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«Yael Lubell Thesis submitted towards the degree of Doctor of Philosophy at the University of London Health Policy Unit London School of Hygiene and ...»

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Enhanced Decision Models for the Diagnosis

and Treatment of Malaria in an age of ACTs

Yael Lubell

Thesis submitted towards the degree of Doctor of

Philosophy at the University of London

Health Policy Unit

London School of Hygiene and Tropical Medicine

University of London

January 2009

1

Statement of work

The data for the analyses in this thesis were obtained through collaborations with

individuals and organizations carrying out four randomized control trials in Africa and Asia.

My role in these trials was to assist in designing their economic evaluation with the advice of LSHTM staff, and to carry out the subsequent analyses. These studies form the core of the thesis. In the course of work on the thesis the following articles were also prepared

and published:

1) Lubell, Y., H. Reyburn, et al. (2007). "The cost-effectiveness of parasitological diagnosis for malaria-suspected patients in an era of combination therapy." Am J Trop Med Hyg 77(Suppl 6): 128-132.

2) Lubell, Y., H. Reyburn, et al. (2008). "The impact of response to the results of diagnostic tests for malaria: cost-benefit analysis." BMJ 336(7637): 202-5.

3) Lubell, Y., H. Hopkins, et al. (2008). "An interactive model for the assessment of the

economic costs and benefits of different rapid diagnostic tests for malaria." Malar J 7:

21.

4) Lubell, Y., Yeung, S. et al. (In press) "Cost-effectiveness of artesunate for the treatment of severe malaria" TMIH I certify being the lead author in the above publications, designing the models and drafting the manuscripts. Fellow authors had inputs relating to trial clinical outcomes, model structure, and reviewing and editing the manuscripts.

I have read and understood the School's definition of plagiarism and cheating given in the Research Degrees Handbook. I declare that this thesis is my own work, and that I have acknowledged all results and quotations from the published or unpublished work of other people.

December 10th 2008 Yoel Lubell Confirmed by Anne Mills 2 Abstract New diagnostics and treatments for malaria have renewed hope in the developing world as they promise relief from the debilitating effects of this illness. Accompanying these interventions are a growing number of economic evaluations assessing their efficiency. To ensure the relevance of economic evaluations to decision making purposes it is imperative that they use best available computational and statistical approaches.

This thesis initially discusses the necessary requirements for economic evaluations to ensure they provide appropriate decision recommendations. This is followed by four evaluations of malaria diagnostics and treatments using methods new to the context of malaria.

The first study expands the range of factors included in the evaluation of diagnostic tests, addressing compromised adherence to test results and societal costs associated with antimalarial use.

The second analysis demonstrates how models can be designed as decision support tools allowing stakeholders to enter local data along with other parameter estimates, priorities and values. Both Bayesian and deterministic models are presented for comparison.

The third analysis demonstrates the use of multilevel models for economic evaluations based on multi-centre trials. The chapter compares the results of a multilevel model evaluating treatments for severe malaria with those obtained in a standard analysis.

The fourth study uses a Markov model to evaluate the efficiency of Home Management of Malaria programmes. The use of a Markov model addresses the restricted portrayal of malaria infection and illness that has characterised many previous evaluations.

In addition to contributing to a better understanding of the cost-effectiveness of the latest malaria treatments and diagnostic tests, this thesis seeks to bridge the growing gap between recent methodological advances in the field of economic evaluation, and the relative paucity of evaluations producing practical and effective policy recommendations for areas of the world where the burden of malaria and other diseases is heaviest.

–  –  –

Statement of work

Abstract

Table of Contents

List of Figures

List of Tables

List of abbreviations

Acknowledgements

Preface

Thesis structure

1. Malaria, research and decision making

1.1 Introduction...........

1.2 A historical overview of malaria research and policy

1.2.1 Early discoveries

1.2.2 Centrally run vertical programmes

1.2.3 Proliferation of research and decision making bodies

1.3 The introduction of artemisinin combination therapies and rapid diagnostic tests

1.4 Overview of malaria pathology

–  –  –

1.4.2 Clinical manifestations

1.4.3 Long term morbidity

1.4.4 Host immunity

Case definition and diagnosis of malaria

1.5 1.6 Consequences of overdiagnosis of malaria

The impact of malaria on the economy

1.7 1.8 Approaches to decision making

1.8.1 The status quo bias

1.8.2 Intuitive decision making





1.8.3 'TIABIM' (Taking into account and bearing in mind)

