8 Key Considerations for Accurate Lung Function Testing in ALS Clinical Trials

In collaboration with Professor Chris McDermott, we outline eight important considerations to improve ALS clinical trial outcomes in lung function assessment.

ALS affects approximately 1 in 300 people over a lifetime, with nearly half of those diagnosed passing within two years (ALS Association, 2022). Currently, there is no cure. Advances in understanding TDP-43 pathology, genetics, and biomarkers highlight promising future research directions.

These considerations will help optimise the performance of ALS clinical trials testing lung function:

1.     Respiratory Monitoring

Respiratory measures such as vital capacity are critical trial endpoints, as they correlate with ALS survival and scores on the ALS Functional Rating Scale-Revised (ALSFRS-R). Tests like Slow Vital Capacity (SVC) and Sniff Nasal Inspiratory Pressure (SNIP) are commonly measured in ALS clinical trials (Chipika et al., 2019).

2.     Trial Site Accessibility

When selecting locations consider patients' mobility challenges and likely progression during the trial. Multi-site or remote options may improve participation. Decentralised monitoring may require additional support for device type, support levels, and reporting.

3.     Reliable Connectivity for Data Transmission

For remote monitoring, robust connectivity and tech support are essential to ensure smooth data collection and transfer. Device compatibility, such as using patients' own devices, should be carefully assessed to maintain data integrity.

4.     Longitudinal Data Collection

Traditional in-clinic monitoring every three months may miss significant disease changes within that timeframe. Continuous, non-intrusive data collection enhances understanding of ALS progression and better reflects patients' everyday experiences (Al-Chalabi et al., 2017).

5.     Adaptive, Patient-Centred Trial Design

Tailoring designs to ALS’s variable progression improves inclusivity and patient relevance. Selection criteria, such as whether to include patients on neuroprotective agents like Riluzole, must be clearly defined to support consistent, meaningful data analysis. A study by Helleman et al. (2022) found that 69% of ALS patients were comfortable with self-monitoring and 75% preferring remote oversight by healthcare providers. The study also noted a preference for a maximum of three devices and weekly check-ins.

6.     Ethics and Inclusivity

Ethical ALS trials prioritise patient autonomy, data security, and equitable access. Inclusive trial designs represent a broader ALS patient population, supporting more comprehensive research outcomes.

7.     Home Monitoring Support and Training

Adequate training, including one-to-one coaching, ensures patients are able to perform home monitoring accurately, improving data reliability and trial adherence (Jackson et al., 2018).

8.     Standardised Testing Protocols

Ensuring that all patients complete tests under uniform conditions, such as sitting versus standing, improves data consistency across sites, supporting reliable trial results.

Learn more:

• Al-Chalabi, A., & Hardiman, O. (2013). The epidemiology of ALS: a global perspective. Journal of Neurology, Neurosurgery & Psychiatry, 84(6), 608-614.

• ALS Association. (2022). Facts You Should Know. Available at: https://www.alsassociation.org.

• Chipika, R. H., et al. (2019). Using imaging biomarkers to assess ALS progression. Journal of Neurology, 266(6), 1388-1401.

• Helleman, J., et al. (2022). Patient perspectives on digital health in ALS management. Journal of Neuromuscular Diseases, 9(1), 35-47.

• Miller, R. G., et al. (2020). Trial design considerations for ALS clinical research. ALS and Frontotemporal Degeneration, 21(2), 110-120.