{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T23:52:13Z","timestamp":1791071533443,"version":"4.1.0"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T00:00:00Z","timestamp":1790985600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T00:00:00Z","timestamp":1790985600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100009619","name":"Japan Agency for Medical Research and Development","doi-asserted-by":"publisher","award":["23mk0121257h0001"],"award-info":[{"award-number":["23mk0121257h0001"]}],"id":[{"id":"10.13039\/100009619","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001700","name":"Ministry of Education, Culture, Sports, Science and Technology","doi-asserted-by":"publisher","award":["22KK0118"],"award-info":[{"award-number":["22KK0118"]}],"id":[{"id":"10.13039\/501100001700","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Clin Oncol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Immune checkpoint inhibitors (ICIs) are a standard treatment for advanced non-small cell lung cancer (NSCLC), but clinically practical predictors of immune-related adverse events (irAEs) and treatment continuity remain limited.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective cohort study using two nationwide Japanese administrative claims databases: Medical Data Vision (MDV) and the Japan Medical Data Center (JMDC). Patients with advanced NSCLC treated with ICIs were identified. Those with available thyroid function data were included in analyses of ICI-induced hypothyroidism (MDV, n\u2009=\u20091786; JMDC, n\u2009=\u20091083), and patients receiving first-line ICIs were analyzed for treatment continuity (MDV, n\u2009=\u20091088; JMDC, n\u2009=\u20091007). Machine learning models including Elastic Net were developed and externally validated to predict hypothyroidism. Treatment durability was assessed using time to next treatment or death (TTNT-D).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Elastic Net showed the most consistent performance across cohorts (AUC: 0.72 training, 0.73 validation, 0.71 test). Baseline thyroid-stimulating hormone (TSH) was the strongest predictor of hypothyroidism. Serum albumin consistently emerged as an important predictor across all machine learning models. Higher albumin levels were associated with an increased incidence of hypothyroidism and significantly prolonged TTNT-D (MDV: HR 0.75; JMDC: HR 0.79; both\n                      <jats:italic>p\u2009<\/jats:italic>\n                      &lt;\u20090.05). Patients with albumin \u2265 3.5\u00a0g\/dL had markedly longer median TTNT-D compared with those &lt; 3.0\u00a0g\/dL (MDV: 15.3 vs 6.1\u00a0months; JMDC: 14.8 vs 5.4\u00a0months; both\n                      <jats:italic>p\u2009<\/jats:italic>\n                      &lt;\u20090.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Baseline TSH was the strongest predictor of hypothyroidism, while serum albumin was associated with both hypothyroidism and treatment continuity in patients receiving first-line ICI therapy for NSCLC, suggesting its potential as a practical biomarker for clinical risk stratification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s10147-026-03202-z","type":"journal-article","created":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T10:50:49Z","timestamp":1791024649000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Serum albumin is associated with immune-related hypothyroidism and treatment continuity in non-small cell lung cancer"],"prefix":"10.1007","author":[{"given":"Kenji","family":"Takada","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6558-2246","authenticated-orcid":false,"given":"Maki","family":"Tanioka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshito","family":"Zamami","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shinichi","family":"Toyooka","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yoshinobu","family":"Maeda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,3]]},"reference":[{"issue":"12","key":"3202_CR1","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.1200\/JCO.21.01308","volume":"40","author":"DR Spigel","year":"2022","unstructured":"Spigel DR, Faivre-Finn C, Gray JE et al (2022) Five-year survival outcomes from the PACIFIC trial: durvalumab after chemoradiotherapy in stage III non-small-cell lung cancer. J Clin Oncol 40(12):1301\u20131311","journal-title":"J Clin Oncol"},{"issue":"10308","key":"3202_CR2","doi-asserted-by":"publisher","first-page":"1344","DOI":"10.1016\/S0140-6736(21)02098-5","volume":"398","author":"E