Authors' objectives: National Institute for Health and Care Excellence technology appraisals assess the effectiveness and cost-effectiveness of medicines at a single point in the treatment pathway. However, for some disease areas, such as non-small cell lung cancer, there are many recommendations, making it difficult to use National Institute for Health and Care Excellence guidance. The treatment pathway for metastatic stage 4 non-small cell lung cancer can be divided into decision points (nodes) based on histology (squamous or non-squamous), programmed death-ligand 1 expression, presence of tumour mutations and line of therapy. The National Institute for Health and Care Excellence commissioned this pilot to assess the potential of taking a ‘pathways approach’ to technology appraisals. The aim was to build a single disease-specific cost-effectiveness model for metastatic stage 4 non-small cell lung cancer patients not eligible for targeted therapies at first line, that can be updated with economic and clinical data as required. The National Institute for Health and Care Excellence helps doctors provide the best care to patients by deciding if new or existing medicines make a difference to patients. These decisions are made using an ‘economic model’, which helps the National Institute for Health and Care Excellence work out if treatments can help patients and are value for money for the NHS. National Institute for Health and Care Excellence technology appraisals (NICE TAs) assess the effectiveness and cost-effectiveness of medicines at a single point in the treatment pathway. However, for some disease areas, this leads to a high number of NICE recommendations, each based on a different model, making it difficult for stakeholders, including patients and clinicians, who need to understand and use NICE guidance. The ‘pathways approach’ can potentially deliver efficiencies by developing a single disease-specific model, with economic and clinical data updated as required. NICE commissioned this pilot to assess the potential of the pathways approach for non-small cell lung cancer (NSCLC) appraisals, selected as there are currently more than 50 NICE recommendations, and more technologies are scheduled for appraisal in the future. Lung cancer is the third most common cancer in the UK, and accounts for around one in five of all cancer deaths. The majority (90%) of lung cancers are NSCLC, and approximately 70% of NSCLC is non-squamous cell carcinoma (mostly adenocarcinoma) and the remainder squamous cell carcinoma. Over half of all cases of lung cancer are not diagnosed until the lung cancer is at an advanced stage, where the tumour has spread either locally (stage 3b) or to the other lung or a distant part of the body (metastatic stage 4). Additionally, NSCLC is classified according to programmed death-ligand 1 (PD-L1) expression which helps determine whether a patient is more likely to respond to immunotherapy treatment. The treatment pathway for advanced metastatic stage 4 NSCLC can be divided into interconnected decision points (nodes) based on histology (squamous or non-squamous), PD-L1 expression, presence of specific tumour mutations and line of therapy after diagnosis of stage 4 disease. This project aims to build a cost-effectiveness model to enable assessment of clinical and cost-effectiveness of multiple treatments at each node in the treatment pathway for patients who are not eligible for targeted therapies at first line after diagnosis of metastatic (stage 4) NSCLC. The objectives for this project were to: Develop a cost-effectiveness model encompassing each decision node in the disease pathway for metastatic stage 4 NSCLC patients not eligible for first-line targeted therapies. Conduct systematic reviews and evidence syntheses to provide estimates of clinical effectiveness of treatment options at each decision node in the pathway to inform the cost-effectiveness model. Explore the value in using observational (real-world) evidence to characterise the treatment pathway, natural history of the condition, and patient characteristics.

Authors' results and conclusions: We included 15 randomised controlled trials and 1 single-arm study in the review, judged as some concerns or low risk of bias. Immunotherapies, in combination with doublet platinum chemotherapy, were most effective first-line treatments, although with higher adverse event rates. Immunotherapy monotherapies were most effective at second line, unless patients were suitable for targeted therapies. Sequences for non-squamous non-small cell lung cancer, programmed death-ligand 1

Authors' methods: We conducted a systematic review (searches last updated 11 July 2025) and network meta-analysis of treatment efficacy and safety at each decision node in the pathway. We used flexible fractional polynomial models for primary outcome progression-free survival, required for a model of treatment sequences. We built a novel cost-effectiveness model that compared sequences of treatments, and was populated using network meta-analyses for progression-free survival, data on overall survival after last-line therapy, evidence on treatment sequences from an analysis of systemic anticancer therapy data, and quality of life, cost and resource use estimates from previous technology appraisals. Drug list prices were used, but confidential discounts are available. Clinical effectiveness review We conducted a systematic review to identify studies of effectiveness of treatments at each decision point (node) in the pathway for metastatic stage 4 NSCLC patients not eligible for targeted therapies at first line. We identified studies from existing NICE TAs and searched three databases and two trial registries for additional trials (searches last updated 11 July 2025). Two reviewers independently screened the title and abstract of studies returned by the searches. We applied a three-stage approach to assessing papers for inclusion. We first assessed inclusion at the review level based on intervention and general population. We then assessed those included at the first stage for node-specific inclusion criteria. Where necessary, we ran additional node-specific searches to identify studies to connect the evidence network for each node. We assessed risk of bias using the Risk of Bias 2 (RoB 2) tool. One reviewer performed the inclusion assessment, data extraction, and risk of bias assessment and a second checked them. We provided a narrative summary of study details, risk of bias and results for each node and each outcome. We produced forest plots to show individual and summary effect estimates with 95% confidence intervals (CIs).

Project Status: Completed

URL for project: https://www.journalslibrary.nihr.ac.uk/programmes/hta/NIHR136097

Year Published: 2026

URL for published report: https://www.journalslibrary.nihr.ac.uk/hta/GJNW3422

URL for additional information: English

English language abstract: An English language summary is available

Publication Type: Full HTA

Country: England, United Kingdom

DOI: 10.3310/GJNW3422

Organisation Name: NIHR Health Technology Assessment programme

Contact Address: NIHR Journals Library, National Institute for Health and Care Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK

Contact Name: journals.library@nihr.ac.uk

Contact Email: journals.library@nihr.ac.uk