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題名：探索紅斑性狼瘡的共病症-全人口病例對照與世代研究
作者：陳瑞鴻
作者(外文)：Chen, Jui-Hung
校院名稱：國立臺灣師範大學
系所名稱：健康促進與衛生教育學系
指導教授：李子奇
學位類別：博士
出版日期：2021
主題關鍵詞：紅斑性狼瘡；糖尿病；甲狀腺機能亢進；病例對照研究；路徑分析；世代研究；Systemic lupus erythematosus；Diabetes mellitus；Thyrotoxicosis；Case-control study；Path analysis；Cohort study
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目的
紅斑性狼瘡(Systemic Lupus Erythematosus, SLE)是一會影響多重器官之系統性自體免疫疾病，因臨床表徵不一，要能及早正確診斷SLE是一大挑戰。鑒於SLE延遲診斷之相關高經濟負擔、低生活品質及加重疾病嚴重程度，為了及早發現潛在可改變或可預防的風險因素，本研究旨在探討與SLE有正、負相關性的共病症，並建構相關共病症和SLE之間的關係路徑。另依據與SLE有正、負相關的共病症之結果，我們分別選取與SLE正相關之甲狀腺機能亢進及負相關之糖尿病進行世代研究，以進一步闡明甲狀腺機能亢進與SLE和糖尿病與SLE之間的關係。
材料與方法
本研究使用台灣全民健康保險研究資料庫及全民健保重大傷病檔進行病例對照與世代研究。於病例對照研究中，病例組研究對象為2010到2013年全民健保重大傷病檔中新診斷SLE病患(ICD-CM-9 710.0)，並以該病患第一次被診斷為SLE之日期為研究基準日。另以性別、年齡、投保單位的城鄉別及健保投保薪資級距等特性進行1:1真實配對以選取對照組，SLE病例與對照組之間以卡方或T檢定來檢驗人口學差異。再以研究基準日往前追溯1年以前、2年以前、…、9年以前被診斷之疾病，使用多變項條件邏輯斯回歸及逐步篩選法來篩選顯著相關共病症。我們更進一步利用路徑分析建構診斷1年以前相關共病症和SLE之間的關係路徑模型。另我們使用全人口資料進行世代研究以探討第二型糖尿病與SLE之間的關係，也進一步以世代研究探討甲狀腺機能亢進對SLE的影響。
結果
經由多變項條件邏輯斯回歸及逐步篩選法，在研究基準日1年以前，總計有23項過去共病症與SLE有相關，其中19項為正相關，4項為負相關。19項為正相關的共病症可被歸類為多個器官的自體免疫疾病，其中包含皮膚、血液、肝臟、牙齒、眼睛、甲狀腺、肺臟及心臟。4項為負相關的共病症則與糖尿病及懷孕相關症狀有關。於SLE診斷1年以前的最後修正模型中，蕁麻疹(ICD-9-CM 708)及糖尿病(ICD-9-CM 250)處於關係路徑模型路徑上層位置，蕁麻疹及糖尿病相對其他相關共病症對SLE的影響力更大，且分別為正相關及負相關之共病症。蕁麻疹與SLE為正相關的共病症(勝算比= 1.35, 95%信賴區間= 1.17–1.56, P < 0.001) , 而糖尿病則為SLE負相關的共病症(勝算比= 0.55, 95%信賴區間= 0.43–0.69, P < 0.001)。
在探討第二型糖尿病與SLE關係的全人口世代研究中，校正相關共變量後，第二型糖尿病與SLE的發生率呈現負相關(危險比= 0.77, 95% 信賴區間= 0.68–0.87, P < 0.001)，而此結果也與我們的病例對照研究一致。而在探討甲狀腺機能亢進與SLE關係的世代研究中，Cox迴歸分析顯示甲狀腺機能亢進與SLE的發生率呈現正相關(粗危險比=1.88, 95%信賴區間= 1.04–3.38, P = 0.036) 。但此相關性於校正其他潛在干擾變項後減弱。
結論
我們的研究結果展示了與SLE有相關的共病症及其關係路徑，研究結果支持甲狀腺機能亢進為SLE正相關的共病症，我們應對罹患多器官自體免疫疾病的病患提高SLE罹病的警覺。然而糖尿病於此研究中為SLE負相關共病症。未來需要進一步的研究去闡明其中可能的機轉以利更進一步了解紅斑性狼瘡的病生理機轉。
Objective
Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by affecting multiple organs. Due to the diversity of clinical manifestations, early accurate diagnosis is still challenging. Delay in SLE diagnosis may cause more healthcare utilization and associated costs, decline the quality of life, and incur serious consequences. For early identification of potentially modifiable or preventable risk factors, the present study attempts to determine prior positive and negative comorbidities associated with SLE simultaneously and construct pathways between comorbidities and SLE. Based on the results of SLE’s positively and negatively associated comorbidities, we selected thyrotoxicosis (positive association) and diabetes (negative association) to conduct cohort studies to further clarify the relationship between hyperthyroidism and SLE and diabetes and SLE.
