grade NMIBC or muscle-invasive bladder cancer occurs. Participants with low-grade Ta that persists at week 12 or recurs anytime after that will undergo TURBT and remain in efficacy follow-up. The primary objectives are to evaluate safety and tolerability and to establish the recommended phase 2 dose. Secondary objectives are pharmacokinetics and complete response rate (the proportion of participants with the absence of visible tumors at the 12-week assessment after initiating treatment) and duration of complete response per local assessment. Future studies (phase 2) will be initiated on completion of dose escalation and based on the totality of data. Clinical trial information: NCT06637423 .

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)0.002
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.090
GPT teacher head0.485
Teacher spread0.395 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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