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ASSESSING THE DETERMINANTS OF HEALTH-RELATED QUALITY OF LIFE IN PATIENTS WITH MYELODYSPLASTIC SYNDROMES
Author(s): ,
Igor Stojkov
Affiliations:
Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment,UMIT - University for Health Sciences, Medical Informatics and Technology,Hall in Tirol,Austria
,
Annette Conrads-Frank
Affiliations:
Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment,UMIT - University for Health Sciences, Medical Informatics and Technology,Hall in Tirol,Austria
,
Ursula Rochau
Affiliations:
Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment,UMIT - University for Health Sciences, Medical Informatics and Technology,Hall in Tirol,Austria
,
Marjan Arvandi
Affiliations:
Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment,UMIT - University for Health Sciences, Medical Informatics and Technology,Hall in Tirol,Austria
,
Karin Koinig
Affiliations:
Department of Internal Medicine V (Hematology and Oncology),Innsbruck Medical University,Innsbruck,Austria
,
Michael Schomaker
Affiliations:
Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment,UMIT - University for Health Sciences, Medical Informatics and Technology,Hall in Tirol,Austria
,
Sibylle Puntscher
Affiliations:
Institute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment,UMIT - University for Health Sciences, Medical Informatics and Technology,Hall in Tirol,Austria
,
Daniela Schmid
Affiliations:
Division for Quantitative Methods in Public Health and Health Services Research, Department of Public Health, Health Services Research and Health Technology Assessment,UMIT - University for Health Sciences, Medical Informatics and Technology,Hall in Tirol,Austria
,
Corine van Marrewijk
Affiliations:
Department of Hematology,Radboud university medical center,Nijmegen,Netherlands
,
Alex Smith
Affiliations:
Epidemiology and Cancer Statistics Group, Department of Health Sciences,University of York,York,United Kingdom
,
Theo de Witte
Affiliations:
Department of Tumor Immunology - Nijmegen Center for Molecular Life Sciences,Radboud university medical center,Nijmegen,Netherlands
,
Uwe Siebert
Affiliations:
UMIT - University for Health Sciences, Medical Informatics and Technology, Dept. of Public Health, Health Services Research & HTA / Harvard Univ.,Dept. Health Policy & Management, Institute for Technology Assessment,Hall i.T. / Boston,Austria
Reinhard Stauder
Affiliations:
Department of Internal Medicine V (Hematology and Oncology),Innsbruck Medical University,Innsbruck,Austria
(Abstract release date: 05/14/20) EHA Library. Stojkov I. 06/12/20; 294713; EP796
Igor Stojkov
Igor Stojkov
Contributions
Abstract

Abstract: EP796

Type: e-Poster

Background

Health-related quality of life (HRQoL) represents a valuable outcome parameter in treatment algorithms in patients with Myelodysplastic Syndromes (MDS).

Aims
To support individualized treatment planning, we identified determinants of impaired HRQoL in patients with MDS.

Methods

We used longitudinal data from the EUMDS Registry, including 2205 patients at baseline (diagnosis) and two follow-up visits with a six month average interval. “Low HRQoL” was assigned to values below the medians of the two primary outcomes, EQ-5D index (0.78) and visual analogue scale (VAS) score (0.70). The EQ-5D dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) were used as secondary outcomes to assess impairment (any level versus “no problem” category).

We used bivariate logistic generalized estimating equation (GEE) models to estimate odds ratios (OR) and 95% confidence intervals (CI) for the associations of disease-specific and patient-related characteristics with HRQoL. In addition, multivariate analyses were performed for each of the two primary outcomes. Missing values were imputed by multiple imputation using the chained equation method. The GEE longitudinal method accounts for the dynamic changes over time and produces an average population estimate within the analyzed period.

Results

Characteristics identified as relevant determinants of low EQ-5D index and VAS score were respectively (ORs and [95%CI]): higher age (1.04 [1.03-1.05]; 1.05 [1.05-1.06]), female sex (1.61 [1.37-1.89]; 1.23 [1.05-1.45]), advanced IPSS-R scoring (1.08 [1.02-1.14]; 1.18 [1.11-1.25]), increased serum ferritin levels ≥1000 μg/L (1.73 [1.37-2.19]; 1.81 [1.47-2.33]), increased neutrophil counts x109/L (1.04 [1.02-1.06]; 1.03 [1.01-1.06]), transfusion dependence (1.44 [1.24-1.66]; 1.75 [1.50-2.04]), MDS-specific comorbidity index (MDS-CI) (1.19 [1.11-1.27]; 1.23 [1.15-1.32]), and Sorror comorbidity index (1.15 [1.10-1.19]; 1.14 [1.10-1.19]). In contrast, increased hemoglobin levels (0.87 [0.84-0.90]; 0.82 [0.80-0.85]) and high Karnofsky performance index (KPI) (0.59 [0.55-0.63]; 0.49 [0.45-0.52]) were associated with improved HRQoL.

