Association of asthma therapy and Churg-Strauss syndrome: an analysis of postmarketing surveillance data

A Real-World Pharmacovigilance Study of Ceftazidime/Avibactam: Data Mining of the Food and Drug Administration Adverse Event Reporting System Database

Ceftazidime/avibactam (CAZ/AVI) is a combination of a well-known third-generation, broad-spectrum cephalosporin with a new beta-lactamase inhibitor that has been approved for the treatment of various infectious diseases (especially multidrug-resistant Gram-negative bacterial infections) by the Food and Drug Administration (FDA). The current study extensively assessed CAZ/AVI-related adverse events (AEs) in the real world through data mining of the FDA Adverse Event Reporting System (FAERS) database to better understand toxicities. The signals of CAZ/AVI-related AEs were quantified using disproportionality analyses, including the reporting odds ratio, the proportional reporting ratio, the Bayesian confidence propagation neural network, and the multi-item gamma Poisson shrinker algorithms. Out of 10,114,815 records retrieved from the FAERS database, 628 cases were identified, where CAZ/AVI was implicated as the primary suspect drug. A total of 61 preferred terms with significant disproportionality that simultaneously met the criteria of all four algorithms were retained. Several unexpected safety signals may also occur, including melena, hypernatremia, depressed level of consciousness, brain edema, petechiae, delirium, and shock hemorrhagic. The median onset time for AEs associated with CAZ/AVI was 4 days, with most cases occurring within 3 days after CAZ/AVI initiation.

Can glucagon-like peptide-1 receptor agonists cause acute kidney injury? An analytical study based on post-marketing approval pharmacovigilance data

Clinical studies after marketing have shown that the use of glucagon-like peptide-1 receptor agonist(GLP-1RA) may lead to acute kidney injury(AKI). However, few epidemiological studies have investigated the risk, clinical features, and outcomes of AKI caused by different GLP-1RA. In this study, Adverse Event Reporting System (FAERS) data were used to compare the association between different GLP-1RA and AKI in the real world.

METHODS

FAERS data from January 2004 to December 2021 were mined using disproportionality analysis and Bayesian analysis to determine the correlation between different GLP-1RA and AKI, and the onset time, mortality, and hospitalization rate of different GLP-1RA were analyzed.

RESULTS

We identified 2670 cases of AKI events associated with GLP-1RA, of which liraglutide was the most commonly reported (34.98%). The patients with AKI were mainly males (47.94%), and the age group was mainly 45-84 years old (73.15%). obese patients with weight more than 99kg (24.42%) were more likely to have AKI. According to different signal mining methods, reporting odds ratio (ROR) (1.50, 95% confidence interval =1.41-1.60) and Bayesian confidence Propagation neural network (0.57, 95% confidence interval =0.54), liraglutide was more strongly associated with AKI than other GLP-1RA. The median time to onset of AKI was 63 days [quartile range (IQR): 15-458.5 days]. In addition, the hospitalization rate and fatality rate of patients with GLP-1RA-related AKI were 45.28% and 4.23% respectively.

CONCLUSIONS

Based on the data in the FAERS database, we analyzed the risk, onset time, and adverse reaction outcomes of GLP-1RA-induced AKI in detail. The results showed that liraglutide had the highest risk of AKI. From the early stage of treatment, we need to monitor patients' renal function regularly, especially for patients with high kidney risks such as obesity and age.

Evaluation of quantitative signal detection in EudraVigilance for orphan drugs: possible risk of false negatives

Different strategies have been studied to allow a better characterization of the safety profile of orphan drugs soon after their approval. At the end of the development phases only few data are available because of the small number of subjects exposed to an orphan medicine for the treatment of rare or ultra-rare conditions. As a consequence, the evaluation of the safety profile is limited at the time of the first approval. In the post-marketing period, all available sources should be combined for a better understanding of the safety of orphan drugs. These sources, include outputs from large databases such as the European Medicines Agency’s EudraVigilance database. Analyses of data from this source are required to be performed by marketing authorization holders (MAHs) as part of their signal management activities. In 2018, the Pharmacovigilance Risk Assessment Committee (PRAC) assessed 114 confirmed signals, 79% of which included data from EudraVigilance. MAHs have access to statistical calculations for drug–event combinations (DECs) from EudraVigilance, provided in the form of measures of disproportionality of ratios of the observed proportion of spontaneous cases for a DEC in relation to the proportion of cases that would be expected if no association existed between the drug and the event. However, such statistical summaries for orphan drugs could be misleading because of the very limited safety data available for orphan drugs (under-reporting together with low numbers of exposed patients). In addition, the applied statistical methodology in most instances is constrained by different confounding factors such as indications of specific medicines and the wide spectrum of medical conditions/diseases of patients from whom reporting of disproportionality ratios are derived (i.e. proportions of DECs for orphan drugs (ODECs) from a small patient population suffering the rare disease and the proportion of DECs in the rest of the population represented in the whole database who have been treated with other medicines for a wide range of indications, and prescribed to treat completely different medical conditions). As expected, these statistical calculations produced not only signals of disproportionate reporting (SDRs) that are false positives, but also not sensitive enough to detect certain SDRs, thus resulting in false negatives. In the context of rare/ultra-rare life-threatening diseases where new molecules have been made available on the market on the basis of their proven efficacy, but with only limited safety data at the time of approval, false negatives could be a special concern since unlikely converted in positives or becoming positives with notable delay. Subgroup analyses (using a limited dataset comprising ADRs within specific individual case safety reports (ICSRs), sorted by indication/disease relevant to the drug of interest could, at least in part, possibly reduce some of the weaknesses resulting from the abovementioned confounding factors. On the other hand it could also cause the loss of some identification of SDRs that would be captured if no database restrictions had been undertaken. Therefore, data subgroup analysis should not be selected as a preferred approach to quantitative signal detection for orphan drugs but rather evaluated as complementary possibly to confirm negatives or to further characterize detected SDRs. Some examples of false negatives originating from quantitative signal detection in EudraVigilance applied to orphan drugs are discussed in this article.

