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Enregistrement W4310119420 · doi:10.1182/blood-2022-159389

Improvement in Individual Symptoms and Total Symptom Score (TSS) and Matching-Adjusted Indirect Comparison (MAIC) Analysis to Compare TSS As a Continuous Endpoint in Patients with Myelofibrosis Treated with Pelabresib in Combination with Ruxolitinib Versus Janus Kinase Inhibitor Monotherapy

2022· article· en· W4310119420 sur OpenAlexaff
Ruben A. Mesa, Marina Kremyanskaya, Andrea Patriarca, Vikas Gupta, Francesca Palandri, Timothy Devos, Claire Harrison, Raajit K. Rampal, Moshe Talpaz, Alessandro M. Vannucchi, Andrew Kuykendall, Jean‐Jacques Kiladjian, Srđan Verstovšek, Gozde Colak, Debarshi Dey, John Mascarenhas

Notice bibliographique

RevueBlood · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueMyeloproliferative Neoplasms: Diagnosis and Treatment
Établissements canadiensUniversity Health Network
Organismes subventionnairesnon disponible
Mots-clésMedicineClinical endpointRuxolitinibInternal medicineClinical trialPhases of clinical researchMyelofibrosisSurrogate endpointSurgery

Résumé

récupéré en direct d'OpenAlex

Background: Pelabresib (CPI-0610; PELA) is a bromodomain and extraterminal domain (BET) inhibitor in development for the treatment of myelofibrosis (MF). PELA combined with ruxolitinib (RUX) has shown a 56% response rate for ≥50% reduction in total symptom score (TSS) at Wk 24 from baseline (BL; TSS50) in Janus kinase inhibitor (JAKi) treatment-naïve patients (pts) with intermediate or high-risk MF in Arm 3 of the open-label Phase 2 MANIFEST study (NCT02158858). TSS50 is a standard measure of symptom improvement; however, the 50% response threshold does not capture clinical benefit in pts with TSS reduction <50% or pts who achieve TSS50 but could benefit from further symptom improvement (Dueck A, et al. European Hematology Association 2017. Poster E1331). Here, we present percentage change in TSS and subdomains as a continuous endpoint from Arm 3 of MANIFEST and indirect comparisons with historical double-blind JAKi trials in MF. Aims: To assess clinically meaningful changes in TSS with PELA in combination with RUX. TSS subdomains were analyzed to assess the underlying impact of PELA + RUX on symptom scores. In the absence of head-to-head studies of PELA + RUX vs JAKi monotherapy, naïve and matching-adjusted indirect comparison (MAIC) analysis (correcting for potential imbalances in baseline characteristics) were used to investigate improvement in TSS as a continuous endpoint in pts treated with PELA + RUX in Arm 3 of the MANIFEST study with historical double-blind Phase 3 JAKi trials: COMFORT-I (RUX), SIMPLIFY-1 (RUX, momelotinib [MOM]) and JAKARTA (fedratinib [FED]). Methods: In MANIFEST, percentage change in TSS and subdomains (fatigue, night sweats, itching, abdominal discomfort, pain under ribs, feeling of fullness and bone pain) from BL at Week (Wk) 12, 24, 36 and 48 were calculated. Pts with BL score = 0 were excluded. For the MAIC analysis, individual pt level data were available for MANIFEST Arm 3, and study-level data were extracted from published waterfall plots using WebPlotDigitizer (Rohatgia A. https://automeris.io/) for COMFORT-I, SIMPLIFY-1 and JAKARTA (FED 400 mg arm). Unanchored MAIC was conducted, whereby pts were reweighted to adjust for imbalances in key prognostic BL characteristics: gender, MF subtype, International Prognostic Scoring System risk status (IPSS), previous hydroxyurea use, platelet count, hemoglobin levels, spleen volume and JAK2V617F status; as a result, bias due to potential unmeasured differences is unlikely. The weights were used to calculate the effective sample size. Pts with IPSS intermediate-1 were excluded from the analysis. Weighted and unweighted treatment effects in terms of difference in least square (LS) means with their 95% confidence intervals using robust sandwich estimators for variance are presented. Studies used different TSS questionnaire versions; however, variations are subtle, and so comparisons across versions are valid (Dueck A, et al.Blood 2017;130:2168). Results: Comparable mean BL TSS scores were observed: 16.1 in MANIFEST Arm 3 and 17.5-19.4 across comparator Phase 3 studies. In MANIFEST Arm 3, a median reduction from BL of >50% was observed for TSS and all subdomains, and this reduction remained consistent across Wk 12 to Wk 48. TSS distribution in MANIFEST at Wk 24 showed greater median and mean reductions from BL vs JAKi monotherapy studies (Figure 1 shows comparison with RUX in SIMPLIFY-1). Complete summary level balance was achieved in the weighted distributions of the prognostic factors in MANIFEST Arm 3 versus comparators. After adjusting for imbalances, >20% greater reduction in LS mean percentage change in TSS from BL at Wk 24 was observed for all comparisons of MANIFEST Arm 3 vs historical studies, as shown in Figure 2. P values for all MAIC analyses were statistically significant. Conclusions: Analyzing TSS as a continuous endpoint in addition to responder analysis overcomes limitations of using TSS50 alone. TSS50 rates in MANIFEST Arm 3 were higher than all comparator MF studies, and clinically relevant improvements in TSS and its subdomains were observed as early as Wk 12 and were durable over time. When indirectly comparing Arm 3 of the Phase 2 MANIFEST study with historical Phase 3 MF studies using MAIC analysis, improved estimates of changes in TSS with PELA + RUX vs RUX, MOM or FED monotherapy were observed. A randomized Phase 3 MANIFEST-2 study of PELA + RUX vs RUX monotherapy in JAKi-naïve pts is ongoing (NCT04603495). Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,008
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,008
Score d'incertitude au seuil0,041

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0080,010
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0020,005
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0070,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,239
Écart entre enseignants0,227 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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