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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 陳秀熙(Hsiu-Hsi Chen) | |
| dc.contributor.author | Jiun-Shiou Lee | en |
| dc.contributor.author | 李俊秀 | zh_TW |
| dc.date.accessioned | 2021-06-16T23:32:12Z | - |
| dc.date.available | 2020-07-27 | |
| dc.date.copyright | 2012-09-17 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-07-27 | |
| dc.identifier.citation | 參考文獻
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65241 | - |
| dc.description.abstract | 研究背景
骨質疏鬆症是臨床上常見的疾病，也是骨折最重要的危險因子之一，截至目前為止，很少有社區大規模之資料探討骨質疏鬆症之發生率，而利用定量式超音波骨質密度(QUS)檢測儀進行測量後所得到的骨質密度測量值(BMD)來預測骨質疏鬆症新病例發生之準確性，也很少被探討。 研究目的 利用社區整合式篩檢(1)估計族群之性別及年齡別骨質疏鬆症發生率；(2)探討定量式超音波骨質密度測量值對於骨質疏鬆症預測之準確性、產值及接受者作業曲線(Receiver Operating Curve, ROC)與最適切點之選定；(3)評估在控制其他相關危險因子下，定量式超音波骨質密度基礎值對於骨質疏鬆症發生是否具有劑量-反應效應(dose-response effect)；(4)評估使用定量式超音波骨質密度所得到時間相依之重複測量值，對於骨質疏鬆症是否也具有相似之劑量-反應效應(dose-response effect)。 材料與方法 本研究對象為40歲以上參與1999至2004年社區篩檢之一般民眾，共計40916位，男性共有17286人，女性共有23630人，研究設計是一個前瞻性研究世代，去除第一次篩檢(1999年)時已有骨質疏鬆症診斷之個案(盛行個案)後，追蹤正常世代至2004年，骨質疏鬆症之新病例個案。對於主要感興趣之骨質密度自變項，是以整合式篩檢為平台，於民眾參與歷次篩檢時，測量個人之定量式超音波骨質密度測量值，且同時進行生理與生化數值檢測，並以問卷蒐集相關疾病病史及危險因子等資訊。除了評估骨質密度篩檢對於骨質疏鬆症之準確性作業曲線及切點之選擇外，亦使用羅吉斯回歸及時間獨立與時間相依之比例風險模型，評估定量式超音波骨質密度基礎值與重複測量值對於骨質疏鬆症發生之劑量反應效應。 研究結果 骨質疏鬆症發生率為每千人年32.65，男性為每千人年11.17；女性為每千人年49.13，女性約為男性4倍。在骨質密度測量值切點訂為 -2的情況下，定量式超音波骨質密度檢測儀之敏感度為55.69%，特異度為66.00%，作業曲線下面積(AUC)為0.65 (95%CI:0.64-0.66)。定量式超音波骨質密度檢測儀之測量值越大，得到骨質疏鬆症的機會越低，此關係呈現因果關係之劑量-反應效應，也就是骨質密度測量值每增加1單位，骨質疏鬆症確診的勝算比減少12% (OR:0.88, 95%CI:0.84-0.91)。調整其他危險因子之後，若使用時間獨立之模型，每增加1單位骨質密度測量值可降低3% (HR:0.97, 95%CI:0.94-1.01)骨質疏鬆之發生。調整其他危險因子之後，若使用時間相依之模型，每增加1單位骨質密度測量值可降低5% (HR:0.95, 95%CI:0.92-0.99)骨質疏鬆之發生。最後考量骨質密度測量值加上年齡、性別、停經狀態等危險因子後，無論在時間獨立(AUC為0.79, 95%CI:0.79-0.80)或時間相依(AUC為0.78, 95%CI:0.77-0.79)之情形下，其骨質疏鬆發生之預測效度相當好。 結論 本研究確定定量式超音波骨質密度檢測儀之測量值與骨質疏鬆症之新發生病例呈現因果關係之劑量-反應效應。考慮定量式超音波骨質密度測量值與其他危險因子後，可以準確預測骨質疏鬆症之發生。此結論建議定量式超音波可以做為社區族群骨質密度之篩檢，進而早期治療骨質疏鬆以避免骨折之發生。 | zh_TW |
| dc.description.abstract | Background
Osteoporosis is a common disease and is also one of the most important risk factors responsible for fracture. It is very rare to study the incidence of osteoporosis by using the population-based and community-based data. Moreover, the accuracy of predicting of Incident osteoporosis in association with bone mineral density (BMD) and related risk factors also has been barely addressed. Purpose By using community-based intergrated screening data, we aimed to (1) estimate the incidence of osteoporosis by age and sex; (2) study the accuracy of predicting incident osteoporosis by using the quantitative ultrasound and the optimal cut off point based on the receiver operating characteristics (ROC) curve; (3) determine if there is a dose-response relationship between the baseline QUS measurement or time-dependent repeated