The invisible costs of obstructive sleep apnea (OSA): Systematic review and cost-of-illness analysis.

BACKGROUND: Obstructive sleep apnea (OSA) is a risk factor for several diseases and is correlated with other non-medical consequences that increase the disease's clinical and economic burden. However, OSA's impact is highly underestimated, also due to substantial diagnosis gaps.
OBJECTIVE: This study aims at assessing the economic burden of OSA in the adult population in Italy by performing a cost-of-illness analysis with a societal perspective. In particular, we aimed at estimating the magnitude of the burden caused by conditions for which OSA is a proven risk factor.
METHODS: A systematic literature review on systematic reviews and meta-analyses, integrated by expert opinion, was performed to identify all clinical and non-clinical conditions significantly influenced by OSA. Using the Population Attributable Fraction methodology, a portion of their prevalence and costs was attributed to OSA. The total economic burden of OSA for the society was estimated by summing the costs of each condition influenced by the disease, the costs due to OSA's diagnosis and treatment and the economic value of quality of life lost due to OSA's undertreatment.
RESULTS: Twenty-six clinical (e.g., diabetes) and non-clinical (e.g., car accidents) conditions were found to be significantly influenced by OSA, contributing to an economic burden ranging from €10.7 to €32.0 billion/year in Italy. The cost of impaired quality of life due to OSA undertreatment is between €2.8 and €9.0 billion/year. These costs are substantially higher than those currently borne to diagnose and treat OSA (€234 million/year).
CONCLUSIONS: This study demonstrates that the economic burden due to OSA is substantial, also due to low diagnosis and treatment rates. Providing reliable estimates of the economic impact of OSA at a societal level may increase awareness of the disease burden and help to guide evidence-based policies and prioritisation for healthcare, ultimately ensuring appropriate diagnostic and therapeutic pathways for patients.

Introduction

Obstructive sleep apnea (OSA) is a disorder characterized by episodic cessation of breathing due to repeated upper airway partial (hypopnea) or total (apnea) obstructions [1, 2]. These events lead to activation of the sympathetic nervous system, sleep fragmentation, intermittent hypoxemia and, in the case of syndrome (OSAS), to excessive daytime sleepiness [3, 4]. Diagnosis of OSA usually requires overnight laboratory polysomnography in order to detect the frequency of disordered breathing events [5]. OSA’s severity is measured through the number of apnea and hypopnea events per hour of sleep (apnea-hypopnea index, AHI), which can be more than 30 in its severe form [6, 7]. The attention towards the disorder is increasing as several studies found that OSA is a risk factor for a substantial number of clinical conditions in adults, including diabetes [8-10], cancer [11, 12], cardiovascular [13, 14] and cerebrovascular diseases [15-17]. Moreover, OSA and its syndrome are associated with decreased quality of life (QoL) [18-20], impaired work performance [21-23] and increased risk of road traffic accidents [24, 25]. According to several population-based studies, prevalence of OSA is relatively high, especially among men [26-31], although methodological differences and difficulties in characterizing this disorder yielded to variability in prevalence estimates [32, 33]. Despite the prevalence of this condition, OSA is frequently undiagnosed, either because patients do not regard their symptoms (e.g., snoring, excessive daytime sleepiness) as the presence of a disorder, thus not seeking medical consultation, or because primary care physicians are often unable to recognize OSA signs and symptoms [5, 34], leading to a potential underestimation of the disease burden and to consequent undertreatment [35, 36]. Therapy with continuous positive airway pressure (CPAP) represents the gold standard for the treatment of OSA [37, 38]. When adherence is optimal, CPAP has been demonstrated to reduce symptoms, the possible sequelae of the disease and to improve self-reported health status [39-42]. As OSA and its related syndrome have been demonstrated to influence the onset of several health conditions and other non-clinical consequences, their low diagnosis and treatment rates are likely to result in increased clinical and economic burden. Several studies have estimated that OSA is associated with substantial economic costs, especially if untreated [43-45]. However, to date there is not available evidence for Italy. The present study aims at assessing the societal economic burden associated with OSA in the adult population in Italy by performing a cost-of-illness (COI) analysis based on a systematic literature review and population attributable fraction methodology. In particular, we aimed at estimating the proportion of the cost-of-illness of conditions for which OSA is a proven risk factor that can be attributed to OSA itself. As in the literature there is not always a clear and consistent distinction between OSA and OSAS, we focused our analyses on the broadest definition of the disease (i.e., OSA). Providing reliable estimates of the economic impact of OSA at a societal level may increase awareness of the disease burden and help to guide evidence-based policies and prioritisation for healthcare in Italy, ultimately ensuring appropriate diagnostic and therapeutic pathways for patients.

Materials and methods

A retrospective, prevalence-based COI study with a societal perspective and a one-year time-horizon was conducted to assess the economic burden of OSA and its syndrome for the Italian adult population.

Estimation of OSA prevalence

A scoping review of the literature, both grey and peer-reviewed, was performed in order to establish the prevalence of OSA in Italy among adult population (aged 15–74 years). Findings from the literature were discussed with clinical experts in order to assess their reliability and generalizability to the Italian context. Moreover, on the basis of the data provided by the Italian association of apneic patients (Associazione Apnoici Italiani Onlus) and expert opinion, we estimated the number of patients currently diagnosed and treated in Italy, in order to assess the extent of underdiagnosis and undertreatment in the national context.

Identification of conditions associated with OSA

A systematic literature review was carried out in order to identify the clinical and non-clinical conditions that have been demonstrated to be influenced by OSA in the adult population. The PRISMA guideline was used in developing this review [46]. The search was performed on PubMed according to a detailed search strategy and limited to studies providing the highest level of evidence, namely systematic reviews and meta-analyses (S1 Table). We decided to perform a “systematic review of systematic reviews” [47] since this approach is recommended when the literature is extremely heterogeneous in terms of methods, definitions and results, as in the case of OSA. The search was carried out on November 19th, 2018, and was updated on May 13th, 2021. The screening and selection of titles and abstracts first and full-texts later were conducted by two researchers in parallel on the basis of pre-defined exclusion criteria (S2 Table). Disagreements between reviewers on study inclusion were solved by consensus or by the decision of a third independent reviewer. The references and citations of the full-texts included were reviewed for additional articles according to a snowballing approach in order to ensure exhaustiveness of the review. Ultimately, studies were included if they provided quantitative evidence on the influence of OSA and its syndrome on other clinical and non-clinical conditions in the adult population. From the selected studies, the following data were extracted according to a predefined template: authors and year of publication; condition investigated (e.g., diabetes); OSA’s severity (i.e., mild, moderate, severe, overall); reference population (i.e., men, women, all); association measure (i.e., relative risk, hazard ratio, odds ratio); magnitude of association (mean value and 95% confidence intervals—CIs); statistical significance of the association (i.e., p-value). Data on magnitude of association (mean values) were used to calculate the proportion of conditions’ epidemiological burden influenced by OSA (see next section) and 95% CIs were used for sensitivity analysis. The exclusion criteria adopted and the results of the systematic review were discussed within a research board composed of health economists and clinicians specialized in different disciplines strongly related to OSA (i.e., neurology, endocrinology, internal medicine with cardiology specialization, gastroenterology). The aim of this phase was to ensure that the conditions retrieved through the review were significant from a clinical standpoint. Ultimately, only conditions for which a statistically significant association with OSA was found (i.e., p-value<0.05) and judged clinically meaningful by experts were included in the next steps of the analysis.

