Kürzinger Marie-Laure, Schück Stéphane, Texier Nathalie, Abdellaoui Redhouane, Faviez Carole, Pouget Julie, Zhang Ling, Tcherny-Lessenot Stéphanie, Lin Stephen, Juhaeri Juhaeri
Epidemiology and Benefit Risk Evaluation, Sanofi, Chilly-Mazarin, France.
Kappa Santé, Paris, France.
J Med Internet Res. 2018 Nov 20;20(11):e10466. doi: 10.2196/10466.
While traditional signal detection methods in pharmacovigilance are based on spontaneous reports, the use of social media is emerging. The potential strength of Web-based data relies on their volume and real-time availability, allowing early detection of signals of disproportionate reporting (SDRs).
This study aimed (1) to assess the consistency of SDRs detected from patients' medical forums in France compared with those detected from the traditional reporting systems and (2) to assess the ability of SDRs in identifying earlier than the traditional reporting systems.
Messages posted on patients' forums between 2005 and 2015 were used. We retained 8 disproportionality definitions. Comparison of SDRs from the forums with SDRs detected in VigiBase was done by describing the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, receiver operating characteristics curve, and the area under the curve (AUC). The time difference in months between the detection dates of SDRs from the forums and VigiBase was provided.
The comparison analysis showed that the sensitivity ranged from 29% to 50.6%, the specificity from 86.1% to 95.5%, the PPV from 51.2% to 75.4%, the NPV from 68.5% to 91.6%, and the accuracy from 68% to 87.7%. The AUC reached 0.85 when using the metric empirical Bayes geometric mean. Up to 38% (12/32) of the SDRs were detected earlier in the forums than that in VigiBase.
The specificity, PPV, and NPV were high. The overall performance was good, showing that data from medical forums may be a valuable source for signal detection. In total, up to 38% (12/32) of the SDRs could have been detected earlier, thus, ensuring the increased safety of patients. Further enhancements are needed to investigate the reliability and validation of patients' medical forums worldwide, the extension of this analysis to all possible drugs or at least to a wider selection of drugs, as well as to further assess performance against established signals.
虽然药物警戒中的传统信号检测方法基于自发报告，但社交媒体的使用正在兴起。基于网络的数据的潜在优势在于其数量和实时可用性，这有助于早期发现不成比例报告信号（SDR）。
本研究旨在（1）评估在法国从患者医学论坛检测到的SDR与从传统报告系统检测到的SDR的一致性，以及（2）评估SDR比传统报告系统更早识别信号的能力。
使用2005年至2015年期间在患者论坛上发布的信息。我们保留了8种不成比例定义。通过描述敏感性、特异性、阳性预测值（PPV）、阴性预测值（NPV）、准确性、受试者工作特征曲线和曲线下面积（AUC），对论坛中的SDR与VigiBase中检测到的SDR进行比较。提供了论坛和VigiBase中SDR检测日期之间以月为单位的时间差。
比较分析表明，敏感性范围为29%至50.6%，特异性范围为86.1%至95.5%，PPV范围为51.2%至75.4%，NPV范围为68.5%至91.6%，准确性范围为68%至87.7%。使用经验贝叶斯几何平均数指标时，AUC达到0.85。高达38%（12/32）的SDR在论坛中比在VigiBase中更早被检测到。
特异性、PPV和NPV较高。总体表现良好，表明医学论坛数据可能是信号检测的宝贵来源。总共高达38%（12/32）的SDR可能已被更早检测到，从而确保提高患者安全性。需要进一步改进，以研究全球患者医学论坛的可靠性和有效性，将此分析扩展到所有可能的药物或至少更广泛的药物选择，以及进一步评估针对既定信号的性能。