QUS measurements and incident osteoporosis. Materials and Methods The study design is based on a prospective community-based cohort study consisting of people who were aged 40 years or over and participated in the community-based intergrated screening between 1999 and 2004. After excluding cases who had been already diagnosed as osteoporosis before the date of first screening date (prevalent cases), a total number of 40916 people (male: 17286, female: 23630) were enrolled. In each round of screening, the QUS measurement, physical, biochemical lab data and questionnares of risk factors of participants were collected. The accuracy of predicting incident osteoporosis by using QUS measurements was assessed by using receiver operating characteristics (ROC) curve. The odds and harzard ratio of QUS measurements and related risk factors were estimated by using logistic regression model and proportional hazards regression model, repectively. The dose-response relationship between incident osteoporosis and baseline QUS measurement or time-dependent repeated QUS measurements was also evaluated with or without adjusting for other significant risk factors. Results The incidence of osteoporosis was 32.65 per 1000 person-years and was higher in females (49.13 per 1000 person-years) than males (11.17 per 1000 person-years). The sensitivity of QUS was 55.69%, the specificity is 66.00% and the area under receiver operating curve is 0.65 (95%CI:0.61-0.66) while the cut-off point value was set at -2 pf BMD. As incremental unit of BMD lead to a 12%(OR:0.88 95%CI:0.84-0.91) reduction of incident osteoporosis. Compared with 0-20 percentage group, there was a dose-response relationship between QUS measurement and incident osteoporosis. After adjusting for related risk factors, an increase in one unit of QUS measurement lead to 3% (95%CI of HR:0.94-1.01) and 5% (95%CI of HR:0.92-0.99) of developing incident osteoporosis by using time-independent model and time-dependent model, respectively. By combing QUS measurements with risk factors, such as age, sex and menopause status, the AUC was 0.79 using time-independent model and 0.78 using time dependent model, both of which suggest the adequacy of model accuracy. Conclusion The results of this large community-based prospective cohort study provide the strong evidence on a dose-response relationship between QUS measurements and incident osteoporosis. Besides, combing QUS measurements with related risk factors has good accuracy of predicting incident osteoposis. This study suggests that baseline continuous QUS may be used for stratifying the risk of osteoporosis in the underlying population community-based screening so people can have earlier and in-time treatment when necessary. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T23:32:12Z (GMT). No. of bitstreams: 1 ntu-101-R99849014-1.pdf: 833265 bytes, checksum: a4e3529eaec2d4759807d4a0a3f202bf (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 目 錄
