Table 2 Association between plasma biomarkers and longitudinal PACC.

From: Plasma biomarkers of Alzheimer’s disease improve prediction of cognitive decline in cognitively unimpaired elderly populations

Model

Beta coefficient

R2 [95% CI]

Ref: basic model

Plasma Aβ42/Aβ40

Plasma P-tau217

Plasma NfL

P value

AICΔ

ATN

−0.15 [−0.24, −0.05]

(P = 0.0026)

−0.15 [−0.25, −0.06]

(P = 0.0020)

−0.12 [−0.21, −0.02]

(P = 0.0141)

0.14 [0.12, 0.17]

<0.0001

−28

A

−0.18 [−0.19, −0.09]

(P = 0.0002)

  

0.11 [0.09, 0.14]

<0.0001

−14

T

 

−0.20 [−0.20, −0.11]

(P < 0.0001)

 

0.09 [0.08, 0.13]

0.0002

−13

N

  

−0.16 [−0.25, −0.06]

(P = 0.0014)

0.10 [0.08, 0.14]

0.002

−9

  1. This table shows the results from fitting linear mixed effects models with longitudinal PACC as outcome and plasma biomarkers added separately or all together to a basic model consisting of age, sex, and education. β-coefficients are presented in terms of “PACC points/year per standard deviation change in biomarker value.” R2 values were evaluated and confidence intervals were calculated using 1000 bootstrapped samples. The basic model consisting of only demographics had R2 = 0.07 (95% CI [0.06, 0.11]) and AIC = 6699. P values represent an ANOVA comparison to the basic model; AICΔ values represent the change in AIC compared to the basic model and an AICΔ value of −2 or lower implies a better fit than the basic model. All statistical tests were two-sided with no adjustment for multiple comparisons.
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