進階搜尋


下載電子全文  
系統識別號 U0026-1507201601103800
論文名稱(中文) 透析病人對健康照護體系的照護負擔:從心血管併發症的定量到成本效益分析
論文名稱(英文) Burden of dialysis patients on the healthcare system: from quantification of cardiovascular events to cost-effectiveness
校院名稱 成功大學
系所名稱(中) 臨床醫學研究所
系所名稱(英) Institute of Clinical Medicine
學年度 104
學期 2
出版年 105
研究生(中文) 張育誌
研究生(英文) Yu-Tzu Chang
學號 S98001088
學位類別 博士
語文別 英文
論文頁數 135頁
口試委員 指導教授-王榮德
指導教授-宋俊明
召集委員-李中一
口試委員-黃景祥
口試委員-洪冠予
口試委員-黃尚志
口試委員-林聖翔
中文關鍵字 糖尿病  末期腎病變  心血管事件  急性心肌梗塞  腦梗塞  鬱血性心衰竭  預期壽命  預期損失壽命  血液透析  腹膜透析  成本效益分析  生活品質  生活品質調整預期壽命  生活品質調整人年 
英文關鍵字 Diabetes  end-stage renal disease  cardiovascular events  acute myocardial infarction  stroke  congestive heart failure  life expectancy  expected years of life lost  hemodialysis  peritoneal dialysis  cost-effectiveness  quality of life  quality-adjusted life expectancy  quality-adjusted life year 
學科別分類
中文摘要 在以前的研究中很少討論到新診斷糖尿病與末期腎病變在心血管事件風險、預期壽命、預期損失壽命之間的交互作用。此外,雖然透析費用花費甚鉅,然而利用配對樣本來研究不同透析模式的成本效益分析卻仍缺乏。為探討糖尿病與末期腎病變對心血管事件風險、預期壽命、預期損失壽命的作用,我們首先藉由兩個有全國代表性的族群資料庫來探討特定年齡與性別及二十年累積心血管事件發生率,包括急性心肌梗塞、腦梗塞、鬱血性心衰竭,在有無糖尿病與末期腎病變分組下的影響。族群資料庫中有小於18歲、過去有心血管或惡性腫瘤病史的人會先被排除。另外Cox比例風險模式同時考慮死亡因素競爭調整也將被使用來分析相關的風險。在本研究特地目的一,總計有648,851的非末期腎病變病人與71,397個末期腎病變病人,其中分別包含53,342與34,754個糖尿病患者,從1998年初開始追蹤到2009年底。結果顯示心血管事件的發生在特定年齡與性別的分層下,隨著有糖尿病與末期腎病變的出現使風險逐漸增加。而末期腎病變後新發生糖尿病組別所導致的心血管事件的風險,特別是急性心肌梗塞、腦梗塞,跟糖尿病引發末期腎病變組別的風險相近。此外,糖尿病與末期腎病變對心血管事件的風險具有近似相乘性的協同作用,其同時具有糖尿病與末期腎病變的族群相對都沒有的族群其發生急性心肌梗塞、腦梗塞的風險值分別提高為5.24倍(95%信賴區間:4.83-5.68)與2.43倍(95%信賴區間:2.32-2.55);而末期腎病變後新發生糖尿病所引起的風險值亦相似,分別為提高4.12倍(95%信賴區間:3.49-4.87)與1.75倍(95%信賴區間:1.57-1.95)。在本研究特地目的二中,更進一步追蹤這一群新發生心血管事件病人的未來死亡率與預期壽命。我們在特定年齡與性別分層後,先利用Kaplan-Meier方法分析追蹤年間的存活率,再利用一個具穩定額外死亡風險的前提假設所發展出的方程式來外推存活曲線到終生來預測各分組的預期壽命、預期損失壽命。在35,793發生心血管事件的病人中,非末期腎病變與非糖尿病且大於65歲的族群中,其預期壽命、預期損失壽命分別為2.08-8.07年與3.07-10.25年; 而在非末期腎病變與非糖尿病但小於65歲的族群中,是分別為4.09-17.28年與6.60-22.45年。出現糖尿病與末期腎病變會分別造成0.57-6.59及2.32-8.74年的預期損失壽命,而末期腎病變後新發生糖尿病的出現會導致最高的預期壽命損失。另外在多變數Cox比例風險模式下,死亡的風險會隨著末期腎病變與糖尿病的出現而逐步增加,而末期腎病變後新發生糖尿病會有最高的死亡風險,特別是在心血管事件發生4.5年之後。最後在本研究特地目的三,我們比較了不同透析模式的成本效益分析。從全國透析病人資料庫中依據臨床特性與傾向分數配對後,共選出4285組新接受血液透析與腹膜透析的配對樣本。利用此樣本族群14年的追蹤資料來預測終生存活率與醫療花費。另外我們在12家透析院所進行EQ-5D的調查,同樣利用臨床特性與傾向分數配對的結果選出179對血液透析與腹膜透析的配對樣本。接下來利用kernal-smoothing method畫出的動態生活品質變化區線與存活函數相乘來得出生活品質調整預期壽命。分析結果顯示,血液透析與腹膜透析病人的預期壽命相似(19.11與19.08年),平均效用值與生活品質調整預期壽命也相似,只有在終生醫療花費中,血液透析病人較腹膜透析病人來的高(237,795美金相對於204,442美金)。最後計算每得到一個生活品質調整人年的花費,腹膜透析病人相較血液透析病人來得低(13,681美金相對於16,643美金)。因此本研究中,我們的研究結果首先證明了糖尿病與末期腎病變對心血管事件的風險是具有近似相乘性的協同作用。糖尿病,特別是末期腎病變後新發生的糖尿病,與末期腎病變兩者都會造成在發生心血管事件後死亡率的提高與更多預期壽命的損失。因此採取初級或次級的預防措施來下降心血管事件的風險與可能壽命的損失是必要的。此外,當考慮到透析模式的成本效益分析時,腹膜透析是相對血液透析為一具成本效益的透析治療,而決定成本效益的主要因子乃是花費在給付給該透析模式與其引起相關併發症的醫療花費。
英文摘要 Very few studies investigated the interaction of incident diabetes and end-stage renal disease (ESRD) on the risks of cardiovascular (CV) events, life expectancy and expected years of life lost (EYLL). In addition, although treatment for the dialysis population is resource intensive, a cost-effectiveness analysis between hemodialysis (HD) and peritoneal dialysis(PD) by matched pairs is still lacking. To investigate the impact of ESRD and diabetes on the risks of CV events and LE and EYLL after CV events, we first determined the age- and sex-specific incidences, twenty-year risks of incident CV events, including acute myocardial infarction (AMI), stroke and congestive heart failure (CHF), stratified by the presence of diabetes, de novo diabetes after ESRD or ESRD by using two representative national cohorts. Individuals were excluded if aged below 18 years or the presence of previous CV events or malignancy before enrollment. Cox proportional hazard models were also constructed with adjustments for competing risk of mortality. A total 648,851 non-ESRD individuals and 71,397 ESRD patients, including 53,342 and 34,754 diabetic patients respectively, were followed up during 1998-2009. A monotonic risk pattern of CV-related incidences was noted with the presence of diabetes, ESRD or both, respectively, after stratified by age and sex. De novo diabetes showed similar increased risks for CV incidences, especially AMI and stroke. There is a multiplicatively synergistic effect of diabetes and ESRD for CV related risks, especially for AMI and stroke, of which the adjusted hazard ratios (aHRs) [95% confidence intervals] were 5.24 [4.83-5.68] and 2.43[2.32-2.55], respectively in comparison with people without diabetes or ESRD; de novo diabetes after ESRD had similar effects with aHRs of 4.12[3.49-4.87] and 1.75[1.57-1.95], respectively. Second, we further followed up these individuals with incident CV events till mortality or the end of 2009. We estimated age- and sex-specific survival rates by the Kaplan-Meier method, which were further extrapolated to lifetime to estimate the LE and EYLL based on an assumption of constant excess hazard. Cox proportional hazard models were also constructed to validate the results. Of 35,793 patients with incident CV events, the LE and EYLL of the non-ESRD/non-diabetes group ranged from 2.08-8.07 and 3.07-10.25 years in patients aged ≥ 65 years, respectively, and 4.09-17.28 and 6.60-22.45 years in those aged under 65. Diabetes and ESRD would result in additional losses of 0.57-6.59 and 2.32-8.74 EYLL, while de novo diabetes after ESRD led to the highest EYLL. After multivariate adjustment, we found a monotonic increase in the relative hazard with the presence of diabetes, ESRD, and both. The effect of de novo diabetes after ESRD on mortality was still the highest, especially among people followed for more than 4.5 years. Finally, we performed the cost-effectiveness analysis between different dialysis modalities. 