Estimation of conditions’ burden influenced by OSA: Population attributable fraction

An extensive review of both published and grey literature was performed to collect Italian epidemiological data of conditions included. In case we could not retrieve an epidemiological study for Italy, we searched for studies referred to other countries. In case more than one study was available for the same condition, we considered the one providing most up-to-date estimates. When prevalence rates were reported, the total number of prevalent cases was derived using data on Italian population by age and sex provided by the Italian National Institute of Statistics for 2018 (Istat) [48].

In order to estimate the proportion of conditions’ epidemiological burden influenced by OSA and its syndrome, a Population Attributable Fraction (PAF) methodology was applied. The PAF can be defined as the proportional reduction in average disease risk that would be achieved by eliminating the exposure to a risk factor [49, 50]. The PAF allows to estimate the amount of disease burden caused by a certain risk factor. In the literature, there are different approaches to estimate PAF. In the present analysis, we chose the approach that was deemed more suitable according to the association data available (i.e., relative risk, odds ratio or hazard ratio). In particular, we used the formula proposed by Levin (1953) [51] when the measure of association provided was relative risk (RR): where p(E) is the prevalence of OSA; RR is relative risk.

It is important to highlight that Levin’s approach could lead to overestimation of PAF when the measure of association provided is adjusted RR [49]. However, studies included did not provide sufficient data to use alternative approaches, suitable in the presence of confounding, therefore we used Levin’s formula for both unadjusted and adjusted RR.

When the measure of association was hazard ratio (HR), a variant of the Levin’s formula was considered [52]: where p(E) is the prevalence of OSA; HR(t) is hazard ratio at time t.

Finally, when the measure of association provided was odds ratio (OR), PAF was calculated according to the method based on Eide and Heunch (2001) [53] and used in a study by Hillman and colleagues (2018) [43]. By solving simultaneously the following two equations for p(D|E) and p(D|~E) the formula for PAF calculation is obtained where p(D|E) is the probability of having the particular condition given that an individual has OSA; p(D|~E) is the probability of having the particular condition given that an individual does not have OSA; p(E) is the probability of having OSA (i.e., OSA prevalence); p(~E) is the probability of not having OSA; p(D) is the probability of having the particular condition; OR is the odds ratio for that condition for individuals with OSA.

The number of prevalent cases for each condition influenced by OSA and its syndrome was obtained by multiplying conditions’ prevalence by the relative PAF.

Cost analysis: Assessment of conditions’ costs and estimation of OSA economic burden

An extensive literature review on scientific databases (e.g., ScienceDirect, Scopus) and on Google was carried out in order to retrieve Italian cost data for the conditions included in the systematic review. A top-down approach was used for cost estimation. As a societal perspective was adopted, all cost categories (i.e., direct healthcare, direct non-healthcare and indirect costs) were included, when available. In case we could not retrieve a cost study for Italy, we included cost studies referred to other countries, adjusting for inflation and purchasing power differences. To estimate indirect costs due to all-cause mortality associated with OSA, the friction method was used. This method assumes that for long term absences, as in the case of premature death, an individual’s work can be replaced by the market, therefore the loss in production is limited to a period in which the market adapts to the changed situation, called friction period [54]. This approach is more conservative than the human capital method, which considers earnings lost over a lifetime [55]. In the present analysis, we considered only productivity losses of employed people, excluding indirect costs of people out of the labour market. Productivity costs were estimated for different age groups to account for differences in wages, considering age and gender-specific yearly paid production value [56] and employment rates [48]. People aged 65–74 were assumed to be retired, therefore their employment rate was set equal to 0. To the best of our knowledge, there are not published data on the friction period for Italy, therefore we used a plausible value of 75 days, in line with the estimates used in another European country (Spain) [57]. Moreover, for employed people, we assumed that the friction period was the same across all age groups. The mean cost per patient/year was calculated for each condition and multiplied for the number of prevalent cases influenced by OSA and its syndrome, as obtained by applying PAF methodology.

As OSA is associated with decreased quality of life (QoL) [18-20], we estimated its burden also in terms of quality-adjusted life years (QALYs) value lost due to OSA undertreatment. QALYs for a single patient can be obtained by multiplying the health utility values for the years lived [58]. Health utilities represent individuals’ preferences for different health states and can take on values from 0 (death) to 1 (perfect health) [58]. Since our time perspective is one year, in the present case the QALY for a single patient coincides with the health utility value. In order to express the QALYs lost due to undertreatment in monetary terms, we evaluated them using a willingness-to-pay (WTP) threshold, which represents a measure of the amount of money a society is willing to invest in order to improve health (in this case, to obtain one additional QALY). Health utility and WTP values were retrieved from a review of the literature. In particular, the WTP threshold was sourced from an empirical work carried out by Woods and colleagues [59]. We adopted a conservative approach and considered the lower WTP value reported by the authors (i.e., $16,712, corresponding to €14,860 in 2018). In line with expert opinion, we assumed that only moderate-severe OSA has a substantial impact on patients’ QoL, therefore the present analysis was focused on this patient subpopulation. QALYs value lost was computed according to the following formulas, for alive and dead moderate-severe patients respectively:

The total economic burden of OSA for the society was estimated by summing the costs of each condition influenced by the disease, the costs due to OSA’s diagnosis and treatment and the QALYs value lost.

All costs were adjusted for inflation to 2018 (most updated data when analysis was carried out) in their national currency using gross domestic product deflators retrieved from the Organisation for Economic Co-operation and Development (OECD) database [60]. Finally, all costs were adjusted for purchasing power differences using OECD Purchasing Power Parities (PPPs) for GDP for 2018 [60]. PPPs serve both as currency convertors and as spatial price deflators: they convert different currencies to a common currency and, in the process of conversion, equalise their purchasing power by eliminating the differences in price levels between countries. This methodology can ensure better comparability between different currencies. As a one-year time-horizon was considered, no discounting on costs was applied.