Felip","year":"2021","unstructured":"Felip E, Altorki N, Zhou C et al (2021) Adjuvant atezolizumab after adjuvant chemotherapy in resected stage IB-IIIA non-small-cell lung cancer (IMpower010): a randomised, multicentre, open-label, phase 3 trial. Lancet 398(10308):1344\u20131357","journal-title":"Lancet"},{"issue":"21","key":"3202_CR3","doi-asserted-by":"publisher","first-page":"1973","DOI":"10.1056\/NEJMoa2202170","volume":"386","author":"PM Forde","year":"2022","unstructured":"Forde PM, Spicer J, Lu S et al (2022) Neoadjuvant nivolumab plus chemotherapy in resectable lung cancer. N Engl J Med 386(21):1973\u20131985","journal-title":"N Engl J Med"},{"issue":"6","key":"3202_CR4","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1056\/NEJMoa2302983","volume":"389","author":"H Wakelee","year":"2023","unstructured":"Wakelee H, Liberman M, Kato T et al (2023) Perioperative pembrolizumab for early-stage non-small-cell lung cancer. N Engl J Med 389(6):491\u2013503","journal-title":"N Engl J Med"},{"issue":"10212","key":"3202_CR5","doi-asserted-by":"publisher","first-page":"1929","DOI":"10.1016\/S0140-6736(19)32222-6","volume":"394","author":"L Paz-Ares","year":"2019","unstructured":"Paz-Ares L, Dvorkin M, Chen Y et al (2019) Durvalumab plus platinum-etoposide versus platinum-etoposide in first-line treatment of extensive-stage small-cell lung cancer (CASPIAN): a randomised, controlled, open-label, phase 3 trial. Lancet 394(10212):1929\u20131939","journal-title":"Lancet"},{"issue":"6","key":"3202_CR6","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1200\/JCO.20.01055","volume":"39","author":"SV Liu","year":"2021","unstructured":"Liu SV, Reck M, Mansfield AS et al (2021) Updated overall survival and PD-L1 subgroup analysis of patients with extensive-stage small-cell lung cancer treated with atezolizumab, carboplatin, and etoposide (IMpower133). J Clin Oncol 39(6):619\u2013630","journal-title":"J Clin Oncol"},{"issue":"4","key":"3202_CR7","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1007\/s11523-024-01063-y","volume":"19","author":"Y Kagawa","year":"2024","unstructured":"Kagawa Y, Wang C, Piao Y et al (2024) Real-world evidence of FOLFIRI combined with anti-angiogenesis inhibitors or anti-EGFR antibodies for patients with early recurrence colorectal cancer after adjuvant FOLFOX\/CAPOX therapy: a Japanese claims database study. Target Oncol 19(4):575\u2013585","journal-title":"Target Oncol"},{"issue":"2","key":"3202_CR8","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1007\/s10549-022-06816-9","volume":"197","author":"M Kawai","year":"2023","unstructured":"Kawai M, Takada M, Nakayama T et al (2023) Patient characteristics, treatment patterns, and outcomes of hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer patients prescribed cyclin-dependent kinase 4 and 6 inhibitors: large-scale data analysis using a Japanese claims database. Breast Cancer Res Treat 197(2):435\u2013447","journal-title":"Breast Cancer Res Treat"},{"issue":"4","key":"3202_CR9","doi-asserted-by":"publisher","DOI":"10.3390\/biom15040589","volume":"15","author":"M Saleem","year":"2025","unstructured":"Saleem M, Watson AE, Anwaar A et al (2025) Optimizing immunotherapy: the synergy of immune checkpoint inhibitors with artificial intelligence in melanoma treatment. Biomolecules 15(4):589","journal-title":"Biomolecules"},{"issue":"8","key":"3202_CR10","doi-asserted-by":"publisher","first-page":"1158","DOI":"10.1038\/s43018-024-00772-7","volume":"5","author":"TG Chang","year":"2024","unstructured":"Chang TG, Cao Y, Sfreddo HJ et al (2024) LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical, pathologic and genomic features. Nat Cancer 5(8):1158\u20131175","journal-title":"Nat Cancer"},{"issue":"36","key":"3202_CR11","doi-asserted-by":"publisher","first-page":"4073","DOI":"10.1200\/JCO.21.01440","volume":"39","author":"BJ Schneider","year":"2021","unstructured":"Schneider BJ, Naidoo J, Santomasso BD et al (2021) Management of immune-related adverse events in patients treated with immune checkpoint inhibitor therapy: ASCO guideline update. J Clin Oncol 39(36):4073\u20134126","journal-title":"J Clin Oncol"},{"issue":"3","key":"3202_CR12","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1001\/jamaoncol.2017.2925","volume":"4","author":"K Haratani","year":"2018","unstructured":"Haratani K, Hayashi H, Chiba Y et al (2018) Association of immune-related adverse events with nivolumab efficacy in non-small-cell lung cancer. JAMA Oncol 4(3):374\u2013378","journal-title":"JAMA