The Relationship Between Disability and Walking Speed in Adults with Multiple Sclerosis

Abstract

Introduction: Timed Twenty-Five Foot Walk (T25FW) and Patient-Determined Disease Steps (PDDSs) are measures commonly used for people with MS (PwMS). However, there is limited knowledge about the utility of using the measures to customize interventions. Aim: This exploratory study aimed to assess the correlation between T25FW and PDDS among PwMS enrolled in the Tele-Exercise and Multiple Sclerosis (TEAMS) study. Methods: The correlation was examined through a Spearman’s rho statistic for T25FW time and PDDS scores. Associations between TEAMS Intervention levels (T25FW baseline benchmarks: <6 s, 6–7.99 s, >8 s, unable to complete) and the PDDS-modified ranges (0–2, 3–4, 5–6, 7) were examined utilizing a chi-square test with Monte Carlo simulations. Results: The results showed a strong statistically significant positive correlation between the T25FW time and the PDDS scores (r_s = 0.72, p < 0.001). An additional Spearman’s correlation showed strong significant positive correlation between T25FW baseline benchmarks and PDDS-modified ranges used for intervention assignment (r_s = 0.73, p < 0.001). A chi-square with Monte Carlo simulations showed a significant association between the TEAMS Intervention Level and PDDS-modified ranges (p = 0.005). Conclusion: In conclusions, the findings suggest that T25FW, when considered with PDDSs, might offer some utility in supporting clinicians as they develop intervention strategies that consider both subjective and objective aspects. These findings also highlight the potential for integrated use of both tools in clinical decision-making, program design, and tailoring interventions to meet individual functional capabilities and self-reported disability in PwMS.

1. Introduction

An estimated 2.8 million adults in the world are living with multiple sclerosis (MS) [1]. This autoimmune disease is characterized by demyelination in the central nervous system, resulting in a diverse range of symptoms that often lead people with MS (PwMS) to seek therapy services. Common symptoms such as fatigue, cognitive impairment, pain, and postural instability are addressed through neurorehabilitation to mitigate the progression of this chronic disease. Effective therapy interventions are essential for improving mobility, endurance, balance, pain management, and independence in activities of daily living (ADLs). To achieve these therapeutic benefits, the use of robust and precise measures is crucial for identifying and assigning appropriate, tailored interventions that meet individual needs and improve overall quality of life in PwMS.

Patient-reported outcomes (PROs) and performance-based measures are increasingly recognized as essential tools in the management of MS, providing valuable insights that can complement traditional clinical assessments. By capturing the perspectives of a participant’s functional status in combination with assessing their abilities, a therapist can identify the impact of MS symptoms on quality of life and activities of daily living. PROs and performance-based measures can empower participants to actively participate in healthcare decisions by ensuring that the intervention algins with a participants ability level.

The Timed Twenty-Five Foot Walk (T25FW) is widely recognized as a clinically relevant performance-based measure used by most clinicians to evaluate mobility in PwMS [2]. Developed as part of the MS Functional Composite, the T25FW primarily focuses on assessing gait speed [2]. It requires an individual to walk 25 feet as quickly and safely as possible, taking the average of two trials. This objective measure provides insight into the physical function and disease progression in PwMS. While this quantitative measure provides valuable assessment of a patient’s mobility, it captures only one aspect of functional ability and thus does not fully account for other important factors such as balance, endurance, and the use of assistive devices. The participant’s perception of fatigue, pain, or fear of falling, all factors that may impact functional mobility, are not captured by this measure. While the T25FW is a valuable tool, it is best used in conjunction with other measures to provide a more comprehensive assessment of the participant.

Increasingly, the Patient-Determined Disease Steps (PDDSs), a subjective evaluation of disease severity and function, has been recognized as a crucial measure to collect for understanding the real-world impact of mobility limitations [3]. The PDDSs provide unique insights into how participants experience disease progression and its impact on daily functioning, complementing objective performance-based measures. The self-assessment offers valuable insight into the invisible symptoms such as pain and fatigue that may not be fully captured by an objective measure. Incorporating additional information from the patient’s perspective may lead to a more reliable and comprehensive evaluation of functional status [4,5,6]. A holistic assessment approach could enhance the ability to tailor interventions, ensuring that they address the full scope of the individual’s functional needs.

