{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T05:17:05Z","timestamp":1788239825437,"version":"build-2803163510"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Pulmonary nodules are frequently detected during routine health-examination chest computed tomography (CT). From a systems-endocrinology perspective, routinely available indices integrating adiposity distribution, lipid metabolism, immune-cell balance, and low-grade inflammation may characterize cross-organ metabolic-inflammatory phenotypes, but their associations with CT-detected pulmonary nodules remain uncertain.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This hospital-based cross-sectional study included 1,072 adults undergoing routine health examinations at the Second Affiliated Hospital of Shandong First Medical University from 2024 to 2025. The primary outcome was any CT-detected pulmonary nodule; the secondary outcome was an institutional Lung-RADS category \u22653. Right-skewed indices were natural-log transformed before standardization. We applied multivariable logistic regression, Benjamini-Hochberg false-discovery-rate (FDR) correction, a reduced non-redundant representative-index model, restricted cubic splines, repeated nested cross-validation, and machine-learning models with SHAP explanations computed only for held-out observations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>CT-detected pulmonary nodules were present in 381 participants (35.54%), and 109 participants (10.17%) had Lung-RADS category \u22653. In the mutually adjusted representative-index model, AIP (OR, 1.38; 95% CI, 1.16-1.64; q = 0.003) and SIRI (OR, 1.37; 95% CI, 1.14-1.64; q = 0.004) were associated with any pulmonary nodule. For the exploratory secondary Lung-RADS category \u22653 outcome (109 events; 6.41 events per model parameter), SIRI was associated with Lung-RADS category \u22653 (OR, 1.48; 95% CI, 1.15-1.91; q = 0.008), but this low-EPV estimate should be interpreted cautiously. In exploratory single-index analyses, several lipid-adiposity and monocyte-related indices remained significant after FDR correction. The basic risk model achieved a cross-validated AUC of 0.76; the derived-index model achieved an AUC of 0.77, without a statistically significant AUC increment (difference, 0.01; P\u00a0=\u00a00.100).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AIP and SIRI were independently associated with CT-detected pulmonary nodules. An exploratory association between SIRI and Lung-RADS category \u22653 was also observed; however, the limited number of events and EPV of 6.41 require cautious interpretation and independent validation. These cross-sectional findings describe an exploratory metabolic-inflammatory phenotype rather than a causal mechanism or clinically ready diagnostic tool. Multicenter longitudinal validation with standardized radiological characterization is required.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1922394","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T04:27:33Z","timestamp":1788236853000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Associations of derived inflammatory, lipid, and anthropometric indices with CT-detected pulmonary nodules: a hospital-based cross-sectional study with explainable machine learning"],"prefix":"10.3389","volume":"17","author":[{"given":"Mengmeng","family":"Wang","sequence":"first","affiliation":[{"name":"Xiyuan Hospital, China Academy of Chinese Medical Sciences","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanyan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Xiyuan Hospital, China Academy of Chinese Medical 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