4285 pairs of incident HD and PD patients were selected from a national cohort after matching for clinical characteristics and propensity scores. Lifetime survival and healthcare expenditure were estimated by data of 14-year follow-up and subsequently extrapolated to lifetime under the assumption of constant excess hazard. A cross-sectional EQ-5D survey were performed in 12 dialysis units, which resulted in 179 matched pairs. The product of survival probability and the mean utility value at each time point, estimated by kernel-smoothing method, were summed up throughout lifetime to obtain the quality-adjusted life expectancy (QALE). The results revealed the estimated life expectancy between HD and PD were nearly equal (19.11 versus 19.08 years). The mean utility values, QALE were also similar, whereas average lifetime healthcare costs were higher in HD than PD (237,795 versus 204,442 USD) and the cost-effectiveness ratios for PD and HD were 13,681 and 16,643 USD per quality-adjusted life year, respectively. In conclusion, our results indicated diabetes and ESRD synergistically increase risks of CV events. Diabetes, especially de novo diabetes after ESRD, and ESRD itself, are both associated with increased risk of mortality and extra loss of LE after various CV events. Intensive proactive and/or reactive preventions are warranted to reduce the CV events and potential loss of life in these cases. When considering the cost-effectiveness between dialysis modality, PD is a more cost-effective therapy than HD, of which the major determinant was the total medical costs paid for the dialysis modality and its associated complications.
論文目次 Contents:
Chapter 1. Introduction……………………………………………………………...1
1.1 The cardiovascular events in patients with diabetes or end-stage renal disease…………………………………………………………………...2
1.2 The life expectancy in patients with diabetes or end-stage renal disease..4
1.3 The cost-effectiveness analysis of dialysis modality…………………….6
1.4 Thesis aims………………………………………………………………8
Chapter 2. Diabetes and end-stage renal disease synergistically contribute to increased incidence of cardiovascular events…………………………10
2.1 Background and Aims…………………………………………………..10
2.2 Materials and Methods………………………………………………….13
2.3 Results…………………………………………………………………..19
2.4 Discussion………………………………………………………………24
2.5 Tables and Figures………………………………………………………31
Chapter 3. Saving of life expectancy from prevention of cardiovascular events in patients with diabetes and/or end stage renal disease………………..47
3.1 Background and Aims…………………………………………………..47
3.2 Materials and Methods………………………………………………….50
3.3 Results…………………………………………………………………..55
3.4 Discussion………………………………………………………………58
3.5 Tables and Figures………………………………………………………63
Chapter 4. Comparison of Cost-effectiveness between hemodialysis and peritoneal dialysis………………………………………………………..78
4.1 Background and Aims…………………………………………………..78
4.2 Materials and Methods………………………………………………….81
4.3 Results…………………………………………………………………..87
4.4 Discussion………………………………………………………………91
4.5 Tables and Figures………………………………………………………96
Chapter 5. General Discussion, Conclusions and Prospects……………………115
5.1 The main findings of the thesis………………………………………..115
5.2 Methodological considerations………………………………………..117
5.3 Prospects………………………………………………………………120
Bibliography……………………………………………………………………….122
Publication lists……………………………………………………………………132 
List of Tables
2-1. Demographic and clinical characteristics of the end stage renal disease (ESRD) and non-ESRD populations stratified by diabetes (for those with first occurring composite cardiovascular events, including acute myocardial infarction, stroke and congestive heart failure)……………...………………………………………………31
2-2. Demographic and clinical characteristics of the end stage renal disease (ESRD) and non-ESRD populations stratified by diabetes (for those with first occurring cardiovascular events of acute myocardial infarction).………………………………32
2-3. Demographic and clinical characteristics of the end stage renal disease (ESRD) and non-ESRD populations stratified by diabetes (for those with first occurring cardiovascular events of stroke).……………..………………………………………33
2-4. Demographic and clinical characteristics of the end stage renal disease (ESRD) and non-ESRD populations stratified by diabetes (for those with first occurring cardiovascular events of congestive heart failure)…………………………………...34
2-5. Incidence rates (IR, per 1000 patient-years) of acute myocardial infarction (AMI), stroke, and congestive heart failure (CHF) in the study population stratified by end stage renal disease (ESRD) and diabetes.…………………………………….…35
2-6. Numbers of new events of acute myocardial infarction (AMI), stroke, and congestive heart failure (CHF) in the study population stratified by end stage renal disease (ESRD) and diabetes.…………………………………………………….….36
2-7. Age- and sex-specific incidence rates (IR, per 1000 patient-years) of composite cardiovascular (CV) events (percentages of acute myocardial infarction, stroke, and congestive heart failure) stratified by end stage renal disease (ESRD) and diabetes..37
2-8. Adjusted hazard ratios (with 95% confidence interval) of the proportional hazard model for acute myocardial infarction (AMI), stroke, congestive heart failure (CHF) and composite cardiovascular (CV) events (including AMI, stroke, and CHF) after accounting for competing risk of mortality……………………………………….…39
2-9. Age- and sex-specific cumulative incidence rates during the whole study period of 12 years (1998-2009) after adjustment for competing risk of mortalities for composite cardiovascular events in panel (a) (including acute myocardial infarction [AMI], stroke, and congestive heart failure [CHF]) and each separate cardiovascular event in panel (b) stratified by end-stage renal disease (ESRD) and diabetes……….40
3-1. International Statistical Classification of Diseases and Related Health Problems, 9th edition (ICD-9) codes used to identify the associated comorbidities in the study..63
3-2. Demographic and clinical characteristics of patients with composite cardiovascular events (either acute myocardial infarction [AMI], stroke or congestive heart failure [CHF]) stratified by diabetes end stage renal disease (ESRD)………....64
3-3. Demographic and clinical characteristics of patients with first acute myocardial infarction (AMI) stratified by diabetes end stage renal disease (ESRD)………….…66
3-4. Demographic and clinical characteristics of patients with first stroke stratified by diabetes end stage renal disease (ESRD).……………………………………………67
3-5. Demographic and clinical characteristics of patients with first congestive heart failure (CHF) stratified by diabetes end stage renal disease (ESRD).…………….…68
3-6. Age- and sex-specific survival rates (SR), life expectancy (LE) and expected years of life lost (EYLL) of specific cardiovascular (CV) events (acute myocardial infarction [AMI], stroke, and congestive heart failure [CHF]) stratified by end stage renal disease (ESRD) and diabetes.…………………………………….……………69
