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Selpercatinib efficacy and safety in patients with <i>RET</i>-altered thyroid cancer: A clinical trial update.

2021· article· en· W3171364159 on OpenAlexaff
Eric J. Sherman, Lori J. Wirth, Manisha H. Shah, Maria E. Cabanillas, Bruce Robinson, Janessa Laskin, Matthias Kroiß, Vivek Subbiah, Alexander Drilon, Jennifer Wright, Victoria Soldatenkova, Pearl Plernjit French, Antoîne Italiano, Daniela Weiler

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsUniversity of British Columbia
FundersEli Lilly and Company
KeywordsMedicineMedullary thyroid cancerVandetanibInternal medicineCabozantinibThyroid cancerClinical endpointPopulationAdverse effectOncologyCancerClinical trialThyroid

Abstract

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6073 Background: Selpercatinib, is a first-in-class, highly selective, CNS active and potent RET inhibitor approved in multiple countries for treatment of RET-fusion positive lung or thyroid cancers. Reported is an update of efficacy and safety results in RET-altered thyroid cancer, with a longer follow up (30 Mar 2020 data cutoff vs 16 Dec 2019) and additional enrolment. Methods: Patients (pts) with RET-mutant medullary thyroid cancer (MTC) and RET-fusion positive thyroid cancer (TC) were enrolled in the global (16 countries, 89 sites) Phase 1/2 LIBRETTO-001 trial (NCT03157128). The primary endpoint was objective response rate (ORR) per RECIST 1.1 by independent review committee (IRC). Secondary endpoints included duration of response (DoR), progression-free survival (PFS), clinical benefit rate (CBR; CR+PR+SD ≥16 weeks), and safety. The integrated analysis set (IAS, n = 143) includes efficacy evaluable MTC pts previously treated with cabozantinib and/or vandetanib (cabo/vande). The primary analysis set (PAS), a subset of IAS, is the first 55 enrolled pts. Cabo/vande naïve MTC pts (N = 112) and TC pts with prior systemic treatment (N = 22) were also analyzed. Safety population includes all pts who received ≥1 dose of selpercatinib (MTC N = 315; TC N = 42) by data cutoff. Results: For MTC patients, the ORR for IAS was 69.2%, in the PAS it was 69.1%, and 71.4% for cabo/vande naïve MTC pts. The ORR for TC pts (n = 22) was 77.3% (see table). Most treatment-emergent adverse events (TEAEs) were low grade; the most common (≥25% of MTC and/or TC pts treated with selpercatinib) were dry mouth, diarrhea, hypertension, fatigue and constipation for both MTC and TC pts, increased ALT/AST, peripheral edema and headache in MTC pts and nausea in TC pts. 4.8% of MTC and TC pts discontinued selpercatinib due to TEAEs but only 1.9% with MTC and none with TC discontinued due to treatment-related adverse events. Conclusions: In this updated analysis, selpercatinib continued to show marked and durable antitumor activity in pts with RET-altered thyroid cancers. Selpercatinib was well tolerated and no new safety concerns were identified. A global, randomized, phase 3 trial (LIBRETTO-531) evaluating selpercatinib compared to cabo/vande in kinase inhibitor naïve MTC pts is ongoing. Clinical trial information: NCT03157128. [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)0.003
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.095
GPT teacher head0.466
Teacher spread0.371 · 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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Citations11
Published2021
Admission routes1
Has abstractyes

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