A single-group target value test sample size estimation parameter setting simulation study_Chinese Journal of Evidence-Based Medicine

Authors：

FENG Yuting ¹ , TAO Liyuan ² , CHAI Qianyun ¹ , LUO Minjing ¹ , GAO Yicheng ¹ , JIA Jinzhu ³ ,  FEI Yutong ¹

1. Center for Evidence-based Medicine, Beijing University of Chinese Medicine, Beijing 100029, P. R. China;
2. Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing 100191, P. R. China;
3. School of Public Health and Center for Statistical Science, Peking University, Beijing 100080, P. R. China;

Corresponding author：

FEI Yutong, Email: feiyt@bucm.edu.cn

Keywords：

Single arm; Performance goal; Sample size estimation; Continuity correction

DOI：

10.7507/1672-2531.202204086

Video：

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Objective To explore the parameter selection of different sample size estimation methods and the differences in estimation results in single-group target value clinical trials with rate as the outcome evaluation index. Methods We conducted a literature review to assess the method of target value selection for single-group target value clinical trials. Then, different values of target value (P₀), clinical expected value (P₁), and class II error level (β) were set through numerical simulation. Sample size results estimated using different sample size estimation methods were obtained using PASS software. The coefficient of variation, range/mean, analysis of variance and other methods were used to compare the differences between different methods. Results Analysis of the data simulation results showed: when the expected value P₁ was fixed, the sample size first decreased rapidly and then decreased slowly along with the increase or decrease of the targeted value P₀ on both sides of the sample size limit value. When the difference between P₀ and P₁ was within 0.15, the ratio before and after correction could be controlled within 0.9. When the difference between P₀ and P₁ was more than 0.6, the ratio before and after correction approached 0.5. When P₀+P₁≈1, the ratio of different standard error choices (Sp₀ or Sp₁) to the estimated sample size was close to 1. When 0.65<P₀+P₁<1.35, the ratio of different standard error choices (Sp₀ or Sp₁) to the estimated sample size was about 3:1. When the confidence was 0.8, P₀ and P₁ were between 0.25 and 0.75 and between 0.20 and 0.80, respectively. We found little difference among the sample sizes estimated using these five methods (CV<0.10, range/mean<0.2). Conclusion There are some differences among different sample size estimation methods, however, when P₀ and P₁ values are around 0.5, the differences between different methods are small, suggesting that appropriate methods should be selected for sample size estimation.

Citation： FENG Yuting, TAO Liyuan, CHAI Qianyun, LUO Minjing, GAO Yicheng, JIA Jinzhu, FEI Yutong. A single-group target value test sample size estimation parameter setting simulation study. Chinese Journal of Evidence-Based Medicine, 2022, 22(9): 1062-1070. doi: 10.7507/1672-2531.202204086 Copy

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1. 万霞, 刘建平. 临床研究中的样本量估算: (2)观察性研究. 中医杂志, 2007, 48(7): 599-601.
2. FDA Center for Devices and Radiological Health. Clinical study designs for catheter ablation devices for treatment of atrial flutter. Guidance for industry and FDA staff. Available at: https://www.fda.gov/media/71116/download.
3. 成琪. 临床试验配对二项资料两组率差和率比可信区间估计研究. 广州: 南方医科大学, 2012.
4. 李雪迎. 临床验证中的单组目标值法. 中国介入心脏病学杂志, 2015, 23(7): 393.
5. Head SJ, Mylotte D, Mack MJ, et al. Considerations and recommendations for the introduction of objective performance criteria for transcatheter aortic heart valve device approval. Circulation, 2016, 133(21): 2086-2093.
6. 李卫, 赵耐青. 单组目标值临床试验的统计学考虑. 中国卫生统计, 2017, 34(3): 505-508.
7. Miller F, Zohar S, Stallard N, et al. Approaches to sample size calculation for clinical trials in rare diseases. Pharm Stat, 2018, 17(3): 214-230.
8. 于明坤, 明扬, 夏如玉, 等. 国际目标值法临床研究的文献和方法学特征分析. 中国循证医学杂志, 2019, 19(11): 1308-1316.
9. Christiansen MP, Klaff LJ, Brazg R, et al. A prospective multicenter evaluation of the accuracy of a novel implanted continuous glucose sensor: PRECISE Ⅱ. Diabetes Technol Ther, 2018, 20(3): 197-206.
10. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group. Effectiveness of continuous glucose monitoring in a clinical care environment: evidence from the Juvenile Diabetes Research Foundation continuous glucose monitoring (JDRF-CGM) trial. Diabetes Care, 2010, 33(1): 17-22.
11. William WN, Feng L, Ferrarotto R, et al. Gefitinib for patients with incurable cutaneous squamous cell carcinoma: a single-arm phase II clinical trial. J Am Acad Dermatol, 2017, 77(6): 1110-1113.
12. Miller AB, Hoogstraten B, Staquet M, et al. Reporting results of cancer treatment. Cancer, 1981, 47(1): 207-214.
13. Cutlip DE, Garratt KN, Novack V, et al. 9-Month clinical and angiographic outcomes of the COBRA polyzene-f nanocoated coronary stent system. JACC Cardiovasc Interv, 2017, 10(2): 160-167.
14. Cutlip DE, Windecker S, Mehran R, et al. Clinical end points in coronary stent trials: a case for standardized definitions. Circulation, 2007, 115(17): 2344-2351.
15. Shammas NW, Pucillo A, Jenkins JS, et al. WIRION embolic protection system in lower extremity arterial interventions: results of the pivotal WISE LE trial. JACC Cardiovasc Interv, 2018, 11(19): 1995-2003.
16. Roberts D, Niazi K, Miller W, et al. Effective endovascular treatment of calcified femoropopliteal disease with directional atherectomy and distal embolic protection: final results of the DEFINITIVE Ca⁺⁺ trial. Catheter Cardiovasc Interv, 2014, 84(2): 236-244.
17. McKinsey JF, Zeller T, Rocha-Singh KJ, et al. Lower extremity revascularization using directional atherectomy: 12-month prospective results of the DEFINITIVE LE study. JACC Cardiovasc Interv, 2014, 7(8): 923-933.
18. Fleiss JL, Levin B, Paik MC. In statistical methods for rates and proportions. New York: John Wiley & Sons Inc, 2003.
19. Ryan TP. Sample size determination and power. New Jersey: Wiley, 2013.
20. Bell ML, Teixeira-Pinto A, McKenzie JE, et al. A myriad of methods: calculated sample size for two proportions was dependent on the choice of sample size formula and software. J Clin Epidemiol, 2014, 67(5): 601-605.
21. Ralph B, Agostino D, Belanger CA. The appropriateness of some common procedures for testing the equality of two independent binomial populations. Am Stat, 1988, 42(3): 198-202.

Chinese Journal of Evidence-Based Medicine

A single-group target value test sample size estimation parameter setting simulation study

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