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Letter by Niu and Xu Regarding Article, "S100B Serum Elevation Predicts In-Hospital Mortality After Brain Arteriovenous Malformation Rupture".

To the Editor: We read with great interest the article by Shotar et al published in Stroke recently. The authors aimed to determine whether elevated S100B protein serum level is associated with increased in-hospital mortality after brain arteriovenous malformation rupture. Two hundred and three ruptures were included retrospectively. The study population was divided into derivation (n=101) and validation (n=102) cohorts in the study. The in-hospital mortality in the 2 cohorts was 14/101 and 9/102, respectively. The authors concluded that elevated S100B protein serum level is strongly associated with in-hospital mortality after brain arteriovenous malformation rupture. The conclusion was based on the results of multivariate logistic regressions. We thought that the death events were too small to perform a multivariate logistic regression. It has been suggested that at least 10 or 20 outcome events per predictor are needed for multivariate logistic regression. Furthermore, 50 outcome events are needed for logistic regression that using stepwise method. In the study by Shotar et al, univariate analysis in the derivation cohort showed that 5 factors were potentially associated with in-hospital mortality (P<0.05). These 5 factors were included in multivariate model by using stepwise logistic regression. However, there were only 14 death events in the derivation cohort, which may cause overfitting of the model. In this study, 3 factors including intraventricular hemorrhage, intracerebral hemorrhage volume, and plasma troponin elevation were excluded from the final multivariate model. It is very possible that at least 1 of these factors and some of other factors such as age were actually associated with in-hospital mortality. Because there was theoretical or biological relationship between some factors (eg, intraventricular hemorrhage) and the outcome of in-hospital mortality, they should be included in the final model mandatory if there were enough outcome events. On the contrary, even there are enough outcome events; the issue of collinearity should be considered when inputting predictors into the multivariate model. S100B protein serum level has been suggested as a biomarker to predict the progress or the prognosis of brain injury. The increased serum level of S100B protein was reported to be associated with impaired blood-brain barrier, which may account for the reported finding that serum level of S100B was closely correlated with Glasgow Coma Scale 48 hours after trauma. Therefore, it is possible that S100B protein serum level is highly correlated with other factors such as Glasgow Coma Scale and hemorrhage volume in patients with brain arteriovenous malformation rupture. Proper measures should be taken to prevent collinearity because the effect of each predictor on the regression model will become less precise if input variables are highly correlated with one another. In conclusion, we agree with the authors that S100B protein serum level may be a promising marker to predict outcome in patients with brain arteriovenous malformation rupture. However, the specific predictive value remains uncertain because the outcome events were too small to make a solid and precise model to reveal the true effect of S100B protein serum level on in-hospital mortality.