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However, NSCLC heterogeneity leads to differences in efficacy; thus, potential biomarkers need to be explored to predict the prognosis of patients. Recently, the prognostic importance of pre-treatment malnutrition and systemic inflammatory response in cancer patients has received increasing attention.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this study, clinical information from 363 NSCLC patients receiving EGFR-TKI treatment at our clinical center was used for analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      High nutritional risk index (NRI) and systemic inflammation response index (SIRI) were significantly associated with poor overall survival (OS) and progression-free survival (PFS) in NSCLC patients (\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&lt;\u20090.05). Importantly, NRI and SIRI were the best combination models for predicting clinical outcomes of NSCLC patients and independent OS and PFS predictors. Moreover, a nomogram model was constructed by combining NRI\/SIRI, sex, smoking history,\n                      <jats:italic>EGFR<\/jats:italic>\n                      mutation, TNM stage, and surgery treatment to visually and personally predict the 1-, 2-, 3-, 4-, and 5-year OS of patients with NSCLC. Notably, risk stratification based on the nomogram model was better than that based on the TNM stage.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>NRI and SIRI were the best combination models for predicting clinical outcomes of NSCLC patients receiving EGFR-TKI treatment, which may be a novel biomarker for supplement risk stratification in NSCLC patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s12094-024-03735-7","type":"journal-article","created":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T15:01:39Z","timestamp":1726844499000},"page":"1529-1538","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["NRI and SIRI are the optimal combinations for prognostic risk stratification in patients with non-small cell lung cancer after EGFR-TKI therapy"],"prefix":"10.1007","volume":"27","author":[{"given":"Xia","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7201-4928","authenticated-orcid":false,"given":"Peipei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guolong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,9,20]]},"reference":[{"issue":"1","key":"3735_CR1","doi-asserted-by":"publisher","first-page":"12","DOI":"10.3322\/caac.21820","volume":"74","author":"RL Siegel","year":"2024","unstructured":"Siegel RL, Giaquinto AN, Jemal A. 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