Sensitivity analysis

A one-way deterministic sensitivity analysis was performed in order to account for uncertainty and test robustness of results regarding conditions’ burden influenced by OSA. In particular, all key parameters of the analysis were tested and varied according to 95% confidence intervals (95% CIs) or plausible ranges of variation: OSA prevalence (±10%), conditions’ prevalence (±10%), magnitude of association (95% CIs) and conditions’ costs (±10%). Each variable was tested at the upper and lower limits of its respective interval. Results were graphically reported through a tornado diagram.

Results

OSA prevalence in Italy

The review of the literature revealed that epidemiological studies on OSA in Italy are scant [61-63], and the estimates provided were either outdated or focused on a local context, therefore hardly generalizable. Moreover, as OSA is a highly undiagnosed condition, epidemiological studies conducted on sample of individuals with suspected OSA are likely to be biased and capture only diagnosed prevalence, thus underestimating the real one. On the basis of clinical expert opinion, two European-based and one literature-based studies were included for OSA’s prevalence estimate in the Italian population aged 15–74 years. In particular, prevalence data provided by one of the European studies identified (HypnoLaus [31]), a population-based study, were considered both representative of OSA epidemiology in Italy, reflecting the prevalence ratio of 2:1 among men and women observed in the Italian adult population [63], and reliable (i.e., reflecting the actual prevalence), as the sample of individuals tested with polysomnography was randomly drawn from the general population, considering all individuals regardless any OSA suspicions. The literature-based study identified [64], which used publicly available data and expert opinion to estimate the global prevalence of OSA, provided lower prevalence data for Italy than those obtained from the HypnoLaus. Therefore, in order to take into account the full range of variation of prevalence estimates, both studies were included in our analyses. The other European-based study by Hedner and colleagues [65] was used to stratify patients according to OSA severity as measured by AHI. Finally, data on the resident population in Italy in 2018 were sourced from Istat [48] and used to derive the number of prevalent cases. Additional information on prevalence estimates are reported in S1 File.

Results suggest that OSA prevalence in Italy is substantial, with moderate-severe condition (AHI≥15) affecting between 9% and 27% of the population aged 15–74 years (Table 1). On the basis of the data collected by the Italian association of apneic patients (Associazione Apnoici Italiani Onlus), in Italy patients currently treated with continuous and automatic positive airway pressure (the standard of care), are approximately 230,000, representing around 2% (model 1) and 6% (model 2) of the estimated prevalence of moderate-severe OSA. According to expert opinion, the patients currently diagnosed are approximately twofold than those treated (around 4% (model 1) and 12% (model 2) of moderate-severe OSA patients), but still far from the actual prevalence rates. These data suggest a substantial gap in both OSA diagnosis and treatment.

Table 1

Prevalence of OSA for the general adult population in Italy (aged 15–74).

	Estimates from the population-based study (model 1)			Estimates from the literature-based study (model 2)
	Female	Male	Total	Female	Male	Total
Rates
Mild (5≤AHI<15)	29.2%	24.8%	27.1%	7.2%	5.2%	6.2%
Moderate-severe (AHI≥15)	18.3%	36.2%	27.1%	5.9%	11.7%	8.8%
Moderate (15≤AHI<30)	9.8%	14.5%	12.1%	3.2%	4.7%	3.9%
Severe (AHI≥30)	8.5%	21.7%	15.0%	2.8%	7.0%	4.9%
Overall (AHI≥5)	47.5%	61.0%	54.2%	13.1%	16.9%	15.0%
Absolute values
Mild (5≤AHI<15)	6,703,067	5,582,051	12,285,118	1,657,025	1,163,534	2,820,559
Moderate-severe (AHI≥15)	4,193,897	8,135,717	12,329,614	1,354,459	2,627,507	3,981,966
Moderate (15≤AHI<30)	2,236,745	3,260,161	5,496,906	722,378	1,052,900	1,775,278
Severe (AHI≥30)	1,957,152	4,875,556	6,832,708	632,081	1,574,607	2,206,688
Overall (AHI≥5)	10,896,964	13,717,768	24,614,732	3,011,484	3,791,041	6,802,526

Source. Our elaboration from Heinzer et al (2015) [31], Benjafield et al (2019) [64], Hedner et al (2011) [65] and Istat data [48].

Conditions influenced by OSA

Of the 702 studies retrieved, 86 were included for full-text reading (Fig 1), as they did not meet any of the exclusion criteria previously established (S2 Table). If more than one study was available for the same condition, only the most recent and comprehensive one was included. However, if studies on the same condition reported discordant results on the association with OSA, they were all included in the analysis. On the basis of full-texts analysis and reference screening, 23 meta-analyses were selected [66-88] (Fig 1). Unfortunately, for some conditions judged relevant by clinicians involved in the research board (e.g., arrhythmias, psoriasis), screened studies either did not provide sufficient quantitative data on the association or provided an association measure that could not be used for PAF calculation (e.g., Cohen’s d, rate ratio), therefore they were excluded from the analysis. For each condition included, data were extracted according to a predefined template presented in the Methods section (Table 2). Four conditions included in data extraction but either judged not clinically meaningful by experts or for which there is a lack of epidemiological/cost evidence (i.e., spontaneous cerebrospinal fluid leak, floppy eyelids syndrome, nonarteritic anterior ischemic optic neuropathy, pulmonary edema during pregnancy) were ultimately excluded from COI analysis, as well as conditions with a non-statistically significant association (Table 2). Overall, 26 clinical and non-clinical conditions from 18 meta-analyses were considered for the estimation of OSA’s economic burden (Fig 1, Table 2). The PRISMA checklist [46] is provided in the S2 File.

Fig 1

Systematic literature review—Screening process (PRISMA flow diagram).

*Reasons for full-text exclusion: 1) OSA exclusively investigated as a consequence of other conditions; 2) no quantitative data provided on the association of OSA with other conditions; 3) focus on parameters that could eventually identify a clinical condition, but not on the clinical condition itself; 4) lack of a control group of non-OSA patients; 5) unclear data on the direction of the association between OSA and the condition investigated; 6) focus on OSA together with other sleep disorders; 7) measure of association that could not be used for PAF calculation; 8) association between increase in AHI and the condition investigated.

Table 2

Results of systematic literature review: Association between OSA and other conditions.

