Real-world large sample assessment of drug-related dry eye risk: Based on the FDA adverse event reporting system database.

PURPOSE AND DESIGN: This study aimed to evaluate the risk of drug-related dry eye using real-world data, underscoring the significance of tracing pharmacological etiology for distinct clinical types of dry eye. METHODS: Analyzing adverse event reports in the Food and Drug Administration Adverse Event Reporting System (FAERS) from January 2004 to September 2023, we employed disproportionality analysis and the Bayesian confidence propagation neural network algorithm. The analysis involved categorizing drugs causing dry eye, assessing risk levels, and conducting segmental assessments based on the time of onset of drug-related dry eye adverse reactions. RESULTS: In the FAERS database, adverse reactions related to dry eye were linked to 1160 drugs. Disproportionality analysis identified 33 drugs with significant risk, notably in ophthalmic (brimonidine, bimatoprost), oncology (tisotumab vedotin, erdafitinib), and other medications (isotretinoin, oxymetazoline). The top three drugs with the highest risk of drug-related dry eye are isotretinoin (Bayesian confidence propagation neural network (BCPNN) = 6.88), tisotumab vedotin (BCPNN = 6.88), and brimonidine (BCPNN = 6.77). Among different categories of drugs, respiratory medications have the shortest mean onset time for drug-related dry eye, averaging 50.99 days. The prevalence skewed towards females (69.9 %), particularly in menopausal and elderly individuals (45-70 years old, mean age 54.7 ± 18.2). Reports of drug-related dry eye adverse reactions showed an annual increase. CONCLUSION: Informed clinical decision-making is crucial for preventing drug-related dry eye. Assessing the risk of dry eyes associated with both local and systemic medications helps optimize treatment and provide necessary cautionary information.

A real-world pharmacovigilance study of FDA adverse event reporting system (FAERS) events for sunitinib.

Background: Sunitinib is approved for the treatment of metastatic renal cell carcinoma (mRCC), imatinib-resistant gastrointestinal stromal tumors (GIST), and advanced pancreatic neuroendocrine tumors (PNET). This study aims to investigate the safety profiles of sunitinib through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS). Methods: The individual case safety reports (ICSRs) on sunitinib from 2006 Q1 to 2024 Q1 were collected from the ASCII data packages in the Food and Drug Administration Adverse Event Reporting System (FAERS). After standardizing the data, a variety of disproportionality analyses, including the reporting odds ratio (ROR), the proportional reporting ratio (PRR), the bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS) were employed to identify the potential safety signals of sunitinib-associated AEs. Results: A total of 35,923 ICSRs of sunitinib as the "primary suspected" drug were identified within the reporting period. The search detected 276 disproportionate preferred terms (PTs). The most common AEs, including diarrhea, asthenia, decreased appetite, hypertension, and dysgeusia, were consistent with the drug label and clinical trials. Unexpected significant AEs, such as uveal melanocytic proliferation, salivary gland fistula, yellow skin, eyelash discoloration, scrotal inflammation, were detected. The median onset time of sunitinib-related AEs was 57 days (interquartile range [IQR]16-170 days), with most of the ICSRs developing within the first month (n = 4,582, 39.73%) after sunitinib therapy as initiated. Conclusion: The results of our study were consistent with routine clinical observations, and some unexpected AEs signals were also identified for sunitinib, providing valuable evidence for the safe use of sunitinib in the real-world and contributing to the clinical monitoring and risk identification of sunitinib.

Adverse events associated with eteplirsen: A disproportionality analysis using the 2016-2023 FAERS data.

