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Self-reported severity among patients with multiple sclerosis in the U.S. and its association with health outcomes
Multiple Sclerosis and Related Disorders, 1, 3, pages 78 - 88
Individuals with multiple sclerosis (MS) experience diminished health outcomes. However, little is known about how these outcomes differ according to disease severity. The aim of this study is to compare health-related quality of life (HRQoL), work productivity, activity impairment, and resource use between MS patients and controls, as well as across MS patients with varying self-reported disease severity.
Data were analyzed from respondents reporting an MS diagnosis (n=536) and controls (n=74,451) in the U.S. 2009 National Health and Wellness Survey (administered online to a nationally representative adult population). Differences were assessed between those with and without MS, and across three MS severity groups: mild (38.4%), moderate (50%), and severe (11.6%).
MS patients vs. controls experienced significantly more activity impairment, decreased work productivity, increased healthcare utilization, and lower HRQoL (allp<0.001). Increasing MS severity was associated with greater activity impairment, lower work productivity, increased healthcare utilization, and lower HRQoL. More significant impairments emerged between individuals who perceived their disease severity as mild vs. moderate than moderate vs. severe.
MS patients reported greater impairment than controls, and impairment increased with disease severity (especially from mild to moderate). These findings show that increasing MS disease severity is associated with worse health outcomes.
- MS can impair quality of life and work productivity and increase resource use.
- Increasing perceived severity of MS can contribute to these impairments.
- Yet, the mild-to-moderate-to-severe transition may be nonlinear.
- Greater health outcomes impairments may occur with mild-to-moderate shifts in disability.
- Findings show increasing disease severity is associated with worse health outcomes.
Abbreviations: BMI - Body Mass Index, CCI - Charlson Comorbidity Index, DMD - Disease Modifying Drug, EDSS - Expanded Disability Status Scale, ER - Emergency Room, NHWS - National Health and Wellness Survey, HRQoL - Health-Related Quality of Life, MCS - Mental Component Summary, MS - Multiple Sclerosis, PCS - Physical Component Summary, PROs - Patient-Reported Outcomes, SF-6D - Short Form 6D, SF-12v2 - The Medical Outcomes Study 12-Item Short Form Survey Instrument, U.S. - United States, WPAI - Work Productivity and Activity Impairment Questionnaire.
Keywords: Multiple sclerosis, Disease severity, Work productivity, Resource use, Quality of life, Self-report.
Multiple Sclerosis (MS), an inflammatory disorder of the central nervous system ( Brook et al., 2009 ), is a leading contributor to non-traumatic neurological disability ( Lad et al., 2010 ), affecting approximately 350,000 to 450,000 individuals in the U.S. today ( Brook et al., 2009 ). Weakness, excessive fatigue, impaired walking, ataxia, bladder complications, bowel disturbances, sensory loss, depression and cognitive and visual declines are typical symptoms of MS (Da Silva et al, 2011, Ivanova et al, 2009, and Miletić et al, 2011; Stüve and Oksenberg 2006 ). These symptoms are all potential contributors to lower health-related quality of life (HRQoL), impaired work productivity, and increased healthcare use.
Several studies have investigated the association between MS and resource utilization (Ivanova et al, 2009, Pope et al, 2002, and Prescott et al, 2007), work productivity ( Ivanova et al., 2009 ), and HRQoL (Ivanova et al, 2009 and Pittock et al, 2004). Few studies have examined differences in outcomes among MS patients with varying disease severity, especially with respect to a broad range of outcomes (HRQoL, work impairment, healthcare utilization) in a U.S. population-based sample. Kobelt et al. (2006) reported that healthcare resource utilization and work productivity losses were significantly correlated with functional status, as assessed by Expanded Disability Status Scale (EDSS) scores, with greater impairment in functioning being associated with increases in resource utilization and productivity losses. However, this study only examined patients with MS who were currently treated with disease-modifying drugs (DMDs). Hviid et al. (2011) discovered that patients with benign (disease duration ≥15 years and EDSS score ≤3.0) MS, had better scores on measures relating to HRQoL, fatigue, depression, and social support, relative to patients with greater disease severity. Naci et al. (2010) reported on fifteen European based studies that demonstrated that as MS disease severity progressed based on EDSS scores costs of MS increased significantly.
The current study compares outcomes between MS patients and controls. The potential impact of varying degrees of patient-reported disease severity (mild, moderate, severe) of MS patients on HRQoL and other patient-reported health outcomes was also assessed, by using a nationally representative U.S. population that includes treated and untreated patients, as well as those with and without health insurance and who are both employed and unemployed. The outcomes of interest included HRQoL, work productivity and activity impairment, and healthcare resource utilization.
2. Material and methods
2.1. Data source
The study examined cross-sectional data from the 2009 U.S. National Health and Wellness Survey (NHWS), an online, self-administered survey that assesses healthcare attitudes and behaviors of a nationally representative sample of 75,000 adults. All data were based upon self-report. Recruiting took place through an existing Internet panel (Lightspeed Research). The NHWS also covers information on demographics, disease status, and outcomes. A stratified random sampling procedure was used to ensure participants were demographically comparable to the overall US population, as reported by the U.S. Census. The Essex Institutional Review Board, Inc. (Lebanon, NJ) approved the NHWS protocol. Respondents gave their informed consent before completing the survey. Representation of NHWS data has been validated and weighted against reliable sources including government agencies' health statistics and unaffiliated third parties (Bolge et al, 2009, DiBonaventura et al, 2011, and Finkelstein et al, 2011).