Improving drug safety: From adverse drug reaction knowledge discovery to clinical implementation

Adverse drug reactions (ADRs) are a major public health concern, causing over 100,000 fatalities in the United States every year with an annual cost of $136 billion. Early detection and accurate prediction of ADRs is thus vital for drug development and patient safety. Multiple scientific disciplines, namely pharmacology, pharmacovigilance, and pharmacoinformatics, have been addressing the ADR problem from different perspectives. With the same goal of improving drug safety, this article summarizes and links the research efforts in the multiple disciplines into a single framework from comprehensive understanding of the interactions between drugs and biological system and the identification of genetic and phenotypic predispositions of patients susceptible to higher ADR risks and finally to the current state of implementation of medication-related decision support systems. We start by describing available computational resources for building drug-target interaction networks with biological annotations, which provides a fundamental knowledge for ADR prediction. Databases are classified by functions to help users in selection. Post-marketing surveillance is then introduced where data-driven approach can not only enhance the prediction accuracy of ADRs but also enables the discovery of genetic and phenotypic risk factors of ADRs. Understanding genetic risk factors for ADR requires well organized patient genetics information and analysis by pharmacogenomic approaches. Finally, current state of clinical decision support systems is presented and described how clinicians can be assisted with the integrated knowledgebase to minimize the risk of ADR. This review ends with a discussion of existing challenges in each of disciplines with potential solutions and future directions.

Evaluation of disproportionality safety signaling applied to healthcare databases

OBJECTIVE

To evaluate the performance of a disproportionality design, commonly used for analysis of spontaneous reports data such as the FDA Adverse Event Reporting System database, as a potential analytical method for an adverse drug reaction risk identification system using healthcare data.

RESEARCH DESIGN

We tested the disproportionality design in 5 real observational healthcare databases and 6 simulated datasets, retrospectively studying the predictive accuracy of the method when applied to a collection of 165 positive controls and 234 negative controls across 4 outcomes: acute liver injury, acute myocardial infarction, acute kidney injury, and upper gastrointestinal bleeding.

MEASURES

We estimate how well the method can be expected to identify true effects and discriminate from false findings and explore the statistical properties of the estimates the design generates. The primary measure was the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

RESULTS

For each combination of 4 outcomes and 5 databases, 48 versions of disproportionality analysis (DPA) were carried out and the AUC computed. The majority of the AUC values were in the range of 0.35 < AUC < 0.6, which is considered to be poor predictive accuracy, since the value AUC = 0.5 would be expected from mere random assignment. Several DPA versions achieved AUC of about 0.7 for the outcome Acute Renal Failure within the GE database. The overall highest DPA version across all 20 outcome-database combinations was the Bayesian Information Component method with no stratification by age and gender, using first occurrence of outcome and with assumed time-at-risk equal to duration of exposure + 30 d, but none were uniformly optimal. The relative risk estimates for the negative control drug-event combinations were very often biased either upward or downward by a factor of 2 or more. Coverage probabilities of confidence intervals from all methods were far below nominal.

CONCLUSIONS

The disproportionality methods that we evaluated did not discriminate true positives from true negatives using healthcare data as they seem to do using spontaneous report data.

Life-threatening dermatologic adverse events in oncology

The incidences of life-threatening toxicities such as Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are inconsistently reported. The potential association of anticancer agents with SJS or TEN has not been systematically investigated. We searched the literature (Ovid: 1950 to June 2013 and PubMed: 1948 to June 2013) using terms for SJS/TEN and anticancer therapies. Primary case reports, case series, and clinical trials were included. In addition, MedWatch, the Food and Drug Administration Adverse Event Reporting System (FAERS), was searched (1968 to August 2012) for SJS/TEN reports associated with anticancer therapies. Proportional reporting ratios (PRR>2, N>3), empirical Bayes geometric mean (EBGM>2, N>3), and lower 95% confidence interval (EBGM0.05>2) were used as thresholds to constitute a signal of association between SJS/TEN and anticancer drugs. There were 46 SJS and 37 TEN cases associated with 18 and 22 anticancer drugs in the literature, respectively. Among cases in the FAERS, significant signals were associated with SJS for bendamustine and with TEN for bendamustine, busulfan, chlorambucil, fludarabine, lomustine, and procarbazine. Several drugs reported in the published literature to be associated with SJS/TEN were not found to have significant signals in FAERS. Proactive pharmacovigilance to detect and define safety signals serves to aid oncology practitioners in the recognition of possible, yet uncommon, serious, and/or life-threatening skin reactions.

Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area

PURPOSE

Disproportionality screening analysis is acknowledged as a tool for performing signal detection in databases of adverse drug reactions (ADRs), e.g., in the European Union (EU) Drug Authority setting. The purpose of this study was to explore the possibility of decreasing false-positive signals of disproportionate reporting (SDR) by calculating the proportional reporting ratio (PRR)-by-therapeutic area (TA), while still maintaining the ability to detect relevant SDRs.