Background: Eteplirsen (Exondys 51) is an orphan drug approved for the treatment of Duchenne muscular dystrophy (DMD), having received accelerated approval from the U.S. Food and Drug Administration (FDA) in 2016. The primary aim of this study is to closely monitor adverse events (AEs) associated with eteplirsen and to identify emerging signals to better characterize their safety profile. Methods: AEs due to eteplirsen usage reported from the third quarter (Q3) of 2016 to the fourth quarter (Q4) of 2023 were collected from the FDA Adverse Event Reporting System (FAERS). The role_code of AEs mainly includes primary suspect (PS), secondary suspect (SS), concomitant (C), and interaction (I). This study targeted reports with a role_cod of 'PS.' According to the FDA deduplication rule, the latest FDA_DT is selected when the CASEID is the same, and the higher PRIMARYID is selected when the CASEID and FDA_DT are the same. Disproportionality analyses, encompassing four algorithms for reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian configuration promotion neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS), were utilized to quantify the signals of AEs associated with eteplirsen. Results: From the FAERS database, a total of 13,205,369 reports were amassed throughout the study duration. Following the eradication of duplicates, the number of reports with eteplirsen designated as the PS amounted to 1480 encompassed 25 organ systems. Among these, "general disorders and administration site conditions," "injury, poisoning, and procedural complications," "respiratory, thoracic, and mediastinal disorders," "infections and infestations," "vascular disorders," and "product issues" met at least one of the four computational criteria. Additionally, 55 Preferred Terms (PTs) aligned with the prescribed algorithms. The median time to AEs in these patients was 903 days with an interquartile range (IQR) of 269-1575 days. Moreover, 70.04 % of AEs manifested one year or more after the initiation of treatment. Conclusion: As an orphan drug granted accelerated approval, our study has confirmed well-known adverse drug reactions and identified potential safety issues associated with eteplirsen treatment. This has contributed to a deeper understanding of the complex interrelations between adverse reactions and the use of eteplirsen. The findings underscore the critical importance of ongoing monitoring and sustained observation to promptly detect and effectively manage AEs, thereby enhancing the overall safety and well-being of patients treated with eteplirsen for DMD.

Cardiac adverse events associated with lacosamide: a disproportionality analysis of the FAERS database.

Lacosamide was the first approved third-generation antiepileptic drug. However, real-world data regarding its adverse cardiac reactions in large samples still need to be completed. We evaluated the cardiac safety profile of lacosamide using the Food and Drug Administration Adverse Event Reporting System (FAERS). We performed disproportionality analysis computing reporting odds ratio (ROR) as a quantitative metric to assess the signal of lacosamide-related cardiac adverse events (AEs) from 2013 Q1 to 2022 Q4. The signal was considered significant when the lower limit of the 95% confidence interval (CI) of the ROR exceeded 1, and ≥ 5 AEs were reported. Serious and nonserious cases were compared by statistical analysis, and signals were further prioritized using a rating scale. A total of 812 cardiac AEs associated with lacosamide were identified, and 92 signals were detected, of which 17 AEs were significantly associated signals. The median time-to-onset (TTO) for moderate priority signals was 10 days, whereas for weak priority signals, it was 54 days. Notably, all cardiac AEs exhibited an early failing pattern, indicating the risk gradually decreasing. Based on the comprehensive analysis of the FAERS database and prioritization of cardiac AE signals, our research enhances the awareness among healthcare professionals regarding cardiac AEs associated with lacosamide.

A pharmacovigilance study of chronic kidney disease in diabetes mellitus patients with statin treatment by using the US Food and Drug Administration adverse event reporting system.

Background: Statins were regarded as a main medication for managing hypercholesterolemia. Administration of statin therapy could reduce the incidence of cardiovascular disease in individuals diagnosed with type 2 diabetes mellitus (DM), which was recognized by multipal clinical guidelines. But previous studies had conflicting results on whether the long-term use of statins could benefit the renal function in diabetic patients. Aim: To evaluate the association between statin treatment and Chronic Kidney Disease in DM patients. Methods: This is a retrospective disproportionality analysis and cohort study based on real-world data. All DM cases reported in US Food and Drug Administration adverse event reporting system (FAERS) between the first quarter of 2004 and the fourth quarter of 2022 were included. Disproportionality analyses were conducted by estimating the reporting odds ratio (ROR) and the information component (IC). We further compared the CKD odds ratio (OR) between the statins group and the other primary suspected drug group among the included diabetes mellitus cases. Results: We finally included 593647 DM cases from FAERS, 5113 (5.31%) CKD cases in the statins group and 8810 (1.77%) CKD cases in the control group. Data analysis showed that the statins group showed a significant CKD signal (ROR: 3.11, 95% CI: 3.00-3.22; IC: 1.18, 95% CI: 1.07-1.29). In case group with two or more statins treatment history, the CKD signal was even stronger (ROR: 19.56, 95% CI: 18.10-21.13; IC: 3.70, 95% CI:3.44-3.93) compared with cases with one statin treatment history. Conclusion: The impact of statin therapy on the progression of renal disease in individuals diagnosed with type 2 diabetes mellitus (DM) remains inconclusive. After data mining on the current FAERS dataset, we discovered significant signals between statin treatment and CKD in diabetic patients. Furthermore, the incidence rate of CKD was higher among DM patients who used statins compared to those who did not.

