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Deep cutaneous fungal infection in tropical regions: A retrospective study from a referral center in southern Taiwan
e38
Abstracts from the 41st Annual Meeting / Journal of Dermatological Science 86 (2017) e1–e95
were differences in baseline EASI scores and frequency of systemic treatment use between the two populations.
P04-37[O2-19]
P04-36[O2-18]
The classification of atopic dermatitis patients using machine learning method, based on the therapeutic outcome for the proactive treatment
Deep cutaneous fungal infection in tropical regions: A retrospective study from a referral center in southern Taiwan
Hiroshi Kawasaki 1,2,∗ , Hiroko Kasai 3 , Takaho A. Endo 4 , Koichi Ashizaki 5 , Fumiyo Yasuda 1 , Masayuki Amagai 1,2 , Tamotsu Ebihara 1
Wen-chien Tsai ∗ , Kwei-lan Liu, Chih-Hung Lee
1
http://dx.doi.org/10.1016/j.jdermsci.2017.02.110
The Department of Dermatology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan Background: Deep cutaneous fungal infections, including of subcutaneous mycoses and systemic fungal infection with skin involvement, result in significant morbidity and mortality. It has become particularly important because of the increasing patients receiving chemotherapy and transplantation. However, there are few epidemiological studies worldwide especially in tropical countries. Methods: We conducted a retrospective study from 2001 to 2014 reviewing patients with deep cutaneous fungal infections at a single referral center in southern Taiwan. This study reviewed the age, gender, clinical presentations, associated medical diseases, microbiological culture reports, and treatment outcomes of patients. Results: Of the 23 patients with deep cutaneous fungal infection, the average age at diagnosis was 56 years. Among 14 patients with primary cutaneous mycoses, 3 were reported with Fonsecaea sp. and the others with non-specific molds or no culture reports. Aspergillus sp., Mucor sp., Cruptococcus sp. and Penicillium marneffei were all cultured from patients of systemic mycoses with skin manifestation. Fifteen patients were immunocompromised and 4 of them had associated malignancies. One patient underwent a liver transplantation, and two patients suffered from acquired immune deficiency syndrome. Eight patients had received long-term corticosteroid therapy. Nine patients had diabetes mellitus. Conclusions: This study helps to identify features of deep cutaneous fungal infections in Taiwan. Immunosuppression, diabetes, and leukopenia are risk factors for advanced mycoses. In particular, long-term corticosteroid use is associated with systemic invasion and poor prognosis in Taiwan. Aspergillosis, mucormycosis, and disseminated cryptococcosis are particularly fatal infections. http://dx.doi.org/10.1016/j.jdermsci.2017.02.111
Department of Dermatology, Keio University School of Medicine, Tokyo, Japan 2 Laboratory for Skin Homeostasis, IMS-RCAIRIKEN, Japan 3 Department of Dermatology, Keiyu Hospital, Japan 4 Integrative Genomics Group, IMS-RCAIRIKEN, Japan 5 Laboratory for Disease Systems Modeling, IMS-RCAIRIKEN, Japan Atopic dermatitis (AD) has a very wide spectrum of the disease course and clinical phenotype. The classification of AD patients based on the clinical response would provide the suitable treatment decision, however the classification strategy of AD remains to be elucidated. Thirty-one patients with moderate AD were enrolled and treated by topical 0.05% betamethasone butyrate propionate ointment twice daily. After the remission, they shifted to apply 0.1% tacrolimus ointment (TACo) on the previous affected areas as proactive treatment. We investigated their characters and identified that the patients were classified into 3 groups by prognosis, which showed remission (n = 15), slow (n = 10) and acute (n = 6) recurrence. Although there were no significant differences in mean SCORAD during the period before the beginning of TACo application, the pattern of blood test data was strikingly different among these 3 groups. We developed a machine learning (ML) software “aiCluster” with a random forest algorithm and assessed whether we can predict the patients into subgroups based on the therapeutic outcome by using ML method with multiple clinical data before the start of the treatment. Plural parameters including blood test and clinical phenotype before the treatment intervention were applied in this system and it showed prediction with more than 95% accuracy of the therapeutic outcome. The analysis of weights of parameters suggested that serum biomarkers such as total IgE, eosinophils and TARC are more deterministic, but the use of combined data set added other parameters to blood test data showed more appropriate prediction. Clustering AD patients using ML methods with biomarkers and clinical phenotype would be beneficial for the treatment decision and lead to tailor-made medicine. http://dx.doi.org/10.1016/j.jdermsci.2017.02.112 P04-38[O2-20] Assessment of serum biomarkers in patients with plaque psoriasis after switching from cyclosporine A to secukinumab (Ph4 study) Hiroyuki Fujita 1,∗ , Ayako Fujishige 1 , Masako Yamaguchi 1 , Mamitaro Ohtsuki 2 , Akimichi Morita 3 , Yumiko Tani 1 , The JP01 Study Group 1
Novartis Pharma K.K., Japan Jichi Medical University, Japan 3 Nagoya City University, Japan Objectives: Secukinumab (SEC), a fully human monoclonal antiIL-17A antibody, has been shown to have significant efficacy in the treatment of moderate to severe psoriasis (Pso). Cyclosporine A (CsA) is used as a systemic treatment of plaque Pso. In the cases 2
Abstracts from the 41st Annual Meeting / Journal of Dermatological Science 86 (2017) e1–e95
were differences in baseline EASI scores and frequency of systemic treatment use between the two populations.
