Signal detection of methylphenidate by comparing a spontaneous reporting database with a claims database

Data mining is critical for signal detection in pharmacovigilance systems. In this study, we compared signals between spontaneous reporting data and health insurance claims data for a socially issued drug, methylphenidate. We implemented data-mining tools for signal detection in both databases: Reporting Odds Ratios (ROR), Proportional Reporting Ratios (PRR), Chi-squared test, and Information Component (IC), in addition to a Relative Risk (RR) tool in the claims database. The claims database generated 15, 15, 36, 1, and 1 adverse drug reactions (ADRs) by ROR, PRR, chi-square, IC, and RR, respectively. The World Health Organization (WHO) spontaneous database generated 91, 91, 137, and 96 ADRs by ROR, PRR, chi-square, and IC, respectively. We found seven potential matching associations from the claims and WHO databases, but only one of them was present in the Korean spontaneous reporting database. In Korea, spontaneous reporting is still underreported and there is a small amount of data for Koreans. Signal comparison between the claims and WHO databases can provide additional regulatory insight.     

Application of quantitative signal detection in the Dutch spontaneous reporting system for adverse drug reactions.

The primary aim of spontaneous reporting systems (SRSs) is the timely detection of unknown adverse drug reactions (ADRs), or signal detection. Generally this is carried out by a systematic manual review of every report sent to an SRS. Statistical analysis of the data sets of an SRS, or quantitative signal detection, can provide additional information concerning a possible relationship between a drug and an ADR. We describe the role of quantitative signal detection and the way it is applied at the Netherlands Pharmacovigilance Centre Lareb. Results of the statistical analysis are implemented in the traditional case-by-case analysis. In addition, for data-mining purposes, a list of associations of ADRs and suspected drugs that are disproportionally present in the database is periodically generated. Finally, quantitative signal generation can be used to study more complex relationships, such as drug-drug interactions and syndromes. The results of quantitative signal detection should be considered as an additional source of information, complementary to the traditional analysis. Techniques for the detection of drug interactions and syndromes offer a new challenge for pharmacovigilance in the near future.     

Drug-related deaths: an analysis of the Italian spontaneous reporting database.

BACKGROUND: Adverse drug reactions (ADRs) represent a major public health concern, with death as the ultimate adverse drug outcome. Despite the relevance of this, the frequency of fatal ADRs (FADRs) is to a large extent unknown. Although spontaneous reporting data cannot give an exact estimate of the magnitude of drug-related mortality, it may highlight the importance and large dimensions of this public health problem. OBJECTIVE: To describe the types and pattern of reported FADRs by analysing data from the national spontaneous reporting system in Italy. METHODS: The Italian Medicines Agency (AIFA) runs a pharmacovigilance database where all the individual case safety reports (since January 2001) are stored. We selected and then analysed in detail all the case reports (to the end of December 2006) in which death was reported as the outcome. We included in the study only FADR case reports with a probable or possible causality assessment, according to the criteria established by the WHO. In line with the Italian reporting form, we divided FADR reports into two groups: (i) suspected ADRs that caused death; and (ii) suspected ADRs that contributed to death. RESULTS: In the AIFA database 38 507 suspected ADR case reports were collected, of which 641 (1.66%) had a fatal outcome. We analysed 450 case reports (1.17% of total reports), 159 (35.33%) of them causing the patient's death and 291 (64.67%) contributing to death. The annual percentage of FADR reports followed a constant trend during the 6-year period. The majority of fatal reports (79%) were sent by hospital doctors. In total, 222 different drugs were suspected as causes of FADRs. 'Systemic anti-infective drugs' was the drug category associated with the highest percentage of FADRs (21.9%), followed by antineoplastic and immunomodulating agents (18.8%), and then by nervous system drugs (14.8%). Other drug categories involved in the fatal case reports were antithrombotic agents, NSAIDs and contrast media. CONCLUSIONS: The drugs most frequently involved in FADRs were drugs of wide usage with a narrow therapeutic range or those that caused serious skin or systemic allergic reactions. Ceftriaxone, ticlopidine and nimesulide were associated with the highest number of fatal case reports; the related FADRs were already known and recognized for each of these drugs. We highlight some cases reflecting probable inappropriate drug use by Italian physicians. This suggests a need for continued clinical pharmacology training and that many FADRs might be preventable through better medical and prescribing practice.     

