摘要
研究目的和背景：
蛋白尿是目前应用最为广泛的早期诊断、预测肾病以及心血管事件的无创性指标之一。从1969年Keen首次发现高血糖患者尿液白蛋白排泄量的增加；到2012年我国颁布的“高血压与糖尿病患者微量白蛋白尿的筛查干预中国专家共识”。人们经过近半个世纪的研究,发现白蛋白尿与心血管事件、肾终点事件发生、临床预后密切相关,也是心血管、肾终点事件链重要暴露因素。检测尿蛋白、特别尿微量白蛋白有助于发现各种疾病的早期肾功能损害,为心血管疾病、肾病高危患者的危险分层与制定个体化干预策略提供依据；管理好尿蛋白可望逆转肾病的病理过程、保护靶器官功能、改善临床预后。
目前明确能治疗蛋白尿的药物是血管紧张素转化酶抑制剂(angiotensin-converting enzyme inhibitor, ACEI)类药物和血管紧张素受体阻断剂(angiotensin receptor blocker,ARB)类药物。而在心血管领域中广泛应用的他汀类药物治疗蛋白尿的作用却有待临床实践和基础研究的进一步探讨。
他汀类药物,即p-羟甲基戊二酰单酰辅酶A(HMG-CoA)还原酶抑制剂,是广泛应用于临床的公认的高效降脂药。他汀类除了调整血脂水平作用外,还具有改善血管内皮；抑制血管平滑肌细胞增殖血管平滑肌细胞增殖；抑制血管炎症反应、抗氧化、防治动脉粥样硬化、改善血压、抗肿瘤、免疫作用等非调脂肪作用。大量的临床实践和基础研究证明,他汀通过其多效的药理机制发挥对心血管、肾功能的保护作用。
他汀对尿蛋白的影响的讨论,无论在动物实验或多个临床试验甚至是大型的临床研究都出现两种不同的结果；而从理论上分析,也有不同的声音：他汀类药物从药理机制上分析能改善血脂指标水平,发挥抗肾脏动脉粥样硬化作用；保护血管内皮和外膜脂肪舒张功能；抑制血管炎症物质活化、系膜细胞过度增殖及胞外基质堆积减轻肾血管的动脉硬化；改善肾局部循环血供和肾小管的重吸收功能；通过潜在的降压机制调节血压、改善肾小球高滤过、高动力状态；保护足细胞、减轻肾小管间质损伤；从而减少尿白蛋白的滤过、减少蛋白尿。但是,某些他汀类药物从药理机制上分析、能诱发管型蛋白尿的产生：干扰了近端肾小管细胞的胆固醇合成、促进肾小管细胞变性退化、从而影响肾小管细胞膜胞吞、重吸收蛋白质的功能；另外,大剂量的他汀经肾排泄,加重了肾小管重吸收的负荷,干扰了蛋白质的重吸收；从而使尿蛋白升高。
无论是动物实验等基础研究、大型临床研究还是meta分析均表明他汀治疗能使肾病患者获益。他汀发挥调脂、非调脂等多效机制改善肾功能：他汀可以有效地降低血浆低密度脂蛋白C(low density lipoprotein-C,LDL-C)水平,减少肾小球系膜区和小管间质中脂蛋白的沉积,降低肾小球毛细血管袢内压,改善肾脏局部异常的血液流变学指标。他汀还可以减少甲羟戊酸的合成而抑制小G蛋白的异戊二烯化,使其以无活性的形式在胞浆内大量堆积,从而抑制高血糖、高脂血症、高胰岛素血症等诱发的肾小球系膜细胞、肾小管上皮细胞、肾间质成纤维细胞、血管内皮细胞等的增殖；抑制细胞因子和生长因子的表达、减轻氧化应激、改善血管内皮功能；调节外周血管舒缩功能,导致血管舒张,降低血压；作用于各种免疫细胞(主要是单核巨噬细胞和T细胞)的聚集、分化、增殖、分泌活动,干预肾脏疾病的免疫应答,改善肾功能。
从肾脏疾病链来谈,尿蛋白是最重要的暴露因素之一；肾脏临床事件是联系暴露因素和终点结局(死亡)最重要的一环；全因死亡是肾病进展的最终结局。评价对全因死亡终点的影响是一切治疗手段有效性最有力的证据。目前单独以尿蛋白、肾脏事件报道、全因死亡例数作为一级观察终点,关于他汀对肾病疾病链全面的系统评价文章,国内外均未见报道。
我们的研究对尿蛋白不同的测量指标进行分析、在尿蛋白从微量白蛋白、显性蛋白尿不同阶段分别做系统评价,较为全面反应他汀类药物对蛋白尿的干预作用。并通过他汀对肾脏事件、非透析患者全因死亡的系统评价,全面评估他汀在从暴露因素、临床事件、结局死亡整个肾脏事件链的干预作用,从而为肾病治疗学发展、临床合理用药提供循证医学证据。
研究方法
第一部分：他汀对尿蛋白的影响
