Epidemiological Evidence of Seasonality in Kawasaki Disease in Taiwan

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Original Acta Cardiol Sin 2007;23:29 34 Pediatric Cardiology Epidemiological Evidence of Seasonality in Kawasaki Disease in Taiwan Ming-Tai Lin, Jou-Kou Wang, Shuenn-Nan Chiu, Chun-An Chen, Hung-Chi Lue and Mei-Hwan Wu Background: Seasonality in the occurrence of a disease often suggests the presence of environmental factors in its etiology. Kawasaki disease (KD) is an acute systemic vasculitis of unknown etiology that occurs predominantly in infants and young children. KD is characterized by fever, bilateral nonexudative conjunctivitis, erythema of the lips and oral mucosa, changes in the extremities, skin rash, and cervical lymphadenopathy. It is believed to be a multifactorial disease, and its seasonality had never been examined epidemiologically. Aim: We sought to examine the seasonality of KD in Taiwan by using a higher-power statistical method. Method: Epidemiologic data of Kawasaki disease in Taiwan between 1996 and 2002 were taken from a published paper. Basically, the database came from the National Health Insurance data and hospitalized patients who were under 18 years old and met criteria listed for KD (ICD-9-CM code: 446.1) were selected. The data were transformed and analyzed in the form of cumulative distribution curve. Kuiper s test was applied to test the seasonality, and differences were deemed significant at a p value < 0.05. Results: The cumulative distribution curve for KD in Taiwan was developed for each year. The results of Kuiper s test for seasonality in each year between 1996 and 2002 showed statistical significance for all years examined, (p < 0.01) and ascertained the presence of seasonality for KD. Conclusion: Epidemiological analysis of KD patients in Taiwan confirmed the seasonality of this disease. This will support the theory that certain infectious agents may cause KD. Extended survey of the ubiquitous etiology is advised. Key Words: Seasonality Kawasaki disease Epidemiology Kuiper s test BACKGROUND The study of seasonal variation in disease frequency has been of great interest to medical professionals and epidemiologists. A seasonal pattern in the occurrence of a disease, say a temporal clustering or a cyclical variation, suggests the presence of environmental factors in its etiology. Many diseases, such as Received: November 22, 2006 Accepted: December 14, 2006 Department of Pediatrics, National Taiwan University Hospital and College of Medicine, National Taiwan University, Taipei, Taiwan. Address correspondence and reprint requests to: Dr. Mei-Hwan Wu, MD, PhD, Department of Pediatrics, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei 100, Taiwan. Tel: 886-2-2312-3456 ext. 5126; Fax: 886-2-2341-2601; E-mail: mhwu@ ha.mc.ntu.edu.tw ischemic heart disease, 1 congenital anomalies, 2 and mental disorders, 3 have been studied for seasonality. In these diseases with multi-factorial etiology, the seasonality component is often obscured by other factors and specific statistical approaches are always adopted to detect the hidden factors of seasonality. Kawasaki disease (KD) is such a case and its seasonality had never been examined by any strict epidemiologic methods. Only the case distribution with the months had been shown in previous reports. KD is an acute systemic vasculitis of unknown etiology that occurs predominantly in infants and young children. KD is characterized by fever, bilateral nonexudative conjunctivitis, erythema of the lips and oral mucosa, changes in the extremities, rash and cervical lymphadenopathy. 4,5 Coronary artery aneurysms or ectasia 29 Acta Cardiol Sin 2007;23:29 34