一种ADR信号检测的改进算法及其在上海市ADR自发呈报数据库上的应用

目的 建立改进的信号检测算法并评估其实际检测效果.方法 建立基于新ADR报告(NAR)的信号检测算法;通过理论分析和实际演算比较基于报告数(REP)和基于药物-不良事件组合(DEC)两种算法的ADR检测效果,评估数据库中已知ADR报告对信号检测的影响;并将NAR算法应用于上海市ADR自发呈报数据库.结果 ①对上海市ADR自发呈报数据库部分数据(2006～2007年)进行了信号检测计算,结果发现基于DEC的算法会产生不合逻辑的虚假信号,而基于REP的算法能避免产生这类信号并能发现被DEC算法忽略的有价值信号;筛除已知ADR报告能提高信号检出率57%.②建立了包含2 650种药物,27 230种DEC的已知ADR数据库,可自动筛选NAR.③采用基于NAR的信号检测算法对上海市2004～2007年ADR自发呈报数据库进行检测,产生信号380条,包括加替沙星-低血糖反应、头孢他啶-过敏性休克,菌栀黄-荨麻疹等值得关注的信号.结论 基于NAR的算法能显著提高ADR信号的检测效率.     

Fluvastatin and hepatic reactions: a signal from spontaneous reporting in Italy.

BACKGROUND: Signal detection is a crucial element in recognising new adverse drug reactions (ADRs) as soon as possible. HMG-CoA reductase inhibitors ('statins'), the most potent cholesterol-lowering drugs, are generally well tolerated but can occasionally lead to liver toxicity. Pre- and postmarketing studies on statins revealed an incidence of 0.1-3% elevation in hepatic transaminase levels. However, these elevations are asymptomatic, reversible, dose related or probably due to other causes. Postmarketing studies clearly showed the lack of evidence of hepatotoxicity from statins, apart from some isolated case reports of serious hepatic damage described in the literature. It is still unclear whether serious hepatic reactions are dose related and more frequent than the expected rate in the general population. OBJECTIVE: In this study, the hypothesis that fluvastatin could cause serious liver injuries more than the other statins is investigated, in the light of a quantitative and qualitative signal analysis, drug consumption data and evidence from the literature. METHODS: The Italian Interregional Group of Pharmacovigilance (Gruppo Interregionale di Farmacovigilanza; GIF) is an example of signal detection within the Italian spontaneous ADR reporting system. The GIF database holds reports of suspected ADRs submitted by five Italian pharmacovigilance regional centres. In the GIF database, all reports of suspected ADRs are classified according to the WHO criteria for causality assessment. The reactions are coded according to the WHO Adverse Reaction Terminology and classified as serious or non-serious events on the basis of the WHO Critical Term List. Every 6 months the GIF database is analysed to extract potential signals through a qualitative case-by-case analysis and using a quantitative methodology called proportional reporting ratio (PRR). This methodology permitted us to identify the potential signal 'fluvastatin and hepatic reactions'. RESULTS: At 31 December 2004, the GIF database contained 35 757 reports with an annual reporting rate of 170 reports per million inhabitants. We found a total of 1260 reports of ADRs related to statins, including 178 of hepatic reactions. Sixty-nine reports were attributed to fluvastatin, which showed the highest PRR in comparison with the other statins. Fluvastatin was associated with 33 serious reactions, mainly hepatitis and cholestatic hepatitis. The number of reports of severe hepatotoxicity associated with fluvastatin started to increase from 2002. About half of them did not report other suspected or concomitant drugs and in one third the hepatotoxicity occurred after <1 month of therapy. Twenty-seven out of 33 patients were female, and fluvastatin was administered at 80 mg/day in 81% of cases reporting complete data on drug dosage. CONCLUSION: In the literature, serious hepatic reactions are rarely described in patients taking statins; however, data gathered by GIF suggest that cases of hepatotoxicity are reported more often than expected. In addition, GIF data seem to reveal that fluvastatin is more likely to cause hepatic reactions than the other statins. However, this is a preliminary signal and future evaluations are certainly needed to confirm it and to quantify this possible risk.     