2.2. Study sample
Participants reporting an MS diagnosis were compared with those without an MS diagnosis. Of the diagnosed MS respondents, severity was captured with the following question: “How severe is your MS?” with possible answers of “mild,” “moderate,” and “severe.” Other disease characteristics included the number of years diagnosed with MS, current medication use, and a count of the following symptoms: breathing problems, constipation, depression, diarrhea, difficulty balancing, difficulty concentrating, difficulty remembering, difficulty with speech, dizziness, fatigue, hearing loss, irritability, mood swings, muscle spasms, numbness, pain, seizures, sexual dysfunction, stiffness, swallowing problems, tremors, urinary incontinence and vision problems.
2.3. Study measures
The following measures were collected: age, gender, race/ethnicity, education level, income, employment status, and health insurance status (see Table 1 ).
|Control N = 74451||All MS N = 536||MS vs. Control|
|HS graduate (e.g., GED) or less||16,665||22.4%||120||22.4%||0.998|
|More than high school||57,785||77.6%||416||77.6%||0.999|
|Less than $25,000||13,667||18.4%||138||25.8%||< 0.001|
|$25,000 to $49,999||22,287||29.9%||155||28.9%||0.608|
|$50,000 to $74,999||15,946||21.4%||106||19.8%||0.356|
|$75,000 and over||18,078||24.3%||103||19.2%||0.006|
|Decline to answer||4473||6.0%||34||6.3%||0.745|
|Full time||27,298||36.7%||112||20.9%||< 0.001|
|Health insurance type|
2.3.2. Health Status
Health status variables included exercise status, current smoking, alcohol use, Body Mass Index (BMI), the adjusted Charlson Comorbidity Index (CCI) ( Charlson et al., 1987 ), and depression, as indicated by the Whooley depression screener ( Whooley et al., 1997 ), a diagnosis of depression, and current use of a prescription medication for depression. The CCI is a validated method for classifying comorbid conditions that may affect the risk of mortality; conditions are assigned varying weights depending on their contribution to mortality risk and are summed (total index scores range from 0 to 32). A higher score signifies greater comorbid burden on the respondent ( Charlson et al., 1987 ). The Whooley depression screener consists of two questions (“During the past month, have you often been bothered by feeling down, depressed, or hopeless?” and “During the past month, have you often been bothered by having little interest or pleasure in doing things?”). Answering yes to at least one question indicates the likelihood of depression.
2.3.3. Outcomes of interest
126.96.36.199. Work productivity
The Work Productivity and Activity Impairment (WPAI) ( Reilly et al., 1993 ) questionnaire is a validated tool that measures lost work productivity and impairment in daily activities over the past seven days. Four component scores are generated in the form of percentages (higher values indicate greater impairment). The three components related to work productivity (absenteeism, presenteeism, and overall work impairment due to health) were calculated only for employed respondents. Work hours missed due to absenteeism and work hours missed due to impairment while working were also reported for employed respondents. The fourth component (impairment during daily activities) was calculated for the entire sample.
The physical (PCS) and mental (MCS) component summary scores derived from the Short Form (SF)-12v2 ( Ware et al., 2002 ) were used to measure HRQoL. Scores for the PCS and MCS are normalized to the U.S. population (mean=50, SD=10) and range from 0 to 100. Higher scores signify greater quality of life. The SF-6D health state utilities measure, which is derived from seven items on the SF-12v2, was also included in the analyses. A health utility score is a preference-based, single index measure based upon general population values, ranging from 0 (equal to death) to 1 (perfect health) (Brazier et al, 2002 and Brazier and Roberts, 2004).
188.8.131.52. Healthcare utilization
This was measured using the following self-report measures: visiting (within the past six months) at least one traditional healthcare provider, such as a neurologist, from a list of 26 options; visiting at least one nontraditional healthcare provider from a list of 10 options, such as a chiropractor; visiting the emergency room (ER) or being hospitalized at least once within the past six months; and current use of a prescription medication. Responses were reported as percentages of respondents who answered “yes.”
2.4. Statistical analyses
Bivariate analyses were used to compare demographic, health status, and unadjusted outcome differences for HRQoL, work productivity, healthcare resource use between MS respondents and controls, as well as between individuals with self-reported mild, moderate, and severe MS. Chi-square tests were utilized for categorical variables, and independent samplest-tests were used with continuous variables. Statistical significance was set atp<0.05. No adjustments for multiple comparisons were made.
