Oswald NK, Halle-Smith J, Mehdi R, Nightingale P, Naidu B, Turner AM. Predicting Postoperative Lung Function Following Lung Cancer Resection: A Systematic Review and Meta-analysis.
EClinicalMedicine 2019;
15:7-13. [PMID:
31709409 PMCID:
PMC6833443 DOI:
10.1016/j.eclinm.2019.08.015]
[Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 07/19/2019] [Accepted: 08/21/2019] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND
Lung resection remains the gold standard treatment for early stage lung cancer; prediction of postoperative lung function is a key selection criterion for surgery with the aim of determining risk of postoperative dyspnoea. We aimed to identify the different prediction techniques used, and compare their accuracy.
METHODS
A systematic review and meta-analysis sought to synthesise studies conducted that assess prediction of postoperative lung function up to 18/02/2018 (n = 135). PROBAST was used to assess risk of bias in studies, 17 studies were judged to be at low risk of bias.
FINDINGS
Meta-analysis revealed CT volume and density measurement to be the most accurate (mean difference 71 ml) and precise (standard deviation 207 ml) of the reported techniques used for predicting FEV1; evidence for predicting gas transfer was lacking.
INTERPRETATION
The evidence suggests using CT volume and density is the preferred technique in the prediction of postoperative FEV1. Further studies are required to ensure that the methods and thresholds we propose are linked to patient reported outcomes.
FUNDING
Salary support for NKO, RM, PN, BN, and AMT was provided by University Hospitals Birmingham NHS Foundation Trust.
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