Hazard ratio (HR) is usually regarded as the effect size in survival studies. Meanwhile, it is supposed to be perfect for pooling results in the meta-analysis of survival data. However, it does not function usually due to absence of original data for pooling HR. As a compromise method, entering data from reading Kaplan-Meier curves and follow-up times into the calculation spreadsheet can also be used to obtain related survival data. But related study on the subject is scarce, and opinions are inconsistent. Accordingly, we conduct this study to further illustrate the procedure in details.
Citation:
LIU Qing, DING Li. Accessibility and validation of survival data in survival curve for meta-analysis. Chinese Journal of Evidence-Based Medicine, 2019, 19(9): 1124-1130. doi: 10.7507/1672-2531.201904111
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- 1. 孙振球, 徐勇勇. 医学统计学. 北京: 人民卫生出版社, 2010: 299-325.
- 2. Sun W, Han X, Wu S, et al. Endoscopic resection versus surgical resection for early gastric cancer: a systematic review and meta-analysis. Medicine, 2015, 94(43): e1649.
- 3. Bhansali MS, Vaidya JS, Bhatt RG, et al. Chemotherapy for carcinoma of the esophagus: a comparison of evidence from meta-analyses of randomized trials and of historical control studies. Ann Oncol, 1996, 7(4): 355-359.
- 4. Tierney JF, Stewart LA, Ghersi D, et al. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials, 2007, 8: 16.
- 5. 周支瑞, 张天嵩, 李博, 等. 生存曲线中 Meta 分析适宜数据的提取与转换. 中国循证心血管医学杂志, 2014, 6(3): 243-247.
- 6. Lim JH, Kim J, Kim SG, et al. Long-term clinical outcomes of endoscopic vs. surgical resection for early gastric cancer with undifferentiated histology. Surg Endosc, 2019, DOI: 10.1007/s00464-018-06641-6.