Evidence map›Paper›PMID 42246395›Full record

SynthesisHealth technology assessment (Winchester, England)2026

Treatments for metastatic non-small cell lung cancer: a pathways pilot with systematic review, evidence synthesis and economic model.

Hugo Pedder, Catalina Lopez Manzano, Lindsay Claxton, Penny Whiting, Lucy Beggs, Ayman Sadek, Kusal Lokuge, Eve Tomlinson, Chris Cooper, Rachel James and 10 more

Abstract readSystematic ReviewNetwork Meta-Analysis
In one paragraph

Synthesis in Health technology assessment (Winchester, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Hugo PedderBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0000-0002-7813-3749
Catalina Lopez ManzanoBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0009-0009-8883-0167
Lindsay ClaxtonNICE Science, Evidence and Analytics Directorate, Manchester, UK.ORCID 0000-0002-1795-7568
Penny WhitingBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0000-0003-1138-5682
Lucy BeggsNICE Science, Evidence and Analytics Directorate, Manchester, UK.ORCID 0000-0002-0574-6325
Ayman SadekBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0009-0000-6565-0790
Kusal LokugeNICE Science, Evidence and Analytics Directorate, Manchester, UK.ORCID 0009-0007-7214-4563
Eve TomlinsonBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0000-0002-0969-602X
Chris CooperBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0000-0003-0864-5607
Rachel JamesBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0000-0001-9299-9461
Yuanyuan ZhangNICE Science, Evidence and Analytics Directorate, Manchester, UK.ORCID 0009-0001-6578-8455
Robert WillansNICE Science, Evidence and Analytics Directorate, Manchester, UK.ORCID 0000-0002-3461-9691
Laura WebsterNational Cancer Registration and Analysis Service (NCRAS), Public Health England, Didcot, UK.ORCID 0000-0002-4307-9631
Joe CarrollBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0009-0004-7006-0938
David PhillippoBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0000-0003-2672-7841
David WonderlingNICE Science, Evidence and Analytics Directorate, Manchester, UK.ORCID 0009-0007-6760-6946
Adam DangoorBristol Cancer Institute, Bristol Haematology and Oncology Centre, Bristol, UK.ORCID 0000-0003-3533-6842
Dharmisha ChauhanNorth Thames Genomic Medicine Service Alliance, Great Ormond Street Hospital, London, UK.ORCID 0009-0002-1781-4011
Stella O'BrienPatient Representative, UK.ORCID 0000-0002-0210-7069
Nicky J WeltonBristol Technology Assessment Group (TAG), Bristol Medical School, Bristol, UK.ORCID 0000-0003-2198-3205

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: 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. 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. Results: 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 starting with atezolizumab + bevacizumab + doublet platinum chemotherapy had similar costs and quality-adjusted life-years to sequences starting with pembrolizumab + doublet platinum chemotherapy. Sequences starting with pemetrexed + platinum chemotherapy had the lowest costs but also the lowest total quality-adjusted life-years. Sequences for non-squamous non-small cell lung cancer, programmed death-ligand 1 ≥ 50%: Sequences starting with pembrolizumab + doublet platinum chemotherapy had highest quality-adjusted life-years, but higher costs compared to other sequences. Sequences starting with pemetrexed + platinum chemotherapy had the lowest cost and the lowest number of quality-adjusted life-years. Sequences for squamous non-small cell lung cancer, programmed death-ligand 1 < 50%: Sequences starting with pembrolizumab + doublet platinum chemotherapy had higher quality-adjusted life-years and higher costs than sequences starting with platinum chemotherapy. Sequences for squamous non-small cell lung cancer, programmed death-ligand 1 ≥ 50%: Sequences starting with atezolizumab had the highest predicted quality-adjusted life-year gains, slightly higher than for sequences starting with pembrolizumab. Sequences starting with platinum chemotherapy had the lowest quality-adjusted life-years, but the lowest total costs. Patients in the systemic anticancer therapy analysis had a shorter time on treatment than those in trials, resulting in lower treatment costs and causing the immunotherapy sequences to appear more cost effective. Conclusions: Our model can be used to estimate either the most cost-effective sequence of treatments or the most cost-effective treatment at a given point in the pathway, although our results are based on drug list prices and these would need to be updated to draw conclusions about the relative cost-effectiveness of different treatment sequences. We were able to use real-world data from systemic anticancer therapy to estimate model parameters and sequences that reflect clinical practice. Our model can readily be updated and used as a reference model for metastatic non-small cell lung cancer. Study registration: The study is registered as PROSPERO CRD42023470119. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR136097) and is published in full in

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsAntineoplastic AgentsCost-Benefit AnalysisCost-Effectiveness AnalysisHumansModels, EconomicNeoplasm MetastasisPilot ProjectsQuality-Adjusted Life YearsTechnology Assessment, BiomedicalAntineoplastic AgentsECONOMIC MODELEVIDENCE SYNTHESISNON-SMALL-CELL LUNG CANCERREGISTRY DATA ANALYSISSYSTEMATIC REVIEWTREATMENT PATHWAYS MODEL

Identifiers

PMID42246395
PMCPMC13266499

What OpenQuestion holds

Textmetadata
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.