Evidence reviews for pulmonary function monitoring in asthma

Evidence reviews for pulmonary function monitoring in asthma

Asthma: diagnosis, monitoring and chronic asthma management (update)

Evidence review M

NICE Guideline, No. 245

London: National Institute for Health and Care Excellence (NICE); 2024 Nov.

ISBN-13: 978-1-4731-6626-4

1. Pulmonary function monitoring

1.1. Review question

In people with asthma, what is the clinical and cost-effectiveness of using measures of pulmonary function assessing asthma control (for example, spirometry and peak expiratory flow) to monitor asthma?

1.1.1. Introduction

It is not clear whether treatment of asthma should be adjusted because of symptoms alone or whether objective measures should also be used. Symptoms are of paramount importance to the person with asthma, but the main symptoms of asthma (cough, breathlessness) can have other causes and there is a danger of overtreatment if dosages are increased too readily. Conversely, some people with asthma do not sense narrowing of their airways until it has become marked, placing them at risk of a severe attack. The purpose of this review is to assess whether regular measurement of airflow obstruction, using either spirometry or peak expiratory flow (PEF), is useful in guiding asthma therapy

1.1.2. Summary of the protocol

For full details see the review protocol in Appendix A.

Table 1

PICO characteristics of review question.

1.1.3. Methods and process

This evidence review was developed using the methods and process described in Developing NICE guidelines: the manual. Methods specific to this review question are described in the review protocol in appendix A and the methods document. Due to the nature of the interventions being assessed in this evidence review, adherence to monitoring strategies within trials has been carefully noted during data extraction; any limitations have been assessed in domain 2b of the Cochrane risk of bias tool.

Declarations of interest were recorded according to NICE’s conflicts of interest policy.

This evidence review is an update of chapter 24 of the previous Asthma guideline NG80.

1.1.4. Effectiveness evidence

1.1.4.1. Included studies

Ten trials were included in the review (Adams, et al., 2001, Buist, et al., 2006, Charlton, et al., 1990, Cote, et al., 1997, Cowie, et al., 1997, Kaya, et al., 2009, Lopez-Vina, et al., 2000, Turner, et al., 1998, Wensley, et al., 2004, Yoos, et al., 2002)all of which focussed on PEF monitoring versus usual care (symptom-based monitoring). Seven studies(Adams et al., 2001, Buist et al., 2006, Cote et al., 1997, Cowie et al., 1997, Kaya et al., 2009, Lopez-Vina et al., 2000) were conducted in adults and two(Wensley et al., 2004, Yoos et al., 2002) were conducted in children and young people; one study (Charlton et al., 1990) was conducted in children and adults. These are summarised in Table 2 below. Evidence from these studies is summarised in the clinical evidence summary (Table 3). There was no evidence identified on spirometry monitoring.

All the studies included in this review were included previously in chapter 24 (NG80); no additional trials have been identified.

See also the study selection flow chart in Appendix C, study evidence tables in Appendix D, forest plots in Appendix E, and GRADE tables in Appendix F.

1.1.4.2. Excluded studies

See the excluded studies list in Appendix I.

1.1.5. Summary of studies included in the effectiveness evidence

Table 2

Summary of studies included in the evidence review.

See Appendix D for full evidence tables.

1.1.6. Summary of the effectiveness evidence

Table 3

Clinical evidence summary: PEF monitoring versus usual care (symptom monitoring) in adults.

Table 4

Clinical evidence summary: PEF monitoring versus usual care (symptom monitoring) in children.

Table 5

Clinical evidence summary: PEF monitoring at symptom-time versus symptom monitoring in children.

See Appendix F for full GRADE tables

1.1.7. Economic evidence

1.1.7.1. Included studies

No health economic studies were included.

1.1.7.2. Excluded studies

No relevant health economic studies were excluded due to assessment of limited applicability or methodological limitations.

See also the health economic study selection flow chart in Appendix G.

1.1.8. Summary of included economic evidence

None.

1.1.9. Economic model

This area was not prioritised for new cost-effectiveness analysis.

1.1.10. Unit costs

Relevant unit costs are provided below to aid consideration of cost effectiveness.

Table 6

PEF per-test cost.

1.1.11. Evidence statements

1.1.11.1. Economic

No relevant economic evaluations were identified.

1.2. The committee's discussion and interpretation of the evidence

1.2.1. The outcomes that matter most

The committee considered the outcomes of mortality, unscheduled healthcare utilisation, severe asthma exacerbations, quality of life, asthma control, lung function, dose of regular asthma therapy/preventer medication, symptoms, reliever/rescue medication and time off school/work. For the purposes of decision making, all outcomes were considered equally important and were rated as critical.

For this review there was no outcome data for mortality, symptoms or asthma control based on the recommended questionnaires (ACT; CACT; ACQ; PACQ; RCP-3).

1.2.2. The quality of the evidence

There were 10 RCTs included in the clinical evidence of this review, all of which investigated the effectiveness of PEF-based monitoring versus symptom-based monitoring of asthma. The review was stratified by population age: adults (>16years) and children/young people (5–16 years). No evidence was identified on the value of measuring spirometry at regular intervals.

The quality of the outcomes varied from low to very low quality. Outcomes were downgraded based on the presence of imprecision or concerns about risk of bias due to, for example, lack of randomisation information, low compliance to the intervention and/or missing data.