Condition	OSA severity	Association measure	Magnitude	95% CIs	p-value	Included in COI analysis	Source
All-cause mortality	Mild	RR	1.26	0.77–2.07	NS	No	Xie et al (2017) [66]
	Moderate	RR	1.04	0.60–1.79	NS	No
	Severe	RR	1.54	1.21–1.97	<0.001	Yes
Cancer mortality	Mild	HR	0.79	0.46–1.34	NS	No	Zhang et al (2017) [67]
	Moderate	HR	1.92	0.63–5.88	NS	No
	Severe	HR	2.09	0.45–9.81	NS	No
	Overall	HR	1.38	0.79–2.41	NS	No
Cardiovascular mortality	Mild	RR	1.80	0.68–4.76	NS	No	Xie et al (2017) [66]
	Moderate	RR	1.11	0.53–2.35	NS	No
	Severe	RR	2.96	1.45–6.01	0.003	Yes
Cancer	Mild	HR	0.91	0.74–1.13	NS	No	Zhang et al (2017) [67]
	Moderate	HR	1.07	0.86–1.33	NS	No
	Severe	HR	1.03	0.85–1.26	NS	No
	Overall	HR	1.04	0.92–1.16	NS	No
	Overall	RR	1.40	1.01–1.95	0.04	Yes	Palamaner Subash Shantha et al (2015) [68]
Diabetic retinopathy	Overall	OR	2.01	1.49–2.72	<0.05	Yes	Zhu et al (2017) [69]
Diabetic kidney disease	Overall	OR	1.59	1.16–2.18	<0.05	Yes	Leong et al (2016) [70]
Type 2 diabetes mellitus	Mild	RR	1.22	0.91–1.63	NS	No	Wang et al (2013) [71]
	Moderate-severe	RR	1.63	1.09–2.45	0.018	Yes
Metabolic syndrome	Mild	OR	2.39	1.65–3.46	<0.05	Yes	Xu et al (2015) [72]
	Moderate-severe	OR	3.42	2.28–5.13	<0.05	Yes
Depression	Overall	OR†	1.12	0.78–1.47	NS	No	Edwards et al (2020) [73]
		RR‡	2.18	1.47–2.88	0.005	Yes
Erectile dysfunction	Overall (men)	RR	1.82	1.12–2.97	<0.05	Yes	Liu et al (2015) [74]
Female sexual dysfunction	Overall (women)	RR	2.00	1.29–3.08	<0.05	Yes	Liu et al (2015) [74]
Parkinson’s disease	Overall	HR	1.59	1.36–1.85	<0.001	Yes	Sun et al (2020) [75]
Stroke	Mild	RR	1.29	0.69–2.41	NS	No	Xie et al (2017) [66]
	Moderate	RR	1.35	0.82–2.23	NS	No
	Severe	RR	2.15	1.42–3.24	<0.001	Yes
Spontaneous cerebrospinal fluid leak	Overall	OR	3.43	1.55–7.59	0.002	No	Bakhsheshian et al (2015) [76]
Floppy eyelids syndrome	Overall	OR	4.70	2.98–7.41	<0.001	No	Huon et al (2016) [77]
Glaucoma	Overall	OR	1.24	1.20–1.28	<0.001	Yes	Huon et al (2016) [77]
Nonarteritic anterior ischemic optic neuropathy	Overall	OR	6.18	2.00–19.11	0.002	No	Wu et al (2016) [78]
Resistant hypertension	Overall	OR	2.84	1.70–3.98	<0.05	Yes	Hou et al (2018) [79]
Essential hypertension	Mild	OR	1.18	1.09–1.27	<0.05	Yes	Hou et al (2018) [79]
	Moderate	OR	1.32	1.20–1.43	<0.05	Yes
	Severe	OR	1.56	1.29–1.84	<0.05	Yes
Ischemic heart disease	Mild	RR	1.25	0.95–1.66	NS	No	Xie et al (2017) [66]
	Moderate	RR	1.38	1.04–1.83	0.026	Yes
	Severe	RR	1.63	1.18–2.26	0.003	Yes
Heart failure	Mild	RR	1.02	0.78–1.34	NS	No	Xie et al (2017) [66]
	Moderate	RR	1.07	0.74–1.54	NS	No
	Severe	RR	1.44	0.94–2.21	NS	No
Aortic dissection	Mild	OR	1.60	1.01–2.53	0.04	Yes	Zhou et al (2018) [80]
	Moderate-severe	OR	4.43	2.59–7.59	<0.001	Yes
Allergic rhinitis	Overall	OR	1.73	0.94–3.20	NS	No	Cao et al (2018) [81]
Non-alcoholic fatty liver disease	Overall	OR	2.34	1.71–3.18	<0.001	Yes	Musso et al (2013) [82]
Gastroesophageal reflux disease	Overall	OR	1.57	1.07–2.08	<0.05	Yes	Wu et al (2018) [83]
Gout	Overall	HR	1.25	0.91–1.70	NS	No	Shi et al (2019) [84]
Pre-eclampsia	Overall (women)	OR	2.35	2.15–2.58	<0.001	Yes	Liu et al (2019) [85]
Gestational hypertension	Overall (women)	OR	1.97	1.51–2.56	<0.001	Yes	Liu et al (2019) [85]
Gestational diabetes	Overall (women)	RR	1.40	0.62–3.19	NS	No	Xu et al (2014) [86]
	Overall (women)	OR	1.55	1.26–1.90	<0.001	Yes	Liu et al (2019) [85]
Preterm delivery	Overall (women)	OR	1.62	1.29–2.02	<0.001	Yes	Liu et al (2019) [85]
Cesarean delivery	Overall (women)	OR	1.42	1.12–1.79	<0.001	Yes	Liu et al (2019) [85]
Pulmonary edema	Overall (women)*	OR	6.35	4.25–9.50	<0.001	No	Liu et al (2019) [85]
Car accidents	Overall	OR	2.43	1.21–4.89	0.013	Yes	Tregear et al (2009) [87]
Work accidents	Overall	OR	1.78	1.03–3.07	<0.001	Yes	Garbarino et al (2016) [88]

Note.

†Estimates obtained from a meta-analysis of cross-sectional studies.

‡Estimates were obtained from a meta-analysis of longitudinal studies.

*The focus was only on pregnant women.

