Comparison of Aggregated N-of-1 Trials with Parallel and Crossover Randomized Controlled Trials Using Simulation Studies

被引:29
作者
Blackston, J. Walker [1 ]
Chapple, Andrew G. [2 ]
McGree, James M. [3 ]
McDonald, Suzanne [4 ]
Nikles, Jane [4 ]
机构
[1] Tulane Univ, Sch Publ Hlth & Trop Med, Dept Epidemiol, New Orleans, LA 70112 USA
[2] Louisiana State Univ, Hlth Sci Ctr, Sch Publ Hlth, Biostat Program, New Orleans, LA 70112 USA
[3] Queensland Univ Technol, Sch Math Sci, Brisbane, Qld 2434, Australia
[4] Univ Queensland, UQCCR, Brisbane, Qld 4006, Australia
关键词
N-of-1; trial; evidence-based medicine; comparative effectiveness; clinical trial; single-case study; simulation study; statistical methods; RCT; CHEMOTHERAPY; MEXILETINE;
D O I
10.3390/healthcare7040137
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: N-of-1 trials offer an innovative approach to delivering personalized clinical care together with population-level research. While increasingly used, these methods have raised some statistical concerns in the healthcare community. Methods: We discuss concerns of selection bias, carryover effects from treatment, and trial data analysis conceptually, then rigorously evaluate concerns of effect sizes, power and sample size through simulation study. Four variance structures for patient heterogeneity and model error are considered in a series of 5000 simulated trials with 3 cycles, which compare aggregated N-of-1 trials to parallel randomized controlled trials (RCTs) and crossover trials. Results: Aggregated N-of-1 trials outperformed both traditional parallel RCT and crossover designs when these trial designs were simulated in terms of power and required sample size to obtain a given power. N-of-1 designs resulted in a higher type-I error probability than parallel RCT and cross over designs when moderate-to-strong carryover effects were not considered or in the presence of modeled selection bias. However, N-of-1 designs allowed better estimation of patient-level random effects. These results reinforce the need to account for these factors when planning N-of-1 trials. Conclusion: N-of-1 trial designs offer a rigorous method for advancing personalized medicine and healthcare with the potential to minimize costs and resources. Interventions can be tested with adequate power with far fewer patients than traditional RCT and crossover designs. Operating characteristics compare favorably to both traditional RCT and crossover designs.
引用
收藏
页码:1 / 13
页数:13
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