Modelling the time to onset of adverse reactions with parametric survival distributions: a potential approach to signal detection and evaluation

Safety evaluation of ILaris: a real-world analysis of adverse events based on the FAERS database

BACKGROUND

There is a lack of real-world studies on the safety of Ilaris in large populations. The purpose of this study was to investigate adverse events (AEs) associated with Ilaris using data from the FDA Adverse Event Reporting System (FAERS) database to guide clinical use.

METHODS

We evaluated retrospectively extracted reports of AEs from the FAERS database between the first quarter of 2009 and the second quarter of 2024. The presence of a significant association between Ilaris and AEs was assessed by using disproportionality analyses including ROR,PRR,BCPNN,MGPS.

RESULTS

After evaluating 14,691,170 data, 7968 ILaris-associated AEs were obtained after removing duplicates and unspecified sex items. A number of AEs were finalized through the study, including Common Pyrexia, Condition Aggravated, Influenza, and unexpected signals not listed in the drug insert, such as Pulmonary Thrombosis, Hepatomegaly, Blood Lactate Dehydrogenase Increased, Splenomegaly, Appendicitis. Ilaris induced AEs involving 27 system organ classes (SOCs). There were gender differences in AEs signaling associated with Ilaris.

CONCLUSIONS

It is critical for healthcare professionals to closely monitor patients for symptoms (such as pulmonary thrombosis, Hepatomegaly, Blood Lactate Dehydrogenase Increased, Splenomegaly, Appendicitis) and other adverse events during treatment.

A real-world pharmacovigilance analysis of adverse events associated with irbesartan using the FAERS and JADER databases

Objective

Hypertension is a leading global risk factor for disability and death. Irbesartan, a potent angiotensin II receptor blocker, requires continuous safety monitoring. We conducted a disproportionality analysis of irbesartan-related adverse drug events (ADEs) using the FDA's FAERS and Japan's JADER databases.

Methods

We extracted irbesartan-related ADE reports from FAERS (Q1 2004 to Q1 2024) and JADER (Q2 2008 to Q4 2023). We used Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM) for signal detection. Sensitivity analyses were conducted to exclude comorbid medications, and subgroup analyses by age and gender were performed to explore ADE occurrence in specific populations. Th time to onset (TTO) of ADEs was assessed using Weibull distribution test and Kaplan-Meier curves.

Results

A total of 5,816 (FAERS) and 366 (JADER) reports were analyzed, with irbesartan-related preferred terms (PTs) involving 27 System Organ Classes (SOCs) in FAERS and 22 in JADER. Three SOCs met detection thresholds in both databases: "metabolism and nutrition disorders," "cardiac disorders," and "renal and urinary disorders." We identified 219 positive signals in FAERS and 20 in JADER, including known signals like hyperkalemia, hypotension, and acute kidney injury. Notably, newly identified signals such as acute pancreatitis (n = 50, ROR: 7.76 [5.88-10.25]) and rhabdomyolysis (n = 50, ROR: 7.76 [5.88-10.25]) in FAERS and respiratory failure (n = 7, ROR: 6.76 [3.20-14.26]) in JADER could have significant clinical implications, as they may lead to severe outcomes if not recognized and managed promptly. Subgroup analyses revealed both similarities and differences in signal detection across gender and age groups. Sensitivity analyses, excluding concomitant medications, confirmed the persistence of key positive signals, including hyperkalemia, angioedema, acute pancreatitis, and agranulocytosis. ADEs mainly occurred within 1 month (34.14%) and after 1 year (32.32%) after dosing, with a median onset of 107 days.

Conclusion

This study provides valuable real-world evidence on the safety profile of irbesartan. The identification of new safety signals underscores the necessity of updating drug labels, particularly for assessing and managing high-risk patients. Additionally, the TTO analysis emphasizes the importance of sustained vigilance for adverse events over time. In conclusion, our findings contribute to a more comprehensive understanding of irbesartan's safety, aiding healthcare professionals in optimizing its use in clinical practice.

Tumor lysis syndrome signal with the combination of encorafenib and binimetinib for malignant melanoma: a pharmacovigilance study using data from the FAERS database

Objective

To investigate the potential association between tumor lysis syndrome (TLS) and drugs for the treatment of malignant melanoma (MM).

Methods

Reports of TLS recorded in the FDA Adverse Event Reporting System (FAERS) (January 2004-2023q3) were identified. Demographic and clinical characteristics were described, and disproportionality signals were assessed through the Reporting Odds Ratio (ROR) and Information Component (IC). The latency of TLS with anticancer drugs was described based on parametric models. Subgroup analysis was conducted to explore the differences of TLS signals in different age and sex.

