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Enregistrement W2979766391 · doi:10.1182/blood.v124.21.165.165

Patient Related Factors Have an Indepedent Impact on Overall Survival in Myelodysplastic Syndrome Patients: A Report of the MDS-Can Registry

2014· article· en· W2979766391 sur OpenAlexaffabout
Rena Buckstein, Richard A. Wells, Nancy Zhu, Thomas J. Nevill, Heather A. Leitch, Karen Yee, Brian Leber, Mitchell Sabloff, Rajat Kumar, Michelle Geddes, April Shamy, Max Levitt, Martha Lenis, Alex Mamedov, Liying Zhang, S. M. H. Alibhai

Notice bibliographique

RevueBlood · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueNutrition and Health in Aging
Établissements canadiensMcGill UniversityVancouver General HospitalPrincess Margaret Cancer CentreUniversity of CalgaryUniversity Health NetworkHealth Sciences CentreCancerCare ManitobaMcMaster University Medical CentreOttawa HospitalSt. Paul's HospitalUniversity of AlbertaUniversity of British ColumbiaSunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineInternational Prognostic Scoring SystemComorbidityHazard ratioProportional hazards modelPhysical therapyGrip strengthMyelodysplastic syndromesUnivariate analysisInternal medicineGerontologyMultivariate analysisConfidence interval

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: MDS is a disease of the elderly; yet, the impact of clinical frailty (an age-related vulnerability state created by a multidimensional loss of reserves) and patient-reported outcomes on overall survival (OS) are unknown. Rockwood et al. have developed a simple 9-point clinical frailty scale (CFS) that correlated highly with the risk of death, institutionalization, worsening health and hospital use (Rockwood K., CMAJ 2005). In a prospective, national MDS registry, participants have undergone annual evaluations with the following: (a) 3 geriatric physical performance tests, (b) Charlson (CCI) and Della Porta comorbidity index (DP-CCI) scores, (c) graded frailty using the Rockwood CFS, (d) disability assessments with the Lawton Brody SIADL, and (e) QOL using the EORTC QLQ C-30 and the EQ-5D. The results of these frailty assessments and the effects of these patient-related factors and reported outcomes on OS, in addition to the IPSS/revised IPSS, will be presented. Methods: Overall survival was measured from time to enrollment. Results from physical performance tests were divided into quintiles with higher scores indicating better performance. We used univariate and multivariable Cox proportional hazard model to determine significant predictive factors of overall survival (OS). The variables considered included age, IPSS, R-IPSS, ferritin, LDH, transfusion dependence, hemoglobin (hgb), ECOG, frailty, CCI and DP-CCI, grip strength, 4 M walk test, stand-sit test, modified short physical performance battery (SPPB), Lawton Brody SIADL, time from diagnosis and selected QOL domains including the EQ-5D summary score, EORTC physical functioning, dyspnea and fatigue scores. Results: 453 MDS patients (pts) have been consented and enrolled locally since January 2008 (n=231) and nationally since January 2012 (n=222). Median time from diagnosis was 5.8 mos (IQR 1.4-21). Median age was 73 y (range, 26-95 y), 65% were male and the R-IPSS scores were very low (14%), low (46%), intermediate (24%), high (10%) and very high (6%). Thirty-three % of pts were transfusion dependent at enrollment. Median CCI and DP-CCI scores were 1 (0-12) and 0 (0-6) respectively with 18% and 24% falling into the highest category scores. Median frailty scale score (n=346) was 3 (1-9) with 25% having scores indicating moderate (4-5) or severe (6-9) frailty. The CCI and DP-CCI strongly correlated (r=0.6; p< .0001) with each other, while frailty significantly but modestly correlated with them (r=0.3-0.35, p<.0001). With a median follow up (from enrollment) of 15 mos (95% CI: 13-16), 159 (35%) pts have died and 28 pts lost to follow up. Actuarial survival was 41.0 mos (range, 33.6 - 48.5 mos). When considering patient related factors - age, frailty, comorbidity (both indices), sex, ECOG, the 10 x stand sit test, the SPPB, Lawton Brody SIADL, and all QOL domains considered above were significantly predictive of OS. The multivariable model with the highest R2 included R-IPSS (p=.0004), frailty (1-3 vs 4-9, p= .004), CCI (0-1 vs >2, p=.03) and EORTC fatigue (p=.01) as summarized in Table 1 below. A frailty score > 3 predicted for worse survival (figure 1: 2 year OS 68.5% vs. 83.8%) and further refined survival within the R-IPSS categories (Figure 2). Frailty was also the single most predictive factor for OS from the start of azacitidine therapy (not shown). Conclusions: Patient-related factors such as frailty and comorbidity (that evaluate physiologic reserve and global fitness) should be considered in addition to traditional MDS prognostic indices. Abstract 165. Table. Independent Covariate Predictive factors at baseline Coefficient SE p -value HR 95% CI of HR R2 (%) Time from diagnosis (months) * 0.0335 0.1076 0.7557 1.034 0.837 1.277 17.29% R-IPSS (5 categories) <.0001 Very high vs. very low 2.5701 0.7289 0.0004 13.066 3.131 54.524 High vs. very low 2.1156 0.6437 0.0010 8.294 2.349 29.285 Intermediate vs. very low 1.0466 0.6430 0.1036 2.848 0.808 10.043 Low vs. very low 0.6346 0.6181 0.3045 1.886 0.562 6.334 Frailty (1-3 vs. 4-9) -0.8323 0.2905 0.0042 0.435 0.246 0.769 Comorbidity Charlson (0-1 vs. ³2) -0.5915 0.2749 0.0314 0.553 0.323 0.949 EORTC fatigue * 0.3671 0.1546 0.0176 1.443 1.066 1.954 natural log-transformation was applied for normalizing distribution Figure 1 Overall survival by Frailty (n=346) Figure 1. Overall survival by Frailty (n=346) Figure 2 Overall Survival by Frailty and R-IPSS Figure 2. Overall Survival by Frailty and R-IPSS Disclosures Buckstein: Celgene Canada: Research Funding. Wells:Celgene: Honoraria, Other, Research Funding; Novartis: Honoraria, Research Funding; Alexion: Honoraria, Research Funding. Leitch:Alexion: Honoraria, Research Funding; Novartis: Honoraria, Research Funding, Speakers Bureau; Celgene: Educational Grant Other, Honoraria, Research Funding. Shamy:Celgene: Honoraria, Other.

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)0,003
score de la tête « metaresearch » (Gemma)0,006
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 enseignants0,006
Score d'incertitude au seuil0,015

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,004
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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 Opus0,016
Tête enseignante GPT0,283
Écart entre enseignants0,267 · 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

Citations3
Publié2014
Routes d'admission2
Résumé présentoui

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