Evidence map›Paper›PMID 38755403›Full record

ArticleApplied health economics and health policy2024

A structured process for the validation of a decision-analytic model: application to a cost-effectiveness model for risk-stratified national breast screening.

Stuart J Wright, Ewan Gray, Gabriel Rogers, Anna Donten, Katherine Payne

Abstract readValidation Study
In one paragraph

Article in Applied health economics and health policy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Stuart J WrightDivision of Population Health, Health Services Research and Primary Care, Manchester Centre for Health Economics, The University of Manchester, Oxford Road, Manchester, M139PL, UK. stuart.j.wright@manchester.ac.uk.ORCID 0000-0002-4064-7998
Ewan GrayGRAIL, New Penderel House 4th Floor, 283-288 High Holborn, London, WC1V 7HP, UK.ORCID 0000-0003-3840-5268
Gabriel RogersDivision of Population Health, Health Services Research and Primary Care, Manchester Centre for Health Economics, The University of Manchester, Oxford Road, Manchester, M139PL, UK.ORCID 0000-0001-9339-7374
Anna DontenDivision of Population Health, Health Services Research and Primary Care, Manchester Centre for Health Economics, The University of Manchester, Oxford Road, Manchester, M139PL, UK.ORCID 0000-0002-4896-6002
Katherine PayneDivision of Population Health, Health Services Research and Primary Care, Manchester Centre for Health Economics, The University of Manchester, Oxford Road, Manchester, M139PL, UK.ORCID 0000-0002-3938-4350

Funding

Cancer Research UK International Alliance for Cancer Early DetectionProgramme Grants for Applied Research RP-PG-1214-20016
6 · The paper itself

Abstract

backgroundDecision-makers require knowledge of the strengths and weaknesses of decision-analytic models used to evaluate healthcare interventions to be able to confidently use the results of such models to inform policy. A number of aspects of model validity have previously been described, but no systematic approach to assessing the validity of a model has been proposed. This study aimed to consolidate the different aspects of model validity into a step-by-step approach to assessing the strengths and weaknesses of a decision-analytic model.

methodsA pre-defined set of steps were used to conduct the validation process of an exemplar early decision-analytic-model-based cost-effectiveness analysis of a risk-stratified national breast cancer screening programme [UK healthcare perspective; lifetime horizon; costs (£; 2021)]. Internal validation was assessed in terms of descriptive validity, technical validity and face validity. External validation was assessed in terms of operational validation, convergent validity (or corroboration) and predictive validity.

resultsThe results outline the findings of each step of internal and external validation of the early decision-analytic-model and present the validated model (called 'MANC-RISK-SCREEN'). The positive aspects in terms of meeting internal validation requirements are shown together with the remaining limitations of MANC-RISK-SCREEN.

conclusionFollowing a transparent and structured validation process, MANC-RISK-SCREEN has been shown to have satisfactory internal and external validity for use in informing resource allocation decision-making. We suggest that MANC-RISK-SCREEN can be used to assess the cost-effectiveness of exemplars of risk-stratified national breast cancer screening programmes (NBSP) from the UK perspective. IMPLICATIONS: A step-by-step process for conducting the validation of a decision-analytic model was developed for future use by health economists. Using this approach may help researchers to fully demonstrate the strengths and limitations of their model to decision-makers.

Indexed as

Breast NeoplasmsCost-Benefit AnalysisDecision Support TechniquesEarly Detection of CancerAgedFemaleHumansMiddle AgedReproducibility of ResultsRisk AssessmentUnited Kingdom

Identifiers

PMID38755403
PMCPMC11178649

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.