1.8.4 Decision analysis

Decision analysis and economic evaluations

1.9 1.10 Chapter conclusion

2. Review of the literature on economic evaluation of malaria diagnostics and treatments

2.1 Aims of the review

Review scope and structure

2.2 2.3 Search strategy

2.4 Sea rch resu Its

2.4.1 Category 1- Trial based evaluations

–  –  –

2.4.3 Category III: Decision analytic models

2.4.4 Category IV: System dynamics

2.5 Chapter conclusion

3. Theoretical foundations of decision models for malaria diagnostics and treatments.. 59 3.1 Overview of economic evaluation frameworks

3.1.1 Economic evaluation frameworks

3.1.2 How results are applied; decision rules

3.1.3 Determining the ceiling ratio using the league table approach

3.1.4 Normative approaches to determining the ceiling ratio

3.1.5 Incorporating ceiling ratios in CUAs

3.1.6 The WHO-CHOICE framework

3.1.7 Drawbacks to the CUA/ceiling ratio approach

3.1.8 Return of the CBA?

3.1.9 Relevance of the economic evaluation frameworks to malaria diagnostics and treatments

3.2 Different levels of uncertainty in modelling and how these are handled............. 75 3.2.1 The use of Bayesian inference to incorporate external data and prior beliefs into the analysis

3.2.2 Generalisability of economic evaluation results

3.3 Chapter conclusion

–  –  –

4.1 Thesis aims

4.2 Main objectives

4.3 The CBA framework

4.3.1 Choice of method to assign monetary values to health benefits

4.3.2 Total costs as a summary measure

4.4 Broadening the range offactors in decision models

4.4.1 Adherence to diagnostic test resu Its

4.4.2 Incorporating adverse treatment outcomes

4.4.3 Capturing patient costs

4.4.4 Health outcomes for NMFls

4.5 Approach to modelling

4.5.1 Patient progression paths - interaction with profiles

4.5.2 Localising decision models instead of generalising results

4.5.3 Use of a fully Bayesian approach for the evaluation of malaria diagnostic tests.

4.5.4 The use of multilevel models to assess the generalisability of multi-centre studies

4.6 Data collection

4.7 Chapter conclusion

5. Broadening the range of factors in decision models: Non-adherence to diagnostic test results and the potential harm of antimalarials

–  –  –

5.2 Choice of diagnostic test

5.3 The impact of non-adherence to the results of ROTs................,

5.4 Harm of Treatment

5.5 Methods

5.5.1 Data

5.5.2 Evaluation framework............. "'"''''''''

5.5.3 Sensitivity analysis

5.6 Resu Its

5.6.1 Costs and accuracies............ """,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,

5.6.2 Ad herence

5.6.3 Harm of treatment

5.6.4 Sensitivity analysis

5.7 Discussion...... "

5.7.1 Lim itation s

5.7.2 Implications for policy and future economic evaluation of malaria diagnostic tests

5.8 Chapter conclusion............. "

6. The localisation of economic evaluations using Decision Support Tools - comparison of methods

6.1 Introd uction

–  –  –

6.3 DSTs - choice of methodological approach

6.4 Background to the decision problem: Choice of rapid diagnostic tests.............. 124 6.5 Factors for consideration in choice of RDT

