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Fig. 3 | BMC Neurology

Fig. 3

From: Dysregulated interleukin networks drive immune heterogeneity in Alzheimer’s disease: an immunogenomic approach to subgroup classification and predictive modeling

Fig. 3

Identification of key interleukin genes in AD and construction of a predictive nomogram. (A) The plot of binomial deviance versus log(λ) shows the process of selecting key interleukin genes based on the minimum cross-validated error, identifying the most relevant genes for AD prediction. (B) The nomogram illustrates how the selected key interleukin genes (IL1R2, IFNLR1, IL10RA, IL4R, IL1RL2, IL22RA1, IL5, and IL12A) contribute to the total score, which predicts the probability of AD. (C) The ROC curve displays the performance of the logistic regression model based on the selected genes. (D) The calibration curve shows the agreement between predicted probabilities from the nomogram and actual observed outcomes. (E) The DCA compares the net benefit of using the nomogram for clinical decision-making across a range of risk thresholds

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BMC Neurology

ISSN: 1471-2377

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