Ming-Tai Lin et al. develop in 5% to 10% of affected children even after the recommended intravenous immunoglobulin therapy. The first patient in Taiwan, found in 1976, died of acute myocardial infarction. 4 KD is now known to occur worldwide, but is clearly more prevalent in Japan, Taiwan, Korea and in children of Japanese or Oriental ancestry, with an annual incidence of around 110 cases per 100,000 children < 5 years old in Japan. The annual incidence of KD has increased steadily and now is around 60 cases per 100,000 in Taiwan, the second highest rate in the world. 4,5 To test for temporal variation (seasonality), several methods with different power are available. Ordinary 2 goodness-of-fit test (with 11 degrees of freedom for monthly data) is easy to use but lacks high statistical power. 6 Edwards test 7 has higher power, but it works only under the hypothesis that the pattern of frequency (incidence) follows a sinusoidal curve over periods of 12 months. The monthly case numbers of KD in Taiwan between 1996 and 2002 didn t follow a sinusoidal pattern. 5 Therefore, we would prefer a more generalized nonparametric method, Kuiper s test, 8 to study the seasonality of KD. The performance of this test has been investigated and proved to be of higher power than 2 goodness-of-fit test. Kuiper s test was first suggested for testing hypothesis about seasonal variation by Dr. Freedman. 8 Concerning this method, we describe its core concept as follows: Suppose, in a certain year (12 months), we have N subjects in our sample and the relationship between cumulative percentage of cases and that of months is plotted as Figure 1. The diagonal line represents the expected cumulative relative frequency if there were no seasonal variation (null hypothesis). The Kuiper s statistic (V N ) is the summation of D + N and D - N, which are the maximal upward (D + N ) and downward (D - N ) departure from the oblique line respectively. Because no generally applicable methods were available for deriving the theoretical distribution of Kuiper s statistic (V N ) under null hypothesis, a ten-thousand-times computer simulation approach was performed in 1979 and each simulation required 11 calls of a random-number generator. 8 Estimated s of the distribution of V N N are shown in Table 1. Ninety percent confidence limits for the s are also given in Table 1. METHODS Patient cohort of Kawasaki disease in Taiwan The data of patients were taken from the report by Chang et al. 5 and transformed into a table (Table 1). In that report, the database was obtained from the National Health Insurance (NHI) database. Patients who were under 18 years old and admitted to hospital with the diagnosis of KD (ICD-9-CM code: 446.1) were selected. The data were presented and analyzed in the form of a series of 12 monthly totals, which means the numbers of Figure 1. The relationship between cumulative percentage of cases and that of months as displayed according to the concept of Kuiper s test. Table 1. Estimated s of the asymptotic distribution of 8 V N N Percentile Estimate 90% confidence limits 10% 0.58 0.576-0.589 20% 0.67 0.670-0.680 30% 0.75 0.744-0.754 40% 0.82 0.811-0.822 50% 0.89 0.882-0.893 60% 0.96 0.950-0.961 70% 1.03 1.028-1.040 80% 1.14 1.128-1.145 85% 1.21 1.199-1.217 90% 1.29 1.280-1.297 95% 1.41 1.400-1.422 99% 1.66 1.641-1.683 Acta Cardiol Sin 2007;23:29 34 30

Seasonality of Kawasaki disease in Taiwan persons diagnosed with KD in each given month of the year. Construction of cumulative distribution curve The percentage and cumulative percentage for each month were calculated, and then the months were ranked, from first to last, according to order in the calendar. The cumulative distribution curve was the plot of the cumulative percentage of cases against the cumulative percentage of months. Statistical analysis Kuiper s test, first described for testing seasonality by Dr. Freedman in 1979, 8 was selected to examine the temporal variation of KD. The diagonal line representing the expected cumulative relative frequency was plotted first. Then, we could get Kuiper s statistic from the summation of D N + and D N -, which are the maximal upward (D N + ) and downward (D N - ) departures from the expected