Rationale: Poor adherence is common in difficult-to-control asthma. Distinguishing patients with difficult-to-control asthma who respond to inhaled corticosteroids (ICS) from refractory asthma is an important clinical challenge.
Objectives: Suppression of fractional exhaled nitric oxide (FeNO) with directly observed ICS therapy over 7 days can identify nonadherence to ICS treatment in difficult-to-control asthma. We examined the feasibility and utility of FeNO suppression testing in routine clinical care within UK severe asthma centers using remote monitoring technologies.
Methods: A web-based interface with integrated remote monitoring technology was developed to deliver FeNO suppression testing. We examined the utility of FeNO suppression testing to demonstrate ICS responsiveness and clinical benefit on electronically monitored treatment with standard high-dose ICS and long-acting β2-agonist treatment.
Measurements and Main Results: Clinical response was assessed using the Asthma Control Questionnaire-5, spirometry, and biomarker measurements (FeNO and peripheral blood eosinophil count). Of 250 subjects, 201 completed the test with 130 positive suppression tests. Compared with a negative suppression test, a positive test identified a FeNO-low population when adherent with ICS/long-acting β2-agonist (median, 26 ppb [interquartile range, 16–36 ppb] vs. 43 ppb [interquartile range, 38–73 ppb]) with significantly greater FEV1% (mean, 88.2 ± 16.4 vs. 74.1 ± 20.9; P < 0.01). Asthma Control Questionnaire-5 improved significantly in both groups (positive test: mean difference, −1.2; 95% confidence interval, −0.9 to −1.5; negative test: mean difference, −0.9; 95% confidence interval, −0.4 to −1.3).
Conclusions: Remote FeNO suppression testing is an effective means of identifying nonadherence to ICS in subjects with difficult-to-control asthma and the substantial population of subjects who derive important clinical benefits from optimized ICS/long-acting β2-agonist treatment.
Nonadherence with inhaled corticosteroids (ICS) in severe asthma is common and consistently associated with poor clinical outcomes. Assessment of adherence to ICS is challenging with physician estimates and patient self-report overestimating adherence when compared with objective measures. The development and validation of protocol-driven adherence assessments would minimize the risk of committing a patient to long-term biologic treatment when their disease is readily controllable with ICS.
The fractional exhaled nitric oxide suppression test, delivered using remote monitoring technology, is straightforward for the patient and the clinician, and demonstrates the value of alignment of an ICS-responsive biomarker (fractional exhaled nitric oxide) with an inhaler-monitoring technology. Profiling the fractional exhaled nitric oxide response to ICS in subjects with difficult-to-control severe asthma is a helpful part of clinical phenotyping and can identify those who are likely to respond well to high-dose ICS/long-acting β2-agonist therapy when taken regularly, and those, who despite good adherence with inhaled treatment, are likely to require additional interventions. This strategy will be of value in identifying ICS-responsive subjects before recruitment to clinical trials investigating interventions that are “add-on” treatments to standard care, and to mechanistic studies investigating “true” inhaled steroid-resistant asthma.
Nondherence with inhaled corticosteroids (ICS) in poorly controlled severe asthma is common and associated with worse clinical outcomes (1–3). Assessment of adherence to inhaled treatments is challenging: physician estimate and patient self-report consistently overestimate adherence compared with objective measures, and other surrogate measures, such as prescription collection records have limitations (4, 5). The advent of novel biologic therapies targeting type-2 cytokines in severe asthma makes identification of suboptimal adherence to ICS important so the issue can be addressed before committing patients to long-term parenteral therapy. Inhaler monitoring technologies remain the gold standard in clinical trials but clinical services have been slow to embrace these in routine care. They are perceived as potentially expensive and cumbersome, and there may be concern from healthcare professionals to challenge or change nonadherent behavior.
Suppression of fractional exhaled nitric oxide (FeNO) is an easily measured predictor of ICS response (6–8). Directly observed ICS treatment over 7 days in subjects with a high FeNO (FeNO ≥45 ppb) can identify subjects with difficult-to-control severe asthma who are responsive to ICS and nonadherent with maintenance ICS treatment (FeNO suppression test [FeNOSuppT]; see online supplement) (9). A value of greater than or equal to 45 ppb was chosen because in subjects with severe asthma, it is associated with frequent exacerbations (10) and identifies subjects who respond to ICS treatment (6, 11). Thus, in poorly controlled severe asthma and FeNO greater than or equal to 45 ppb, the key clinical issue is whether subjects are taking their ICS treatment effectively or whether they need treatment escalation.
