{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T04:56:23Z","timestamp":1781585783927,"version":"3.54.5"},"reference-count":34,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T00:00:00Z","timestamp":1781568000000},"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. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Monoclonal immunoglobulin (MIg)-related disorders are clonal plasma cell diseases defined by aberrant MIg overproduction, typically presenting with subtle, non-specific manifestations that lead to underrecognition in routine clinical practice, delayed diagnosis, and subsequent irreversible organ damage and poor outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>To address this critical gap and facilitate timely MIg diagnosis, we developed and compared eight machine learning models using clinical and routine laboratory data. Cohort 1 (n=5018) included patients undergoing their first serum immunofixation electrophoresis (IFE) test at Xijing Hospital between 2017 and 2024, comprising 2038 MIg-positive and 2980 MIg-negative cases. The top-performing model was subsequently advanced for Cohort 2 (n=2270), consisting of three subsets (Set 1: Xijing Hospital, n=1753; Set 2: 3201 Hospital, n=398; Set 3: Shaanxi Provincial People\u2019s Hospital, n=119), served as a fully independent multi-institutional cohort, and was applied to assess the generalizability of the model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Feature selection identified ten key variables\u2013urinary cast count, mean corpuscular volume, prothrombin time, activated partial thromboplastin time, albumin\/globulin ratio, globulin, total protein, calcium, age, and sex\u2013which were used for final model construction. Among the eight machine learning algorithms, the light gradient boosting machine (LightGBM) model showed superior performance, achieving an AUC of 0.945 (87.0% sensitivity, 89.6% specificity) in the Cohort 2, and achieved 84.6% sensitivity, significantly outperforming the conventional serum protein electrophoresis (75.3% sensitivity) in the subset of cohort 2. In a separate cohort of newly enrolled patients, its 88.2% sensitivity also exceeded that of three non-specialist clinicians.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This LightGBM model, built on readily available clinical and routine laboratory data, may help identify potential MIg-related cases and prioritize patients for further specialized confirmatory testing, which could facilitate earlier recognition and reduce diagnostic delays.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1856505","type":"journal-article","created":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T04:26:50Z","timestamp":1781584010000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Multi-center validation of a machine learning model for early detection of monoclonal immunoglobulin-related disorders using routine laboratory data"],"prefix":"10.3389","volume":"17","author":[{"given":"Yujiao","family":"Hu","sequence":"first","affiliation":[{"name":"Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Hao","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hailong","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Hematology, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruixi","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Clinical Medicine, Xi\u2019an Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianrui","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, 3201 Hospital","place":["Hanzhong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weihua","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Hematology, Shaanxi Provincial People\u2019s Hospital","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinran","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yitong","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Computer Science, Xianyang Normal University","place":["Xianyang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, 3201 Hospital","place":["Hanzhong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanjun","family":"Diao","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Clinical Laboratory Medicine, Xijing Hospital, Fourth Military Medical University","place":["Xi\u2019an, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,16]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1136\/jcp-2023-208774","article-title":"Screening for and diagnosis of monoclonal gammopathy","volume":"76","author":"Chong","year":"2023","journal-title":"J Clin Pathol"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2025.1670408","article-title":"Biochemical analysis reveals aberrant and variable immunoglobulin M composition in Waldenstr\u00f6m macroglobulinemia and IgM monoclonal gammopathy of unknown significance","volume":"16","author":"Oskam","year":"2025","journal-title":"Front Immunol"},{"key":"B3","doi-asserted-by":"publisher","first-page":"3430","DOI":"10.1182\/blood-2019-127625","article-title":"An institutional retrospective study on recognizing the delay in multiple myeloma diagnosis","volume":"134","author":"Ghalehsari","year":"2019","journal-title":"Blood"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1093\/ndt\/gfaf254","article-title":"Management of monoclonal gammopathy of renal significance: treatment standard","volume":"41","author":"Jaturapisanukul","year":"2026","journal-title":"Nephrol Dial Transplant"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1002\/ajh.27422","article-title":"Multiple myeloma: 2024 update on diagnosis, risk-stratification, and management","volume":"99","author":"Rajkumar","year":"2024","journal-title":"Am J Hematol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2014.8237","article-title":"Protein electrophoresis and immunofixation for the diagnosis of monoclonal gammopathies","volume":"312","author":"Rajkumar","year":"2014","journal-title":"JAMA"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1038\/s41408-023-00795-w","article-title":"Delayed diagnosis resulting in increased disease burden in multiple myeloma: the legacy of the COVID-19 pandemic","volume":"13","author":"Carmichael","year":"2023","journal-title":"Blood Cancer J"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1016\/j.clml.2026.01.003","article-title":"Diagnostic journeys and delays in AL amyloidosis: insights from a cross-sectional patient survey","volume":"26","author":"Abdallah","year":"2026","journal-title":"Clin Lymphoma Myeloma Leuk"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1002\/ajh.26801","article-title":"Assessment of renal outcome following therapy in monoclonal immunoglobulin deposition disease: emphasizing the need for a consensus approach","volume":"98","author":"Pianko","year":"2023","journal-title":"Am J Hematol"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1007\/s00277-023-05584-w","article-title":"Prognostic significance of serum monoclonal proteins based on immunofixation electrophoresis in B-cell non-Hodgkin lymphoma","volume":"103","author":"Gao","year":"2024","journal-title":"Ann