3.1. Sample description
Of the 75,000 respondents from the U.S. NHWS, 536 (0.71%) reported an MS diagnosis, while 74,451 (99.3%) did not report an MS diagnosis. Thirteen respondents indicated that they “experienced MS” but did not report having a physician diagnosis; these respondents were excluded from the study. Among those with MS, 206 (38.4%) characterized their disease severity as mild, 268 (50.0%) as moderate, and 62 (11.6%) as severe. Mild patients reported experiencing a mean MS symptom count of 6.1 and moderate and severe patients reported counts of 9.2 (vs. mild;p<0.001) and 9.0 (vs. mild;p<0.001), respectively. No significant differences were found in mean years diagnosed with MS (mild=12.1 years vs. moderate=13.2 vs. severe=12.3). The number of patients treated with a prescription medication for their MS varied significantly for the mild vs. moderate and severe groups (mild=58.3% vs. moderate=77.6% and severe=74.2%,p<0.020). No significant difference was found between moderate and severe patients on MS prescription use.
3.2. Bivariate comparisons of MS respondents vs. controls
Significantly fewer MS respondents, when compared with controls, were male (34.9% vs. 48.7%, respectively,p<0.001), employed full-time (20.9% vs. 36.7%,p<0.001), uninsured (9.9% vs. 17.7%,p<0.001), or made $75,000 or more per year (19.2% vs. 24.3%,p=0.006). Significantly more MS respondents made less than $25,000 per year when compared with controls (25.8% vs. 18.4%,p<0.001). There were no significant differences between MS respondents and controls on education or age ( Table 1 ).
3.2.2. Health status
A greater proportion of MS respondents vs. controls had a Whooley depression screener score ≥1 (49.1% vs. 36.3%, respectively,p<0.001), were diagnosed with depression (36.0% vs. 18.0%,p<0.001), and used a prescription for depression (27.8% vs. 11.9%,p<0.001). CCI scores were significantly higher among MS respondents than controls (0.90 vs. 0.49,p<0.001). More MS respondents vs. controls were underweight (3.4% vs. 1.8%,p=0.005), but fewer consumed alcohol (60.3% vs. 65.0%,p=0.023) and exercised (53.2% vs. 63.3%,p<0.001). More MS respondents vs. controls reported being current smokers (32.6% vs. 22.6%,p<0.001) ( Table 2 ).
|Control N = 74,451||All MS N = 536||MS vs. Control|
|Current smoker||16,844||22.6%||175||32.6%||< 0.001|
|Body Mass Index|
|Decline to answer||1417||1.9%||14||2.6%||0.232|
|Whooley Depression Screener (≥1)||27,036||36.3%||263||49.1%||< 0.001|
|Using a prescription||8884||11.9%||149||27.8%||<0.001|
|Charlson comorbidity index (CCI)||0.49||1.04||0.90||3.00||< 0.001|
Among employed respondents (MS respondents:n=192; controls:n=40,057), those with MS reported greater absenteeism, greater presenteeism, more hours missed from work, more hours missed due to impairment at work, and greater overall work impairment, compared with controls (allp<0.001). Those with MS reported over twice the amount of activity impairment as did controls (56.5% vs. 25.6%,p<0.001) ( Table 3 ).
|Control N=74,451||All MS N=536||MS vs. Control|
|Health-related quality of life|
|Mental component summary score||47.7||11.1||43.8||12.5||< 0.001|
|Physical component summary score||47.5||10.9||34.6||11.4||< 0.001|
|Health utilities||0.73||0.14||0.62||0.13||< 0.001|
|% of missed work time (absenteeism) *||4.0||14.3||10.5||21.1||<0.001|
|Hours missed (absenteeism) *||1.4||5.5||3.8||8.8||< 0.001|
|% of impairment at work (presenteeism) *||16.0||23.6||32.0||29.7||< 0.001|
|Hours missed due to impairment (presenteeism) *||5.2||8.4||9.6||10.7||< 0.001|
|% of overall impairment *||18.1||26.4||36.8||32.8||< 0.001|
|% of activity impairment||25.6||29.4||56.5||29.8||< 0.001|
|Total number of prescription medications||3.1||3.8||6.5||10.9||< 0.001|
|Traditional healthcare visit||58,584||78.7%||502||93.7%||< 0.001|
|Nontraditional healthcare visit||15,887||21.3%||179||33.4%||< 0.001|
|Using a prescription||52,618||70.7%||494||92.2%||<0.001|
|ER visit||9500||12.8%||100||18.7%||< 0.001|
These variables were assessed for the subgroup of employed respondents only.
Respondents with MS had significantly lower HRQoL than controls across all measures (MCS: 43.8 vs. 47.7, respectively; PCS: 34.6 vs. 47.5; and health utilities: 0.62 vs. 0.73; allp<0.001) ( Table 3 ).
3.2.5. Healthcare utilization
MS respondents reported greater frequency of visiting a traditional (93.7% vs. 78.7%,p<0.001) or nontraditional (33.4% vs. 21.3%,p<0.001) provider, using a prescription medication (92.2% vs. 70.7%,p<0.001), ER visits (18.7% vs. 12.8%,p<0.001), and hospitalizations (14.0% vs. 7.7%,p<0.001) ( Table 3 ).