The aim of this work was to assess the utility of home-based delivery of the FeNOSuppT using a remote monitoring technology enabling “directly observed therapy” to identify subjects who would achieve good asthma control with better inhaler technique or adherence to inhaled treatment. Some of the results of this study have been previously reported in the form of an abstract (12).
This was a prospective evaluation of the FeNOSuppT in subjects attending UK severe asthma centers in the UK Refractory Asthma Stratification Program (RASP-UK) (see online supplement) (13). The Health Research Authority Research UK Ethics Committee and the Research Leads of participating centers approved the study as a clinical service evaluation.
The inhaler monitoring technology used was the INCA device, designed to work with the Diskus inhaler (see Figure E1 in the online supplement) (14). This acoustic monitoring technology provides a time-stamped sound file that can be analyzed using an automated validated algorithm providing information on timing and inhaler technique (see Figure E2) (14). FeNO was measured using the Niox VERO and clinical services were provided with inhaler monitoring and FeNO technology with appropriate staff training.
Subjects considered for FeNOSuppT were attending a severe asthma clinic with poor asthma control despite prescription of high-dose ICS with long-acting β2-agonist (LABA) and an elevated FeNO (FeNO ≥45 ppb [high-FeNO group]). Subjects were asked to measure their FeNO daily and to take high-dose ICS for 7 days (1,000 μg fluticasone daily) via the Diskus with an INCA device, in addition to their usual ICS/LABA. Printed instruction sheets for the inhaler and the Niox VERO were given to each patient.
On return to the clinic, results from the INCA and Niox VERO were uploaded to a server using the Vitalograph IC Data Compression Utility and analyzed using the embedded sound analysis algorithm (see Figure E3). A FeNOSuppT test was defined as previously (9) but in effect, a 42% fall in FeNO between the Day 0/Day 1 and the Day 4/Day 5 mean values equates to a positive FeNOSuppT. If a patient could use the Diskus device efficiently, they were offered the opportunity to replace their current ICS/LABA with salmeterol 50 μg/fluticasone 500 μg Diskus one inhalation twice daily with an INCA device, and were informed inhaler use was being monitored for a 1-month period (see Figure E4).
After 1 month of monitoring, the relationship between the FeNOSuppT and biomarker (FeNO and peripheral blood eosinophil count [PBE]) and clinical outcomes (Asthma Control Questionnaire [ACQ-5] and spirometry) in subjects with good adherence was examined (mean adherence was 73% using biofeedback in a clinical trial setting with the INCA device, so good adherence was defined as ≥70% as best achievable in a real-world setting ).
In parallel, a subgroup of subjects with poor asthma control despite high-dose ICS/LABA treatment and FeNO less than 45 ppb at one clinical center (Belfast) (low-FeNO group) were offered INCA monitoring; if training device use was efficient after instruction, they were provided with salmeterol (50 μg/fluticasone 500 μg Diskus one inhalation twice per day) with an INCA device, to be taken twice daily for 1 month.
Normally distributed variables are presented as mean ± SD or mean difference (95% confidence interval [CI]), and independent or paired Student’s t tests are used to compare between groups. Nonnormally distributed variables are presented as median (interquartile range [IQR]) or median difference (with bootstrapped 95% CI), and the Mann-Whitney U or Wilcoxon signed rank tests are used to compare between groups. Chi-square tests are used to test for differences for categorical variables. Correlation analyses are conducted using the Spearman rank test. All statistical analyses were performed using STATA version 14.
Patient disposition and demographic details for high- and low-FeNO groups are shown in Figure 1 and Table E1.
Of 250 subjects with FeNO greater than or equal to 45 ppb who performed a FeNOSuppT, 49 of 250 (20%) subjects were unable to complete the test; 16 (6%) did not measure daily FeNO and 33 (13%) had critical inhalation errors or missed multiple doses (<70% of the additional ICS inhaler over 7 d) despite awareness that inhaler usage was being monitored, detailed verbal and written instructions, and an initial ability to measure their FeNO and use the Diskus efficiently in the clinic.