In a pragmatic randomized control trial, Tele Exercise and Multiple Sclerosis (TEAMS), participants were assigned to personalized intervention programs based on their scores from the T25FW and the Patient Determined Disease Steps (PDDSs). The complementary alternative medicine (CAM) intervention consisted of yoga, Pilates, and dual-tasking exercises delivered either at the therapy clinic (DirectCAM) or through preloaded videos on a tablet (TeleCAM). The intervention consisted of 20 sessions delivered over 12 weeks, two times per week for 8 weeks and one time per week for 4 weeks. PwMS did yoga, Pilates, and dual-tasking for 8 weeks and then did only yoga and Pilates for the final 4 weeks. The yoga and Pilates exercises primarily focused on flexibility, strength, balance, and coordination. The dual tasking portion of the intervention involved motor-motor and cognitive-motor tasks. Within each TEAMS exercise level based on the PDDS and T25FW scores, the participants were allowed to select a version of lower or higher difficulty to either modify or challenge the exercise. The participants were given equipment based on their TEAMS level and arm assignment.

Instead of utilizing the typical PDDS categories of mild (0–2), moderate (3–5) and severe (6–8) [7], the intervention content was tailored based on modified PDDS ranges (PDDS 0–2, PDDS 3–4, PDDS 5–6, PDDS 7), allowing the programs to be adapted to each participant’s perceived ability level. The T25FW was used during baseline testing, and established benchmarks (<6 s, 6–7.99 s, >8 s, unable to complete) [8] from this test were critical in determining the appropriate intervention level for each participant. Within each TEAMS exercise level based on the PDDS score and the T25FW time, the participants were allowed to select a version of lower or higher difficulty to either modify or challenge the exercise. The participants were give equipment based on their TEAMS level and arm assignment. The rationale for using both PDDS and T25FW was to integrate subjective perceptions of participants’ functional abilities with objective, performance-based data, ensuring a more comprehensive and accurate assignment to intervention groups.

For purposes of this exploratory analysis, which used data from the TEAMS study, we analyzed the correlation between the PDDS score and the T25FW time on continuous scale to determine if both data points collected led to an appropriate placement of participants into the interventions designed in the study. We hypothesized that the T25FW baseline benchmarks established for each intervention level would be correlated with the PDDS-modified ranges utilized in the creation of the intervention levels, leading to the appropriate intervention assignment for PwMS in the TEAMS study. The analysis aimed to evaluate whether the combination of an objective performance-based measure (T25FW) and a subjective self-reported measure (PDDS) would provide a more comprehensive framework for individualized intervention assignment. In addition, we wanted to assess the potential of these measures to be jointly applied for future clinical and telehealth settings to enhance the precision for tailored intervention for PwMS.

2. Methods

2.1. Study Design

Data from participants enrolled in the TEAMS study between November 2016 and November 2021 were utilized for this exploratory analysis. The TEAMS study was a cluster-randomized controlled trial across 43 outpatient clinics in Alabama, Mississippi, and Tennessee. Participants were assessed at these clinics by occupational and physical therapists and data was collected at baseline, 3, 6, and 12 months. The participants were randomized to either the DirectCAM arm (intervention delivered either at the therapy clinic) or the TeleCAM arm (videos preloaded on a tablet).

Four levels of the intervention were developed based on the PDDS-modified ranges 0–2 (TEAMS Intervention Level 1), PDDS 3–4 (TEAMS Intervention Level 2), PDDS 5–6 (TEAMS Intervention Level 3), and PDDS 7 (TEAMS Intervention Level 4). After the TEAMS stakeholder panel and data safety monitoring board reviewed the intervention, study investigators added another version of Level 3 and 4 for participants with osteoporosis (TEAMS Intervention Level 3-OP and TEAMS Intervention Level 4-OP). Utilizing the modified PDDS ranges instead of the standard PDDS categories allowed for more individualized intervention options than the broader, standard categories by tailoring the intervention to the specific ability levels observed within each modified range.

Scores from the T25FW were used as an extra objective measure at baseline testing to place participants in the appropriate TEAMS intervention. These baseline benchmarks were derived from expert opinion and a study conducted by Goldman et al. (2013), which identified “performance benchmarks” in PwMS [8]. Participants were assigned to an intervention based on their T25FW baseline benchmarks in the following manner: TEAMS Intervention Level 1 (<6 s); TEAMS Intervention Level 2 (6–7.99 s); TEAMS Intervention Level 3 (>8 s); and TEAMS Intervention Level 4 (unable to complete the T25FW). If a participant self-reported a diagnosis of osteoporosis and was able to complete the T25FW they were assigned to TEAMS Intervention Level 3-OP. Those diagnosed with osteoporosis who could not complete the T25FW were assigned to TEAMS Intervention Level 4-OP.

