Statistical analysis
Descriptive statistics were used and expressed as mean (standard
deviation), median (range), or count (frequency). Demographic and
clinical characteristics were compared between the two groups using thet test and chi-square test. The mean difference and odds ratio
with their corresponding 95% confidence intervals (CIs) were used to
evaluate the effect size between groups.
Patients with a long history of ITP often received multiple drugs
successively or simultaneously. To assess the effect of HCQ on platelet
counts in this context, we regressed platelet counts against HCQ
treatment using a mixed-effects model with adjustment for potential
confounding factors: sex, age at onset, and treatments which may affect
platelet counts (including corticosteroids, IVIG, TPO-RAs, rituximab,
and splenectomy). In this model, multiple measures within one individual
were set as random-effects intercept. Explanatory variables included
main effects of HCQ and ANA level, and an interaction term between HCQ
and ANA level.
IVIG and rituximab were drugs used in a discontinuous mode, and platelet
counts on the initiation date of the two drugs did not reflect their
therapeutic effect in the mixed-effects model, which would weaken their
effect on platelet counts. Thus, we performed a sensitivity analysis to
check the robustness of main findings. In the sensitivity analysis, the
effective duration of IVIG was defined to be one week, according to the
clinical experience that patients with chronic ITP usually had poor
response to IVIG, and the effective duration of rituximab was defined to
be one year.
The t test and chi-square test were conducted using the SPSS
Statistics software (version 26.0, IBM Corp). The mixed-effects model
was performed using R (version 4.1.3, R Foundation,
www.r-project.org, Vienna, Austria)
with lme4 and lmerTest packages.13, 14 A
two-sided p value of less than 0.05 was considered statistically
significant.