Huh Ki Young, Song Ildae
Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea.
Clinical Trials Center, Seoul National University Hospital, Seoul 03080, Korea.
Transl Clin Pharmacol. 2024 Dec;32(4):177-186. doi: 10.12793/tcp.2024.32.e17. Epub 2024 Dec 16.
Identifying how trial sites collaborate is essential for multicenter trials. The ways in which collaboration among trial sites is established can vary according to study phase and clinical trial domains. In this study, we employed association rule mining to reveal trial collaboration. We used trial approval data provided by the Ministry of Food and Drug Safety in Korea and organized the trial sites. We collected trial information from 2012 to 2023 and categorized the trials according to study phase and clinical trial domain. We performed association rule mining based on study phase and clinical trial domain. We identified 209 valid trial sites and analyzed 11,107 clinical trials conducted during this period. By study phase, phase 1 trials accounted for the largest number (5,451), followed by phase 3 (2,492), others (1,826), and phase 2 (1,338). We found that phase 1 clinical trials had the highest lift metrics. The mean lift for phase 1 trials was 5.40, which was significantly greater than that of phase 2 (1.68) and phase 3 trials (1.72). Additionally, the network structure for trial collaboration in phase 1 trials was highly condensed, with several trial sites located in Seoul and Gyeonggi-do. Different trial collaboration characteristics were noted among clinical trial domains, with mean and variability of the lift metrics for pediatrics being the highest. In conclusion, association rule mining can identify collaborations among trial sites. Collaboration in phase 1 trials is relatively more exclusive than in other phases, and aspects of collaboration differ among clinical trial domains.
识别试验点如何协作对于多中心试验至关重要。试验点之间建立协作的方式可能因研究阶段和临床试验领域而异。在本研究中，我们采用关联规则挖掘来揭示试验协作情况。我们使用了韩国食品药品安全部提供的试验批准数据，并对试验点进行了整理。我们收集了2012年至2023年的试验信息，并根据研究阶段和临床试验领域对试验进行了分类。我们基于研究阶段和临床试验领域进行了关联规则挖掘。我们识别出209个有效的试验点，并分析了在此期间进行的11107项临床试验。按研究阶段划分，1期试验数量最多（5451项），其次是3期（2492项）、其他（1826项）和2期（1338项）。我们发现1期临床试验的提升指标最高。1期试验的平均提升度为5.40，显著高于2期（1.68）和3期试验（1.72）。此外，1期试验的协作网络结构高度集中，几个试验点位于首尔和京畿道。在临床试验领域中观察到了不同的试验协作特征，儿科的提升指标均值和变异性最高。总之，关联规则挖掘可以识别试验点之间的协作情况。1期试验中的协作相对比其他阶段更为排他，并且协作方面在不同临床试验领域存在差异。