第一章 前言……………………………………………………………………… 1 第二章 骨質疏鬆症與骨質疏鬆篩檢文獻回顧 ………………………………… 4 一、骨質疏鬆症定義 ……………………………………………………… 4 二、骨質疏鬆症診斷標準 ………………………………………………… 4 三、骨質疏鬆症描述性流行病學 ……………………………………… 5 四、骨質疏鬆症與骨折 ………………………………………………… 6 五、骨質疏鬆症危險因子與骨質疏鬆性骨折之風險 ………………… 7 六、骨質疏鬆性骨折風險評估 …………………………………………… 12 (一)、骨折風險因子評估工具：FRAX ………………………………… 12 (二)、骨質密度檢測 ……………………………………………………… 14 1. 雙能量X光骨質密度儀(dual-energy x-ray absorptiometry, DXA) …… 15 2. 定量電腦斷層檢測(Quantitative computerized tomography, QCT) … 16 七、定量式超音波骨質密度檢測(Quantitative Ultrasound, QUS) …………… 16 八、檢測工具準確度(Measures of accuracy) ………………………………… 25 九、診斷概似函數比(diagnostic likelihood ratios, DLR) ……………………… 26 十、接受者作業曲線(Receiver operating characteristic curve)與曲線下面積… 27 十一、接受者作業曲線之最適切點選擇(Cut point selection) ………………… 29 十二、非時間相依風險函數模型 ……………………………………… 31 十三、時間相依比例風險迴歸模型 ……………………………………… 33 第三章 材料與方法 …………………………………………………………… 38 一、資料來源 …………………………………………………………… 38 (一)、整合式篩檢目標族群 …………………………………………… 38 (二)、研究樣本及設計 ………………………………………………… 38 (三)、骨質密度量測(定量式超音波骨質密度)及骨質疏鬆 ……… 41 (四)、骨質密度超音波檢測(QUS)數值與陽性個案定義 …………… 43 (五)、解釋變項蒐集 ………………………………………………… 44 二、統計分析 (一)、工具準確度及診斷概似函數比 ………………………………… 44 (二)、接受者作業曲線之曲線面積(AUC)與最適切點選擇 …………… 44 (三)、羅吉斯迴歸模型與風險函數模型架構 ……………………… 44 第四章 結果 ……………………………………………………………………… 46 一、描述性結果 …………………………………………………………… 46 二、骨質疏鬆症疾病分類正確率與概似函數 …………………………… 51 三、定量式超音波骨質密度檢測儀之AUC與測量值最適切點選擇 … 51 四、定量式超音波測量準確率之影響因子 …………………………… 53 五、骨質疏鬆症疾病風險函數模型 ……………………………………… 55 六、骨質疏鬆症疾病時間相依風險函數模型 …………………………… 57 七、模式驗證 …………………………………………………………… 58 第五章 討論 ……………………………………………………………………… 60 一、主要發現 …………………………………………………………… 60 二、骨質疏鬆症發生率 ………………………………………………… 60 三、定量式超音波骨質密度檢測儀之準確性 …………………………… 61 四、骨質密度與骨質疏鬆之劑量效應 ………………………………… 61 五、定量式超音波骨質密度檢測與整合式篩檢之重要性 …………… 62 六、骨質疏鬆症與骨折相關未來研究 ………………………………… 63 七、模式預測效度 ……………………………………………………… 64 八、研究限制 …………………………………………………………… 64 第六章 結論 ……………………………………………………………………… 65 參考文獻 ……………………………………………………………………… 78 | |
| dc.language.iso | zh-TW | |
| dc.title | 骨質密度檢測值與相關危險因子預測骨質疏鬆症發生率 | zh_TW |
| dc.title | Prediction of Incident Osteoporosis in Association with Bone Mineral Density and Related Risk Factors | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 黃國晉(Kuo-Chin Huang),鄭尊仁(Tsun-Jen Cheng),陳祈玲(Chi-Ling Chen),邱月暇(Yueh-Hsia Chiu) | |
| dc.subject.keyword | 骨質疏鬆症發生率,骨質密度,接受者作業曲線,劑量反應效應, | zh_TW |
| dc.subject.keyword | Incident Osteoporosis,Bone Mineral Density,Receiver Operating Curve,Dose-Response Effect, | en |
| dc.relation.page | 88 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-07-30 | |
| dc.contributor.author-college | 公共衛生學院 | zh_TW |
| dc.contributor.author-dept | 流行病學與預防醫學研究所 | zh_TW |
| 顯示於系所單位： | 流行病學與預防醫學研究所 | |
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