Patient Related Factors Have an Indepedent Impact on Overall Survival in Myelodysplastic Syndrome Patients: A Report of the MDS-Can Registry
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».