A computerized system for detecting signals due to drug–drug interactions in spontaneous reporting systems

AIMS

In spontaneous reporting systems (SRS), there is a growing need for the automated detection of adverse drug reactions (ADRs) resulting from drug–drug interactions. In addition, special attention is also needed for systems facilitating automated data preprocessing. In our study, we set up a computerized system to signal possible drug–drug interactions by which data acquisition and signal detection could be carried out automatically and the process of data preprocessing could also be facilitated.

METHODS

This system was developed with Microsoft Visual Basic 6.0 and Microsoft Access was used as the database. Crude ADR reports submitted to Shanghai SRS from January 2007 to December 2008 were included in this study. The logistic regression method, the Ω shrinkage measure method, an additive model and a multiplicative model were used for automatic detection of drug–drug interactions where two drugs were used concomitantly.

RESULTS

A total of 33 897 crude ADR reports were acquired from the SRS automatically. The 10 drug combinations most frequently reported were found and the 10 most suspicious drug–drug ADR combinations for each method were detected automatically after the performance of the system.

CONCLUSIONS

Since the detection of drug–drug interaction depends upon the skills and memory of the professionals involved, is time consuming and the number of reports is increasing, this system might be a promising tool for the automated detection of possible drug–drug interactions in SRS.     

A prediction model‐based algorithm for computer‐assisted database screening of adverse drug reactions in the Netherlands

Purpose

The statistical screening of pharmacovigilance databases containing spontaneously reported adverse drug reactions (ADRs) is mainly based on disproportionality analysis. The aim of this study was to improve the efficiency of full database screening using a prediction model‐based approach.

Methods

A logistic regression‐based prediction model containing 5 candidate predictors was developed and internally validated using the Summary of Product Characteristics as the gold standard for the outcome. All drug‐ADR associations, with the exception of those related to vaccines, with a minimum of 3 reports formed the training data for the model. Performance was based on the area under the receiver operating characteristic curve (AUC). Results were compared with the current method of database screening based on the number of previously analyzed associations.

Results

A total of 25 026 unique drug‐ADR associations formed the training data for the model. The final model contained all 5 candidate predictors (number of reports, disproportionality, reports from healthcare professionals, reports from marketing authorization holders, Naranjo score). The AUC for the full model was 0.740 (95% CI; 0.734–0.747). The internal validity was good based on the calibration curve and bootstrapping analysis (AUC after bootstrapping = 0.739). Compared with the old method, the AUC increased from 0.649 to 0.740, and the proportion of potential signals increased by approximately 50% (from 12.3% to 19.4%).

Conclusions

A prediction model‐based approach can be a useful tool to create priority‐based listings for signal detection in databases consisting of spontaneous ADRs.     

A comparison of disproportionality analysis methods in national adverse drug reaction databases of China

Objective: Several disproportionality analysis methods are widely used for signal detection. The goal of this study was to compare the concordance of the performance characteristics of these methods in spontaneous reporting system of China.

Methods: Algorithms including reporting odds ratio (ROR), proportional reporting ratio (PRR) and information component (IC), a composite criterion previously used by Medicines and Healthcare Products Regulatory Agency (MHRA) were compared. Kappa coefficient was used as the gauge to test the concordance. Reports received in the year 2004 and 2005 were extracted for analysis in this study.

Results: After data processing, 361,872 reports representing 52,769 combinations were analysed. The analysis generated 24,022, 22,646, 5637 and 5302 signals of disproportionality by PRR, ROR, MHRA and IC, respectively. The kappa coefficient increased with the threshold of number of drug-adverse drug reactions (ADR) combination, and the coefficient exceeded 0.7 when the number of suspected drug–ADR exceeded 2.

Conclusion: This study shows that different measures used are broadly comparable in spontaneous reporting system in China when two or more cases per combination have been collected.     

