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Table 2 Associations between antibody responses and complement fixation activity over time using linear mixed modeling (n = 30)

From: Induction and decay of functional complement-fixing antibodies by the RTS,S malaria vaccine in children, and a negative impact of malaria exposure

Factora

bb (s.e.)

95% CI

p valuec

f 2d

IgG1

   

0.38

 Linear term

1.10 (0.16)

0.78, 1.41

< 0.001

 

 Interaction term

− 0.28 (0.05)

− 0.38, − 0.18

< 0.001

 

IgG2

   

0.02

 Linear term

0.11 (0.13)

− 0.14, 0.37

0.388

 

 Interaction term

− 0.01 (0.05)

− 0.10, 0.08

0.805

 

IgG3

   

0.18

 Linear term

0.54 (0.15)

0.24, 0.83

< 0.001

 

 Interaction term

− 0.07 (0.05)

− 0.18, 0.03

0.177

 

IgG4

   

0.02

 Linear term

0.21 (0.86)

− 1.47, 1.90

0.802

 

 Interaction term

0.07 (0.31)

− 0.53, 0.68

0.808

 

IgM

   

0.03

 Linear term

− 0.21 (0.18)

− 0.57, 0.38

0.233

 

 Interaction term

− 0.02 (0.07)

− 0.11, 0.15

0.792

 
  1. aLinear mixed modeling (LMM) analyses where the natural log of C1q-fixation was regressed on the natural log of antibody responses (linear term) conditioning on other antibody response factors to provide an independent association. This LMM model included a term for the natural log of time (not shown) and relaxed the constraint of a consistent association between C1q-fixation and antibody responses across time (interaction term). The LMMs applied a random intercept for study participant and random slope for time
  2. bRegression coefficient (b) and standard error (s.e.) represent the percent change in participant C1q-fixation level for a percent increase in antibody responses
  3. cProbability values based on Wald statistics
  4. dCohen’s f2 represents the ratio of the unique variance explained by a specific antibody response factor to the variance explained by an intercept-only model. Higher values indicate a stronger effect