Of the 201 subjects who successfully performed a FeNOSuppT, 130 (65%) were positive and 71 negative (35%) (Figure 2, FeNO suppression curves as % of baseline; see Figure E6). Subjects with a positive FeNOSuppT had similar levels of FeNO at baseline, but were younger (P < 0.001), more likely to be female (P = 0.007), had higher rates of atopic eczema (P < 0.001), higher IgE levels (P = 0.012), and were less likely to be on maintenance prednisolone (P = 0.025) (Table 1).
|Positive FeNO Suppression Test (n = 130)||Negative FeNO Suppression Test (n = 71)||P Value|
|Female, n (%)||86 (66.2)||33 (46.5)||0.007|
|Age, yr||38.8 (15.4)||49.8 (13.8)||<0.001|
|Smoking, n (%)||0.539|
|Never smoked||100 (76.9)||54 (76.1)|
|Ex-smoker||26 (20.0)||16 (22.5)|
|Current smoker||2 (1.5)||0 (0.0)|
|Data not available: n = 3|
|Atopic, n (%)*||84 (64.6)||39 (54.9)||0.102|
|Data not available: n = 4|
|ACQ-5||3.0 (1.4)||2.5 (1.4)||0.028|
|FeNO, ppb||85 (64–125)||78 (57–118)||0.251|
|Blood eosinophils, cells ×109/L||0.50 (0.22–0.79)||0.39 (0.25–0.65)||0.428|
|Inhaled steroid (BDP equivalent μg)†||1,727 (757)||1,670 (643)||0.598|
|On maintenance prednisolone, n (%)||61 (46.9)||45 (63.4)||0.025|
|Prednisolone dose, mg||12.7 (7.9)||10.5 (6.3)||0.137|
|Hospital admission past 12 mo, n (%)||0.227|
|0||80 (61.5)||51 (71.8)|
|1||19 (14.6)||13 (18.3)|
|2||10 (7.7)||3 (4.2)|
|3+||17 (13.1)||4 (5.6)|
|Data not available: n = 4|
|Unscheduled attendance with asthma (GP or ER) past 12 mo||2 (0–6)||3 (1–5)||0.791|
|Ever admitted to an ICU, n (%)||14 (10.8)||12 (16.9)||0.249|
|Data not available: n = 4|
|Ever invasive ventilation, n (%)||8 (6.2)||6 (8.5)||0.600|
|Data not available: n = 14|
|Eczema, n (%)||31 (23.8)||4 (5.6)||<0.001|
|Data not available: n = 13|
|Nasal polyps, n (%)||30 (23.1)||24 (33.8)||0.197|
|Data not available: n = 16|
|FEV1, %||75.5 (19.7)||68.6 (19.0)||0.020|
|FVC, %||90.9 (17.0)||86.5 (21.0)||0.118|
|FEV1/FVC, %||69.2 (12.3)||64.6 (11.6)||0.013|
|IgE, kU/L||282 (93–754)||147 (72–285)||0.012|
There was no difference in baseline FeNO in subjects with a positive FeNOSuppT on maintenance prednisolone (median, 84 ppb; IQR, 65–111 ppb) compared with subjects not taking prednisolone (median, 92 ppb; IQR, 63–127 ppb), whereas PBE were significantly lower in subjects on prednisolone (median, 0.40 × 109/L [IQR, 0.19–0.61 × 109/L] vs. 0.56 × 109/L [IQR, 0.30–0.84 × 109/L]; P < 0.01). In subjects prescribed maintenance prednisolone, 61 (58%) had a positive FeNOSuppT and 45 (42%) had a negative test and there was an identical pattern of FeNO suppression in subjects taking prednisolone compared with subjects not taking prednisolone with no differences in baseline, Day 4, or Day 7 FeNO levels (see Figure E7). This was also was the case in those subjects on maintenance prednisolone with contemporaneous positive prednisolone/cortisol levels on Day 0 (n = 59, data not shown).