Post-marketing safety concerns of sotorasib: A disproportionality analysis based on FDA adverse event reporting system.

Background: Sotorasib has been approved for the treatment of adult patients with KRAS G12C-mutated locally advanced or metastatic non-small cell lung cancer (NSCLC). Due to the limitations of clinical trials, potential adverse events (AEs) and long-term safety issues cannot be detected. The presented study aimed to evaluate sotorasib-associated AEs using the FDA Adverse Event Reporting System (FAERS) database. Methods: Post-marketing AE reports of sotorasib in the database were collected for analysis. Disproportionality analyses, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), information component (IC) and empirical bayes geometric mean (EBGM) algorithms, were performed to mine the signals of sotorasib-associated AEs. The median duration, quartiles and the Weibull shape parameter (WSP) test were used to assess the onset time data. Results: The database contained 1538 cases of sotorasib as primary suspect (PS), with 27 signals detected, scattering in 5 SOCs. The SOC of hepatobiliary disorders (182, ROR 4.48, PRR 4.07, IC 2.02, EBGM 4.07) met the four methodological thresholds. The median onset time of sotorasib-associated AEs was 42 days (interquartile range [IQR] 14-86.75 days). Different SOCs had different types of risk over time. Conclusion: After obtaining marketing authorization, the study identified all potentially relevant adverse event (AE) signals expected to have a reporting frequency higher than anticipated and characterized them during sotorasib treatment.

CDK4/6 inhibitors in drug-induced liver injury: a pharmacovigilance study of the FAERS database and analysis of the drug-gene interaction network.

Objective: The aim of this study was to investigate the potential risk of drug-induced liver injury (DILI) caused by the CDK4/6 inhibitors (CDK4/6is abemaciclib, ribociclib, and palbociclib by comprehensively analyzing the FDA Adverse Event Reporting System (FAERS) database. Moreover, potential toxicological mechanisms of CDK4/6is-related liver injury were explored via drug-gene network analysis. Methods: In this retrospective observational study, we collected reports of DILI associated with CDK4/6i use from the FAERS dated January 2014 to March 2023. We conducted disproportionality analyses using the reporting odds ratio (ROR) with a 95% confidence interval (CI). Pathway enrichment analysis and drug-gene network analyses were subsequently performed to determine the potential mechanisms underlying CDK4/6i-induced liver injury. Results: We found positive signals for DILI with ribociclib (ROR = 2.60) and abemaciclib (ROR = 2.37). DILIs associated with liver-related investigations, signs, and symptoms were confirmed in all three reports of CDK4/6is. Moreover, ascites was identified as an unlisted hepatic adverse effect of palbociclib. We isolated 189 interactive target genes linking CDK4/6 inhibitors to hepatic injury. Several key genes, such as STAT3, HSP90AA1, and EP300, were revealed via protein-protein analysis, emphasizing their central roles within the network. KEGG pathway enrichment of these genes highlighted multiple pathways. Conclusion: Our study revealed variations in hepatobiliary toxicity among the different CDK4/6 inhibitors, with ribociclib showing the highest risk of liver injury, followed by abemaciclib, while palbociclib appeared relatively safe. Our findings emphasize the need for cautious use of CDK4/6 inhibitors, and regular liver function monitoring is recommended for long-term CDK4/6 inhibitor use.

