Brief Introduction of Trial Sequential Analysis_Chinese Journal of Evidence-Based Medicine

Authors：

WANG Quan ^1,2 , TIAN Jinhui ¹ , LI Lun ^1,2 , HE Xiran ³ , SHI Chunhu ¹ ,  YANG Kehu ^1,2

1. Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China;2. The First Clinical Medicine College, Lanzhou University, Lanzhou 730000, China;3. The School of Clinical Oncology, Perking University, Beijing 100142, China;

Corresponding author：

YANG Kehu, Email: kehuyangebm2006@126.com

Keywords：

Trial sequential analysis; Cumulative meta-analysis; Methodology

DOI：

10.7507/1672-2531.20130216

Video：

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Abstract Full text Figures/Tables Video References Cited by

Trial Sequential Analysis (TSA), one kind of cumulative meta-analysis, is a method which introduces sequential analysis into traditional meta-analysis to avoid random errors (false positive or false negative outcomes) that occurred during repeated updates when traditional meta-analysis is performing. It is also applied to calculate required information size (RIS) of a firm conclusion. This study aims to summarize the proposal, fundamental theory, application software, and current limitation of TSA, and to clarify the advantages of TSA on the basis of detailed examples, in order to attract more attention of researchers and promote the methodological development of meta-analysis in China.

Citation： WANG Quan,TIAN Jinhui,LI Lun,HE Xiran,SHI Chunhu,YANG Kehu. Brief Introduction of Trial Sequential Analysis. Chinese Journal of Evidence-Based Medicine, 2013, 13(10): 1265-1268. doi: 10.7507/1672-2531.20130216 Copy

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2.	Borm GF, Donders A. Updating meta-analyses leads to larger type I errors than publication bias. J Clin Epidemiol, 2009, 62: 825.
3.	Brok J, Thorlund K, Gluud C, et al. Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses. J Clin Epidemiol, 2008, 61(8): 763-769.
4.	Pereira TV, Ioannidis J. Statistically significant meta-analyses of clinical trials have modest credibility and inflated effects. J Clin Epidemiol, 2011, 64(10): 1060-1069.
5.	Pogue JM, Yusuf S. Cumulating evidence from randomized trials: utilizing sequential monitoring boundaries for cumulative meta-analysis. Control Clin Trials, 1997, 18(6): 580-593.
6.	Thorlund K, Devereaux P, Wetterslev J, et al. Can trial sequential monitoring boundaries reduce spurious inferences from meta-analyses? Int J Epidemiol, 2009, 38(1): 276-286.
7.	Trikalinos TA, Churchill R, Ferri M, et al. Effect sizes in cumulative meta-analyses of mental health randomized trials evolved over time. J Clin Epidemiol, 2004, 57(11): 1124-1130.
8.	Wetterslev J, Thorlund K, Brok J, et al. Trial sequential analysis may establish when firm evidence is reached in cumulative meta-analysis. J Clin Epidemiol, 2008, 61(1): 64-75.
9.	Thorlund K, Imberger G, Walsh M, et al. The number of patients and events required to limit the risk of overestimation of intervention effects in meta-analysis- a simulation study. PLoS One, 2011, 6(10): e25491.
10.	Higgins JSG. Cochrane handbook for systematic reviews of interventions, version 5.1.0. Updated March 2011. The Cochrane Collaboration, 2011. In Edition.
11.	Thorlund K, Engstrøm J, Wetterslev J, et al. User manual for trial sequential analysis (TSA). Copenhagen Trial Unit. Available from: http://wwwctudk/tsa/files/tsa_manualpdf. Accessed 2011.
12.	刘树贤. 临床流行病学(六）——序贯试验. 疑难病杂志, 2004, 3(4): 253-255.
13.	何清坡, 苏炳华. 成组序贯试验的原理和方法. 现代预防医学, 1999, 26(3): 310-312.
14.	余松林. 随机临床试验中的成组序贯设计与期中分析方法. 中国临床药理学与治疗学杂志, 1998, 3: 206-206.
15.	Demets DL, Lan K. Interim analysis: the alpha spending function approach. Stat Med, 1994, 13(13-14): 1341-1352.
16.	Higgins J, Whitehead A, Simmonds M. Sequential methods for random-effects meta-analysis. Stat Med, 2011, 30(9): 903-921.
17.	Wetterslev J, Thorlund K, Brok J, et al. Estimating required information size by quantifying diversity in random-effects model meta-analyses. BMC Med Res Methodol, 2009, 9: 86.
18.	王权, 何曦冉, 田金徽, 等. 艾迪联合紫杉醇和顺铂治疗晚期非小细胞肺癌的 Meta 分析. 中国肺癌杂志, 2010, 13(11): 1027-1034.
19.	Wetterslev J, Engstrøm J, Gluud C, et al. Trial sequential analysis: methods and software for cumulative meta-analyses. Cochrane Methods, 2012, 14: 29-35.