3.3. Bivariate comparisons among degrees of MS severity
More men reported severe MS relative to mild (48.4% vs. 31.6%, respectively,p=0.015) and moderate severity (34.3%,p=0.039). There were no significant differences in age across groups ( Table 4 ).
|Mild MS N=206||Moderate MS N=268||Severe MS N=62||Mild vs. -Moderate||Mild vs. Severe||Moderate vs. Severe|
|n||%||n||%||n||%||p- value||p -value||p -value|
|HS graduate (e.g., GED) or less||41||19.9%||60||22.4%||19||30.6%||0.513||0.075||0.170|
|More than high school||165||80.1%||208||77.6%||43||69.4%||0.513||0.075||0.170|
|Less than $25,000||48||23.3%||70||26.1%||20||32.3%||0.482||0.155||0.328|
|$25,000 to $49,999||53||25.7%||93||34.7%||9||14.5%||0.036||0.066||0.002|
|$50,000 to $74,999||44||21.4%||44||16.4%||18||29.0%||0.170||0.209||0.022|
|$75,000 and over||46||22.3%||45||16.8%||12||19.4%||0.129||0.618||0.630|
|Decline to answer||15||7.3%||16||6.0%||3||4.8%||0.567||0.501||0.730|
|Full time||63||30.6%||39||14.6%||10||16.1%||< 0.001||0.025||0.753|
|Health insurance type|
While there were no significant differences between severity groups among those making less than $25,000, a greater proportion of individuals with moderate MS made $25,000-$49,999 than those with mild MS (34.7% vs. 25.7%,p=0.036). Also, significantly more moderate vs. severe MS respondents made $25,000–$49,999 (34.7% vs. 14.5%,p=0.002). However, significantly fewer individuals with moderate vs. severe MS made $50,000–$74,999 (16.4% vs. 29.0%,p=0.022). There were no significant differences across severity groups making ≥$75,000. Significantly more individuals with mild MS (30.6%) were employed full-time than those with moderate (14.6%,p<0.001) and severe MS (16.1%,p=0.025) ( Table 4 ).
3.3.2. Health status
Both severe (1.48,p=0.006) and mild MS respondents (1.12,p=0.034) reported higher CCI scores relative to moderate MS respondents (0.59). However, fewer mild (43.7%) vs. moderate (53.4%) MS respondents had depression based on the Whooley depression screener (p=0.037). No differences were found on self-reported diagnosed depression or the use of a prescription for depression among the three severity groups ( Table 5 ).
|Mild MS N=206||Moderate MS N=268||Severe MS N=62||Mild vs. Moderate||Mild vs. Severe||Moderate vs. Severe|
|n||%||n||%||n||%||p -value||p -value||p -value|
|Body Mass Index|
|Decline to answer||6||2.9%||8||3.0%||0||0.0%||0.963||0.174||0.168|
|Whooley Depression Screener (≥1)||90||43.7%||143||53.4%||30||48.4%||0.037||0.514||0.480|
|Using a prescription||48||23.3%||83||31.0%||18||29.0%||0.064||0.358||0.765|
|Mean||SD||Mean||SD||Mean||SD||p -value||p -value||p -value|
|Charlson comorbidity index (CCI)||1.12||3.84||0.59||1.16||1.48||4.75||0.034||0.533||0.006|
More respondents with severe MS were underweight vs. mild (12.9% vs. 2.4%, respectively,p=0.001) and moderate MS respondents (1.9%,p<0.001). Relative to those with mild MS (63.6%), fewer of those with severe (43.5%,p=0.005) and moderate MS (47.4%,p<0.001) reported exercising. Significantly fewer respondents with moderate vs. mild MS reported consuming alcohol (56.0% vs. 67.0%,p=0.015), while significantly more respondents with moderate vs. mild MS reported smoking (35.8% vs. 27.2%,p=0.046) ( Table 5 ).
Among employed MS respondents (mild:n=94; moderate:n=83; severe:n=15), moderate and severe MS respondents reported greater presenteeism, more hours missed due to impairment at work, and greater overall work impairment, compared with mild MS respondents (allp<0.01). Severe respondents reported greater presenteeism vs. moderate MS respondents (56.4% vs. 37.9%,p=0.029). Across the groups, mild MS respondents reported the lowest amount of activity impairment (42.6%), and severe MS respondents reported the highest (74.5%) (allp<0.002) ( Table 6 ).
