Exploratory cost-effectiveness model of electromagnetic navigation bronchoscopy (ENB) compared with CT-guided biopsy (TTNA) for diagnosis of malignant indeterminate peripheral pulmonary nodules.


Journal

BMJ open respiratory research
ISSN: 2052-4439
Titre abrégé: BMJ Open Respir Res
Pays: England
ID NLM: 101638061

Informations de publication

Date de publication:
08 2020
Historique:
received: 26 03 2020
revised: 04 06 2020
accepted: 26 06 2020
entrez: 16 8 2020
pubmed: 17 8 2020
medline: 11 6 2021
Statut: ppublish

Résumé

Lung cancer is accountable for 35 000 deaths annually, and prognosis is improved when the cancer is diagnosed early. CT-guided biopsy (transthoracic needle aspiration, TTNA) and electromagnetic navigation bronchoscopy (ENB) can be used to investigate indeterminate pulmonary nodules if the patient is unfit for surgery. However, there is a paucity of clinical and health economic evidence that directly compares ENB with TTNA in this population group. This cost-effectiveness study aimed to explore potential scenarios whereby ENB may be considered cost-effective when compared with TTNA. A cohort decision analytic model was developed using a UK National Health Service perspective. ENB was assumed to have equal sensitivity to TTNA at 82%. Lifetime costs and quality-adjusted life-year (QALY) gain were calculated to estimate the net monetary benefit at a £20 000 per QALY threshold. Sensitivity analyses were used to explore scenarios where ENB could be considered a cost-effective intervention. Under the assumption that ENB has equal efficacy to TTNA, ENB was found to be dominant (less costly and more effective) when compared with TTNA, due to having a reduced risk and cost of adverse events. This conclusion was most sensitive to changes in the cost of intervention, estimates of effectiveness and adverse event rates. ENB is expected to be cost-effective when the likelihood of an accurate diagnosis is equal to (or better than) TTNA, which may occur in certain subgroups of patients in whom TTNA is unlikely to accurately diagnose malignancy or when an experienced practitioner achieves a high accuracy with ENB.

Identifiants

pubmed: 32796019
pii: 7/1/e000595
doi: 10.1136/bmjresp-2020-000595
pmc: PMC7430329
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Commentaires et corrections

Type : ErratumIn

Informations de copyright

© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: VP and SM are employees of York Health Economics Consortium who were commissioned by Medtronic to provide consultancy, develop the economic model and write the manuscript. CL and PM are employees of Medtronic.

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Auteurs

William Rickets (W)

Barts Thorax Centre, Barts Health NHS Trust, London, London, UK.

Kelvin Kar Wing Lau (KKW)

Barts Thorax Centre, Barts Health NHS Trust, London, London, UK.

Vicki Pollit (V)

York Health Economics Consortium, Heslington, North Yorkshire, UK.

Stuart Mealing (S)

York Health Economics Consortium, Heslington, North Yorkshire, UK stuart.mealing@york.ac.uk.

Catherine Leonard (C)

Medtronic United Kingdom, Watford, Hertfordshire, UK.

Philip Mallender (P)

Medtronic United Kingdom, Watford, Hertfordshire, UK.

Nilanjan Chaudhuri (N)

Leeds Teaching Hospitals NHS Trust, Leeds, Leeds, UK.

Pallav L Shah (PL)

NIHR Respiratory Biomedical Research Unit, Royal Brompton and Harefield NHS Foundation Trust and Imperial College, London, UK.

Umamamaheswar Babu Naidu (UB)

Queen Elizabeth Hospital Birmingham, Birmingham, Birmingham, UK.

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Classifications MeSH