S ISTEMA D E C LASIFICACIÓN U NIFICADA D E S UELOS (S UCS )

Purpose of the review

We undertook a systematic review of existing economic analyses of FeNO testing in the diagnosis of asthma and for the management of patients with diagnosed asthma. This also included a focused review of economic studies of other interventions for the diagnosis and/or management of asthma. The purpose of the review of existing health economic analyses was threefold:

1. to identify existing economic analyses of FeNO testing using NIOX MINO, NIOX VERO or NObreath for the diagnosis and/or management of asthma

2. to identify existing models that may be used to inform the structure of the de novo economic models developed by the EAG

3. to identify potentially relevant evidence sources to inform parameter values within the de novo economic models developed by the EAG.

Review methods

Methods used to identify existing economic studies

We undertook systematic searches across a range of electronic databases to identify published studies of FeNO testing for the diagnosis and/or management of asthma. We also searched for other economic studies of interventions for the diagnosis or management of asthma. All searches were undertaken by an information specialist (RW) during the period 30 May 2013 to 7 June 2013.

Four separate strands of searching were undertaken, which are detailed in the following sections.

Economic search 1: NIOX MINO/NObreath in either the diagnosis or the management of asthma (30 May 2013)

This search used free-text terms relating to NIOX MINO and NObreath (including manufacturer names), with the terms combined with a sensitive economic search filter.

Economic search 2: models of asthma and FeNO (30 May 2013)

This search used the search strategies developed for the management studies in the clinical effectiveness review (seeChapter 3,Clinical reviews search methodology) and combined these with a sensitive economic search filter. Studies that were found in the first search would also be retrieved in this search.

Economic search 3: asthma management models (3 June 2013)

This focused search used free-text terms for asthma combined with cost terms in the title and the economic model subject heading. A sensitive economic filter was not applied in this search.

Economic search 4: asthma diagnostic models (7 June 2013)

This focused search used free-text terms for asthma (as used in economic search 3) combined with a sensitive economic evaluations search filter and a diagnostic search filter.

These four searches are shown diagrammatically inFigure 20.

All of the above searches were performed within the following databases:

l MEDLINE and MEDLINE-In-Process & Other Non-Indexed Citations (Ovid): 1948–present l EMBASE (Ovid): 1974–present

l The Cochrane Library (Wiley Interscience): ¢ CDSR: 1996–present

¢ HTA database: 1995–present ¢ NHS EED: 1995–present

l SCIE (Web of Science): 1899–present l CPCI-S (Web of Science): 1990–present.

The economic MEDLINE search strategy is detailed inAppendix 13.

As noted inChapter 3(seeAdditional search for NIOX VERO), an additional separate search was also undertaken in August 2013 to identify evidence relating to NIOX VERO.

Inclusion and exclusion criteria for the review

Given the anticipated dearth of published economic analyses relating to FeNO, we adopted broad inclusion criteria for the review (Box 1).

Data sifting

The titles and abstracts of all records identified by the search were reviewed by one member of the research team (JM). The full texts of studies considered eligible for inclusion were then retrieved for a more detailed examination.

Critical appraisal methods

The identified studies of FeNO were critically appraised using the Drummondet al.144_{checklist for economic}

evaluations and the NICE reference case for diagnostic studies.145_{The identified studies were also informally}

assessed against current guidelines for the development and reporting of health economic models.146

Asthma terms Asthma terms

Intervention and manufacturer terms Lower respiratory tract symptom terms Exhaled nitric oxide terms AND

AND AND AND

AND Exhaled nitric oxide terms AND Economic filter OR OR

For example, NIOX MINO, NObreath, aerocrine, bedfont

For example, asthma, bronchoconstriction, bronchial spasm

For example, FeNO, ENO, fractional NO

Asthma model review

Model terms in title Economic filter

Diagnostic filter

Asthma combined with economic filter and diagnostic filter 4.

3.

2.

1.

Studies of other interventions for the diagnosis and/or management of asthma were not subjected to a formal critical appraisal but were instead used to inform the design and development of the de novo health economic analyses (detailed inDevelopment of two de novo models to estimate the cost-effectiveness of FeNO testing for the diagnosis and management of asthma).

Results of the review of FeNO testing for asthma diagnosis and/or management

Number and type of studies included in the review

The results of the four economic searches are presented inTable 51. A total of 1898 potentially relevant citations were identified from the four searches. The full texts of 27 studies were retrieved for further examination. The full text of one of these studies could not be retrieved and was excluded. Of the remainder, only two studies147,148_{were identified that related to FeNO testing for the diagnosis and/or}

management of asthma. The focused searches did not identify any further cost–utility models of other interventions for the diagnosis of asthma. Sifting of the focused management model searches identified a further 13 studies149–161_{that were used more generally to inform the model structure, although none of}

these related to FeNO testing. In addition, one additional management study13_{that was detailed in the}

appendices of a UK HTA report was identified.

