Читать книгу Cobert's Manual Of Drug Safety And Pharmacovigilance (Third Edition) - William Gregory - Страница 50

When a new adverse event (AE) begins to be reported in association with a product, the two fundamental questions raised in the eyes of the regulator and the manufacturer are about frequency (How often will it happen?) and causality (Can it happen?).

Suppose that one or two spontaneous reports of liver injury with drug X are received at the safety department or health authority shortly after the first approval and use of the drug. First, what is the likely causality link between the liver problem and that suspect drug in those reports? Was the patient exposed to only the suspect drug X or were they concomitantly taking other drugs, including over-the-counter (OTC) medicines, “natural” or homeopathic or “traditional” products, and so forth? Was the time to onset, between taking the drug and start of liver injury, short enough to be suggestive of a causal link or was it so long that suspicion is rather low? Was there significant alcohol consumption, underlying infectious hepatitis, or other plausible causes of hepatic compromise? Was the patient in perfect health or was he or she at high risk of developing viral, alcoholic or other hepatitis? Is there a known background rate of hepatic dysfunction in the exposed population (subpopulation)?

According to these and other diagnostic criteria, the PV clinician will roughly assess causality using categories such as definite, probable, possible, or unlikely or some other causality grading system. When enough details are available and when the information is complete enough, these judgments are feasible and they matter. We then say these reports are valid and (it is hoped) of high quality. Various techniques described elsewhere in this Manual are used to judge whether this is a strong enough signal worth publicizing or, if weaker, requiring only continued surveillance.

Note: Many causal relationship methods have been published over the last decades. One interesting reference has been published by an epidemiologist in 1965.¹

The next question is the frequency (or risk) of occurrence of this reported AE. In other words, what is the probability of the next patient exposed to drug X developing severe liver disease? One in 10, 1 in 100, 1 in 1,000 people treated? To put it another way: What is the number of patients treated for another liver injury to be observed, also known as “Number Needed to Harm” 10, 100, 1,000? It is obviously important to know.

Over the years, many attempts have been made to apply statistics and epidemiologic quantitative methods to study case series of AEs, primarily using spontaneously reported AEs to inform causality. The results did not meet expectations.

It is necessary to differentiate between AEs reports received in clinical trials (experimental) or epidemiologic studies (observational) and those received spontaneously or in a solicited manner (surveillance or monitoring systems). The use of statistics is well described and defined for data generated in formal clinical trials. The patient populations are largely under the control of the investigator or researcher. The methodology for efficacy and safety analysis is well described and largely agreed on. Placebo- and comparator-controlled trials give clear pictures of occurrence rates of AEs, and significance values and confidence intervals can be determined and used to draw conclusions (at least for efficacy criteria). Clinical trials are usually not designed with sufficient statistical power to make safety judgments using statistics beyond descriptive statistics.

Different types of trials have different purposes in the world of pharmaceuticals. Randomized clinical trials are experimental and test one drug versus another or placebo or both. Pharmacoepidemiology studies look at observational use of drugs already on the market (in most cases). Pharmacovigilance studies are done for surveillance or monitoring of drug use and toxicity. Each type of study has a different though sometimes overlapping use.

The safety and efficacy data in the clinical trials are usually very solid, because data integrity is good to excellent. In addition, the data collected are usually complete. As patients are seen by the investigator at periodic intervals and as the investigator and his or her staff question the patient on AEs, it is believed that few AEs are missed, especially serious or dramatic ones. Incidence rates of AEs calculated from these data are held to be valid and useful.

Spontaneous reports received from routine healthcare practice are a different situation entirely. The data are unsolicited in most cases and may come from consumers or healthcare professionals. Follow-up for additional information is variable, and source documents (e.g., laboratory reports, office and hospital records, autopsy reports) are not always available because of privacy issues, busy physicians or pharmacists unable to supply records from multiple sources, patients not wanting to disclose information, and so on. If no healthcare professional was involved, such as when a patient uses an OTC product, the data usually cannot be verified. Hence, the data integrity of individual spontaneous reports is variable and inconsistent. There may also be duplicate reports if more than one person reports the case unbeknownst to the others.