1.2.3. Benefits and harms

When assessing the clinically significant impact of the evidence included, the GC agreed an approach for use of MIDs. For continuous outcomes, published MIDs were applied for SF-36 (MID =2 for physical total score, 3 for mental total score) and FEV1 (L) (0.23). In the absence of published MIDs, default calculations for MID were applied based on baseline SD (where available) for the rest of the continuous outcomes. For dichotomous outcomes a threshold of 100/1000 people for changes in absolute effects was applied when assessing the following outcomes: unscheduled visits to doctors, emergency GP visits and time off school/work. A threshold of 30/1000 people for changes in absolute effects was applied when assessing the following outcomes: asthma exacerbations; emergency department visits; and hospital admissions; this is because the committee considered small differences between the intervention and comparison groups likely to be important.

Adults

In the adult population there was a clinically significant benefit of PEF-based monitoring seen for one outcome, unscheduled healthcare utilisation (urgent asthma treatment), based on one RCT. However, the certainty of the evidence was low. The remainder of the RCTs demonstrated a clinical benefit favouring symptoms-based monitoring for several outcomes: unscheduled healthcare utilisation (ED visits and unscheduled doctor visits), severe asthma exacerbations, quality of life (SF-36 physical total score and mental total score) and lung function (FEV, L). The GC considered that PEF monitoring helps to identify exacerbations at an earlier stage and the increase in healthcare utilisation may therefore not necessarily be a detrimental finding. The lower quality of life measurement with PEF monitoring was unexpected but it was noted that some people might become anxious if their PEF level is not consistently at its best, and that regular recording of PEF measurements is an imposition, either of which may explain the finding. The committee were mindful that these outcomes were all taken from small studies of low to very low quality due to imprecision and risk of bias.

The remaining outcomes showed no clinically significant difference between PEF and symptom-based monitoring, including various measures of asthma related healthcare utilisation (mean ER visits and mean hospital admissions, hospital admissions as events and total asthma-related health-care utilisation) lung function (FEV1% predicted) and time off work.

Children

A clinically significant difference favouring symptom-based monitoring was found for: severe asthma exacerbations only (very low certainty evidence). The GC noted that PEF monitoring may be helping identify exacerbations at an earlier stage, although it is equally plausible that PEF monitoring is causing over-anxiety about symptoms in some people and leading to unnecessary treatment. There were no clinically significant differences seen for any other outcome: unscheduled healthcare utilisation, lung function, and time off school (low to very low quality).

The committee acknowledged that PEF monitoring is embedded in healthcare, with routine use in clinics, emergency departments and as part of asthma action plans. This, however, was not necessarily indicative of its effectiveness. They agreed that there was insufficient evidence of benefit to make a recommendation favouring the routine use of PEF-monitoring.

1.2.4. Cost effectiveness and resource use

No relevant published health economic analyses were identified for this review. The unit cost of PEF was presented to aid committee consideration of cost effectiveness. The unit cost of undertaking PEF for diagnostic purposes was £25.78 for adults and £25.88 for children. This included the health care professional time for instructing people on home testing and interpreting the result (£21.13) as well as the flowmeter (£4.65/£4.75 for adults/paediatrics respectively).

The committee discussed the clinical evidence and agreed that it was insufficient to make a positive recommendation, so they recommended against using PEF for monitoring asthma. The committee acknowledged that PEF is typically used in current practice, so the recommendation represents a significant change. The recommendations are expected to reduce the use of PEF for monitoring in favour of using an asthma control questionnaire and FeNO. Given the lack of benefits identified in this review, this is not expected to cause harm to people and could save resource for the NHS that could be reinvested in a more effective monitoring plan.

1.2.5. Other factors the committee took into account

The committee were mindful that some people’s symptoms do not correlate well with their lung function measurements. This may result in an underappreciation of the severity of an exacerbation, or conversely in over-sensitivity where symptoms associated with very little change in lung function are perceived as severe. In such people PEF monitoring can be helpful. The committee were therefore reluctant to make a recommendation advising against regular PEF monitoring in all circumstances. However, as the evidence showed no overall benefit for the majority of people with asthma they recommended against its routine use.

No evidence was available on the use of spirometry for monitoring. The GC noted that it has been suggested to be a useful routine measurement but they noted that it is time-consuming and in their experience is unlikely to provide helpful information in the absence of changes in symptoms or other measurements. They therefore made no recommendation on the routine use of spirometry.

1.2.6. Recommendations supported by this evidence review

This evidence review supports recommendation 1.5.3.

1.3. References

Adams RJ, Boath K, Homan S, et al (2001) A randomized trial of peak-flow and symptom-based action plans in adults with moderate-to-severe asthma Respirology 6 (4): 297–304. [PubMed: 11844120]
Buist AS, Vollmer WM, Wilson SR, et al (2006) A Randomized Clinical Trial of Peak Flow versus Symptom Monitoring in Older Adults with Asthma American Journal of Respiratory and Critical Care Medicine 174 (10): 1077–1087. [PMC free article: PMC2648108] [PubMed: 16931634]
Charlton I, Charlton G, Broomfield J, et al (1990) Evaluation of peak flow and symptoms only self management plans for control of asthma in general practice British Medical Journal 301 (6765): 1355. [PMC free article: PMC1664498] [PubMed: 2148702]
Cote J, Cartier A, Robichaud P, et al (1997) Influence on asthma morbidity of asthma education programs based on self-management plans following treatment optimization American Journal of Respiratory and Critical Care Medicine 155 (5): 1509–1514. [PubMed: 9154850]
Cowie RL, Revitt SG, Underwood MF, et al (1997) The Effect of a Peak Flow-Based Action Plan in the Prevention of Exacerbations of Asthma Chest 112 (6): 1534–1538. [PubMed: 9404750]
Jones K, Birch S, Dargan A, et al Unit Costs of Health and Social Care 2022. Available from: https://www.pssru.ac.uk/unitcostsreport/ Last accessed: 26/04/2024.
Kaya Z, Erkan F, Ozkan M, et al (2009) Self-Management Plans for Asthma Control and Predictors of Patient Compliance Journal of Asthma 46 (3): 270–275. [PubMed: 19373635]
Lopez-Vina A, Del Castillo-Arevalo F (2000) Influence of peak expiratory flow monitoring on an asthma self-management education programme Respiratory Medicine 94 (8): 760–766. [PubMed: 10955751]
National Institute for Health and Care Excellence. Developing NICE guidelines: the manual. . London. National Institute for Health and Care Excellence, 2014. Available from: http://www.nice.org.uk/article/PMG20/chapter/1%20Introduction%20and%20overview [PubMed: 26677490]
NHS Supply Chain Catalogue. NHS Supply Chain, 2022. Available from: http://www.supplychain.nhs.uk/
Turner MO, Taylor D, Bennett RON, et al (1998) A Randomized Trial Comparing Peak Expiratory Flow and Symptom Self-management Plans for Patients with Asthma Attending a Primary Care Clinic American Journal of Respiratory and Critical Care Medicine 157 (2): 540–546. [PubMed: 9476870]
Wensley D, Silverman M (2004) Peak Flow Monitoring for Guided Self-management in Childhood Asthma American Journal of Respiratory and Critical Care Medicine 170 (6): 606–612. [PubMed: 15184205]
Yoos HL, Kitzman H, McMullen A, et al (2002) Symptom monitoring in childhood asthma: a randomized clinical trial comparing peak expiratory flow rate with symptom monitoring Annals of Allergy, Asthma & Immunology 88 (3): 283–291. [PubMed: 11926622]