中药药物不良反应评价与药物流行病学新方法

近年来,中药药物不良反应(ADR)报道不断增多,而中药的ADR评价有一定的难度。本文从讨论中药ADR的定义开始,讨论了药物流行病学的新方法,提出根据具体的情况选用合适的药物流行病学新方法来评价中药ADR。     

The nature of the scientific evidence leading to drug withdrawals for pharmacovigilance reasons in France

INTRODUCTION: Because of design, objectives and number of included subjects, clinical studies are insufficient to assess the safety of new drugs. Sometimes, serious adverse drug reactions (ADRs) led to withdrawal of the drug from the market after their approval. The objective of our study was to determine the scientific evidences leading to drug withdrawal for pharmacovigilance reasons in France. METHODS: Data coming from French Health Products Safety Agency, literature and Toulouse Pharmacovigilance Center allowed to identify all drugs withdrawn from the French market for pharmacovigilance reasons from 1998 to 2004. We classified data according to their study design (Randomized Clinical Trial [RCT], case serie or case report, case-control study, cohort study, observational study, animal study), the organ/system affected and the type of ADR. RESULTS: A total of 21 drugs were withdrawn for safety reasons between 1998 and 2004 in France. The most frequent ADRs were hepatic (n = 7), cardiovascular (n = 4) or neurological (n = 3) ones. Eleven withdrawals were due to type-B ('unexpected') reactions (52%). For 19 out of 21 drugs, scientific evidence leading to drug withdrawal came from spontaneous case reports (or case series). Among these, case reports were the sole evidence in 12 cases. Withdrawals were based on evidence from case reports in combination with case-control or cohort study in four cases, in combination with observational study in two cases or in combination with animal study in two other cases. In only one case, a RCT supported the decision. CONCLUSIONS: This study underlines the importance of spontaneous case reports in detecting signals and supporting withdrawal of drug for pharmacovigilance reasons in France. Health authorities suffer from lack of comparative data resource. In this perspective, a pharmaco-epidemiological population-based database could represent a helpful tool to both generate and test safety hypotheses.     

药品上市后不良反应监测及信号自动发现方法

本研究借鉴国外经验,通过数据收集、数据整理和计算机信号筛选3个方面探讨药品上市后不良反应监测和不良反应信号自动发现方法。监测的方法应尽可能多样化,数据编码字典要统一化,信号筛选算法也最好不要只选一种,整个监测-评价系统要有定期评估,以保证信号发现系统的良好运作。     

培美曲塞上市后安全信号的检测和分析

目的:检测培美曲塞上市后的安全信号,对其上市后安全性作初步评价, 为临床合理用药提供参考。方法:采用报告比值比法(ROR)对美国食品药品监督管理局(FDA)不良事件报告系统(AERS)数据库进行培美曲塞安全信号检测,并利用 SPSS 19.0 分析年龄、性别、用药时长、剂量及适应证对不良反应的影响。结果:在进行分析的5 397 235份报告中,查找到以培美曲塞为首要怀疑药物的不良反应报告4 219份,经ROR法检测,共得到173个培美曲塞安全信号,其中心血管系统信号21个。统计学分析发现,相比于其他系统ADR,心血管系统ADR在用药时长(P=0.445)中分布无统计学意义,在性别(P=0.008)、年龄(P=0.035)、用药剂量(P=0.003)、适应证(P=0.000)中分布有统计学意义,其中,男性患者、40岁以上、MPM和非鳞状NSCLC、剂量800~1 000 mg可能更易发生心血管系统ADR。结论:通过对培美曲塞安全信号的检测和分析发现,有必要对其进行进一步信号评价和验证,决定临床应用中是否采取相应风险防范措施。     

Exposure-time-varying hazard function ratios in case-control studies of drug effects