Psychiatric adverse events associated with GLP-1 receptor agonists: a real-world pharmacovigilance study based on the FDA Adverse Event Reporting System database.

Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are widely used due to their profound efficacy in glycemic control and weight management. Within real-world contexts, the manifestation of certain psychiatric adverse events (AEs) has been observed, which is potentially linked to the administration of GLP-1 RAs. The objective of this study was to undertake a comprehensive investigation and characterization of the psychiatric AEs associated with GLP-1 RAs. Methods: We retrieved reports of AEs associated with treatment with GLP-1 RAs during the period from the first quarter (Q1) of 2004 to Q1 2023 from the FDA Adverse Event Reporting System (FAERS) database. Descriptive analysis was performed to examine the clinical characteristics and time to onset of the psychiatric AEs caused by GLP-1 RAs. Moreover, disproportionality analyses were performed using the reporting odds ratio (ROR) to identify GLP-1 RA-related psychiatric AEs. Results: A total of 8,240 reports of psychiatric AEs were analyzed out of 181,238 AE reports with treatment with GLP-1 RAs. Among these cases, a higher percentage was represented by women compared to men (65.89% vs. 30.96%). The median age of these patients was 56 years, with an interquartile range (IQR) of 48-67 years, based on data available in 286 case reports. This study showed that the median time to onset of the overall GLP-1 RA-related AEs was 31 days (IQR = 7-145.4 days), which varied among GLP-1 RA regimens. Specifically, exenatide had a significantly longer onset time at 45 days (IQR = 11-213 days), with statistically significant differences from the onset times of the other five GLP-1 RAs (p< 0.0001). Moreover, eight categories of psychiatric AEs, namely, nervousness (ROR = 1.97, 95% CI = 1.85-2.11), stress (ROR = 1.28, 95% CI = 1.19-1.38), eating disorder (ROR = 1.57, 95% CI = 1.40-1.77), fear of injection (ROR = 1.96, 95% CI = 1.60-2.40), sleep disorder due to general medical condition-insomnia type (ROR = 2.01, 95% CI = 1.60-2.52), binge eating (ROR = 2.70, 95% CI = 1.75-4.16), fear of eating (ROR 3.35, 95% CI = 1.65-6.78), and self-induced vomiting (ROR = 3.77, 95% CI = 1.77-8.03), were defined as GLP-1 RA-related psychiatric AEs through disproportionality analysis. Conclusion: Our findings demonstrate a significant association between GLP-1 RAs and the development of specific psychiatric AEs. Despite the observational nature of this pharmacovigilance study and the inherent limitations of the FAERS database, our preliminary findings in this work could provide a better basis for understanding the potential psychiatric AEs that may occur with GLP-1 RA treatment, assisting clinicians to focus on these AEs and provide early intervention for optimal risk management.

Adverse event profile of CGRP monoclonal antibodies: findings from the FDA adverse event reporting database.

BACKGROUND: Four CGRP Monoclonal Antibodies (mAbs) have been approved for migraine prophylaxis by the Food and Drug Administration (FDA) since 2018. However, there are concerns about the safety of these four drugs for real-world use. OBJECTIVE: To compare the adverse event profiles of four CGRP-mAbs with FAERS data. METHODS: The study was based on records from the FAERS database. Only reports containing one of the active ingredients with CGRP-mAbs were included in this study. Disproportionality analyses including but not limited to reporting odds ratio (ROR) and information components (IC) were conducted to identify drug-AE associations. RESULTS: In total, 58110 reports were identified for CGRP-mAbs. 80 overlapping signals were disproportionately reported. They affected a range of organs and systems, including the gastrointestinal and cardiovascular systems, skin, and hair. Additionally, the rare cardiovascular adverse events were significantly different among the four CGRP-mAbs. CONCLUSION: We identified numerous shared underlying signals (overlapping signals) for CGRP-mAbs as suspected drugs in multiple systems and organs. The unlabeled common signals may indicate potential safety issues. In addition, the underlying safety signals varied among the four CGRP-mAbs, particularly in the cardiovascular system, and further studies are needed to confirm these associations and the potential clinical implications.

