本文選題：臨床隨訪研究　切入點：刪失率　出處：《南京醫(yī)科大學》2017年碩士論文

【摘要】：背景與目的:臨床隨訪研究中以生存時間作為主要療效指標較為常見,而數(shù)據(jù)刪失是生存資料的重要特征之一。有研究表明,過高的刪失率將導(dǎo)致療效估計偏差,檢驗效能降低。實際研究中,往往組間的刪失率水平不同,有時還相差較大,這種情況下對療效評價產(chǎn)生何種影響尚無定論。此外,很多臨床試驗中觀察的事件(例如腫瘤研究中發(fā)生進展)只有在訪視時才能發(fā)現(xiàn),因此,并不知道準確的事件發(fā)生時間,即區(qū)間刪失。本文主要探討臨床試驗中這兩個問題:(1)組間不同刪失率情況下常規(guī)療效評價方法的統(tǒng)計學性質(zhì),(2)區(qū)間刪失時,生存時間的不同定義方法對參數(shù)估計結(jié)果的影響。方法:采用Monte-Carlo模擬方法,基于指數(shù)分布和Weibull分布分別產(chǎn)生生存時間,在不同情況下,分別采用log-rank檢驗及Cox比例風險回歸模型進行相應(yīng)的參數(shù)估計和組間療效的比較。論文分為兩個部分,第一部分:在組間刪失率相同和不同時,從假設(shè)檢驗的一類錯誤和檢驗效能、參數(shù)估計的準確度估計偏差等三個方面來評價對療效評價的影響;第二部分:區(qū)間刪失時,事件發(fā)生時間不確定,比較3種不同的生存時間的定義方法,對中位生存時間和風險比估計的影響。結(jié)果:1)在生存分析中,刪失率的變化,會導(dǎo)致第一類錯誤率變化,且隨刪失率的增大,檢驗效能逐漸下降;2)相比于兩組刪失率相等的情況,兩組刪失率不等時,一類錯誤增加,HR的偏倚增大;且兩組刪失率相差越大,第一類錯誤率越大,檢驗的結(jié)果越不可信。3)區(qū)間刪失時,生存時間的不同定義對中位生存時間有影響,在隨訪間隔不是很大時,對中位生存時間之差以及HR的估計影響不大。4)采用Cox比例風險回歸模型進行療效評價時,所得結(jié)果與log-rank檢驗相似。結(jié)論:1)臨床隨訪研究中,總刪失率應(yīng)控制在30%以內(nèi),組間刪失率之差應(yīng)控制在10%以內(nèi),否則將導(dǎo)致一類錯誤膨脹。2)區(qū)間刪失時,事件發(fā)生時間不確定,應(yīng)盡可能縮短每次訪視的時間,無論采用何種生存時間定義,不宜估計各組的中位生存時間,但估計中位生存時間之差或HR是可行的。
[Abstract]:Background & objective: survival time is common in clinical follow-up studies, and data deletion is one of the important characteristics of survival data. Test effectiveness is reduced. In actual studies, the level of deletion rate is often different among groups, and sometimes there is a big difference. In this case, the impact on the evaluation of curative effect has not been decided. The events observed in many clinical trials (such as progress in cancer studies) can only be detected during the visit, so the exact time of the event is not known. This paper mainly discusses the statistical properties of the conventional evaluation methods of curative effect under different deletion rates in clinical trials. Methods: Monte-Carlo simulation method is used to generate survival time based on exponential distribution and Weibull distribution respectively. Log-rank test and Cox proportional risk regression model were used to estimate the parameters and compare the efficacy of the two groups. The effect of hypothesis test on the evaluation of efficacy is evaluated from three aspects: the error of hypothesis test and the efficiency of test, the error of estimating accuracy of parameter estimation, etc. The second part: when the interval is censored, the time of event occurrence is uncertain. The effects of three different definition methods of survival time on median survival time and risk ratio estimation were compared. Results: in survival analysis, the change of deletion rate will lead to the change of error rate of the first kind, and increase with the increase of deletion rate. Compared with the two groups with the same deletion rate, the bias of HR increased when the deletion rate of two groups was not equal, and the greater the difference between the two groups, the greater the error rate of the first group. The less reliable. 3) interval deleted, the different definitions of survival time had an effect on median survival time, and when the interval of follow-up was not very large, The difference of median survival time and the estimated impact of HR. 4) when the Cox proportional risk regression model was used to evaluate the efficacy, the results were similar to that of the log-rank test. Conclusion: in the clinical follow-up study, the total deletion rate should be controlled within 30%. The difference of deletion rate between groups should be controlled within 10%, otherwise it will cause a class of errors to expand. 2) when the time of occurrence is uncertain, the time of each visit should be shortened as far as possible, no matter what definition of survival time is used. It is not suitable to estimate the median survival time of each group, but it is feasible to estimate the difference of median survival time or HR.
【學位授予單位】：南京醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R195.1

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