For many adverse effects of drugs, the instantaneous risk of an incident event per day of therapy (i.e., the hazard function) varies by duration of therapy and by prior exposure. In cohort studies of adverse drug effects time-varying hazard functions are easily modeled using standard statistical software packages. Tests of the hypothesis of a constant proportional hazard function ratio are also available. In case control studies, the need to consider time-varying hazard functions seems to be somewhat less well-recognized than in cohort studies. When the hazard function ratio for an adverse drug event is not constant over time, an overall single odds ratio (OR) estimated in a case control study not accounting for the time variation in the hazard function is a weighted average of duration-specific ORs with weights reflecting the distribution of exposure time in the study population. The resulting estimate depends not only on the drug but also on the exposure time distribution in the study population. This can lead to misleading conclusions when comparing the risks of two drugs within the same population and when comparing risks of the same drug in different populations. Analytic approaches for addressing time-varying hazard functions in case-control studies have been published but seem to be less used than in cohort studies. This article discusses adverse drug effects with time-varying hazard functions and methods for addressing these in case-control studies during study design, data collection, and analysis.     

Characteristics of drugs safety signals that predict safety related product information update

Purpose

Investigation of drug safety signals is one of the major tasks in pharmacovigilance. Among many potential signals identified, only a few reflect adverse drug reactions requiring regulatory actions, such as product information (PI) update. Limited information is available regarding the signal characteristics that might predict PI update following signal evaluation. The objective of this study was to identify signal characteristics associated with PI updates following signal evaluation by the European Medicines Agency Pharmacovigilance Risk Assessment Committee during 2012 to 2016.

Methods

A comparative study was performed based on data from 172 safety signals. Characteristics of signals were extracted from the European Pharmacovigilance Issues Tracking Tool database. Multivariable logistic regression analysis was used to assess the relationship between signal characteristics and the decision to update the PI.

Results

Multivariable logistic regression analysis showed that the presence of evidence in multiple types of data sources (adjusted odds ratio [OR] 7.8 95% CI [1.5, 40.1]); mechanistic plausibility of the drug‐event association (adjusted OR 3.9 95% CI [1.9, 8.0]); seriousness of the event (adjusted OR 4.2 95% CI [1.3, 13.9]); and age of drugs ≤5 years (adjusted OR 3.9 95% CI [1.2, 12.7]) were associated with the decision to change the PI (P < 0.05).

Conclusions

This study identified 4 characteristics of drug safety signals that have shown to be associated with PI changes as outcome of signal evaluation. These characteristics may be used as criteria for selection and prioritization of potential signals that are more likely to necessitate product information updates.     

Clinical perspectives in drug safety and adverse drug reactions

Adverse drug reactions (ADRs) remain a common clinical problem since they can mimic many diseases and cause significant morbidity and mortality. Judicious prescribing is important to minimize their occurrence. Apart from the recent identification of a few pharmacogenomic biomarkers for serious reactions, many remain unpredictable. Spontaneous reporting continues to play an important role in pharmacovigilance and the value of astute clinical observation and well-documented reports of suspicions of a causal link cannot be underestimated. Many national reporting schemes have developed considerable experience and expertise over many years and have large ADR databases, which are national assets. Despite advances in pharmacovigilance, numerous deficiencies have been identified; postmarketing surveillance remains the weakest link in the regulatory process. Regulatory authorities have tended to act later rather than sooner in response to safety signals, and this, when combined with under-reporting, may have led to exposure of a large number of patients to drug-related harm before restriction or withdrawal. In an attempt to improve vigilance, international surveillance may benefit by moving from its current passive/reactive mode toward active surveillance systems with a prospective, comprehensive and systematic approach to monitoring, collecting, analyzing and reporting data on ADRs. This will include increased pressure on pharmaceutical companies to conduct postmarketing studies. Such an active/proactive approach, while maintaining focus on ADR detection, could also aim to extend knowledge of safety, such that emerging changes in risk–benefit during a drug’s marketed life are effectively communicated to clinicians and patients. Drug safety monitoring and its regulation are now undergoing an overhaul and it is hoped that vigilance, public safety and trust will improve as a result.