Results

We found 5 (1.49%), 59 (17.61%), 79 (23.58%), 19 (5.67%), 13 (3.88%), 13 (3.88%), 33 (9.85%), 49 (14.63%), 16 (4.78%) TLS reports with pembrolizumab, nivolumab, ipilimumab, dabrafenib, vemurafenib, dacarbazine, "encorafenib and binimetinib", "nivolumab and ipilimumab", "dabrafenib and trametinib", respectively. The combination of encorafenib and binimetinib showed the strongest signal of TLS (IC025 = 3.98). The median days of latency of TLS with combination of encorafenib and binimetinib is 2 days, which was much shorter than nivolumab (22.0 days) and ipilimumab (21.5 days). TLS cases associated with drugs for MM were predominantly recorded in females and aged 25-65 years. After excluding confounding factors such as pre-existing diseases and co-treated drugs, the disproportionate signal of TLS with "encorafenib and binimetinib" remained strong.

Conclusions

Stronger disproportionate signal of TLS was detected in MM patients using the combination of encorafenib and binimetinib than other drugs. Further research is needed to investigate the underlying mechanisms and identify patient-related predisposing factors to support safe prescribing of the combination of encorafenib and binimetinib.

Lessons Learned on Observed-to-Expected Analysis Using Spontaneous Reports During Mass Vaccination

During the COVID-19 vaccination campaign, observed-to-expected analysis was used by the European Medicines Agency to contextualise data from spontaneous reports to generate real-time evidence on emerging safety concerns that may impact the benefit-risk profile of COVID-19 vaccines. Observed-to-expected analysis compares the number of cases spontaneously reported for an event of interest after vaccination ('observed') to the 'expected' number of cases anticipated to occur in the same number of individuals had they not been vaccinated. Observed-to-expected analysis is a robust methodology that relies on several assumptions that have been described in regulatory guidelines and scientific literature. The use of observed-to-expected analysis to support the safety monitoring of COVID-19 vaccines has provided valuable insights and lessons on its design and interpretability, which could prove to be beneficial in future analyses. When undertaking an observed-to-expected analysis within the context of safety monitoring, several aspects need attention. In particular, we emphasise the importance of stratified and harmonised data collection both for vaccine exposure and spontaneous reporting data, the need for alignment between coding dictionaries and the crucial role of accurate background incidence rates for adverse events of special interest. While these considerations and recommendations were determined in the context of the COVID-19 mass vaccination setting, they are generalisable in principle.

Towards a comprehensive safety understanding of granulocyte-colony stimulating factor biosimilars in treating chemotherapy associated febrile neutropenia: Trends from decades of data

Filgrastim, a biopharmaceutical listed on WHO model list of essential medicines, was approved in USA in 1991 for patients with non-myeloid malignancies associated with severe neutropenia and fever. Several filgrastim biosimilars have now been approved in USA, Europe and elsewhere since 2008, based on the reference product which has lost patent exclusivity; however their immunogenicity and safety is controversial. We conducted a retrospective, post market study between 1991 and May 2018 using VigiBase®. The study included all adverse events with case reports ≥150. Overall, 11,183 adverse drugs reaction reports were identified during observation period; of which 5764; 51.5% reports concerned to Neupogen®, the originator, and rest consists of Leucostim® (N = 680), Zarzio® (N = 622), Grasin® (N = 545), Nivestim® (N = 359) and Tevagrastim® (N = 152) biosimilars. When compared with the originator, Grasin® was associated with higher reporting of pyrexia (11.5% vs 7.9%, ROR 1.52, IC₀₂₅ 1.12), myalgia (37% vs 2.2%, ROR 25.94, IC₀₂₅ 2.11) and back pain (11.3% vs 4%, ROR 3.09, IC₀₂₅ 2.32). Zarzio® was associated with increased reporting of arthralgia (4.5% vs 2.9%, ROR 1.59, IC₀₂₅ 1.25) and neutropenia (11.4% vs 4%, ROR 2.59, IC₀₂₅ 3.07). Bone pain was reported more often with Nivestim® (14.4% vs 8.3%, ROR 1.87, IC₀₂₅ 5.30). Drug ineffectiveness was reported in cases with Zarzio® (35.9%), Nivestim® (19.4%) and Tevagrastim® (42.2%). Authors observed significant differences among originator and biosimilars in particular to efficacy, adverse events reported and time to onset of occurrences. Large epidemiologic studies are needed to further confirm these finding and provide additional insights.

Time to onset in statistical signal detection revisited: A follow-up study in long-term onset adverse drug reactions

Purpose

In a previous study, we developed a signal detection method using the time to onset (TTO) of adverse drug reactions (ADRs). The aim of the current study was to investigate this method in a subset of ADRs with a longer TTO and to compare its performance with disproportionality analysis.

Methods

Using The Netherlands's spontaneous reporting database, TTO distributions for drug—ADR associations with a median TTO of 7 days or more were compared with other drugs with the same ADR using the two‐sample Anderson–Darling (AD) test. Presence in the Summary of Product Characteristics (SPC) was used as the gold standard for identification of a true ADR. Twelve combinations with different values for the number of reports and median TTO were tested. Performance in terms of sensitivity and positive predictive value (PPV) was compared with disproportionality analysis. A sensitivity analysis was performed to compare the results with those from the previous study.

Results

A total of 38 017 case reports, containing 32 478 unique drug—ADR associations. Sensitivity was lower for the TTO method (range 0.08‐0.34) compared with disproportionality analysis (range 0.60‐0.87), whereas PPV was similar for both methods (range 0.93‐1.0). The results from the sensitivity analysis were similar to the original analysis.

