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BACKGROUND AND OBJECTIVE: Understanding the socioeconomic burden of multiple sclerosis (MS) is essential to inform policymakers and payers. Real-world studies have associated increasing costs and worsening quality of life (QoL) with disability progression. This study aims to further evaluate the impact of cognition, fatigue, upper and lower limb function (ULF, LLF) impairments, and disease progression per Expanded Disability Status Scale (EDSS) level, on costs and QoL. METHODS: This was a cross-sectional cohort study including 20,988 patients from the German NeuroTransData MS registry from 2009 to 2019. QoL analyses were based on EQ-5D-5L. Cost analyses included indirect/direct medical and non-medical costs. Eight subgroups, ranging from 439 to 1812 patients were created based on presence of measures for disease progression (EDSS), cognition (Symbol Digit Modalities Test [SDMT]), fatigue (Modified Fatigue Impact 5-Item Scale [MFIS-5]), ULF (Nine-Hole Peg Test [9HPT]), and LLF (Timed 25-Foot Walk [T25FW]). Multivariable linear regression assessed the independent effect of each test's score on QoL and costs, while adjusting for EDSS and 12 other confounders. RESULTS: Lower QoL was associated with decreasing cognition (p < 0.001), worsening ULF (p = 0.025), and increasing fatigue (p < 0.0001); however, the negative impact of LLF worsening on QoL was not statistically significant (p = 0.54). Higher costs were associated with decreasing cognition (p < 0.001), worsening of ULF (p = 0.0058) and LLF (p = 0.049), and increasing fatigue (p < 0.0001). Each 1-scale-step worsening function of SDMT, MFIS-5, 9HPT, and T25FW scores resulted in 170, 790, 330, and 520 higher costs, respectively. Modeling disability progression based on SDMT, MFIS-5, 9HPT, and T25FW scores as an interaction with EDSS strata found associations with lower QoL and higher costs at variable EDSS ranges. CONCLUSIONS: Disease progression in MS measured by 9HPT, SDMT, and MFIS-5 had a significant negative impact on QoL and broad socioeconomic costs independent of EDSS. T25FW had a significant negative association with costs. Cognition, fatigue, ULF, and LLF have stronger impact on costs and QoL in patients with higher EDSS scores. Additional determinants of MS disability status, including SDMT, MFIS-5, 9HPT, and T25FW, should be considered for assessing cost effectiveness of novel therapeutics for MS.
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Background: Multiple sclerosis (MS) comparative effectiveness research needs to go beyond average treatment effects (ATEs) and post-host subgroup analyses. Objective: This retrospective study assessed overall and patient-specific effects of dimethyl fumarate (DMF) versus teriflunomide (TERI) in patients with relapsing-remitting MS. Methods: A novel precision medicine (PM) scoring approach leverages advanced machine learning methods and adjusts for imbalances in baseline characteristics between patients receiving different treatments. Using the German NeuroTransData registry, we implemented and internally validated different scoring systems to distinguish patient-specific effects of DMF relative to TERI based on annualized relapse rates, time to first relapse, and time to confirmed disease progression. Results: Among 2791 patients, there was superior ATE of DMF versus TERI for the two relapse-related endpoints (p = 0.037 and 0.018). Low to moderate signals of treatment effect heterogeneity were detected according to individualized scores. A MS patient subgroup was identified for whom DMF was more effective than TERI (p = 0.013): older (45 versus 38 years), longer MS duration (110 versus 50 months), not newly diagnosed (74% versus 40%), and no prior glatiramer acetate usage (35% versus 5%). Conclusion: The implemented approach can disentangle prognostic differences from treatment effect heterogeneity and provide unbiased patient-specific profiling of comparative effectiveness based on real-world data.