Appendices

Appendix H. Economic evidence tables

None.

Appendix I. Excluded studies

Clinical studies

Table 13

Studies excluded from the clinical review.

Health economic studies

Published health economic studies that met the inclusion criteria (relevant population, comparators, economic study design, published 2006 or later and not from non-OECD country or USA) but that were excluded following appraisal of applicability and methodological quality are listed below. See the health economic protocol for more details.

None.

Final

BTS/NICE/SIGN collaborative guideline NG245

Evidence reviews underpinning recommendation 1.5.3 in the guideline

Developed by BTS, NICE and SIGN

Disclaimer: The recommendations in this collaborative guideline represent the view of BTS, NICE and SIGN, arrived at after careful consideration of the evidence available. When exercising their judgement, professionals are expected to take this guideline fully into account, alongside the individual needs, preferences and values of their patients or service users. The recommendations in this guideline are not mandatory and the guideline does not override the responsibility of healthcare professionals to make decisions appropriate to the circumstances of the individual patient, in consultation with the patient and/or their carer or guardian.

Local commissioners and/or providers have a responsibility to enable the guideline to be applied when individual health professionals and their patients or service users wish to use it. They should do so in the context of local and national priorities for funding and developing services, and in light of their duties to have due regard to the need to eliminate unlawful discrimination, to advance equality of opportunity and to reduce health inequalities. Nothing in this guideline should be interpreted in a way that would be inconsistent with compliance with those duties.

This collaborative guideline covers health and care in England and Scotland. Decisions on how they apply in other UK countries are made by ministers in the Welsh Government and Northern Ireland Executive. This collaborative guideline is subject to regular review and may be updated or withdrawn.

Bookshelf ID: NBK612148PMID: 39965063

Table 1PICO characteristics of review question

Population	People with asthma All ages, stratified into the following 2 different groups: Children/young people (5–16 years old) Adults (>17 years old) Exclusions: Severe asthma Children <5 years
Interventions	Monitoring lung function using the following tests, and using the outcomes to adjust management/therapy according to physician decision or personalised treatment plan Spirometry (FEV1; FEV1/FVC; Flow loop measures) PEF
Comparisons	Comparison of adjustment of asthma therapy based on lung function tests to: Usual care: e.g. clinical symptoms according to guidelines (including BTS/SIGN, GINA) Asthma control or QOL questionnaires Comparison of adjustment of asthma therapy based on: Spirometry versus PEF
Outcomes	Mortality Unscheduled healthcare utilisation (ED/A&E visit; hospital admissions; GP out of hours or walk-in centre) Severe asthma exacerbations (defined as asthma exacerbations requiring oral corticosteroid use- dichotomous outcome at ≥6 months, latest time point if more than one) Asthma control (assessed by validated questionnaires (ACT; CACT; ACQ; PACQ; RCP-3; continuous outcome at ≥3 months) Quality of life (QoL assessed via any validated scale including asthma specific questionnaires: AQLQ; pAQLQ; St George’s respiratory questionnaire); (continuous outcome at ≥3 months) Lung function (FEV1, PEF) Symptoms (annual symptom free days) Dose of regular asthma therapy / preventer medication (ICS dose) Reliever/Rescue medication (SABA use; continuous outcome at ≥3months) Time off school or work
Study design	RCTs SRs of RCTs

Table 2Summary of studies included in the evidence review

Study

Intervention and comparison

Population

Outcomes

Comments

PEF based monitoring

Adams 2001(Adams et al., 2001)

PEF monitoring (self-management plan activated by a fall in PEF).

Usual care (self-management plans activated by increase in symptoms)

Adults aged 16–70 years with moderate-severe asthma (not defined).

N=134

Ethnicity: not reported

Education level: not reported

Language: English

Australia

Unscheduled healthcare utilisation (emergency department visit, hospital admissions)

Lung function (FEV₁)

Time off work

12 months follow-up

Understanding of self-management protocols was 76–78%

Population indirectness: participants described as moderate-severe asthma; baseline characteristics suggestive of severe

Buist 2006(Buist et al., 2006)

PEF monitoring (twice daily or as-needed) plus education including inhaler technique and asthma action plan.