Conditions’ burden associated with OSA

For the conditions included, epidemiological data were retrieved from different sources [48, 89–110] and reported in S3 File. Conditions’ prevalence data (or incidence when appropriate) were used, together with data on magnitude of association (Table 2) and prevalence of OSA (Table 1), to estimate the proportion of burden associated with OSA through PAF methodology [43, 51, 52]. The PAF for car and work accidents was derived considering only OSA population with excessive daytime sleepiness (EDS), estimated at 19% [35]. Moreover, for the conditions providing only estimates for overall OSA, a conservative approach was adopted and PAF was calculated considering moderate-severe subpopulation as, according to expert opinion, these patients are more likely to develop comorbidities than mild ones. Table 3 provides the results for PAF (i.e., the proportion of each condition influenced by the presence of OSA and its syndrome) and the total number of cases/year for each condition, calculated using OSA prevalence data from either the population-based (model 1) or the literature-based study (model 2), and stratified by OSA severity.

Table 3

Conditions’ burden influenced by OSA: PAF and number of cases/year among general adult population in Italy (aged 15–74 years).

Condition	OSA severity	Model 1		Model 2		Source of epidemiological data
		PAF	Number of cases/year	PAF	Number of cases/year
All-cause mortality	Severe	7.5%	11,129	2.6%	3,797	Istat [48]
Cardiovascular mortality	Severe	22.7%	7,377	8.7%	2,823	Istat [48]
Cancer	Overall*	9.7%	184,224	3.4%	64,038	AIOM-AIRTUM (2018) [89]
Diabetic retinopathy	Overall*	20.7%	246,930	7.8%	92,650	AMD et al (2015) [90]
Diabetic kidney disease	Overall*	13.5%	92,915	4.8%	33,131	AMD-SID (2018) [91]
						IDF (2017) [92]
Type 2 diabetes	Moderate-severe	14.5%	450,426	5.2%	162,188	IDF (2017) [92]
Metabolic syndrome	Mild	16.4%	2,454,641	3.9%	587,706	Tocci et al (2015) [93]
	Moderate-severe	23.2%	3,470,981	7.8%	1,171,728
Depression◻	Overall*	24.2%	175,121	9.4%	67,954	Istat (2018) [94]
Erectile dysfunction	Overall (men)*	22.8%	511,257	8.7%	196,081	Nicolosi et al (2003) [95]
Female sexual dysfunction	Overall (women)*	15.3%	1,014,992	5.6%	371,226	Graziottin (2007) [96]
Parkinson’s disease	Overall*	13.7%	7,726	4.9%	2,766	Riccò et al (2020) [97]
Stroke†	Severe	14.7%	10,757	5.3%	3,869	Stevens et al (2017) [98]
Glaucoma	Overall*	6.0%	48,430	2.0%	16,373	Tham et al (2014) [99]
Resistant hypertension	Overall*	32.5%	235,129	13.4%	97,135	Giampaoli et al (2015) [100]
						Dovellini (2000) [101]
Essential hypertension	Mild	3.2%	442,561	0.8%	103,155	Giampaoli et al (2015) [100]
	Moderate	2.4%	327,235	0.8%	107,445
	Severe	4.9%	673,131	1.6%	221,359	Dovellini (2000) [101]
Ischemic heart disease	Moderate	4.4%	99,296	1.5%	33,325	Giampaoli et al (2015) [100]
	Severe	8.6%	196,584	3.0%	67,625
Aortic dissection†	Mild	13.9%	224	3.6%	58	Pacini et al (2013) [102]
	Moderate-severe	48.1%	774	23.1%	372
Non-alcoholic fatty liver disease	Overall*	19.9%	1,844,121	7.0%	653,912	Younossi et al (2016) [103]
Gastroesophageal reflux disease	Overall*	11.0%	536,097	3.8%	185,754	Darbà et al (2011) [104]
Pre-eclampsia	Overall (women)*	19.5%	1,790	7.4%	676	Fox et al (2017) [105]
Gestational hypertension	Overall (women)*	14.9%	2,041	5.4%	744	FIGO (2016) [106]
Gestational diabetes	Overall (women)*	9.0%	4,486	3.1%	1,567	Meregaglia et al (2018) [107]
Preterm delivery	Overall (women)*	10.0%	2,801	3.5%	986	Merinopoulou et al (2018) [108]
Cesarean delivery	Overall (women)*	7.0%	11,525	2.4%	3,967	OECD [109]
Car accidents ‡	Overall*	5.3%	11,420	2.1%	92,650	Istat-Aci (2017) [110]
Work accidents ‡	Overall*	3.3%	845	1.2%	33,131	Istat-Aci (2017) [110]

Note. Model 1: Statistics calculated using OSA prevalence data derived from the population-based study. Model 2: Statistics calculated using OSA prevalence data derived from the literature-based study.

◻Estimates are referred to major depression.

†Incidence data were considered.

‡Only OSA population with excessive daytime sleepiness was considered for PAF calculation.

*Only conservative estimates (i.e., referred to moderate-severe subpopulation) were provided.

OSA economic burden

For all-cause and cardiovascular premature mortality, indirect costs were estimated using the friction cost method, for both model 1 and model 2 (S4 File). Cost data of all other conditions were retrieved from the literature [107, 111–129] and expressed in 2018 Euros standardized for inflation and PPP (S5 File). In order to avoid double counting, only productivity losses due to morbidity were considered for these conditions when the original study reported separate estimates for costs due morbidity and mortality, as indirect costs due to mortality were computed separately. Unfortunately, for some conditions, it was not possible to retrieve an Italian cost study. Moreover, the majority of studies did not report estimates for all cost categories, leading to a possible underestimation of the overall economic burden. Through the multiplication of the cost per patient/year by the number of prevalent (or incident) cases due to OSA, we estimated the total economic burden influenced by OSA in Italy in one year. Mean estimates are provided in Table 4. Results suggest that the economic burden due to conditions influenced by OSA in Italy is substantial and ranges from €10.7 billion (model 2) to €32.0 billion (model 1) per year, corresponding to €177 and €530 per Italian resident respectively. The main driver of economic burden are direct healthcare costs, which account for 60% and 57% of total cost according to model 1 and model 2 respectively, followed by indirect costs (37% and 39%) and direct non-healthcare costs (both 4%). Considering the health expenditure per capita in Italy in 2018 (€3,429) [130], the direct healthcare costs per resident generated by conditions influenced by OSA represent between the 3% (model 2) and 9% (model 1) of national health expenditure.

Table 4

Annual economic burden of conditions influenced by OSA in Italy.

