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Pleyer L, Heibl S, Tinchon C, Vallet S, Schreder M, Melchardt T, Stute N, Föhrenbach Quiroz KT, Leisch M, Egle A, Scagnetti L, Wolf D, Beswick R, Drost M, Larcher-Senn J, Grochtdreis T, Vaisband M, Hasenauer J, Zaborsky N, Greil R, Stauder R. Health-Related Quality of Life as Assessed by the EQ-5D-5L Predicts Outcomes of Patients Treated with Azacitidine-A Prospective Cohort Study by the AGMT. Cancers (Basel) 2023; 15:cancers15051388. [PMID: 36900181 PMCID: PMC10000211 DOI: 10.3390/cancers15051388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 02/10/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
In this prospective study (NCT01595295), 272 patients treated with azacitidine completed 1456 EuroQol 5-Dimension (EQ-5D) questionnaires. Linear mixed-effect modelling was used to incorporate longitudinal data. When compared with a matched reference population, myeloid patients reported more pronounced restrictions in usual activities (+28%, p < 0.0001), anxiety/depression (+21%, p < 0.0001), selfcare (+18%, p < 0.0001) and mobility (+15%, p < 0.0001), as well as lower mean EQ-5D-5L indices (0.81 vs. 0.88, p < 0.0001), and lower self-rated health on the EuroQol Visual Analogue Scale (EQ-VAS) (64 vs. 72%, p < 0.0001). After multivariate-adjustment, (i) the EQ-5D-5L index assessed at azacitidine start the predicted time with clinical benefit (TCB) (9.6 vs. 6.6 months; p = 0.0258; HR = 1.43), time to next treatment (TTNT) (12.8 vs. 9.8 months; p = 0.0332; HR = 1.42) and overall survival (OS) (17.9 vs. 12.9 months; p = 0.0143; HR = 1.52); (ii) Level Sum Score (LSS) predicted azacitidine response (p = 0.0160; OR = 0.451) and the EQ-5D-5L index showed a trend (p = 0.0627; OR = 0.522); (iii) up to 1432 longitudinally assessed EQ-5D-5L response/clinical parameter pairs revealed significant associations of EQ-5D-5L response parameters with haemoglobin level, transfusion dependence and hematologic improvement. Significant increases of the likelihood ratios were observed after addition of LSS, EQ-VAS or EQ-5D-5L-index to the International Prognostic Scoring System (IPSS) or the revised IPSS (R-IPSS), indicating that they provide added value to these scores.
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Affiliation(s)
- Lisa Pleyer
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Correspondence: or ; Tel.: +43-(0)676-8997-58271
| | - Sonja Heibl
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- 4th Medical Department of Internal Medicine, Hematology, Internistic Oncology and Palliative Medicine, Klinikum Wels-Grieskirchen GmbH, 4600 Wels, Austria
| | - Christoph Tinchon
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Department for Hemato-Oncology, LKH Hochsteiermark, 8700 Leoben, Austria
| | - Sonia Vallet
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Department of Internal Medicine 2, University Hospital Krems, Karl Landsteiner Private University of Health Sciences, 3500 Krems, Austria
| | - Martin Schreder
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- 1st Department of Internal Medicine, Center for Oncology and Hematology, Klinik Ottakring, Wiener Gesundheitsverbund, 1030 Vienna, Austria
| | - Thomas Melchardt
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
| | - Norbert Stute
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
| | - Kim Tamara Föhrenbach Quiroz
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
| | - Michael Leisch
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
| | - Alexander Egle
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
| | - Lukas Scagnetti
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- 4th Medical Department of Internal Medicine, Hematology, Internistic Oncology and Palliative Medicine, Klinikum Wels-Grieskirchen GmbH, 4600 Wels, Austria
| | - Dominik Wolf