Oncol"},{"issue":"12","key":"3202_CR13","doi-asserted-by":"publisher","first-page":"1952","DOI":"10.1001\/jamaoncol.2020.5012","volume":"6","author":"B Shankar","year":"2020","unstructured":"Shankar B, Zhang J, Naqash AR et al (2020) Multisystem immune-related adverse events associated with immune checkpoint inhibitors for treatment of non-small cell lung cancer. JAMA Oncol 6(12):1952\u20131956","journal-title":"JAMA Oncol"},{"issue":"8","key":"3202_CR14","doi-asserted-by":"publisher","first-page":"1795","DOI":"10.1007\/s00262-021-03128-7","volume":"71","author":"YM Cheung","year":"2022","unstructured":"Cheung YM, Wang W, McGregor B et al (2022) Associations between immune-related thyroid dysfunction and efficacy of immune checkpoint inhibitors: a systematic review and meta-analysis. Cancer Immunol Immunother 71(8):1795\u20131812","journal-title":"Cancer Immunol Immunother"},{"key":"3202_CR15","doi-asserted-by":"publisher","first-page":"1039121","DOI":"10.3389\/fmolb.2022.1039121","volume":"9","author":"DC Guven","year":"2022","unstructured":"Guven DC, Sahin TK, Erul E et al (2022) The association between albumin levels and survival in patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis. Front Molecul Biosci 9:1039121","journal-title":"Front Molecul Biosci"},{"key":"3202_CR16","doi-asserted-by":"publisher","first-page":"1522368","DOI":"10.3389\/fonc.2025.1522368","volume":"15","author":"T Xie","year":"2025","unstructured":"Xie T, Dong Z, Wu C et al (2025) Association between CONUT scores and survival outcomes in patients with non-small cell lung cancer: meta-analysis from 4973 Asian cases. Front Oncol 15:1522368","journal-title":"Front Oncol"},{"key":"3202_CR17","doi-asserted-by":"publisher","first-page":"1213255","DOI":"10.3389\/fnut.2023.1213255","volume":"10","author":"X Yan","year":"2023","unstructured":"Yan X, Wang J, Mao J et al (2023) Identification of prognostic nutritional index as a reliable prognostic indicator for advanced lung cancer patients receiving immune checkpoint inhibitors. Front Nutr 10:1213255","journal-title":"Front Nutr"},{"issue":"1","key":"3202_CR18","doi-asserted-by":"publisher","first-page":"11244","DOI":"10.1038\/s41598-024-61150-y","volume":"14","author":"LVM Leek","year":"2024","unstructured":"Leek LVM, Notohardjo JCL, de Joode K et al (2024) Multi-omic analysis identifies hypoalbuminemia as independent biomarker of poor outcome upon PD-1 blockade in metastatic melanoma. Sci Rep 14(1):11244","journal-title":"Sci Rep"},{"issue":"6","key":"3202_CR19","doi-asserted-by":"publisher","first-page":"2898","DOI":"10.1002\/jcsm.13367","volume":"14","author":"JH Lee","year":"2023","unstructured":"Lee JH, Kang D, Ahn JS et al (2023) Obesity paradox in patients with non-small cell lung cancer undergoing immune checkpoint inhibitor therapy. J Cachexia Sarcopenia Muscle 14(6):2898\u20132907","journal-title":"J Cachexia Sarcopenia Muscle"},{"issue":"1","key":"3202_CR20","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1038\/s41698-022-00267-7","volume":"6","author":"SK Yoo","year":"2022","unstructured":"Yoo SK, Chowell D, Valero C et al (2022) Pre-treatment serum albumin and mutational burden as biomarkers of response to immune checkpoint blockade. NPJ Precis Oncol 6(1):23","journal-title":"NPJ Precis Oncol"},{"key":"3202_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2023.e17400","author":"H Xia","year":"2023","unstructured":"Xia H, Zhang W, Zheng Q et al (2023) Predictive value of the prognostic nutritional index in advanced non-small cell lung cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis. Heliyon. https:\/\/doi.org\/10.1016\/j.heliyon.2023.e17400","journal-title":"Heliyon"},{"issue":"11","key":"3202_CR22","doi-asserted-by":"publisher","DOI":"10.1002\/cti2.1472","volume":"12","author":"J Saal","year":"2023","unstructured":"Saal J, Ellinger J, Ritter M et al (2023) Pretreatment albumin is a prognostic and predictive biomarker for response to atezolizumab across solid tumors. Clin Transl Immunol 12(11):e1472","journal-title":"Clin Transl Immunol"},{"key":"3202_CR23","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1016\/j.lungcan.2019.08.006","volume":"136","author":"F Shoji","year":"2019","unstructured":"Shoji F, Takeoka H, Kozuma Y et al (2019) Pretreatment prognostic nutritional index as a novel biomarker in non-small cell lung cancer patients treated with immune checkpoint inhibitors. Lung Cancer 136:45\u201351","journal-title":"Lung Cancer"},{"key":"3202_CR24","doi-asserted-by":"publisher","DOI":"10.1136\/jitc-2022-005670","author":"M Zheng","year":"2022","unstructured":"Zheng