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Volume 11, Number 11—November 2005

Research

Neutralizing Antibody Response and SARS Severity

Mei-Shang Ho*, Wei-Ju Chen*, Hour-Young Chen†, Szu-Fong Lin†, Min-Chin Wang†, Jiali Di†, Yen-Ta Lu‡, Ching-Lung Liu‡, Shan-Chwen Chang§, Chung-Liang Chao¶, Chwan-Chuen King§, Jeng-Min Chiou*, Ih-Jen Su#, and Jyh-Yuan Yang†Comments to Author 
Author affiliations: *Academia Sinica, Taipei, Taiwan; †Center for Disease Control, Taipei, Taiwan; ‡Taipei Mackay Memorial Hospital, Taipei, Taiwan; §National Taiwan University, Taipei, Taiwan; ¶Taipei Hospital, Taipei, Taiwan; #National Health Research Institutes, Taipei, Taiwan

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Table 5

Multivariate analysis of factors affecting seropositivity and neutralizing antibody titer of severe acute respiratory syndrome (SARS) patients

Variables*† Seropositivity*
Antibody titer†
OR (95% CI) p value Parameter estimates + SE p value
Age (y) (n + 1 vs. n) 0.97 (0.94-1.00) 0.065 0.0056 + 0.0079 0.478
Women vs. men 1.24 (0.47-3.3) 0.67 –0.417 + 0.235 0.081
Infection source, known vs. unknown 15.6 (5.9-41.4) <0.0001 0.248 + 0.313 0.431
Duration of illness (d) (n+1 vs. n, n = 1 through 44 d) 1.08 (1.025-1.143) 0.004 0.0638 + 0.0233 0.008
Time of convalescent-phase serum sample (weeks after fever onset) (n + 1 vs. n, n = 3 through 15 wk) 0.449 + 0.198 0.026
(Duration of illness) ×(Time of convalescent-phase serum sample) –0.005 + 0.0024 0.037
(Time of convalescent-phase serum sample)2 –0.025 + 0.012 0.042

*Logistic model: age, with every additional year of age, the odds of seropositivity is 0.97 (odds ratio, OR) (see Figure 1); sex, the odds for women to be seropositive is 1.24 (OR) when compared with men; infectious source, the odds of patients with known infection source to be seropositive is 15.6 times that of the patients without known source of infection; duration of illness, for every additional day of illness, the odds of seropositivity increases by 1.08.
†Linear mixed model: log2 (neutralizing antibody titer) = β0 + β1 (age) – β1 (sex) + β3 (infection source) + β4 (duration of illness) + β5 (time of convalescent-phase serum sample) –β6 (duration of illness ×time of convalescent-phase serum sample) –β7 (time of convalescent-phase serum sample)2. In results above, the model estimates are based on log2 (titers), to which the time of convalescent-phase serum collection (in weeks postonset of illness, starting from week 3) contributed in 3 terms; the antibody rise follows the first order of weeks postonset, and decay follows the second order of weeks postonset and an interactive term between duration of illness and weeks postonset.

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