Table 1. TEAMS intervention levels based on T25FW times.

TEAMS Intervention Level	T25FW Score
1	<6 s
2	6–7.99 s
3	>8 s
4	Unable to complete
3-OP	Able to complete
4-OP	Unable to complete

provides an overview of the different intervention levels.

2.2. Participants

The TEAMS study enrolled 759 PwMS across the 43 outpatient clinics. Participant inclusion criteria for the study were as follows: (1) received permission from their physician to participate in the study; (2) mild to moderate disability (i.e., able to ambulate with/without assistive device (PDDS 0–7); (3) able to use arms and/or legs for exercise; and (4) aged 18 to 70 years. Participant exclusion criteria were as follows: (1) significant visual acuity deficits that prevented seeing a tablet screen to follow the intervention exercises; (2) cardiovascular event, severe pulmonary disease, or renal failure within the past 6 months; (3) active pressure ulcer; (4) currently pregnant; or (5) within 30 days of receiving an exercise or rehabilitation program led by an occupational or physical therapist. Written informed consent was obtained from each participant prior to data collection.

2.3. Data Collection

The study was approved by the Institutional Review Board of the University of Alabama at Birmingham and was conducted in accordance with a clinical trial protocol registered at ClinicalTrials.gov (NCT03117881). Occupational and physical therapists were trained to administer the outcome measures and given scripts for each test. Therapists gathered functional outcome measures and PDDS scores at the clinic at baseline, 3 month, 6 month, and 12 month testing visits. Data was collected via paper forms and transferred to the study Research Electronic Data Capture (REDCap) database [9]. These data points were exported from REDCap and analyzed for this study.

T25FW was administered by asking the participant to walk a clearly marked 25-foot path as quickly and safely as possible [2]. The participant started from a standing position, using an assistive device if needed, and the timing began as soon as the participant took the first step. The timing stopped when the last foot crossed the 25-foot finish line and the average of the two trials was recorded.

Disease modifying therapies (DMTs), other symptom management medications, and types of MS were collected at each assessment visit to provide a clinical profile of each of the participants. However, this data was not included in the current analysis of the correlation between the T25FW and PDDS. The decision not to include this data was based on the study’s primary aim to evaluate the correlation and association of the two measures independently of the impact of DMTs or type of MS. Exclusion of these details allowed for a focused analysis of the alignment between the PDDSs and T25FW without the confounding effects of varied treatment regimens and MS type.

2.4. Data Analysis

This exploratory analysis was conducted using SAS version 9.4 [10]. Strength and direction of the correlation between the T25FW and PDDSs were assessed using Spearman’s correlation coefficient (r_s). Correlation strength was categorized as follows: very strong (0.90–1.00), strong (0.70–0.89), moderate (0.50–0.69), weak (0.30–0.49), and negligible (<0.30) [9]. Statistical significance was set at p < 0.05. An additional analysis was performed to examine the association between TEAMS Intervention levels, categorized based baseline T25FW benchmarks and modified PDDS ranges using a chi-square test. To address zero cell counts, p-values were calculated using the Monte Carlo simulation [11].

3. Results

The study sample (n = 756) had an average age of 50.1 ± 10.7 years old. The majority were female, comprising 89.0% (n = 673) of the participants. In terms of racial distribution, 72.5% (n = 548) identified as White, 23.8% (n = 180) as African American, and 3.7% (n = 28) identified as other races. For residence, the majority of participant lived in urban communities (n = 633, 87.3%) compared with 133 participants (16.3%) residing in non-urban areas, as shown in

Table 2. Demographic characteristics.

Demographic Characteristics (n = 756)	n (%)
Age (mean, SD)	50.1 ± 10.7
Gender
Female	673 (89.0)
Male	83 (11.0)
Race
White	548 (72.5)
Black	180 (23.8)
Other *	28 (3.7)
Residence
Urban (RUCA 1–3)	623 (83.7)
Non-urban (RUCA (4))	133 (16.3)

* Other includes American Indian, Pacific Islander, Latino, and multiracial. RUCA: Rural-Urban Commuting Area Codes.

.

