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Enregistrement W3097099568 · doi:10.1182/blood-2020-141635

Fatigue, However Measured, Continues to Refine Prognosis in Higher Risk MDS: An MDS-CAN Study

2020· article· en· W3097099568 sur OpenAlexaffabout
Irina Amitai, Michelle Geddes, Nancy Zhu, Mary‐Margaret Keating, Mitchell Sabloff, Grace Christou, Brian Leber, Dina Khalaf, Heather A. Leitch, Ève St‐Hilaire, Nicholas Finn, April Shamy, Karen Yee, John M. Storring, Thomas J. Nevill, Robert Delage, Mohamed Elemary, Versha Banerji, Lisa Chodirker, Lee Mozessohn, Anne Parmentier, Mohammed Siddiqui, Alexandre Mamedov, Liying Zhang, Rena Buckstein

Notice bibliographique

RevueBlood · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueOccupational and environmental lung diseases
Établissements canadiensUniversity of British ColumbiaDr. Georges-L.-Dumont University Hospital CentreSt. Paul's HospitalMcMaster UniversityCancerCare ManitobaUniversity Health NetworkHealth Sciences CentreOttawa HospitalMcGill University Health CentreMcGill UniversityUniversity of OttawaQueen Elizabeth II Health Sciences CentreUniversity of AlbertaPrincess Margaret Cancer CentreUniversity of CalgaryHôpital de l'Enfant-JésusJuravinski Cancer CentreSunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineInternational Prognostic Scoring SystemQuality of life (healthcare)Internal medicineMyelodysplastic syndromesRating scaleDiseasePopulationCancerPhysical therapyGerontologyOncologyPsychologyEnvironmental health

Résumé

récupéré en direct d'OpenAlex

Background: The incorporation of patient-reported outcomes with traditional disease risk classification, was found to strengthen survival prediction in patients with myelodysplastic syndromes (MDS). A recently reported model, FA-IPSS(h), found that patients' reported fatigue, assessed by the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life-Core 30 (QLQ-C30), among higher-risk IPSS population, further stratifies them into distinct sub-groups with different survival outcomes (Efficace et al, 2018). Compared to the IPSS, the revised IPSS (IPSS-R) is more refined in prognostic assessment and an IPSS-R score of > 3.5 may identify higher risk disease (Pfeilstocker et al, 2016). The Edmonton Symptom Self Assessment Scale (ESAS) Global Fatigue Scale (GFS), is a single-item fatigue rating scale (0-10, with 10 being the highest degree), which has been previously recommended by the National Comprehensive Cancer Network to screen for fatigue in all cancer populations. Aims: (1) to validate the FA-IPSS(h), among the Canadian MDS registry (2) investigate whether a modified index, integrating higher risk by IPSS-R with patient reported fatigue according to the GFS, is able to identify individual subgroups with divergent overall survival (OS). Methods: All adult patients diagnosed with MDS with an IPSS-R score >3.5 within 6 months before the date of registration were eligible for this analysis. Fatigue was assessed both by the QLQ-C30 questionnaire and the GFS. Frailty was assessed by the Canadian Study of Health and Aging (CSHA) 9 point Rockwood clinical frailty scale. Survival was calculated using standard Kaplan-Meier analysis. Results: This analysis included 331 patients. Median age was 73 years (range, 30-98 years), 65.7% were male, median blast % was 6% (range, 0-30), median IPSS-R score was 5.2 (range, 3.5-10) and 55% had high and intermediate-2 (Int-2) IPSS risk, 68% had high and very high IPSS-R risk disease, 66% were exposed to a hypomethylating agent. Median fatigue scores increased with Rockwood frailty scores. The median QLQ-C30 fatigue score was 33 (interquartile range (IQR), 22-55.6) and 4 (IQR, 2-6) by the GFS with 59% recording high fatigue (>4). At a median follow-up of 17 months (IQR, 9-30 months), 233 deaths were observed. The actuarial median OS was 19.3 months (95% CI, 16.5-21.7). We applied the FA-IPSS(h) using QLQ-C30 fatigue cutoffs of 45 (figure 1a) and found a significant difference in OS (p<0.0001) (table 1). We then divided the cohort into 2 groups: A) IPSS-R score >3.5 + Low Fatigue (<45) (n=226) and B) IPSS-R score >3.5 + High Fatigue (≥45) (n=96). We found a significant difference in OS between these 2 groups, median OS 19.5 months (95% CI, 17.2-24.3) in group A versus 15.2 months (95% CI, 11.9-22.0) in group B (p=0.02) (figure 1b). We found similar results with these refinements, using the QLQ-C30 cutoff of 33 (the median in our patient population) (p<0.0001). Similarly, high fatigue defined by ESAS GFS (>4), was able to distinguish OS using the IPSS (p<0.0001) (figure 1c) and IPSS-R >3.5 (p=0.005) (figure 1d). Conclusions: We were able to externally validate the FA-IPSS (h) using a threshold QLQ-C30 fatigue score of 45, as originally described and 33 (Canadian median), using both the IPSS and IPSS-R (score >3.5) classifications to define higher risk MDS. The easier to deploy ESAS GFS score of >4 further discriminates survival using the IPSS and IPSS-R. This emphasizes the power of self-reported fatigue at refining OS predictions in higher risk MDS and further bolsters the importance of considering patient related outcomes in global assessments. Disclosures Geddes: Taiho: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jazz: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees, Research Funding. Keating:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Hoffman La Roche: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Consultancy; Servier: Membership on an entity's Board of Directors or advisory committees; Shire: Membership on an entity's Board of Directors or advisory committees; Taiho: Membership on an entity's Board of Directors or advisory committees. Leber:Lundbeck: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Otsuka Pharmaceutical: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS/Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda/Palladin: Honoraria, Membership on an entity's Board of Directors or advisory committees; Treadwell: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Leitch:AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Taiho: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Exjade: Speakers Bureau. Shamy:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Storring:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Nevill:Jazz Pharmaceuticals: Honoraria; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Alexion: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Delage:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Elemary:Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Chodirker:Hoffman Laroche: Honoraria. Buckstein:Novartis: Honoraria; Celgene: Research Funding; Takeda: Research Funding; Celgene: Honoraria; Astex: Honoraria.

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)0,004
score de la tête « metaresearch » (Gemma)0,007
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,110
Score d'incertitude au seuil0,218

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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 Opus0,067
Tête enseignante GPT0,286
Écart entre enseignants0,218 · 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

Citations2
Publié2020
Routes d'admission2
Résumé présentoui

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