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Long-term clinical outcome assessments in patients with tenosynovial giant cell tumor treated with vimseltinib: 1-year results from the MOTION phase 3 trial.

2025· article· en· W4410802961 on OpenAlexaff
Vivek A. Bhadri, Hans Gelderblom, Silvia Stacchiotti, Sebastian Bauer, Andrew J. Wagner, Michiel A. J. van de Sande, Nicholas M. Bernthal, Antonio López–Pousa, Albiruni Ryan Abdul Razak, Antoîne Italiano, Mahbubl Ahmed, Axel Le Cesne, Christopher Tait, Amanda Saunders, Nicholas Zeringo, B. Harrow, Maitreyi G. Sharma, Matthew L. Sherman, Jean‐Yves Blay, William D. Tap

Bibliographic record

VenueJournal of Clinical Oncology · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal synovial abnormalities and treatments
Canadian institutionsPrincess Margaret Cancer Centre
FundersDeciphera Pharmaceuticals
KeywordsMedicineTerm (time)Range of motionClinical trialOutcome (game theory)Physical therapyOncologyInternal medicinePhysical medicine and rehabilitationSurgery

Abstract

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11558 Background: Tenosynovial giant cell tumor (TGCT) is a locally aggressive neoplasm caused by dysregulation of the colony-stimulating factor 1 ( CSF1 ) gene leading to overproduction of CSF1. Patients with TGCT often report substantial pain and stiffness, impaired physical function, and limited range of motion (ROM), supporting the need for an effective, well-tolerated CSF1 receptor (CSF1R)-targeted therapy that provides long-term improvements in functional health and quality of life (QoL). Vimseltinib is an oral, switch-control inhibitor of CSF1R. In part 1 of the MOTION phase 3 trial, vimseltinib showed statistically significant and clinically meaningful improvements vs placebo in tumor response as well as clinical outcome assessments (COAs; active ROM and patient-reported outcomes [PROs]) in patients with TGCT not amenable to surgery at week 25 (Gelderblom H, et al. Lancet . 2024). Here we report 1-year COA results from MOTION. Methods: MOTION is a global, phase 3 trial composed of double-blind (part 1; to week 25), open-label (part 2; week 25–49), and extension periods (NCT05059262). Patients received vimseltinib 30 mg twice weekly. COAs reported here include change from baseline in active ROM of the affected joint, physical function (PRO Measurement Information System physical function score [PROMIS-PF]), stiffness (worst stiffness numeric rating scale [NRS]), health status (EuroQol Visual Analog Scale [EQ-VAS]), and pain (brief pain inventory [BPI] worst pain). BPI worst pain response rate is also reported with response defined as ≥30% decrease in worst pain without ≥30% increase in narcotic analgesic use. Results are reported in patients randomized to vimseltinib during part 1 whose 1-year (week-49) assessments were complete at data cutoff (Feb 22, 2024). Results: Of 83 patients randomized to vimseltinib in part 1, 73 continued treatment in the open-label part of the study. Consistent with results from part 1, COAs at 1 year continued to show improvement from baseline. Mean (standard error [SE]) change from baseline in active ROM was 14.9 (5.0) percentage points. Mean (SE) changes from baseline in PROMIS-PF, worst stiffness NRS, and EQ-VAS were 6.5 (1.2), −2.7 (0.4), and 11.0 (3.5) points, respectively. Mean (SE) change from baseline in BPI worst pain was −2.8 (0.4) points, and the BPI worst pain response rate was 40% (33/83; 95% confidence interval, 29 to 51). Conclusions: These 1-year COA results from the MOTION phase 3 trial demonstrate durable and continued improvements in active ROM, physical function, stiffness, health status, and pain with ongoing vimseltinib treatment. Continued treatment with vimseltinib provides clinically meaningful benefit in functional health and QoL beyond week 25 for patients with symptomatic TGCT whose disease is not amenable to surgery. Clinical trial information: NCT05059262 .

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.003
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 head0.085
GPT teacher head0.470
Teacher spread0.384 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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