Can home spirometry and FeNO testing improve asthma diagnosis? a feasibility study

This feasibility study demonstrates that home-based spirometry and FeNO monitoring are clinically feasible, show high diagnostic sensitivity and specificity, and have the potential to improve asthma diagnosis accuracy while reducing reliance on bronchial challenge testing.

The Gist

Imagine you are trying to figure out if a car engine is misfiring. The mechanic (the doctor) usually asks you to drive the car into the shop, rev the engine once, and listen. If the engine sounds fine at that exact moment, they might say, "Your car is fine." But what if the engine only misfires when it's cold, or when you're driving up a hill, or after you've been sitting in traffic for an hour? A single test in the shop might miss the problem entirely.

This is exactly the problem with diagnosing asthma. Asthma is a "shape-shifter." The airways in your lungs can be wide open one minute and tight and inflamed the next. Traditional diagnosis relies on a single visit to the clinic. If you happen to visit when your lungs are feeling good, you might be told you don't have asthma, even if you do. This leads to people being treated for the wrong thing or suffering unnecessarily.

This study, led by Dr. Ran Wang and colleagues, asked a simple question: What if we let the patients do the testing at home, over several days, instead of just once in the clinic?

Here is a breakdown of their findings using some everyday analogies:

1. The "Weather Forecast" vs. The "Snapshot"

• The Old Way (Clinic Test): This is like taking a single photo of the sky at noon. If it's sunny, you assume it's a sunny day. But you miss the storm that happened at 6 AM or the rain coming at 8 PM.
• The New Way (Home Testing): This is like having a weather station in your backyard that records the temperature, wind, and rain every few hours for a week. You get the whole picture of the weather, not just a snapshot.

The researchers gave patients two portable devices:

• A Spirometer: A small handheld machine that measures how much air you can blow out (like checking the engine's power).
• A FeNO Tester: A device that measures nitric oxide in your breath, which acts like a "smoke detector" for inflammation in your lungs.

2. The "Homework" Challenge

The study asked patients to use these devices at home four times a day for a week, and then twice a day for a second week. They wanted to know: Can regular people actually do this without getting frustrated or breaking the equipment?

The Verdict: Yes!

• Adherence: About 7 out of 10 people stuck to the schedule.
• Ease of Use: The devices were easy to learn. It took about 9 minutes to learn the spirometer and 5 minutes for the FeNO tester.
• No Breakages: No devices were lost or broken.
• The "Digital Diary": Patients also filled out a daily mood/health diary. While some people stopped filling it out after a week (just like how we stop using a new fitness app after a month), the data collected was enough to prove the concept works.

3. The "Detective" Results

The researchers compared the home data against the "gold standard" diagnosis made by a panel of expert asthma specialists.

• The "Peek-a-Boo" Effect: They found that many people's lung function and inflammation levels changed drastically throughout the day. Some people had "normal" lungs in the morning but "asthma-like" lungs in the afternoon.
• Better than the Old Home Test: The old standard for home testing was a "Peak Flow Meter" (a simple plastic tube you blow into). It's cheap but often inaccurate and hard to use correctly. The new digital home tests were much better at spotting the "shape-shifting" asthma.
• The Magic Metric: They found that looking at the variability (how much the numbers changed) was the key. If your lung numbers jumped around a lot during the day, it was a strong sign of asthma.

4. The "Traffic Jam" Solution

Currently, if a doctor isn't sure if you have asthma after a clinic visit, they send you to a specialist for a "Bronchial Challenge Test" (BCT). This is a bit like a stress test for your lungs where they make you cough to see if your airways tighten. It's expensive, time-consuming, and requires a specialist.

The study found that if they added the home testing to the current diagnostic process:

• They could cut the need for these specialist stress tests by 57%.
• Imagine a traffic jam where everyone is waiting for a toll booth. The home testing acts like a fast lane that lets half the cars pass through without stopping at the booth, saving time and money for the whole system.

The Bottom Line

This study is like a successful "pilot program" for a new way of diagnosing asthma. It proved that:

1. It's possible: Regular people can use these high-tech medical devices at home.
2. It's useful: It catches asthma that single clinic visits miss because it captures the "daily drama" of the lungs.
3. It's efficient: It could save the healthcare system a lot of time and money by reducing unnecessary specialist visits.

The Future:
The researchers aren't saying we should stop going to the doctor. Instead, they are suggesting a "hybrid" approach: Go to the doctor for the initial check, but if it's unclear, take the "weather station" home for a week. This gives the doctor a much clearer map of your lung health, leading to faster, more accurate diagnoses and better treatment for patients.

Note: This study is a "feasibility study," meaning it proved the idea works in a small group. The next step is a larger study to confirm these results for everyone.

Technical Summary

1. Problem Statement

• Diagnostic Challenges: Asthma is characterized by temporal variability in airway obstruction and inflammation. However, current diagnostic guidelines (e.g., BTS/NICE/SIGN 2024) rely heavily on single-point, clinic-based measurements.
• Limitations of Current Methods:
  • False Negatives: Patients may have normal test results during clinic visits if they are not symptomatic at that specific moment.
  • Over/Under-diagnosis: Misdiagnosis rates are high (up to 1/3 over-diagnosed, 19-73% under-diagnosed), leading to unnecessary treatment or lack of treatment.
  • Inadequate Home Monitoring: The only currently recommended home test, Peak Expiratory Flow (PEF) diurnal variability, has poor diagnostic yield, low sensitivity (~15%), and poor patient adherence.
  • Resource Bottleneck: Patients with inconclusive clinic tests often require Bronchial Challenge Testing (BCT), which is restricted to secondary care, causing delays and high costs.
• Objective: To evaluate the clinical feasibility, adherence, and potential diagnostic utility of home-based spirometry and fractional exhaled nitric oxide (FeNO) monitoring as an alternative to capture disease variability and improve diagnostic accuracy.