Bench testing of nebulizers: a comparison of three methods.

Although nebulizers can vary widely in performance, there is no uniformly accepted method for bench testing these devices. In the present study, we compared three bench methods of measuring the performance of three commercial jet nebulizers (Whisper Jet [WJ; Marquest Medical, Englewood, CO], Sidestream [SS; Marquest Medical], and Vixone [VO; Westmed, Tucson, AZ] to assess the impact of the method of testing on reported nebulizer performance. Each nebulizer was charged with 3 mL of albuterol mixed with a radiotracer (technetium [99mTc]), and the radioactivity captured on a paper filter was expressed as a percentage of the nebulizer charge (% delivered). The nebulizers were tested with and without duplication of spontaneous respiration by a piston pump (spontaneous respiration and standing cloud methods, respectively). The nebulizers were also tested using a model of mechanical ventilation (mechanical ventilation method). For all three devices, the addition of the standardized breathing pattern significantly reduced the % delivered with all three nebulizers compared with the standing cloud method. For the standing cloud method, the presence of the T-piece/mouth-piece significantly reduced the % delivered with the WJ but not with the other two devices. The mechanical ventilation method had the lowest % delivered for all three devices. The magnitude of the differences between nebulizers varied with duration of treatment. The findings of this study emphasize the importance of bench testing that duplicates intended clinical usage, because significant differences in nebulizer performance may be manifested under certain clinical conditions but not under others.     

Providing drug information to health professionals and consumers: role and responsibility of the pharmaceutical manufacturer

There is no law requiring any pharmaceutical firm to maintain a drug information center for their products. The package insert that accompanies the product is all that is legally mandated. Roche and other drug manufacturers provide these services because they believe it is in their own best interest and that of the users of their products to do so. Pharmacists are currently involved in providing drug information in numerous settings, particularly health sciences schools, hospitals, colleges, federal agencies and associations, as well as corporations. To date, they have been frequent users of company drug information services. It is hoped this discussion will stimulate anyone in need of product information to contact the manufacturer. They have the most complete data available on their products and are generally willing to share their information with other drug information services, practitioners and, in a more limited way, consumers.     

Use of screening algorithms and computer systems to efficiently signal higher-than-expected combinations of drugs and events in the US FDA's spontaneous reports database.

Since 1998, the US Food and Drug Administration (FDA) has been exploring new automated and rapid Bayesian data mining techniques. These techniques have been used to systematically screen the FDA's huge MedWatch database of voluntary reports of adverse drug events for possible events of concern. The data mining method currently being used is the Multi-Item Gamma Poisson Shrinker (MGPS) program that replaced the Gamma Poisson Shrinker (GPS) program we originally used with the legacy database. The MGPS algorithm, the technical aspects of which are summarised in this paper, computes signal scores for pairs, and for higher-order (e.g. triplet, quadruplet) combinations of drugs and events that are significantly more frequent than their pair-wise associations would predict. MGPS generates consistent, redundant, and replicable signals while minimising random patterns. Signals are generated without using external exposure data, adverse event background information, or medical information on adverse drug reactions. The MGPS interface streamlines multiple input-output processes that previously had been manually integrated. The system, however, cannot distinguish between already-known associations and new associations, so the reviewers must filter these events. In addition to detecting possible serious single-drug adverse event problems, MGPS is currently being evaluated to detect possible synergistic interactions between drugs (drug interactions) and adverse events (syndromes), and to detect differences among subgroups defined by gender and by age, such as paediatrics and geriatrics. In the current data, only 3.4% of all 1.2 million drug-event pairs ever reported (with frequencies > or = 1) generate signals [lower 95% confidence interval limit of the adjusted ratios of the observed counts over expected (O/E) counts (denoted EB05) of > or = 2]. The total frequency count that contributed to signals comprised 23% (2.4 million) of the total number, 10.4 million of drug-event pairs reported, greatly facilitating a more focused follow-up and evaluation. The algorithm provides an objective, systematic view of the data alerting reviewers to critically important, new safety signals. The study of signals detected by current methods, signals stored in the Center for Drug Evaluation and Research's Monitoring Adverse Reports Tracking System, and the signals regarding cerivastatin, a cholesterol-lowering drug voluntarily withdrawn from the market in August 2001, exemplify the potential of data mining to improve early signal detection. The operating characteristics of data mining in detecting early safety signals, exemplified by studying a drug recently well characterised by large clinical trials confirms our experience that the signals generated by data mining have high enough specificity to deserve further investigation. The application of these tools may ultimately improve usage recommendations.     

