{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T12:15:11Z","timestamp":1788437711462,"version":"build-2803163510"},"reference-count":30,"publisher":"IMR Press","issue":"8","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hunan Province Clinical Medical Technology Innovation Guidance Project","award":["2020SK50904"],"award-info":[{"award-number":["2020SK50904"]}]},{"name":"Innovation Platform and Talent Plan Project of Hunan Provincial Department of Science and Technology","award":["2023SK4056"],"award-info":[{"award-number":["2023SK4056"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Br. J. Hosp. Med. (Lond)"],"abstract":"<jats:p>Aims\/Background: Post-chemotherapy infection is a major cause of treatment failure in lung cancer (LC) patients undergoing neoadjuvant chemotherapy (NAC). This study aimed to identify risk factors for post-NAC infection using the Least Absolute Shrinkage and Selection Operator (LASSO) regression and to develop and validate a corresponding risk prediction model. Methods: Clinical data from 144 LC patients who underwent NAC at Hunan Provincial People's Hospital between January 2021 and December 2024 were retrospectively analysed. Patients were stratified into a non-infection group (n = 81) and an infection group (n = 63) based on the occurrence of infection. LASSO-logistic regression was used to identify risk factors for post-chemotherapy infection. A risk prediction nomogram was subsequently constructed and validated based on these factors. Results: The optimal LASSO model was selected at lambda.1se (\u03bb = 0.074), which retained 9 of the 15 candidate predictors. Eastern Cooperative Oncology Group Performance Status (ECOG-PS) \u22652, recent invasive procedures\/catheterization, and Nutritional Risk Screening 2002 (NRS-2002) score \u22653 were identified as significant risk factors for post-chemotherapy infection, while a high cluster of differentiation 4-positive (CD4+) count served as a protective factor (p &lt; 0.05). A nomogram incorporating these variables was subsequently developed. Internal validation using the bootstrap method (1000 iterations) demonstrated a good predictive performance with an area under the curve (AUC) of 0.831 (95% confidence interval [CI]: 0.761\u20130.901, p &lt; 0.001), sensitivity of 76.2%, and specificity of 79.0% at the optimal cutoff. The calibration curve demonstrated good agreement between predicted and observed outcomes. Decision curve analysis (DCA) confirmed the clinical utility of the nomogram by showing a positive net benefit across a wide range of threshold probabilities. Conclusion: The LASSO-derived nomogram integrates key variables (ECOG-PS \u22652, invasive procedures\/catheterization, NRS-2002 score \u22653, and CD4+ level) to enable individualised prediction of post-NAC infection risk in LC patients. Targeted interventions addressing these risk factors, together with maintenance of protective factors, may help reduce infection rates and improve treatment outcomes, providing a scientific basis for infection prevention and management.<\/jats:p>","DOI":"10.31083\/bjhm57260","type":"journal-article","created":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T11:29:22Z","timestamp":1788434962000},"source":"Crossref","is-referenced-by-count":0,"title":["Development of a LASSO Regression-Based Nomogram to Predict Post-Neoadjuvant Chemotherapy Infection Risk in Lung Cancer Patients"],"prefix":"10.31083","volume":"87","author":[{"given":"Lijie","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Hunan Provincial People\u2019s Hospital, The First Affiliated Hospital of Hunan Normal University, 410005 Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuejia","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Hunan Provincial People\u2019s Hospital, The First Affiliated Hospital of Hunan Normal University, 410005 Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juanli","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Hunan Provincial People\u2019s Hospital, The First Affiliated Hospital of Hunan Normal University, 410005 Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Hunan Provincial People\u2019s Hospital, The First Affiliated Hospital of Hunan Normal University, 410005 Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiangchuan","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Hunan Provincial People\u2019s Hospital, The First Affiliated Hospital of Hunan Normal University, 410005 Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3921-1959","authenticated-orcid":true,"given":"Jianmin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Hunan Provincial People\u2019s Hospital, The First Affiliated Hospital of Hunan Normal University, 410005 Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huan","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Hunan Provincial People\u2019s Hospital, The First Affiliated Hospital of Hunan Normal University, 410005 Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"16242","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","unstructured":"Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. 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