本部分实验又分为两组。根据基线尿蛋白测量指标水平分为显性蛋白尿组和微量白蛋白尿组。显性蛋白尿组：基线24h尿蛋白定量大于1000mg;尿微量白蛋白组：基线微量的白蛋白排出<30mg/24h、或尿白蛋白与肌酐比值(urinary albumin to creatinine ratio, UACR)为30-300mg/g,或尿白蛋白排泄率(urinary albumin excretion ratio, UAER)定量20-200mg/min。利用PubMed、Cochrane library、EMBASE数据库,全面检索迄今为止他汀对尿蛋白、尿微量白蛋白影响的临床随机对照试验。他汀检索词：'HMG CoA reductase inhibitors" OR"statin" OR "Simvastatin" OR "fluvastatin" OR "lovastatin " OR "Rosuvastatin" OR "atorvastatin" OR "xuezhikang";尿蛋白的检索词："urinary microalbumin" OR "microalbuminuria" OR "albumin creatinine ratio" OR "ACR" OR "urinary albumin excretion ratio" OR "AER"OR "proteinuria" OR "24h albumin";随机对照试验检索词："randomized controlled"OR "clinical trial"OR "random" OR "control"OR"RCT"。各个不同范筹检索词用“AND”连接,进行检索；同时在各个数据库进行扩展检索,阅读相关综述和相关文献的参考文献,通过制定的纳入标准、排除标准纳入试验、同时对纳入文献进行质量评价。提取实验组和对照组患者的基本情况、试验后尿蛋白或微量白蛋白测量值的均值和标准差、利用RevMan软件对其行meta分析、评价他汀类药物对显性蛋白尿、微量白蛋白尿的影响。绘制森林图分析结果、并绘制漏斗图分析发表偏倚；根据检验结果采用相应效应模型进行合并效应量。当各研究间有统计学同质性I2<50%时,采用固定效应模型；反之,I2>50%,采用随机效应模型分析。
第二部分：他汀对肾脏事件的影响
肾脏事件包括终末期肾脏疾病(肾衰竭导致透析或移植),肌酐水平增加一倍,肾小球滤过率(glomerular filtration rate, GFR)下降50%。利用PubMed、 Cochrane library、EMBASE数据库,全面检索迄今为止他汀与各级肾脏事件发生事件报道有关的临床随机对照试验。他汀检索词：“HMG CoA reductaseinhibitors " OR "statin "OR"Simvastatin" OR"fluvastatin"OR"lovastatin " OR "Rosuvastatin" OR "atorvastatin" OR"xuezhikang";肾脏事件的检索词："End stage renal disease"OR " doubling of creatinine" OR "progression of impaired renal function" OR"50%decrease in eGFR"OR"kidney event""Dialysis"OR"kidney transplantation";随机对照试验检索词："randomized controlled"OR"clinical trial"OR "random" OR "control"OR "RCT"。各个不同范筹检索词用“AND”连接,进行检索；同时在各个数据库经行扩展检索,阅读相关综述和相关文献的参考文献,通过制定的纳入标准、排除标准纳入试验、同时对纳入文献进行质量评价。主要的观察指标是应用他汀后,各种肾脏事件发生例数。利用RevMan软件对其行neta分析、评价他汀类药物肾脏事件发生的影响。绘制森林图分析结果、并绘制漏斗图分析发表偏倚；根据检验结果采用相应效应模型进行合并效应量。当各研究间有统计学同质性I2<50%时,采用固定效应模型；反之,I2>50%,采用随机效应模型分析。
第三部分他汀对肾病非透析患者全因死亡的影响