In the multivariate analysis, age above 75 years (1.84 [1.39-2.45]; 1.44 [1.07-1.92]), female sex (1.70 [1.43-2.03]; 1.22 [1.02-1.46]), serum ferritin levels ≥1000μg/L (1.41 [1.06-1.87]; 1.37 [1.02-1.84]), increased MDS-CI (1.11 [1.02-1.20]; 1.14 [1.05-1.25]) and high KPI (0.62 [0.58-0.67]; 0.53 [0.49-0.57]) remained relevant determinants for both low EQ-5D index and VAS score.

Regarding the secondary outcomes, around 30% of patients reported impairments in four EQ-5D dimensions and 10-11% in the dimension “self-care”. Female sex, KPI, Sorror comorbidity index, hemoglobin count and transfusion-related variables (transfusion dependence, cumulative number of transfusions and transfusion density) are major determinants of low HRQoL in all five dimensions. Advanced age increased the risk for low HRQoL, particularly in the dimension “mobility” and “self-care”. Fewer significant determinants were observed for the dimension “anxiety/depression”.

Conclusion
We identified female sex, comorbidities, advanced age and increased ferritin levels as key determinants of low HRQoL in newly diagnosed patients with MDS. These determinants provide valuable knowledge for quality-of-life assessment, treatment planning and monitoring, and early preventive measures in MDS.

Session topic: 10. Myelodysplastic syndromes - Clinical

Keyword(s): MDS, Quality of life

Abstract: EP796

Type: e-Poster

Background

Health-related quality of life (HRQoL) represents a valuable outcome parameter in treatment algorithms in patients with Myelodysplastic Syndromes (MDS).

Aims
To support individualized treatment planning, we identified determinants of impaired HRQoL in patients with MDS.

Methods

We used longitudinal data from the EUMDS Registry, including 2205 patients at baseline (diagnosis) and two follow-up visits with a six month average interval. “Low HRQoL” was assigned to values below the medians of the two primary outcomes, EQ-5D index (0.78) and visual analogue scale (VAS) score (0.70). The EQ-5D dimensions (mobility, self-care, usual activities, pain/discomfort, anxiety/depression) were used as secondary outcomes to assess impairment (any level versus “no problem” category).

We used bivariate logistic generalized estimating equation (GEE) models to estimate odds ratios (OR) and 95% confidence intervals (CI) for the associations of disease-specific and patient-related characteristics with HRQoL. In addition, multivariate analyses were performed for each of the two primary outcomes. Missing values were imputed by multiple imputation using the chained equation method. The GEE longitudinal method accounts for the dynamic changes over time and produces an average population estimate within the analyzed period.

Results

Characteristics identified as relevant determinants of low EQ-5D index and VAS score were respectively (ORs and [95%CI]): higher age (1.04 [1.03-1.05]; 1.05 [1.05-1.06]), female sex (1.61 [1.37-1.89]; 1.23 [1.05-1.45]), advanced IPSS-R scoring (1.08 [1.02-1.14]; 1.18 [1.11-1.25]), increased serum ferritin levels ≥1000 μg/L (1.73 [1.37-2.19]; 1.81 [1.47-2.33]), increased neutrophil counts x109/L (1.04 [1.02-1.06]; 1.03 [1.01-1.06]), transfusion dependence (1.44 [1.24-1.66]; 1.75 [1.50-2.04]), MDS-specific comorbidity index (MDS-CI) (1.19 [1.11-1.27]; 1.23 [1.15-1.32]), and Sorror comorbidity index (1.15 [1.10-1.19]; 1.14 [1.10-1.19]). In contrast, increased hemoglobin levels (0.87 [0.84-0.90]; 0.82 [0.80-0.85]) and high Karnofsky performance index (KPI) (0.59 [0.55-0.63]; 0.49 [0.45-0.52]) were associated with improved HRQoL.

In the multivariate analysis, age above 75 years (1.84 [1.39-2.45]; 1.44 [1.07-1.92]), female sex (1.70 [1.43-2.03]; 1.22 [1.02-1.46]), serum ferritin levels ≥1000μg/L (1.41 [1.06-1.87]; 1.37 [1.02-1.84]), increased MDS-CI (1.11 [1.02-1.20]; 1.14 [1.05-1.25]) and high KPI (0.62 [0.58-0.67]; 0.53 [0.49-0.57]) remained relevant determinants for both low EQ-5D index and VAS score.

Regarding the secondary outcomes, around 30% of patients reported impairments in four EQ-5D dimensions and 10-11% in the dimension “self-care”. Female sex, KPI, Sorror comorbidity index, hemoglobin count and transfusion-related variables (transfusion dependence, cumulative number of transfusions and transfusion density) are major determinants of low HRQoL in all five dimensions. Advanced age increased the risk for low HRQoL, particularly in the dimension “mobility” and “self-care”. Fewer significant determinants were observed for the dimension “anxiety/depression”.

Conclusion
We identified female sex, comorbidities, advanced age and increased ferritin levels as key determinants of low HRQoL in newly diagnosed patients with MDS. These determinants provide valuable knowledge for quality-of-life assessment, treatment planning and monitoring, and early preventive measures in MDS.

Session topic: 10. Myelodysplastic syndromes - Clinical

Keyword(s): MDS, Quality of life

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