Diminishing returns of disease-modifying treatment in older participants of multiple sclerosis clinical trials

TL;DR

This study shows that disease-modifying treatments for multiple sclerosis become less effective as patients age, based on clinical trial data.

Contribution

The novel use of Number Needed to Treat (NNT) to quantify diminishing treatment efficacy with age in multiple sclerosis trials.

Findings

Inflammatory disease activity decreases with age, leading to higher NNTs in older patients.

NNTs to prevent T2 lesions or relapses increase significantly in older age groups.

NNTs offer a practical framework for balancing treatment benefits and harms in clinical decision-making.

Abstract

It remains uncertain whether the relative benefit of disease-modifying treatments (DMTs) diminish as patients age because of a natural decline of inflammatory disease activity. To better capture the balance of benefit and harm, the statistical concept of the Number Needed to Treat (NNT) provides a useful and easily interpretable metric.

We examined the relationship between treatment efficacy and age by applying the NNT concept to three pivotal randomized clinical trials of high-efficacy DMTs: AFFIRM, SENTINEL, and DECIDE (3,954 participants together). NNTs were calculated to determine how many individuals within each age group would need to be treated to prevent one additional inflammatory event (by different definitions of significant inflammation).

Inflammatory disease activity decreased with advancing age, resulting in progressively higher NNTs in older participants. For instance, in the SENTINEL trial, the NNT to prevent one additional new/enlarging T2 lesion annually was one for the youngest patients (⩽30 years) compared with 10 for the oldest (>50 years). Similarly, in AFFIRM, the NNT to prevent one relapse was two in the youngest group (⩽30 years) versus four in the oldest (41–50 years).

NNTs provide a framework for contextualizing treatment efficacy against potential harms, supporting more individualized therapeutic decision-making.

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