|Mild n=206||Moderate n=268||Severe n=62||Mild vs. Moderate||Mild vs. Severe||Moderate vs. Severe|
|Mean||SD||Mean||SD||Mean||SD||p -value||p -value||p -value|
|Health-related quality of life|
|Mental component summary score||45.2||12.6||43.1||12.5||42.2||12.5||0.075||0.111||0.632|
|Physical component summary score||40.7||10.8||31.2||10.1||28.7||9.1||< 0.001||< 0.001||0.080|
|Health utilities||0.67||0.15||0.59||0.10||0.57||0.11||< 0.001||< 0.001||0.142|
|Work productiv ity|
|% of missed work time (absenteeism) *||7.1||16.5||13.2||24.3||16.1||25.6||0.052||0.083||0.683|
|Hours missed (absenteeism) *||2.6||7.3||5.2||10.2||4.1||8.3||0.051||0.454||0.711|
|% of impairment at work (presenteeism) *||23.2||27.5||37.9||27.7||56.4||33.4||0.001||< 0.001||0.029|
|Hours missed due to impairment (presenteeism) *||6.9||9.6||11.7||10.6||15.3||12.9||0.002||0.005||0.271|
|% of overall impairment *||26.2||30.7||44.8||30.9||59.1||34.7||< 0.001||< 0.001||0.119|
|% of activity impairment||42.6||30.9||63.0||25.1||74.5||25.4||< 0.001||< 0.001||0.001|
|Total number of prescription medications||5.7||8.1||5.9||4.5||11.6||26.7||0.742||0.006||0.001|
|n||%||n||%||n||%||p -value||p- value||p -value|
|Traditional healthcare visit||190||92.2%||253||94.4%||59||95.2%||0.344||0.431||0.813|
|Nontraditional healthcare visit||62||30.1%||88||32.8%||29||46.8%||0.525||0.015||0.039|
|Using a prescription||186||90.3%||250||93.3%||58||93.5%||0.234||0.431||0.940|
|ER visit||22||10.7%||58||21.6%||20||32.3%||0.002||< 0.001||0.076|
|Hospitalization||15||7.3%||37||13.8%||23||37.1%||0.024||< 0.001||< 0.001|
These variables were assessed for the subgroup of employed respondents only.
HRQoL was lowest in individuals with severe MS. Significant differences were found between severe and mild MS groups for PCS (28.7 vs. 40.7,p<0.001) and health utility scores (0.57 vs. 0.67,p<0.001). Moderate vs. mild MS groups also reported significant impairments on PCS (31.2 vs. 40.7,p<0.001) and health utility scores (0.59 vs. 0.67,p<0.001). No significant differences across any of the HRQoL measures were found between the moderate and severe MS groups ( Table 6 ).
3.3.5. Healthcare utilization
The proportion of individuals with non-traditional provider visits was greater in severe MS (46.8%) vs. mild (30.1%,p=0.015) and moderate MS (32.8%,p=0.039). More individuals with severe MS (37.1%) had been hospitalized than moderate (13.8%,p<0.001) and mild MS respondents (7.3%,p<0.001). More individuals with moderate and severe MS had ER visits vs. mild MS (allp<0.050). Severe vs. moderate MS comparisons on ER visits were not significant ( Table 6 ).
This study used self-reported data from a nationally representative sample to compare HRQoL, work and activity impairment, and healthcare utilization between MS respondents and controls, as well as among individuals with MS reporting varying degrees of disease severity. Many of the previous studies were limited by only focusing on employed respondents, insured individuals, or those who were treated with DMDs (Ivanova et al, 2009, Kobelt et al, 2006, and Pope et al, 2002). The current study addressed this gap by including individuals who were treated and untreated, had varying levels of employment, and were both insured and uninsured.
This study replicates earlier findings that MS patients experience increased activity and work impairment, healthcare resource utilization, and lower HRQoL relative to those without MS (Ivanova et al, 2009, Jennum et al, 2012, Pittock et al, 2004, Pope et al, 2002, and Wundes et al, 2010). Overall, increasing MS severity was associated with greater work and activity impairment, lower HRQoL, and increased healthcare utilization. In particular, more significant differences were found between groups reporting their disease severity as mild and moderate, rather than between moderate and severe. This differs somewhat from a previous study using objective severity categories derived from the EDSS, where the strongest differences in PROs were observed between the two benign and one late-MS groups ( Hviid et al., 2011 ). Although the measure of severity used in the current study was a simple, single self-report item, in contrast to the EDSS and Multiple Sclerosis Functional Composite, the relationships revealed vis-à-vis patient-reported outcomes (PROs) are important in representing the entirety of patients' experience with MS (Balcer, 2001, Miller et al, 2010, Robinson et al, 2009, and Rudick and Miller, 2008), and strong relationships have been demonstrated elsewhere between severity measures such as the EDSS and clinical data ( Ingram et al., 2010 ).
No significant differences emerged between moderate and severe groups on any HRQoL measures, indicating the transition from mild to moderate may be more consequential in terms of quality of life. A recent review of MS studies found a similar trend, with intangible costs resulting from reduced HRQoL linked to greater disability, with the largest increase in cost occurring between mild and moderate disability levels ( Wundes et al., 2010 ). It is possible that once patients reach a perceived level of moderate impairment, their HRQoL and functionality are significantly impaired enough that more severe levels of impairment are not reflected in noticeable additional declines. In addition, the three severity groups did not report any significant differences in traditional healthcare provider visits and prescription use; however, those with increasing levels of MS severity tended to report a greater number of nontraditional provider visits, ER visits, and hospitalizations. On the other hand, the severity measure in the current study may not have been sufficiently sensitive to capture differences between moderate and severe levels, given that moderate and severe patients with MS were similar in terms of number of years diagnosed with MS, mean number of MS symptoms, and frequency of treatment with a prescription medication for their MS. Mild patients reported experiencing a significantly lower number of MS symptoms and less frequent prescription treatment for their MS, compared with moderate and severe patients, suggesting that the mild-to-moderate difference was more substantial.
In the current study, the female-to-male ratio among severe respondents resembled that of the controls. MS in males tends to progress faster than in females ( Tremlett et al., 2006 ). Therefore, the finding that there were fewer males among mild and moderate MS patients may be explained by the rapid transition of male respondents, as compared with females, out of the mild and moderate groups and into the severe MS category.