1. 杨克虎. 循证医学. 北京: 人民卫生出版社, 2007:.
2. Borm GF, Donders A. Updating meta-analyses leads to larger type I errors than publication bias. J Clin Epidemiol, 2009, 62: 825.
3. Brok J, Thorlund K, Gluud C, et al. Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses. J Clin Epidemiol, 2008, 61(8): 763-769.
4. Pereira TV, Ioannidis J. Statistically significant meta-analyses of clinical trials have modest credibility and inflated effects. J Clin Epidemiol, 2011, 64(10): 1060-1069.
5. Pogue JM, Yusuf S. Cumulating evidence from randomized trials: utilizing sequential monitoring boundaries for cumulative meta-analysis. Control Clin Trials, 1997, 18(6): 580-593.
6. Thorlund K, Devereaux P, Wetterslev J, et al. Can trial sequential monitoring boundaries reduce spurious inferences from meta-analyses? Int J Epidemiol, 2009, 38(1): 276-286.
7. Trikalinos TA, Churchill R, Ferri M, et al. Effect sizes in cumulative meta-analyses of mental health randomized trials evolved over time. J Clin Epidemiol, 2004, 57(11): 1124-1130.
8. Wetterslev J, Thorlund K, Brok J, et al. Trial sequential analysis may establish when firm evidence is reached in cumulative meta-analysis. J Clin Epidemiol, 2008, 61(1): 64-75.
9. Thorlund K, Imberger G, Walsh M, et al. The number of patients and events required to limit the risk of overestimation of intervention effects in meta-analysis- a simulation study. PLoS One, 2011, 6(10): e25491.
10. Higgins JSG. Cochrane handbook for systematic reviews of interventions, version 5.1.0. Updated March 2011. The Cochrane Collaboration, 2011. In Edition.
11. Thorlund K, Engstrøm J, Wetterslev J, et al. User manual for trial sequential analysis (TSA). Copenhagen Trial Unit. Available from: http://wwwctudk/tsa/files/tsa_manualpdf. Accessed 2011.
12. 刘树贤. 临床流行病学(六）——序贯试验. 疑难病杂志, 2004, 3(4): 253-255.
13. 何清坡, 苏炳华. 成组序贯试验的原理和方法. 现代预防医学, 1999, 26(3): 310-312.
14. 余松林. 随机临床试验中的成组序贯设计与期中分析方法. 中国临床药理学与治疗学杂志, 1998, 3: 206-206.
15. Demets DL, Lan K. Interim analysis: the alpha spending function approach. Stat Med, 1994, 13(13-14): 1341-1352.
16. Higgins J, Whitehead A, Simmonds M. Sequential methods for random-effects meta-analysis. Stat Med, 2011, 30(9): 903-921.
17. Wetterslev J, Thorlund K, Brok J, et al. Estimating required information size by quantifying diversity in random-effects model meta-analyses. BMC Med Res Methodol, 2009, 9: 86.
18. 王权, 何曦冉, 田金徽, 等. 艾迪联合紫杉醇和顺铂治疗晚期非小细胞肺癌的 Meta 分析. 中国肺癌杂志, 2010, 13(11): 1027-1034.
19. Wetterslev J, Engstrøm J, Gluud C, et al. Trial sequential analysis: methods and software for cumulative meta-analyses. Cochrane Methods, 2012, 14: 29-35.

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