Usual care (symptom based monitoring, plus education including inhaler technique and asthma action plan)

Adults aged 50–92 years using medication suggestive of moderate-severe asthma

N=296

Ethnicity: not reported

Education level: not reported.

Language: English

USA

Unscheduled healthcare utilisation (rate of acute asthma care: hospital, ED, other acute care)

6, 24 months follow-up

Population indirectness: participants described as moderate-severe asthma

Charlton 1990(Charlton et al., 1990)

PEF monitoring (self-management plan activated by PEF

Usual care (symptom based self-management action plan)

Children and adults attending an asthma clinic (no baseline characteristics)

N=115 (46 children and 69 adults)

Ethnicity: not reported

Education level: not reported

Language: English

England

Severe asthma exacerbations (needing oral steroids) (adults and children outcomes reported separately)

12 month follow-up

No baseline characteristics

Cote 1997(Cote et al., 1997)

PEF monitoring (twice per day and reviewed at follow-up visits, with PEF-directed 4 step self-action plan.

Usual care (symptom based self-management plan)

Adults with moderate to severe asthma, aged ≥16 y, and taking daily anti-inflammatory agent

N=95

Ethnicity: not reported

Education level: not reported

Language: English

Canada

Unscheduled healthcare utilisation (hospital admissions, emergency room visit)

Time off school/work (days lost from work/school)

12 months follow-up

Cowie 1997(Cowie et al., 1997)

PEF monitoring (PEF-based action plan)

Usual care (symptom based action plan)

Adults and adolescents who had received urgent treatment at the emergency department for asthma exacerbations in the preceding 12 months and used asthma medication

Mean (SD) age in years =39.1 (14.41); 36.8 (16.50

N=91 (completed and included in analysis)

Ethnicity: not reported

Education level: not reported

Language: English

Canada

Unscheduled healthcare utilisation [number of people attending for urgent treatment of asthma; hospital admissions (total number of admissions for asthma)]

6 months follow-up

Kaya 2009(Kaya et al., 2009)

PEF monitoring (PEF-based action plan)

Usual care (symptom based self-management)

Adults, mean age=43 years (SD 10.48)

According to GINA guidelines, 14.3% of the patients were classified as mild (n = 9), 47.6% (n = 30) as moderate, and 38.1% (n = 24) as severe persistent asthmatics.

N=63

Ethnicity: not reported

Education level: mixed

Language: not reported

Turkey

Health related QoL (SF-36)

Lung function (FEV1 predicted)

3, 6 months follow-up

Followed up for 12 months but compliance decreased after 6 months, no 12 months outcomes reported

Population indirectness: downgraded because 38.1% severe asthma

Lopez-Vina 2000 (Lopez-Vina et al., 2000)

PEF monitoring (PEF-based self-management plan)

Usual care (symptom based self-management plan)

Adults aged 17 to 65 years who had required emergency asthma treatment in previous 18 months.

N= 100

Ethnicity: not reported

Education level: not reported

Language: not reported

Spain

Unscheduled healthcare utilisation (hospital admissions, visits to emergency ward)

Lung function (FEV₁% predicted)

Time off school/work (absenteeism from work/school)

12 months follow-up

Turner 1998(Turner et al., 1998)

PEF monitoring (self-management plan based on PEF monitoring)

Usual care (self-management plan based on symptom monitoring)

Adults aged 18–55 years.

N=92

Ethnicity: mixed

Education level: not reported

Language: English

Canada

Unscheduled healthcare utilisation (hospitalisation, emergency department visits, unscheduled doctor visits)

Severe asthma exacerbations (prednisone treatments)

Time off school or work (days lost school/work)

6 months follow-up

Wensley 2004(Wensley et al., 2004)

PEF monitoring (PEF-based action plan plus symptom monitoring)

Usual care (symptom based management)

Children aged 7 to 14 (median 11, 12 years)

N=90

Ethnicity: not reported

Education level: not reported

Language: not reported

England

Unscheduled healthcare utilisation (hospital admissions, attendance at A&E. emergency GP visits)

Time off school or work (absent from school)

12 weeks follow-up

Yoos 2002(Yoos et al., 2002)

PEF monitoring (Twice daily PEF monitoring and symptom-time PEF monitoring in two arms) with personal action plan zones based on symptoms and PEF.

Usual care, with personal action plan based on symptoms only

Children and adolescents aged 6–19 years

N=168

Ethnicity: mixed

Education level: mixed

Language: English

USA

Lung function (FEV₁% predicted)

3 months follow-up

Proportion of people aged 17–19 years not reported, no mean (SD) for age given

Table 3Clinical evidence summary: PEF monitoring versus usual care (symptom monitoring) in adults

