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Phase 1b study of weekly split-dose selinexor in soft tissue sarcoma (STS).

2022· article· en· W4281747213 on OpenAlexaff
Abdulazeez Salawu, Abha A. Gupta, Esmail Mutahar Al-Ezzi, Sofia Genta, Eoghan Ruadh Malone, Tushar Vora, Geoffrey Alan Watson, Olga Vornicova, Lisa Wang, Limore Arones, Madeline Phillips, Jasmine Lee, Albiruni Ryan Abdul Razak

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineTolerabilityClinical endpointAdverse effectRegimenInternal medicineCommon Terminology Criteria for Adverse EventsPhases of clinical researchToxicityDosingClinical trialOncologySurgery

Abstract

fetched live from OpenAlex

11563 Background: Selinexor has demonstrated clinical activity in a variety of tumors including STS. Selinexor dosing at 60mg twice a week or 80mg once a week in later phase trials was associated with gastrointestinal and hematologic toxicities requiring frequent dose interruption and reduction. Preclinical in vivo studies show that selinexor use in a split-dose regimen or sustained-release formula is associated with less toxicity. This phase 1b study aimed to evaluate the safety and tolerability of split-dose selinexor in patients (pts) with advanced STS. Methods: Eligible pts with advanced STS of any histologic subtype, and ECOG performance status (PS) ≤ 1 were treated with split-dose selinexor (40mg, 20mg, 20mg in the morning, afternoon, and evening, respectively) on days 1, 8, 15 and 22 of a 28-day cycle, until unacceptable toxicity or disease progression. Antiemetic prophylaxis (oral dexamethasone and ondansetron) was given to all pts. The primary endpoint was the rate of grade ≥ 3 treatment-related adverse events (TRAE) by CTCAE v5.0. The secondary endpoint was assessment of quality of life (QoL) using the EORTC QLQ-c30 tool v3. Descriptive analyses of Global Health Status (GHS) QoL scores at screening (baseline) and cycle 2 day 1 (C2D1) were performed. Radiologic tumor assessments (by RECIST v1.1) were performed every 8 weeks while on treatment. Results: Nineteen pts [12 female and 7 male; ECOG 0/1, 8/11; median age 61 years (range 41 – 83)] were enrolled. The most frequent of 12 STS subtypes was leiomyosarcoma (n = 7, 37%). Among 18 patients evaluable for toxicity, there were no grade ≥ 3 TRAE. The most common grade ≤ 2 TRAE were dysgeusia (n = 11, 61%), nausea (n = 11, 61%), fatigue (n = 10, 56%) and vomiting (n = 10, 56%). Grade ≤ 2 hematologic TRAE were thrombocytopenia (n = 6, 33%), neutropenia (n = 4, 22%) and anemia (n = 1, 6%). Dose reduction was required in 3 pts (17%) due to intolerable grade 2 TRAE (fatigue, nausea, thrombocytopenia). No serious adverse event due to selinexor was noted. QoL scores were evaluable for 15 pts. The mean (± SEM) change in GHS QoL score from baseline to C2D1 was -10.6 (± 4.8). Among 16 pts evaluable for radiologic response, the best response was stable disease (SD) in 10 pts (63%), and progressive disease (PD) in 6 pts (37%). Durable clinical benefit (SD for > 16 weeks) was seen in 5 pts (31%; 95%CI 11.0 – 58.7%) The median PFS was 3.6 months (95%CI 1.7 – 7.3). Conclusions: Split-dose selinexor was well tolerated in this heterogeneous group of pts with advanced STS and warrants further interrogation. Updated toxicity, safety, efficacy and QoL data will be presented at the meeting. Clinical trial information: NCT04811196.

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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.002

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 head0.163
GPT teacher head0.520
Teacher spread0.357 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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