Hematol"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2022.0003","article-title":"Diagnosis and management of multiple myeloma: a review","volume":"327","author":"Cowan","year":"2022","journal-title":"JAMA"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.1045002","article-title":"Monoclonal gammopathies of clinical significance (MGCS): in pursuit of optimal treatment","volume":"13","author":"Oganesyan","year":"2022","journal-title":"Front Immunol"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1097\/rli.0000000000000986","article-title":"Prediction of bone marrow biopsy results from MRI in multiple myeloma patients using deep learning and radiomics","volume":"58","author":"Wennmann","year":"2023","journal-title":"Invest Radiol"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1111\/ijlh.14324","article-title":"Construction of the prediction model for multiple myeloma based on machine learning","volume":"46","author":"Cai","year":"2024","journal-title":"Int J Lab Hematol"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.608191","article-title":"Employment of artificial intelligence based on routine laboratory results for the early diagnosis of multiple myeloma","volume":"11","author":"Yan","year":"2021","journal-title":"Front Oncol"},{"key":"B16","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1186\/s40537-021-00516-9","article-title":"A survey on missing data in machine learning","volume":"8","author":"Emmanuel","year":"2021","journal-title":"J Big Data"},{"key":"B17","doi-asserted-by":"publisher","first-page":"1834","DOI":"10.1007\/s00134-016-4528-8","article-title":"Collinearity and multivariable analysis","volume":"42","author":"Claret","year":"2016","journal-title":"Intensive Care Med"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1097\/js9.0000000000003647","article-title":"A multi-omics pipeline integrating machine learning and spatial-cellular analysis identifies SASH1 as a prognostic biomarker and therapeutic target in head and neck squamous cell carcinoma","volume":"111","author":"Dai","year":"2025","journal-title":"Int J Surg"},{"key":"B19","doi-asserted-by":"publisher","DOI":"10.1016\/j.pacs.2025.100776","article-title":"Radiomics-driven perfusion prediction in clinical photoacoustic foot imaging","volume":"46","author":"Huang","year":"2025","journal-title":"Photoacoustics"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.3390\/covid5100167","article-title":"Machine learning models to discriminate COVID-19 severity with biomarkers available in Brazilian public health","volume":"5","author":"Prado","year":"2025","journal-title":"COVID"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.2147\/ijnrd.s280179","article-title":"Light chain cast nephropathy in multiple myeloma: prevalence, impact and management challenges","volume":"15","author":"Men\u00e8","year":"2022","journal-title":"Int J Nephrol Renovasc Dis"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1053\/j.ajkd.2018.07.012","article-title":"Urine sediment examination in the diagnosis and management of kidney disease: core curriculum 2019","volume":"73","author":"Cavanaugh","year":"2019","journal-title":"Am J Kidney Diseases: Off J Natl Kidney Foundation"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1182\/blood-2025-1305","article-title":"Monoclonal gammopathy-related coagulopathies: a systematic analysis","volume":"146","author":"Lavorgna","year":"2025","journal-title":"Blood"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2024.e34111","article-title":"Rediscovering hemostasis abnormalities in multiple myeloma: the new era","volume":"10","author":"Huang","year":"2024","journal-title":"Heliyon"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.3389\/frhem.2025.1435193","article-title":"Abnormalities of primary and secondary hemostasis in multiple myeloma: insights from studies on thrombopoiesis, the coagulation system, and the bone marrow microenvironment","volume":"4","author":"Abdi","year":"2025","journal-title":"Front Hematol"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1111\/ijlh.13958","article-title":"The effect of haemoglobin, albumin, lymphocyte and platelet score on the prognosis in patients with multiple myeloma","volume":"45","author":"Solmaz","year":"2023","journal-title":"Int J Lab Hematol"},{"key":"B27","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1038\/s41408-025-01371-0","article-title":"Hypoalbuminemia: a new risk factor for progression in patients with monoclonal gammopathy of uncertain significance","volume":"15","author":"Alejo","year":"2025","journal-title":"Blood Cancer J"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1182\/blood.V116.21.1925.1925","article-title":"Mean corpuscular volume as an early predictor of Malignant evolution of monoclonal gammopathy of undetermined significance","volume":"116","author":"Khalife","year":"2010","journal-title":"Blood"},{"key":"B29","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1038\/s41572-024-00529-7","article-title":"Multiple myeloma","volume":"10","author":"Malard","year":"2024","journal-title":"Nat Rev Dis Primers"},{"key":"B30","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1182\/blood-2020-139006","article-title":"Multiple myeloma cell defects erythropoiesis and results anemia via high level of CCL3 in bone marrow microenvironment","volume":"136","author":"Liu","year":"2020","journal-title":"Blood"},{"key":"B31","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1186\/s13046-021-01876-z","article-title":"O-GlcNAcylation homeostasis controlled by calcium influx channels regulates multiple myeloma dissemination","volume":"40","author":"Samart","year":"2021","journal-title":"J Exp Clin Cancer Res"},{"key":"B32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v106.i01","article-title":"Elastic net regularization paths for all generalized linear models","volume":"106","author":"Tay","year":"2023","journal-title":"J Stat Softw"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bty750","article-title":"Precision lasso: accounting for correlations and linear dependencies in high-dimensional genomic data","volume":"35","author":"Wang","year":"2019","journal-title":"Bioinformatics"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.1093\/clinchem\/hvae116","article-title":"Failure of serum immunofixation electrophoresis to detect intact monoclonal IgD lambda unraveled by mass spectrometry","volume":"70","author":"Nevejan","year":"2024","journal-title":"Clin Chem"}],"container-title":["Frontiers in Immunology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2026.1856505\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T04:26:53Z","timestamp":1781584013000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fimmu.2026.1856505\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,16]]},"references-count":34,"alternative-id":["10.3389\/fimmu.2026.1856505"],"URL":"https:\/\/doi.org\/10.3389\/fimmu.2026.1856505","relation":{},"ISSN":["1664-3224"],"issn-type":[{"value":"1664-3224","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,16]]},"article-number":"1856505"}}