6.6 Modelling the costs and consequences of alternative diagnostic strategies...... 127 6.6.1 The deterministic model

6.6.2 The Bayesian model

6.7 Discussion

6.8 Chapter conclusion

7. Multilevel modelling for the evaluation of artesunate for the treatment of severe malaria

7.1 Introduction to multilevel modelling

7.2 How does MLM differfrom multiple regression analysis?

7.3 Use of MLM in estimating the cost of treatments for severe malaria................. 148 7.3.1 Background

7.4 Methodology

Analysis

7.5 Results

7.5.1 Regression analyses

7.5.2 Testing model fit using DIC

7.6 Discussion

–  –  –

7.7 Chapter conclusion

8. Markov model for the evaluation of ACTs in the Ugandan HMM programme............ 164 8.1 Background

8.1.1 The Ugandan HMM programme

8.1.2 Considerations for policy regarding use of ACTs in HMM

8.2 Methods

8.2.1 Evaluation framework

8.2.2 Model structure

8.2.3 Input parameters

8.2.4 Perspective of the analysis

8.2.5 Model output

8.2.6 Data used in the analysis ofthe Uganda HMM programme

8.2.7 Sensitivity analysis

8.3 Results

8.3.1 Costs

8.3.2 Model output for the use of HOMAPAK@ in HMM

8.3.3 Model output for the use of Al in HMM

8.3.4 Sensitivity analysis

8.4 Discussion

8.4.1 Assumptions and limitations

–  –  –

8.4.3 Policy implications

8.5 Chapter conclusion

9. Discussion

9.1 Gaps in the literature and strengths and weaknesses of the methods used to address these

9.1.1 Choice of economic evaluation framework

9.1.2 Comprehensiveness of the analysis

9.1.3 Loca I releva nce of resu Its

9.1.4 Appropriate model structures

9.2 Sources of data

9.3 Main policy findings and implications

9.4 Relevance to non-malarial contexts

9.5 Further research

9.6 Conclusion

References

Annex 1: Papers cited in literature review of economic analyses of malaria treatments/diagnostics

Annex 2: Delphi Expert Consultation on untreated malaria and febrile illness: Probabilities of severe disease and death

Annex 3: Cost-effectiveness of artesunate for the treatment of severe malaria................ 252

–  –  –

Figure 2-1- A simple decision tree for the management of malaria suspected patients.......... 51 Figure 3-1: A cost-effectiveness plane

Figure 4-1 - Illustration of a Markov model for malaria suspected patients

Figure 5-1: Mindline model for the overdiagnosis of malaria

Figure 5-2: Decision trees in the model.

Figure 5-3: Total cost for ROTs, microscopy and presumptive treatment across all prevalences for children under five and adults

Figure 5-4: Model output for a 15 year old patient..

Figure 5-5: Cost savings with ROTs and microscopy

Figure 5-6: Most attractive strategy stratified by patient age

Figure 5-7: Preferred strategy with and without the inclusion of the harm of treatment factor for patients aged 5 to 14

Figure 5-8: Model output for children under 5 with the inclusion on the harm of treatment factor

Figure 5-9a,b,c: Most efficient strategy by adherence and prevalence

Figure 5-10: Total costs for children under 5 with the baseline estimate of the harm of treatment and a low estimate

Figure 6-1 Patient progression paths and subsequent costs

Figure 6-2. The deterministic model user interface

–  –  –

Figure 6-4: Model structure for estimation of total costs for each RDT

Figure 6-5 Results from the Bayesian model in WinBUGS

Figure 7-1 - OLS regression for the effect oftreatment on Net Monetary Benefit.................. 141 Figure 7-2: The effect oftreatment on net benefit by site considerably

Figure 7-3: Pooled and stratified regression lines

Figure 7-4: The individual centre regression lines

Figure 7-5: Differences in treatment costs and 95% confidence intervals across all sites and the pooled estimate

Figure 7-6:Graphs representing the incremental cost for all models

Figure 8-1: Markov health states and possible transitions between them

Figure 8-2: Model interface

Figure 8-3: Model output for the Uganda HMM programme with the use of HOMAPAK®... 181 Figure 8-4: Model output for the Uganda HMM programme with the use of AL

Figure 8-5: Model output for an ideal antimalarial, compared with AL as first line treatment in health facilities

Figure 8-6: Model output with the inclusion of the harm of treatment factor, with AL being used in both HMM and health facilities

Figure 8-7: Model output using a societal perspective................. Errorl Bookmark not defined.

Figure 9-1: An illustration ofthe thesis aim and themes

–  –  –

Table 4-1: Summary of frameworks and methods used in the analyses

Table 5-1: Parameter inputs

Table 6-1: Initial parameter estimates used in the models

Table 7-1: Regression coefficients and the uncertainty surrounding these



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