line respectively. Differences were deemed significant at p value < 0.05. From 1996 to 2002, monthly case numbers of KD in Taiwan were tabulated (Table 2, only data in 1998 and 2002 are shown as examples). Then we calculated the cumulative cases and percentage in each month of years between 1996 and 2002. The results of years 1998 and 2002 are shown here as examples (Figures 2 and 3, Table 3). The next step was to measure the differences (departure) between sample and expected cumulative percentages of cases in each month between 1996 and 2002. Under the null hypothesis (no seasonality), the expected cumulative percentage of cases for January through December should be equal to 1/12, 2/12, 3/12,.,11/12, 12/12 respectively. The results of 1998 and 2002 are taken for examples and shown in Table 4. Then we could get Kuiper s statistic (V N ) for each year from the summation of D N + and D N -, which were the maximal upward Figure 2. Cumulative monthly case number of Kawasaki disease in 1998 and 2002. RESULTS Figure 3. Cumulative distribution curve of the occurrence of Kawasaki disease in 1998 and 2002. Table 2. Monthly case number of KD in Taiwan (presented in 1998 and 2002) month 1 2 3 4 5 6 7 8 9 10 11 12 Total year 1998 72 70 113 100 162 116 122 108 089 87 84 77 1200 2002 82 81 083 116 104 112 096 096 101 75 80 50 1076 Table 3. Cumulative case number and percentage of Kawasaki disease in 1998 and 2002 Month 1 2 3 4 5 6 7 8 9 10 11 12 Cumulative cases 1998 72 142 255 355 517 633 755 863 952 1039 1123 1200 Percentage of 1998.060.12.21.29.43.53.63.72.79.87.94 1.00 Cumulative cases 2002 82 163 246 362 466 578 674 770 871 946 1026 1076 Percentage of 2002.076.15.23.34.43.54.63.72.81.88.95 1.00 31 Acta Cardiol Sin 2007;23:29 34

Ming-Tai Lin et al. Table 4. Difference between cumulative percentage of Kawasaki disease and expected cumulative percentage in 1998 and 2002 Month Expected cumulative percentage Sample percentage of 1998 Difference between 1998 and expected Sample percentage of 2002 Difference between 2002 and expected 1 0.083 0.060-0.023-0.076-0.007-2 0.167 0.118-0.049-0.152-0.015-3 0.250 0.213-0.037-0.229-0.021-4 0.333 0.296-0.037-0.336-0.003-5 0.416 0.431 0.015 0.433 0.017 6 0.500 0.527 0.027 0.537 0.037 7 0.583 0.629 0.046 0.626 0.043 8 0.667 0.719 0.052 0.716 0.049 9 0.750 0.793 0.043 0.810 0.060 10 0.833 0.866 0.033 0.879 0.046 11 0.917 0.936 0.019 0.954 0.037 12 1.000 1.000 0 1.000 0 (D N + ) and downward (D N - ) departures from the expected line, respectively. The Kuiper s statistic for year 1998 is 0.101 and 0.081 for year 2002. The results for the other 5 years are shown in Table 5. Based on Tables 1 and 5, all adjusted Kuiper s statistics were all greater than 1.66, which represented the 99 th of the estimated distribution of adjusted Kuiper s statistic. The results may conclude statistically significant seasonality for the occurrence of KD in Taiwan. DISCUSSION Although previous studies 4,5 from Taiwan have shown possibly more patients in the summer, the seasonality has never been examined by any epidemiological method. In this study, we applied a more stringent statistical method to examine the seasonality of KD. The results gave strong evidence to support the presence of seasonality (seasonal variation) for the occurrence of KD in Taiwan. Such seasonality for KD would suggest that certain environmental factors play an important role in the etiology of KD. The environmental factors with seasonality would most likely be infectious agents. This finding will also echo the general hypothesis for KD, that is, KD may occur only when certain infectious agent(s) meet the genetically susceptible population. The phenomenon of seasonal clustering in KD has been described in Japan 9,10 and Beijing. 11 But, only the distributions of the patients with the month were shown in these studies. In Japan, there were two high peaks in the monthly occurrence of KD. One peak was in January and the other was during June to August. 