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Department of Internal Medicine V, Innsbruck Medical University, 6020 Innsbruck, Austria
| | - Richard Beswick
- International Marketing, Swiss Business School, 8302 Zurich, Switzerland
| | - Manuel Drost
- Assign Data Management and Biostatistics GmbH, 6020 Innsbruck, Austria
| | | | - Thomas Grochtdreis
- Department of Health Economics and Health Services Research, Hamburg Center for Health Economics, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany
| | - Marc Vaisband
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Jan Hasenauer
- Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Nadja Zaborsky
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
- Laboratory of Immunological and Molecular Cancer Research (LIMCR), 5020 Salzburg, Austria
| | - Richard Greil
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Salzburg Cancer Research Institute (SCRI), Center for Clinical Cancer and Immunology Trials (CCCIT), Austria and Cancer Cluster Salzburg (CCS), 5020 Salzburg, Austria
- 3rd Medical Department with Hematology, Medical Oncology, Hemostaseology, Rheumatology and Infectiology, Oncologic Center, Paracelsus Medical University, 5020 Salzburg, Austria
| | - Reinhard Stauder
- Austrian Group for Medical Tumor Therapy (AGMT) Study Group, 1180 Vienna, Austria
- Department of Internal Medicine V, Innsbruck Medical University, 6020 Innsbruck, Austria
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Matza LS, Deger KA, Howell TA, Koetter K, Yeager AM, Hogge D, Fisher V, Louie AC, Chung KC. Health state utilities associated with treatment options for acute myeloid leukemia (AML). J Med Econ 2019; 22:567-576. [PMID: 30775943 DOI: 10.1080/13696998.2019.1584108] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Aims: Acute myeloid leukemia (AML) treatment typically involves remission induction chemotherapy followed by consolidation chemotherapy. New treatments for AML have recently been introduced, including a chemotherapy formulation called CPX-351, which is administered via less time-intensive IV infusion than the standard "7 + 3" continuous infusion regimen of cytarabine plus an anthracycline. The purpose of this study was to estimate utilities that could be used in economic modeling of AML treatment. Materials and methods: In time trade-off interviews, participants from the UK general population valued 12 health states drafted based on literature and clinician interviews. To identify disutility associated with chemotherapy, two types of induction and four types of consolidation were added to an otherwise identical health state describing AML. The decrease in utility when adding these chemotherapy regimens represents the disutility of each regimen. Five additional health states were valued to estimate utilities associated with other AML treatments. Results: Two hundred participants completed interviews. Mean (SD) utilities were 0.55 (0.31) for pre-treatment AML and 0.66 (0.29) for AML in temporary remission. Adding any chemotherapy significantly decreased utility (p < 0.0001). Induction had a mean disutility of -0.11 with CPX-351 and -0.15 with 7 + 3. Mean disutility for consolidation ranged from -0.03 with outpatient CPX-351 to -0.11 with inpatient 5 + 2. Utilities are also reported for other AML treatments (e.g. transplant, low-intensity chemotherapy). Limitations: One limitation is that the differences in adverse event profiles between the treatment regimens were based on clinician opinion. Future use of CPX-351 in clinical trials or clinical settings will provide additional information on its adverse event profile. Conclusions: While all chemotherapy regimens were associated with disutility, regimens with shorter hospitalization and less time-intensive infusion were generally perceived as preferable. These utilities may be useful in cost-utility models comparing the value of AML treatments.
