To develop risk stratification tools for ALS and assist in identifying high-risk groups.
Approach:
Study Design: A prospective cohort study using the UK Biobank with 500,033 participants, divided into training and validation sets.
Frailty Index Calculation: Calculated frailty index (FI) and modified frailty index (MFI) based on 49 health deficits.
Statistical Analysis: Utilized univariate Cox regression and time-dependent ROC curve to evaluate the models' performance.
Key Findings:
Five deficits significantly associated with ALS were identified: falls, whole-body pain, long-standing illness, disability or infirmity, self-rated health, and tiredness or lethargy.
Both FI and MFI were linked to a higher risk of ALS (HRFI = 4.58, 95% CI = 1.31–16.07; HRMFI = 4.59, 95% CI = 2.79–7.53).
The combination of MFI, gender, age, and BMI showed the best discriminative ability with a C-index of 0.696.
Interpretation:
The MFI may enhance the identification of individuals at elevated risk of ALS, serving as a potential screening tool.
Limitations:
The study relies on self-reported health deficits which may introduce bias, potentially affecting the accuracy of the findings.
The applicability of findings may be limited to the UK population.
Conclusion:
The MFI could improve the ability to identify high-risk individuals for ALS.