3.7. Age- and sex-specific survival rates (SR), life expectancy (LE) and expected years of life lost (EYLL) of composite cardiovascular (CV) events (acute myocardial infarction [AMI], stroke, and congestive heart failure [CHF]) stratified by end stage renal disease (ESRD) and diabetes.………………………………………………….71
3-8. Adjusted hazards ratios for all-cause mortality after various cardiovascular events (composite cardiovascular [CV] events, acute myocardial infarction [AMI], stroke and congestive heart failure [CHF]) in the study population (time-dependent cox model) stratified by diabetes, end-stage renal disease (ESRD) and de novo diabetes after ESRD.………………………………………………………………………….72
4-1. International Statistical Classification of Diseases and Related Health Problems, 9th edition codes used to identify the associated comorbidities in the study……….96
4-2. Mean utility values of the cross-sectional samples stratified by age and dialysis modalities.…………………………………………………………………………...97
4-3. Comparison of demographic and clinical characteristics of dialysis patients among the national cohort, respondents and non-respondents of cross-sectional sample stratified by modality (HD: hemodialysis, PD: peritoneal dialysis).………..98
4-4. Comparison of demographic and clinical characteristics between dialysis patients after matching for individual characteristics, major comorbidities, and propensity score stratified by hemodialysis (HD) and peritoneal dialysis (PD).…………….....100
4-5. Frequency distributions of various EQ-5D domain scores, utility values and visual analogue scales (VAS) for cross-sectional samples of dialysis patients after and before matching.…………………………………………………………………….101
4-6. Comparison of demographic and clinical characteristics between dialysis patients after 1:1 matching for individual characteristics, employment status, major comorbidities, and propensity score stratified by hemodialysis (HD) and peritoneal dialysis (PD).………………………………………………………………………..102
4-7. Comparison of frequency distributions of EQ-5D domain scores, utility values and visual analogue scales (VAS) between dialysis patients after 1:1 matching for individual characteristics, employment status, major comorbidities, and propensity score stratified by hemodialysis and peritoneal dialysis……………………………103
4-8. Comparison of cost-effectiveness for maintenance hemodialysis (HD) and peritoneal dialysis (PD): Lifetime survival functions were estimated from 1:1 matched national cohorts (n=4285 pairs) based on 14 years of follow-up plus extrapolation, and utility values measured for current patients after matching (n=179 pairs)…….104
4-9. Comparison of demographic and clinical characteristics between 2:1 matching of hemodialysis (HD) and peritoneal dialysis (PD) patients for individual characteristics, major comorbidities, and propensity score.………………………………………...105
4-10. Comparison of cost-effectiveness for maintenance hemodialysis (HD) and peritoneal dialysis (PD): Lifetime survival functions were estimated from 2:1 matched national cohorts (numbers of HD and PD: 6984 and 3492, respectively) based on 14 years of follow-up plus extrapolation, and utility values measured for current patients after matching (n=179 pairs).……………………………………………………….106
4-11. Comparison of EQ-5D mean utility values between the total cross-sectional samples of dialysis patients and the general population either before or after matched by age and sex.……………………………………………………………………...107


List of Figures
2-1. Flow chart of the establishment of the cohort…………………………………..42
2-2. Kaplan-Meier curves for cumulative CV composite event-free (acute myocardial infarction, stroke or congestive heart failure) (Panel A) or individual CV event-free survival rate (Panels B, C and D) in patients stratified by the presence of end-stage renal disease (ESRD), diabetes or de novo diabetes after ESRD.……………...……43
3-1. Overall survival rate after occurring of composite CV events (acute myocardial infarction, stroke or congestive heart failure) (Panel A) or individual CV event (Panels B, C and D) in patients stratified by the presence of end-stage renal disease (ESRD), diabetes or de novo diabetes after ESRD.…………………………………………....74
4-1. The flow chart of the establishment of the national dialysis cohort and cross-sectional samples to estimate quality-adjusted life expectancy (QALE) and cost per quality adjusted life year (QALY).………………………………………………….108
4-2. Estimation of quality-adjusted life expectancy (QALE) for patients under hemodialysis (HD) and peritoneal dialysis (PD). Lifetime survival curves of HD and PD were depicted in the black and red lines, respectively. The QALE was estimated by summarizing the total area under the survival curve.…………………………....109
4-3. (a) Average monthly costs for inpatient and outpatient healthcare expenditures and (b) monthly proportions of outpatient costs within total healthcare expenditures of patients selected from 1:1 matched hemodialysis (HD) and peritoneal dialysis (PD) during the 13-year follow-up period.…………………………………………….…110
Figure 4-4. The comparison of survival curves between 2:1 matched hemodialysis (HD) and peritoneal dialysis (PD) patients during a 14-year follow-up period…....111
4-5. (a) Average monthly costs for inpatient and outpatient healthcare expenditures and (b) monthly proportions of outpatient costs within total healthcare expenditures of patients selected from 2:1 matched hemodialysis (HD) and peritoneal dialysis (PD) during the follow-up period.……………………………………………………..…112
4-6. The comparison of survival curves between 1:1 matched hemodialysis (HD) and peritoneal dialysis (PD) patients during a 14-year follow-up period.………………113
4-7. Dynamic changes of mean EQ-5D utility values after initiation of dialysis estimated by kernel smoothing method for 179 pairs of matched patients under hemodialysis (HD, left panel) and peritoneal dialysis (PD, right panel) who were collected cross-sectionally from 12 dialysis units.……………………………….…114
參考文獻 Bibliography:
1.Couser, W. G., Remuzzi, G., Mendis, S. & Tonelli, M. The contribution of chronic kidney disease to the global burden of major noncommunicable diseases. Kidney Int 80, 1258-1270, doi:10.1038/ki.2011.368 (2011).