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Affiliation(s)
- Louis S Matza
- a Patient-Centered Research , Evidera , Bethesda , MD , USA
| | | | | | | | | | - Donna Hogge
- e Gordon and Leslie Diamond Health Care Centre , Vancouver , BC , Canada
| | - Vicki Fisher
- f Jazz Pharmaceuticals, Inc , Palo Alto , CA , USA
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Forsythe A, Brandt PS, Dolph M, Patel S, Rabe APJ, Tremblay G. Systematic review of health state utility values for acute myeloid leukemia. CLINICOECONOMICS AND OUTCOMES RESEARCH 2018; 10:83-92. [PMID: 29416365 PMCID: PMC5790088 DOI: 10.2147/ceor.s153286] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Background Cost-utility analyses for acute myeloid leukemia (AML) require health state utility values (HSUVs) in order to calculate quality-adjusted life-years (QALYs) for each health state. Aim This study reviewed AML-related HSUVs that could be used in economic evaluation studies. Materials and methods EMBASE, MEDLINE, and Cochrane databases were searched from January 2000 to November 2016 for relevant studies that reported quality of life (QoL) and HSUVs in AML. Identified relevant European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 values were mapped to HSUVs. HSUVs for each health state in the AML treatment pathway were then collated. Results Ten relevant studies were identified. Six were cost-effectiveness analyses utilizing HSUVs for calculation of QALYs, one was an effectiveness analysis (incremental QALY), and two were QoL studies reporting AML-specific utilities. An additional study reported QoL for patients undergoing stem cell transplantation (SCT). Since no study reported HSUVs for relapse, values from a study of secondary AML patients who failed prior treatment for myelodysplastic syndrome were used. Where multiple HSUVs were available, collected values were given priority over assumed values. AML treatment (induction, consolidation, or SCT) was associated with decreased HSUV, while post-treatment complete remission led to increased HSUV. Conclusion There are some methodologically robust HSUVs that can be directly used in economic evaluations for AML. Careful interpretation is advised considering significant differences in methodologies and patient population (inclusion, size). We need to develop HSUVs with larger-sized studies, making greater use of condition-specific data.
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Affiliation(s)
| | | | | | - Sachin Patel
- Novartis Pharmaceuticals UK Limited, Frimley, Camberley, Surrey, UK
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Khan KM, Evans SS, Bielko SL, Rohlman DS. Efficacy of technology-based interventions to increase the use of hearing protections among adolescent farmworkers. Int J Audiol 2017; 57:124-134. [PMID: 28918682 DOI: 10.1080/14992027.2017.1374568] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
OBJECTIVE Adolescent farmworkers are exposed to loud noise during farm activities. We present a prospective study that evaluated the efficacy of low-cost, technology-based intervention approaches in high schools to enhance the use of hearing protection among adolescent farmworkers. DESIGN Six high schools in Iowa that agreed to participate in the study were divided into three equal groups through cluster-randomisation with each group receiving one of the three formats of hearing protection intervention: (a) classroom training, (b) classroom training coupled with smartphone app training and (c) computer training. Participants completed baseline (pre-training) and six-week post-intervention surveys for assessing hearing protection knowledge, attitudes and behaviour. STUDY SAMPLE Seventy participants from six schools were initially enrolled but 50 completed both pre- and post-intervention surveys. RESULTS In most cases, all three groups showed significant improvement in hearing protection knowledge, attitude and frequency of use from pre- to post-intervention. However, changes between groups were statistically non-significant. CONCLUSIONS Although all three formats led to improvements on hearing protection knowledge, attitude and behaviour, the findings of the study, perhaps due to the small sample size, did not allow us to detect whether technology-based hearing protection interventions were more effective than the traditional face-to-face training for adolescent farmworkers.