A real-world disproportionality analysis of apalutamide: data mining of the FDA adverse event reporting system.

Background: Apalutamide is a new drug class, which is approved to treat prostate cancer (PCa). The aim of our study was to assess the safety profiles of apalutamide in real-world through data mining of the United States Food and Drug Administration Adverse Event Reporting System (FAERS). Method: We included adverse event (AE) reports regarding apalutamide submitted to the FAERS from 2018 quarter 1 (2018Q1) to 2022 quarter 1 (2022Q1). Disproportionality analyses, including reporting odds ratio (ROR), were performed to identify the signals of AEs in patients receiving apalutamide. A signal was detected if the lower limit of the 95% confidence interval (CI) of ROR >1 and at least 3 AEs were reported. Results: The FAERS database documented 4,156 reports regarding apalutamide from 1 January 2018, to 31 March 2022. A total of 100 significant disproportionality preferred terms (PTs) were retained. Frequently observed AEs in patients receiving apalutamide included rash, fatigue, diarrhea, hot flush, fall, weight decreased, hypertension. The most significant system organ class (SOC) was "skin and subcutaneous tissue disorders", which mainly consisted of dermatological adverse events (dAEs). The additional AEs observed with the significantly signal contain lichenoid keratosis, increased eosinophil count, bacterial pneumonia, pulmonary tuberculosis, hydronephrosis. Conclusion: Our findings provide valuable evidence for apalutamide safety profile in the real-world, which could help clinicians and pharmacists to enhance their vigilance and improve the safety of apalutamide in clinical practice.

Drug-induced tooth discoloration: An analysis of the US food and drug administration adverse event reporting system.

Background: Certain drugs can cause intrinsic or extrinsic tooth discoloration, which is not only a clinical issue but also an esthetic problem. However, limited investigations have focused on drug-induced tooth discoloration. The present work aimed to determine the drugs causing tooth discoloration and to estimate their risks of causing tooth discoloration. Methods: An observational, retrospective, and pharmacovigilance analysis was conducted, in which we extracted adverse event (AE) reports involving tooth discoloration by using the data of the US Food and Drug Administration's Adverse Event Reporting System (FAERS) from the first quarter (Q1) of 2004 to the third quarter (Q3) of 2021. Disproportionality analyses were performed to examine risk signals for tooth discoloration and determine the drugs inducing tooth discoloration. Results: Based on predefined inclusion criteria, 1188 AE reports involving 302 suspected drugs were identified. After data mining, 25 drugs generated positive risk signals for tooth discoloration, of which 10 were anti-infectives for systemic use. The top reported drug was tetracycline (n = 106), followed by salmeterol and fluticasone (n = 68), amoxicillin (n = 60), chlorhexidine (n = 54), and nicotine (n = 52). Cetylpyridinium (PRR = 472.2, ROR = 502.5), tetracycline (PRR = 220.4, ROR = 277), stannous fluoride (PRR = 254.3, ROR = 262.8), hydrogen peroxide (PRR = 240.0, ROR = 247.6), and chlorhexidine (PRR = 107.0, ROR = 108.4) showed stronger associations with tooth discoloration than the remaining drugs. Of 625 AE reports involving 25 drugs with positive risk signals, tooth discoloration was mostly reported in patients aged 45-64 (n = 110) and ≤18 (n = 95), and 29.4% (192/652) of the reports recorded serious outcomes. Conclusion: This study revealed that certain drugs are significantly associated with tooth discoloration. Caution should be exercised when using these drugs, especially during pregnancy and early childhood.

Considerations on the use of different comparators in pharmacovigilance: A methodological review.

Pharmacovigilance studies based on spontaneous reporting systems use disproportionality analysis methods to identify drug-event combinations with higher-than-expected reporting. Enhanced reporting is deemed as a proxy for a detected signal and is used to generate drug safety hypotheses, which can then be tested in pharmacoepidemiologic studies or randomized controlled trials. Higher-than-expected reporting means that the reporting rate of a drug-event combination of interest is disproportionately higher than the rate in a specific comparator or reference set. Currently, it is unclear which comparator is the most appropriate for use in pharmacovigilance. Moreover, it is also unclear how the selection of a comparator may affect the directionality of the various reporting and other biases. This paper reviews commonly used comparators chosen for signal detection studies (active comparator, class-exclusion comparator, and full data reference set). We give an overview of the advantages and disadvantages of each method based on examples from the literature. We also touch upon the challenges related to the derivation of general recommendations for the selection of comparators when mining spontaneous reports for pharmacovigilance.