2.Coresh, J. et al. Prevalence of chronic kidney disease in the United States. JAMA 298, 2038-2047, doi:10.1001/jama.298.17.2038 (2007).
3.Ganesh, S. K., Hulbert-Shearon, T., Port, F. K., Eagle, K. & Stack, A. G. Mortality differences by dialysis modality among incident ESRD patients with and without coronary artery disease. J. Am. Soc. Nephrol. 14, 415-424 (2003).
4.US Renal Data System. USRDS 2015. Annual data report: atlas of chronic kidney disease and end-stage renal disease in the United States, 2015. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD. Available at: https://www.usrds.org/adr.aspx. (Accessed:11 May 2016).
5.US Renal Data System. USRDS 2012. Annual data report: atlas of chronic kidney disease and end-stage renal disease in the United States, 2012. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD. Available at: https://www.usrds.org/atlas12.aspx. (Accessed:11 May 2016).
6.International Diabetes Federation. IDF Diabetes Atlas - 7th edition. (2015). Available at: http://www.diabetesatlas.org. (Accessed:11 May 2016).
7.Haffner, S. M., Lehto, S., Ronnemaa, T., Pyorala, K. & Laakso, M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. N. Engl. J. Med. 339, 229-234, doi:10.1056/NEJM199807233390404 (1998).
8.Stamler, J., Vaccaro, O., Neaton, J. D. & Wentworth, D. Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care 16, 434-444 (1993).
9.Longenecker, J. C. et al. Traditional cardiovascular disease risk factors in dialysis patients compared with the general population: the CHOICE Study. J. Am. Soc. Nephrol. 13, 1918-1927 (2002).
10.Xue, J. L., Frazier, E. T., Herzog, C. A. & Collins, A. J. Association of heart disease with diabetes and hypertension in patients with ESRD. Am. J. Kidney Dis. 45, 316-323 (2005).
11.Gansevoort, R. T. et al. Chronic kidney disease and cardiovascular risk: epidemiology, mechanisms, and prevention. Lancet 382, 339-352, doi:10.1016/S0140-6736(13)60595-4 (2013).
12.Fox, C. S. et al. Trends in cardiovascular complications of diabetes. JAMA 292, 2495-2499, doi:10.1001/jama.292.20.2495 (2004).
13.Roberts, M. A., Polkinghorne, K. R., McDonald, S. P. & Ierino, F. L. Secular trends in cardiovascular mortality rates of patients receiving dialysis compared with the general population. Am. J. Kidney Dis. 58, 64-72, doi:10.1053/j.ajkd.2011.01.024 (2011).
14.Collins, A. J. et al. Chronic kidney disease and cardiovascular disease in the Medicare population. Kidney Int. Suppl. S24-31 (2003).
15.Baigent, C., Burbury, K. & Wheeler, D. Premature cardiovascular disease in chronic renal failure. Lancet 356, 147-152, doi:10.1016/S0140-6736(00)02456-9 (2000).
16.Tonelli, M. et al. Risk of coronary events in people with chronic kidney disease compared with those with diabetes: a population-level cohort study. Lancet 380, 807-814, doi:10.1016/S0140-6736(12)60572-8 (2012).
17.Emerging Risk Factors, C. et al. Association of Cardiometabolic Multimorbidity With Mortality. JAMA 314, 52-60, doi:10.1001/jama.2015.7008 (2015).
18.Chang, Y. T., Liu, C. C., Tsai, L. M., Li, C. Y. & Sung, J. M. Separate and joint effects of diabetes mellitus and chronic kidney disease on the risk of acute coronary syndrome: a population-based cohort study. Medicine (Baltimore) 93, e261, doi:10.1097/MD.0000000000000261 (2014).
19.Herzog, C. A. Acute myocardial infarction in patients with end-stage renal disease. Kidney Int. Suppl. 71, S130-133 (1999).
20.Roy, P., Bouchard, J., Amyot, R. & Madore, F. Prescription patterns of pharmacological agents for left ventricular systolic dysfunction among hemodialysis patients. Am. J. Kidney Dis. 48, 645-651, doi:10.1053/j.ajkd.2006.06.006 (2006).
21.Saaddine, J. B. et al. Improvements in diabetes processes of care and intermediate outcomes: United States, 1988-2002. Ann. Intern. Med. 144, 465-474 (2006).
22.Sirois, C., Moisan, J., Poirier, P. & Gregoire, J. P. Suboptimal use of cardioprotective drugs in newly treated elderly individuals with type 2 diabetes. Diabetes Care 30, 1880-1882, doi:10.2337/dc06-2257 (2007).
23.Charytan, D. & Kuntz, R. E. The exclusion of patients with chronic kidney disease from clinical trials in coronary artery disease. Kidney Int. 70, 2021-2030, doi:10.1038/sj.ki.5001934 (2006).
24.US Renal Data System. USRDS 2011. Annual data report: atlas of chronic kidney disease and end-stage renal disease in the United States, 2011. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD. Available at: https://www.usrds.org/atlas11.aspx. (Accessed: 2 May 2012)
25.Sarnak, M. J. Cardiovascular complications in chronic kidney disease. Am. J. Kidney Dis. 41, 11-17 (2003).
26.Foley, R. N., Parfrey, P. S. & Sarnak, M. J. Clinical epidemiology of cardiovascular disease in chronic renal disease. Am. J. Kidney Dis. 32, S112-119 (1998).
27.Perneger, T. V., Klag, M. J. & Whelton, P. K. Cause of death in patients with end-stage renal disease: death certificates vs registry reports. Am. J. Public Health 83, 1735-1738 (1993).
28.Mukamal, K. J. et al. Impact of diabetes on long-term survival after acute myocardial infarction: comparability of risk with prior myocardial infarction. Diabetes Care 24, 1422-1427 (2001).
29.Icks, A., Claessen, H., Morbach, S., Glaeske, G. & Hoffmann, F. Time-dependent impact of diabetes on mortality in patients with stroke: survival up to 5 years in a health insurance population cohort in Germany. Diabetes Care 35, 1868-1875, doi:10.2337/dc11-2159 (2012).
30.Dries, D. L., Sweitzer, N. K., Drazner, M. H., Stevenson, L. W. & Gersh, B. J. Prognostic impact of diabetes mellitus in patients with heart failure according to the etiology of left ventricular systolic dysfunction. J. Am. Coll. Cardiol. 38, 421-428 (2001).
31.Miettinen, H. et al. Impact of diabetes on mortality after the first myocardial infarction. The FINMONICA Myocardial Infarction Register Study Group. Diabetes Care 21, 69-75 (1998).
32.Herzog, C. A., Ma, J. Z. & Collins, A. J. Long-term outcome of dialysis patients in the United States with coronary revascularization procedures. Kidney Int. 56, 324-332, doi:10.1046/j.1523-1755.1999.00540.x (1999).