METHODS

In the EudraVigilance (EV) Database, output from PRR calculated with a restricted TA comparator background was compared in detail to output from conventional authority-setting PRR calculations for four drugs: bicalutamide, abiraterone, metformin, and vildagliptin, within the TAs of prostate gland disease and type 2 diabetes mellitus.

RESULTS

ADR reports per investigated drug ranged from 2,400 to 50,000. The PRR-TA's ability to detect true-positive SDRs (as acknowledged in approved labeling) was increased compared to the conventional PRR, and performed 8-31 % better than a recently proposed stricter EU-SDR definition. The PRR-TA removed false SDRs confounded by disease or disease spill-over by up to 63 %, while retaining/increasing the number of unclassified SDRs relevant for manual validation, and thereby improving the ratio between confounded SDRs (i.e., noise) and unclassified SDRs for all investigated drugs (possible signals).

CONCLUSIONS

The performance of the PRR was improved by background restriction with the PRR-TA method; the number of false-positive SDRs decreased, and the ability to detect true-positive SDRs increased, improving the signal-to-noise ratio. Further development and validation of the method is needed within other TAs and databases, and for disproportionality analysis methods.

Acute kidney injury and bisphosphonate use in cancer: a report from the research on adverse drug events and reports (RADAR) project

PURPOSE

To determine whether acute kidney injury (AKI) is identified within the US Food and Drug Administration's Adverse Events and Reporting System (FDA AERS) as an adverse event resulting from bisphosphonate (BP) use in cancer therapy.

METHODS

A search of the FDA AERS records from January 1998 through June 2009 was performed; search terms were "renal problems" and all drug names for BPs. The search resulted in 2,091 reports. We analyzed for signals of disproportional association by calculating the proportional reporting ratio for zoledronic acid (ZOL) and pamidronate. Literature review of BP-associated renal injury within the cancer setting was conducted.

RESULTS

Four hundred eighty cases of BP-associated acute kidney injury (AKI) were identified in patients with cancer. Two hundred ninety-eight patients (56%) were female; mean age was 66 ± 10 years. Multiple myeloma (n = 220, 46%), breast cancer (n = 98, 20%), and prostate cancer (n = 24, 5%) were identified. Agents included ZOL (n = 411, 87.5%), pamidronate (n = 8, 17%), and alendronate (n = 36, 2%). Outcomes included hospitalization (n = 304, 63.3%) and death (n = 68, 14%). The proportional reporting ratio for ZOL was 1.22 (95% CI, 1.13 to 1.32) and for pamidronate was 1.55 (95% CI, 1.25 to 1.65), reflecting a nonsignificant safety signal for both drugs.

CONCLUSION

AKI was identified in BP cancer clinical trials, although a safety signal for BPs and AKI within the FDA AERS was not detected. Our findings may be attributed, in part, to clinicians who believe that AKI occurs infrequently; ascribe the AKI to underlying premorbid disease, therapy, or cancer progression; or consider that AKI is a known adverse drug reaction of BPs and thus under-report AKI to the AERS.

A reference standard for evaluation of methods for drug safety signal detection using electronic healthcare record databases

BACKGROUND

The growing interest in using electronic healthcare record (EHR) databases for drug safety surveillance has spurred development of new methodologies for signal detection. Although several drugs have been withdrawn postmarketing by regulatory authorities after scientific evaluation of harms and benefits, there is no definitive list of confirmed signals (i.e. list of all known adverse reactions and which drugs can cause them). As there is no true gold standard, prospective evaluation of signal detection methods remains a challenge.

OBJECTIVE

Within the context of methods development and evaluation in the EU-ADR Project (Exploring and Understanding Adverse Drug Reactions by integrative mining of clinical records and biomedical knowledge), we propose a surrogate reference standard of drug-adverse event associations based on existing scientific literature and expert opinion.

METHODS

The reference standard was constructed for ten top-ranked events judged as important in pharmacovigilance. A stepwise approach was employed to identify which, among a list of drug-event associations, are well recognized (known positive associations) or highly unlikely ('negative controls') based on MEDLINE-indexed publications, drug product labels, spontaneous reports made to the WHO's pharmacovigilance database, and expert opinion. Only drugs with adequate exposure in the EU-ADR database network (comprising ≈60 million person-years of healthcare data) to allow detection of an association were considered. Manual verification of positive associations and negative controls was independently performed by two experts proficient in clinical medicine, pharmacoepidemiology and pharmacovigilance. A third expert adjudicated equivocal cases and arbitrated any disagreement between evaluators.

RESULTS

Overall, 94 drug-event associations comprised the reference standard, which included 44 positive associations and 50 negative controls for the ten events of interest: bullous eruptions; acute renal failure; anaphylactic shock; acute myocardial infarction; rhabdomyolysis; aplastic anaemia/pancytopenia; neutropenia/agranulocytosis; cardiac valve fibrosis; acute liver injury; and upper gastrointestinal bleeding. For cardiac valve fibrosis, there was no drug with adequate exposure in the database network that satisfied the criteria for a positive association.

CONCLUSION

A strategy for the construction of a reference standard to evaluate signal detection methods that use EHR has been proposed. The resulting reference standard is by no means definitive, however, and should be seen as dynamic. As knowledge on drug safety evolves over time and new issues in drug safety arise, this reference standard can be re-evaluated.