利用PuMed、Cochrane library、EMBASE数据库,全面检索迄今为止他汀与非肾脏透析肾病患者死亡发生例数报道有关的临床随机对照试验。他汀检索词：" HMG CoA reductase inhibitors " OR "statin "OR "Simvastatin "OR "fluvastatin" OR "lovastatin "OR"Rosuvastatin"OR "atorvastatin"OR"xuezhikang";非透析治疗的检索词："not requiring dialysis"OR "nondialytic treatment";随机对照试验检索词："randomized controlled"OR"clinical trial"OR "random" OR "control"OR "RCT";全因死亡的检索词“all cause mortality" OR"death "OR "mortality"OR "end point "。各个不同范筹检索词用“AND”连接,进行检索；同时在各个数据库经行扩展检索,阅读相关综述和相关文献的参考文献,通过制定的纳入标准、排除标准纳入试验、同时对纳入文献进行质量评价。主要的观察指标是应用他汀后,非透析病人发生死亡例数。利用RevMan软件对其行meta分析、评价他汀类药物肾脏事件发生的影响。绘制森林图分析结果、并绘制漏斗图分析发表偏倚；根据检验结果采用相应效应模型进行合并效应量。当各研究间有统计学同质性I2<50%时,采用固定效应模型；反之,I2>50%,采用随机效应模型分析。
结果：
第一部分他汀对尿蛋白的影响
本研究共纳入8个试验,其中显性蛋白尿6个、微量白蛋白尿2个；6个研究为B级,2个研究为C级。Jadad评分为1-3分。显性蛋白尿组分析共纳入6个研究,共患者311例。他汀治疗组156例、对照组155例；入选文献异质性检验I2<50%,采用固定效应模型进一步分析；结果显示与对照组相比经他汀治疗后,可降低显性蛋白尿患者24小时尿蛋白定量734.44mg [(95%CI-826.41,-642.48), z=15.65, P<0.01]。结果提示他汀类药物可有效降低显性蛋白尿；漏斗图提示6个研究分布不对称,存在发表偏倚的可能。
微量蛋白尿组共纳入2个研究,均以白蛋白排泄率为测量指标。入选文献异质性检验I2=51%,采用随机效应模型进一步分析；结果显示与对照组相比经他汀治疗后,略降低微量蛋白尿患者UAER34.27μg/min [(95%CI-88.06,19.51),Z=1.25,P>0.05]。这表明他汀类药物有降低尿微量白蛋白的趋势,但未达到统计学意义。
第二部分他汀对肾脏事件的影响
本研究共纳入5个试验,均为高质量的研究,Jadad评分为3-5分(5分表)。他汀治疗组18064例、对照组18073例；入选文献异质性检验I2<50%,采用固定效应模型进一步分析；结果显示与对照组相比经他汀治疗后,可降低患者肾脏事件的发生[OR=0.91,(95%CI0.83,0.99),z=2.09, P=0.04]。这表明他汀类药物减少肾脏事件的发生；剔除SUB-SHARP研究行敏感性分析。结果提示,他汀有降低肾脏事件发生趋势,但无统计学意义[OR=0.79,(95%CI0.61,1.01),z=1.86,P=0.06]。这说明本次meta分析结论欠稳定；漏斗图提示5个研究大致分布对称,发表偏倚可能性不大。
第三部分他汀对肾病非透析患者全因死亡的影响
本研究共纳入7个试验,Jadad评分为1-5分(5分表)。他汀治疗组14197例、对照组14404例；入选文献异质性检验I2<50%,采用固定效应模型进一步分析；结果显示与对照组相比经他汀治疗后,可减少患者全因死亡例数[OR=0.77,(95%CI0.70,0.85),Z=5.32,P<0.01]。剔除PPP研究行敏感性分析,未实质性改变原来结果,说明本次研究结论较为可信。[OR=0.64,(95%CI0.49,0.84),Z=3.21,P<0.01]。漏斗图提示7个研究大致分布对称,发表偏倚可能性不大。
结论：