A strong positive correlation was observed between the T25FW and the PDDSs at baseline (r_s = 0.72, p < 0.001) as shown in Figure 1. The PDDS scores 0–2 are clustered near the bottom of the y-axis indicating shorter walking times which suggests that participants with mild disability tend to have faster gait speed. For the PDDS scores 3–5, there is a broader distribution of T25FW times, indicating increased variability in walking performance with moderate disability in the TEAMS participants. As the PDDS scores increase so do the T25FW times, showing slower walking performance. In the severe PDDS categories 6–7, the T25FW scores tend to be much higher with a few exceeding 200 s, indicating significant limitations in mobility.

An additional Spearman’s rho found a strong positive correlation between the T25FW baseline benchmarks and the PDDS-modified ranges established for TEAMS intervention level assignment (r_s = 0.73, p < 0.001). Specifically, a Spearman’s correlation coefficient (r_s = 0.73) suggests a robust association between these two variables that is statistically significant (p < 0.001). This finding supports internal consistency between subjective and objective assessments of disability.

A chi-square test examined the association between TEAMS Intervention levels and the PDDS categories. The Monte Carlo simulation yielded a significant result (p = 0.005). These findings are depicted in

Table 3. Association between TEAMS Intervention Level (T25FW times) and PDDS scores.

TEAMS Intervention Levels (T25FW Benchmarks) **	PDDS (0–2)	PDDS (3–4)	PDDS (5–6)	PDDS (7)	Chi Square Test with Monte-Carlo Simulation
1 (>6 s)	257 (78.8%)	68 (20.9%)	0 (0.0%)	0 (0%)	0.0005 *
2 (6–7.99 s)	88 (47.8%)	83 (45.1%)	13 (7.1%)	0 (0%)
3 (>8 s)	22 (10.5%)	78 (37.3%)	95 (45.5%)	14 (6.7%)
4 (unable)	0 (0%)	1 (3.3%)	7 (23.3%)	22 (73.3%)

* Statistically significant = p-value ≤ 0.05. ** TEAMS Intervention Level 1 = T25FWT < 6 s; TEAMS Intervention Level 2 = T25FWT 6–7.99 s; TEAMS Intervention Level 3 = T25FWT > 8 s; TEAMS Intervention Level 4 = unable to complete T25FWT.

. For Intervention Level 1, most participants (n = 257, 78.8%) are in the PDDS 0–2 category, suggesting those with minimal disabilities perform well on the T25FW. No participants were assigned to Intervention Level 1 that were PDDSs 5–7. In TEAMS Intervention Level 2, nearly half of the participants (47.8%) are still in the PDDS 0–2 group, but there is a similar percentage in the PDDS 3–4 range (45.1%). A few (7.1%) fall into PDDSs 5–6 and there are no participants in the PDDS 7 category. The highest disability group with 73.3% in TEAMS Intervention Level 4 with a PDDS score of 7, indicates the inability to complete the T25FW is strongly associated with the most severe disability score.

4. Discussion

In this study, we found a strong correlation between performance on the T25FW and the PDDS scale among PwMS. This correlation, observed at baseline, suggests that gait speed is linked to participants’ perception of how MS affects their daily living. The scatter plot indicates a general trend where higher PDDS scores correlate with longer T25FW completion time. This is expected, as increased physical disability often results in reduced mobility. Our correlation is only slightly stronger than the value of 0.67 reported in a PDDS validation study [12]. In another validity study conducted by Bethoux et al. (2016), the researchers examined the MS Functional Composite scale and observed a strong positive correlation between the EDSS and T25FW scores (r_s = 0.69, p < 0.001) [2]. Our study findings align with their results. Other studies have shown that the T25FW is also correlated with the MS Walking Scale-12, another self-reported measure (r_s = 0.44, p < 0.001) [3] as well as other performance-based tests such as the 6-Minute Walk Test (r_s = −0.83, p < 0.001) [13].

All collected data points were included in the scatterplot to preserve the completeness of the dataset. As a result, a few data points on the scatterplot are far from the trend which may be explained by data entry errors, inconsistent understanding of the questions on the PDDSs, or atypical disease presentation. Despite these outliers, the regression line demonstrated a positive association. The slope of the line suggested that for each 1-point increase in the PDDS score, the T25FW time increased by approximately 2–2.5 s, and the intercept was estimated around 4 s. While the inclusion for all data led to some dispersion among data points, the overall trend supported a strong linear relationship between the objective and subjective measures. The observed dispersion reflects the natural variability in human performance or perception and inclusion of all of the data strengthens the validity of our findings.