PBE (Figures 3A and 3B) fell significantly from Day 0 to Day 7 in those subjects who had a positive FeNOSuppT (median difference, −0.14; 95% CI, −0.03 to −0.23; P < 0.001) but not in subjects with a negative FeNOSuppT (median difference, 0.02; 95% CI, −0.12 to 0.14; P = 0.684). This difference was more apparent for subjects not on maintenance prednisolone; after a positive FeNOSuppT from Day 0 to Day 7 (median difference, −0.21; 95% CI, −0.27 to −0.11; P < 0.001) but not in those subjects with a negative FeNOSuppT (median difference, 0.06; 95% CI, −0.25 to 0.45; P = 0.842) (Figures 3C and 3D).
Of the subjects who successfully performed FeNOSuppT, 130 subjects agreed to proceed to monitoring for 1 month to assist with inhaled treatment usage (89 [68%] with a positive test and 41 [58%] with a negative test) (Table 2). All of these subjects could use the Diskus device proficiently based on monitoring during the FeNOSuppT. Of these, one patient with a negative FeNOSuppT required rescue steroids during the monitoring month and five subjects did not complete monitoring. After performing 1-month monitoring, 54 of 85 subjects (64%) with a positive FeNOSuppT and 27 of 39 subjects (69%) with a negative FeNOSuppT had greater than or equal to 70% adherence with salmeterol 50 μg/fluticasone 500 μg Diskus (mean adherence, 81 ± 12% positive test vs. 84 ± 9% negative test). For subjects who failed to achieve good adherence (≥70%) during the 1-month monitoring period, both critical inhaler technique error and missed doses were common problems (mean adherence, 45 ± 18%).
|FeNO High||P Value|
|FeNO Low (n = 40)||Positive FeNO Suppression Test (n = 89)||Negative FeNO Suppression Test (n = 41)||FeNO Low vs.Positive Suppression||FeNO Low vs. NegativeSuppression|
|Female, n (%)||30 (75.0)||58 (65.2)||18 (43.9)||0.267||0.004|
|Age, yr||46.5 (12.6)||39.1 (15.3)||47.4 (15.1)||0.009||0.769|
|Smoking, n (%)||0.313||0.403|
|Never smoked||26 (65.0)||69 (77.5)||31 (75.6)|
|Ex-smoker||13 (32.5)||18 (20.2)||10 (24.4)|
|Current smoker||1 (2.5)||2 (2.2)||0 (0.0)|
|Atopic, n (%)*||20 (50.0)||59 (66.3)||22 (53.7)||0.066||0.742|
|ACQ-5||2.6 (1.4)||2.8 (1.4)||2.7 (1.4)||0.306||0.699|
|FeNO, ppb||28 (14–36)||85 (65–122)||83 (59–114)||<0.001||<0.001|
|Blood eosinophils, ×109/L||0.24 (0.10–0.50)||0.44 (0.21–0.80)||0.36 (0.22–0.64)||0.005||0.146|
|Inhaled steroid (BDP equivalent μg)†||1,642 (400)||1,659 (662)||1,732 (748)||0.883||0.514|
|On maintenance prednisolone, n (%)||23 (57.5)||41 (46.1)||22 (53.7)||0.230||0.728|
|Prednisolone dose, mg||10.6 (5.5)||11.6 (6.2)||11.2 (7.8)||0.513||0.750|
|Hospital admission past 12 mo, n (%)||0.076||0.743|
|0||25 (62.5)||59 (66.3)||30 (73.2)|
|1||12 (30.0)||12 (13.5)||8 (19.5)|
|2||1 (2.5)||7 (7.9)||1 (2.4)|
|3+||2 (5.0)||11 (12.4)||2 (4.9)|
|Unscheduled attendance with asthma (GP or ER) past 12 mo||4 (2–10)||2 (0–7)||4 (1–6)||0.074||0.230|
|Ever admitted to an ICU, n (%)||3 (7.5)||9 (10.1)||4 (9.8)||0.637||0.718|
|Ever invasive ventilation, n (%)||2 (5.0)||6 (6.7)||1 (2.4)||0.650||0.556|
|Data not available: n = 6||0 (0.0)||5 (5.6)||1 (2.4)|
|Eczema, n (%)||6 (15.0)||23 (25.8)||3 (7.3)||0.136||0.271|
|Data not available: n = 4|
|Nasal polyps, n (%)||12 (30.0)||19 (21.3)||14 (34.1)||0.416||0.689|
|Data not available: n = 7|
|FEV1, %||75.6 (19.9)||79.2 (18.5)||68.9 (17.6)||0.341||0.126|
|FVC, %||90.0 (18.1)||93.9 (16.3)||83.5 (21.1)||0.246||0.155|
|FEV1/FVC, %||67.3 (11.6)||69.7 (10.5)||66.7 (11.0)||0.268||0.811|
|IgE, kU/L||108 (48–303)||332 (99–750)||194 (93–381)||0.021||0.079|
