Establishing the Minimal Clinically Important Difference (MCID) for Smartphone-Derived Gait Measures in Multiple Sclerosis

The gist The study establishes robust and clinically meaningful MCIDs for smartphone-derived digital gait measures in progressive MS, providing a framework for interpreting remote monitoring data.

Background

Digital health technologies allow for frequent, remote gait monitoring in people with multiple sclerosis (MS) but established minimal clinically important differences (MCID) are required to differentiate daily variability from actual disease progression in longitudinal data <ref:2606.28449#pg2> Gait impairments are among the most prevalent and impactful manifestations of MS, affecting patients’ quality of life, functional independence, and overall well-being <ref:2606.28449#pg4> Advances in digital health technologies, particularly the use of smartphone-based inertial measurement units (IMUs), have enabled the collection of continuous and high-resolution gait data in both clinical and real-world settings <ref:2606.28449#pg6> Gait measures, such as total distance walked and spatiotemporal measures like step velocity, step duration, and step length derived from smartphone IMUs during remote walking tests offer a promising complement to traditional clinical assessments <ref:2606.28449#pg8> However, for these digital gait measures to be interpretable and actionable, it is critical to understand what constitutes a clinically meaningful change <ref:2606.28449#pg9> The minimal clinically important difference (MCID) is the most common approach, and it represents the smallest within-patient change in an outcome measure that is meaningful to patients, reflecting a tangible improvement or worsening in their daily lives <ref:2606.28449#pg10> Currently, there is limited published evidence on MCID values for digital gait measures, which limits their integration into medical research and clinical decision-making To address this gap, we estimated MCIDs for smartphone-based digital gait measures using an anchorbased method that included multiple clinician-administered and patient-reported outcomes The analyses were conducted in a prospective cohort of patients with progressive MS enrolled into the CONSONANCE (NCT03523858) study over 2 years Additionally, this work was supplemented with qualitative results to ensure these digital gait measures are meaningful and relevant to patients.

Methods

The researchers utilized a phase 3b study of ocrelizumab in progressive MS, CONSONANCE (NCT03523858), where participants underwent daily, unsupervised, smartphone-based Two-Minute Walk Test (2MWT) <ref:2606.28449#pg10> Digital gait measures derived from the 2MWT include those assessing the quality of gait and those assessing the quantity of gait. Multiple anchors were administered during study visits, including performance-based measures (Timed 25-Foot Walk [T25FW]), clinician-rated measures (EDSS and its Ambulation Score subcomponent), and patient-reported outcome measures (12-item Multiple Sclerosis Walking Scale [MSWS-12]) <ref:2606.28449#pg9> Additional anchors included patient-reported outcomes on lower-limb specific symptoms (Patient Impression of Severity for Lower Limbs [PSI [Lower Limbs]]), disease severity (Patient Global Impression of Severity [PGI-S]), and change in disease severity (Patient Global Impression of Change [PGI-C]). Longitudinal change was determined using median values aggregated over 4-week windows at baseline and Week 96 for digital gait measures For each anchor, patients were dichotomized into “worsened” or “stable” cohorts based on predefined 96-week change thresholds.

Digital Gait Measures and Correlations

Longitudinal Spearman rank-order correlations were in the expected direction, with worsening on the anchors associated with worsening in all digital gait measures Overall, change in patient-perceived walking impairment as measured by MSWS-12 demonstrated the strongest correlations with digital gait measures, followed by the T25FW For multiple digital gait measures, at least one correlation with ρ ≥ 0.3 was observed, with the highest absolute correlation between Step Velocity Scaled to Walking Time and MSWS-12 (ρ = -0.33).

MCID Estimates

Triangulation of the median changes from baseline obtained with the different anchors yielded the following MCIDs of MS disease progression The proposed MCID estimates for MS disease progression (Step Velocity: -0.16 m/s; Step Velocity Scaled to Walking Time: -0.18 m/s; Step Duration: 0.06 s; Step Length: -0.07 m; Total Number of Steps: -28; Total Distance Walked: -24 m) are consistent with prior research.

Clinical Relevance and Limitations

The proposed MCID estimates are robust and conservative estimates for four main reasons, including the anchor-based method used here is generally more accepted than distribution-based methods The CONSONANCE dataset was sufficiently large for deriving robust MCID estimates Furthermore, the study highlights that the digital measures are highly relevant to patients with MS, as patients reported symptoms directly related to gait performance and daily activities These MCIDs enable the identification of clinically meaningful progression of gait in clinical trials and serve as thresholds for time-to-event-based endpoints. However, limitations include sample size constraints and the need for further validation in larger, independent MS cohorts.

