Does your age predict how well you respond to DMTs?

Did you know that if you have MS and are older than 53 years of age you are unlikely to respond to DMTs?




Statistical Speak: A regression analysis, described in the meta-analysis below, predicts zero efficacy of DMTs beyond approximately age 53 years. 

Plain English: Age is an important confounder when it comes to disability progression. Based on published data pwMS who are older than 53 years of age don't respond to DMTs when it comes to slowing down worsening disability. Are you surprised? 

Did you know that age is the most powerful predictor of developing 'progressive MS'? We need to tackle ageing and its impact on worsening MS. The evidence that early, or premature, ageing from the reduced brain, and cognitive, reserve drives worsening of MS in older pwMS. We urgently need methods to dissect-out premature ageing from MS-specific disease mechanisms. The other issue with ageing is the emergence of comorbidities as a driver of worsening MS; in particular, smoking, hypertension, hypercholesterolaemia, metabolic syndrome, diabetes and a sedentary lifestyle. The latter is the proverbial 'elephant in the room'. 

The meta-analysis also differentiates the high-efficacy DMTs from the low-efficacy DMTs. Surprise, surprise the high-efficacy drugs outperform low-efficacy drugs in slowing down MS disability worsening, but this was only noted for pwMS who were younger than 40.5 years.

Do you think regulators and payers should take age into account when licensing and paying for access to DMTs? 

P.S. This meta-analysis only tells half the story and does not take into account new insights, in particular, therapeutic lag. What the analysis is looking at is short-term observations across 2-3 years of phase 3 trials. With more advanced MS (and age) brain and spinal cord reserve are reduced and it, therefore, takes longer to see a treatment effect. So older people may see an effect, it will just take longer for it to manifest. I have plenty of examples (anecdotes in MedicSpeak) of more mature or older pwMS responding to DMTs. This analysis, however, does support the treat early and effectively philosophy; protecting Brain is easier when you have reserve and age on your side. 

Weideman et al. Meta-analysis of the Age-Dependent Efficacy of Multiple Sclerosis Treatments. Front Neurol. 2017 Nov 10;8:577. doi: 10.3389/fneur.2017.00577

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.

ProfG    

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