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. 2022 Sep 22;28(11):2309–2320. doi: 10.1038/s41591-022-01980-3

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Extended Data Fig. 7 — a) Displayed are C-index deltas between the CPH model trained on the PANEL + APOE4 predictor set, its metabolomic state addition (PANEL + APOE4 + MET), and CPH models trained on the PANEL set and its respective metabolomic state addition (PANEL + MET). The metabolomic state adds predictive information over the PANEL + APOE4. b) Partial trajectory for MET deciles (Top, Median, Bottom 10%) adjusted for PANEL and PANEL + APOE4, respectively. c) Hazard Ratio for the Metabolomic State adjusted for the predictors of the PANEL and PANEL + APOE4. d) Decision curve analysis for PANEL/PANEL + MET and PANEL + APOE4/PANEL + APOE4 + MET. The areas in between the solid and dotted lines indicate added net benefits resulting from metabolomic state addition to PANEL (gray lines, red area) and PANEL + APOE4 (black lines, violet area), respectively. Adding MET to PANEL improves net population benefit between the 2–8% decision threshold. In the case of PANEL + APOE4, MET addition improves utility at thresholds between 5–10%. Statistical measures were derived from n = 117.245 individuals without dementia at recruitment. Data are presented as median (center of error bar) and 95% CI (line of error bar) determined by bootstrapping with 1000 iterations.