How to Read a Pharmacovigilance Signal: What FAERS Can and Cannot Tell Us
Pharmacovigilance databases such as the FDA Adverse Event Reporting System (FAERS) occupy an unusual and often misunderstood position in modern drug safety science. They sit somewhere between the controlled clarity of clinical trials and the expansive but noisy reality of real-world epidemiology. FAERS is built on spontaneous reporting, meaning that adverse events are submitted by clinicians, patients and manufacturers without a standardized denominator of total drug exposure.
As a result, the raw numbers cannot be used to estimate incidence or absolute risk. Instead, FAERS is designed to identify statistical disproportion: specific events that appear more frequently with a drug than would normally be expected based on the database as a whole. These disproportionate patterns are known as “signals,” and they serve as early flags that demand closer scrutiny rather than functioning as evidence that a drug causes the event in question.
Understanding the meaning of these signals requires familiarity with the algorithms used to generate them. The reporting odds ratio and proportional reporting ratio rely on comparisons within the database to determine whether a particular event appears unusually common for a given medication. Bayesian methods such as the BCPNN and MGPS incorporate prior probability estimates and shrinkage factors, helping reduce false positives that arise from small sample sizes or random fluctuations. When all methods converge on the same signal, the probability that the association is due to noise decreases substantially. In the sildenafil analysis, the researchers employed all four approaches, an uncommon level of methodological redundancy that strengthens confidence in the internal coherence of the findings.
Sildenafil is an especially fertile candidate for this kind of analysis because of its massive global use, its diverse prescribing patterns and the broad demographic range of its users. With more than thirty-three thousand adverse event reports included in the FAERS dataset examined in the study, the sample size provides enough granularity to detect both the well-known adverse effects and those that only emerge when millions of real-world exposures accumulate over time. But the same strengths can also mislead. High public awareness of the drug can inflate reporting, while the underlying indications for sildenafil use, particularly cardiovascular comorbidity, can create confounding patterns in vascular and thrombotic events. Interpreting the results therefore requires a disciplined balance: openness to the possibility that the signal represents a genuine pharmacological effect, and caution in recognising that FAERS cannot distinguish correlation from causation.
The most responsible way to read these data is to treat them as a map rather than a verdict. They highlight where the terrain looks uneven, where unexpected features emerge, and where established assumptions may warrant re-examination. What they cannot do is tell us definitively whether sildenafil increases the risk of melanoma, aortic dissection or rare coagulopathies. That judgment must come from mechanistic research and epidemiological studies that follow. Yet the presence of consistent, cross-method signals in a dataset of this size suggests that further investigation is not only reasonable, but necessary. Pharmacovigilance at its best does not resolve controversies; it reveals where they may exist.
Expected Adverse Events Confirmed: Visual Disturbances, Auditory Loss, Priapism, and Cardiovascular Symptoms
Before turning to the unexpected findings, it is important to situate sildenafil within its well-established safety landscape. The FAERS analysis reaffirmed the adverse events that clinicians already recognise as characteristic of PDE5 inhibitor pharmacology. Sildenafil’s mechanism of action, i.e., potentiation of nitric oxide signalling through inhibition of phosphodiesterase type 5, predictably produces transient vasodilation, shifts in blood pressure regulation and changes in perfusion of vascular-rich tissues. These effects, although generally mild, explain the familiar constellation of headaches, flushing and nasal congestion seen in routine practice. More distinctive are the visual disturbances, including blue-tinged vision and increased light sensitivity, that arise from incidental inhibition of phosphodiesterase type 6 in retinal photoreceptors. These events have been documented since early clinical development and continue to appear in post-marketing surveillance, reinforcing the biological plausibility of the signal.
Similarly, reports of auditory impairment, including sudden sensorineural hearing loss, have long been recognized in association with PDE5 inhibitors and appear with consistent frequency across pharmacovigilance systems.
Priapism, although uncommon, remains one of the most clinically significant adverse events, particularly in patients with hematologic disorders. The FAERS data confirm these patterns, lending internal validity to the database: when a source reliably reproduces well-known signals, confidence grows that it may also detect novel associations rather than merely random noise.
ardiovascular symptoms, too, reflect a mixture of expected pharmacodynamic effects and underlying patient comorbidity. Many sildenafil users have baseline risk factors such as hypertension or coronary disease, making it essential to interpret chest pain, arrhythmia or dyspnea with nuance. The FAERS findings do not challenge the known safety profile of the drug, but they establish a trustworthy backdrop against which the more surprising signals of melanoma, vascular injury and coagulopathy stand out.
Unexpected and High-Signal Events: Melanoma, Pulmonary Hypertension, Coagulopathies, and Aortic Pathologies
What distinguishes the sildenafil FAERS analysis from earlier pharmacovigilance studies is the number and consistency of unexpected adverse-event signals that emerged across all major detection algorithms. These are events not traditionally considered part of sildenafil’s safety profile, yet they appeared frequently enough (and disproportionately enough) to demand careful attention.
Among them, the association with malignant melanoma stands out both for its statistical strength and for its resonance with a decade of debate surrounding PDE5 inhibitors and skin cancer risk. Several epidemiological studies in the 2010s suggested a small but measurable elevation in melanoma incidence among users, prompting speculation that cGMP-pathway signalling could promote melanoma cell proliferation or migration. Although later analyses cast doubt on the magnitude of this effect and emphasized confounding lifestyle factors, the FAERS findings revive the question by demonstrating that melanoma, including several of its subtypes, is disproportionately reported in connection with sildenafil use. The data cannot establish causation, but the recurrence of a controversial signal across multiple methodologies is difficult to dismiss outright.
