Variation in Model-Based Economic Evaluations of Low-Dose Computed Tomography Screening for Lung Cancer: A Methodological Review
OBJECTIVES: There is significant heterogeneity in the results of published model-based economic evaluations of low-dose computed tomography (LDCT) screening for lung cancer. We sought to understand and demonstrate how these models differ. METHODS: An expansion and update of a previous systematic review (N = 19). Databases (including MEDLINE and Embase) were searched. Studies were included if strategies involving (single or multiple) LDCT screening were compared with no screening or other imaging modalities, in a population at risk of lung cancer. More detailed data extraction of studies from the previous review was conducted. Studies were critically appraised using the Consensus Health Economic Criteria list. RESULTS: A total of 16 new studies met the inclusion criteria, giving a total of 35 studies. There are geographic and temporal differences and differences in screening intervals and eligible populations. Studies varied in the types of models used, for example, decision tree, Markov, and microsimulation models. Most conducted a cost-effectiveness analysis (using life-years gained) or cost-utility analysis. The potential for overdiagnosis was considered in many models, unlike with other potential consequences of screening. Some studies report considering lead-time bias, but fewer mention length bias. Generally, the more recent studies, involving more complex modeling, tended to meet more of the critical appraisal criteria, with notable exceptions. CONCLUSIONS: There are many differences across the economic evaluations contributing to variation in estimates of the cost-effectiveness of LDCT screening for lung cancer. Several methodological factors and evidence needs have been highlighted that will require consideration in future economic evaluations to achieve better agreement.
Citation
@article{j.l.2022,
author = {Peters, J. L. and Snowsill, T. M. and Griffin, E. and
Robinson, S. and Hyde, C. J.},
title = {Variation in {Model-Based} {Economic} {Evaluations} of
{Low-Dose} {Computed} {Tomography} {Screening} for {Lung} {Cancer:}
{A} {Methodological} {Review}},
journal = {Value in Health},
volume = {25},
number = {4},
pages = {656 - 665},
date = {2022-04-01},
url = {https://tristansnowsill.co.uk/variation-in-model-based-economic.html},
doi = {10.1016/j.jval.2021.11.1352},
langid = {en},
abstract = {OBJECTIVES: There is significant heterogeneity in the
results of published model-based economic evaluations of low-dose
computed tomography (LDCT) screening for lung cancer. We sought to
understand and demonstrate how these models differ. METHODS: An
expansion and update of a previous systematic review (N = 19).
Databases (including MEDLINE and Embase) were searched. Studies were
included if strategies involving (single or multiple) LDCT screening
were compared with no screening or other imaging modalities, in a
population at risk of lung cancer. More detailed data extraction of
studies from the previous review was conducted. Studies were
critically appraised using the Consensus Health Economic Criteria
list. RESULTS: A total of 16 new studies met the inclusion criteria,
giving a total of 35 studies. There are geographic and temporal
differences and differences in screening intervals and eligible
populations. Studies varied in the types of models used, for
example, decision tree, Markov, and microsimulation models. Most
conducted a cost-effectiveness analysis (using life-years gained) or
cost-utility analysis. The potential for overdiagnosis was
considered in many models, unlike with other potential consequences
of screening. Some studies report considering lead-time bias, but
fewer mention length bias. Generally, the more recent studies,
involving more complex modeling, tended to meet more of the critical
appraisal criteria, with notable exceptions. CONCLUSIONS: There are
many differences across the economic evaluations contributing to
variation in estimates of the cost-effectiveness of LDCT screening
for lung cancer. Several methodological factors and evidence needs
have been highlighted that will require consideration in future
economic evaluations to achieve better agreement.}
}