33.Herzog, C. A., Ma, J. Z. & Collins, A. J. Poor long-term survival after acute myocardial infarction among patients on long-term dialysis. N. Engl. J. Med. 339, 799-805, doi:10.1056/NEJM199809173391203 (1998).
34.Iseki, K., Fukiyama, K. & Okawa Dialysis Study, G. Clinical demographics and long-term prognosis after stroke in patients on chronic haemodialysis. The Okinawa Dialysis Study (OKIDS) Group. Nephrol. Dial. Transplant. 15, 1808-1813 (2000).
35.Wetmore, J. B. et al. Relationship between stroke and mortality in dialysis patients. Clin. J. Am. Soc. Nephrol. 10, 80-89, doi:10.2215/CJN.02900314 (2015).
36.Banerjee, D., Ma, J. Z., Collins, A. J. & Herzog, C. A. Long-term survival of incident hemodialysis patients who are hospitalized for congestive heart failure, pulmonary edema, or fluid overload. Clin. J. Am. Soc. Nephrol. 2, 1186-1190, doi:10.2215/CJN.01110307 (2007).
37.Haenszel, W. A standardized rate for mortality defined in units of lost years of life. Am. J. Public Health Nations Health 40, 17-26 (1950).
38.Grover, S. A. et al. Years of life lost and healthy life-years lost from diabetes and cardiovascular disease in overweight and obese people: a modelling study. Lancet Diabetes Endocrinol. 3, 114-122, doi:10.1016/S2213-8587(14)70229-3 (2015).
39.Hayes, A. J., Leal, J., Kelman, C. W. & Clarke, P. M. Risk equations to predict life expectancy of people with Type 2 diabetes mellitus following major complications: a study from Western Australia. Diabetes Med. 28, 428-435, doi:10.1111/j.1464-5491.2010.03189.x (2011).
40.Klarenbach, S. W., Tonelli, M., Chui, B. & Manns, B. J. Economic evaluation of dialysis therapies. Nat. Rev. Nephrol. 10, 644-652, doi:10.1038/nrneph.2014.145 (2014).
41.Weidmann, P., Beretta-Piccoli, C., Steffen, F., Blumberg, A. & Reubi, F. C. Hypertension in terminal renal failure. Kidney Int. 9, 294-301 (1976).
42.Levey, A. S. et al. Chronic kidney disease as a global public health problem: approaches and initiatives - a position statement from Kidney Disease Improving Global Outcomes. Kidney Int. 72, 247-259, doi:10.1038/sj.ki.5002343 (2007).
43.Haller, M., Gutjahr, G., Kramar, R., Harnoncourt, F. & Oberbauer, R. Cost-effectiveness analysis of renal replacement therapy in Austria. Nephrol. Dial. Transplant. 26, 2988-2995, doi:10.1093/ndt/gfq780 (2011).
44.Howard, K. et al. The cost-effectiveness of increasing kidney transplantation and home-based dialysis. Nephrology (Carlton) 14, 123-132, doi:10.1111/j.1440-1797.2008.01073.x (2009).
45.Chanouzas, D., Ng, K. P., Fallouh, B. & Baharani, J. What influences patient choice of treatment modality at the pre-dialysis stage? Nephrol. Dial. Transplant. 27, 1542-1547, doi:10.1093/ndt/gfr452 (2012).
46.Davies, S. J. Peritoneal dialysis--current status and future challenges. Nat. Rev. Nephrol. 9, 399-408, doi:10.1038/nrneph.2013.100 (2013).
47.Li, P. K. & Chow, K. M. Peritoneal dialysis-first policy made successful: perspectives and actions. Am. J. Kidney Dis. 62, 993-1005, doi:10.1053/j.ajkd.2013.03.038 (2013).
48.Peeters, P., Rublee, D., Just, P. M. & Joseph, A. Analysis and interpretation of cost data in dialysis: review of Western European literature. Health Policy 54, 209-227 (2000).
49.McDonald, S. P., Marshall, M. R., Johnson, D. W. & Polkinghorne, K. R. Relationship between dialysis modality and mortality. J. Am. Soc. Nephrol. 20, 155-163, doi:10.1681/ASN.2007111188 (2009).
50.Collins, A. J. et al. Mortality risks of peritoneal dialysis and hemodialysis. Am. J. Kidney Dis. 34, 1065-1074, doi:10.1016/S0272-6386(99)70012-0 (1999).
51.Murphy, S. W. et al. Comparative mortality of hemodialysis and peritoneal dialysis in Canada. Kidney Int. 57, 1720-1726, doi:10.1046/j.1523-1755.2000.00017.x (2000).
52.Stack, A. G., Molony, D. A., Rahman, N. S., Dosekun, A. & Murthy, B. Impact of dialysis modality on survival of new ESRD patients with congestive heart failure in the United States. Kidney Int. 64, 1071-1079, doi:10.1046/j.1523-1755.2003.00165.x (2003).
53.Vonesh, E. F., Snyder, J. J., Foley, R. N. & Collins, A. J. The differential impact of risk factors on mortality in hemodialysis and peritoneal dialysis. Kidney international 66, 2389-2401, doi:10.1111/j.1523-1755.2004.66028.x (2004).
54.Jaar, B. G. et al. Comparing the risk for death with peritoneal dialysis and hemodialysis in a national cohort of patients with chronic kidney disease. Ann. Intern. Med. 143, 174-183 (2005).
55.Weinhandl, E. D. et al. Propensity-matched mortality comparison of incident hemodialysis and peritoneal dialysis patients. J. Am. Soc. Nephrol. 21, 499-506, doi:10.1681/ASN.2009060635 (2010).
56.Nelson, C. B., Port, F. K., Wolfe, R. A. & Guire, K. E. Comparison of continuous ambulatory peritoneal dialysis and hemodialysis patient survival with evaluation of trends during the 1980s. J. Am. Soc. Nephrol. 3, 1147-1155 (1992).
57.Mehrotra, R., Chiu, Y. W., Kalantar-Zadeh, K., Bargman, J. & Vonesh, E. Similar outcomes with hemodialysis and peritoneal dialysis in patients with end-stage renal disease. Arch. Intern. Med. 171, 110-118, doi:10.1001/archinternmed.2010.352 (2011).
58.Liem, Y. S., Wong, J. B., Hunink, M. G., de Charro, F. T. & Winkelmayer, W. C. Comparison of hemodialysis and peritoneal dialysis survival in The Netherlands. Kidney Int. 71, 153-158, doi:10.1038/sj.ki.5002014 (2007).
59.Lukowsky, L. R. et al. Comparing mortality of peritoneal and hemodialysis patients in the first 2 years of dialysis therapy: a marginal structural model analysis. Clin. J. Am. Soc. Nephrol. 8, 619-628, doi:10.2215/CJN.04810512 (2013).
60.Kim, H. et al. A population-based approach indicates an overall higher patient mortality with peritoneal dialysis compared to hemodialysis in Korea. Kidney Int. 86, 991-1000, doi:10.1038/ki.2014.163 (2014).
