Application of trial sequential analysis in time-to-event data_Chinese Journal of Evidence-Based Medicine

Authors：

WENG Hong ¹ , GONG Kan ² , LIU Xiaoping ¹ , LI Xudong ³ , PENG Jianping ⁴ ,  ZENG Xiantao ^1,4

1. Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University; Center for Evidence-Based and Translational Medicine, Wuhan University; Department of Evidence-Based Medicine and Clinical Epidemiology, The Second Clinical Medical College of Wuhan University, Wuhan, 430071, P.R.China;
2. Department of Urology, Peking University First Hospital, Beijing, 100034, P.R.China;
3. Department of Urology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, P.R.China;
4. Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, P.R.China;

Corresponding author：

ZENG Xiantao, Email: zengxiantao1128@163.com

Keywords：

Trial sequential analysis; Meta-analysis; Time-to-event data

DOI：

10.7507/1672-2531.201607062

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Abstract Full text Figures/Tables Video References Cited by

The sample size of a meta-analysis should not be less than a single randomized controlled trial. Trial sequential analysis (TSA) can provide required information size and monitoring boundary to justify the conclusion of meta-analysis. However, the TSA software is only suitable for binary and continuous data, and it cannot analyze the time-to-event data. This paper aimed to introduce how to analyze the time-to-event data using TSA approach.

Citation： WENGHong, GONGKan, LIUXiaoping, LIXudong, PENGJianping, ZENGXiantao. Application of trial sequential analysis in time-to-event data. Chinese Journal of Evidence-Based Medicine, 2017, 17(2): 239-242. doi: 10.7507/1672-2531.201607062 Copy

1.	Pogue J, Yusuf S. Overcoming the limitations of current meta-analysis of randomised controlled trials. Lancet, 1998, 351(9095): 47-52.
2.	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.
3.	Miladinovic B, Mhaskar R, Hozo I,et al. Optimal information size in trial sequential analysis of time-to-event outcomes reveals potentially inconclusive results because of the risk of random error. J Clin Epidemiol, 2013, 66(6): 654-659.
4.	曾宪涛, 冷卫东, 李胜, 等. 如何正确理解及使用 GRADE 系统. 中国循证医学杂志, 2011, 11(9): 985-990.
5.	陈耀龙, 杨克虎, 姚亮, 等. GRADE 系统方法学进展. 中国循证儿科杂志, 2013, 8(1): 64-65.
6.	陈耀龙, 姚亮, Norris S, 等. GRADE 在系统评价中应用的必要性及注意事项. 中国循证医学杂志, 2013, 13(12): 1401-1404.
7.	翁鸿, 李胜, 曾宪涛. 试验序贯分析在 Stata 软件中的实现. 中国循证医学杂志, 2016, 16(12): 1472-1476.
8.	曾宪涛, 张超. R 与 Meta 分析. 第 1 版. 北京: 军事医学科学出版社, 2014.
9.	Meng XY, Liao Y, Liu XP,et al. Concurrent cisplatin-based chemoradiotherapy versus exclusive radiotherapy in high-risk cervical cancer: a meta-analysis. Onco Targets Ther, 2016(9): 1875-1888.

1. Pogue J, Yusuf S. Overcoming the limitations of current meta-analysis of randomised controlled trials. Lancet, 1998, 351(9095): 47-52.
2. 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.
3. Miladinovic B, Mhaskar R, Hozo I,et al. Optimal information size in trial sequential analysis of time-to-event outcomes reveals potentially inconclusive results because of the risk of random error. J Clin Epidemiol, 2013, 66(6): 654-659.
4. 曾宪涛, 冷卫东, 李胜, 等. 如何正确理解及使用 GRADE 系统. 中国循证医学杂志, 2011, 11(9): 985-990.
5. 陈耀龙, 杨克虎, 姚亮, 等. GRADE 系统方法学进展. 中国循证儿科杂志, 2013, 8(1): 64-65.
6. 陈耀龙, 姚亮, Norris S, 等. GRADE 在系统评价中应用的必要性及注意事项. 中国循证医学杂志, 2013, 13(12): 1401-1404.
7. 翁鸿, 李胜, 曾宪涛. 试验序贯分析在 Stata 软件中的实现. 中国循证医学杂志, 2016, 16(12): 1472-1476.
8. 曾宪涛, 张超. R 与 Meta 分析. 第 1 版. 北京: 军事医学科学出版社, 2014.
9. Meng XY, Liao Y, Liu XP,et al. Concurrent cisplatin-based chemoradiotherapy versus exclusive radiotherapy in high-risk cervical cancer: a meta-analysis. Onco Targets Ther, 2016(9): 1875-1888.

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