ALS is a progressive neurodegenerative disease. The stage of disease reached can be described using a simple system based on the number of central nervous system regions involved. Historically, datasets have not attempted to record clinical stage, but being able to re-analyse the data by stage would have several advantages. We therefore explored the possibility of using an algorithm based on the revised ALS Functional Rating Scale (ALSFRS-R), which is commonly used in clinical practice, to estimate clinical stage. We devised an algorithm to convert ALSFRS-R score into clinical stage. ALSFRS-R domains were mapped to equivalent CNS regions. Stage 4 is reached when gastrostomy or non- invasive ventilation is needed, but as a proxy we used provision. We collected ALSFRS-R from clinic visits, and compared the estimation of clinical stage from the ALSFRS-R with the actual stage. Results showed that the agreement between staging by the two methods was excellent with an intraclass correlation coefficient of 0.92 (95% confidence interval 0.88-0.94). There was no systematic bias towards over-staging or under-staging using the algorithm. In conclusion, we have shown that clinical stage in ALS can be reliably estimated using the ALSFRS-R in historical data and in current data where stage has not been recorded.
Keywords: Epidemiology; clinical trials; survival.