ReviewDiagnostics (Basel, Switzerland)2026
Biomarkers for Lung Nodule Risk Stratification: Are We There Yet?
Review in Diagnostics (Basel, Switzerland), 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
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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.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The number of pulmonary nodules detected is steadily increasing. While some are low or high risk, most are indeterminate. Within the indeterminate group, the vast majority are benign. Statification of indeterminate pulmonary nodules (IPNs) is challenging. Validated risk calculators are not routinely employed in clinical practice because they are cumbersome. Most clinicians rely upon clinical gestalt. This strategy often results in unnecessary biopsies, which are costly, stressful, and have the potential for iatrogenic injury. There are a number of commercially available lung cancer risk biomarkers, which each have their own strengths and weaknesses. Barriers to widespread adoption include lack of guideline support, clinical practice inertia, and limited clinical utility data. Upcoming multicenter trials aim to provide high quality data that could lead to guideline incorporation.
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Registered trials
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.