Materials and Methods
We conducted a total population-based case-control study and nationwide population-based cohort studies with data collected from Taiwan’s National Health Insurance Research Database and Registry for Catastrophic Illness Patients Database (RCIPD). For the case-control study, the case group was defined as newly diagnosed SLE (International Classification of Disease, Ninth Revision, Clinical Modification, ICD-9-CM 710.0) between 2010 and 2013 collected from the RCIPD. The index date was set as the date of first diagnosis of SLE. These patients were exactly matched according to sex, age, residence, and insurance premium of the health insurance with a matching ratio of 1:1 with the control group. Chi-square or t test was performed to examine the differences in participants’ demographic characteristics between case and control groups. Prior diseases were screened out for 1–9 years prior to the index date. A multivariable conditional logistic regression with stepwise selection was used to identify the associated comorbidities. Furthermore, path analysis was performed to construct pathways between the associated comorbidities and SLE 1 year prior to the index date. For cohort studies, we conducted a total population-based cohort study to investigate the association between type 2 diabetes mellitus (T2DM) and SLE and a population-based cohort study to reveal the association between thyrotoxicosis and SLE.
Results
A total of 23 prior comorbidities were associated with SLE, with 19 comorbidities having positive associations and 4 comorbidities having negative associations 1 year prior to the index date. The 19 positively associated comorbidities could be categorized as autoimmune-related inflammation of multiple organs, including the skin, blood, liver, tooth, eye, thyroid, lung, and heart. The 4 negatively associated comorbidities could be attributed to diabetes mellitus (DM, ICD-9-CM 250) and pregnancy-related symptoms. In the final corrected Model 1 year prior to the index date, urticaria (ICD-9-CM 708) and DM were at the upper position and had more potent effects on SLE incidence than other associated comorbidities. Urticaria represented the positively associated comorbidity (Odds ratio, OR = 1.35, 95% CI = 1.17–1.56, P < 0.001), and DM represented the negatively associated comorbidity (OR = 0.55, 95% CI = 0.43–0.69, P < 0.001).
In the total population-based cohort study to reveal the association between T2DM and SLE, T2DM was found to be negatively associated with SLE incidence (hazard ratio, HR = 0.77, 95% CI = 0.68–0.87, P < 0.001) after controlling for other covariates; this was in agreement with our main finding in the case-control study. Moreover, in the population-based cohort study for the association between thyrotoxicosis and SLE, thyrotoxicosis was associated with a higher risk of incidental SLE in the Cox regression analysis with crude HR = 1.88, 95% CI = 1.04–3.38, and P = 0.036, but the association attenuated after adjusting for other covariates.
Conclusion
Our study revealed the prior comorbidities associated with SLE and pathways between the associated comorbidities and SLE. Our results supported that thyrotoxicosis was positively associated with SLE incidence. Increased awareness of SLE may be warranted for patients with autoimmune-related comorbidities of multiple organs. However, DM was negatively associated with SLE incidence in this study. Further studies are warranted to elucidate the possible underlying mechanism and for better understanding the pathogenesis of SLE.
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