Outcomes	№ of participants (studies) Follow-up	Certainty of the evidence (GRADE)	Relative effect (95% CI)	Anticipated absolute effects
Outcomes	№ of participants (studies) Follow-up	Certainty of the evidence (GRADE)	Relative effect (95% CI)	Risk with symptoms monitoring: adults	Risk difference with PEF	Comments
Unscheduled healthcare utilisation (total asthma-related, lower is better, 24 months)	294 (1 RCT)	⨁⨁◯◯ Low^a^,^b	-	The mean unscheduled healthcare utilisation (total asthma-related health care utilisation, lower is better, 24 months) was 1.5	MD 0.11 lower (0.59 lower to 0.37 higher) No clinical difference	MID=1.23 (calculated as baseline SD of both arms/2)
Unscheduled healthcare utilisation (urgent asthma treatment, lower is better, 6 months)	91 (1 RCT)	⨁⨁◯◯ Low^c^,^d	RR 0.35 (0.14 to 0.89)	311 per 1,000	202 fewer per 1,000 (268 fewer to 34 fewer) Clinically important benefit of PEF	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 30 per 1000
Unscheduled healthcare utilisation (hospital admissions, events, lower is better, 6–12 months)	417 (4 RCTs)	⨁◯◯◯ Very low^b^,^e^,^f	RR 0.80 (0.35 to 1.83)	51 per 1,000	10 fewer per 1,000 (50 fewer to 30 more) No clinical difference	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 30 per 1000
Unscheduled healthcare utilisation (mean hospital admissions over 1 year, lower is better, 12 months)	95 (1 RCT)	⨁◯◯◯ Very low^g^,^h	-	The mean unscheduled healthcare utilisation (mean hospital admissions over 1 year, lower is better, 12 months) was 0.09	MD 0.05 lower (0.16 lower to 0.06 higher) No clinical difference	MID = 0.138 (SDs of both arms at follow-up/2)
Unscheduled healthcare utilisation (ED visits, lower is better, 6–12 months)	326 (3 RCTs)	⨁◯◯◯ Very low^f^,ⁱ^,^j	RR 1.63 (0.39 to 6.77)	59 per 1,000	37 more per 1,000 (36 fewer to 339 more) Clinically important benefit of symptom monitoring	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 30 per 1000
Unscheduled healthcare utilisation (mean number of ED visits, lower is better, 12 months)	95 (1 RCT)	⨁⨁◯◯ Low^g	-	The mean unscheduled healthcare utilisation (mean number of ED visits, lower is better, 12 months) was 0.7	MD 0 (0.54 lower to 0.54 higher) No clinical difference	MID=0.675 (SDs of both arms at follow-up/2)
Unscheduled healthcare utilisation (unscheduled doctor visits, lower is better, 6 months)	92 (1 RCT)	⨁◯◯◯ Very low^d^,^k	RR 1.55 (0.84 to 2.86)	250 per 1,000	138 more per 1,000 (40 fewer to 465 more) Clinically important benefit of symptom monitoring	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 100 per 1000
Severe asthma exacerbations (taking oral steroids, lower is better, 6 months)	152 (2 RCTs)	⨁◯◯◯ Very low^f^,^l^,^m	RR 1.28 (0.29 to 5.57)	160 per 1,000	45 more per 1,000 (114 fewer to 733 more) Clinically important benefit of symptom monitoring	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 30 per 1000
Quality of life (SF-36, range 0–100, higher is better, 6 months) - Physical total score	63 (1 RCT)	⨁◯◯◯ Very lowⁿ^,^o^,^p	-	The mean quality of life (SF-36, range 0–100, higher is better, 6 months) - Physical total score was 65.3	MD 6.49 lower (17.18 lower to 4.2 higher) Clinically important benefit of symptom monitoring	MID=2 (published MID)
Quality of life (SF-36, range 0–100, higher is better, 6 months) - Mental total score	63 (1 RCT)	⨁◯◯◯ Very lowⁿ^,^o	-	The mean quality of life (SF-36, range 0–100, higher is better, 6 months) - Mental total score was 74.17	MD 11.78 lower (20.39 lower to 3.17 lower) Clinically important benefit of symptom monitoring	MID=3 (published MID)
Lung function (FEV1 % predicted, higher is better, 6–12 months)	163 (2 RCTs)	⨁⨁◯◯ Low^q	-	The mean lung function (FEV1 % predicted, higher is better, 6–12 months) was 84.07	MD 0.1 higher (0.92 lower to 1.12 higher) No clinical difference	MID=5.846 (baseline SDs of both arms/2)
Lung function (FEV1, L, higher is better, 12 months)	88 (1 RCT)	⨁◯◯◯ Very low^b^,^e^,^r	-	The mean lung function (FEV1, L, higher is better, 12 months) was 2.71	MD 0.26 lower (0.61 lower to 0.09 higher) Clinically important benefit of symptom monitoring	MID=0.23 (published MID)
Time off school/work (mean days off work, lower is better, 12 months)	183 (2 RCTs)	⨁◯◯◯ Very low^b^,^e	-	The mean time off school/work (mean days off work, lower is better, 12 months) was 2.6	MD 2.5 higher (1.27 higher to 3.74 higher) No clinical difference	MID=3.8 (SDs of both arms at follow-up/2)
Time off school/work (time off work events, lower is better, 6–12 months)	192 (2 RCTs)	⨁◯◯◯ Very low^f^,^k	RR 1.41 (0.62 to 3.21)	87 per 1,000	40 more per 1,000 (50 fewer to 120 more) No clinical difference	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 100 per 1000

a: Downgraded by one increment for risk of bias due to some concerns about low adherence to intervention.

b: Downgraded by one increment for population indirectness (moderate-severe asthma population)

c: Downgraded by one increment for risk of bias due to some concerns about: lack of information on adherence to intervention; outcome self-reported via questionnaire and study unblinded.

d: Downgraded by one increment for imprecision because the 95% confidence interval crosses one MID (0.8–1.25)

e: Downgraded by two increments because the evidence is at high risk of bias (per protocol analysis, missing data, unblinded and low adherence to intervention)

f: Downgraded by two increments for imprecision because the 95% confidence interval crosses both MIDs (0.8–1.25)

g: Downgraded by two increments because the study is at high risk of bias (no information on randomisation process or adherence; analysis method unclear; only drop out information at the time of randomisation, not at follow-up)

h: Downgraded by one increment for imprecision because the 95% confidence interval crosses one MID (MID calculated as follow-up SD of both groups/2=0.138)

i: downgraded by two increments because the evidence is at high risk of bias (no information on randomisation, issues with adherence, missing data or analysis)

j: Downgraded by one increment for inconsistency (I squared = 53%)

k: Downgraded by two increments because the evidence is at high risk of bias (poor adherence to interventions and unclear how handled in analysis; differential in missing data across arms, and related to compliance with intervention)