61.Kumar, V. A., Sidell, M. A., Jones, J. P. & Vonesh, E. F. Survival of propensity matched incident peritoneal and hemodialysis patients in a United States health care system. Kidney Int. 86, 1016-1022, doi:10.1038/ki.2014.224 (2014).
62.Harris, S. A., Lamping, D. L., Brown, E. A., Constantinovici, N. & North Thames Dialysis Study, G. Clinical outcomes and quality of life in elderly patients on peritoneal dialysis versus hemodialysis. Perit. Dial. Int. 22, 463-470 (2002).
63.Korevaar, J. C. et al. Effect of starting with hemodialysis compared with peritoneal dialysis in patients new on dialysis treatment: a randomized controlled trial. Kidney Int. 64, 2222-2228, doi:10.1046/j.1523-1755.2003.00321.x (2003).
64.Manns, B. et al. Quality of life in patients treated with hemodialysis or peritoneal dialysis: what are the important determinants? Clin. Nephrol. 60, 341-351 (2003).
65.Kutner, N. G., Zhang, R., Barnhart, H. & Collins, A. J. Health status and quality of life reported by incident patients after 1 year on haemodialysis or peritoneal dialysis. Nephrol. Dial. Transplant. 20, 2159-2167, doi:10.1093/ndt/gfh973 (2005).
66.Wu, A. W. et al. Developing a health-related quality-of-life measure for end-stage renal disease: The CHOICE Health Experience Questionnaire. Am. J. Kidney Dis. 37, 11-21 (2001).
67.Wasserfallen, J. B. et al. Quality of life on chronic dialysis: comparison between haemodialysis and peritoneal dialysis. Nephrol. Dial. Transplant. 19, 1594-1599, doi:10.1093/ndt/gfh175 (2004).
68.Cameron, J. I., Whiteside, C., Katz, J. & Devins, G. M. Differences in quality of life across renal replacement therapies: a meta-analytic comparison. Am. J. Kidney Dis. 35, 629-637 (2000).
69.Wyld, M., Morton, R. L., Hayen, A., Howard, K. & Webster, A. C. A systematic review and meta-analysis of utility-based quality of life in chronic kidney disease treatments. PLoS Med. 9, e1001307, doi:10.1371/journal.pmed.1001307 (2012).
70.World Health Organization. Preventing chronic diseases: a vital investment. 2005.
71.Meguid El Nahas, A. & Bello, A. K. Chronic kidney disease: the global challenge. Lancet 365, 331-340, doi:10.1016/S0140-6736(05)17789-7 (2005).
72.Levey, A. S. et al. National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann. Intern. Med. 139, 137-147 (2003).
73.National Health Research Institutes: National Health Insurance ResearchDatabase. Available from: http://www.nhri.org.tw/nhird/date_01. html#_edn1. (Assess: 2 May 2012)
74.Bureau of National Health Insurance. 2001 National Health Insurance Annual Statistical Report. Taipei, Taiwan; 2002.
75.Lai, M. N., Wang, S. M., Chen, P. C., Chen, Y. Y. & Wang, J. D. Population-based case-control study of Chinese herbal products containing aristolochic acid and urinary tract cancer risk. J. Natl. Cancer Inst. 102, 179-186, doi:10.1093/jnci/djp467 (2010).
76.Wu, C. Y. et al. Early Helicobacter pylori eradication decreases risk of gastric cancer in patients with peptic ulcer disease. Gastroenterology 137, 1641-1648 e1641-1642, doi:10.1053/j.gastro.2009.07.060 (2009).
77.Tsan, Y. T., Lee, C. H., Wang, J. D. & Chen, P. C. Statins and the risk of hepatocellular carcinoma in patients with hepatitis B virus infection. J. Clin. Oncol. 30, 623-630, doi:10.1200/JCO.2011.36.0917 (2012).
78.JD., W. Basic principles and practical applications in epidemiological research. Singapore, World Scientific 2002:p.135-137.
79.W., D. Cancer registration and its techniques. Lyon, International agency for research on cancer 1978:p.162-163.
80.Yang, W. C., Hwang, S. J. & Taiwan Society of, N. Incidence, prevalence and mortality trends of dialysis end-stage renal disease in Taiwan from 1990 to 2001: the impact of national health insurance. Nephrol. Dial. Transplant. 23, 3977-3982, doi:10.1093/ndt/gfn406 (2008).
81.Sarnak, M. J. & Levey, A. S. Cardiovascular disease and chronic renal disease: a new paradigm. Am. J. Kidney Dis. 35, S117-131 (2000).
82.Tripepi, G. et al. Inflammation and asymmetric dimethylarginine for predicting death and cardiovascular events in ESRD patients. Clin. J. Am. Soc. Nephrol. 6, 1714-1721, doi:10.2215/CJN.11291210 (2011).
83.Krzyzanowska, K., Mittermayer, F., Wolzt, M. & Schernthaner, G. Asymmetric dimethylarginine predicts cardiovascular events in patients with type 2 diabetes. Diabetes Care 30, 1834-1839, doi:10.2337/dc07-0019 (2007).
84.Hayden, J. M. & Reaven, P. D. Cardiovascular disease in diabetes mellitus type 2: a potential role for novel cardiovascular risk factors. Curr. Opin. Lipidol. 11, 519-528 (2000).
85.Blacher, J. et al. Impact of aortic stiffness on survival in end-stage renal disease. Circulation 99, 2434-2439 (1999).
86.Barreto, F. C. et al. Serum indoxyl sulfate is associated with vascular disease and mortality in chronic kidney disease patients. Clin. J. Am. Soc. Nephrol. 4, 1551-1558, doi:10.2215/CJN.03980609 (2009).
87.Ritz, E., Dikow, R., Adamzcak, M. & Zeier, M. Congestive heart failure due to systolic dysfunction: the Cinderella of cardiovascular management in dialysis patients. Semin. Dial. 15, 135-140 (2002).
88.Cheung, A. K. et al. Atherosclerotic cardiovascular disease risks in chronic hemodialysis patients. Kidney Int. 58, 353-362, doi:10.1046/j.1523-1755.2000.00173.x (2000).
89.Prinsen, B. H. et al. A broad-based metabolic approach to study VLDL apoB100 metabolism in patients with ESRD and patients treated with peritoneal dialysis. Kidney Int. 65, 1064-1075, doi:10.1111/j.1523-1755.2004.00466.x (2004).
90.Anand, S. S. et al. Risk factors for myocardial infarction in women and men: insights from the INTERHEART study. Eur. Heart J. 29, 932-940, doi:10.1093/eurheartj/ehn018 (2008).
91.Kappert, K. et al. Impact of sex on cardiovascular outcome in patients at high cardiovascular risk: analysis of the Telmisartan Randomized Assessment Study in ACE-Intolerant Subjects With Cardiovascular Disease (TRANSCEND) and the Ongoing Telmisartan Alone and in Combination With Ramipril Global End Point Trial (ONTARGET). Circulation 126, 934-941, doi:10.1161/CIRCULATIONAHA.111.086660 (2012).