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Affiliation(s)
- Khalid M Khan
- a Department of Environmental Health, School of Public Health , Indiana University , Bloomington , IN , USA and
| | - Sydney S Evans
- a Department of Environmental Health, School of Public Health , Indiana University , Bloomington , IN , USA and
| | - Sylvanna L Bielko
- a Department of Environmental Health, School of Public Health , Indiana University , Bloomington , IN , USA and
| | - Diane S Rohlman
- b Occupational and Environmental Health , College of Public Health, The University of Iowa , Iowa City , IA , USA
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Allart P, Soubeyran P, Cousson-Gélie F. Are psychosocial factors associated with quality of life in patients with haematological cancer? A critical review of the literature. Psychooncology 2012; 22:241-9. [PMID: 22287503 DOI: 10.1002/pon.3026] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2011] [Revised: 12/08/2011] [Accepted: 12/08/2011] [Indexed: 11/12/2022]
Abstract
BACKGROUND Haematological cancers differ from other cancers mainly with regard to treatment strategies: surgery is used for diagnostic purposes but rarely for treatment, whereas chemotherapy is of central importance and, in some cases, cures patients. This article reviews studies that examine the relationships between psychosocial factors and quality of life (QoL) in haematological cancer patients. METHODS A review of the literature was conducted from the databases 'PsycInfo', 'Medline' and 'Science Direct' using the keywords 'lymphoma', 'leukaemia', 'myeloma', 'quality of life', 'psychosocial factors', 'coping', 'social support', 'personality', 'anxiety,' 'depression', 'locus of control' and 'alexithymia'. RESULTS Fourteen studies were analysed. One study found positive relationships between sense of coherence and health-related QoL, whereas another showed a positive link between self-esteem and QoL. Another study suggested that a high external health locus of control was related to a better QoL. Fighting spirit had a positive impact on QoL for two studies, and helplessness-hopelessness was positively related to emotional distress in one study. Two studies indicated the relationships between emotional distress and QoL. Satisfaction with information about disease determined emotional distress in another study. Social support, general health perceptions, global meaning or spirituality were found to improve QoL in four other reports. CONCLUSION Literature about the relationships between psychosocial factors and QoL is lacking. Sense of coherence, self-esteem and health locus of control, coping strategies, social support, global meaning or emotional distress are associated with QoL. Results concerning coping and social support should be interpreted with caution because of level II evidence in studies.
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Affiliation(s)
- Priscilla Allart
- Laboratory of Psychology Health and Quality of Life, University Bordeaux Segalen, Bordeaux, France.
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Economic analysis of decitabine versus best supportive care in the treatment of intermediate- and high-risk myelodysplastic syndromes from a US payer perspective. Clin Ther 2011; 32:2444-56. [PMID: 21353113 DOI: 10.1016/j.clinthera.2010.12.003] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/04/2010] [Indexed: 11/21/2022]
Abstract
BACKGROUND Myelodysplastic syndromes (MDS) are blood and bone marrow disorders that occur primarily in the elderly population, with 30% of all cases progressing to acute myeloid leukemia (AML). Red blood cell transfusions--a conventional treatment of MDS--have been associated with high costs and decreased quality of life compared with transfusion independence. Phase III clinical trial data suggest that decitabine may offer an improved AML-free survival versus best supportive care (BSC), which consists of red blood cell transfusions, deferoxamine, erythropoiesis-stimulating agents, platelet transfusions, and colony-stimulating factors. The US Food and Drug Administration has approved a 5-day outpatient decitabine dosing regimen, which might reduce administration costs compared with the standard 3-day inpatient regimen. OBJECTIVE The aim of this study was to assess the cost-effectiveness of 5-day dosing of decitabine versus BSC in US patients with intermediate- and high-risk MDS from a US payer perspective. METHODS A Markov model with 3 health states (MDS, AML, and death) was constructed to simulate natural disease progression. The model followed patients in 4-week cycles for ≤ 5 years. Clinical inputs and patient characteristics were based on decitabine Phase III clinical trial data. Costs of supportive care and adverse events were based on trial resource utilization data. Drug and AML costs were obtained from published sources. Deterministic and probabilistic sensitivity analyses were performed to determine the impact of model parameters on results. RESULTS In the base-case model, decitabine yielded 0.276 additional year of AML-free survival and 0.052 more quality-adjusted life-year (QALY) compared with BSC. Total decitabine and administration costs over the 5-year time horizon were $28,933. Total direct medical costs were $122,940 in the decitabine arm and $122,666 in the BSC arm. The incremental cost-effectiveness ratio for decitabine versus BSC was $5277 per QALY gained. Sensitivity analyses indicated that decitabine had a higher probability than BSC of being cost-effective despite the uncertainty around some model parameters, including survival. CONCLUSION In this study, decitabine administered on a 5-day dosing schedule was likely a cost-effective treatment option in patients with intermediate- and high-risk MDS from a US payer perspective.
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