Conclusion

These MCIDs lay the groundwork for integrating digital gait measures into the evolving landscape of MS outcome measures, advancing personalized care and trial design. The following suggested MCID reference points for Step Velocity (-0.16 m/s), Step Velocity Scaled to Walking Time (-0.18 m/s), Step Duration (0.06 s), Step Length (-0.07 m), Total Number of Steps (-28), and Total Distance Walked (-24 m) provide a conservative yet reliable framework for interpreting gait progression in people with multiple sclerosis. These thresholds have important implications for clinical trials, enabling the evaluation of diseasemodifying therapies, and for real-world monitoring, offering objective insights into gait changes. The findings highlight the sensitivity and clinical relevance of digital gait measures while acknowledging the need for further validation in larger, independent MS populations.

Supplementary Information

The supplementary analyses included longitudinal correlations between digital gait measures and PSI [Lower Limbs], PGI-S, or PGI-C scales These results generally showed that worse performance on the 2MWT was associated with more severe or greater worsening in MS-related symptoms. The only instances of counterintuitive directionality were correlations between the change from Week 72 at Week 96 in digital gait measures and PGI-C, where correlations were non-significant and near zero. The median changes on digital gait measures in both worsening and stable groups were generally consistent with those used for deriving the MCID estimates. The study also provided qualitative insights, showing that patients reported symptoms directly related to gait performance and daily activities. The qualitative findings suggest that the digital measures are highly relevant to patients with MS. The final MCID estimates are Step Velocity = -0.16 m/s, Step Velocity Scaled to Walking Time = -0.18 m/s, Step Duration = 0.06 s, Step Length = -0.07 m, Total Number of Steps = -28, and Total Distance Walked = -24 m. The study was funded by F. Hoffmann-La Roche Ltd. The authors confirm that all intellectual content, data interpretation, and conclusions were generated by the authors.

1. Bold header: Establish objective disease progression endpoints for clinical trials

This improved AI system can identify clinically meaningful worsening by using anchor-based methods to triangulate digital gait measures, as described in the text: Triangulated MCIDs are: Step Velocity = -0.16 m/s, Step Velocity Scaled to Walking Time = -0.18 m/s, Step Duration = 0.06 s, Step Length = -0.07 m, Total Number of Steps = -28, and Total Distance Walked = -24 m.

2. Bold header: Develop remote monitoring frameworks for personalized patient care

The system can provide objective, real-world monitoring to advance personalized patient care by using the derived MCIDs as a framework for interpreting data from smartphone-based tests, enabling longitudinal assessments of the patient’s daily functioning of gait as opposed to the evaluation of gait in a supervised, clinical setting.

3. Bold header: Enhance predictive modeling for disease progression

The AI can utilize longitudinal correlations to predict future outcomes by analyzing how digital measures relate to various anchors; for example, it can identify that Overall, change in patient-perceived walking impairment as measured by MSWS-12 demonstrated the strongest correlations with digital gait measures.

4. Bold header: Improve sensitivity in identifying subclinical disease changes

The system can better distinguish meaningful progression from noise by employing a conservative approach where the median changes on the digital gait measures in the worsening group correspond to the 50th percentile of the Empirical Cumulative Distribution Function (ECDF) of the respective anchor.

5. Bold header: Integrate qualitative patient relevance into quantitative metrics

The system can contextualize digital data by incorporating patient-reported insights, such as those found in concept elicitation interviews, which highlighted that walking and completing their every-day routines were identified as daily activities impacted by the same MS symptoms that affect their 2MWT performance.

Background: Digital health technologies allow for frequent, remote gait monitoring in people with multiple sclerosis (MS). However, to differentiate daily variability from actual disease progression in longitudinal data, established minimal clinically important differences (MCID) are required. Currently, there is limited literature defining these thresholds for digital gait metrics. Objective: To establish MCIDs for digital gait measures reflecting progression in MS. Methods: Digital gait measures were captured via daily, remote, smartphone-based Two-Minute Walk Tests in CONSONANCE (NCT03523858), a phase 3b study of ocrelizumab in progressive MS. Using an anchor-based approach, median changes from baseline at Week 96 on digital gait measures were computed for patients showing clinically meaningful worsening on either Timed 25-Foot Walk, Ambulation Score, Expanded Disability Status Scale, or 12-item Multiple Sclerosis Walking Scale. These changes were subsequently triangulated to derive the MCID estimates. Results: 243 patients with progressive MS (female: n=125 (51%); mean [SD] age: 49.3 [9.3]; mean [SD] EDSS: 4.8 [1.4]) had digital gait data available at baseline and Week 96. Median changes were generally consistent across anchors. Triangulated MCIDs are: Step Velocity = -0.16 m/s, Step Velocity Scaled to Walking Time = -0.18 m/s, Step Duration = 0.06 s, Step Length = -0.07 m, Total Number of Steps = -28, and Total Distance Walked = -24 m. Conclusion: These MCIDs provide a framework for interpreting meaningful gait changes and integrating digital measures into MS outcome evaluation. Beyond facilitating novel clinical trial endpoints to evaluate treatment efficacy, they enable objective, real-world monitoring to advance personalized patient care.