Efficacy of Episil® in patients with hematologic malignancies: a comparative study.

BACKGROUND: Episil® is a nonabsorbable liquid medical material used to coat and protect the mucosa in patients with oral mucositis. A few studies have reported its efficacy in patients with head and neck cancer. However, reports on its use in patients with hematologic malignancies are scarce. Thus, we aimed to evaluate the efficacy of Episil for the treatment of oral mucositis in patients with acute myelogenous leukemia, malignant lymphoma, acute lymphocytic leukemia, multiple myeloma, and myelodysplastic syndrome. METHODS: Between May 2018 and March 2019, a total of thirty-seven patients with acute myelogenous leukemia, malignant lymphoma, acute lymphocytic leukemia, multiple myeloma, and myelodysplastic syndrome who received Episil® for the treatment of oral mucositis were included in this study. All patients were treated at the Hiroshima Red Cross and Atomic-bomb Surgery Hospital. To determine the severity of oral mucositis, 22 out of the 37 patients were interviewed and compared objectively using the Common Terminology Criteria for Adverse Events, version 3.0. In addition, subjective measures of the effects of oral mucositis were assessed using an original evaluation protocol (a unique evaluation chart specific to the Department of Oral Surgery, Hiroshima Red Cross & Atomic-bomb Survivors Hospital). RESULTS: Out of 37 participants recruited in the study, 31 (84%) described the sensation of Episil® as very good or good. Moreover, the severity of mucositis was found to decrease after the use of Episil® in seven patients out of 22 (19%), particularly in those with mucositis at multiple sites. Participants' evaluations revealed pain relief and improvement in speech and feeding functions. Participants with grade 3 mucositis reported a greater improvement in pain relief, speech, and feeding functions than those with grade 2 mucositis. CONCLUSIONS: This study suggests the efficacy of Episil® in treating oral mucositis in patients with hematologic malignancies, particularly in those with oral mucositis at multiple sites. In addition to pain relief, Episil® may improve speech and feeding functions.

Statistical inference for estimating the incidence of cancer at the prefectural level in Japan.

Information of prefectural cancer incidence in Japan is an important resource to plan an effective regional cancer control program. In order to obtain accurate prefectural cancer incidence, we have to adjust for both of completeness of regional cancer registries and regional dispersion, simultaneously, Then, we developed a hierarchal Bayes model with a completeness adjustment by using the relation between MI ratio (mortality divided by incidence) and proportion of death certificate notified among incidence. Prefectural cancer incidence is estimated with the 95% credible interval, which suggests that the national MI ratio should be 0.386 if the registry were complete. Because cancer behavior has a variation depending on prefecture, such accurate incidence must contribute to plan and assess regional cancer control program.

An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis.

Statistical inference is considered for variables of interest, called primary variables, when auxiliary variables are observed along with the primary variables. We consider the setting of incomplete data analysis, where some primary variables are not observed. Utilizing a parametric model of joint distribution of primary and auxiliary variables, it is possible to improve the estimation of parametric model for the primary variables when the auxiliary variables are closely related to the primary variables. However, the estimation accuracy reduces when the auxiliary variables are irrelevant to the primary variables. For selecting useful auxiliary variables, we formulate the problem as model selection, and propose an information criterion for predicting primary variables by leveraging auxiliary variables. The proposed information criterion is an asymptotically unbiased estimator of the Kullback-Leibler divergence for complete data of primary variables under some reasonable conditions. We also clarify an asymptotic equivalence between the proposed information criterion and a variant of leave-one-out cross validation. Performance of our method is demonstrated via a simulation study and a real data example.