本研究通过观察他汀干预肾脏疾病链三个重要的环节(暴露因素、临床事件、终点死亡)的影响,来系统、全面评价他汀类药物对肾脏疾病的影响。结果显示：他汀类药物干预能有效减少显性蛋白尿,减少肾脏事件的发生；降低肾病非透析患者全因死亡；但未能减少尿微量白蛋白。以上结果清晰表达以下结论：他汀类药物能有效干预肾病危险因素、减少临床事件,最终改变临床结局。
局限性及展望：
第一部分他汀对尿蛋白的影响
共纳入8个研究,纳入的样本量不多,为中、低质量的研究,降低了本次研究的检验效能。我们虽多次扩大检索范围,但遗憾的是本研究微量白蛋白组纳入研究只有2个、入选病例少、我们应谨慎对待他汀对微量白蛋白尿的研究结果。随着研究的深入,未来必将有更多,大样本、高质量的随机对照研究来支持、验证我们的研究结论。
第二部分他汀对肾脏事件的影响
纳入共5个随机对照试验(randomized controlled trial, RCT)的Jadad评分在3-5分之间,证据水平为高级。入选的RCT虽然质量高,但只有5个,这也限制了我们通过亚组分析他汀对不同的肾脏事件行的影响；纳入研究样本量差异较大(从123-16145)、SUB-SHARP研究占的权重大,行敏感性分析提示单一研究对最后结果影响大,影响了统计效力；尽管漏斗图未显示明显偏倚,但发表偏倚不可避免。
未来还需要更多高质量、大样本、前瞻性的随机对照实验以肾脏事件为一级终点而不是安全性指标,来观察他汀对临床肾脏事件的影响。
第三部分他汀对肾病非透析患者全因死亡的影响
本次研究入选的RCT7个,6个为中、高级质量研究、1个为低质量研究。纳入研究少,这限制了我们通过亚组分析他汀对不同病因造成死亡的影响；纳入研究样本量差异较大(从17-16824)、PPP研究占的权重大,单一研究对最后结果影响大,影响了统计效力；但敏感性分析提示本次研究结论较为稳定；尽管漏斗图未显示明显偏倚,但发表偏倚不可避免。究竟他汀能不能改变肾病最终结局,答案还待未来临床实践、循证试验去揭晓。
Background and Objectives
Proteinuria (PU) is one of the widely adopted, noninvasive indicators for the early diagnosis and prediction of diabetic nephropathy (DN) and cardio-vascular events (CVE). From Keen's discovery of increased uAE in urine of patients with hyperglycemia in1969, to China's "The Chinese Experts Consensus on Screening Intervention of Microalbuminuria (MAU) in Patients Suffer Hypertension and Diabetes" in2012, after half a century, it is found that albuminuria is an important indicator and tightly connected with cardiovascular events, final renal events and their clinical prognosis. Early laboratory detection of PU, especially MAU, can prevent the damage to renal functions, and assists to process the risk stratify and formulate personalized intervention and therapies for patients suffer CVE and DN. At the same time, good management of MAU is believed to inverse the pathological process of kidney disease, protect the targeted organ functions and improve clinical recovery.
