Validation of a blood-based autoantibody test to assess lung cancer risk in 4–30 mm pulmonary nodules: a retrospective pooled analysis of four cohort studies

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Authors: Trevor J. Pitcher, Kathryn J. Long, Michael Nolan Kammer, S Schuldheisz, Bharat Bajantri, Tammy Gleeson, Dragos Zanchi, Sandeep Bansal, Luke Yuhico, Laura J. Peek, James R. Jett, Viswam S. Nair
+1 more Gerard A. Silvestri
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Abstract

To validate a blood-based autoantibody test (AAT) as a high specificity, rule-in biomarker for 4–30 mm indeterminate pulmonary nodules (IPN) across malignancy risk. Retrospective pooled analysis of four cohorts including adults with a 4–30 mm IPN, AAT result, and benign or malignant diagnosis. AAT results were classified as Moderate Level (all patients with elevated autoantibodies), High Level (stricter subset within Moderate Level), or No Significant Level of Autoantibodies Detected (NSLAD). Post-test probability of cancer (pCA) was calculated by applying AAT likelihood ratios to pretest pCA. Performance was assessed overall, by nodule size, and risk strata. Among 1164 patients (35% cancer prevalence), Moderate Level results showed sensitivity 16%, specificity 91%, and PPV 50%. A stricter subset of positives at the High Level, specificity 96%, and PPV 57%, with sensitivity 9%. When post-test pCA exceeded 65%, specificity was 97% and PPV 69%, while sensitivity was 12%. Performance was consistent across cohorts, nodule sizes, and risk strata, indicating size- and risk-independent discrimination. ~10% of intermediate-risk cancers (pretest 5–65%) were reclassified above the 65% threshold, creating a group with enriched malignancy risk. AAT provides size- and risk-independent, high-specificity rule-in performance, identifying subsets of patients whose malignancy risk may justify expedited evaluation.

Fields of Study & Subjects

Lung Cancer Diagnosis and Treatment Lung Cancer Research Studies Occupational and environmental lung diseases

Publication details

Journal / source
Figshare
Publication date
18 February 2026
Language
EN
Document type
Dataset