Conclusions

Because of its low sensitivity, the developed TTO method cannot replace disproportionality analysis as a signal detection tool. It may be useful in combination with other methods.

The value of time-to-onset in statistical signal detection of adverse drug reactions: a comparison with disproportionality analysis in spontaneous reports from the Netherlands

PURPOSE

In pharmacovigilance, the commonly used disproportionality analysis (DPA) in statistical signal detection is known to have its limitations. The aim of this study was to investigate the value of the time to onset (TTO) of ADRs in addition to DPA.

METHODS

We performed a pilot study using individual case safety reports (ICSRs) for three drugs (Cervarix®, nitrofurantoin and simvastatin) from the Lareb spontaneous reporting database. TTO distributions for drug - ADR associations were compared to other ADRs for the same drug and to other drugs for the same ADR using two-sample Anderson-Darling testing. Statistically significant associations were considered true positive (TP) signals if the association was present in the official product information of the drug. Sensitivity and specificity for the TTO method were compared with the DPA method. As a measure of disproportionality, the reporting odds ratio (ROR) was used.

RESULTS

In general, sensitivity was lower, and specificity was higher for the TTO method compared to DPA. The TTO method showed similar sensitivity for all three drugs, whereas specificity was lower for Cervarix®. Eight additional TP signals were found using the TTO method compared to DPA.

CONCLUSIONS

Our study shows that statistical signal detection based on the TTO alone resulted in a limited number of additional signals compared to DPA. We therefore conclude that the TTO method is of limited value for full database statistical screening in our setting. Copyright © 2016 John Wiley & Sons, Ltd.

Estimating time-to-onset of adverse drug reactions from spontaneous reporting databases

BACKGROUND

Analyzing time-to-onset of adverse drug reactions from treatment exposure contributes to meeting pharmacovigilance objectives, i.e. identification and prevention. Post-marketing data are available from reporting systems. Times-to-onset from such databases are right-truncated because some patients who were exposed to the drug and who will eventually develop the adverse drug reaction may do it after the time of analysis and thus are not included in the data. Acknowledgment of the developments adapted to right-truncated data is not widespread and these methods have never been used in pharmacovigilance. We assess the use of appropriate methods as well as the consequences of not taking right truncation into account (naive approach) on parametric maximum likelihood estimation of time-to-onset distribution.

METHODS

Both approaches, naive or taking right truncation into account, were compared with a simulation study. We used twelve scenarios for the exponential distribution and twenty-four for the Weibull and log-logistic distributions. These scenarios are defined by a set of parameters: the parameters of the time-to-onset distribution, the probability of this distribution falling within an observable values interval and the sample size. An application to reported lymphoma after anti TNF- α treatment from the French pharmacovigilance is presented.

RESULTS

The simulation study shows that the bias and the mean squared error might in some instances be unacceptably large when right truncation is not considered while the truncation-based estimator shows always better and often satisfactory performances and the gap may be large. For the real dataset, the estimated expected time-to-onset leads to a minimum difference of 58 weeks between both approaches, which is not negligible. This difference is obtained for the Weibull model, under which the estimated probability of this distribution falling within an observable values interval is not far from 1.

CONCLUSIONS

It is necessary to take right truncation into account for estimating time-to-onset of adverse drug reactions from spontaneous reporting databases.

The impact of duration of treatment on reported time-to-onset in spontaneous reporting systems for pharmacovigilance

Within pharmacovigilance, knowledge of time-to-onset (time from start of drug administration to onset of reaction) is important in causality assessment of drugs and suspected adverse drug reactions (ADRs) and may indicate pharmacological mechanisms involved. It has been suggested that time-to-onset from individual case reports can be used for detection of safety signals. However, some ADRs only occur during treatment, while those that do occur later are less likely to be reported. The aim of this study was to investigate the impact of treatment duration on the reported time-to-onset. Case reports from the WHO Global ICSR database, VigiBase, up until February 5^th 2010 were the basis of this study. To examine the effect of duration of treatment on reported time-to-onset, angioedema and hepatitis were selected to represent short and long latency ADRs, respectively. The reported time-to-onset for each of these ADRs was contrasted for a set of drugs expected to be used short- or long-term, respectively. The study included 2,980 unique reports for angioedema and 1,159 for hepatitis. Median reported time-to-onset for angioedema in short-term treatments ranged 0-1 days (median 0.5), for angioedema in long-term treatments 0-26 days (median 8), for hepatitis in short-term treatments 4-12 days (median 7.5) and for hepatitis in long term treatments 19-73 days (median 28). Short-term treatments presented significantly shorter reported time-to-onset than long-term treatments. Of note is that reported time-to-onset for angioedema for long-term treatments (median value of medians being 8 days) was very similar to that of hepatitis for short-term treatments (median value of medians equal 7.5 days). The expected duration of treatment needs to be considered in the interpretation of reported time-to-onset and should be accounted for in signal detection method development and case evaluation.