At present, ACEI and ARB are proved effective for MAU, while in the field of cardiovascular system, the clinical effect of statins treating PU still requires further clinical evidence and basic research.
Statins, that is, β-hydroxymethyl-glutaryl coenzyme A (HMG-CoA) reductase inhibitors are widely used clinically recognized high lipid lowering drugs. In addition to adjusting lipid level, Statin can also improve endothelial function; inhibit vascular smooth muscle cell proliferation; inhibit vascular inflammation, anti-oxidation; prevent and treat atherosclerosis; improve blood pressure; anti-tumor; immune function, and other non-fat regulating functions. A large number of clinical practice and basic research proved that statins play a protective role in cardiovascular and renal function through its pleiotropic pharmacological mechanisms.
Two contradictory results about discussion of statins on urinary protein were shown in animal experiments, clinical trails, and even large-scale clinical research. Besides, the theoretical analysis also show the controversies:pharmaceutically, statins can improve the level of serum lipids index, protect the diastolic function vascular endothelium and adventitia, and exhibit the activation of vascular active substance, prevent the renal arterial arteriosclerosis to improve the local renal blood cycle and absorption function of renal tubules, inhibit excessive proliferation of mesangial cell and accumulation of extracellular matrix to allievate renal vascular atherosclerosis; Regulate blood pressure by potential mechanisms, improve glomerular filtration and high power state; protect podocytes and reduce tubulointerstitial injury; and then decrease the filtration of urinary albumin and PU. However, some stains can trigger the cylindruria and consequently lead to the increase of urine protein. some statins might Interfere cholesterol synthesis in proximal tubular cells, promote the degradation of renal tubular cell degeneration, which affects the function of renal tubular cell membrane, such as endocytosis, reabsorption of protein. In addition, large doses of statins were excreted by kidney, increased the burden of tubular reabsorption interfered with protein resorption; thereby increased urinary protein.
Whether it is the basic animal experiments or large clinical studies, meta analysis showed that patients with kidney disease can benefit from statin therapy. Statins improve renal function through lipid and non-lipid pleiotropic mechanism, such as:Statins can effectively reduce plasma LDL-C levels, reduce the quality of the lipoprotein deposition in glomerular mesangial and small tube area, decrease the glomerular capillary inner loop pressure and improve local kidney hemorheologic abnormalities. Statins can also inhibit prenylation of small G proteins by reducing the synthesis of mevalonate, in order to accumulate a large number of inactive form in the cytoplasm; thereby suppressing the proliferation of renal mesangial cells, renal tubular epithelial cells, renal interstitial fibroblasts, endothelial cells, etc. that induced by hyperglycemia, hyperlipidemia, hyperinsulinemia; inhibiting the expression of cytokines and growth factors, reducing oxidative stress, improving endothelial function; regulating systolic and diastolic function of peripheral vessel, leading to vasodilation, lower blood pressure;playing a role in various immune cells (mainly macrophages and T cells),affecting their aggregation, differentiation, proliferation and secretory activity,thus, interfering with the immune response of kidney disease, improving renal function.
When it talks to the chain of kidney disease, proteinuria is one of the most important risk factors.clinical renal events play the most important part in linking exposure factors and the end outcome (death); All-cause death was the ultimate outcome of kidney disease progression. Assessing the impact on all-cause mortality endpoint is the most powerful and effective evidence of treatment. Currently regarding proteinuria, reported renal events or cases of all-cause mortality as an endpoint, and comprehensive systematic review articles on statins for kidney disease chains have not been reported both at home and abroad.
