Evidence map›Paper›PMID 37903130›Full record

ArticlePloS one2023

Evaluating the health and health economic impact of the COVID-19 pandemic on delayed cancer care in Belgium: A Markov model study protocol.

Yasmine Khan, Nick Verhaeghe, Robby De Pauw, Brecht Devleesschauwer, Sylvie Gadeyne, Vanessa Gorasso, Yolande Lievens, Niko Speybroek, Nancy Vandamme, Miet Vandemaele and 5 more

Erratum issuedOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 17% of its field
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

4 citing papers in PubMed, 5 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 4 institutions in 1 country.

Yasmine KhanDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.ORCID 0000-0002-4679-8236
Nick VerhaegheDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.
Robby De PauwDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.ORCID 0000-0002-4242-9062
Brecht DevleesschauwerDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Sylvie GadeyneInterface Demography, Department of Sociology, Vrije Universiteit Brussel, Brussels, Belgium.
Vanessa GorassoDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.
Yolande LievensRadiation Oncology Department, Ghent University Hospital and Ghent University, Ghent, Belgium.
Niko SpeybroekResearch Institute of Health and Society, University of Louvain, Brussels, Belgium.
Nancy VandammeResearch Department, Belgian Cancer Registry, Brussels, Belgium.ORCID 0000-0003-4636-7636
Miet VandemaeleRadiation Oncology Department, Ghent University Hospital and Ghent University, Ghent, Belgium.
Laura Van den BorreDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Sophie VandepitteDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.
Katrien VanthommeDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.
Freija VerdoodtResearch Department, Belgian Cancer Registry, Brussels, Belgium.
Delphine De SmedtDepartment of Public Health and Primary Care, Ghent University, Ghent, Belgium.
Ghent University · BEVrije Universiteit Brussel · BEGhent University Hospital · BEUCLouvain · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionCancer causes a substantial burden to our society, both from a health and an economic perspective. To improve cancer patient outcomes and lower society expenses, early diagnosis and timely treatment are essential. The recent COVID-19 crisis has disrupted the care trajectory of cancer patients, which may affect their prognosis in a potentially negative way. The purpose of this paper is to present a flexible decision-analytic Markov model methodology allowing the evaluation of the impact of delayed cancer care caused by the COVID-19 pandemic in Belgium which can be used by researchers to respond to diverse research questions in a variety of disruptive events, contexts and settings.

methodsA decision-analytic Markov model was developed for 4 selected cancer types (i.e. breast, colorectal, lung, and head and neck), comparing the estimated costs and quality-adjusted life year losses between the pre-COVID-19 situation and the COVID-19 pandemic in Belgium. Input parameters were derived from published studies (transition probabilities, utilities and indirect costs) and administrative databases (epidemiological data and direct medical costs). One-way and probabilistic sensitivity analyses are proposed to consider uncertainty in the input parameters and to assess the robustness of the model's results. Scenario analyses are suggested to evaluate methodological and structural assumptions. DISCUSSION: The results that such decision-analytic Markov model can provide are of interest to decision makers because they help them to effectively allocate resources to improve the health outcomes of cancer patients and to reduce the costs of care for both patients and healthcare systems. Our study provides insights into methodological aspects of conducting a health economic evaluation of cancer care and COVID-19 including insights on cancer type selection, the elaboration of a Markov model, data inputs and analysis.

Indexed as

COVID-19NeoplasmsBelgiumCost-Benefit AnalysisDelivery of Health CareHumansMarkov ChainsModels, EconomicPandemicsQuality-Adjusted Life Years

Identifiers

PMID37903130
PMCPMC10615261
OpenAlexW4388019658

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.