My last bog talked about mitigating data overload with proactive pharmacovigilance (PV). The next blog in this series analyzes the history of PV, AEs and clinical therapeutics.
As early as the 1980s, it was recognized that prostaglandins were important in renal function, especially in hypertensive patients. Prostaglandins preserve and maintain renal blood flow and thus healthy renal function.
In 1982, one of the first peer-reviewed publications appeared in the literature indicating the adverse effect of non-steroidal anti-inflammatory drugs (NSAIDs) in patients with hypertension. NSAIDs were shown to diminish the control of blood pressure in treated hypertension patients. Common NSAIDs such as ibuprofen, naproxen, and aspirin are staple drugs for the treatment of mild/moderate pain from a variety of conditions and are available in most countries as OTC products. They are effective analgesics because they block the enzyme cyclooxygenase which downstream, blocks the production of prostaglandins; mediators of pain but also important mediators of appropriate renal blood flow and protection of the gastric mucosa. The protection of gastric mucosa lends a familiar reference to NSAIDs and their known AE of gastric irritation. Ranging from mild heartburn to severe ulcerations and bleeding, NSAID inhibition of protective gastric prostaglandins can limit the use of these drugs in some patients.
The use of NSAIDs in hypertensive patients had both an interaction with antihypertensive drugs and had negative impact on blood pressure control. Since that time, there have been hundreds of peer-reviewed studies confirming this association.
Despite the longevity of knowledge of this therapeutic group of drugs, there continues to be a high rate of adverse events in hypertensive patients who are prescribed NSAIDs or take them as OTC medications. The data is conclusive that hypertensive, congestive heart failure, and other cardiovascular disease patients have a higher rate of adverse outcomes of existing disease with NSAID use.
In a retrospective study by Varga et al. in 2019 involving more than one million patients followed over 10 years, more than half of the patients received a potentially inappropriate (drug-drug or drug-disease interacting) medication. Meaning, there was a known risk of drug-drug or drug-disease or special patient considerations where the drug should not have been prescribed. In this patient cohort, hospitalization risk was increased in patients who received drugs that had known drug-drug or drug-disease interactions.
This guide analyzes how artificial intelligence – including machine learning – can be used by pharmaceutical and medical device companies to improve the clinical data review and cleansing process.
Not surprisingly, NSAIDs were the drug class with the highest rates of adverse events that led to hospitalizations. As with any product, AEs are temporal to the use of the medication. They are not always causal, but in the case of NSAIDs and certain patients, there is enough data to confirm with clinical and scientific certainty that the relationship between out-of-control blood pressure and NSAID use in hypertensive patients exists.
In a comparative retrospective study in 2016 by Shehab et al., the investigators found that in 56 Emergency Departments across the US, 4/1000 visits were due to drug adverse events, and of those, 27% resulted in hospitalization. An adverse event so serious that it requires hospitalization does no one any favors. Many in this study could and should have been prevented. Shehab et al. reported that 34.5% of patients were older than 65 years of age (high-risk patient population), a rise in hospitalization by 8% in less than 10 years. In this study, anticoagulants and drugs for diabetes comprised 47% of the ED (emergency department) visits and included known AEs such as hemorrhage, allergic reactions, and hypoglycemia. More wrenching is that antibiotic-related AEs were the most common drug class in children less than five years of age that required ED evaluation.
Similar findings were reported by Jolivot et al. in 2016, in which 743 ICU patient admissions were categorized into preventable AEs, unpreventable AEs, and the control group.15 Similar to Shehab et al., Jolivot and colleagues found that 23.3% of 743 consecutive ICU admissions were due to an AE. Further, 13.7% of those AEs were preventable, and 9.6% ICU admissions were due to unpreventable AEs. In total, 102/173
AE-related ICU admissions were preventable. The 102 preventable AE related ICU admissions (59%) accounted for a total of 528 days of ICU hospitalizations and an associated cost of €747,651.
Hence, the knowledge gap and the result is not surprising. This study shows that predictable and known AEs can have a significant negative impact on patients.
NSAIDs are not the only class of drugs with AEs frequently seen in medical literature. In 2017, Kumar et al. reported adverse events in outpatients with mental disorders, including schizophrenia, bipolar disease, and depression. Even at a fairly young mean age (32 years), more than 40% of patients reported sedation and 25% reported weight gain. While sedation and weight gain seem to be small tradeoffs for disease control, sedation and weight gain are common reasons that patients discontinue mediation–often without informing their health care provider.
In the pharmacovigilance world, non-compliance is often reported as an AE. For example, a report of a lack of drug effect or lack of efficacy can be the AE reported when in reality, if you don’t take the drug as prescribed, it can’t be expected to work. Or, non-compliance can result in the progression of underlying diseases and sequelae. For example, a patient with diabetes who does not adhere to their insulin regimen may report an AE of renal impairment or loss of vision, a well-known sequelae of uncontrolled diabetes. Anyone who has to fight with the big chain mailorder pharmacies to get their drugs approved, much less delivered on time, understands that non-compliance can be a complicated, multi-factorial problem.
Can we really expect favorable outcomes when we do a poor job in bridging the knowledge gap between pharmacovigilance data and clinical treatment? Is this a knowledge gap or are we so overwhelmed by just performing pharmacovigilance practices for compliance reasons that we lose sight of what the data means to healthcare providers and patients and do not seek meaningful ways to bridge that gap? We are clearly not learning or paying attention to the data, not because we are lax, but because the volume of data is overwhelming. Many investigators have looked at technology solutions to ease this burden but to date, no one approach has proven to be truly effective.
Even with the decades of scientific and clinical awareness that AEs drive poor clinical outcomes, interfere with other treatments, and negatively impact disease progression, we still struggle with known drug-drug interactions, underreporting, and drug-disease interactions. Despite our wealth of knowledge, upwards of 30% of AEs are due to known drug-drug interactions.
To learn more about the history of pharmacovigilance, current challenges and ROI opportunities, and how to remain proactive in the future, you can download our guide here. Or, you can submit the form below.