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Record W4223496858 · doi:10.1200/jco.21.01829

Selinexor in Advanced, Metastatic Dedifferentiated Liposarcoma: A Multinational, Randomized, Double-Blind, Placebo-Controlled Trial

2022· article· en· W4223496858 on OpenAlexaff
Mrinal M. Gounder, Albiruni Abdul Razak, Neeta Somaiah, Sant P. Chawla, Javier Martín‐Broto, Giovanni Grignani, Scott M. Schuetze, Bruno Vincenzi, Andrew J. Wagner, Bartosz Chmielowski, Robin L. Jones, Richard F. Riedel, Silvia Stacchiotti, Elizabeth T. Loggers, Kristen N. Ganjoo, Axel Le Cesne, Antoîne Italiano, Xavier García del Muro, Melissa Burgess, Sophie Piperno‐Neumann, Christopher W. Ryan, Mary F. Mulcahy, Charles Forscher, Nicolas Penel, Scott H. Okuno, Anthony Elias, Lee Hartner, Tony Philip, Thierry Alcindor, Bernd Kasper, Peter Reichardt, Lore Lapeire, Jean‐Yves Blay, Christine Chevreau, Claudia Maria Valverde Morales, Gary K. Schwartz, James L. Chen, Hari A. Deshpande, Elizabeth J. Davis, Garth Nicholas, Stefan Gröschel, Helen Hatcher, Florence Duffaud, Antonio Casado, Roberto Díaz Beveridge, Giuseppe Badalamenti, Mikael Eriksson, Christian F. Meyer, Margaret von Mehren, Brian A. Van Tine, Katharina S. Götze, F Mazzeo, Alexander Yakobson, Aviad Zick, Alexander T.J. Lee, Anna Estival, Andrea Napolitano, Mark A. Dickson, Dayana Michel, Changting Meng, Lingling Li, Jianjun Liu, Osnat Ben‐Shahar, Dane R. Van Domelen, Christopher J. Walker, Hua Chang, Yosef Landesman, Jatin J. Shah, Sharon Shacham, Michael Kauffman, Steven Attia

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsOttawa HospitalMcGill University Health CentrePrincess Margaret Cancer Centre
FundersNational Center for Advancing Translational SciencesNational Cancer Institute
KeywordsMedicinePlaceboInternal medicineClinical endpointAdverse effectNauseaRandomized controlled trialHazard ratioCrossover studyGastroenterologyPhases of clinical researchClinical trialSurgeryConfidence intervalPathology

Abstract

fetched live from OpenAlex

PURPOSE Antitumor activity in preclinical models and a phase I study of patients with dedifferentiated liposarcoma (DD-LPS) was observed with selinexor. We evaluated the clinical benefit of selinexor in patients with previously treated DD-LPS whose sarcoma progressed on approved agents. METHODS SEAL was a phase II-III, multicenter, randomized, double-blind, placebo-controlled study. Patients age 12 years or older with advanced DD-LPS who had received two-five lines of therapy were randomly assigned (2:1) to selinexor (60 mg) or placebo twice weekly in 6-week cycles (crossover permitted). The primary end point was progression-free survival (PFS). Patients who received at least one dose of study treatment were included for safety analysis (ClinicalTrials.gov identifier: NCT02606461 ). RESULTS Two hundred eighty-five patients were enrolled (selinexor, n = 188; placebo, n = 97). PFS was significantly longer with selinexor versus placebo: hazard ratio (HR) 0.70 (95% CI, 0.52 to 0.95; one-sided P = .011; medians 2.8 v 2.1 months), as was time to next treatment: HR 0.50 (95% CI, 0.37 to 0.66; one-sided P < .0001; medians 5.8 v 3.2 months). With crossover, no difference was observed in overall survival. The most common treatment-emergent adverse events of any grade versus grade 3 or 4 with selinexor were nausea (151 [80.7%] v 11 [5.9]), decreased appetite (113 [60.4%] v 14 [7.5%]), and fatigue (96 [51.3%] v 12 [6.4%]). Four (2.1%) and three (3.1%) patients died in the selinexor and placebo arms, respectively. Exploratory RNA sequencing analysis identified that the absence of CALB1 expression was associated with longer PFS with selinexor compared with placebo (median 6.9 v 2.2 months; HR, 0.19; P = .001). CONCLUSION Patients with advanced, refractory DD-LPS showed improved PFS and time to next treatment with selinexor compared with placebo. Supportive care and dose reductions mitigated side effects of selinexor. Prospective validation of CALB1 expression as a predictive biomarker for selinexor in DD-LPS is warranted.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.139
GPT teacher head0.468
Teacher spread0.329 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized 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

Citations42
Published2022
Admission routes1
Has abstractyes

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