The T25FW baseline benchmarks used to determined intervention level assignment were also strongly correlated with the PDDS-modified ranges, resulting in the placement of participants in the TEAMS study into tailored interventions. The strong relationship found in this study supports the use of T25FW baseline benchmarks PDDS for development and delivery of a tailored intervention. This information could be useful for future intervention design. Our study findings were consistent with another study that demonstrated a significant positive correlation between T25FW baseline benchmarks (<6 s, 6–7.99, >8 s) and three subgroups of EDSS scores (2.3, 3.5, 5.0) [14].

The final outcome revealed a significant association between walking ability as measured by the T25FW, grouped into TEAMS intervention levels, and the level of physical disability (PDDS). This data shows a clear trend—as PDDS scores increase, gait speed decreases. Those in TEAMS Intervention Level 1 (fast walkers) tend to have lower PDDS scores, indicating mild disability, while those in TEAMS Level 3 or 4 (slow walkers or unable to complete the test) tend to have higher PDDS scores, indicating moderate to severe disability. The clear trend described here of decreasing gait speed with increasing PDDS scores allows clinicians to track both outcomes to better gauge the rate of functional decline in patients to identify when to adjust therapies or introduce adaptive devices. Further research is needed to track how PDDS scores and T25FW scores evolve over time in order to learn if PDDS can predict mobility outcomes.

Initially, the research team piloted using the PDDS alone for intervention assignment. However, it was discovered that perceived disability in PwMS can be complicated by the variability of symptoms at any one point in time. Following a review of the literature and further discussion, the T25FW was incorporated to provide objective, performance-based data to complement the PDDSs. This dual-measure approach was intended to enhance the accuracy of intervention level assignments by the study therapists.

As a result, a higher percentage of participants were appropriately assigned to intervention level 1 (mild disease) and intervention level 4 (severe disease) aligning with the PDDS-modified ranges and corresponding T25FW benchmarks. Greater variability was observed between intervention level assignments 2 and 3. This inconsistency could be attributed to fluctuating symptoms, use of adaptive devices for ambulation, and ambiguity in interpreting PDDS scores between 1 and 3, which tend to be less focused on ambulation and more subjective in nature. This finding is particularly relevant for therapists when evaluating the difference between a participant’s perceived ability and their actual functional performance. This approach could be valuable in other commonly used assessments for individuals with MS, such as pairing the Fatigue Severity Scale with the Six Minute Walk Test or the Subjective Visual Vertical Test with the Dizziness Handicap Inventory. Utilizing both subjective and objective data may enhance accuracy in assessments, inform intervention strategies and improve post assessment evaluations.

The results of this study are not without limitations. The sample was predominantly white females which is characteristic of MS; however, the findings may not translate to other races and genders. While the large overall sample size (n = 756) is a strength, the sample for the PDDS severe category (6–7) was relatively small compared to the other groups. Additionally, the majority of participants resided in an urban community which may limit translation of results for those living within non-urban communities due to differences in healthcare access, availability of rehabilitation services, assistive technology, and environmental factors that can influence mobility and disease management.

Both the T25FW and the PDDS measures have inherent limitations. The T25FW primarily measures gait speed, failing to capture other nuances of MS such as fatigue, pain, and cognition that may also influence functional mobility, ADL independence, and quality of life. The subjective nature of the PDDS scale introduces potential biases, including mood-dependent reporting, reliance on participant insight, perception biases, and symptom variability, which may affect the objectivity of the results.

5. Conclusions

The significant correlation found in this study between the T25FW and PDDS demonstrates the alignment between patient-perceived disease progression and objectively measured gait speed. The findings support the use of both subjective (PDDSs) and objective (T25FW) assessments to measure physical disability, showing that as the PDDS score increases, gait speed decreases. While many MS specialists advocate for the routine use of the T25FW as a performance-based measure for PwMS, it is essential to also consider incorporating subjective assessments, like the PDDSs.

The dual-measure approach used to assign TEAMS participants to an intervention level resulted in alignment with functional abilities, particular in the mild and severe ends of the disease. The variability in levels 2 and 3 underscore the influence of “invisible” symptoms of MS on gait speed and highlights the interpretation challenges in self-reported outcome measures.

Clinically, utilizing both measures allows for a more comprehensive evaluation of functional performance, providing both subjective and objective insights that can inform tailored interventions for PwMS. Despite limitations related to the sample demographics and the outcome measures, the study underscores the value of combining a subjective and objective measures in MS rehabilitation and research. Further longitudinal studies should be conducted to assess the correlation of these tools over time.