There was a strong relationship between Day 7 FeNO (end of FeNOSuppT) and FeNO after 1-month monitored treatment in all subjects with good adherence, and when restricting to those on maintenance prednisolone (Figure 4). There was also a significant reduction in PBE in subjects with a positive FeNOSuppT and good adherence who were not taking prednisolone (median difference, −0.25; 95% CI, −0.37 to −0.03; P < 0.001) (Figure 5C), which was not seen in those with a negative FeNOSuppT (median difference, 0.11; 95% CI, −0.13 to 0.19; P = 0.88) (Figure 5D). A similar trend was observed when subjects on prednisolone were included (median difference, −0.06; 95% CI, −0.17 to 0.02; P = 0.054) (Figure 5A); however, this just failed to reach statistical significance because, as previously noted, subjects on prednisolone had lower baseline PBE (Figure 5). Again, there was no difference in subjects with a negative FeNOSuppT (median difference, −0.03; 95% CI, −0.13 to 0.08; P = 0.71) (Figure 5B). The correlation between the Day-7 biomarkers after FeNOSuppT and post–1-month monitoring values are shown in Figure 6 (FeNO: r = 0.69; P < 0.001) (PBE: r = 0.60; P < 0.001). Post–1-month monitoring FeNO was generally lower than the Day-7 FeNO value.
We also examined the predictive value of a positive FeNOSuppT for FeNO level in subjects with good adherence after 1-month monitoring, using receiver operating characteristic analysis (see Figure E8). The area under the curve was 0.81 (95% CI, 0.72–0.91) and the optimal cutpoint for specificity and sensitivity was FeNO 35 ppb (in severe asthma, FeNO <35 ppb has been shown to be associated with significantly less airway reactivity, airflow limitation, and hyperinflation and significantly reduced emergency room and intensive care unit admissions ). The sensitivity of a positive FeNOSuppT for postmonitoring FeNO less than or equal to 35 ppb when adherent with treatment was 89% (95% CI, 76–96%) and specificity 61% (95% CI, 44–77%). In terms of predictive value, 40 of 54 positive tests had a post–1-month monitoring FeNO less than or equal to 35 ppb, and 22 of 27 negative tests had a FeNO greater than 35 ppb, giving a positive predictive value for a FeNO less than or equal to 35 ppb of 74% (95% CI, 65–81%) and a negative predictive value of 82% (95% CI, 65–91%). For the 14 of 54 subjects with FeNO greater than 35 ppb after 1-month monitoring, there was still significant suppression (baseline FeNO, 97 ppb [IQR, 81–190 ppb]; Day 7 FeNO, 40 ppb [IQR, 32–69 ppb]; Day 30 FeNO, 57 ppb [IQR, 41–68 ppb]; P < 0.001).
In the low-FeNO group (<45 ppb), who proceeded to monitoring for 1 month (n = 40, Table 2), again, despite being able to use the Diskus efficiently based on the initial dose taken in clinic and being informed and aware that they were being monitored, only 18 of 40 subjects (45%) achieved adherence greater than or equal to 70% over the 1 month monitoring period (mean adherence, 82 ± 8%). For FeNO-low subjects who failed to achieve greater than or equal to 70% adherence during the 1-month monitoring period, both critical inhaler technique error and missed doses were again common with mean adherence 35 ± 21%. For those subjects who were adherent over the 1-month period (n = 18), there was a small change in FeNO (baseline median FeNO, 32 ppb [IQR, 21–41 ppb]; postmonitoring median FeNO, 22.5 ppb [IQR, 16–35 ppb]; P = 0.045). There was no significant difference in PBE (baseline median, 0.26 [IQR, 0.17–0.52] vs. postmonth median, 0.27 [IQR, 0.10–0.48]; P = 0.776) irrespective of being prescribed maintenance prednisolone.
