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Summary variables from exploratory factor analysis (EFA) assessed the markers\u2019 collective impact on survival. We integrated ALS functional rating scale-revised (ALSFRS-R) scores with survival data using a joint latent class model to identify patterns of functional decline. Multinomial logistic regression determined how the EFA-derived factors predicted the decline trajectories post-diagnosis.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Higher levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B, and albumin at diagnosis were linked to lower mortality in ALS patients, while increased neurofilament light chain (NfL), leukocyte count, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and carbon dioxide (CO<jats:sub>2<\/jats:sub>) levels indicated higher mortality. The \u2018Red blood cell profile\u2019 factor, derived from EFA, emerged as a significant predictor of survival, independent of other prognostic indicators. The joint latent class model identified three distinct patient groups based on functional decline, with \u2018Red blood cell profile\u2019 suggesting a lower likelihood of being in the groups with slower progression.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>Clinical chemistry markers, including NfL, lipids, albumin, leukocyte count, MCV, MCH, CO<jats:sub>2<\/jats:sub>, and the \u2018Red blood cell profile,\u2019 were associated with ALS survival. As these markers represent broader bodily functions, integrating them in ALS patient care could improve disease management.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s00415-024-12774-7","type":"journal-article","created":{"date-parts":[[2024,12,12]],"date-time":"2024-12-12T12:04:25Z","timestamp":1734005065000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Exploring clinical chemistry markers in amyotrophic lateral sclerosis: insights into survival and disease trajectories"],"prefix":"10.1007","volume":"272","author":[{"given":"Ioannis","family":"Psychogios","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8948-4376","authenticated-orcid":false,"given":"Yihan","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christina","family":"Seitz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emily E.","family":"Joyce","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anik\u00f3","family":"Lovik","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caroline","family":"Ingre","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Fang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,12]]},"reference":[{"issue":"2","key":"12774_CR1","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1056\/NEJMra1603471","volume":"377","author":"RH Brown","year":"2017","unstructured":"Brown RH, Al-Chalabi A (2017) Amyotrophic lateral sclerosis. 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