Concomitant use of statins and sodium-glucose co-transporter 2 inhibitors and the risk of myotoxicity reporting: A disproportionality analysis.

AIMS: Recent case reports have suggested that sodium-glucose co-transporter 2 (SGLT2) inhibitors may interact with statins to increase their risk of myotoxicity. We assessed the risk of myotoxicity reporting associated with concomitant use of SGLT2 inhibitors and statins. METHODS: We queried the US Food and Drug Administration Adverse Event Reporting System (FAERS) from 2013 to 2021 for reports including SGLT2 inhibitors, statins or both. We estimated several measures of disproportionate reporting of myopathy and rhabdomyolysis associated with concomitant use of SGLT2 inhibitors and statins: reporting odds ratio (ROR) with 95% confidence interval (CI), Ω shrinkage measure (safety signal if >0) and an extension of the proportional reporting ratio (PRR) (two-criteria set, safety signal if both criteria are met), using the full FAERS dataset as the reference set. In sensitivity analyses, we focussed on specific SGLT2 inhibitor-statin pairs with higher interaction potential (canagliflozin-rosuvastatin, empagliflozin-rosuvastatin) and accounted for stimulated reporting. RESULTS: There were 456 myopathy and 77 rhabdomyolysis reports involving both an SGLT2 inhibitor and a statin. Concomitant use of SGLT2 inhibitors and statins was not associated with an increased risk of myopathy (ROR 0.79, 95% CI 0.70 to 0.89) or rhabdomyolysis (ROR 0.58, 95% CI 0.41 to 0.83) reporting. For both outcomes, the Ω shrinkage measure was negative and only one criterion of the PRR extension was met. SGLT2 inhibitor-statin pairs with higher interaction potential yielded potential signals for rhabdomyolysis; these signals disappeared after accounting for stimulated reporting. CONCLUSION: There was no increased risk of myotoxicity reporting associated with concomitant use of SGLT2 inhibitors and statins or for specific drug pairs.

Adverse event profiles of PCSK9 inhibitors alirocumab and evolocumab: Data mining of the FDA adverse event reporting system.

BACKGROUND: Proprotein convertase subtilisin/kexin type (PCSK9) inhibitor is a new drug class approved for treating dyslipidemias. Herein, we aimed to investigate the safety profiles of PCSK9 inhibitors (alirocumab and evolocumab) using the Food and Drug Administration Adverse Event Reporting System (FAERS). METHODS: We included adverse event (AE) reports regarding alirocumab and evolocumab submitted to the FAERs between 2015Q3 to 2021Q1. Disproportionality analyses, including reporting odds ratio (ROR), were performed to detect risk signals from the FAERs data to identify potential drug-AE associations. A signal was considered when the lower limit of the 95% confidence interval of ROR exceeded 1 and ≥3 AEs were reported. The definition relied on system organ class and preferred terms established by the Medical Dictionary for Regulatory Activities. RESULTS: The FAERS database documented 31 475 reports regarding PCSK9 inhibitors (alirocumab and evolocumab) from July 1, 2015, to March 31, 2021. Although some differences were detected, alirocumab and evolocumab shared considerably similar safety profiles. The most significant RORs and most common reports were injection-site reactions (eg, injection-site pain, bruising, haemorrhage, erythema), muscle-related AEs (eg, myalgia, back pain, arthralgia, muscle spasms), influenza-like illness, pain and headache. CONCLUSION: Data mining of the FAERs is useful for examining PCSK9 inhibitor-induced AEs. Herein, our findings were largely consistent with clinical experience and could help clinicians improve the safety of PCSK9 inhibitors in clinical practice.

A meta-epidemiological study found lack of transparency and poor reporting of disproportionality analyses for signal detection in pharmacovigilance databases.