Lung function data and ACQ-5 scores at baseline and post–1-month monitoring in all subjects with good adherence are shown in Table 3. There was a significant improvement in FEV1 in those with a positive FeNOSuppT (mean difference, 242 ml; 95% CI, 90–395 ml) (Table 3) which was not seen in subjects with a negative FeNOSuppT (mean difference, 122 ml; 95% CI, −143 to 389 ml) (Table 3). There was a significant improvement in ACQ-5 in both suppressor and nonsuppressor groups, which was numerically greater in subjects with a positive FeNOSuppT (mean difference, −1.2; 95% CI, −0.9 to −1.5) compared with those with a negative FeNOSuppT test (mean difference, −0.9; 95% CI, −0.4 to −1.3) and there was a significant correlation between % fall in FeNO and % improvement in ACQ-5 in all FeNO high subjects (r = 0.39; P < 0.001). For the 14 of 54 subjects with a positive FeNOSuppT and FeNO greater than 35 ppb after 1-month monitoring, there were significant improvements in FEV1% (81.9 ± 20.1% to 91.9 ± 19.2%; P = 0.05) and ACQ5 (2.49 ± 1.5 to 1.65 ± 0.99; P < 0.05). Five patients had a negative FeNOSuppT and postmonitoring FeNO less than 35 ppb, and these patients generally displayed small improvements in lung function and asthma symptoms after the monitoring period. There was no change in ACQ-5 with good monitored adherence in subjects with initial FeNO less than 45 ppb (Table 3) and no improvement in lung function (mean difference, −114 ml; 95% CI, −267 to 37 ml) (Table 3). The minimally clinical important change for ACQ-5 of 0.5 was seen in 40 of 54 (FeNO >45 ppb and positive FeNOSuppT), 14 of 27 (FeNO >45 ppb and negative FeNOSuppT), and 5 of 18 (FeNO <45 ppb) (chi-square between group difference, P = 0.015).
|FeNO ≥45 ppb, Positive Suppression Test (n = 54)||FeNO ≥45 ppb, Negative Suppression Test (n = 27)||FeNO <45 ppb (n = 18)|
|Baseline (Day 0)||Postmonitoring Period||P Value||Baseline||Postmonitoring Period||P Value||Baseline||Postmonitoring Period||P Value|
|FEV1, L||2.65 ± 0.87||2.89 ± 0.82||0.003||2.28 ± 0.67||2.40 ± 0.78||0.35||2.29 ± 0.42||2.18 ± 0.42||0.13|
|FEV1% predicted||80.1 ± 16.4||88.2 ± 16.4||0.001||70.1 ± 16.0||74.1 ± 20.9||0.30||74.5.0 ± 12.0||71.0 ± 14.5||0.15|
|FVC, L||3.69 ± 0.97||3.88 ± 0.98||<0.001||3.50 ± 0.84||3.45 ± 0.91||0.71||3.42 ± 0.67||3.35 ± 0.61||0.44|
|FVC % predicted||93.3 ± 13.2||98.1 ± 14.0||<0.001||86.1 ± 15.9||85.4 ± 19.8||0.83||89.3 ± 11.0||87.6 ± 10.6||0.50|
|FEV1/FVC ratio||71.2 ± 8.8||74.7 ± 9.1||0.049||64.6 ± 8.9||69.2 ± 12.5||0.12||66.9 ± 10.0||65.2 ± 9.9||0.08|
|ACQ-5||2.76 ± 1.25||1.55 ± 1.21||<0.001||2.81 ± 1.61||1.96 ± 1.43||<0.001||1.96 ± 1.35||1.79 ± 1.32||0.32|
This study demonstrates in subjects with difficult-to-control severe asthma and FeNO greater than or equal to 45 ppb, 65% had a positive FeNOSuppT and with effective adherence to LABA/ICS during a 1-month monitored period, there were significant improvements in symptoms and lung function and FeNO was maintained at target levels associated with reduced exacerbation, emergency room attendances, and ICU admissions (15, 16). In contrast, among those with a negative FeNOSuppT, there was a lesser reduction in FeNO despite taking high-dose ICS/LABA efficiently, with no improvement in lung function and less improvement in symptoms.
