Investigation of factors associated with PIRA development
DISEASE, SEPARATION, EVENT
We then set out to investigate factors that could be associated with the development of PIRA. In an exploratory manner, we used Cox proportional hazard models to compare PIRA development between subgroups (Fig. Factors associated with PIRA development probability. Kaplan-Meyer estimates of clinical, demographical, and OCT factors associated with PIRA event probabilities. The panels (In order to investigate disease duration prior to ocrelizumab therapy as a possible factor, we stratified the time since diagnosis according to quartiles, with the 25% quartile being at 2.6 years, the 50% quartile at 9 years, and the 75% quartile at 15.3 years. Figure Distribution of baseline characteristics propensity score in different cohort subpopulations.Propensity Score(SD)0.519(0.058)0.480(0.082)Propensity Score(SD)0.527(0.053)0.471(0.079)Propensity Score(SD)0.499(0.071)0.476(0.087)Propensity Score(SD)0.480(0.084)0.505(0.066)Propensity Score(SD)0.490(0.080)0.472(0.079)Propensity Score(SD)0.479(0.106)0.502(0.078)Propensity Score(SD)0.453(0.092)0.504(0.056)Propensity Score(SD)0.465(0.093)0.510(0.077)A propensity score for the development of PIRA was calculated using logistic regression taking into account the baseline characteristics sex, EDSS at baseline, ARR at baseline and age at ocrelizumab treatment. A higher score indicates a higher likelihood for baseline characteristics that favor PIRA development. The table compares the scores of different subgroups. Significance of differences between subgroups was tested using a Mann–Whitney-U test. Differences were considered statistically significant with the following Similarly, though not statistically significant, a numerically higher cumulative PIRA probability appeared to be present in those patients that used ocrelizumab as first-line therapy compared to those with ocrelizumab as second-line therapy, i.e. escalation therapy (Fig. Propensity score calculation based on baseline characteristics revealed no significant differences between the different patient subgroups analyzed, with the exception of EDSS based separation, for which a significant difference was observed (Table 