92.Roger, V. L. et al. Executive summary: heart disease and stroke statistics--2012 update: a report from the American Heart Association. Circulation 125, 188-197, doi:10.1161/CIR.0b013e3182456d46 (2012).
93.Lam, C. S. & Little, W. C. Sex and cardiovascular risk: are women advantaged or men disadvantaged? Circulation 126, 913-915, doi:10.1161/CIRCULATIONAHA.112.121582 (2012).
94.Sutton-Tyrrell, K. et al. Sex-hormone-binding globulin and the free androgen index are related to cardiovascular risk factors in multiethnic premenopausal and perimenopausal women enrolled in the Study of Women Across the Nation (SWAN). Circulation 111, 1242-1249, doi:10.1161/01.CIR.0000157697.54255.CE (2005).
95.Karakitsos, D. et al. Androgen deficiency and endothelial dysfunction in men with end-stage kidney disease receiving maintenance hemodialysis. Am. J. Nephrol. 26, 536-543, doi:10.1159/000097816 (2006).
96.Khan, N. A. et al. Ethnicity and sex affect diabetes incidence and outcomes. Diabetes Care 34, 96-101, doi:10.2337/dc10-0865 (2011).
97.O'Donnell, M. J. et al. Risk factors for ischaemic and intracerebral haemorrhagic stroke in 22 countries (the INTERSTROKE study): a case-control study. Lancet 376, 112-123, doi:10.1016/S0140-6736(10)60834-3 (2010).
98.Yusuf, S. et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 364, 937-952, doi:10.1016/S0140-6736(04)17018-9 (2004).
99.Saran, R. et al. US Renal Data System 2014 Annual Data Report: Epidemiology of Kidney Disease in the United States. Am. J. Kidney Dis. 65, A7, doi:10.1053/j.ajkd.2015.05.001 (2015).
100.Hwang, J. S. & Wang, J. D. Monte Carlo estimation of extrapolation of quality-adjusted survival for follow-up studies. Stat. Med. 18, 1627-1640 (1999).
101.Galvin, J. E. et al. The AD8: a brief informant interview to detect dementia. Neurology 65, 559-564, doi:10.1212/01.wnl.0000172958.95282.2a (2005).
102.Hung, M. C., Sung, J. M., Chang, Y. T., Hwang, J. S. & Wang, J. D. Estimation of physical functional disabilities and long-term care needs for patients under maintenance hemodialysis. Med. Care 52, 63-70, doi:10.1097/MLR.0000000000000010 (2014).
103.Fang, C. T. et al. Life expectancy of patients with newly-diagnosed HIV infection in the era of highly active antiretroviral therapy. QJM 100, 97-105, doi:10.1093/qjmed/hcl141 (2007).
104.McDonald, K. M., Miller, P. D., Anderson, R. J., Berl, T. & Schrier, R. W. Hormonal control of renal water excretion. Kidney Int. 10, 38-45 (1976).
105.Lee, H. Y., Hwang, J. S., Jeng, J. S. & Wang, J. D. Quality-adjusted life expectancy (QALE) and loss of QALE for patients with ischemic stroke and intracerebral hemorrhage: a 13-year follow-up. Stroke 41, 739-744, doi:10.1161/STROKEAHA.109.573543 (2010).
106.Chu, P. C., Wang, J. D., Hwang, J. S. & Chang, Y. Y. Estimation of life expectancy and the expected years of life lost in patients with major cancers: extrapolation of survival curves under high-censored rates. Value Health 11, 1102-1109, doi:10.1111/j.1524-4733.2008.00350.x (2008).
107.Hung, M. C. et al. Cost per QALY (quality-adjusted life year) and lifetime cost of prolonged mechanical ventilation in Taiwan. PloS One 7, e44043, doi:10.1371/journal.pone.0044043 (2012).
108.Hung, M. C. et al. Life expectancies and incidence rates of patients under prolonged mechanical ventilation: a population-based study during 1998 to 2007 in Taiwan. Crit. Care 15, R107, doi:10.1186/cc10128 (2011).
109.Yang, D. C. et al. Estimation of expected life-years saved from successful prevention of end-stage renal disease in elderly patients with diabetes: a nationwide study from Taiwan. Diabetes Care 35, 2279-2285, doi:10.2337/dc12-0545 (2012).
110.Kao, T. W. et al. Life expectancy, expected years of life lost and survival of hemodialysis and peritoneal dialysis patients. J. Nephrol. 23, 677-682 (2010).
111.Lilienfeld, D. S. a. D. E. Lilienfeld's Foundations of Epidemiology 4th Edition. Oxford University Press. (2015).
112.Christopher J. L. Murray, J. A. S., Colin D. Mathers and Alan D. Lopez. Summary Measures of Population Health. Concepts, Ethics, Measurement and Applications. World Health Organization Geneva. (2002)
113.Chang, Y. T., Wu, J. L., Hsu, C. C., Wang, J. D. & Sung, J. M. Diabetes and end-stage renal disease synergistically contribute to increased incidence of cardiovascular events: a nationwide follow-up study during 1998-2009. Diabetes Care 37, 277-285, doi:10.2337/dc13-0781 (2014).
114.Tien, K. J. et al. Epidemiology and mortality of new-onset diabetes after dialysis: Taiwan national cohort study. Diabetes Care 36, 3027-3032, doi:10.2337/dc12-2148 (2013).
115.Szeto, C. C. et al. New-onset hyperglycemia in nondiabetic chinese patients started on peritoneal dialysis. Am. J. Kidney Dis. 49, 524-532, doi:10.1053/j.ajkd.2007.01.018 (2007).
116.Dandona, P., Aljada, A. & Bandyopadhyay, A. Inflammation: the link between insulin resistance, obesity and diabetes. Trends Immunol. 25, 4-7 (2004).
117.Dahabreh, I. J. & Kent, D. M. Index event bias as an explanation for the paradoxes of recurrence risk research. JAMA 305, 822-823, doi:10.1001/jama.2011.163 (2011).
118.Wu, C. Y. et al. Association between nucleoside analogues and risk of hepatitis B virus-related hepatocellular carcinoma recurrence following liver resection. JAMA 308, 1906-1914 (2012).
119.Just, P. M. et al. Reimbursement and economic factors influencing dialysis modality choice around the world. Nephrol. Dial. Transplant. 23, 2365-2373, doi:10.1093/ndt/gfm939 (2008).
120.Lin, C. C., Lai, M. S., Syu, C. Y., Chang, S. C. & Tseng, F. Y. Accuracy of diabetes diagnosis in health insurance claims data in Taiwan. J. Formos. Med. Assoc. 104, 157-163 (2005).
121.Chen, H. F., Chen, P. & Li, C. Y. Risk of malignant neoplasms of liver and biliary tract in diabetic patients with different age and sex stratifications. Hepatology 52, 155-163, doi:10.1002/hep.23641 (2010).