Smoking tobacco has been found to be associated with MS disease progression and increased disease risk ( Wingerchuk, 2012 ). Greater proportions of current smokers were found within the three MS severity categories compared with the controls. Moreover, smoking rates were higher among the moderate vs. mild MS respondents. Thus, it is important to emphasize the importance of smoking cessation with MS patients. Similarly, the majority of the differences in alcohol consumption and exercise between MS respondents and controls are accounted for by the moderate and severe MS groups.
Aligned with previous data ( Formica et al., 1997 ), our analyses showed that MS patients tend to have lower BMI levels (especially moderate and severe patients) compared with controls. However, it is uncertain if disease severity is associated with diet in MS patients ( Payne, 2001 ).
Mild depression was more common in mild MS while severe depression was more common in moderate and severe MS. No differences in treatment for depression were found between severity levels; it is possible that untreated or under-treated depression played a role in the worse illness severity and HRQoL perceived by moderate patients relative to patients with mild MS. A previous study has shown that, as the severity of depression increased, so did the level of disability in MS patients ( McIvor et al., 1984 ). HRQoL in MS patients has been found to be strongly correlated with the level of depression and MS disease severity ( Göksel Karatepe et al., 2011 ), and the severity of depression in MS is a significant predictor of suicide attempts ( Feinstein, 2002 ). Similar work has found that depression is a major factor affecting quality of life among MS patients ( Lobentanz et al., 2004 ).
MS respondents were more frequently insured in comparison with controls, which may reflect selection biases such as the tendency of uninsured cases not to participate in the survey. Of the MS respondents, 48.7% had Medicare, whereas only 30.4% of the control group had Medicare coverage, a difference that likely relates to their level of disability.
A decrease in the employment rate between the mild to moderate severity groups may reflect the impact of MS severity on the possibility of employment or impairment while working. Fewer significant work productivity differences were detected between moderate and severe MS, while both groups reported significantly greater presenteeism, more work hours missed, and greater overall work impairment compared with those with mild MS. MS symptoms typically manifest during prime working ages of 20 to 50 years, and can interfere greatly with an individual’s ability to work (Ivanova et al, 2009 and Rumrill and Roessler, 2004). It is possible that the intensification of severity and frequency of symptoms between mild and moderate MS has a more pronounced impact on the ability to work than the shift from moderate to severe.
4.1. Study limitations
Due to the self-report nature of this study, patient perceptions may not align with objective clinical measures of disease severity, such as the EDSS, and diagnoses, treatment and symptoms could not be verified against clinician data. The cross-sectional study design allows detection of associations between variables at a single point in time, but limits causal inferences. Therefore, the higher resource utilization cannot be ascribed specifically to MS, since resource use was not assessed as having been caused by the disease and its symptoms per se. Results were based on descriptive bivariate analyses. No statistical adjustments (e.g., weighting of results, matching of respondents, or adjustments for multiple comparisons) were made in the study, and multivariable analyses did not control for potential confounding influences across groups. It should be noted that a variety of covariates are likely to have an impact on healthcare utilization (e.g., health insurance), HRQoL (e.g., comorbidities), and work-related impairment (e.g. type of employment).
The overall study sample was representative of the U.S. population, but may not have been representative of the entire U.S. MS population. The sample sizes of the mild and moderate groups were three to four times larger than that of the severe group. These disparities may have contributed to the greater number of significant differences between mild vs. moderate relative to moderate vs. severe groups. Also, because the NHWS is an Internet-based survey, respondents with extremely severe cases of MS may be under-represented in the study.
The significant differences in outcomes between MS and control respondents highlight that MS can greatly interfere with an individual’s quality of life and work productivity and lead to increased healthcare resource use. This study reveals that perceived disease severity can play an important role in HRQoL, work and activity impairment, and healthcare utilization. Prior research has shown that in individuals with MS, illness perception is an independent factor contributing to HRQoL ( Spain et al., 2007 ). In addition to diminished HRQoL, increases in MS severity may be accompanied by greater work and activity impairment and healthcare utilization. Moreover, the transition across degrees of severity may be nonlinear, such that a shift from mild-to-moderate MS may be associated with greater changes in health outcomes of interest compared with a shift from moderate-to-severe MS. These findings likewise show that increasing MS disease severity is associated with worse health outcomes. Further work is needed to better characterize the relationship between patient-reported levels of severity and more objective clinical measures and how they each relate to HRQoL and other health outcomes. Additionally, longitudinal study designs may help clarify the nonlinear relationships between changes in patient-reported severity and health outcomes.
Conflict of interest
The authors declare no conflict of interest.
The National Health and Wellness Survey (NHWS) is conducted by Kantar Health. Ms. Gupta and Dr. Goren are current employees of Kantar Health and paid consultants to EMD Serono Inc. and Pfizer Inc. in connection with the development of this manuscript and the execution of the study. Dr. Phillips and Dr. Dangond are current employees of EMD Serono Inc., and Dr. Stewart is a current employee of Pfizer Inc. who jointly oversaw the study and manuscript development.
