{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T19:57:52Z","timestamp":1792699072282,"version":"4.5.0"},"reference-count":44,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2024,3,11]],"date-time":"2024-03-11T00:00:00Z","timestamp":1710115200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2024,4,2]]},"abstract":"<jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>The optimal cut-off for Alzheimer\u2019s disease (AD) CSF biomarkers remains controversial.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>\n                      To analyze the performance of cut-off points standardized by three methods: one that optimized the agreement between\n                      <jats:sup>11<\/jats:sup>\n                      C-Pittsburgh compound B PET (a-PET) and CSF biomarkers (A\u03b2\n                      <jats:sub>1\u201342<\/jats:sub>\n                      , pTau, tTau, and A\u03b2\n                      <jats:sub>1\u201342<\/jats:sub>\n                      \/A\u03b2\n                      <jats:sub>1\u201340<\/jats:sub>\n                      ratio) in our population, called PET-driven; an unbiased cut-off using data from a healthy research cohort, called data-driven, and that provided by the manufacturer. We also compare changes in ATN classification.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>\n                      CSF biomarkers measured by the LUMIPULSE G600II platform and qualitative visualization of amyloid positron emission tomography (a-PET) were performed in all the patients. We established a cut-off for each single biomarker and A\u03b2\n                      <jats:sub>1\u201342<\/jats:sub>\n                      \/A\u03b2\n                      <jats:sub>1\u201340<\/jats:sub>\n                      ratio that optimized their agreement with a-PET using ROC curves. Sensitivity, Specificity, and Overall Percent of Agreement are assessed using a-PET or clinical diagnosis as gold standard for every cut-off. Also, we established a data-driven cut-off from our cognitively unimpaired cohort. We then analyzed changes in ATN classification.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      One hundred and ten patients were recruited. Sixty-six (60%) were a-PET positive. PET-driven cut-offs were: pTau\u200a&gt;\u200a57, tTau\u200a&gt;\u200a362.62, A\u03b2\n                      <jats:sub>1\u201342<\/jats:sub>\n                      \/A\u03b2\n                      <jats:sub>1\u201340<\/jats:sub>\n                      \u200a&lt;\u200a0.069. For a single biomarker, pTau showed the highest accuracy (AUC 0.926). New PET-driven cut-offs classified patients similarly to manufacturer cut-offs (only two patients changed). However, 20 patients (18%) changed when data-driven cut-offs were used.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec specific-use=\"heading-level-1\">\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>We established our sample\u2019s best CSF biomarkers cut-offs using a-PET as the gold standard. These cut-offs categorize better symptomatic subjects than data-driven in ATN classification, but they are very similar to the manufacturer\u2019s.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3233\/jad-230678","type":"journal-article","created":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T12:54:16Z","timestamp":1710248056000},"page":"957-967","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Where Should I Draw the Line: PET-Driven, Data-Driven, or Manufacturer Cut-Off?"],"prefix":"10.1177","volume":"98","author":[{"given":"Antonio","family":"S\u00e1nchez-Soblechero","sequence":"first","affiliation":[{"name":"Neurology Department, Hospital General Universitario Gregorio Mara\u00f1\u00f3n, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara","family":"L\u00f3pez-Garc\u00eda","sequence":"additional","affiliation":[{"name":"Neurology Department, Cognitive 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