SynthesisBMJ open2026
Clinical similarity in cost-comparison evaluations: a systematic review of current methods in NICE appraisals and the development of a framework for the formal assessment of clinical similarity.
Synthesis in BMJ open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo review how statistically non-significant indirect treatment comparison (ITC) results are interpreted within National Institute for Health and Care Excellence (NICE) cost-comparison evaluations (CCEs) and develop a framework to support interpretations of these results from Bayesian network meta-analyses (NMAs).
designA systematic review of CCEs between 2017 (first introduced) and April 2025. A framework (point-and-density plots) was developed to better interpret statistically non-significant NMA results for CCEs. DATA SOURCES: CCEs were identified through NICE website searches, references of similar reviews and communications with NICE. ELIGIBILITY CRITERIA: NICE technology appraisals (from 2017) that followed a CCE approach ab initio, had final guidance available and used non-statistically significant ITC results were included. DATA EXTRACTION AND SYNTHESIS: A single reviewer performed screening and data extraction with validation by a second reviewer. Narrative syntheses were performed separately for company, External Assessment Group (EAG) and committee perspectives. Point-and-density plots combine elements of forest plots and density plots alongside reporting the probability that a treatment is non-inferior relative to a comparator. These were applied to a recent CCE (TA1019) for crovalimab for patients with paroxysmal nocturnal haemoglobinuria.
resultsAmong 41 CCEs, EAGs raised concerns about statistically non-significant ITC results while companies relied heavily on them. Only ∼32% of CCEs applied formal methods to explore ITC result uncertainty.For the example framework analysis, comparisons of crovalimab to eculizumab (mean difference (MD): 0.018; 95% CIs -0.22 to 0.25) and ravulizumab (MD: 0.079; 95% CIs -0.25 to 0.41) were statistically non-significant, with non-inferiority not demonstrated. However, point-and-density plots indicated a 95.9% and 86.3% probability of non-inferiority of crovalimab versus eculizumab and ravulizumab.
conclusionsInterpretations of statistically non-significant ITC results are inconsistent within individual CCEs and across appraisals. Implementation of the presented recommendations and framework would improve the consistency and robustness of CCEs. PROSPERO REGISTRATION NUMBER: CRD420251034143.
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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 Socratic graph.