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Drug-induced second tumors: a disproportionality analysis of the FAERS database
Shupeng Chen1, Yuzhe Zhang2, Xiaojian Li1
1School of Clinical Medicine, Jiangxi University of Chinese Medicine, Nanchang, 330004, China.
Background:
Drug-induced second tumors (DIST) refer to new primary cancers that develop during or after the treatment of an initial cancer due to the long-term effects of medications. As a severe long-term adverse event, DIST has gained widespread attention globally in recent years. With the increasing prevalence of cancer treatments and the prolonged survival of patients, drug-induced second tumors have become more prominent and pose a significant public health challenge. However, most existing studies have focused on individual drugs or small patient cohorts, lacking large-scale, real-world data evaluations. Particularly, the potential second-tumor risk of new drugs remains underexplored.
Objective:
This study aims to systematically assess the adverse event signals between drugs and second tumors using the U.S. FDA Adverse Event Reporting System (FAERS) database, employing disproportionality analysis (DPA) methods. It particularly focuses on uncovering drugs that have not clearly labeled second-tumor risks.
Methods:
Data from the FDA Adverse Event Reporting System (FAERS), covering reports from its inception to the third quarter of 2024, was retrieved. After data standardization, four disproportionality methods were used: Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS). These methods assessed the correlation between azacitidine and adverse drug events (ADEs). Additionally, the Weibull Shape Parameter (WSP) was used to analyze the characteristic patterns of time-to-onset curves. Newly discovered signals were verified against FDA drug labels to confirm their novelty. The Weibull analysis was conducted to examine the temporal aspects of adverse event occurrences.
Results:
Since 2004, drug-induced tumor events have been increasing annually, with a total of 7597 drug-related tumor adverse events recorded. A total of 250 drugs were identified as having potential risk signals. High-incidence populations were primarily aged between 65 and 85 years, with a higher proportion of individuals with a body weight ≥ 90 kg. The most frequent occurrence was observed in patients with Chronic Myeloid Leukemia (13.36%). Among the top 5 drugs with the highest number of reported drug-induced second tumor adverse events, IMATINIB (906 reports), RUXOLITINIB (554 reports), PALBOCICLIB (552 reports), OCTREOTIDE (399 reports), and DOXORUBICIN (380 reports) were identified. Among these, PALBOCICLIB, OCTREOTIDE, and DOXORUBICIN are drugs for which the risk of drug-induced second tumors is not explicitly mentioned in their labels. A total of 76 drugs were identified through four disproportionality algorithms (ROR, PRR, MGPS, BCPNN), with a minimum time to drug-induced tumor occurrence of 5 years, exhibiting an early failure-type curve.
Conclusion:
This study, based on large-scale real-world data, reveals the potential associations between drugs and second tumors, especially highlighting the risks of some new drugs. The findings provide valuable insights for drug safety monitoring and have significant public health implications. By uncovering previously unrecognized potential risks, this research lays the groundwork for further advancements in pharmacovigilance.
Insights
This study identified 250 drugs potentially linked to drug-induced second tumors (DIST) using real-world data. Some new drugs like PALBOCICLIB, OCTREOTIDE, and DOXORUBICIN show risks not yet labeled, impacting public health and drug safety monitoring.
Area of Science:
- Pharmacovigilance and Drug Safety
- Oncology and Cancer Research
- Public Health and Epidemiology
Background:
- Drug-induced second tumors (DIST) are new cancers developing during or after cancer treatment due to medication side effects.
- DIST is a growing public health concern due to increased cancer survival and treatment prevalence.
- Existing research on DIST often lacks large-scale, real-world data, especially for newer medications.
Purpose of the Study:
- To systematically assess drug-associated adverse event signals for second tumors.
- To utilize the U.S. FDA Adverse Event Reporting System (FAERS) database for disproportionality analysis (DPA).
- To identify drugs with potential, unlabelled second-tumor risks.
Main Methods:
- Analysis of FAERS data from inception to Q3 2024.
- Application of four disproportionality methods: ROR, PRR, BCPNN, and MGPS.
- Weibull Shape Parameter (WSP) analysis for time-to-onset patterns and signal novelty verification against FDA labels.
Main Results:
- 7597 drug-related tumor adverse events recorded since 2004, with increasing annual incidence.
- 250 drugs identified with potential risk signals, primarily affecting individuals aged 65-85.
- PALBOCICLIB, OCTREOTIDE, and DOXORUBICIN identified as drugs with potential risks not explicitly labeled.
Conclusions:
- Large-scale real-world data analysis reveals potential drug-second tumor associations, including for newer medications.
- Findings offer critical insights for enhancing drug safety monitoring and pharmacovigilance.
- Identification of previously unrecognized risks supports public health initiatives and future research.
