Research Decoder: Outcome measures I – Clinical

hClinical trials are an indispensable part of the process that determines which disease-treating interventions (including drugs, procedures, technologies, or lifestyle modifications) can move from the experimental stage to the public realm. Health care decision makers that establish health policy, such as the approval of new drugs or repurposing existing drugs for new indications, rely on the findings of clinical trials about the safety and effectiveness of an intervention since they provide some of the most reliable evidence of the value of an intervention. But how do the investigators who conduct the trials determine whether an intervention really works?

When designing a clinical trial, research investigators chose appropriate outcome measures, or endpoints, that they will monitor in order to determine the effectiveness of the intervention they are studying. Outcome measures come in a variety of forms, and can be either objective (such as the results of a laboratory test), subjective (such as a participant’s perception of their fatigue) or oftentimes a combination of the two. They can also be classified as primary or secondary. Primary endpoints measure outcomes that answer the key question being asked by the trial, and the number of participants enrolled in the trial is chosen in order to have enough statistical power to detect differences in this primary measure. Secondary endpoints capture measures that, although not as imperative as the primary endpoint, are still relevant to the study and can sometimes even lead to follow-up trials in which investigators have the chance to fine-tune the outcome measures and study design.

The types of outcome measures chosen depend on a number of factors, including the number of participants enrolled, the unique characteristics of the population under study, and the specific question being asked. For example, let’s say that the aim of a trial is to test the effectiveness of a new drug in improving mobility in participants with a high level of disability. An outcome measure that uses a test to assess how quickly participants can walk one mile would probably be inappropriate; not only would it be difficult for participants with high disability to complete the test, but the test might not have enough sensitivity to detect any improvement in the treated group.

Ultimately, choosing the right outcomes measures from the get-go is one of the most important aspects of clinical trial design, since a poorly chosen measure might not capture the true impact of the intervention, or can even distort it.

In part one of this Research Decoder series, I’ll be describing some of the clinical outcome measures commonly used to assess changes in MS disease activity and disability progression in clinical trials.

  • Relapse rate: A common primary outcome measure of many MS clinical trials, relapse rate is fairly easy to quantify and is a tangible measure of inflammatory disease activity. Preventing relapses can also have an immediate impact for people living with relapsing forms of MS. Changes in relapses can be measured in various ways, including annualized relapse rate, time to first relapse, or measuring the proportion of participants who have a relapse at a certain time point. Despite the usefulness of this measure, there are some limitations to using relapse rate as an outcome measure; since relapses can be separated by many months or sometimes years, trials must be conducted over a long period of time and enrol many participants in order to produce meaningful results.
  • Expanded Disability Status Scale (EDSS): This 10-point scale of disease severity quantifies a participant’s disability using scores in eight functional systems that relate to visual, physical and psychological disability on a scale from 0.0 (normal neurological exam) through 5.0 (ambulatory without aid for 200 metres) to 10.0 as the most serious outcome. The EDSS is the most widely used tool to assess disease progression, which in most cases is defined as a 0.5 or 1.0 point step increase in score after 3 or 6 months. Like relapse rate, EDSS may not be sensitive to changes in disability over short periods of time, and EDSS methodology continues to be fine-tuned – such as the creation of the Multiple Sclerosis Severity Scale (MSSS) that integrates EDSS and disease duration – to improve its accuracy and reliability.
  • MS functional composite (MSFC): This is a relatively new outcome measure that improves on some of the limitations of the EDSS. The MSFC uses a series of three tests to measure ambulation, arm function and cognitive processing speed. Some of the advantages of the MSFC are that it is very fast and can be administered by a trained technician rather than a clinician, making it well suited to clinical trials with hundreds of participants. The MSFC correlates well with other clinical and imaging outcome measures. Very importantly, it is sensitive to changes over short periods of time, which can lead to shortened trials and provide information about short-term changes in disability that are immediately meaningful to participants. Since the MSFC does not include an assessment of vision loss, an additional test called the low contrast letter acuity (LCLA) assessment can be used in tandem with the MSFC.

Stay tuned for part two, where I’ll be delving into some of the imaging outcome measures used in MS clinical trials.

References

  1. Goldman MD et al. (2010) Possible clinical outcome measures for clinical trials in patients with multiple sclerosis. Ther Adv Neurol Disord. 3(4):229–39.
  2. Lavery AM et al. (2014) Outcome Measures in Relapsing-Remitting Multiple Sclerosis: Capturing Disability and Disease Progression in Clinical Trials. Mult Scler Int. 2014:262350.

Image credits: © Cornelius20 | Dreamstime.com – Brain Maze Photo

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