ObjectivesTo explore the characteristics of the international clinical studies using objective performance criteria (OPC) and provide a reference to design clinical trials and determine external controls.MethodsPubMed, The Cochrane Library and EMbase databases were searched for all clinical studies which used OPC. Two reviewers independently screened literature, extracted data and descriptive analysis was then performed.ResultsA total of 51 English language articles were included. Merely one was published in 2001, and others were published between 2010 and 2018. Twenty-seven articles (27/51, 52.9%) were published between 2017 and 2018, with accumulated impact factors of 411. In the article referring to the reasons for using the objective performance criteria, reasons for using OPC study was primarily the difficulties of randomization and comparison (8/11, 72.7%). Articles with cardiovascular disease and peripheral vascular disease accounted for 86%, and articles on the effectiveness or safety of medical devices accounted for 76.5%. Single-arm trial (40), randomized controlled trials (2), case-control studies (2), case series (5) and diagnostic tests (2) were included. OPCs were mostly derived from the data of clinical trials of other similar products, national standards, specialist association standard and meta-analysis of multiple clinical studies. A total of 27 articles (27/51, 52.9%) used hypothesis testing to compare research results with objective performance goal, and 24 articles (24/51, 47.1%) used the confidence interval method.ConclusionsOPC studies are primarily used for safety intervention and effect evaluation. OPC studies are developing very rapidly, especially in the field of cardiovascular studies. Methodological details are reported reasonably sufficient. Reasons for using OPC study are primarily the difficulties of randomization and comparison. Factors such as source of the OPC, sample size, and comparison method should be taken into account. The application of the OPC can not only solve the difficulties of the implementation of numerous clinical research, but also provide new insights for solving the practical difficulties of clinical research in the real-world.
ObjectiveTo 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. MethodsWe 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. ResultsAnalysis 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). ConclusionThere 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.