Equally noteworthy is the appearance of pulmonary hypertension as an adverse event. It is a paradoxical signal for a drug that is therapeutically used to treat pulmonary arterial hypertension in specific formulations. This raises the possibility of misclassification in reporting, yet FAERS researchers often treat such contradictions as meaningful, since paradoxical reactions can reveal subtype differences, drug disease interactions or off-target physiological effects not captured in clinical trials. The same logic applies to the vascular anomalies highlighted in the analysis, including aortic rupture and intracranial artery dissection. These events are extremely rare, but their disproportionate representation in the dataset suggests more than statistical noise. Because sildenafil influences vascular smooth muscle tone and systemic hemodynamics, a mechanistic hypothesis, however speculative, is not difficult to conceptualize, particularly in individuals with pre-existing aortic pathology or connective-tissue fragility.
The signal for acquired hemophilia adds another layer of complexity, connecting sildenafil to an autoimmune coagulopathy that is itself rare enough to make disproportionality analysis challenging. Yet the presence of the signal across several detection algorithms implies that it is not an isolated oddity. While immunologic mechanisms remain entirely hypothetical, the consistency of the association invites further exploration through case-series analysis or targeted epidemiological study.
Taken together, these unexpected findings do not convict sildenafil of causing melanoma, vascular injury or coagulopathy. Instead, they broaden the perimeter of scientific curiosity. When different statistical tools converge on the same set of anomalies in a dataset this large, the appropriate response is neither alarmism nor indifference, but methodical follow-up, that is, an approach that protects patients without undermining the drug’s well-established therapeutic value.
What These Signals Mean for Practicing Clinicians: Risk Stratification, Patient Counseling, and Sensible Caution
For clinicians, the challenge is to integrate pharmacovigilance findings into patient care without overreacting to associations that have not yet been confirmed by epidemiological or mechanistic evidence. Sildenafil remains widely regarded as a safe and effective medication (Doses, Safety, Contraindications of Sildenafil), and nothing in the FAERS dataset contradicts its overall risk benefit profile. Yet the unexpected signals like melanoma, vascular injury and rare coagulopathies, invite a more nuanced approach to prescribing, one that balances reassurance with vigilance. The task is not to discourage use but to recognize circumstances in which a clinician’s situational awareness should be heightened. When a patient has a history that intersects with one of the high-signal categories, the threshold for clinical attention may need to be lower. A man with a prior melanoma, for example, may not need to avoid sildenafil entirely, but he should be encouraged to maintain dermatologic surveillance and promptly report any evolving skin lesions. Individuals with connective tissue disorders, aortic aneurysms or unexplained, severe chest or back pain require a thoughtful assessment of whether the timing of symptoms corresponds to sildenafil exposure. Likewise, the appearance of spontaneous bruising, prolonged bleeding or unusual hematomas may merit laboratory evaluation, even though acquired hemophilia remains exceptionally uncommon. These precautions do not reflect proven drug toxicity; rather, they represent prudent clinical reasoning in the face of emerging, incomplete data.
For the vast majority of patients, the practical advice remains unchanged: sildenafil can be used safely when taken as prescribed, with attention to cardiovascular status and known contraindications. The FAERS signals should not prompt routine discontinuation or alarm, but they reinforce the value of individualized care. Pharmacovigilance findings are reminders that drug safety is dynamic, shaped by real-world exposures that extend far beyond the controlled environment of clinical trials. By acknowledging uncertainty without magnifying it, clinicians can protect patients while maintaining trust in therapies that continue to offer meaningful benefits.
The Intersection of Real-World Pharmacovigilance and Mechanistic Research: Why These Signals Deserve Further Study
The sildenafil FAERS analysis underscores how post-marketing surveillance often functions as the first indicator of safety questions that clinical trials are not powered to detect. Trials typically exclude patients with complex comorbidities, rare genetic susceptibilities or overlapping medications, whereas real-world use exposes the drug to biological diversity on a far larger scale. When unexpected patterns emerge, such as melanoma, arterial dissections, or coagulopathies, they do not claim causality but instead illuminate where scientific inquiry should next be directed. The strength of the sildenafil findings lies not in any single statistic but in the convergence of several detection algorithms, each governed by different assumptions, pointing to the same anomalies.
What happens after a signal appears is equally important. Mechanistic research can test whether PDE5 inhibition plausibly influences pathways involved in melanoma proliferation, vascular integrity or immune dysregulation. Epidemiological studies, especially those with robust adjustment for confounders, can help determine whether the signal holds in population-level data or fades when rigorously examined. These processes take time, but they exemplify how pharmacovigilance fits into a broader ecosystem of drug safety science.
In this sense, the sildenafil signals are neither warnings nor curiosities. They are hypotheses in motion, guiding future research toward the areas where clarity is most needed.
References
- Wang, Q., Feng, Y., Hu, X., Sun, J., & Wang, T. (2023). Postmarketing safety signal detection of sildenafil using FDA adverse event reporting system. Annals of Translational Medicine, 11(18), 707. https://pubmed.ncbi.nlm.nih.gov/37724699/