	Model 1				Model 2
Condition	Direct healthcare cost	Direct non-healthcare cost	Productivity losses cost*	Total cost	Direct healthcare cost	Direct non-healthcare cost	Productivity losses cost*	Total cost
Mortality †			€ 17,468,314	€ 17,468,314			€ 5,960,283	€ 5,960,283
Cancer	€ 1,053,335,086	€ 843,866,787	€ 21,976,498	€ 1,919,178,370	€ 366,149,501	€ 293,336,287	€ 7,639,244	€ 667,125,033
Diabetic retinopathy	€ 75,903,881	€ 59,787,476	€ 142,872,419	€ 278,563,776	€ 28,479,821	€ 22,432,800	€ 53,607,020	€ 104,519,641
Diabetic kidney disease	€ 74,076,551			€ 74,076,551	€ 26,413,493			€ 26,413,493
Type 2 diabetes	€ 1,741,141,727		€ 1,960,219,449	€ 3,701,361,176	€ 626,945,056		€ 705,829,901	€ 1,332,774,957
Metabolic syndrome	€ 11,260,422,980		€ 531,818,651	€ 11,792,241,631	€ 3,343,442,091		€ 157,907,466	€ 3,501,349,558
Depression◻	€ 152,472,494	€ 86,853,842	€ 340,910,896	€ 580,237,232	€ 59,165,781	€ 33,702,967	€ 132,287,858	€ 225,156,606
Erectile dysfunction	€ 208,151,669			€ 208,151,669	€ 79,831,780			€ 79,831,780
Female sexual dysfunction	€ 772,808,563			€ 772,808,563	€ 282,649,080			€ 282,649,080
Parkinson’s disease	€ 47,486,623	€ 37,281,979	€ 9,360,588	€ 94,129,190	€ 16,997,509	€ 13,344,827	€ 3,350,558	€ 33,692,894
Stroke	€ 144,697,413	€ 91,324,306	€ 9,755,712	€ 245,777,431	€ 52,047,358	€ 32,849,162	€ 3,509,109	€ 88,405,629
Glaucoma	€ 47,690,291			€ 47,690,291	€ 16,122,559			€ 16,122,559
Resistant hypertension	€ 56,172,997			€ 56,172,997	€ 23,205,874			€ 23,205,874
Essential hypertension	€ 344,718,771			€ 344,718,771	€ 103,196,342			€ 103,196,342
Ischemic heart disease	€ 442,622,880	€ 103,029,886	€ 135,642,496	€ 681,295,262	€ 151,016,288	€ 35,152,252	€ 46,279,185	€ 232,447,725
Aortic dissection	€ 37,984,396			€ 37,984,396	€ 16,358,614			€ 16,358,614
Non-alcoholic fatty liver disease	€ 2,208,249,940		€ 8,158,942,384	€ 10,367,192,324	€ 783,029,477		€ 2,893,102,030	€ 3,676,131,507
Gastroesophageal reflux disease	€ 165,097,914		€ 99,881,300	€ 264,979,215	€ 57,205,202		€ 34,608,129	€ 91,813,331
Pre-eclampsia	€ 8,356,628			€ 8,356,628	€ 3,157,267			€ 3,157,267
Gestational hypertension	€ 24,202,545			€ 24,202,545	€ 8,824,400			€ 8,824,400
Gestational diabetes	€ 16,844,415			€ 16,844,415	€ 5,883,403			€ 5,883,403
Preterm delivery	€ 25,281,917		€ 27,402,594	€ 52,684,511	€ 8,897,225		€ 9,643,535	€ 18,540,759
Cesarean delivery	€ 28,991,021		€ 10,865,180	€ 39,856,201	€ 9,979,392		€ 3,740,051	€ 13,719,443
Car accidents	€ 106,754,952		€ 272,184,561	€ 378,939,513	€ 42,564,671		€ 108,523,736	€ 151,088,407
Work accidents	€ 7,900,413		€ 20,143,051	€ 28,043,464	€ 2,906,425		€ 7,410,278	€ 10,316,703
Total	€ 19,051,366,068	€ 1,222,144,276	€ 11,759,444,093	€ 32,032,954,437	€ 6,114,468,608	€ 430,818,296	€ 4,173,398,383	€ 10,718,685,287

Note. Model 1: Statistics calculated using OSA prevalence data derived from the population-based study. Model 2: Statistics calculated using OSA prevalence data derived from the literature-based study.

†Costs due to cardiovascular mortality were included in all-cause mortality costs in order to avoid double counting.

◻Estimates are referred to major depression.

*Only productivity losses due to morbidity were included for conditions different from mortality when the original study reported separate estimates for costs due morbidity and mortality.

The yearly per patient cost of OSA diagnosis and treatment in Italy amounts to approximately €381 and €256, respectively (see S6 File for all details on data sources and calculation). According to the Italian association of apneic patients (Associazione Apnoici Italiani Onlus) and expert opinion, in Italy there are approximately 460,000 patients diagnosed and 230,000 treated. Therefore, the total yearly cost of OSA diagnosis and treatment amounts to €175,347,041 and €58,880,000 respectively, with an overall cost of €234,227,041.

As regards estimation of QALYs value lost due to undertreatment, health utility values were derived from a study by Català and colleagues [131], who found a significant difference in utility values between treated (utility = 0.84) and untreated patients (utility = 0.79). By using these values in the formulas presented in the methods section, we estimated a QALYs value lost ranging from €2.8 billion (model 2) to €9.0 billion (model 1) (see S7 File for additional details on calculation).

As summarized by Table 5, in Italy the total economic burden of OSA ranges from around € 13.8 billion/year (model 2) to €41.3 billion/year (model 2).

Table 5

Total annual economic burden of OSA in Italy.

	Model 1	Model 2
OSA diagnosis and treatment	€ 234,227,041	€ 234,227,041
Conditions influenced by OSA	€ 32,032,954,437	€ 10,718,685,287
QALYs value lost	€ 9,029,365,722	€ 2,801,136,971
Total economic burden	€ 41,296,547,200	€ 13,754,049,299

All key parameters used to estimate conditions’ burden influenced by OSA were tested in one-way deterministic sensitivity analysis. The majority of them, however, did not significantly influence the results obtained in the base-case analysis. The tornado plot shows only those variables whose variation caused at least 1% increase or decrease of base-case result. For both model 1 (Fig 2) and model 2 (Fig 3), the five parameters with the highest impact on conditions’ burden influenced by OSA were the magnitude of association with OSA of metabolic syndrome, non-alcoholic fatty liver disease, type 2 diabetes and cancer, and OSA prevalence.

Fig 2

Tornado plot for sensitivity analysis (model 1).

Fig 3

Tornado plot for sensitivity analysis (model 2).