The original description of the FeNOSuppT previously used physician directly observed treatment over 7 days and defined a positive FeNOSuppT for nonadherence on poor prescription filling. The remote monitoring acoustic technology in this study effectively delivers directly observed treatment by time-stamping inhaler activation and analyzing inhalation technique, which also identifies “nonintentional” nonadherence, where common critical inhaler errors prevent effective treatment. Given these patients were prescribed high-dose ICS/LABA at the time of FeNOSuppT, we believe the suppression of FeNO with effectively administered ICS/LABA treatment reflects prior inefficient ICS treatment caused by intentional and nonintentional nonadherence.
In subjects with a positive FeNOSuppT, there was also a significant fall in PBE consistent with both biomarkers being ICS responsive when adherent with monitored treatment. Composite biomarker profiling using FeNO and PBE allows better prognostic risk stratification with highest risk seen when both type 2 biomarkers are high and vice versa (17, 18), suggesting that for subjects with a positive FeNOSuppT and resultant biomarker low profile there should be a parallel risk reduction for exacerbations. The longer term clinical and adherence outcomes for subjects characterized using FeNOSuppT in a severe asthma population are currently being studied (clinicaltrials.gov NCT02307669), but it is worth commenting that a small number of subjects, despite a good response to monitored treatment in terms of FeNO, ACQ-5, and lung function improvement, have a persistently elevated peripheral PBE. This suggests that the biologic driver of PBE in these subjects may not be as ICS responsive as FeNO, and we are also currently exploring the clinical significance of this “dissociated” biomarker profile in terms of exacerbation risk and clinical outcome (clinicaltrials.gov NCT02717689). However, our data suggest that the biomarker profile (FeNO and PBE) after 1 week of FeNOSuppT is closely related to the profile when taking optimized ICS/LABA treatment, thus facilitating identification of subjects where adherence intervention to optimize inhaled treatment may be of most value before considering treatment escalation but also potentially identifying those subjects who are likely remain biomarker high despite optimized ICS/LABA treatment and suitable for novel type 2 biologic therapies.
Near maximal FeNO suppression has also been shown after 7 days of high-dose ICS treatment in mild asthma (7, 19, 20) and our data suggest that similar maximal suppression is seen in subjects with more severe asthma given the strong correlation between Day 7 FeNO post-FeNOSuppT and postmonitoring FeNO. In those subjects despite having a positive test and FeNO greater than 35 ppb after monitoring, significant falls in both FeNO was seen compared with baseline with improvements in lung function and symptom scores consistent with prior ICS nonadherence and suggesting a period of optimized inhaled treatment with clinical monitoring before treatment escalation is appropriate. The same proportion of subjects on maintenance prednisolone had positive FeNOSuppT compared with those not on prednisolone, which we believe reflects unidentified suboptimal baseline adherence to inhaled treatment and progression to oral corticosteroids. Key questions are whether this progression would have been initially prevented with optimized inhaled treatment and if these subjects can subsequently withdraw prednisolone. We are currently exploring the longer term outcome of this subgroup of patients.
The availability of novel biologic therapies targeting type 2 cytokines makes identification of suboptimal adherence to ICS important so this can be targeted before treatment escalation. An attractive proposition is to move away from imperfect surrogate measures of adherence (e.g., patient self-report, physician impression, prescription records) to using an ICS-responsive biomarker (FeNO) as part of a clinical phenotyping strategy and precision medicine delivery. The FeNO-low group (FeNO <45 ppb) demonstrates small reductions in FeNO with monitored optimized treatment with FeNO in a similar range to those subjects with a positive FeNOSuppT and optimized treatment. There was no change in PBE, ACQ-5 or lung function, which may reflect the fact that this low-FeNO group are more adherent to background ICS treatment and the potential for further clinical improvement with optimized ICS/LABA in this FeNO-low group is less.