l: downgraded by two increments because the majority of evidence is at high risk of bias (no information about allocation concealment, adherence or baseline characteristics; missing data without reasons reported; unblinded to outcome assessors)

m: Downgraded by one increment for inconsistency (I squared = 74%)

n: Downgraded by two increments because the evidence is at high risk of bias (no randomisation information; poor adherence to interventions and not clear how handled in analysis; self-reported outcome and unblinded)

o: Downgraded by one increment for population indirectness (38.1% severe asthma)

p: Downgraded by two increments for imprecision because the 95% confidence interval crosses both MIDs (published MID=2)

q: Downgraded by two increments because the majority of evidence was at high risk of bias (no information on randomisation, adherence or analysis; 50/150 missing data with no reasons given)

r: Downgraded by one increment for imprecision because the 95% confidence interval crosses one MID (published MID=0.23 L)

Table 4Clinical evidence summary: PEF monitoring versus usual care (symptom monitoring) in children

Outcomes	№ of participants (studies) Follow-up	Certainty of the evidence (GRADE)	Relative effect (95% CI)	Anticipated absolute effects
Outcomes	№ of participants (studies) Follow-up	Certainty of the evidence (GRADE)	Relative effect (95% CI)	Risk with symptoms monitoring: children	Risk difference with PEF	Comments
Unscheduled healthcare utilisation (hospital admissions, lower better, 12 weeks)	89 (1 RCT)	⨁◯◯◯ Very low^a^,^b	Peto OR 7.56 (0.15 to 381.04)	0 per 1,000	20 more per 1,000 (40 fewer to 80 more) No clinical difference	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 30 per 1000
Unscheduled healthcare utilisation (attendance at A&E, lower is better, 12 weeks)	89 (1 RCT)	⨁◯◯◯ Very low^a^,^b	Peto OR 7.56 (0.15 to 381.04)	0 per 1,000	20 fewer per 1,000 (40 fewer to 80 more) No clinical difference	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 30 per 1000
Unscheduled healthcare utilisation (emergency GP visit, lower is better, 12 weeks)	89 (1 RCT)	⨁◯◯◯ Very low^a^,^b	RR 0.93 (0.44 to 1.97)	244 per 1,000	17 fewer per 1,000 (137 fewer to 237 more) No clinical difference	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 30 per 1000
Severe asthma exacerbations (needing oral corticosteroids, lower is better, 12 months)	46 (1 RCT)	⨁◯◯◯ Very low^b^,^c	Peto OR 16.34 (3.25 to 82.24)	0 per 1,000	370 more per 1,000 (150 more to 590 more) Clinically important benefit of symptom monitoring	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 30 per 1000
Lung function (FEV1 % predicted, higher is better, 3 months)	113 (1 RCT)	⨁⨁◯◯ Low^d	-	The mean lung function (FEV1 % predicted, higher is better, 3 months) was 90	MD 2 lower (9.67 lower to 5.67 higher) No clinical difference	MID=10.4 (SD at follow-up for both arms/2)
Time off school (absent from school, events, lower is better,12 weeks)	89 (1 RCT)	⨁◯◯◯ Very low^a^,^b	RR 1.18 (0.64 to 2.18)	289 per 1,000	52 more per 1,000 (104 fewer to 341 more) No clinical difference	MID (imprecision) = 0.8 – 1.25 MID (clinical importance) = 100 per 1000

a: Downgraded by two increments because the study was at high risk of bias (some concerns on multiple domains: no information about randomisation, some issues with adherence to interventions and self-reported outcome/unblinded)

b: Downgraded by two increments for imprecision because the 95% confidence interval crosses both MIDs (0.8–1.25)

c: Downgraded by two increments because the study is at high risk of bias (no information about allocation concealment or adherence; no baseline characteristics reported; unblinded to outcome assessors)

d: Downgraded by two increments because the study was at high risk of bias (lack of information on randomisation, baseline characteristics or adherence to intervention; missing data unclear)

Table 5Clinical evidence summary: PEF monitoring at symptom-time versus symptom monitoring in children

Outcomes

№ of participants (studies) Follow-up

Certainty of the evidence (GRADE)

Relative effect (95% CI)

Anticipated absolute effects

Risk with symptoms monitoring: children

Risk difference with PEF monitoring at symptom-time

Comments

Lung function (FEV1% predicted, higher is better, 3 months))

111 (1 RCT)

⨁◯◯◯ Very low^a^,^b

The mean lung function (FEV1% predicted, higher is better, 3 months) was 90

MD 4 higher (3.67 lower to 11.67 higher)

No clinical difference

MID=10.27 (SD at follow-up for both arms/2)

a: Downgraded by two increments because the study is at high risk of bias (no information on randomisation, baseline characteristics, or adherence; missing data unclear)

b: Downgraded by one increment for imprecision because the 95% confidence interval crosses one MID (calculated as FUP SD of both arms/2=10.27)

Table 6PEF per-test cost

Resource	Quantity	Unit costs	Total cost	Source
Adult mini-wright peak flowmeter	1	£4.65 per flowmeter	£4.65	NHS Supply Chain Catalogue(NHS Supply Chain Catalogue., 2022)
Low range mini-wright paediatric	1	£4.75 per flowmeter	£4.75	NHS Supply Chain Catalogue(NHS Supply Chain Catalogue., 2022)
Time of practice nurse	10 – 20 minutes^(a)	£63.38 per hour	£10.57 – £21.13	PSSRU 2022(Jones, et al.)
Total cost – adults	£15.22 – £25.78
Total cost – children	£15.32 – £25.88

