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effectiveness analysis of preventive interventions

Disease description and classification

COPD is a lung disease of progressive airflow obstruction or limitation, which is not fully reversible and typically worsen slowly over time (GOLD, 2014). There is clear evidence that health care cost (Jansson et al., 2013), quality of life decrements (Pickard et al., 2008) and mortality risk (Mannino et al., 2006) in COPD patients greatly depend on their levels of airflow ob- struction.

Since anatomical and clinical symptoms may vary between patients, diag- nosis of COPD is internationally defined by airflow obstruction. The latter is measured by a set of spirometric criteria, namely forced expiratory flow in 1 second (F EV1) and forced vital capacity (F V C), i.e forced emptying capac-

ity of the lungs. The American Thoracic Society, the European Respiratory Society, the National Institute for health and Care Excellence in England and the Global Initiative for Obstructive Lung Disease (GOLD) define COPD as a reduced F EV1/F V C ratio strictly lower than 70% (Celli et al., 2004; NICE,

2010; GOLD, 2014).

Sub-classification of the disease is based on a third measure known as F EV1%, which is the ratio of measured F EV1 against predicted F EV1, based

on age, height and gender. In conjunction to a F EV1/F V C ratio lower than

70%, a F EV1% greater than 80% defines “mild” COPD1, a F EV1% between

50% and 79% defines “moderate” COPD, a F EV1% between 30% and 49%

defines “severe” COPD and a F EV1% lower than 30% defines “very severe”

COPD. “Mild”, “moderate”, “severe” and “very severe” stages are also re- ferred to as GOLD1, GOLD2, GOLD3 and GOLD4.

Finally, in order to solely account for persistent airflow limitation, there is global agreement that all spirometric measures should always be taken post administration of a bronchodilator, i.e. a drug that help alleviate symptoms of airflow limitation (Celli et al., 2004; NICE, 2010; GOLD, 2014).

1_{In contrast to the American Thoracic Society, the European Respiratory Society and GOLD, NICE} recommends that symptoms should also be present to confirm diagnosis of the mild stage of the disease (NICE, 2010).

Substantial underdiagnosis

In England, based on cross-sectional data on population respiratory health obtained from the Health Survey for England (HSE) in 2001, Shahab et al. (2006) found that 80% of individuals aged 30 and over affected by spirometry- defined COPD reported no respiratory diagnosis.

As the analysis of HSE respiratory data collected in 2010 used a differ- ent methodology to compute COPD prevalence statistics than in 2001, it is not possible to evaluate with precision whether COPD underdiagnosis has decreased over time in England. Indeed, instead of using the fixed ratio of F EV1/F V C < 70%, in HSE 2010, COPD was defined based on the lower

limit of normal (LLN) values of the F EV1/F V C ratio, with the bottom 5%

classified as abnormal. Whilst each criteria has its pro and cons, LLN values are highly dependant on reference equations to compare the distribution of F EV1/F V C values and no scientific evidence to date supports LLN over the

fixed ratio of F EV1/F V C < 70% as best criteria to define COPD (GOLD,

2014).

Nevertheless, analysis of HSE results for the year 2010 greatly confirmed the magnitude of disease underdiagnosis, whereby less than a third (28% of males and 27% of females) of individuals with probable airflow limitation reported a doctor-diagnosis of COPD (Aresu et al., 2011).

Late diagnosis

While COPD is underdiagnosed as a whole, underdiagnosis is less pro- nounced for individuals in the severe and very severe stages of the disease (GOLD, 2014). In England, Shahab et al. (2006) reported that 50% of indi- viduals found to be in the severe and very severe stages of the disease2 were not diagnosed, whereas across all severity stages underdiagnosis reached 80%. Indeed, as symptoms worsen alongside disease progression, the disease is more

likely to be detected at an advanced stage. Based on HSE (2001) data, the UK Department of Health (2010) estimated that in England, 95% of the to- tal underlying (i.e. “true”) cases of GOLD stage 1 were underdiagnosed, as opposed to 79% for stage 2, 60% for stage 3 and only 7% for stage 4.

5.2.2 Implications for cost-effectiveness analysis

The key characteristics of the COPD disease have three major implications for the cost-effectiveness analysis of preventive interventions such as air pollu- tion control.

First, as health care cost, quality of life decrements and mortality risk greatly depend on the level of airflow obstruction, in order to evaluate most accurately the impact of an intervention that contribute to alleviate the health burden of COPD, one should account for the various levels of disease severity and the speed of disease progression.

Second, since the probabilities to transition between health states are typi- cally informed by diagnostic statistics (also referred to as incidence) underdiag- nosis will threaten the accuracy of modelling results. More precisely, disease underdiagnosis will underestimate the population’s baseline risk of developing COPD, and thus the total population health gain associated with an interven- tion that reduces the risk of developing COPD or mitigates its consequences. Total population health gain is typically irrelevant when assessing whether a health care technology is cost-effective or not, since the focus of interest is on the ratio of the incremental cost and health benefit per patient. By contrast, it is of particular importance when evaluating the cost-effectiveness of an in- tervention characterised by a large fixed investment cost, as is typically the case of interventions of air pollution reduction. For these interventions, disease underdiagnosis will underestimate total population health gain and thus, the probability of the intervention to be cost-effective.

known, despite COPD being a progressive disease, one should account for late diagnosis in order to avoid underestimating the total population of subjects with COPD. Late diagnosis is accounted for by allowing for transitions from the “healthy” state to any stages of the disease. Such an approach was fol- lowed by Hoogendoorn et al. (2005, 2011) when constructing a Markov model of COPD applied to the Dutch population, although the rationale for doing so was not stated.