As part of the appraisal process, Aerocrine submitted evidence relating to the cost-effectiveness of NIOX MINO for the diagnosis and management of asthma (Aerocrine.Submission to NICE–Assessing the Impact of FeNO in the Management and Diagnosis of Asthma. Slideset and Microsoft Excel model, 2013). This submission included a Microsoft Excel 2010 spreadsheet model (Microsoft Corporation, Redmond, WA, USA) and a brief slideset. This submission is included as part of the economic review presented in this chapter. Aerocrine did not submit any economic evidence relating to the cost-effectiveness of the NIOX VERO device and Bedfont Scientific did not submit any evidence relating to either the effectiveness or the cost-effectiveness of the NObreath device.

BOX 1 Inclusion and exclusion criteria for the review of economic analyses of asthma diagnosis and management

Inclusion criteria

l Economic analyses of costs and consequences of interventions for the diagnosis and/or management of asthma in children and/or adults.

l Studies reporting on the cost-effectiveness of NIOX MINO, NIOX VERO or NObreath for the diagnosis and/or management of asthma.

Exclusion criteria

l Letters, commentaries and editorials.

l Economic studies that do not relate to diagnostic or management interventions.

l Studies that do not relate to asthma.

l Studies that do not involve (i) a model-based analysis, (ii) economic evaluations alongside trials or other forms of empirical clinical study or (iii) estimates of the costs and consequences of FeNO testing for the diagnosis of asthma.

Existing economic analyses of FeNO testing for the diagnosis of asthma

Methods and results of the included diagnostic studies

The searches included only one UK model-based published economic analysis relating to the diagnosis of asthma;147_{this study assessed the cost-effectiveness of FeNO testing (specifically NIOX MINO) compared}

with standard diagnostic tests. This model has been published across two papers147,148_{and also forms the}

basis of the Aerocrine submission to NICE for this appraisal. The general model structure and many of the evidence inputs are the same across these three analyses.

An economic evaluation of NIOX MINO airway inflammation monitor in the United Kingdom: diagnostic model147

Description of the economic model and analysis Priceet al.147_{presents the methods and results of}

two economic analyses: (1) a model to assess the cost savings associated with using NIOX MINO for the diagnosis of asthma and (2) a model to assess the cost-effectiveness of NIOX MINO for the management of asthma. The model of asthma management is reviewed in detail inExisting economic analyses of FeNO testing for the management of asthma.

The conceptual form of the Priceet al.147_{diagnostic model is presented inFigure 21. Within the model, the}

costs and outcomes of competing diagnostic strategies are modelled using a simple deterministic decision tree based on the true underlying probability of asthma and the operating characteristics of a variety of tests used for the diagnosis of asthma in the NHS. The population under evaluation within the model is reported to relate to‘non-smoking adult patients with mild to severe asthma as seen in both primary and secondary care’(p. 433).147_{The intervention is defined in the base-case analysis as FeNO testing using}

NIOX MINO alone, although a secondary analysis is also reported for a joint diagnostic modality consisting of NIOX MINO plus spirometry using FEV1testing. The comparator within the base-case analysis is a

blended comparison of standard diagnostic tests: (1) lung function testing, (2) reversibility test, (3) bronchial provocation and (4) sputum eosinophil count. The selection of tests included in the analysis was based on the BTS/SIGN asthma guidelines,8_{although the source for the proportionate weighting of each of these is unclear}

within the Priceet al.147_{paper. It should also be noted that current BTS/SIGN guidelines}8_{state that sputum}

induction is not in common usage and it currently remains a research tool. In contrast to the published Priceet al.147_{model, the Aerocrine submission model does not adopt a blended comparison approach but}

instead evaluates each individual diagnostic test as a decision option in its own right.

TABLE 51 Summary of the results of the economic searches

Database Search 1. NIOX MINO/NObreath 2. Asthma and FeNO models 3. Asthma management models 4. Asthma diagnostic models MEDLINE and MEDLINE-In-Process & Other

Non-Indexed Citations 2 29 311 338 EMBASE 7 144 420 590 CDSR 0 48 0 69 HTA database 4 8 4 0 DARE 0 2 3 14 NHS EED 1 2 119 12 SCIE 5 85 295 457 CPI-S 0 3 15 37

Choose Standard diagnostics Asthma Non-asthma Prevalence True positive sensitivity # # specificity False positive False negative True negative # # weight weight weight Lung function testing

Clone 1: Diagnosis Clone 1: Diagnosis Clone 1: Diagnosis Clone 1: Diagnosis Reversibility test Bronchial provocation

Sputum eosinophil count

NIOX MINO

1

FIGURE 21 Model structure employed within the Priceet al.147_{diagnostic model. Reproduced with permission from}

Price D, Berg J, Lindgren P. An economic evaluation of NIOX MINO airway inflammation monitor in the United

Kingdom.Allergy2009;64:431–8.147_{John Wiley & Sons. © 2009 The Authors. Journal compilation © 2009}

Blackwell Munksgaard.