This research focused on the analysis of different measurement indexes. We extracted PU from urines contains MAU and albuminuria (AU). This process can reflect statins intervention to PU. We also adopted meta-analysis to completely evaluate the intervention effect of statins on the complete renal event chain, from exposure, clinical events to death, in order to provide evidence-based information for reasonable clinical administration and support evidence for the development of therapeutics of kidney disease,
Methodology and Data
Part One Effect of Statins on PU
The experiments were divided into2groups-group of AU and group MAU according to the baseline of PU level. The group of24-hour baseline PU level higher than1000mg was defined as group of AU, and that of MAU less than30mg, or UACR30-300mg/g, or UAER within20-200mg/g were defined as group of MAU.
The literature were collected from PubMed, Cochrane library and EMBASE to gather all published papers on the clinical trials of statins on UP and MAU. The keywords used to present statins were as follows:"HMG Co A reductase inhibitors","statin","simvastatin","fluvastatin","lovastatin ","Rosuvastatin","atorvastatin" and"xuezhikang"; those for PU were"urinary microalbumin","microalbuminuria","albumin creatinine ratio","ACR","urinary albumin excretion ratio","AER","proteinuria" or"24h albumin"; those for randomized controlled trail were:"randomized controlled","clinical trial","random""control" or "RCT".
"And" was used to connect words from different categories. The extended search was performed and each related reviews and referential references were read to set out the include criteria and exclude criteria. The included papers were evaluated to control the quality. The basic information of2groups and the means and standard errors were of the each index were recorded. RevMan5.2software was adopted to perform the meta-analysis and evaluate the effect of statins. The forest plots and funnel plots were made to analyze results. The proper effect models were chosen in accord with the results:when I2<50%, fixed effect models were chosen, and when I2>50%, random effect model was the choice.
Part Two Influence of Statins on Renal Events
Renal events included end-stage renal disease (dialysis or transplantation caused by kidney failure), doubled creatinine level, and50%decrease of GFR. Literatures on statins related to all level renal events were searched for in PubMed, Cochrane library and EMBASE. The keywords used for statins were "HMG CoA reductase inhibitors" or "statin" or "Simvastatin" or "fluvastatin" or "lovastatin" or "Rosuvastatin" or "atorvastatin" or "xuezhikang"; keywords for renal events were "End stage renal disease" or "doubling of creatinine" or "progression of impaired renal function" or "50%decrease in eGFR" or "kidney event" or "dialysis" or "kidney transplantation"; keyword for randomized controlled trial were "randomized controlled" or "clinical trial" or "random" or "control" or "RCT".
"And" was used to connect words from different categories. The extended search was performed and each related reviews and referential references were read to set out the include criteria and exclude criteria. The included papers were evaluated to control the quality. The major indexes were the number of renal events cases. RevMan5.2software was adopted to perform the meta-analysis and evaluate the effect of statins. The forest plots and funnel plots were made to analyze results. The proper effect models were chosen in accord with the results:when I2<50%, fixed effect model was chosen, and when I250%, random effect model was the choice.
Part Three Effect of Statins on All-cause Mortality in Non-dialysis Patients
PubMed、Cochrane library、EMBASE were adopted to search for the papers on randomized statins clinical trials related to mortality of non-dialysis patients.
The keywords used to present statins were as follows:"HMG CoA reductase inhibitors","statin","Simvastatin","fluvastatin","lovastatin ","Rosuvastatin","atorvastatin"and "xuezhikang"; keywords for non-dialysis treatment were "not requiring dialysis" or "nondialytic treatment"; keyword for randomized controlled trial were "randomized controlled" or "clinical trial" or "random" or "control" or "RCT". Keywords for all-cause mortality were "all course mortality" OR"death ""mortality""end point".
"And" was used to connect words from different categories. The extended search was performed and each related reviews and referential references were read to set out the include criteria and exclude criteria. The included papers were evaluated to control the quality. The major index was the number of mortality after statins administration. RevMan5.2software was adopted to perform the meta-analysis and evaluate the effect of statins. The forest plots and funnel plots were made to analyze results. The proper effect models were chosen in accord with the results:when I2<50%, fixed effect models were chosen, and when I2>50%, random effect model was the choice.
