What is the optimal management of potentially resectable stage III-N2 NSCLC? Results of a fixed effects network meta-analysis and economic modelling

Matthew Evison*, Ross Maconachie, Toby Mercer, Caitlin H Daly, Nicky J Welton, Shahzeena Aslam, Doug West, Neal Navani

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)

Abstract

Introduction: There is a critical need to understand the optimal treatment regimen in patients with potentially resectable stage III-N2 non-small cell lung cancer (NSCLC).

Methods: A systematic review of randomised controlled trials using a literature search including the CDSR, CENTRAL, DARE, HTA, EMBASE and MEDLINE bibliographic databases. Selected trials were used to perform a Bayesian fixed effects network meta-analysis and economic modelling of treatment regimens relevant to current day treatment options: chemotherapy plus surgery (CS), chemotherapy plus radiotherapy (CR) and chemoradiotherapy followed by surgery (CRS).

Findings: Six trials were prioritised for evidence synthesis. The fixed effects network meta-analyses demonstrated an improvement in Disease-Free Survival (DFS) for CRS vs CS and CRS vs CR of 0.34 years (95% CI 0.02-0.65) and 0.32 years (95% CI 0.05-0.58) respectively, over a five-year period. No evidence of effect were observed in overall survival although point estimates favoured CRS. The probabilities that CRS had a greater average survival time and greater probability of being alive than the reference treatment of CR 5 years were 89% and 86% respectively. Survival outcomes for CR and CS were essentially equivalent. The economic model calculated that CRS and CS had ICERs of £19,000/QALY and £78,000/QALY compared to CR. The probability that CRS generated more QALYs than CR and CS was 94%.

Interpretation: CRS provides an extended time in a disease-free state leading to improved cost-effectiveness over CR and CS in potentially resectable stage III-N2 NSCLC
Original languageEnglish
Article number00299-2022
Number of pages11
JournalERJ Open Research
Volume9
Issue number2
Early online date3 Apr 2023
DOIs
Publication statusE-pub ahead of print - 3 Apr 2023

Bibliographical note

Funding Information:
Conflicts of interest: R. Maconachie currently works as Associate Director, Value, Access and Devolved Nations, Merck, Sharp and Dohme (UK) Ltd (MSD). During the time of this work, his role was Technical Adviser, Centre for Guidelines, National Institute for Health and Care Excellence (NICE). MSD market treatments for lung cancer but this work was completed entirely while in employment with NICE and there are no obvious conflicts of interest related to MSD’s activities. NICE funds the technical support unit at the University of Bristol which supported C.H. Daly and N.J Welton for the work on this manuscript. N. Navani is supported by a Medical Research Council Academic Research Partnership (MR/T02481X/1). This work was partly undertaken at The University College London Hospitals/University College London that received a proportion of funding from the Department of Health’s National Institute for Health Research (NIHR) Biomedical Research Centre’s funding scheme. N. Navani reports honoraria for non-promotional educational talks or advisory boards from Amgen, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Guardant, Janssen, Lilly, Merck Sharp & Dohme, OIympus, OncLive, PeerVoice, Pfizer and Takeda. M. Evison reports honoraria for non-promotional educational talks or advisory boards from AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Lilly, Merck Sharp & Dohme and Pfizer. N.J Welton has received honoraria for delivering masterclasses/workshops/courses on behalf of Association of the British Pharmaceutical Industry (ABPI), Takeda, Cochrane Ireland, NICE International and NICE Scientific Advice, and Centre for Global Development, all outside the submitted work. The remaining authors have nothing to disclose.

Publisher Copyright:
© The authors 2023.

Research Groups and Themes

  • Multi-parameter Evidence Synthesis Research
  • BrisTAG

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