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How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review
BACKGROUND: There are an increasing number of studies using simulation models to conduct cost-effectiveness analyses for type 2 diabetes mellitus. OBJECTIVE: To evaluate the relationship between improvements in glycosylated haemoglobin (HbA(1c)) and simulated health outcomes in type 2 diabetes cost-...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5306373/ https://www.ncbi.nlm.nih.gov/pubmed/27873225 http://dx.doi.org/10.1007/s40273-016-0466-0 |
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author | Hua, Xinyang Lung, Thomas Wai-Chun Palmer, Andrew Si, Lei Herman, William H. Clarke, Philip |
author_facet | Hua, Xinyang Lung, Thomas Wai-Chun Palmer, Andrew Si, Lei Herman, William H. Clarke, Philip |
author_sort | Hua, Xinyang |
collection | PubMed |
description | BACKGROUND: There are an increasing number of studies using simulation models to conduct cost-effectiveness analyses for type 2 diabetes mellitus. OBJECTIVE: To evaluate the relationship between improvements in glycosylated haemoglobin (HbA(1c)) and simulated health outcomes in type 2 diabetes cost-effectiveness studies. METHODS: A systematic review was conducted on MEDLINE and EMBASE to collect cost-effectiveness studies using type 2 diabetes simulation models that reported modelled health outcomes of blood glucose-related interventions in terms of quality-adjusted life-years (QALYs) or life expectancy (LE). The data extracted included information used to characterise the study cohort, the intervention’s treatment effects on risk factors and model outcomes. Linear regressions were used to test the relationship between the difference in HbA(1c) (∆HbA(1c)) and incremental QALYs (∆QALYs) or LE (∆LE) of intervention and control groups. The ratio between the ∆QALYs and ∆LE was calculated and a scatterplot between the ratio and ∆HbA(1c) was used to explore the relationship between these two. RESULTS: Seventy-six studies were included in this research, contributing to 124 pair of comparators. The pooled regressions indicated that the marginal effect of a 1% HbA(1c) decrease in intervention resulted in an increase in life-time QALYs and LE of 0.371 (95% confidence interval 0.286–0.456) and 0.642 (95% CI 0.494–0.790), respectively. No evidence of heterogeneity between models was found. An inverse exponential relationship was found and fitted between the ratio (∆QALY/∆LE) and ∆HbA(1c). CONCLUSION: There is a consistent relationship between ∆HbA(1c) and ∆QALYs or ∆LE in cost-effectiveness analyses using type 2 diabetes simulation models. This relationship can be used as a diagnostic tool for decision makers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40273-016-0466-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5306373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-53063732017-02-27 How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review Hua, Xinyang Lung, Thomas Wai-Chun Palmer, Andrew Si, Lei Herman, William H. Clarke, Philip Pharmacoeconomics Systematic Review BACKGROUND: There are an increasing number of studies using simulation models to conduct cost-effectiveness analyses for type 2 diabetes mellitus. OBJECTIVE: To evaluate the relationship between improvements in glycosylated haemoglobin (HbA(1c)) and simulated health outcomes in type 2 diabetes cost-effectiveness studies. METHODS: A systematic review was conducted on MEDLINE and EMBASE to collect cost-effectiveness studies using type 2 diabetes simulation models that reported modelled health outcomes of blood glucose-related interventions in terms of quality-adjusted life-years (QALYs) or life expectancy (LE). The data extracted included information used to characterise the study cohort, the intervention’s treatment effects on risk factors and model outcomes. Linear regressions were used to test the relationship between the difference in HbA(1c) (∆HbA(1c)) and incremental QALYs (∆QALYs) or LE (∆LE) of intervention and control groups. The ratio between the ∆QALYs and ∆LE was calculated and a scatterplot between the ratio and ∆HbA(1c) was used to explore the relationship between these two. RESULTS: Seventy-six studies were included in this research, contributing to 124 pair of comparators. The pooled regressions indicated that the marginal effect of a 1% HbA(1c) decrease in intervention resulted in an increase in life-time QALYs and LE of 0.371 (95% confidence interval 0.286–0.456) and 0.642 (95% CI 0.494–0.790), respectively. No evidence of heterogeneity between models was found. An inverse exponential relationship was found and fitted between the ratio (∆QALY/∆LE) and ∆HbA(1c). CONCLUSION: There is a consistent relationship between ∆HbA(1c) and ∆QALYs or ∆LE in cost-effectiveness analyses using type 2 diabetes simulation models. This relationship can be used as a diagnostic tool for decision makers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40273-016-0466-0) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-11-21 2017 /pmc/articles/PMC5306373/ /pubmed/27873225 http://dx.doi.org/10.1007/s40273-016-0466-0 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Systematic Review Hua, Xinyang Lung, Thomas Wai-Chun Palmer, Andrew Si, Lei Herman, William H. Clarke, Philip How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review |
title | How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review |
title_full | How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review |
title_fullStr | How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review |
title_full_unstemmed | How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review |
title_short | How Consistent is the Relationship between Improved Glucose Control and Modelled Health Outcomes for People with Type 2 Diabetes Mellitus? a Systematic Review |
title_sort | how consistent is the relationship between improved glucose control and modelled health outcomes for people with type 2 diabetes mellitus? a systematic review |
topic | Systematic Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5306373/ https://www.ncbi.nlm.nih.gov/pubmed/27873225 http://dx.doi.org/10.1007/s40273-016-0466-0 |
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