Patient-reported severity of lower extremity + upper limb disability in Charcot-Marie-Tooth disease type 1A: findings from a digital real-world study
X⁹, Day L¹⁰, Kudlac A¹⁰, Lau JKL¹⁰, Llewellyn S¹⁰, Larkin M¹⁰, Boutalbi Y⁹ ¹Department of Neurology, Hackensack Meridian School of Medicine, Hackensack University Medical Center, Hackensack, NJ, USA ²Hospital University la Timone, Filnemus ERN-NMD, Marseille, France
³Hospital Universitari I Politècnic La Fe, Universitate de Valencia, CIBERER, Valencia, Spain⁴ACMT-Rete per la malattia di Charcot-Marie-Tooth OdV, Bologna, Italy⁵Charcot-Marie-Tooth Association, Glenolden, PA, USA ⁶Charcot-Marie-Tooth UK, Christchurch, UK⁷CMT France, Saint-Alban, France⁸Hereditary Neuropathy Foundation, NewYork, NY, USA ⁹Pharnext, Paris, France¹⁰Vitaccess, Oxford, UK Corresponding author: Youcef
Background &Objectives
Charcot-Marie-Tooth disease type 1A (CMT1A) is an inherited rare peripheral nerve disease, leading to progressive, predominantly distal, muscle weakness, atrophy, sensory loss, and limb deformities1,2 This analysis explores the relationship between lower extremity/upper limb disability in CMT1A and a range of clinical variables.
Methods
Adults with CMT1A in France, Germany, Italy, Spain, the UK, or the USA were recruited to an ongoing, international, digital study exploring the real-world impact of CMT. Patient-reported outcome (PRO) data were collected via the study app, CMT&Me, on the impact of lower extremity disability (via the Lower Extremity Functional Scale; LEFS)3 and upper limb disability (via the abbreviated form of the Disabilities of the Arm, Shoulder, and Hand questionnaire; QuickDASH)4
Linear regression was used to evaluate relationships between the PRO responses and a series of explanatory clinical variables; these variables included demographics, symptoms, medical history, and treatment history. Explanatory variables in the models comprised data collected at registration, while PRO outcome variables in the models comprised data collected at the most recent timepoint of completion.
The LEFS and QuickDASH linear regression models are shown in Fig. 1 and Fig. 2, respectively.
For the LEFS, atotal score(0-80) is obtained by summing all survey items3. The severity threshold is 20, where an LEFS score of below 20 is classified as “Severe” (1), and an LEFS score of above 20 is classified as “Non-severe” (0).
For the QuickDASH, a final score (0-100) is an adjusted average score computed from all completed survey items4. The severity threshold is 75, where a QuickDASH score of below 75 is classified as “Non-severe” (0), and a QuickDASH score of above 75 is classified as “Severe” (1).
Results
Country of residence
The country of residence (reported at registration) of the 1,030 respondents in the analysis population is presented in Table 1.
Linear regression models
Results for the LEFS and QuickDASH linear regression models are shown in Fig. 3 and Fig. 4, respectively. There were 1,573 responses to the LEFS, and 1,585 responses to the QuickDASH (over multiple timepoints). A range of explanatory variables had an effect on the severity of lower extremity and upper limb disability in the respective models.
The regression models were statistically significant overall in both cases (LEFS: Adj. R2 = 0.238, F = 10.278; QuickDASH: Adj. R2 = 0.161, F = 6.753), indicating a good fit of the models to the data. Additionally, a strong positive association was identified between LEFS and QuickDASH scores (r(2293)=0.79, p<0.01).
Beta represents the coefficient in the models, showing the direction and magnitude of the effect on the PRO variable.
Residency in Germany (LEFS: ß=0.172, p<0.001; QuickDASH: ß=0.097, p<0.001) and Italy (LEFS: ß=0.173, p<0.001; QuickDASH: ß=0.065, p=0.025) were associated with greater severity of both lower extremity and upper limb disabilities when compared with the USA (reference).
Diagnosis age of 21 to 30 years was associated with greater severity of lower extremity disabilities (LEFS: ß=0.074, p<0.015), but lesser severity of upper limb disabilities (QuickDASH: ß=-0.044, p=0.028), when compared with diagnosis age of 31 to 40 years (reference).
Reporting of hammer toes (LEFS: ß=0.112, p<0.001), falls (LEFS: ß=0.159, p<0.001), aching (LEFS: ß=0.063, p=0.023; QuickDASH: ß=0.076, p<0.001), or severe fatigue (LEFS: ß=0.237, p<0.001; QuickDASH: ß=0.098, p<0.001) was associated with greater severity in both cases.
Reporting of high (LEFS: ß=-0.133, p<0.001) and/or flat (LEFS: ß=-0.089, p=0.024) arches was associated with lesser severity in both cases.
Reported use of CBD oil (LEFS: ß=0.088, p=0.016; QuickDASH: ß=0.051, p=0.036) was associated with greater severity in both cases.
Figure 3: LEFS linear regression model results (n=1,573 responses from 660 responding participants; p<0.05).
Discussion &Conclusions
This study evidences that a range of clinical variables affect the severity of lower extremity/upper limb disability in CMT1A.
The LEFS and QuickDASH models identified several clinical variables similarly affecting the severity of lower extremity and upper limb disability, respectively. Variables found to be associated with greater severity in both cases – for instance, reporting of hammer toes, falls, or aching – could be relevant when identifying effective therapeutic targets.
https://www.physio-pedia.com/Lower_Extremity_Functional_Scale_(LEFS); 2022 [accessed 7 December 2022] 4 Physiopedia. DASH Outcome Measure, https://www.physio-pedia.com/index.php?title=DASH_Outcome_Measure&oldid=320309; 2022 [accessed 7 December 2022]
Figure 1: LEFS linear regression model Figure 2: QuickDASH linear regression model Table 1: Country of residence (n=1,030)