: Note: all prices are VAT exclusive

(a): 20 minutes assumed in the base case scenario

Table 13Studies excluded from the clinical review

Excluded studies
Study	Exclusion reason
Abramson, Michael J, Schattner, Rosa L, Holton, Christine et al (2015) Spirometry and regular follow-up do not improve quality of life in children or adolescents with asthma: Cluster randomized controlled trials. Pediatric pulmonology 50(10): 947–54 [PubMed: 25200397]	- Study does not contain an intervention relevant to this review protocol the participants attended clinical for spirometry however there is no mention of consequential treatment adjustment.
Barnes, Camilla Boslev and Ulrik, Charlotte Suppli (2015) Asthma and adherence to inhaled corticosteroids: current status and future perspectives. Respiratory care 60(3): 455–68 [PubMed: 25118311]	- Systematic review used as source of primary studies Review examining methods to improve medication adherence, not specifically pulmonary monitoring
Bateman, E., Reddel, H.K., O'Byrne, P.M. et al (2018) Severe exacerbations and inhaled corticosteroid load with as-needed budesonide/formoterol vs maintenance budesonide in mild asthma. American Journal of Respiratory and Critical Care Medicine 197(meetingabstracts)	- Conference abstract
Bindler, R., Haverkamp, H.C., O'Flanagan, H. et al (2022) Feasibility and acceptability of home monitoring with portable spirometry in young adults with asthma. Journal of Asthma [PMC free article: PMC10191873] [PubMed: 36525469]	- Study design not relevant to this review protocol Not randomised and no comparator
Bookser, M., Drennen, C., Leonard, E. et al (2018) Pharmacist-led medication intervention for patients with asthma and COPD within a primary care setting. Journal of the American Pharmacists Association 58(3): e24	- Conference abstract
Boonjindasup, Wicharn, Chang, Anne B, McElrea, Margaret S et al (2022) Does the routine use of spirometry improve clinical outcomes in children?-A systematic review. Pediatric pulmonology 57(10): 2390–2397 [PMC free article: PMC9796376] [PubMed: 35754141]	- Systematic review used as source of primary studies Review identified one relevant study, included in this review
Burkhart, PV (1996) Effect of contingency management on adherence to peak flow monitoring in school-age children with asthma. Dissertation/ thesis: 276p	- Study design not relevant to this review protocol
Celler, Branko, Argha, Ahmadreza, Varnfield, Marlien et al (2018) Patient Adherence to Scheduled Vital Sign Measurements During Home Telemonitoring: Analysis of the Intervention Arm in a Before and After Trial. JMIR medical informatics 6(2): e15 [PMC free article: PMC5913569] [PubMed: 29631991]	- Study design not relevant to this review protocol Before and after trial that included many chronic conditions, not just asthma
Choi, B., Lee, S., Jung, J. et al (2017) Impact of patient education on medication on health outcomes and adherence in patients with asthma. Allergy: European Journal of Allergy and Clinical Immunology 72(supplement103): 380–381	- Conference abstract
Ferrés, Cristina Subirana (2018) La utilidad de ios medidores de flujo espiratorio máximo en el diagnóstico de la gravedad del asma. Metas de Enfermería 21(10): 57–65	- Systematic review does not contain factors of interest based on diagnosing asthma
Fielding, Shona, Pijnenburg, Marielle, de Jongste, Johan C et al (2019) Change in FEV1 and Feno Measurements as Predictors of Future Asthma Outcomes in Children. Chest 155(2): 331–341 [PMC free article: PMC6688975] [PubMed: 30359613]	- Study does not contain an intervention relevant to this review protocol Study examined measurement of spirometry or FeNO as risk-prediction tools, not methods of monitoring
Hale, Elaine Mac, Greene, Garrett, Mulvey, Christopher et al (2023) Use of digital measurement of medication adherence and lung function to guide the management of uncontrolled asthma (INCA Sun): a multicentre, single-blinded, randomised clinical trial. The Lancet. Respiratory medicine [PubMed: 36963417]	- Study does not contain an intervention relevant to this review protocol focused on increasing treatment adherence
Kim, M.-A., Ye, Y.-M., Park, J.-W. et al (2014) A computerized asthma-specific quality of life: A novel tool for reflecting asthma control and predicting exacerbation on behalf of the premier researchers aiming new era in asthma and allergic diseases (PRANA) study group. International Archives of Allergy and Immunology 163(1): 36–42 [PubMed: 24247849]	- Study design not relevant to this review protocol Observational study aiming to validate asthma control tool
Kohlbrenner, Dario, Clarenbach, Christian F, Ivankay, Adam et al (2022) Multisensory Home-Monitoring in Individuals With Stable Chronic Obstructive Pulmonary Disease and Asthma: Usability Study of the CAir-Desk. JMIR human factors 9(1): e31448 [PMC free article: PMC8892320] [PubMed: 35171107]	- Study design not relevant to this review protocol Observational study examining the utility of a home-monitoring device
Lake, C.; Wong, K.; Brannan, J. (2020) Monitoring Asthma Control with Inhaled Corticosteroids (ICS) Using Airway Hyperresponsiveness (AHR) to Mannitol Compared to Routine Spirometry in A Pulmonary Function Laboratory (PFL). Respirology 25: 5	- Conference abstract
Letz, K.L.; Schlie, A.R.; Smits, W.L. (2004) A Randomized Trial Comparing Peak Expiratory Flow Versus Symptom Self-Management Plans for Children with Persistent Asthma. Pediatric Asthma, Allergy & Immunology 17(3): 177–190	- No outcomes relevant to protocol
Letz, K and Smits, W (2004) A randomized trial comparing peak expiratory flow versus symptom self-management plans for children with persistent asthma. Journal of allergy and clinical immunology 113(suppl2): 286	- Conference abstract
Moeller, Alexander, Carlsen, Kai-Hakon, Sly, Peter D et al (2015) Monitoring asthma in childhood: lung function, bronchial responsiveness and inflammation. European respiratory review: an official journal of the European Respiratory Society 24(136): 204–15 [PMC free article: PMC9487806] [PubMed: 26028633]	- Review article but not a systematic review
Patel, P.J., Abou Baker, N., Travis, R. et al (2015) Assessing subjective and objective measures of asthma control in an inner city pediatric and adolescent population. Annals of Allergy, Asthma and Immunology 115(5suppl1): a22	- Conference abstract
Perry, T.T., Halterman, J.S., Brown, R.H. et al (2015) Breath connection: A school-based telemedicine program for rural children with asthma. Journal of Allergy and Clinical Immunology 135(2suppl1): ab169	- Conference abstract
Portnoy, Jay M, Waller, Morgan, De Lurgio, Stephen et al (2016) Telemedicine is as effective as in-person visits for patients with asthma. Annals of allergy, asthma & immunology: official publication of the American College of Allergy, Asthma, & Immunology 117(3): 241–5 [PubMed: 27613456]	- Study design not relevant to this review protocol non-randomised comparison between telemonitoring and in-person monitoring for children with asthma
Thomas, RP, Rani, NV, Kannan, G et al (2015) Impact of pharmacist-led continuous education on the knowledge of inhalation technique in asthma and COPD patients. International journal of medical and health sciences 4: 40–46	- Study does not contain an intervention relevant to this review protocol assessing inhalor techniques
Tolnai, J., Petak, F., Sudy, R. et al (2021) Remote monitoring of lung function in asthmatic children with telespirometry. European Respiratory Journal 58(suppl65)	- Conference abstract
Turner, S.W. (2019) The uncertain role of spirometry in managing childhood asthma in the UK 2019. Thorax 74(supplement2): a126–a127 [PubMed: 31270092]	- Conference abstract
Van Vliet, D, Van Horck, M, Van De Kant, K et al (2014) Electronic monitoring of symptoms and lung function to assess asthma control in children. Annals of allergy, asthma and immunology 113(3): 257–262 [PubMed: 24950912]	- Study design not relevant to this review protocol Observational
Wallace-Farquharson, Tanya, Rhee, Hyekyun, Oguntoye, Anne O et al (2023) Adolescents' practical knowledge of asthma self-management and experiences in the context of acute asthma: a qualitative content analysis. The Journal of asthma: official journal of the Association for the Care of Asthma 60(2): 277–287 [PMC free article: PMC9470766] [PubMed: 35195484]	- Full text paper not available Full paper due to release in February 2024
Wang, L, Zheng, S, Wang, Q et al (2023) emergency nursing based on PEWS can improve the condition of children with acute asthma. Alternative therapies in health and medicine. http://alternative-therapies.com/oa/index.html?fid=9854 [PubMed: 37971472]	- Study does not contain an intervention relevant to this protocol Intervention does not involve PEF or spirometry. Also an emergency setting context, patients in hospital with acute asthma episode.
Wen, Tzu-Ning, Lin, Hsueh-Chun, Yeh, Kuo-Wei et al (2022) Effectiveness of eAsthmaCare on Symptoms, Childhood Asthma Control Test, and Lung Function among Asthmatic Children. Journal of medical systems 46(11): 71 [PubMed: 36161540]	- Study does not contain an intervention relevant to this review protocol Comparing e-asthma care programme to usual care
Zhang, Olivier; Minku, Leandro L; Gonem, Sherif (2021) Detecting asthma exacerbations using daily home monitoring and machine learning. The Journal of asthma: official journal of the Association for the Care of Asthma 58(11): 1518–1527 [PubMed: 32718193]	- Study design not relevant to this review protocol Secondary analysis of SAKURA trial - participants were randomised to treatments, not monitoring strategies