9,10 For such data with biphasic pattern, traditional 2 test is not good to detect the underlying seasonal clustering. Kuiper s test is consistent for all types of monthly departures from uniformity. That s why we adopted Kuiper s approach rather than other methods. In Taiwan, there was only one peak (April-June) in the monthly number of KD patients (Table 2). January is always annually the month with the lowest incidence of KD. The reasons for such differences between Japan and Table 5. Original and adjusted Kuiper s statistic in 1996-2002 Year 1996 1997 1998 1999 2000 2001 2002 Kuiper s statistic 0.069 0.097 0.101 0.063 0.066 0.075 0.081 Adjusted Kuiper s statistic * 2.243 2.921 3.499 2.109 2.253 2.594 2.657 Comparison with null hypothesis *Adjusted Kuiper s statistic = Kuiper s statistic (V N ) total number of cases in certain year ( N ) Acta Cardiol Sin 2007;23:29 34 32

Seasonality of Kawasaki disease in Taiwan Taiwan remain unclear. But, the possibility that different interaction between infectious agents and genetic predisposing factors may be elucidated in the future studies. As shown in Table 5, the largest adjusted Kuiper s statistic (V N N = 3.499) occurred in 1998, when there happened to be an epidemic of enterovirus 71 infection in Taiwan. Up to now, there was no report regarding the relationship between EV71 and Kawasaki disease. Therefore, whether there is a significant association or not warrants further extended studies. In conclusion, by using Kuiper s method to examine the epidemiological data of KD from 1996 to 2002, we confirmed the presence of seasonality in the occurrence of KD in Taiwan. REFERENCES 1. Bowie C, Prothero D. Finding causes of seasonal diseases using time series analysis. Int J Epidemiol 1981;10:87-92. 2. Johnbloet PH, Mulder AM, Hamers AJ. Seasonality of preovulatory non-disjunction and its aetiology of Down syndrome: an European collaborative study. Hum Genet 1982;62:134-8. 3. Symonds RL, Williams P. Seasonal variation in the incidence of mania. Br J Psychiatry 1976;129:45-8. 4. Lue HC, Philip S, Chen MR, et al. Surveillance of Kawasaki disease in Taiwan and review of the literature. Acta Paediatr Taiwan 2004;45:8-14. 5. Chang LY, Chang IS, Lu CY, et al. Epidemiologic features of Kawasaki disease in Taiwan, 1996-2002. Pediatrics 2004;114: e678-82. 6. Horns SD. Goodness-of-fit tests for discrete data: a review and an application to a health impairment scale. Biometrics 1977;33: 237-48. 7. Edwards JJ. The recognition and estimation of cyclic trends. Ann Hum Genet 1961;25:83-6. 8. Freedman LS. The use of a Kolmogorov-Smirnov type statistic in testing hypotheses about seasonal variation. J Epidemiol Community Health 1979;33:223-8. 9. Yanagawa H, Nakamura Y, Yashiro M, et al. Results of the Nationwide Epidemiologic Survey of Kawasaki Disease in 1995 and 1996 in Japan. Pediatrics 1998;102:e65. 10. Yanagawa H, Nakamura Y, Yashiro M, et al. Incidence of Kawasaki disease in Japan: the nationwide surveys of 1999-2002. Pediatr International 2006;48:356-61. 11. Du ZD, Zhang TH, Lu L, et al. Epidemiologic picture of Kawasaki disease in Beijing from 1995 through 1999. Pediatr Infect Dis J 2002;21:103-7. 33 Acta Cardiol Sin 2007;23:29 34

Original Acta Cardiol Sin 2007;23:29 34 台灣地區川崎病的季節集中趨勢 : 流行病學觀點 林銘泰王主科邱舜南陳俊安呂鴻基吳美環台北市台灣大學醫學院附設醫院小兒部 背景當疾病的發生率呈現明顯的季節性分布時, 常暗示環境因素在致病機轉中佔有一重要的角色 川崎病 (Kawasaki disease) 是一種原因未明的血管炎, 好發於年紀較小的兒童, 它有以下五個特徵 : 發燒持續五天以上 兩側非化膿性結膜炎 口腔黏膜發紅 四肢肢端皮膚變化 紅疹及頸部淋巴結 一般相信川崎病 (Kawasaki disease) 的發病具有多重因子. 然而它的季節性在台灣未曾被以流行病學的方法檢視過 方法從過去的文獻我們擷取出 1996 到 2002 年之間川崎病 (Kawasaki disease) 的流行病學資料, 基本上這些資料是從國民健康保險的資料庫中取得, 其中未滿 18 歲住院且符合川崎病診斷標準 (ICD: 446.1) 的病人才列入統計, 然後這些資料將被轉型成累積分布曲線 ; 我們應用 Kuiper s test 來分析這條曲線並研究其是否有明顯的季節性分布 結果從 1996 年到 2002 年間每年的累積分布曲線 (cumulative distribution curve) 被畫出 ; 運用 Kuiper s test 的結果發現在研究期間, 每一年的季節集中性均大於百分之九十九, 意即有明顯的季節趨勢 結論流行病學的分析結果顯示, 川崎病在台灣有明顯的季節分布, 這也支持了過去的理論, 川崎病可能是由某些病原體所誘發的 進一步針對致病病原的研究是有相當的必要性 關鍵詞 : 季節性 川崎病 流行病學 Kuiper s 試驗 34