Skip To Main Content

Ocrelizumab Safety Resources


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.3

Incidence Rate and Patient-time of Exposure3,4

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.

An incidence rate can be interpreted in a variety of ways, for example, 1 case per 1000 patient-years exposed could be interpreted as: 1 new case observed among 1000 persons during 1 year of exposure, or 1 new case observed among 500 patients during 2 years of exposure.

Standardized Incidence Ratio (SIR)3,4

The standardized 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).
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.
The calculation for the SIR in this case, would be the following:
SIR = 3 observed cases / 6 expected cases = 0.5

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.

Confidence Interval (CI)3,4

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.


Refers to the time after a drug or biological product has been approved by FDA.5

Carry-over PML

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.6


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.7