Discussion

This study aimed at providing reliable estimates of the extent of OSA consequences in Italy and assessing the societal economic burden associated with OSA in the adult population by performing a COI analysis. Several studies demonstrated that OSA is a severely underdiagnosed condition worldwide [1, 132, 133]. We estimated a prevalence of moderate-severe OSA in Italy ranging from approximately 4 to 12 million patients (9% to 27% of the adult population). However, the number of diagnosed and treated patients is substantially lower (around 460,000 and 230,000 patients respectively), suggesting a huge gap in both OSA diagnosis and treatment. The reasons underlying poor diagnosis of OSA are several, and start from lack of awareness [134, 135], both among healthcare professionals and general population, to limited routine screening and diagnostic sleep centres [136]. Even when a diagnosis occurred, evidence shows that acceptance and adherence to treatment with CPAP—despite its technological advances—is generally low, ranging from 30 to 60% [137, 138].

The systematic literature review revealed that several clinical and non-clinical conditions were found to be significantly influenced by OSA and its syndrome. Through the PAF approach, we attributed a portion of each conditions’ burden to OSA, which allowed us to estimate the economic impact associated with the sleep disorder. Results of COI revealed that the economic burden for the society due to conditions associated with OSA in Italy is very high, ranging from €10.7 to €32.0 billion per year, with the main cost driver represented by direct healthcare costs. Moreover, the QALYs value lost due to OSA undertreatment is substantial, and contributes at increasing OSA’s yearly economic burden by €2.8 to €9.0 billion.

Several studies demonstrated that appropriate diagnostic and therapeutic pathways for OSA may have a substantial impact in reducing clinical and non-clinical consequences related to the disease, whereas untreated disease may result in increased clinical and economic burden [3, 139]. In particular, therapy with CPAP was demonstrated to be effective in preventing the onset and reducing the burden of some of the associated conditions, including all-cause and cardiovascular mortality [140], stroke [141], car [142] and work accidents [143]. Overall, these results suggest that OSA’s underdiagnosis and undertreatment have a detrimental effect both on the onset of associated conditions and on patients’ quality of life, ultimately leading to loss of value for the society. An increasing awareness towards the disease is fundamental in order to implement appropriate diagnostic and treatment pathways for OSA patients and reduce its substantial clinical and economic burden.

Study limitations

This study has some limitations. First, the review performed may not be fully exhaustive as we did not consider individual studies but focused only on systematic reviews and meta-analyses, including the latter for COI analysis. The reason underlying this choice is that evidence on OSA’s association with other conditions is very heterogeneous, therefore we opted for the “systematic review of systematic reviews” method [47], which is recommended in all cases where individual studies are heterogeneous in terms of methods, definitions and results. Moreover, we further restricted the selection on systematic reviews presenting a meta-analysis because we needed a reliable quantitative assessment of the intensity of association between OSA and other conditions. Although a vast literature exists on OSA association with other conditions, in some cases single studies either provide insufficient quantitative evidence or no quantitative evidence at all. Second, due to lack of Italian data, we had to rely on OSA epidemiological estimates derived from two different studies, a population-based study conducted in another European country and a model-based study. Estimated prevalence data, although validated by a clinical expert, should be interpreted cautiously. Further research is needed in order to provide up-to-date evidence on OSA epidemiology in Italy, which in turn might increase awareness of the extent of conditions’ burden for our country. Third, few conditions’ prevalence data were lacking for Italy, and we had to use estimates derived from other countries. The same happened for cost data, although we adjusted for purchasing power differences to ensure better comparability between different currencies. Moreover, it was not always possible to retrieve data on all relevant cost components, namely direct non-healthcare costs and productivity losses due to morbidity, potentially leading to an underestimation of OSA economic burden.

Conclusions

Results of the present COI analysis suggest that the burden of OSA in Italy is substantial but subtle, because it is greatly hidden behind the cost of other conditions for which OSA is a risk factor. Moreover, underdiagnosis and low treatment rates are observed. More appropriate diagnosis rates and clinical pathways for OSA patients, in particular for moderate-severe population, are recommended.

Search strategy.

(DOCX)

Click here for additional data file.

Exclusion criteria.

(DOCX)

Click here for additional data file.

Additional information on OSA prevalence estimation.

(DOCX)

Click here for additional data file.

PRISMA checklist.

(DOCX)

Click here for additional data file.

Prevalence of conditions significantly associated with OSA.

(DOCX)

Click here for additional data file.

Indirect costs due to all-cause and cardiovascular mortality.

(DOCX)

Click here for additional data file.

Cost of conditions.

(DOCX)

Click here for additional data file.

Cost of OSA diagnosis and treatment.

(DOCX)

Click here for additional data file.

Additional information on QALYs value lost calculation.

(DOCX)

Click here for additional data file.

13 Apr 2021

PONE-D-21-03912

The invisible costs of obstructive sleep apnea (OSA): a cost-of-illness analysis

PLOS ONE

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Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #1: This study submitted by Borsoi and colleagues aimed at assessing the economic burden of OSA in the adult population in Italy. The attempt is interesting but there are several concerns regarding these data:

1-Litterature review is by far non exhaustive.

2-The novelty is limited as previous similar analysis and markov models have been conducted and published both in scientific journals or reported by Frost and Sullivan and Mc Kinsey (“The price of fatigue”) for the American academy of sleep medicine.

3-The main novelty is to provide these data for Italy. I think that the paper is more suitable for an Italian journal of health policy or management.

Reviewer #2: I think the topic is of outmost importance. The problem is hugely undermined in daily life. Therefore the possible outcomes in socioeconomic domain is a smart one to explore.

I only have one comment to the authors: We have seen in the last Covid outbreak that no tow country is same for medical measures. Therefore the sentence on line 136 "referred to other countries whose health care systems

can be comparable to the Italian one" may actually be off.

Reviewer #3: Obstructive sleep apnoea (OSA) is an underdiagnosed chronic disease with a high prevalence in adults. As it is becoming a significant social problem associated with a low quality of life and increased mortality, the cost-effectiveness ratio of diagnostic and therapeutic management of OSA is important to counteract the demand of objective diagnosis. This cost-of-illness study is considered an essential evaluation technique in health care, helping health-care decision-makers to set up and prioritize health-care policies and interventions. Therefore, this well written manuscript is worth being published.

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Reviewer #3: Yes: Sophia E Schiza

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27 May 2021

Dear Academic Editor and Reviewers,

We would like to thank you for your valuable comments, which helped us to further improve the manuscript. Please find below our answers to each revision request.

Academic Editor

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

We thank the Editor for this comment. We have checked the entire manuscript and revised the title, citing the method used (i.e. systematic review).

2. We note that your literature search was performed on 2018;to allow an up-to-date view of the topic, we would request that the search is updated. Moreover, to meet our criteria on reproducibility, please provide more information on how data obtained from the systematic review was analysed and used for your cost- of-illness analysis.