Results
Part One Effect of Statins on PU
Eight experiments were involved in this research with6in AU group and2in MAU group, and6of them were of B level and2were of C level. Jadad code was1-3. There were311subjects in group MAU, with study group (statins treatment)156, and control group155. For the included literature, the heterogeneity test result was I2<50%, so fixed effect model was adopted for further analysis. Compared with the control group, statins can reduce24h AU to734.44mg [(95%CI-826.41,-642.48), z^15.65, P<0.01], indicating statins can significantly decrease AU. The funnel plot demonstrated unsymmetrical distribution in6experiments, indicating publication bias.
Two experiments included in group of MAU, and UAER was adopted as index. For the inclusive literature, I2=51%, and randomized effect model was used for the further analysis. The results showed that compared with control group, statins decreased UAER of patients with MAU to34.27μg/min[(95%CI-88.06,19.51),Z=1.25, P>0.05]。 It shows the tendency that statins decrease MAU, but it is not statistically significant.
Part Two Effect of Statins to Renal Events
A total of5high quality experiments were involved. Jadad code was3-5(full mark). There were18064subjects in statins (study) group, and18073in control group. The heterogeneity test result was I2<50%, so the fix effect model was adopted for further analysis. The results show that renal events decreased in statins group statistically [OR=0.91,(95%CI0.83,0.99),z=2.09, P=0.04].Sensitivity analysis showed that the result was not stable. The fennel plot showed5symmetric distribution of5experiments, indicating unlikelihood of publish bias.
Part Three Effect of Statins on All-cause Mortality of Non-dialysis Patients
Seven experiments were involved in this part. Jadad code was1-5. Statins (study) group involved14197subjects and the control14404. The heterogeneity test for included literature resulted I2<50%, and the fix effect model was adopted for further analysis. The results showed the mortality cases were decreased in statins group [OR=0.77,(95%CI0.70,0.85), Z=5.32, P<0.01]. Sensitivity analysis showed that the result was stable. The funnel indicated few possibility of public bias.
Conclusion
Statins can reduce proteinuria, disease renal event effectively,and lessen the all-cause mortality among un-dialysis patients, but it neither show effect on reduction of MAU.
This research was designed to systemically evaluate the effect of statins on renal disease by observing how statins intervene the3important segments of the disease (exposure factors, clinical events, and the death). The results showed that statins intervention contributed to significant decrease of AU, renal events, and all-cause mortality of non-dialysis patients, but it did not show any influence on decrease MAU. The findings supported the conclusion that statins can effectively intervene risk factors of renal diseases, decease clinical events and finally changed the clinical results.
Limitation and Expectation
Part One Effect of Statins on UP
There involved only8experiments, so the number of samples was not large enough. The quality of this research is of middle level, which may affect the testing efficiency. Though we tried for many times expanding the search scope, still, the samples qualified for the group of MAU were only two. But we were cautiously tested and explained the results of MAU group. We believe that with the further research, there would be research with larger samples and higher quality to support this research.
Part Two Effect of Statins on Renal Events
Jadad codes of5RCT were between3and5. According to GRADE criteria, the evidence level is high. Though the quality of RCT was high, the number of them still restricted the analysis of the effect of statins. Though the number of samples in5groups varied(from123to16145), and so was the statistical weight of SUB-SHARP, the single research influenced the results and defected the statistical power. As well, the publication bias is unavoidable though the fennel plot did not show obvious bias.
More high-quality, large-sample and prospective randomized controlled research are needed for the further research.
Part Three Effect of Statins on All-cause Mortality of Non-dialysis Patients
The quality of7RCTs were of low and high level. The further subgroup analysis was restricted by limited samples. The statistic power was affected by the distinct number of samples (from17to16824), as well as the influential weight of PPP analysis. The publication bias is unavoidable though the fennel plot did not show obvious bias. Whether statins can change the ending of renal disease needs clinical and evidence-based research.
引文
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