Role of the funding source
EMD Serono Inc. and Pfizer Inc. purchased access to the NHWS dataset and funded the analysis and preparation of this manuscript.
The authors wish to acknowledge the background research and editorial assistance of Sara Bodnar, MPH, who is a paid consultant of Kantar Health.
- Balcer, 2001 L.J. Balcer. Clinical outcome measures for research in multiple sclerosis. Journal of Neuro-Ophthalmology. 2001;21:296-301
- Brazier et al., 2002 J.E. Brazier, J. Roberts, M. Deverill. The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics. 2002;21:271-292
- Brazier and Roberts, 2004 J.E. Brazier, J. Roberts. The estimation of a preference-based measure of health from the SF-12. Medical Care. 2004;42:851-859
- Bolge et al., 2009 S.C. Bolge, J.F. Doan, H. Kannan, R.W. Baran. Association of insomnia with quality of life, work productivity, and activity impairment. Quality of Life Research. 2009;18:415-422
- Brook et al., 2009 R.A. Brook, K. Rajagopalan, N. Kleinman, A.K. Melkonian. Absenteeism and health-benefit costs among employees with MS. Current Medical Research and Opinion. 2009;25:1469-1476
- Charlson et al., 1987 M.E. Charlson, P. Pompei, K.L. Ales, C.R. Mackenzie. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. Journal of Chronic Diseases. 1987;40:373-383
- Da Silva et al., 2011 A.M. Da Silva, E. Vilhena, A. Lopes, E. Santos, M.A. Gonçalves, C. Pinto, et al. Depression and anxiety in a Portuguese MS population: associations with physical disability and severity of disease. Journal of the Neurological Sciences. 2011;306:66-70
- DiBonaventura et al., 2011 M. DiBonaventura, J.S. Wagner, Y. Yuan, G. L’Italien, P. Langley, W. Ray Kim. The impact of hepatitis C on labor force participation, absenteeism, presenteeism and non-work activities. Journal of Medical Economics. 2011;14:253-261
- Feinstein, 2002 A. Feinstein. An examination of suicidal intent in patients with multiple sclerosis. Neurology. 2002;59:674-678
- Finkelstein et al., 2011 E.A. Finkelstein, B.T. Allaire, M.D. Dibonaventura, S.M. Burgess. Direct and indirect costs and potential cost savings of laparoscopic adjustable gastric banding among obese patients with diabetes. Journal of Occupational and Environmental Medicine. 2011;53:1025-1029
- Formica et al., 1997 C.A. Formica, F. Cosman, J. Nieves, J. Herbert, R. Lindsay. Reduced bone mass and fat-free mass in women with multiple sclerosis: effects of ambulatory status and glucocorticoid use. Calcified Tissue International. 1997;61:129-133
- Göksel Karatepe et al., 2011 A. Göksel Karatepe, T. Kaya, R. Günaydn, A. Demirhan, P. Ce, M. Gedizlioğlu. Quality of life in patients with multiple sclerosis: the impact of depression, fatigue, and disability. International Journal of Rehabilitation Research. 2011;34:290-298
- Hviid et al., 2011 L.E. Hviid, B.C. Healy, D.J. Rintell, T. Chitnis, H.L. Weiner, B.I. Glanz. Patient reported outcomes in benign multiple sclerosis. Multiple Sclerosis. 2011;17:876-884
- Ingram et al., 2010 G. Ingram, E. Colley, Y. Ben-Shlomo, M. Cossburn, C.L. Hirst, T.P. Pickersgill, et al. Validity of patient-derived disability and clinical data in multiple sclerosis. Multiple Sclerosis. 2010;16:472-479
- Ivanova et al., 2009 J.I. Ivanova, H.G. Birnbaum, S. Samuels, M. Davis, A.L. Phillips, D. Meletiche. The cost of disability and medically related absenteeism among employees with multiple sclerosis in the US. Pharmacoeconomics. 2009;27:681-691
- Jennum et al., 2012 P. Jennum, B. Wanscher, J. Frederiksen, J. Kjellberg. The socioeconomic consequences of multiple sclerosis: a controlled national study. European Neuropsychopharmacology. 2012;22:36-43
- Kobelt et al., 2006 G. Kobelt, J. Berg, D. Atherly, O. Hadjimichael. Costs and quality of life in multiple sclerosis: a cross-sectional study in the United States. Neurology. 2006;66:1696-1702
- Lad et al., 2010 S.P. Lad, C.H. Chapman, M. Vaninetti, L. Steinman, A. Green, M. Boakye. Socioeconomic trends in hospitalization for multiple sclerosis. Neuroepidemiology. 2010;35:93-99
- Lobentanz et al., 2004 I.S. Lobentanz, S. Asenbaum, K. Vass, C. Sauter, G. Klösch, H. Kollegger, et al. Factors influencing quality of life in multiple sclerosis patients: disability, depressive mood, fatigue, and sleep quality. Acta Neurologica Scandinavica. 2004;110:6-13
- McIvor et al., 1984 G.P. McIvor, M. Riklan, M. Reznikoff. Depression in multiple sclerosis as a function of length and severity of illness, age, remissions, and perceived social support. Jouirnal of Clinical Psychology. 1984;40:1028-1033