P04-37[O2-19]
P04-36[O2-18]
The classification of atopic dermatitis patients using machine learning method, based on the therapeutic outcome for the proactive treatment
Deep cutaneous fungal infection in tropical regions: A retrospective study from a referral center in southern Taiwan
Hiroshi Kawasaki 1,2,∗ , Hiroko Kasai 3 , Takaho A. Endo 4 , Koichi Ashizaki 5 , Fumiyo Yasuda 1 , Masayuki Amagai 1,2 , Tamotsu Ebihara 1
Wen-chien Tsai ∗ , Kwei-lan Liu, Chih-Hung Lee
1
http://dx.doi.org/10.1016/j.jdermsci.2017.02.110
The Department of Dermatology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan Background: Deep cutaneous fungal infections, including of subcutaneous mycoses and systemic fungal infection with skin involvement, result in significant morbidity and mortality. It has become particularly important because of the increasing patients receiving chemotherapy and transplantation. However, there are few epidemiological studies worldwide especially in tropical countries. Methods: We conducted a retrospective study from 2001 to 2014 reviewing patients with deep cutaneous fungal infections at a single referral center in southern Taiwan. This study reviewed the age, gender, clinical presentations, associated medical diseases, microbiological culture reports, and treatment outcomes of patients. Results: Of the 23 patients with deep cutaneous fungal infection, the average age at diagnosis was 56 years. Among 14 patients with primary cutaneous mycoses, 3 were reported with Fonsecaea sp. and the others with non-specific molds or no culture reports. Aspergillus sp., Mucor sp., Cruptococcus sp. and Penicillium marneffei were all cultured from patients of systemic mycoses with skin manifestation. Fifteen patients were immunocompromised and 4 of them had associated malignancies. One patient underwent a liver transplantation, and two patients suffered from acquired immune deficiency syndrome. Eight patients had received long-term corticosteroid therapy. Nine patients had diabetes mellitus. Conclusions: This study helps to identify features of deep cutaneous fungal infections in Taiwan. Immunosuppression, diabetes, and leukopenia are risk factors for advanced mycoses. In particular, long-term corticosteroid use is associated with systemic invasion and poor prognosis in Taiwan. Aspergillosis, mucormycosis, and disseminated cryptococcosis are particularly fatal infections. http://dx.doi.org/10.1016/j.jdermsci.2017.02.111
Department of Dermatology, Keio University School of Medicine, Tokyo, Japan 2 Laboratory for Skin Homeostasis, IMS-RCAIRIKEN, Japan 3 Department of Dermatology, Keiyu Hospital, Japan 4 Integrative Genomics Group, IMS-RCAIRIKEN, Japan 5 Laboratory for Disease Systems Modeling, IMS-RCAIRIKEN, Japan Atopic dermatitis (AD) has a very wide spectrum of the disease course and clinical phenotype. The classification of AD patients based on the clinical response would provide the suitable treatment decision, however the classification strategy of AD remains to be elucidated. Thirty-one patients with moderate AD were enrolled and treated by topical 0.05% betamethasone butyrate propionate ointment twice daily. After the remission, they shifted to apply 0.1% tacrolimus ointment (TACo) on the previous affected areas as proactive treatment. We investigated their characters and identified that the patients were classified into 3 groups by prognosis, which showed remission (n = 15), slow (n = 10) and acute (n = 6) recurrence. Although there were no significant differences in mean SCORAD during the period before the beginning of TACo application, the pattern of blood test data was strikingly different among these 3 groups. We developed a machine learning (ML) software “aiCluster” with a random forest algorithm and assessed whether we can predict the patients into subgroups based on the therapeutic outcome by using ML method with multiple clinical data before the start of the treatment. Plural parameters including blood test and clinical phenotype before the treatment intervention were applied in this system and it showed prediction with more than 95% accuracy of the therapeutic outcome. The analysis of weights of parameters suggested that serum biomarkers such as total IgE, eosinophils and TARC are more deterministic, but the use of combined data set added other parameters to blood test data showed more appropriate prediction. Clustering AD patients using ML methods with biomarkers and clinical phenotype would be beneficial for the treatment decision and lead to tailor-made medicine. http://dx.doi.org/10.1016/j.jdermsci.2017.02.112 P04-38[O2-20] Assessment of serum biomarkers in patients with plaque psoriasis after switching from cyclosporine A to secukinumab (Ph4 study) Hiroyuki Fujita 1,∗ , Ayako Fujishige 1 , Masako Yamaguchi 1 , Mamitaro Ohtsuki 2 , Akimichi Morita 3 , Yumiko Tani 1 , The JP01 Study Group 1
Novartis Pharma K.K., Japan Jichi Medical University, Japan 3 Nagoya City University, Japan Objectives: Secukinumab (SEC), a fully human monoclonal antiIL-17A antibody, has been shown to have significant efficacy in the treatment of moderate to severe psoriasis (Pso). Cyclosporine A (CsA) is used as a systemic treatment of plaque Pso. In the cases 2