The model structure employs a single decision node whereby the model cohort is assumed to receive a single imperfect diagnostic intervention; those patients who receive an incorrect diagnosis are later assumed to achieve a correct diagnosis of either true asthma or not asthma. The published model estimates the costs associated with NIOX MINO compared with those of the blended comparison of standard diagnostic tests. The analysis takes the form of a comparative cost analysis and health outcomes are not explicitly considered in the published analysis (note that the number of misdiagnoses are not reported within the Priceet al.147

paper but could be easily calculated from the table of model input parameters). Diagnostic outcomes in terms of TPs, FPs, TNs and TPs are estimated explicitly within the Aerocrine model. Within the Priceet al.147

paper, costs are valued at 2005 prices. The model time horizon is undefined but relates to the time from presentation to correct diagnosis. No discounting is applied to costs.

The Priceet al.147_{diagnostic model makes the following structural assumptions:}

l NIOX MINO will replace existing diagnostic tests rather than be used alongside them

l time is not explicitly considered within the model with respect to the resolution of incorrect diagnoses (FPs or FNs)

l negative health consequences [quality-adjusted life-year (QALY) losses] associated with incorrect diagnoses are not quantified within the model

l all incorrect diagnoses are assumed to be corrected at the next outpatient visit.

The parameter values and evidence sources from which these are drawn are reported inTable 52.

The headline results of the economic analysis are presented as a simple cost difference between NIOX MINO and the blended comparison of standard tests for asthma diagnosis. Uncertainty surrounding model input parameters was explored using simple one-way sensitivity analyses. These analyses include varying model parameters describing test sensitivity, true underlying asthma prevalence in the modelled

population, the costs of NIOX MINO and other diagnostic tests, the number of additional visits required to resolve an initially incorrect diagnosis, a comparison of NIOX MINO with reversibility testing plus peak expiratory flow (PEF) charting and a comparison of NIOX MINO plus FEV and standard tests.

TABLE 52 All parameter values and evidence sources used in the Priceet al.147

diagnostic model

Parameter Value Source

Test operating characteristics

Sensitivity FeNO testing (flow rate 50 ml/second;_>20 ppb) 0.88 Smithet al.86

Specificity FeNO testing (flow rate 50 ml/second;>20 ppb) 0.79

Sensitivity FeNO testing (flow rate 50 ml/second;_>33 ppb)₊FEV1<80% predicted 0.94

a

Smith and Taylor162

Specificity FeNO testing (flow rate 50 ml/second;>33 ppb)+FEV1predicted<80% 0.93

Sensitivity PEF A%M_>21.6% 0.43 Hunteret al.163

Specificity PEF A%M>21.6% 0.75

Sensitivity reversibility test: FEV1>2.9% improvement after salbutamol 0.49

Specificity reversibility test: FEV1>2.9% improvement after salbutamol 0.70

Sensitivity bronchial provocation: methacholine PC20<8 mg/ml 0.91

Specificity bronchial provocation: methacholine PC20<8 mg/ml 0.90

Sensitivity sputum eosinophil count_>1% 0.72

Specificity sputum eosinophil count>1% 0.80

Disease characteristics

Asthma prevalence 0.36 Smithet al.86

Comparator usage (blended comparison weightings)

Proportion using PEF charting 0.485 BTS/SIGN164

Proportion using reversibility testing 0.485

Proportion using bronchial provocation 0.025

Proportion using sputum eosinophil count 0.005

Cost parameters (£)

Cost NIOX MINO 22.90 Aerocrine

Cost peak flow charting (two visits) 89.27 NHS Reference Costs165

Cost reversibility test 29.27

Cost bronchial provocation 48.50

Cost sputum eosinophil count 48.50

Cost outpatient GP visit 30.00 Curtis and Netten166

Cost outpatient lung practitioner 44.00

methacholine PC20<8 mg/ml, provocative concentration of methacholine causing>20% fall in FEV1; PEF, peak expiratory

flow; PEF A%M>21.6%, maximum within-day peak expiratory flow amplitude mean percentage (calculated from PEF measured twice daily over 14 days as the best of three blows).

a Note that this is a non-systematic review/opinion paper. Although Smith and Taylor162_{do state these sensitivity and}

specificity values and refer to two other empirical studies, neither includes the quoted estimates. The empirical source of the reported values for FeNO plus FEV1is unclear.