Criteria-based adverse drug reaction reporting and the use of a relational database

The criteria-based ADR reporting program at Shands Hospital has been successful. When the Joint Commission reviewed this program in January 1991, they were satisfied that it met their standards. Efforts are now focusing on improving the capture of ADRs, which will make the information available from the database even more valuable. Data from Shands Hospital will contribute to postmarketing surveillance, patient care, and staff education, and these data will influence drug usage evaluations and the formulary. Observations will be used to recommend alternate therapies to prevent ADRs as well as methods to manage reactions should they occur. The listing of criteria has facilitated the reporting of ADRs at Shands Hospital, and communication of the information has been greatly enhanced by the ADR database. Efficiency has been improved as a result.     

Implementation of an automated signal detection method in the French pharmacovigilance database: a feasibility study

Purpose  

In France, early detection of adverse effects does not currently involve any automatic signal detection method. The present objective was to assess the feasibility and measure the potential benefit of the incorporation of an automatic signal detection tool (GPS_pH0) in the French pharmacovigilance system.     

The comparison of some pharmacokinetic parameters of sulphadimethoxine estimated by high performance liquid chromatography and three spectrophotometric methods

The influence of the method used for determination of drugs in biological fluids on the pharmacokinetic parameters of sulphadimethoxine was investigated in healthy adult human subjects. Sulphonamide concentrations were determined by four chemical methods: high performance liquid chromatography (HPLC) and three spectrophotometric techniques, i.e. Bratton-Marshall original method as well as Rieder's modification and author's modification of the Morris technique. The compatibility of pharmacokinetic parameter values calculated from these results was good, the correlation coefficients between HPLC and all spectrophotometric methods were high. It has also been shown that the phenotype of acetylation as well as moderate cigarette smoking which can induce some enzymes responsible for the formation of glucuronide conjugates, i.e. main metabolic pattern for sulphadimethoxine, does not affect the half-time of this drug.     

Comparison of three methods to find the vapor activity of a hydration step.

The formation of a stochiometric salt hydrate takes place at a well defined vapor activity. We have compared three methods to measure this vapor activity. In two of the methods we used a sorption balance in step mode and in ramp mode, respectively, and in one method we used a newly developed sorption microcalorimeter. The tests were made with the formation of morphine sulphate pentahydrate from its dihydrate at 25 degrees C. With all three methods this transition was found to take place at a vapor activity close to 0.21.     

三种方法检验盐酸左旋咪唑片剂含量的方法比较

目的 筛选比较各国药典中盐酸左旋咪唑片含量测定方法的优异.方法 利用重现实验和回收实验重点考查<中国药典>和<印度药典>所采用的高氯酸非水滴定方法和<美国药典>采用的高效液相梯度洗脱方法.结果 <中国药典>方法回收率为100.09%(RSD=3.66%);<印度药典>方法回收率为96.13%(RSD=0.86%);<...