Webinar Debrief: Optimising Spirometry Endpoints in Clinical Trials

Variability in spirometry data remains one of the biggest challenges in respiratory clinical trials. As endpoint expectations become more demanding and patient populations more complex, sponsors, CROs, and site teams are increasingly questioning whether traditional quality assurance frameworks fully reflect the realities of respiratory disease.

This article explores the key insights from our webinar Optimising Spirometry Endpoints in Clinical Trials featuring Grant Sowman, VP Clinical Services (Vitalograph) and Holly Wilson (RPFT).

The Challenge: Standardisation Does Not Always Reflect Physiology

Spirometry endpoints such as FEV₁ and FVC remain central to evaluating treatment efficacy across respiratory clinical trials. Consequently, robust quality assurance processes are essential for ensuring data integrity and regulatory confidence. ATS/ERS guidelines provide an important framework for standardising testing and minimising poor-quality data.

However, respiratory diseases do not affect patients uniformly. Individuals with restrictive lung disease, severe airflow obstruction, or neuromuscular conditions may face physiological limitations that influence their ability to meet specific quality criteria despite producing clinically meaningful and repeatable results. This creates a challenge for sponsors and trial teams seeking to balance quality standards with endpoint usability.

Key Insight 1: Spirometry Quality Challenges Are Often Disease-Specific

Large-scale respiratory trial datasets show that certain quality assurance issues are consistently associated with specific disease populations. Patients with IPF, for example, are more likely to struggle with start-of-test criteria such as back extrapolated volume (BEV), while patients with COPD more frequently exhibit artefact later in the expiratory manoeuvre. Neuromuscular disease populations often encounter difficulties maintaining maximal effort throughout testing.

These patterns suggest that what appears to be a testing error may sometimes be an expected consequence of disease physiology.

Expert Commentary

The respiratory clinical research industry has traditionally applied a common QA framework across diverse patient populations. While standardisation remains essential, understanding disease-specific testing challenges provides an opportunity to improve how endpoint data is evaluated. The question is no longer simply whether a test passed or failed, but whether the observed finding reflects poor technique or the physiological reality of the study population.

Key Insight 2: Automated QA Is Powerful, But Context Matters

Automated spirometry quality assurance has transformed respiratory clinical trials by providing immediate feedback and standardised review processes at scale. These systems play a vital role in identifying potential testing issues and supporting site performance.

However, algorithms assess predefined criteria rather than clinical context. A COPD patient's airway artefact may appear similar to a cough event, while a restrictive lung disease patient may narrowly miss a start-of-test threshold despite demonstrating highly repeatable lung function measurements.

Expert Commentary

Automation is highly effective at identifying potential quality concerns, but it cannot determine whether a flagged result is driven by inadequate testing or disease-related physiology. As respiratory trials become increasingly specialised, combining automated review with expert assessment may provide a more comprehensive approach to quality management.

Key Insight 3: Endpoint Usability May Extend Beyond Technical Acceptability

Clinical trial protocols often define strict criteria for spirometry test acceptability. While these standards support consistency, they may not always capture the full value of the data collected.

In some cases, a manoeuvre may narrowly fail a specific quality criterion while still producing highly repeatable FEV₁ and FVC measurements. For trial teams, the challenge becomes determining whether technically imperfect data may still be suitable for endpoint analysis.

Expert Commentary

Acceptability and usability should not automatically be treated as identical concepts. Especially in studies involving severe disease populations, evaluating repeatability, consistency, and overall clinical context may provide a more meaningful assessment of endpoint quality than reliance on a single threshold alone.

Key Insight 4: Expert Over-Reading Remains Critical

Despite continued advances in digital tools and automated review, experienced respiratory physiologists and over-readers remain central to effective spirometry quality management. Their expertise allows them to identify recurring physiological patterns, review longitudinal performance, and assess whether quality flags represent true testing errors or expected disease-related findings.

Human review also supports a more targeted feedback process, enabling site teams to improve coaching based on the specific challenges associated with individual respiratory conditions.

Expert Commentary

The future of spirometry quality assurance is unlikely to be fully automated. Instead, the greatest value may come from combining technology with specialist expertise, creating a collaborative review process that balances consistency with clinical judgement.

What This Means in Practice

For sponsors, CROs, and clinical trial sites, optimising spirometry endpoints increasingly requires more than implementing established guidelines alone.

Practical considerations include:

Developing disease-specific spirometry QA frameworks that complement ATS/ERS standards.
Incorporating expert over-reading pathways for borderline or complex cases.
Tailoring site training and coaching to address disease-specific testing challenges.
Establishing clear processes for documenting scientific rationale when reviewing tests that fall outside standard criteria.
Encouraging collaboration between sponsors, CROs, investigators, and central reviewers when assessing endpoint usability.

As respiratory trials become more complex, a nuanced approach to quality assurance may help reduce missing data, minimise unnecessary repeat testing, and improve overall endpoint reliability.

Future Outlook

The broader clinical research industry is increasingly embracing precision approaches to trial design, patient selection, and endpoint assessment. Spirometry quality assurance is likely to follow a similar trajectory.

Future programmes may combine automated analytics, disease-specific QA frameworks, longitudinal trend analysis, and expert review to create a more sophisticated model of endpoint quality management. Rather than replacing standards, this approach would apply them in a way that better reflects the physiological characteristics of individual patient populations.

Conclusion

High-quality spirometry remains fundamental to respiratory clinical trials, but maintaining quality does not necessarily require a uniform approach to every patient population. As understanding of disease-specific testing patterns continues to grow, there is an opportunity to refine how spirometry endpoints are assessed and interpreted.

By combining established ATS/ERS standards with disease-specific expertise, targeted coaching, and expert over-reading, sponsors and CROs can strengthen endpoint quality while maximising the value of collected data. The result is a more informed, evidence-based approach to spirometry endpoint management that supports both scientific rigour and operational efficiency.