2. Methodology

• Study Design: A feasibility study nested within the larger RADicA (Rapid Asthma Diagnostics for Asthma) prospective cohort study.
• Participants: Symptomatic, untreated adults (>16 years) with GP-suspected asthma, recruited from primary care.
  • Recruitment: 67 eligible, 51 consented (76%), 38 had a definitive diagnosis confirmed by an expert panel.
  • Demographics: 63% recruited from the most deprived areas (IMD deciles <3).
• Intervention (Home Testing Protocol):
  • Devices: Portable spirometer (MIR Spirobank Smart) and FeNO monitor (NOBreath).
  • Schedule:
    • Week 1: 4 times daily (every 4-5 hours) for both spirometry and FeNO to characterize diurnal patterns.
    • Week 2: Spirometry twice daily (morning/evening); FeNO only when symptomatic.
  • Training: In-person training (median 9 mins for spirometry, 5 mins for FeNO) and app-based virtual assistance.
  • Data Collection: Participants recorded symptoms (VAS) and completed daily EQ-5D-5L health utility diaries.
• Reference Standard: An expert panel (≥2 asthma specialists) confirmed or excluded asthma based on clinical history and all in-clinic tests (BDR, BCT, blood eosinophils, in-clinic FeNO). Crucially, home test results were blinded to the panel.
• Statistical Analysis:
  • Feasibility metrics: Recruitment, retention, adherence rates, device failure.
  • Diagnostic performance: Receiver Operating Characteristic (AUROC) analysis.
  • Metrics evaluated: Variability in FEV1% predicted, PEF, and FeNO (median, max, variability).
  • Specificity threshold: Diagnostic thresholds were set to achieve ≥90% specificity (prioritizing rule-in capability).

3. Key Contributions

• Feasibility of High-Frequency Home Monitoring: Demonstrated that patients can successfully perform complex respiratory tests (spirometry and FeNO) multiple times daily at home with high adherence, challenging the notion that home testing is too burdensome.
• Superiority over PEF: Showed that home spirometry metrics (specifically FEV1 variability) outperformed traditional PEF diurnal variability in diagnostic discrimination.
• Pathway Optimization: Proposed a new diagnostic algorithm integrating home testing that significantly reduces the need for secondary care referrals and Bronchial Challenge Testing (BCT).
• Health-Economic Data: Successfully collected prospective health-economic data (EQ-5D-5L, productivity, costs) in a home-testing setting, paving the way for cost-effectiveness modeling.

4. Key Results

• Feasibility & Adherence:
  • Recruitment: 76% of eligible patients consented.
  • Adherence: Median adherence was 66.7% for spirometry and 78.5% for FeNO among those who completed at least one test.
  • Data Quality: 56.9% of spirometry readings met Grade C or higher quality standards. No devices were lost or damaged.
  • Economic Data: 71% of participants provided sufficient data for economic costing across all domains.
• Diagnostic Performance (in the 38 confirmed cases):
  • Home Spirometry: The maximum fluctuation in FEV1% predicted (FEV1%Predmax-min) showed an AUROC of 0.78. At a threshold of ≥16% fluctuation, it achieved 100% specificity and 52.4% sensitivity.
  • Home FeNO: Median FeNO showed an AUROC of 0.82. At a threshold of ≥25 ppb, it achieved 90% specificity and 77.3% sensitivity.
  • Comparison: Home FeNO and spirometry metrics demonstrated higher sensitivity than traditional clinic-based tests (e.g., BDR, in-clinic FeNO) while maintaining high specificity.
  • PEF Performance: Traditional PEF variability showed poor performance (AUROC 0.61, sensitivity only 19.1% at 100% specificity).
• Pathway Impact:
  • Integrating home testing into the BTS/NICE/SIGN 2024 pathway reduced the need for BCT by 57% to 65%.
  • The integrated pathway achieved 94.6% diagnostic accuracy compared to 89.2% for the standard pathway.
  • It was estimated that 1.5 patients need to undergo home testing to avoid one unnecessary BCT.

5. Significance and Implications

• Clinical Practice: This study provides strong evidence that moving asthma diagnosis from a "single time-point" model to a "longitudinal home monitoring" model is feasible and potentially more accurate. It suggests that home spirometry and FeNO can serve as effective triage tools to rule in asthma or rule out the need for invasive BCT.
• Healthcare Efficiency: By reducing reliance on BCT (which is resource-intensive and limited to secondary care), this approach could significantly shorten diagnostic pathways, reduce waiting times, and lower healthcare costs.
• Future Research: The authors call for adequately powered diagnostic accuracy studies to validate these findings. Future work should focus on:
  • Optimizing testing frequency (e.g., reducing from 4x daily to symptom-triggered or specific time windows).
  • Device optimization for home use.
  • Formal health-economic modeling to assess cost-effectiveness at scale.
• Policy: The findings support the potential inclusion of home-based physiological monitoring in future updates of national asthma guidelines (e.g., BTS/NICE/SIGN), similar to how ambulatory blood pressure monitoring is used for hypertension.

Conclusion: The study successfully demonstrates that home spirometry and FeNO monitoring are feasible, acceptable to patients, and offer superior diagnostic potential compared to current home-based PEF monitoring. This strategy holds promise for improving asthma diagnosis accuracy and streamlining clinical pathways.