Bisphosphonates and nonhealing femoral fractures: analysis of the FDA Adverse Event Reporting System (FAERS) and international safety efforts: a systematic review from the Research on Adverse Drug Events And Reports (RADAR) project

BACKGROUND

In the United States, hip fracture rates have declined by 30% coincident with bisphosphonate use. However, bisphosphonates are associated with sporadic cases of atypical femoral fracture. Atypical femoral fractures are usually atraumatic, may be bilateral, are occasionally preceded by prodromal thigh pain, and may have delayed fracture-healing. This study assessed the occurrence of bisphosphonate-associated nonhealing femoral fractures through a review of data from the U.S. FDA (Food and Drug Administration) Adverse Event Reporting System (FAERS) (1996 to 2011), published case reports, and international safety efforts.

METHODS

We analyzed the FAERS database with use of the proportional reporting ratio (PRR) and empiric Bayesian geometric mean (EBGM) techniques to assess whether a safety signal existed. Additionally, we conducted a systematic literature review (1990 to February 2012).

RESULTS

The analysis of the FAERS database indicated a PRR of 4.51 (95% confidence interval [CI], 3.44 to 5.92) for bisphosphonate use and nonhealing femoral fractures. Most cases (n = 317) were attributed to use of alendronate (PRR = 3.32; 95% CI, 2.71 to 4.17). In 2008, international safety agencies issued warnings and required label changes. In 2010, the FDA issued a safety notification, and the American Society for Bone and Mineral Research (ASBMR) issued recommendations about bisphosphonate-associated atypical femoral fractures.

CONCLUSIONS

Nonhealing femoral fractures are unusual adverse drug reactions associated with bisphosphonate use, as up to 26% of published cases of atypical femoral fractures exhibited delayed healing or nonhealing.

Data mining methodologies for pharmacovigilance

Medicines are designed to cure, treat, or prevent diseases; however, there are also risks in taking any medicine - particularly short term or long term adverse drug reactions (ADRs) can cause serious harm to patients. Adverse drug events have been estimated to cause over 700,000 emergency department visits each year in the United States. Thus, for medication safety, ADR monitoring is required for each drug throughout its life cycle, including early stages of drug design, different phases of clinical trials, and postmarketing surveillance. Pharmacovigilance (PhV) is the science that concerns with the detection, assessment, understanding and prevention of ADRs. In the pre-marketing stages of a drug, PhV primarily focuses on predicting potential ADRs using preclinical characteristics of the compounds (e.g., drug targets, chemical structure) or screening data (e.g., bioassay data). In the postmarketing stage, PhV has traditionally involved in mining spontaneous reports submitted to national surveillance systems. The research focus is currently shifting toward the use of data generated from platforms outside the conventional framework such as electronic medical records (EMRs), biomedical literature, and patient-reported data in online health forums. The emerging trend of PhV is to link preclinical data from the experimental platform with human safety information observed in the postmarketing phase. This article provides a general overview of the current computational methodologies applied for PhV at different stages of drug development and concludes with future directions and challenges.

Comparative analysis of pharmacovigilance methods in the detection of adverse drug reactions using electronic medical records

OBJECTIVE

Medication  safety requires that each drug be monitored throughout its market life as early detection of adverse drug reactions (ADRs) can lead to alerts that prevent patient harm. Recently, electronic medical records (EMRs) have emerged as a valuable resource for pharmacovigilance. This study examines the use of retrospective medication orders and inpatient laboratory results documented in the EMR to identify ADRs.

METHODS

Using 12 years of EMR data from Vanderbilt University Medical Center (VUMC), we designed a study to correlate abnormal laboratory results with specific drug administrations by comparing the outcomes of a drug-exposed group and a matched unexposed group. We assessed the relative merits of six pharmacovigilance measures used in spontaneous reporting systems (SRSs): proportional reporting ratio (PRR), reporting OR (ROR), Yule's Q (YULE), the χ(2) test (CHI), Bayesian confidence propagation neural networks (BCPNN), and a gamma Poisson shrinker (GPS).

RESULTS

We systematically evaluated the methods on two independently constructed reference standard datasets of drug-event pairs. The dataset of Yoon et al contained 470 drug-event pairs (10 drugs and 47 laboratory abnormalities). Using VUMC's EMR, we created another dataset of 378 drug-event pairs (nine drugs and 42 laboratory abnormalities). Evaluation on our reference standard showed that CHI, ROR, PRR, and YULE all had the same F score (62%). When the reference standard of Yoon et al was used, ROR had the best F score of 68%, with 77% precision and 61% recall.

CONCLUSIONS

Results suggest that EMR-derived laboratory measurements and medication orders can help to validate previously reported ADRs, and detect new ADRs.

Amiodarone-associated optic neuropathy: a critical review

Although amiodarone is the most commonly prescribed anti-arrhythmic drug, its use is limited by serious toxicities, including optic neuropathy. Current reports of amiodarone-associated optic neuropathy identified from the Food and Drug Administration's Adverse Event Reporting System and published case reports were reviewed. A total of 296 reports were identified: 214 from the Adverse Event Reporting System, 59 from published case reports, and 23 from adverse events reports for patients enrolled in clinical trials. Mean duration of amiodarone therapy before vision loss was 9 months (range 1-84 months). Insidious onset of amiodarone-associated optic neuropathy (44%) was the most common presentation, and nearly one third were asymptomatic. Optic disk edema was present in 85% of cases. Following drug cessation, 58% had improved visual acuity, 21% were unchanged, and 21% had further decreased visual acuity. Legal blindness (<20/200) was noted in at least one eye in 20% of cases. Close ophthalmologic surveillance of patients during the tenure of amiodarone administration is warranted.