122.Wang, H. H., Hung, S. Y., Sung, J. M., Hung, K. Y. & Wang, J. D. Risk of stroke in long-term dialysis patients compared with the general population. Am. J. Kidney Dis. 63, 604-611, doi:10.1053/j.ajkd.2013.10.013 (2014).
123.Rabin, R. & de Charro, F. EQ-5D: a measure of health status from the EuroQol Group. Ann. Med. 33, 337-343 (2001).
124.Dolan, P. Modeling valuations for EuroQol health states. Med. Care 35, 1095-1108 (1997).
125.Rosenbaum PR, R. D. The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41-55, doi:10.1093/biomet/70.1.41 (1983).
126.Rosenbaum PR, R. D. Reducing bias in observational studies using subclassification on the propensity score. J. Am. Stat. Assoc. 79, 516-524, doi:10.1080/01621459.1984.10478078 (1984).
127.Tan, H. F., Tseng, H. F., Chang, C. K., Lin, W. & Hsiao, S. H. Accessibility assessment of the Health Care Improvement Program in rural Taiwan. J. Rural Health 21, 372-377 (2005).
128.Moreno, F., Lopez Gomez, J. M., Sanz-Guajardo, D., Jofre, R. & Valderrabano, F. Quality of life in dialysis patients. A spanish multicentre study. Spanish Cooperative Renal Patients Quality of Life Study Group. Nephrol. Dial. Transplant. 11 Suppl 2, 125-129 (1996).
129.Mingardi, G. et al. Health-related quality of life in dialysis patients. A report from an Italian study using the SF-36 Health Survey. DIA-QOL Group. Nephrol. Dial. Transplant. 14, 1503-1510 (1999).
130.Baiardi, F. et al. Effects of clinical and individual variables on quality of life in chronic renal failure patients. J. Nephrol. 15, 61-67 (2002).
131.Yang, S. C., Kuo, P. W., Wang, J. D., Lin, M. I. & Su, S. Quality of life and its determinants of hemodialysis patients in Taiwan measured with WHOQOL-BREF(TW). Am. J. Kidney Dis. 46, 635-641, doi:10.1053/j.ajkd.2005.06.015 (2005).
132.Life tables for Repubic of China. (Taiwan). Available at: http://sowf.moi.gov.tw/stat/english/elife/elist.htm. (Accessed: 17 April 2016).
133.Hwang, J. S. (2014). iSQoL software: A software used for integration of Survival with Quality of Life. Taipei, Taiwan. Available at: http://www.stat.sinica.edu.tw/isqol/ (Accessed: 17 August 2015).
134.Chang, K. C. et al. Estimation of life expectancy and the expected years of life lost among heroin users in the era of opioid substitution treatment (OST) in Taiwan. Drug Alcohol. Depend. 153, 152-158, doi:10.1016/j.drugalcdep.2015.05.033 (2015).
135.Hwang, J. S., Tsauo, J. Y. & Wang, J. D. Estimation of expected quality adjusted survival by cross-sectional survey. Stat. Med. 15, 93-102, doi:10.1002/(SICI)1097-0258(19960115)15:1<93::AID-SIM155>3.0.CO;2-2 (1996).
136.Choosing interventions that are cost-effective. Geneva: World Health Organization. Available from: http://www.who.int/choice/en/. (Accessed: 17 May 2016).
137.Lee, H. Y. et al. Estimating quality weights for EQ-5D (EuroQol-5 dimensions) health states with the time trade-off method in Taiwan. J. Formos. Med. Assoc. 112, 699-706, doi:10.1016/j.jfma.2012.12.015 (2013).
138.Vonesh, E. F., Snyder, J. J., Foley, R. N. & Collins, A. J. Mortality studies comparing peritoneal dialysis and hemodialysis: what do they tell us? Kidney Int. Suppl. S3-11, doi:10.1038/sj.ki.5001910 (2006).
139.Jager, K. J. et al. The effect of contraindications and patient preference on dialysis modality selection in ESRD patients in The Netherlands. Am. J. Kidney Dis. 43, 891-899 (2004).
140.Mehrotra, R., Marsh, D., Vonesh, E., Peters, V. & Nissenson, A. Patient education and access of ESRD patients to renal replacement therapies beyond in-center hemodialysis. Kidney Int. 68, 378-390, doi:10.1111/j.1523-1755.2005.00453.x (2005).
141.Little, J., Irwin, A., Marshall, T., Rayner, H. & Smith, S. Predicting a patient's choice of dialysis modality: experience in a United Kingdom renal department. Am. J. Kidney Dis. 37, 981-986 (2001).
142.Liem, Y. S., Bosch, J. L. & Hunink, M. G. Preference-based quality of life of patients on renal replacement therapy: a systematic review and meta-analysis. Value Health 11, 733-741, doi:10.1111/j.1524-4733.2007.00308.x (2008).
143.Fukuhara, S. et al. Health-related quality of life among dialysis patients on three continents: the Dialysis Outcomes and Practice Patterns Study. Kidney Int. 64, 1903-1910, doi:10.1046/j.1523-1755.2003.00289.x (2003).
144.Berry, S. D., Ngo, L., Samelson, E. J. & Kiel, D. P. Competing risk of death: an important consideration in studies of older adults. J. Am. Geriatr. Soc. 58, 783-787, doi:10.1111/j.1532-5415.2010.02767.x (2010).
145.Sennfalt, K., Magnusson, M. & Carlsson, P. Comparison of hemodialysis and peritoneal dialysis--a cost-utility analysis. Perit. Dial. Int. 22, 39-47 (2002).
146.Villa, G. et al. Cost-effectiveness analysis of the Spanish renal replacement therapy program. Perit. Dial. Int. 32, 192-199, doi:10.3747/pdi.2011.00037 (2012).
147.Shih, Y. C., Guo, A., Just, P. M. & Mujais, S. Impact of initial dialysis modality and modality switches on Medicare expenditures of end-stage renal disease patients. Kidney Int. 68, 319-329, doi:10.1111/j.1523-1755.2005.00413.x (2005).
148.St Peter, W. L., Khan, S. S., Ebben, J. P., Pereira, B. J. & Collins, A. J. Chronic kidney disease: the distribution of health care dollars. Kidney Int. 66, 313-321, doi:10.1111/j.1523-1755.2004.00733.x (2004).
149.Wu, A. W. et al. Changes in quality of life during hemodialysis and peritoneal dialysis treatment: generic and disease specific measures. J. Am. Soc. Nephrol. 15, 743-753 (2004).
150.Merkus, M. P. et al. Quality of life over time in dialysis: the Netherlands Cooperative Study on the Adequacy of Dialysis. NECOSAD Study Group. Kidney Int. 56, 720-728, doi:10.1046/j.1523-1755.1999.00563.x (1999).
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2018-08-01起公開。
  • 同意授權校外瀏覽/列印電子全文服務,於2018-08-01起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw