PML that develops a few months after stopping one disease-modifying therapy (DMT) and starting a different DMT. In these cases, PML could have developed without causing symptoms while the patient was still on the previous DMT, or shortly after stopping the previous DMT.1

The confidence interval (CI) is an interval estimate with two components to it:

  • An estimated range of values within which one would expect the true population value to fall.

  • A probability (oftentimes 95%) that the true value would fall within that range.

How to interpret CIs that are calculated around SIRs:

  • If the CI includes 1.0, then any difference between the observed and expected number of events is likely to have occurred by chance.

  • If the CI does not include 1.0, then the difference between the observed and expected number of events is somewhat unlikely to have occurred by chance.

Additionally, it is important to note that factors such as the size of the study populations and number of events can affect how wide the confidence interval is. More narrow CIs are associated with more precise estimates.

Confounding of adverse event reporting occurs when the assessment of association between exposure to a drug and an adverse event is distorted by the effect of one or several other variables that are also risk factors for the outcome of interest.4

The incidence rate is a statistical measure that represents a measure of event occurrence per population, taking into account the length of time that each member of the population was observed. In technical terms, the incidence rate of an event in a population is the ratio of new events in a specified time period (numerator) divided by the patient-time exposure (which is the sum of the periods of time at risk for each of the patients) as the denominator.2,3

An incidence rate can be interpreted in a variety of ways, for example, 1 case per 1,000 patient-years exposed could be interpreted as: 1 new case observed among 1,000 persons during 1 year of exposure, or 1 new case observed among 500 patients during 2 years of exposure.2,3

In a study with 100 patients, 25 of whom participated for 2 years, and the other 75 who participated for 6 years, the denominator of the incidence rate as the total number of patient-years exposed is 500 patient-years [(25 patients x 2 years) + (75 patients x 6 years) = 50 + 450 patient-years].

If among those 100 patients, 5 occurrences of accidental bone fracture were observed, then the risk (proportion) would have been 5/100 patients or 5%.

We assume that the risk during the remaining 4 years for the 25 patients with 2-year participation would be no different from their first 2 years or from the 6 years of participation of the other 75 patients.

However, the incidence rate of accidental bone fracture would have been 5 per 500 patient-years, or 1/100 patient-years. This means that, on average, there was 1 occurrence of accidental bone fracture per 100 patients, over the course of each 1 year of treatment.

Incidence rates are used in many epidemiological studies and statistical assessments of risk which allows researchers to reveal trends and communicate levels of risk.

Studies of new medicines can express their safety findings using incidence rates based on 100 patient-years.5

Refers to the time after a drug or biological product has been approved by health authorities.6,7

The risk for a disease (or adverse event) represents the probability for the event to occur among a defined susceptible (or exposed) population. For example, the risk of a skin rash in the first week of treatment in patients receiving an antimicrobial. When risk is presented as a proportion (per 100 patients), we assume that all patients were exposed for the same length of time. In the example above, all patients were observed for 1 week. However, it is expected that the longer a patient is susceptible, or exposed, the higher is the probability for events to be observed. Incidence rates can be used to account for different lengths of times exposed when measuring risk.2,5

The standardised incidence ratio (SIR) is a statistical measure that is used to help determine if the occurrence of an event in a study population is high or low. The SIR compares the observed number of cases of an event with the number of events that would be expected in a larger reference population and age distribution (e.g. in the surrounding state or country).2,3

For example, say there were 3 bone fractures in a study of 100 people, but the standard population incidence rate of bone fractures was 6 per every 100 people. That would mean there are 3 observed cases/6 expected cases which gives an SIR of 0.5.2,3

The calculation for the SIR in this case, would be the following:

How to interpret SIRs:

  • If the SIR=1, then the number of observed events is the same as the number of expected events.

  • If the SIR <1, then the number of observed events is less than the number of expected events.

  • If the SIR >1, then the number of observed events is greater than the number of expected events.


1. Giovannoni G, et al. Pract Neurol 2016;16:389–93;

2. Rothman KJ, Greenland S, Lash TL (2008). Modern Epidemiology (3rd ed.). Philadelphia, PA: Lippincott Williams and Wilkins; 

3. New Jersey Department of Health and Senior Services. Fact sheet: Explanation of Standardized Incidence Ratios. Accessed October 2021;

4. Varallo FR, et al. Clin Ther 2017;39:686–96;

5. Porta M (Ed.) (2014) A dictionary of epidemiology (6th ed.). New York, NY: Oxford University Press. Accessed October 2021;

6. European Medicines Agency. Post-marketing authorisation: Regulatory and procedural guidance. Accessed October 2021;

7. US Food and Drug Administration. Postmarketing requirements and commitments: Reports. Accessed October 2021.


M-XX-00007227 (Date of preparation: October 2021)