Disproportionality analysis for signal detection of implantable cardioverter-defibrillator-related adverse events in the Food and Drug Administration Medical Device Reporting System

BACKGROUND

The Food and Drug Administration (FDA) became aware of lead fracture and inappropriate shock events related to Sprint Fidelis leads in January 2007. The manufacturer announced a voluntary market withdrawal in October 2007.

AIM

Our aim was to retrospectively evaluate this safety signal using disproportionality analysis to estimate whether disproportionality analysis could have detected this particular safety signal earlier than actually occurred.

MATERIALS AND METHODS

The Manufacturer and User Facility Device Experience (MAUDE) database contains reports on device-related adverse events, of which, FDA receives several hundred thousand every year. For each manufacturer, a list of the top lead brand names was ranked by frequency of reports. We used the Multi-item Gamma Poisson Shrinker (MGPS) method for analysis. We isolated 11 top-reported implantable cardioverter defibrillator (ICD) lead brand names. Using MGPS methodology, we calculated the one-sided 95% lower confidence bound EB05 on the empirical Bayes geometric mean of the reporting ratio.

RESULTS

We performed individual MGPS analysis for each of the top reported adverse events in 2006 for ICD leads. Fidelis had the highest EB05 scores for lead fractures and inappropriate shock.

DISCUSSION

Through disproportionality analysis of the MAUDE database, we were able to identify known safety signals associated with the Medtronic Sprint Fidelis lead.

CONCLUSION

If utilized at the time, this disproportionality analysis would have identified signals earlier for lead fractures, oversensing, high impedance, and inappropriate shock.

Are all quantitative postmarketing signal detection methods equal? Performance characteristics of logistic regression and Multi-item Gamma Poisson Shrinker

PURPOSE

The detection of safety signals with medicines is an essential activity to protect public health. Despite widespread acceptance, it is unclear whether recently applied statistical algorithms provide enhanced performance characteristics when compared with traditional systems. Novartis has adopted a novel system for automated signal detection on the basis of disproportionality methods within a safety data mining application (Empirica™ Signal System [ESS]). ESS uses two algorithms for routine analyses: empirical Bayes Multi-item Gamma Poisson Shrinker and logistic regression (LR).

METHODS

A model was developed comprising 14 medicines, categorized as "new" or "established." A standard was prepared on the basis of safety findings selected from traditional sources. ESS results were compared with the standard to calculate the positive predictive value (PPV), specificity, and sensitivity. PPVs of the lower one-sided 5% and 0.05% confidence limits of the Bayes geometric mean (EB05) and of the LR odds ratio (LR0005) almost coincided for all the drug-event combinations studied.

RESULTS

There was no obvious difference comparing the PPV of the leading Medical Dictionary for Regulatory Activities (MedDRA) terms to the PPV for all terms. The PPV of narrow MedDRA query searches was higher than that for broad searches. The widely used threshold value of EB05 = 2.0 or LR0005 = 2.0 together with more than three spontaneous reports of the drug-event combination produced balanced results for PPV, sensitivity, and specificity.

CONCLUSIONS

Consequently, performance characteristics were best for leading terms with narrow MedDRA query searches irrespective of applying Multi-item Gamma Poisson Shrinker or LR at a threshold value of 2.0. This research formed the basis for the configuration of ESS for signal detection at Novartis.

A potential competition bias in the detection of safety signals from spontaneous reporting databases

PURPOSE

To study whether reports related to known drug-event associations could hinder the detection of new signals by increasing the detection thresholds when using disporportionality analyses in spontaneous reporting (SR) databases.

METHODS

The French SR database (2005-2006 data) was used to test this hypothesis for the following events: bleeding, headache, hepatitis, myalgia, myocardial infarction, stroke, and toxic epidermal necrolysis (TEN). For each of these, using the Proportional Reporting Ratio (PRR) and the Reporting Odds Ratio (ROR), the number of cases needed to trigger a signal out of 50, 100, and 200 reports for a hypothetical newly introduced drug were computed before and after removing from the database reports involving drugs known to be associated with the event.

RESULTS

For bleeding and stroke, removing potentially competitive data resulted in a decrease of the number of cases needed to trigger a signal for a newly introduced drug for both PRR and ROR (e.g., from 9 to 4, and 5 to 3 cases out of 50 reports for bleeding and stroke, respectively using the PRR). They were not or only slightly modified for the other studied events.

CONCLUSIONS

Removing reports related to known drug-event associations could increase the sensitivity of signal detection in SR databases. This should be considered when using SR databases for signal detection as it could result in earlier identification of new drug-event associations.

The course of asthma in Churg-Strauss syndrome

OBJECTIVES

Asthma is one of the key features of Churg-Strauss syndrome (CSS); however its course in the disease is unclear. The aim of this study was to analyze the asthma course in CSS patients.

PATIENTS AND METHODS

We conducted a retrospective study of 22 CSS patients. Medical documentation was studied and patients were questioned about asthma symptoms during follow-up visits, which took place at four points of the disease. These points, at which lung function tests were performed, were CSS diagnosis; introduction of treatment at hospital discharge; and assessment of the first and last clinical and laboratory CSS remissions. Asthma control and severity were assessed in compliance with current guidelines.

