Abstract: Evaluating the cluster formation of clinical attacks in chronic relapsing diseases is an important statistical issue because the presence of attack clusters may influence therapeutic strategies for relapse prevention. We recently reported the occurrence of unevenly clustered attacks in patients with anti-aquaporin-4 (AQP4) antibody-positive neuromyelitis optica spectrum disorder (NMOSD) (Akaishi et al., 2020a). The presence of attack clusters implies the necessity of implementing intensive relapse prevention with highly efficient drugs, such as the anti-complement C5 monoclonal antibody (eculizumab), during the cluster period (Pittock et al., 2019). This is especially true in diseases in which relapse is an established factor that causes severe and irreversible sequelae, such as NMOSD (Akaishi et al., 2020b). In this report, we present the following two statistical methods for evaluating the presence of uneven cluster formation of attacks in relapsing diseases including anti-AQP4-positive NMOSD: (1) the chi-square goodness-of-fit test and (2) the Kolmogorov-Smirnov (KS) test.