Evidence reviews for pulmonary function monitoring in asthma

1. Pulmonary function monitoring

1.1. Review question

1.1.1. Introduction

1.1.2. Summary of the protocol

Table 1

1.1.3. Methods and process

1.1.4. Effectiveness evidence

1.1.4.1. Included studies

1.1.4.2. Excluded studies

1.1.5. Summary of studies included in the effectiveness evidence

Table 2

1.1.6. Summary of the effectiveness evidence

Table 3

Table 4

Table 5

1.1.7. Economic evidence

1.1.7.1. Included studies

1.1.7.2. Excluded studies

1.1.8. Summary of included economic evidence

1.1.9. Economic model

1.1.10. Unit costs

Table 6

1.1.11. Evidence statements

1.1.11.1. Economic

1.2. The committee's discussion and interpretation of the evidence

1.2.1. The outcomes that matter most

1.2.2. The quality of the evidence

1.2.3. Benefits and harms

Adults

Children

1.2.4. Cost effectiveness and resource use

1.2.5. Other factors the committee took into account

1.2.6. Recommendations supported by this evidence review

1.3. References

Appendices

Appendix A. Review protocols

Appendix B. Literature search strategies

Appendix C. Effectiveness evidence study selection

Appendix D. Effectiveness evidence

Appendix E. Forest plots

Appendix F. GRADE tables

Appendix G. Economic evidence study selection

Appendix H. Economic evidence tables

Appendix I. Excluded studies

Clinical studies

Table 13

Health economic studies

Table 1PICO characteristics of review question

Table 2Summary of studies included in the evidence review

Table 3Clinical evidence summary: PEF monitoring versus usual care (symptom monitoring) in adults

Table 4Clinical evidence summary: PEF monitoring versus usual care (symptom monitoring) in children

Table 5Clinical evidence summary: PEF monitoring at symptom-time versus symptom monitoring in children

Table 6PEF per-test cost

Table 13Studies excluded from the clinical review