RESULTS

In the asthmatic group examined, 21 patients had an adult-onset asthma, with a mean age of onset 35.5 ± 11.8 years, preceded by sinusitis (100%) and nasal polyposis (36%). Asthma at its onset was severe in 68.5%, moderate in 27%, and very poorly controlled in 21 patients. Atopy was present in 64% of patients. Onset of vasculitic symptoms and CSS diagnosis was accompanied by high blood eosinophilia (maximal 7.2 x 10(3)/l [1.2 - 32], asthma exacerbation with airway obstruction in 16 patients (mean values of FEV1 68.8 ± 17.5% and FVC 84.8 ± 19.6%), and lung involvement. After introducing the treatment and achieving stable remission, asthma severity/control and lung function tests (forced expiratory volume in 1 s 92.7 ± 13.3%, and forced vital capacity 101 ± 15.5%; p < .001) improved.

CONCLUSIONS

Asthma in CSS, although severe as its onset improves after achieving CSS remission.

Prospective data mining of six products in the US FDA Adverse Event Reporting System: disposition of events identified and impact on product safety profiles

BACKGROUND

The use of data mining has increased among regulators and pharmaceutical companies. The incremental value of data mining as an adjunct to traditional pharmacovigilance methods has yet to be demonstrated. Specifically, the utility in identifying new safety signals and the resources required to do so have not been elucidated.

OBJECTIVES

To analyse the number and types of disproportionately reported product-event combinations (DRPECs), as well as the final disposition of each, in order to understand the potential utility and resource implications of routinely conducting data mining in the US FDA Adverse Event Reporting System (AERS).

METHODS

We generated DRPECs from AERS for six of Wyeth's products, prospectively tracked their dispositions and evaluated the appropriate DRPECs in the company's safety database. We chose EB05 (the lower bound of the 90% confidence interval around the Empirical Bayes Geometric Mean) > or =2 as the appropriate metric, employing stratification based on age, sex and year of report.

RESULTS

A total of 861 DRPECs were identified - the average number of DRPECs was 144 per product. The proportion of unique preferred terms (PTs) in AERS for each drug with an EB05 > or =2 was similar across the six products (5.1-8.5%). Overall, 64.0% (551) of the DRPECs were closed after the initial screening (44.8% labelled, 14.3% indication related, 4.9% non-interpretable). An additional 9.9% (85) had been reviewed within the prior year and were not further reviewed. The remaining 26.1% (225) required full case review. After review of all pertinent reports and additional data, it was determined which of the DRPECs necessitated a formal review by the company's ongoing Safety Review Team (SRT) process. In total, 3.6% (31/861) of the DRPECs, yielding 16 medical concepts, were reviewed by the SRT, leading to seven labelling changes. These labelling changes involved 1.9% of all DRPECs generated. Four of the six compounds reviewed as part of this pilot had an identified labelling change. The workload required for this pilot, which was driven primarily by those DRPECs requiring review, was extensive, averaging 184 hours per product.

CONCLUSION

The number of DRPECs identified for each drug approximately correlated with the number of unique PTs in the database. Over one-half of DRPECs were either labelled as per the company's reference safety information (RSI) or were under review after identification by traditional pharmacovigilance activities, suggesting that for marketed products these methods do identify adverse events detected by traditional pharmacovigilance methods. Approximately three-quarters of the 861 DRPECs identified were closed without case review after triage. Of the approximately one-quarter of DRPECs that required formal case review, seven resulted in an addition to the RSI for the relevant products. While this pilot does not allow us to comment on the utility of routine data mining for all products, it is significant that several new safety concepts were identified through this prospective exercise.

Thrombocytopenia from combination treatment with oseltamivir and probenecid: case report, MedWatch data summary, and review of the literature

The possibility of an avian flu pandemic has spurred interest in preventive treatments with antivirals such as oseltamivir. Combining treatment with probenecid to delay excretion may extend limited supplies of oseltamivir. We previously conducted a pharmacokinetic study of oseltamivir plus probenecid among healthy volunteers. In this article, we describe a 68-year-old woman who, during the pharmacokinetic study, developed severe thrombocytopenia 2 weeks after starting oseltamivir plus probenecid. She was receiving no other drug therapy at the time. Her platelet count decreased from 200 to 15 x 10(3)/mm(3), although no clinically evident bleeding abnormalities were noted. The two drugs were discontinued. One week later, without any therapeutic intervention, her platelet count returned to normal. By using the Naranjo adverse drug reaction probability scale to assess the strength of the association between the drugs and the adverse event, a score of 7 was derived for both drugs, indicating that the association was probable. We found no previous literature reports of thrombocytopenia associated with either drug. However, a review of the United States Food and Drug Administration's Adverse Event Reporting System database found 93 cases of thrombocytopenia and/or decreased platelet counts associated with oseltamivir and 24 cases associated with probenecid administration. Signal detection analyses were significant for oseltamivir (p=0.001), but not probenecid. The underlying mechanism of thrombocytopenia with these drugs is unknown. Clinicians should be aware that the use of oseltamivir and probenecid has been reported to be associated with thrombocytopenia.

Churg-Strauss syndrome associated with montelukast therapy

Churg-Strauss syndrome is a rare form of eosinophilic vasculitis associated with asthma. Several cases of eosinophilic conditions including Churg-Strauss syndrome have recently been reported in asthmatic patients being treated with antileukotriene receptor antagonists. However, whether these drugs have a direct pathogenic role remains controversial. We describe two patients who developed Churg-Strauss syndrome after starting treatment with montelukast.

