Vivekanandan Kalaiselvan, Tripathi Arunabh, Saurabh Archana, Kumar Ranvir, Kumar Rishi, Prasad Thota, Singh Gyanendra Nath
1 Indian Pharmacopoeia Commission, Ghaziabad, India.
Ther Innov Regul Sci. 2015 Nov;49(6):898-902. doi: 10.1177/2168479015589822.
The Pharmacovigilance Programme of India (PvPI) is responsible for collecting reports of adverse drug reactions (ADRs) to assess the association between particular drugs and ADRs. The aim of the present study was to apply statistical tools to determine associations between drugs and ADRs for signal detection in the PvPI.
Four methods were proposed for quantitative signal detection: one was based on Bayesian inference and others on classical inference procedures. The effectiveness of the proposed methods was assessed by applying them to 4 drug-ADR combinations.
The proposed methods were easy to apply and relevant to the Indian context. In selected methods, the information component value was more specific, whereas the proportional relative risk was more sensitive.
The proposed methods may help in the identification of new signals in Indian individual case safety reports.
印度药物警戒计划（PvPI）负责收集药品不良反应（ADR）报告，以评估特定药物与ADR之间的关联。本研究的目的是应用统计工具来确定PvPI中用于信号检测的药物与ADR之间的关联。
提出了四种定量信号检测方法：一种基于贝叶斯推理，其他基于经典推理程序。通过将这些方法应用于4种药物-ADR组合来评估所提出方法的有效性。
所提出的方法易于应用且与印度情况相关。在选定的方法中，信息成分值更具特异性，而比例相对风险更敏感。
所提出的方法可能有助于在印度个体病例安全报告中识别新信号。