A strength of this data is that it occurred in a “real world” setting, bypassing the challenging aspect of engaging a nonadherent difficult-to-control asthma population in a clinical trial (21). Only 16 patients were unable or forgot to perform daily FeNO during the 7-day home FeNOSuppT suggesting that this is not a major barrier to domiciliary delivery. However, inadequate use of the monitored ICS over a 7-day period was substantially more common (33 of 49; 67%) despite being able to use the inhaler proficiently at the clinic. These data are still useful clinically because inability to take 7-day monitored treatment immediately identifies a major issue with adherence in these patients. As well as providing insight into ICS therapeutic response in a short period of time, this approach identifies subjects who can use a particular inhaler efficiently and wish to engage with a monitoring strategy to assist them with their inhaler use. However, notably 70 of 169 subjects (41%) failed to take greater than or equal to 70% or complete 1-month monitoring of inhaled treatment despite being proficient in inhaler use and keen for support, suggesting barriers to even short-term use of technological support to assist with inhaled treatment adherence. If these barriers could be identified and addressed, there could be substantial gains with optimized inhaled treatment in this poorly controlled, high-risk asthma population.
Defining the best intervention to change nonadherent behavior is out or the scope of this study, but a recent systematic review of mobile text messaging in chronic disease management confirmed improved adherence rates from 50 to 67.8% (22), and simple reminder systems have also been shown to improve inhaled maintenance treatment in asthma (23) suggesting the gains are potentially large in this population. Multiple pharmaceutical companies are engaged with connected inhaler platforms to target adherence and utility of one of these systems aligned with exhaled nitric oxide response is currently under clinical trial (clinicaltrials.gov NCT03380429).
Formal cost-effectiveness analysis of biomarker-based assessments with adherence monitoring is required; however, this seems likely by identifying subjects who may achieve adequate asthma control without the need for treatment escalation to expensive biologic agents. Subjects with a positive FeNOSuppT were younger with more eczema and higher IgE suggesting greater ICS responsiveness in this group, although hospital admissions were equally prevalent in the high-FeNO group with positive and negative FeNOSuppT. In the NHLBI Severe Asthma Research Program, a high FeNO (>35 ppb) was associated with greater emergency room visits and hospital and ICU admissions and again in a younger, more atopic patient cohort (15). If adherence could be satisfactorily addressed in this ICS-responsive FeNO high difficult-to-control asthma population, there could potentially be a substantial impact on hospital admission rates.
In summary, we have demonstrated that and FeNOSuppT can be delivered using remote monitoring technology in routine clinical care in specialist severe asthma services in the United Kingdom. Short-term profiling of biomarker responses to ICS exposure in subjects with difficult-to-control severe asthma is a helpful part of clinical phenotyping to identify those who are likely to respond better to high-dose ICS/LABA therapy when used regularly and those who, despite good adherence with inhaled treatment, are likely to require additional treatment. In addition, this approach may be of value in identifying ICS-responsive subjects before recruitment to clinical trials investigating interventions that are “add-on” treatments to standard care (ICS/LABA) and also to studies investigating “true” ICS-resistant disease. Future studies are required to identify the optimal intervention to maintain ongoing adherence in a difficult-to-control severe asthma population, but understanding the potential therapeutic benefit in an individual patient is a useful part of routine care.
The authors are grateful to Kathy Hetherington for assistance in project support and the medical teams who helped integrate these tests into their clinical practice, in particular: Belfast Health & Social Care Trust (Dr. Claire A. Butler, Dr. Jacqui Gamble, Kirsty Honeyford), Oxford University Hospitals NHS Trust (Luisa Vaz Batista, Claire Connolly, Katie Borg), Glenfield Hospital, University Hospitals of Leicester NHS Trust (Michelle Craner, Claire Boddy), Wythenshawe Hospital, University Hospitals of South Manchester NHS Trust (Leanne-Jo Homes), Gartnavel General and Glasgow Royal Infirmary Hospitals, Greater Glasgow Health Board (Dr. Douglas Cowan, Dr. Jieqiong Freda Yang, Diane Murray, Femke Steffenson), and Heartlands Hospital, Heart of England NHS Foundation Trust (Verity Mitchell).
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The service evaluation was embedded in the UK Refractory Asthma Stratification Program with program support from Aerocrine AB and Vitalograph.
Author Contributions: All authors contributed to study design and set-up, provision of data, and review of the manuscript.
This article has an online supplement, which is accessible from this issue's table of contents at www.atsjournals.org.
Originally Published in Press as DOI: 10.1164/rccm.201806-1182OC on October 19, 2018