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A review of modelling methods to evaluate screening programmes identified the natural history modelling approach as the preferred general method.

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Abstract

OBJECTIVES

To undertake a structured review and critical appraisal of methods for the model-based cost-utility analysis of screening programmes. Also to develop guidelines and an assessment checklist of good practice in the development of screening models.

DATA SOURCES

Major electronic databases of healthcare and operational research literatures were searched up to June 2003.

REVIEW METHODS

Searches of the literature were undertaken to identify applied and methodological studies of economic evaluations of healthcare screening programmes. All applied screening models were also reviewed in three broad disease areas (cancer, cardiovascular disease and diabetes), as well as antenatal screening. A second-level review focused on particular aspects of the modelling process through case study assessments of screening models for three specific disease areas (colorectal cancer, abdominal aortic aneurysms and antenatal screening for haemoglobinopathies). A separate literature review of studies reporting the utility effects of screening was also undertaken. Guidelines and an assessment checklist for good practice for screening modelling were developed.

RESULTS

Few relevant methodological studies were identified, and no studies reporting direct empirical comparisons of alternative methodologies were retrieved. From the review of disease-based screening models, it was apparent that many alternative modelling methods had been applied, including some relatively new approaches that had not been widely disseminated. Natural history modelling is the preferred approach. Alternative modelling approaches were generally only used to extrapolate the observed effects of screening and were unsuitable for evaluating unobserved screening options. More complex model structures may incorporate important additional aspects of the disease natural history, although any benefits should outweigh the consequences of additional unobservable input parameters and increased complexity in implementing the model. No direct comparisons of more detailed and less detailed screening model structures informed areas in which more realistic representations of the disease process may be most beneficial, so only general aspects of good practice could be defined. Two structural aspects that were not well handled by existing screening models included post-diagnosis disease progression and screening uptake. Most models described the former using historical mortality rates, rather than treatment models that are representative of current treatment patterns for different stages of the disease. Constant screening uptake rates were applied to all screening programmes and attendance was not linked to disease incidence or progression. Evidence exists to inform a more detailed representation of screening uptake. The most commonly applied modelling techniques were cohort Markov models and individual sampling simulation models. Individual sampling simulation models may provide more flexibility in their representation of a screening decision problem, but any benefits should outweigh the consequences of the need to assess both variability and uncertainty. Complex mathematical models describing input parameters as continuous variables have analysed the cost-effectiveness of screening; these require further development to estimate the cost-utility of screening directly, or to inform a more detailed representation of the preclinical section of a natural history model (with a traditional state-based model describing pathways' post-clinical presentation). Calibration is a common aspect of screening models, whereby models are fitted to observed data describing outputs of the model in order to populate unobserved input parameters. The review concluded that the estimation of a reference case input parameter set is not recommended.

CONCLUSIONS

The review of methods for the model-based cost-utility analysis of screening programmes identified the natural history modelling approach as the preferred general method of evaluation for screening programmes. State transition models have generally been used to represent disease natural histories, with individual sampling models more prevalent than in treatment intervention evaluations. No comparative methodological studies were identified, so no empirical data were available to inform the relative merits of alternative methodologies. The defined guidelines and assessment checklist are informed, therefore, by theoretical interpretations of the impact of alternative approaches to different components of the modelling process when applied to the cost-utility analysis of screening programmes. Further research is needed into methods with the potential to improve the accuracy of screening models, and to respond to the needs of model users.

Abstract

OBJECTIVES

To undertake a structured review and critical appraisal of methods for the model-based cost-utility analysis of screening programmes. Also to develop guidelines and an assessment checklist of good practice in the development of screening models.

DATA SOURCES

Major electronic databases of healthcare and operational research literatures were searched up to June 2003.

REVIEW METHODS

Searches of the literature were undertaken to identify applied and methodological studies of economic evaluations of healthcare screening programmes. All applied screening models were also reviewed in three broad disease areas (cancer, cardiovascular disease and diabetes), as well as antenatal screening. A second-level review focused on particular aspects of the modelling process through case study assessments of screening models for three specific disease areas (colorectal cancer, abdominal aortic aneurysms and antenatal screening for haemoglobinopathies). A separate literature review of studies reporting the utility effects of screening was also undertaken. Guidelines and an assessment checklist for good practice for screening modelling were developed.

RESULTS

Few relevant methodological studies were identified, and no studies reporting direct empirical comparisons of alternative methodologies were retrieved. From the review of disease-based screening models, it was apparent that many alternative modelling methods had been applied, including some relatively new approaches that had not been widely disseminated. Natural history modelling is the preferred approach. Alternative modelling approaches were generally only used to extrapolate the observed effects of screening and were unsuitable for evaluating unobserved screening options. More complex model structures may incorporate important additional aspects of the disease natural history, although any benefits should outweigh the consequences of additional unobservable input parameters and increased complexity in implementing the model. No direct comparisons of more detailed and less detailed screening model structures informed areas in which more realistic representations of the disease process may be most beneficial, so only general aspects of good practice could be defined. Two structural aspects that were not well handled by existing screening models included post-diagnosis disease progression and screening uptake. Most models described the former using historical mortality rates, rather than treatment models that are representative of current treatment patterns for different stages of the disease. Constant screening uptake rates were applied to all screening programmes and attendance was not linked to disease incidence or progression. Evidence exists to inform a more detailed representation of screening uptake. The most commonly applied modelling techniques were cohort Markov models and individual sampling simulation models. Individual sampling simulation models may provide more flexibility in their representation of a screening decision problem, but any benefits should outweigh the consequences of the need to assess both variability and uncertainty. Complex mathematical models describing input parameters as continuous variables have analysed the cost-effectiveness of screening; these require further development to estimate the cost-utility of screening directly, or to inform a more detailed representation of the preclinical section of a natural history model (with a traditional state-based model describing pathways' post-clinical presentation). Calibration is a common aspect of screening models, whereby models are fitted to observed data describing outputs of the model in order to populate unobserved input parameters. The review concluded that the estimation of a reference case input parameter set is not recommended.

CONCLUSIONS

The review of methods for the model-based cost-utility analysis of screening programmes identified the natural history modelling approach as the preferred general method of evaluation for screening programmes. State transition models have generally been used to represent disease natural histories, with individual sampling models more prevalent than in treatment intervention evaluations. No comparative methodological studies were identified, so no empirical data were available to inform the relative merits of alternative methodologies. The defined guidelines and assessment checklist are informed, therefore, by theoretical interpretations of the impact of alternative approaches to different components of the modelling process when applied to the cost-utility analysis of screening programmes. Further research is needed into methods with the potential to improve the accuracy of screening models, and to respond to the needs of model users.

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