Venous thromboembolism in myelodysplastic syndrome patients receiving lenalidomide: results from postmarketing surveillance and data mining techniques

BACKGROUND AND OBJECTIVES

Multiple myeloma treatment with lenalidomide-based regimens is associated with risk of venous thromboembolism (VTE), particularly during concomitant use with erythropoiesis-stimulating agents (ESAs). The risk of VTE in myelodysplastic syndrome (MDS) patients treated with lenalidomide is not well characterized and the background risk in untreated patients is not known. This study set out to determine the reporting rate of VTE in MDS patients on lenalidomide in the two years of postmarketing experience in the US, and to investigate whether there is a disproportional signal of VTE in MDS patients on lenalidomide by screening the US FDA Adverse Event Reporting System (AERS) safety database.

METHODS

The MDS population exposed to lenalidomide was obtained from RevAssist, the company's proprietary restrictive distribution programme. VTE reports were identified from the company's postmarketing surveillance safety database. The FDA AERS database was used for disproportionality analysis, and signal scores computed using three algorithms: multi-item gamma Poisson shrinker (MGPS), proportional reporting ratio (PRR), and reporting odds ratios (ROR).

RESULTS

A total of 7764 MDS patients were prescribed lenalidomide during the first two years of commercial use in the US. VTE representing deep vein thrombosis and pulmonary embolism was reported in 41 patients, a reporting rate of 0.53%. The computed signal scores did not exceed the statistical threshold for identification of a significant disproportional signal for VTE in MDS reports involving use of lenalidomide without concomitant use of ESAs. However, a disproportional signal of VTE was detected in MDS reports where lenalidomide was concurrently used with ESAs.

CONCLUSION

The VTE reporting rate for MDS patients receiving lenalidomide during the first two years of postmarketing exposure was low (0.53%). Disproportionality analysis demonstrated a statistically meaningful association of VTE with lenalidomide concomitantly used with ESAs in MDS patients, but the association was not statistically significant when lenalidomide was used in the absence of ESAs.

Active computerized pharmacovigilance using natural language processing, statistics, and electronic health records: a feasibility study

OBJECTIVE It is vital to detect the full safety profile of a drug throughout its market life. Current pharmacovigilance systems still have substantial limitations, however. The objective of our work is to demonstrate the feasibility of using natural language processing (NLP), the comprehensive Electronic Health Record (EHR), and association statistics for pharmacovigilance purposes. DESIGN Narrative discharge summaries were collected from the Clinical Information System at New York Presbyterian Hospital (NYPH). MedLEE, an NLP system, was applied to the collection to identify medication events and entities which could be potential adverse drug events (ADEs). Co-occurrence statistics with adjusted volume tests were used to detect associations between the two types of entities, to calculate the strengths of the associations, and to determine their cutoff thresholds. Seven drugs/drug classes (ibuprofen, morphine, warfarin, bupropion, paroxetine, rosiglitazone, ACE inhibitors) with known ADEs were selected to evaluate the system. RESULTS One hundred thirty-two potential ADEs were found to be associated with the 7 drugs. Overall recall and precision were 0.75 and 0.31 for known ADEs respectively. Importantly, qualitative evaluation using historic roll back design suggested that novel ADEs could be detected using our system. CONCLUSIONS This study provides a framework for the development of active, high-throughput and prospective systems which could potentially unveil drug safety profiles throughout their entire market life. Our results demonstrate that the framework is feasible although there are some challenging issues. To the best of our knowledge, this is the first study using comprehensive unstructured data from the EHR for pharmacovigilance.

Risk of Hepatotoxicity Associated with the Use of Telithromycin: A Signal Detection Using Data Mining Algorithms

Background:

With the exception of case reports, limited data are available regarding the risk of hepatotoxicity associated with the use of telithromycin.

Objective:

To detect the safety signal regarding the reporting of hepatotoxicity associated with the use of telithromycin using 4 commonly employed data mining algorithms (DMAs).

Methods:

Based on the Adverse Events Reporting System (AERS) database of the Food and Drug Administration, 4 DMAs, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the information component (IC), and the Gamma Poisson Shrinker (GPS), were applied to examine the association between the reporting of hepatotoxicity and the use of telithromycin. The study period was from the first quarter of 2004 to the second quarter of 2006. The reporting of hepatotoxicity was identified using the preferred terms indexed in the Medical Dictionary for Regulatory Activities. The drug name was used to identify reports regarding the use of telithromycin.

Results:

A total of 226 reports describing hepatotoxicity associated with the use of telithromycin were recorded in the AERS. A safety problem of telithromycin associated with increased reporting of hepatotoxicity was clearly detected by 4 algorithms as early as 2005, signaling the problem in the first quarter by the ROR and the IC, in the second quarter by the PRR, and in the fourth quarter by the GPS.

Conclusions:

A safety signal was indicated by the 4 DMAs suggesting an association between the reporting of hepatotoxicity and the use of telithromycin. Given the wide use of telithromycin and serious consequences of hepatotoxicity, clinicians should be cautious when selecting telithromycin for treatment of an infection. In addition, further observational studies are required to evaluate the utility of signal detection systems for early recognition of serious, life-threatening, low-frequency drug-induced adverse events.

Leukotriene receptor antagonists and Churg-Strauss syndrome: cause, trigger or merely an association?

