Meta-analysis of the Age-Dependent Efficacy of Multiple Sclerosis Treatments

Abstract

Objective: To perform a meta-analysis of randomized, blinded, multiple sclerosis (MS) clinical trials, to test the hypothesis that efficacy of immunomodulatory disease-modifying therapies (DMTs) on MS disability progression is strongly dependent on age.

Methods: We performed a literature search with pre-defined criteria and extracted relevant features from 38 clinical trials that assessed efficacy of DMTs on disability progression. We fit a linear regression, weighted for trial sample size, and duration, to examine the hypothesis that age has a defining effect on the therapeutic efficacy of immunomodulatory DMTs.

Results: More than 28,000 MS subjects participating in trials of 13 categories of immunomodulatory drugs are included in the meta-analysis. The efficacy of immunomodulatory DMTs on MS disability strongly decreased with advancing age (R2 = 0.6757, p = 6.39e-09). Inclusion of baseline EDSS did not significantly improve the model. The regression predicts zero efficacy beyond approximately age 53 years. The comparative efficacy rank derived from the regression residuals differentiates high- and low-efficacy drugs. High-efficacy drugs outperform low-efficacy drugs in inhibiting MS disability only for patients younger than 40.5 years.

Conclusion: The meta-analysis supports the notion that progressive MS is simply a later stage of the MS disease process and that age is an essential modifier of a drug efficacy. Higher efficacy treatments exert their benefit over lower efficacy treatments only during early stages of MS, and, after age 53, the model suggests that there is no predicted benefit to receiving immunomodulatory DMTs for the average MS patient.

Keywords: clinical practice; clinical trials; meta-analysis; neuroimmunology; neuroinflammation.

Figures

Figure 1

PRISMA flow chart for immunomodulatory multiple sclerosis drug efficacy meta-analysis. The diagram summarizes our search strategy for including clinical trials in the meta-analysis.

Figure 2

Efficacy of interferon-beta preparations and all immunomodulatory drugs on sustained disability progression decreases with age. Linear regression of the efficacy of all interferon-beta formulations against placebo on sustained disability progression as a function of age (top panel). Each contributing trial has assigned weight proportional to the number of subjects and trial duration (see Eq. 2 in Materials and Methods). The resulting linear regression was used to estimate percent inhibition of disability progression (%IDP) of interferon beta against placebo at baseline age (see Eq. 1). This estimate was then used to recalculate %IDP for all immunomodulatory drugs against placebo as a function of age (see Eq. 7). Linear regression of the efficacy of all drugs against placebo on sustained disability progression as a function of age (bottom panel). Again, each contributing trial has assigned weight proportional to the number of subjects and trial duration. The coefficient of determination (R2) and p-values are indicated in the respective plots, while the inset legends denote the trial indices.

Figure 3

Relationship between immunomodulatory drugs and original linear regression model used for computing drug-specific weighted residuals. Due to the overlap of clinical trials in the Figure 2 (bottom panel) linear regression model, we provide a separate visual representation of all clinical trials that studied individual drugs or drug classes. Each circle corresponds to a single clinical trial with area proportional to the number of subjects and trial duration (weight=πr2→r=weight/π,where r is the radius of the circle). The gray area depicts 95% confidence interval estimates. Trials with circle center above the regression line have better-than-average efficacy adjusted for age, while trials with circle center below the regression line have worse-than-average efficacy adjusted for age. The distances from the circle center to the regression line (i.e., residuals) are adjusted by weight and SD (see Eq. 8 in Materials and Methods) and then averaged to compute the drug-specific weighted residuals (Figures 4A,B).

Figure 4

Low- and high-efficacy categories derived from drug-specific weighted residuals and development of optimized model with interaction between age and efficacy. Comparative efficacy ranks for standardized, drug-specific weighted residual means computed from the linear regression fit to all drugs (A) or fit to clinical trials of FDA-approved drugs studied in FDA-approved indications (B). The means of the drug-specific residuals are provided directly in the lollipop plots. FDA-approved immunomodulatory disease-modifying therapies from (B) were then separated into high-efficacy drugs (i.e., drugs with positive means) and low-efficacy drugs (i.e., drugs with negative means). A regression model that includes all FDA-approved drugs with an interaction between age and efficacy (0 for low-efficacy, 1 for high-efficacy) is depicted in (C). Simple weighted linear regressions were fit to clinical trials of low-efficacy (D) and high-efficacy (E) drugs using only trials that studied FDA-approved drugs. Corresponding coefficients of determination (R2) and p-values are included in the individual plots, while the inset legends provide color and alphabet code for individual drugs. (F) The 95% confidence interval denotes the statistically significant difference in means between low- and high-drug efficacy as a function of age. The gray dashed vertical line indicates that there is no significant difference between low- and high-efficacy drugs past age 40.5 years.