M (2022) Serum albumin: a pharmacokinetic marker for optimizing treatment outcome of immune checkpoint blockade. J Immunother Cancer. https:\/\/doi.org\/10.1136\/jitc-2022-005670","journal-title":"J Immunother Cancer"},{"key":"3202_CR25","first-page":"15085012","volume":"16","author":"Q Fang","year":"2025","unstructured":"Fang Q, Qian Y, Xie Z et al (2025) Predictors of severity and onset timing of immune-related adverse events in cancer patients receiving immune checkpoint inhibitors: a retrospective analysis. Front Immunol 16:15085012","journal-title":"Front Immunol"},{"issue":"15","key":"3202_CR26","doi-asserted-by":"publisher","DOI":"10.1002\/cam4.70080","volume":"13","author":"R Ozawa","year":"2024","unstructured":"Ozawa R, Sonehara K, Hachiya T et al (2024) Evaluation of the association between predictive factors and the development of immune-related adverse events and prognostic factors for chemoimmunotherapy in patients with non-small cell lung cancer: A multicenter retrospective study. Cancer Med 13(15):e70080","journal-title":"Cancer Med"},{"issue":"9","key":"3202_CR27","doi-asserted-by":"publisher","first-page":"1813","DOI":"10.1007\/s00262-020-02585-w","volume":"69","author":"L Peng","year":"2020","unstructured":"Peng L, Wang Y, Liu F et al (2020) Peripheral blood markers predictive of outcome and immune-related adverse events in advanced non-small cell lung cancer treated with PD-1 inhibitors. Cancer Immunol Immunother 69(9):1813\u20131822","journal-title":"Cancer Immunol Immunother"},{"key":"3202_CR28","doi-asserted-by":"publisher","first-page":"1777","DOI":"10.2147\/JIR.S450804","volume":"17","author":"B Zhang","year":"2024","unstructured":"Zhang B, Chen J, Yu H et al (2024) Prognostic nutritional index predicts efficacy and immune-related adverse events of first-line chemoimmunotherapy in patients with extensive-stage small-cell lung cancer. J Inflamm Res 17:1777\u20131788","journal-title":"J Inflamm Res"},{"key":"3202_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2024.108360","volume":"255","author":"X Cheng","year":"2024","unstructured":"Cheng X, Wu Z, Lin J et al (2024) A two-stage ensemble learning based prediction and grading model for PD-1\/PD-L1 inhibitor-related cardiac adverse events: a multicenter retrospective study. Comput Methods Programs Biomed 255:108360","journal-title":"Comput Methods Programs Biomed"},{"key":"3202_CR30","doi-asserted-by":"publisher","first-page":"1138489","DOI":"10.3389\/fimmu.2023.1138489","volume":"14","author":"L Gong","year":"2023","unstructured":"Gong L, Gong J, Sun X et al (2023) Identification and prediction of immune checkpoint inhibitors-related pneumonitis by machine learning. Front Immunol 14:1138489","journal-title":"Front Immunol"},{"key":"3202_CR31","doi-asserted-by":"publisher","DOI":"10.3390\/ph16081097","author":"W Kim","year":"2023","unstructured":"Kim W, Cho YA, Min KH et al (2023) Machine learning approaches for assessing risk factors of adrenal insufficiency in patients undergoing immune checkpoint inhibitor therapy. Pharmaceuticals (Basel). https:\/\/doi.org\/10.3390\/ph16081097","journal-title":"Pharmaceuticals (Basel)"},{"issue":"19","key":"3202_CR32","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13193065","volume":"13","author":"J McGale","year":"2023","unstructured":"McGale J, Hama J, Yeh R et al (2023) Artificial intelligence and radiomics: clinical applications for patients with advanced melanoma treated with immunotherapy. Diagnostics 13(19):3065","journal-title":"Diagnostics"},{"issue":"2","key":"3202_CR33","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics15020226","volume":"15","author":"SJ Park","year":"2025","unstructured":"Park SJ, Yang S, Lee S et al (2025) Machine-learning parsimonious prediction model for diagnostic screening of severe hematological adverse events in cancer patients treated with PD-1\/PD-L1 inhibitors: retrospective observational study by using the common data model. Diagnostics (Basel) 15(2):226","journal-title":"Diagnostics (Basel)"},{"issue":"10","key":"3202_CR34","doi-asserted-by":"publisher","DOI":"10.1136\/jitc-2021-002545","volume":"9","author":"H Samuel Peter","year":"2021","unstructured":"Samuel Peter H, Reed F, Tomas GN et al (2021) Predicting cardiac adverse events in patients receiving immune checkpoint inhibitors: a machine learning approach. J Immunother Cancer 9(10):e002545","journal-title":"J Immunother Cancer"},{"issue":"6","key":"3202_CR35","doi-asserted-by":"publisher","first-page":"844","DOI":"10.1038\/s43018-023-00572-5","volume":"4","author":"C