Diagnostic model results presented by Priceet al.147 _{The diagnostic model results reported by} Priceet al.147_{are summarised inTable 53. In the base-case analysis, the authors report that the cost of an}

asthma diagnosis made using NIOX MINO was £29 per patient, or £43 less than when using standard diagnostic tests (£72 per patient).

The results indicate that, within the base-case analysis, NIOX MINO is expected to produce cost savings (£43) compared with the blended comparison of standard diagnostic tests for asthma. These results do not account for potential health benefits associated with the improved accuracy of diagnosis. The sensitivity analysis indicates that NIOX MINO is expected to produce cost savings in all scenarios except (1) when the cost of NIOX MINO is increased by 200% and (2) within the comparison of NIOX MINO plus FEV1testing

compared with the blended comparison of current standard diagnostic tests.

The authors note that‘is it is likely that, in practice, FeNO measurement will be used in conjunction with other tests rather than as their replacement. We examined this scenario and found that the combination of FeNO measurement plus lung function testing increased costs for diagnosing asthma by £42’(p. 435).147

Given the authors’interpretation of the likely placement of NIOX MINO, it is unclear why the base-case analysis within the paper does not reflect this scenario and, given the proposed placement of FeNO within the existing pathway and the absence of quantified health outcomes within the Priceet al.147_diagnostic

model, it is unclear whether the potential additional benefits associated with diagnosis using FeNO testing outweigh the opportunity costs associated with generating them.

TABLE 53 Summary of cost-minimisation results presented by Priceet al.147

Scenario NIOX MINO (£) Standard tests (£) Incremental cost (£) Base case 29 72 _–43

Variation in test sensitivity–50% (all tests simultaneously) 35 76 –40

Variation in test sensitivity₊10% (all tests simultaneously) 29 72 _–43

Variation in test sensitivity–50% (bronchial provocation and

sputum only)

39 81 –42

Variation in test sensitivity₊10% (bronchial provocation and

sputum only)

28 71 _–43

Asthma prevalence set to 10% 30 70 –40

Asthma prevalence set to 50% 29 74 _–45

Asthma prevalence set to 90% 28 78 –50

NIOX MINO cost_–50% 18 72 _–54

NIOX MINO cost+200% 75 72 3

Cost of standard diagnostic tests₊50% 29 72 _–43

Cost of standard diagnostic tests+100% 29 102 –72

Cost of standard diagnostic tests₊150% 29 131 _–102

Cost of standard diagnostic tests+200% 29 161 –131

Two visits for false diagnosis 36 86 _–50

Four visits for false diagnosis 49 113 –63

NIOX MINO vs. reversibility₊PEF charting 29 131 _–102

NIOX MINO+FEV1testing vs. standard tests 115 72 42

Source: reproduced with permission from Price D, Berg J, Lindgren P. An economic evaluation of NIOX MINO airway inflammation monitor in the United Kingdom.Allergy2009;64:431–8.147

John Wiley & Sons. © 2009 The Authors. Journal compilation © 2009 Blackwell Munksgaard.

The next section briefly outlines the economic analysis of NIOX MINO for asthma diagnosis as presented within the Aerocrine submission to NICE.

(ii) Additional analysis presented within the submitted Aerocrine diagnostic model

As noted earlier, Aerocrine also submitted a spreadsheet model to NICE as part of the appraisal process. The model was accompanied by a brief Microsoft PowerPoint slideset although this does not include a description of the intended base-case analysis results and little detail is provided supporting the structure, assumptions or choices regarding evidence used to inform the model parameters. The submitted Aerocrine model adopts a very similar structure and similar assumptions to those of the diagnostic model reported by Priceet al.147_{It should be noted that, in the absence of a detailed written description of the Aerocrine}

submission model, it is difficult to provide a full critique of its methods and results. This task was further hindered as the worksheet tabs and many sets of calculations were structurally hidden within the Microsoft Excel worksheet, making formula auditing problematic.

The following differences should be noted between the Priceet al.diagnostic model147_{and the Aerocrine}

diagnostic model:

1. Differences in the specification of diagnostic options. The Aerocrine model assesses a different set of options compared with Priceet al.:147

i. spirometry alone

ii. spirometry and (if negative) MCT

iii. spirometry and (if negative) FeNO testing iv. spirometry and FeNO testing

v. FeNO testing alone

vi. spirometry and (if negative) sputum induction.

It should be noted that some of these options include sequences of diagnostic tests. These are implemented within the model by assuming that the probabilities of obtaining a positive or negative result from sequences of tests are uncorrelated with one another; in other words, the use of prior tests in a sequence will remove some candidates from the population, will alter the prevalence of true

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