OBJECTIVES: To review and appraise methods and reporting characteristics of pharmacovigilance disproportionality analyses. STUDY DESIGN AND SETTING: We randomly selected 100 disproportionality analyses indexed in Medline found during a systematic literature search. We then extracted and synthetized methodological and reporting characteristics using seven key items: (1) title transparency; (2) protocol pre-registration; (3) date of data extraction and analysis; (4) outcome, population, exposure and comparator definitions; (5) adjustment and stratification of results; (6) method and threshold for signal detection; (7) secondary and sensitivity analyses. RESULTS: We found that methods used to generate disproportionality signals were extremely heterogeneous; there were nearly as many unique analyses as studies. The authors used various populations, methods, signal detection thresholds, adjustment or stratification variables, generally without justification for their choice or pre-specification in protocols. Moreover, 78% of studies failed to report methods for case, adverse drug reactions or comparator selection and 32 studies did not define the threshold for signal generation. CONCLUSION: Our survey raises major concerns regarding all aspects of disproportionality analyses that could lead to misleading results and generate unjustified alarms. We advocate for a strong and transparent rationale for variable selection, choice of population and comparators pre-specified in a protocol and assessed by sensitivity analyses.

High prevalence of spin was found in pharmacovigilance studies using disproportionality analyses to detect safety signals: a meta-epidemiological study.

OBJECTIVE: To systematically review and appraise misinterpretation of pharmacovigilance disproportionality analysis results in published studies. STUDY DESIGN AND SETTING: We randomly selected 100 studies that performed disproportionality analyses and indexed in Medline identified during a systematic literature search. Titles, abstracts and main texts (results, discussion and conclusion) were evaluated for spin independently by two reviewers. Spin in pharmacovigilance studies was classified according to three main categories: inappropriate interpretation, inappropriate extrapolations and misleading reporting. RESULTS: Of the 100 studies evaluated, we found that 63%, 56% and 51% had at least one type of spin in their abstract, main text or conclusion respectively, and 40% used causal language to interpret their results in the abstract or conclusion. Spin in titles and results were exclusively represented by inappropriate interpretations of findings (12% and 21% respectively), with terms such as "risk of" or "risks associated with" or results erroneously presented as regular Odds Ratios. Spin in discussion sections mostly concerned inappropriate interpretations (38%)and misleading reporting (12%). Misleading reporting, notably failing to acknowledge the limitations of disproportionality analyses, was the most frequent type of spin in abstracts (55%) and conclusion sections (37%). CONCLUSION: We found that spin is frequent in publications of pharmacovigilance disproportionality analyses, notably in abstracts. This consisted notably in an over-interpretation of the results suggesting a proven causative link between a drug use and the risk of an event.

Leveraging the Variability of Pharmacovigilance Disproportionality Analyses to Improve Signal Detection Performances.

Background: A plethora of methods and models of disproportionality analyses for safety surveillance have been developed to date without consensus nor a gold standard, leading to methodological heterogeneity and substantial variability in results. We hypothesized that this variability is inversely correlated to the robustness of a signal of disproportionate reporting (SDR) and could be used to improve signal detection performances. Methods: We used a validated reference set containing 399 true and false drug-event pairs and performed, with a frequentist and a Bayesian disproportionality method, seven types of analyses (model) for which the results were very unlikely to be related to actual differences in absolute risks of ADR. We calculated sensitivity, specificity and plotted ROC curves for each model. We then evaluated the predictive capacities of all models and assessed the impact of combining such models with the number of positive SDR for a given drug-event pair through binomial regression models. Results: We found considerable variability in disproportionality analysis results, both positive and negative SDR could be generated for 60% of all drug-event pairs depending on the model used whatever their truthfulness. Furthermore, using the number of positive SDR for a given drug-event pair largely improved the signal detection performances of all models. Conclusion: We therefore advocate for the pre-registration of protocols and the presentation of a set of secondary and sensitivity analyses instead of a unique result to avoid selective outcome reporting and because variability in the results may reflect the likelihood of a signal being a true adverse drug reaction.