Sung","year":"2023","unstructured":"Sung C, An J, Lee S et al (2023) Integrative analysis of risk factors for immune-related adverse events of checkpoint blockade therapy in cancer. Nat Cancer 4(6):844\u2013859","journal-title":"Nat Cancer"},{"key":"3202_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2025.106036","volume":"203","author":"Y Wang","year":"2025","unstructured":"Wang Y, Lei J, Jin Z et al (2025) Development and validation of a machine learning-based clinical prediction model for monitoring liver injury in patients with pan-cancer receiving immunotherapy. Int J Med Inform 203:106036","journal-title":"Int J Med Inform"},{"issue":"12","key":"3202_CR37","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics12123157","volume":"12","author":"X Yu","year":"2022","unstructured":"Yu X, Wu R, Ji Y et al (2022) Identifying patients at risk of acute kidney injury among patients receiving immune checkpoint inhibitors: a machine learning approach. Diagnostics (Basel) 12(12):3157","journal-title":"Diagnostics (Basel)"},{"key":"3202_CR38","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.862752","volume":"13","author":"JG Zhou","year":"2022","unstructured":"Zhou JG, Wong AH, Wang H et al (2022) Elucidation of the application of blood test biomarkers to predict immune-related adverse events in atezolizumab-treated NSCLC patients using machine learning methods. Front Immunol 13:862752","journal-title":"Front Immunol"},{"issue":"9","key":"3202_CR39","doi-asserted-by":"publisher","first-page":"e3704","DOI":"10.1210\/clinem\/dgab263","volume":"106","author":"CA Muir","year":"2021","unstructured":"Muir CA, Clifton-Bligh RJ, Long GV et al (2021) Thyroid immune-related adverse events following immune checkpoint inhibitor treatment. J Clin Endocrinol Metab 106(9):e3704\u2013e3713","journal-title":"J Clin Endocrinol Metab"},{"issue":"1","key":"3202_CR40","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/s12020-023-03323-9","volume":"81","author":"L Wu","year":"2023","unstructured":"Wu L, Xu Y, Wang X et al (2023) Thyroid dysfunction after immune checkpoint inhibitor treatment in a single-center Chinese cohort: a retrospective study. Endocrine 81(1):123\u2013133","journal-title":"Endocrine"},{"key":"3202_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.phrs.2023.107048","volume":"199","author":"TT Vu","year":"2024","unstructured":"Vu TT, Kim K, Manna M et al (2024) Decoupling FcRn and tumor contributions to elevated immune checkpoint inhibitor clearance in cancer cachexia. Pharmacol Res 199:107048","journal-title":"Pharmacol Res"},{"issue":"4","key":"3202_CR42","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1016\/j.cllc.2021.12.010","volume":"23","author":"Y Guo","year":"2022","unstructured":"Guo Y, Wei L, Patel SH et al (2022) Serum albumin: early prognostic marker of benefit for immune checkpoint inhibitor monotherapy but not chemoimmunotherapy. Clin Lung Cancer 23(4):345\u2013355","journal-title":"Clin Lung Cancer"},{"key":"3202_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.esmoop.2021.100340","author":"S Branchoux","year":"2022","unstructured":"Branchoux S, Sofeu CL, Gaudin AF et al (2022) Time to next treatment or death as a candidate surrogate endpoint for overall survival in advanced melanoma patients treated with immune checkpoint inhibitors: an insight from the phase III CheckMate 067 trial. ESMO Open. https:\/\/doi.org\/10.1016\/j.esmoop.2021.100340","journal-title":"ESMO Open"}],"container-title":["International Journal of Clinical Oncology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10147-026-03202-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10147-026-03202-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10147-026-03202-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T23:03:11Z","timestamp":1791068591000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10147-026-03202-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,3]]},"references-count":43,"alternative-id":["3202"],"URL":"https:\/\/doi.org\/10.1007\/s10147-026-03202-z","relation":{},"ISSN":["1341-9625","1437-7772"],"issn-type":[{"value":"1341-9625","type":"print"},{"value":"1437-7772","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,3]]},"assertion":[{"value":"14 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 September 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 October 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"All the authors have no conflict of interest to declare.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}}]}}