Concern has been raised in the medical literature that the use of leukotriene receptor antagonists for the treatment of asthma may be associated with an increased incidence of Churg-Strauss syndrome, a rare small-vessel vasculitic syndrome. This review provides a critical appraisal of the literature to address this question. The incidence of Churg-Strauss syndrome in the general population is one to four cases per million. In patients with asthma it is 20-60 cases per million patient-years, which is similar to that seen in a population receiving leukotriene receptor antagonists. There is no evidence for a direct causative role of leukotriene receptor antagonists in the development of Churg-Strauss syndrome. There may be multiple other non-causative reasons for an association, including the fact that these agents may be initiated in patients who are already in the process of developing Churg-Strauss syndrome, or that the use of leukotriene receptor antagonists leads to a reduction in corticosteroid use, which in turn allows the Churg-Strauss syndrome to be 'unmasked'.

Signal detection methodologies to support effective safety management

The increased focus on the safety of medical products, as well as the growing volume of available safety information, has created a need for objective quantitative approaches to supplement the medical review of individual case safety reports. Statistical algorithms can be used to identify trends and relationships in both clinical and postmarketing safety databases in support of safety signal detection. Powerful data visualization tools facilitate the medical review of the complex information generated by these methods. In addition, all these approaches need to be integrated into the daily practice of clinical safety and postmarketing pharmacovigilance.

Asthma drug use and the development of Churg-Strauss syndrome (CSS)

PURPOSE

Case reports suggest that leukotriene modifier use may be associated with the onset of Churg-Strauss syndrome (CSS). Using pooled data from two nested case-control studies, we examined the association between asthma drug use and the development of CSS.

METHODS

The study was performed in three US managed care organizations and a US national health plan with chart access and complete electronic pharmacy data, with a covered population of 13.9 million. There were 47 cases of possible or definite CSS and 4700 asthma drug user controls identified between January 1, 1995 and December 31, 2002. We examined exposure to asthma drugs in cases and controls, including leukotriene modifiers (6 cases and 202 controls), in the two to 6 months prior to the onset of adjudicated CSS.

RESULTS

While the crude association between use of leukotriene modifiers and CSS was strong (odds ratio (OR) 4.00, 95% confidence interval (CI): 1.49-10.60), in a multivariable analysis controlling for use of oral corticosteroids, inhaled corticosteroids, and number of categories of asthma drugs dispensed, there was no significant association (OR 1.32, 95% CI: 0.44-3.96). Use of inhaled and oral corticosteroids, evaluated as markers of asthma severity, were associated with CSS (OR 3.07, 95% CI: 1.34-7.03 and OR 5.36, 95% CI: 2.51-11.45, respectively).

CONCLUSIONS

No association was found between CSS and leukotriene modifiers after controlling for asthma drug use However, it is not possible to rule out modest associations with asthma treatments given CSS is so rare and so highly correlated with asthma severity, suggesting further investigation is warranted.

[Antileukotrienes and Churg-Strauss syndrome]

Churg-Strauss syndrome is a systemic necrotizing vasculitis involving small and medium-sized vessels. Classic features include asthma and hypereosinophilia. Antineutrophil cytoplasm antibodies (ANCA) are detected in about 40% of patients. Churg-Strauss syndrome has been reported in patients receiving leukotriene modifiers for asthma, in particular, leukotriene receptor antagonists (LTRA) (montelukast, zafirlukast or pranlukast). Clinical manifestations cases do not differ in these cases from those in Churg-Strauss syndrome without antileukotriene exposure. It is increasingly less likely that LTRA is the direct cause of this syndrome in those patients, although this hypothesis has not been completely ruled out. In many patients, LTRA treatment is prescribed because of worsening asthma, which is an early sign of Churg-Strauss syndrome. LTRA for asthma patients should be prescribed with great care, especially in cases of atypical or rapidly aggravated asthma. The onset of Churg-Strauss syndrome in patients treated with LTRA usually requires that they stop this treatment. Prescription of LTRA In patients with Churg-Strauss syndrome should be discussed with specialists.

Churg-Strauss syndrome associated with leukotriene receptor antagonists (LTRA)

Churg-Strauss syndrome (CSS) is a rare vasculitic disorder that generally occurs in patients with bronchial asthma. CSS is being increasingly recognized in asthmatic patients treated with leukotriene receptor antagonists. However, the nature of this relationship remains to be elucidated. The present report describes three asthmatic patients who developed clinical manifestations highly suggestive of CSS, although one patient lacked the presence of eosinophilia. The patient, however, exhibited biopsy-proven cutaneous necrotizing vasculitis, which improved after withdrawal of montelukast. The second patient presented with systemic constitutional signs including fever, malaise, arthralgias, clinical jaundice, peripheral blood eosinophilia, and biopsy-proven eosinophilic hepatitis. The third patient also had circulating eosinophilia, scleritis, and arthritis. All patients improved after discontinuation of the leukotriene receptor antagonist (montelukast).

Churg-Strauss syndrome associated with hypersensitivity to acetaminophen

Acetaminophen is a widely used antipyretic drug. We describe a 64-year-old Japanese woman who developed typical Churg-Strauss syndrome after frequent use of acetaminophen. Following the ingestion of acetaminophen, she exhibited various allergic reactions such as asthmatic attacks, pyrexia and petechiae on legs. In the lymphocyte transformation test, a positive reaction to acetaminophen was detected. A muscle biopsy revealed massive extravascular eosinophil infiltration and a necrotizing vasculitis. Hypersensitivity to acetaminophen may be implicated in the development of Churg-Strauss syndrome in this case.