Abstract

The reduction in ALS Functional Rating Score (ALSFRS) from reported symptom onset to diagnosis is used to estimate rate of disease progression. ALSFRS decline may be non-linear or distorted by drop-outs in therapeutic trials, reducing the reliability of change in slope as an outcome measure. The PRO-ACT database uniquely allows such measures to be explored using historical data from negative therapeutic trials. The decline of functional scores was analysed in 18 pooled trials, comparing rates of decline based on symptom onset with rates calculated between interval assessments. Strategies to mitigate the effects of trial drop-out were considered. Results showed that progression rate calculated by symptom onset underestimated the subsequent rate of disability accumulation, although it predicted survival more accurately than four-month interval estimates of δALSFRS or δFVC. Individual ALSFRS and FVC progression within a typical trial duration were linear. No simple solution to correct for trial drop-out was identified, but imputation using δALSFRS appeared least disruptive. In conclusion, there is a trade-off between the drive to recruit trial participants soon after symptom onset, and reduced reliability of the ALSFRS-derived progression rate at enrolment. The need for objective markers of disease activity as an alternative to survival-based end-points is clear and pressing.

Highlights

  • ALS is a heterogeneous condition with multiple pathological pathways culminating in overlapping disease phenotypes [1]

  • Results showed that progression rate calculated by symptom onset underestimated the subsequent rate of disability accumulation, it predicted survival more accurately than fourmonth interval estimates of dALSFRS or dFVC

  • The key findings of this study were: Initial rates of ALS progression calculated from recalled date of symptom onset tended to underestimate the subsequent rate of disability progression

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Summary

Introduction

ALS is a heterogeneous condition with multiple pathological pathways culminating in overlapping disease phenotypes [1]. Despite this complexity, clinical and demographic characteristics readily assessed at time of presentation can inform prediction of disease progression [2,3,4,5,6,7]. Even within clinically-defined subtypes [8] or genotypes [9,10], progression rates remain relatively dispersed. Whether measured by self-reported loss of function scales (most commonly the revised ALS Functional Rating Score, ALSFRS-R), or by objective structured assessment

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