- Miletić et al., 2011 S. Miletić, G. Tončev, J. Jevđić, B. Jovanović, D. Canović. Fatigue and depression in multiple sclerosis: correlation with quality of life. Archives of Biological Sciences. 2011;63:617-622
- Miller et al., 2010 D. Miller, R.A. Rudick, M. Hutchinson. Patient-centered outcomes: translating clinical efficacy into benefits on health-related quality of life. Neurology. 2010;74(Suppl 3):S24-S35
- Naci et al., 2010 H. Naci, R. Fleurence, J. Birt, A. Duhig. Economic burden of multiple sclerosis: a systematic review of the literature. Pharmacoeconomics. 2010;28(5):363-379
- Payne, 2001 A. Payne. Nutrition and diet in the clinical management of multiple sclerosis. Journal of Human Nutrition and Dietetics. 2001;14:349-357
- Pittock et al., 2004 S.J. Pittock, W.T. Mayr, R.L. McClelland, N.W. Jorgensen, S.D. Weigand, J.H. Noseworthy, et al. Quality of life is favorable for most patients with multiple sclerosis: a population-based cohort study. Archives of Neurology. 2004;61:679-686
- Pope et al., 2002 G.C. Pope, C.J. Urato, E.D. Kulas, R. Kronick, T. Gilmer. Prevalence, expenditures, utilization, and payment for persons with MS in insured populations. Neurology. 2002;58:37-43
- Prescott et al., 2007 J.D. Prescott, S. Factor, M. Pill, G.W. Levi. Descriptive analysis of the direct medical costs of multiple sclerosis in 2004 using administrative claims in a large nationwide database. Journal of Managed Care Pharmacy. 2007;13:44-52
- Reilly et al., 1993 M.C. Reilly, A.S. Zbrozek, E.M. Dukes. The validity and reproducibility of a work productivity and activity impairment instrument. Pharmacoeconomics. 1993;4:353-365
- Robinson et al., 2009 D. Robinson Jr, N. Zhao, T. Gathany, L.L. Kim, D. Cella, D. Revicki. Health perceptions and clinical characteristics of relapsing-remitting multiple sclerosis patients: baseline data from an international clinical trial. Current Medical Research and Opinion. 2009;25:1121-1130
- Rumrill and Roessler, 2004 P. Rumrill, R. Roessler. Life at work after multiple sclerosis. Journal of Vocational Rehabilitation. 2004;20:153-154
- Rudick and Miller, 2008 R.A. Rudick, D.M. Miller. Health-related quality of life in multiple sclerosis: current evidence, measurement and effects of disease severity and treatment. CNS Drugs. 2008;22:827-839
- Spain et al., 2007 L.A. Spain, N. Tubridy, T.J. Kilpatrick, S.J. Adams, A.C. Holmes. Illness perception and health-related quality of life in multiple sclerosis. Acta Neurologica Scandinavica. 2007;116:293-299
- Stüve and Oksenberg, 2010 Stüve O, Oksenberg J. Multiple sclerosis overview. In: Pagon RA, Adam MP, Bird TD, Dolan CR, Fong CT, Stephens K, editors. GeneReviews™ [Internet]. Seattle (WA): University of Washington, 1993-2013; 2006 Jan 2010 [updated 2010 May 11]
- Tremlett et al., 2006 H. Tremlett, D. Paty, V. Devonshire. Disability progression in multiple sclerosis is slower than previously reported. Neurology. 2006;66:172-177
- Ware et al., 2002 J.E. Ware Jr, M. Kosinski, D.M. Turner-Bowker, B. Gandek. How to score version 2 of the SF-12® health survey (with a supplemental documenting version 1). (QualityMetric Incorporated, Lincoln, RI, 2002)
- Whooley et al., 1997 M.A. Whooley, A.L. Avins, J. Miranda, W.S. Browner. Case-finding instruments for depression. Two questions are as good as many. Journal of General Internal Medicine. 1997;12:439-445
- Wingerchuk, 2012 D.M. Wingerchuk. Smoking: effects on multiple sclerosis susceptibility and disease progression. Therapeutic Advances in Neurological Disorders. 2012;5:13-22
- Wundes et al., 2010 A. Wundes, T. Brown, E.J. Bienen, C.I. Coleman. Contribution of intangible costs to the economic burden of multiple sclerosis. Journal of Medical Economics. 2010;13:626-632
a Health Outcomes Practice, Kantar Health, 1 Independence Way, Suite 220, Princeton, NJ 08540, USA
b Health Outcomes Practice, Kantar Health, 11 Madison Avenue, 12th Floor, New York, NY 10010, USA
c Health Outcomes & Market Access, EMD Serono Inc., One Technology Place, Rockland, MA 02370, USA
d US Medical Affairs, Neurodegenerative Diseases, EMD Serono Inc., One Technology Place, Rockland, MA 02370, USA
e Specialty Care Medicines Development Group, Pfizer Inc., 445 Eastern Point Road, MS 8260-2514, Groton, CT 06340, USA
1 An affiliate of Merck KGaA, Darmstadt, Germany.
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