Risk of herpes zoster in SLE Chen HH et al. lupus nephritis, and positive anti-Sm antibodies have been reported to be valuable risk factors for HZ in SLE patients.5 However, although the greater frequency of HZ infection in SLE patients is well recognized, a population-based cohort study has not yet been conducted. Moreover, the impact of age and gender on the risk of HZ in SLE patients remains unclear. The purpose of the present study was to examine the estimated risk ratio for HZ among SLE patients in the three- year period after disease onset compared to that of a cohort of patients without SLE during the same time period using the Taiwanese National Health Insurance Research Database (NHIRD). PATIENTS AND METHODS Data source The data source for the present study was the NHIRD, which includes inpatient and ambulatory care claims from 1996 to 2006. The National Health Insurance Program of the Bureau of National Health Insurance (BNHI) was imple- mented on March 1, 1995 and has since covered more than 98% of the population. The BNHI’s computerized compre- hensive database, including all of the medical claims for ambulatory care services and hospitalization, can facilitate a nationwide population-based cohort study. The NHIRD established a registry system for "Catastrophic Illnesses", including cancer, chronic mental illness, end-stage renal disease, congenital illness, and several autoimmune diseases such as SLE. The BNHI performs routine validations of the diagnoses by reviewing the original medical charts of all of the patients who applied for catastrophic illness registration. In Taiwan, the American College of Rheumatology classifica- tion criteria for SLE was used to validate the SLE diagnosis using the versions published in 1982 or 1997 based on the timing of making SLE diagnosis. Because the present study enrolled SLE patients solely from this particular registry, the accuracy of the SLE diagnosis was not a concern. The NHIRD established a representative database from the entire set of enrollees by randomly selecting 1,000,000 subjects. The present study used all of the claims data for these 1,000,000 subjects during the period of 1996 to 2006 to select a comparison cohort of patients without SLE. This cohort matched the study cohort for age, gender, and the date of the first ambulatory visit after the SLE diagnosis. Because the NHIRD consisted of de-identified secondary data that were released to the public for research purposes, the present study was exempted from a full review by the Internal Review Board. Study samples The present study was a retrospective cohort study that consisted of a study cohort and a comparison cohort. The study cohort consisted of SLE patients (International Classification of Diseases, 9th Revision, Clinical Modification [ICD9-CM] Code 710.0) in Taiwan from the registry of catastrophic illness patients during the period of 1996 to 2006. The index date for the study cohort was identified as the date of the first-time ambulatory care visit that had a diagnosis code for SLE during that period. To identify new SLE cases, those who had an index date before January 1, 1998 were excluded. The SLE patients who were followed-up for less than three years were also excluded from the present study. To minimize the possibility of enrolling SLE patients with an 1178 CLINICS 2011;66(7):1177-1182 episode of HZ before the index date or with a diagnosis code for HZ for prescribing medications for post-herpetic neuralgia after the index date, patients with any ambulatory visit for HZ (ICD9-CM code 053) within one year before the index date were excluded from the present study. The study cohort consisted of 10,337 SLE patients. The comparison cohort was selected from a 1,000,000 representative cohort. Patients with an SLE diagnosis in any of the claims data during the time period of 1996 to 2006 were excluded from the present study. Patients from the registry of beneficiaries (six for every patient in the study cohort) were then randomly extracted as the comparison cohort, matching the study cohort for the age at SLE onset (i.e., 1-17, 18-24, 25-34, 35-44, 45-54, 55-64, .64 years), gender, and the year of the index date. The date of the first- time ambulatory visit within one year of the index date was selected as the index date for the comparison cohort. Patients with less than three years of ambulatory visit records after the index date were excluded from the present study. Patients with an ambulatory visit for HZ within one year before the index date were also excluded. The comparison cohort included 62,022 patients without SLE. The potential confounding variables included the level of insurance as the economic index, the urbanization level, the geographic region (northern, central, southern, or eastern) of the patients, the types of medications, the presence of co- morbid medical diseases, and the Charlson co-morbidity index (CCI), as adapted by Deyo.11 The level of insurance was transformed to ordinal variables according to the 25th, 50th and 75th percentiles. In Taiwan, the urbanization levels were stratified into seven clusters, ranging from level one (most urbanized) to level seven (least urbanized).12 However, because the patient numbers in levels five through seven were small in both cohorts, these three levels were combined into one level (level five). The presence of prescription medication that was adjusted in the regression model included the average daily steroid dose (i.e., 0, ,10, 10-20 and .20 mg prednisolone equivalent) and the use of azathioprine, cyclophosphamide, mycophenolate, cyclos- porin, methotrexate, or hydroxychloroquine. Diabetes mellitus (ICD9-CM code 250), lymphoma (ICD9- CM codes 200-202), leukemia (ICD9-CM codes 204-208), breast cancer (ICD9-CM codes 174-175), liver cancer (ICD9- CM code 155), and HIV/AIDS (ICD9-CM code 042) were co- morbid medical disorders because previous studies have suggested that these disorders are risk factors for HZ.7 The CCI was also calculated for the adjustments for possible confounding co-morbidities. Using the diagnosis codes in two or more ambulatory claims that were made six months before or after the index date, the co-morbidities were identified, and the CCI was calculated. Statistical analysis To examine the unadjusted comparisons, a t-test was used for the normally distributed continuous variables, and a Pearson x2 test was used to analyze the categorical variables. The correlations between the variables were analyzed using Pearson’s correlation coefficients. The Kaplan-Meier method was performed to estimate the three-year HZ-free survival rates, and the log-rank test was used to examine the differences in the risk of HZ between the two cohorts. Cox proportional hazard regres- sions were used to compute the crude and adjusted risk ratios (RR) with a 95% confidence interval (95% CI). A