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Background: Multiple sclerosis (MS) is a progressively debilitating neurologic disease that poses significant costs to the healthcare system and workforce. Objective: To evaluate the impact of MS disease progression on societal costs and quality of life (QoL) using data from the German NeuroTransData (NTD) MS registry. Methods: Cross-sectional cohort study. The cost cohort included patients with MS disability assessed using Expanded Disability Status Scale (EDSS) in 2019 while the QoL cohort included patients assessed using EDSS and EuroQol-5 Dimension 5-Levels between 2009 and 2019. Direct and indirect medical, and non-medical resource use was quantified and costs derived from public sources. Results: Within the QoL cohort (n = 9821), QoL worsened with increasing EDSS. Within the cost cohort (n = 7286), increasing resource use with increasing EDSS was observed. Societal costs per patient, excluding or including disease-modifying therapies, increased from 5694 or 19,315 at EDSS 0 to 3.5 to 25,419 or 36,499 at EDSS 4 to 6.5, and 52,883 or 58,576 at EDSS 7 to 9.5. In multivariate modeling, each 0.5-step increase in EDSS was significantly associated with increasing costs, and worsening QoL. Conclusion: This study confirms the major socioeconomic burden associated with MS disability progression. From a socioeconomic perspective, delaying disability progression may benefit patients and society.
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BACKGROUND: Primary progressive multiple sclerosis (PPMS) is characterised by gradual worsening of disability from symptom onset. Knowledge about the natural course of PPMS remains limited. METHODS: PPMS patients from the German NeuroTransData (NTD) MS registry with data from 56 outpatient practices were employed for retrospective cross-sectional and longitudinal analyses. The cross-sectional analysis included a contemporary PPMS cohort with a documented visit within the last 2 years before index date (1 Jan 2021). The longitudinal analysis included a disease modifying therapy (DMT)-naïve population and focused on the evolution of expanded disability status scale (EDSS) from the first available assessment at or after diagnosis within the NTD registry to index date. Outcome measures were estimated median time from first EDSS assessment to first 24-week confirmed EDSS ≥ 4 and ≥ 7. Besides EDSS change, the proportion of patients on disability pension were described over time. RESULTS: The cross-sectional analysis included 481 PPMS patients (59.9% female, mean [standard deviation, SD] age 60.5 [11.5] years, mean [SD] EDSS 4.9 [2.1]). Estimated median time from first EDSS assessment after diagnosis to reach 24-week confirmed EDSS ≥ 4 for DMT-naïve patients was 6.9 years. Median time to EDSS ≥ 7 was 9.7 years for 25% of the population. Over a decade mean (SD) EDSS scores increased from 4.6 (2.1) to 5.7 (2.0); the proportion of patients on disability pension increased from 18.9% to 33.3%. CONCLUSIONS: This study provides first insights into the German NTD real-world cohort of PPMS patients. Findings confirm the steadily deteriorating course of PPMS accompanied by increasingly limited quality of life.
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Multiple Sclerosis, Chronic Progressive , Multiple Sclerosis , Humans , Female , Middle Aged , Male , Retrospective Studies , Multiple Sclerosis, Chronic Progressive/epidemiology , Cross-Sectional Studies , Quality of Life , Disease Progression , RegistriesABSTRACT
Background: With increasing availability of disease-modifying therapies (DMTs), treatment decisions in relapsing-remitting multiple sclerosis (RRMS) have become complex. Data-driven algorithms based on real-world outcomes may help clinicians optimize control of disease activity in routine praxis. Objectives: We previously introduced the PHREND® (Predictive-Healthcare-with-Real-World-Evidence-for-Neurological-Disorders) algorithm based on data from 2018 and now follow up on its robustness and utility to predict freedom of relapse and 3-months confirmed disability progression (3mCDP) during 1.5 years of clinical practice. Methods: The impact of quarterly data updates on model robustness was investigated based on the model's C-index and credible intervals for coefficients. Model predictions were compared with results from randomized clinical trials (RCTs). Clinical relevance was evaluated by comparing outcomes of patients for whom model recommendations were followed with those choosing other treatments. Results: Model robustness improved with the addition of 1.5 years of data. Comparison with RCTs revealed differences <10% of the model-based predictions in almost all trials. Treatment with the highest-ranked (by PHREND®) or the first-or-second-highest ranked DMT led to significantly fewer relapses (p < 0.001 and p < 0.001, respectively) and 3mCDP events (p = 0.007 and p = 0.035, respectively) compared to non-recommended DMTs. Conclusion: These results further support usefulness of PHREND® in a shared treatment-decision process between physicians and patients.
