Multiple sclerosis (MS) treatment has shifted away from injectable agents, toward oral/infusible disease-modifying therapies (DMTs) that show greater efficacy in reducing disease activity. Clinical benefit has been observed in some patients on these high-efficacy DMTs, but factors that contribute to the likelihood of benefit are unknown.
To assess the impact of patient demographics, MS disease characteristics, and brain volumes on likelihood of clinical benefit in patients treated with high-efficacy DMTs, as assessed by patient-reported outcome (PRO) measures.
This retrospective chart review included adults with MS who completed 2 Patient-Determined Disease Steps (PDDS) measures and at least 2/10 Neurology Quality of Life (NeuroQOL) Short Form scales across 2 time points ≥10 months apart, taking a high-efficacy DMT at baseline. Qualifying DMTs included fingolimod, dimethyl fumarate, natalizumab, rituximab, and ocrelizumab. We examined the influence of various demographics, disease characteristics, and normalized brain volumes on likelihood of clinical benefit. PRO measures included the PDDS and 10 NeuroQOL domains. Patients were grouped as Clinical Benefit vs. Clinical Worsening by change in PDDS score over time (clinically significant change = +/- 1 point). Clinical Benefit was defined as No Change or Improvement on PDDS. Influence of NeuroQOL baseline and change scores was also investigated. NeuroQuant MRI reports provided volumetric data. Statistical analyses used Spearman correlations and logistic regression.
314 patients met inclusion criteria. Factors significantly predicting likelihood of clinical benefit included smoking history (Current v. Former: Odds Ratio (OR)=1.251, CI 5, 95=0.520, 3.008; Current v. Never: OR=2.332, CI 5, 95=1.017, 5.350; Former v. Never: OR=1.864, CI 5, 95=1.070, 3.249; p=.029), body mass index (Odds Ratio (OR)=1.049; CI 5, 95=1.009, 1.089; p=.015), and number of clinical relapses within the study period (OR=1.638; CI 5, 95=1.071, 2.505; p=.023). NeuroQOL scores significantly influencing likelihood of clinical benefit included baseline Fatigue (OR=1.043; CI 5, 95=1.014, 1.073; p=0.004), Sleep Disturbance (OR=1.045; CI 5, 95=1.014, 1.076; p=0.004), and Emotional and Behavioral Dyscontrol (OR=1.030; CI 5, 95=1.002, 1.058; p=0.033); and Social Participation change score (OR=0.918; CI 5, 95=0.876, 0.962; p<0.001).
Patient demographic and disease characteristics appear to better predict clinical benefit than brain volumes. As better baseline and follow-up functioning in several NeuroQOL domains appears to be associated with clinical benefit, clinicians who actively treat these symptoms may see enhanced patient outcomes.