We thank the Editor for this useful comment. We have updated the review as requested (last update: 13th May 2021), revised the manuscript and all other materials (figures, supplementary files). Please, note that, besides the manuscript, the following files have been revised: Fig 1, Fig 2, Fig 3, S1 Table, S4 File, S5 File, S7 File. We reported the detail on how data obtained from the systematic review was analysed and used for cost-of-illness analysis in the main text. In particular, main information can be found in the methods section titled “Identification of conditions associated with OSA”.

3. We note that this manuscript is a systematic review or meta-analysis; our author guidelines therefore require that you use PRISMA guidance to help improve reporting quality of this type of study. Please upload copies of the completed PRISMA checklist as Supporting Information with a file name “PRISMA checklist”.

We thank the Editor for the comment. The PRISMA checklist had been already included in the original submission as supporting file (S4 File). However, we have updated it after the changes made to the manuscript.

4. Thank you for stating the following in the Financial Disclosure section:

CERGAS SDA Bocconi received an unrestricted grant for research from Philips S.p.A. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

We note that you received funding from a commercial source: Philips S.p.A

Please provide an amended Competing Interests Statement that explicitly states this commercial funder, along with any other relevant declarations relating to employment, consultancy, patents, products in development, marketed products, etc.

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We thank the Editor for the comment. We have changed the Competing Interests Statement and reported the amended version in the cover letter as requested.

5. Thank you for stating the following in the Competing Interests section:

Ludovica Borsoi, Patrizio Armeni, Gleb Donin and Francesco Costa have no competing interests todeclare. Luigi Ferini-Strambi declares the following competing interests (last 3 years): Philips-Respironics (fee for lectures), Resmed (fee for advisory board).

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authorshttp://journals.plos.org/plosone/s/competing-interests). If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

We thank the Editor for the comment. We have changed the Competing Interests Statement and reported the amended version in the cover letter as requested.

Reviewer #1

This study submitted by Borsoi and colleagues aimed at assessing the economic burden of OSA in the adult population in Italy. The attempt is interesting but there are several concerns regarding these data:

1. Literature review is by far non exhaustive.

We thank the Reviewer for the comment. We acknowledge the fact that our inclusion criteria are particularly strict, since we decided to include only systematic reviews and meta-analyses. The reason for this choice is that we were looking for directional associations between OSA and other conditions and realized that in most cases the literature was extremely heterogeneous in terms of methods, definitions and results: therefore we opted for the “systematic review of systematic reviews” (Smith et al., 2011) which is a recommended method in this kind of cases. Moreover, we further restricted the selection on systematic reviews presenting a meta-analysis because we needed a reliable quantitative assessment of the intensity of association between OSA and other conditions. We know that a vast literature exists, suggesting that OSA might be connected to many conditions, but in some cases there is no sufficient quantitative evidence and in other cases there is no quantitative evidence at all. We decided to keep a conservative approach. Our results show that, even based only on the most reliable quantitative evidence (systematic reviews with meta-analyses) the economic impact of OSA on the society is huge, well beyond the one suggested so far by less structured studies. In addition, with respect to the original manuscript, we have updated the literature review to 2021 in order to collect relevant evidence published after the original search carried out on November 19th, 2018. We have acknowledged in the “Study limitations” section that the review performed may not be fully exhaustive as we did not consider individual studies but focused only on systematic reviews and meta-analyses, including the latter for COI analysis and included the methodological reference suggesting the “systematic review of systematic reviews” approach. In this perspective, the aim of our literature review is to be exhaustive in systematic reviews and meta-analyses only.

2. The novelty is limited as previous similar analysis and markov models have been conducted and published both in scientific journals or reported by Frost and Sullivan and Mc Kinsey (“The price of fatigue”) for the American academy of sleep medicine.

3. The main novelty is to provide these data for Italy. I think that the paper is more suitable for an Italian journal of health policy or management.

We thank the Reviewer for these comments (2 and 3). We acknowledge the fact that other studies have been previously investigated the topic in other national contexts (we have cited the most relevant and comprehensive ones in the “Introduction” section). However, some of them either did not perform a systematic review to identify the conditions influenced by OSA (e.g., Hillman et al, 2018) or were not published in peer-reviewed journals (e.g., report by McKinsey) and in general all of them followed a less systematic and structured approach, thus not limiting the risk of biased analysis (e.g. the report by McKinsey was not transparent on the reason for inclusion of specific association measures between OSA and other conditions). We believe that, given the enormous amount of studies, but the relative scarcity of reliable synthetic quantitative information, a well structured, transparent and solid approach is necessary when investigating OSA’s relationship with other clinical and non-clinical conditions. Therefore, in addition to having adopted a systematic approach in the identification of studies reporting quantitative data on the influence of OSA on all other clinical and non-clinical conditions, the novelty of our study is that we included in our cost-of-illness analysis exclusively those providing the highest level of evidence, i.e. meta-analyses, overcoming the limitations of single studies. Moreover, unlike other studies, we provided also estimates on the QALYs value lost due to undertreatment of OSA. This is a major point, with strong policy implications, since it allows to measure not only the financial component of the cost-of-illness but also the economic counterpart of the health benefit lost by patients (which is the most important object of public expenditure in health). We show how important this component of the burden is, and no previous study did something similar. Although our results are focused on a specific national context (i.e., Italy), we believe that the methodological approach used, and extensively reported in our manuscript, may be interesting also for a non-Italian readership, also taking into account that all other studies are based on specific national contexts (e.g. Australia, the US, etc.). Differently from the previous literature, however, the specific context could be considered a limitation only with respect to epidemiological data, while our per-patient results are more generalizable than the ones presented in previous studies since we based our analysis on synthetic evidence and not on single studies.

Reviewer #2

1. I think the topic is of outmost importance. The problem is hugely undermined in daily life. Therefore the possible outcomes in socioeconomic domain is a smart one to explore. I only have one comment to the authors: We have seen in the last Covid outbreak that no tow country is same for medical measures. Therefore the sentence on line 136 "referred to other countries whose health care systems can be comparable to the Italian one" may actually be off.

We completely agree with the Reviewer’s point and revised the sentence. Moreover, we have also reported this limitation in a dedicated section (“Study limitations”). We thank the Reviewer for the useful comment.

Reviewer #3

1. Obstructive sleep apnoea (OSA) is an underdiagnosed chronic disease with a high prevalence in adults. As it is becoming a significant social problem associated with a low quality of life and increased mortality, the cost-effectiveness ratio of diagnostic and therapeutic management of OSA is important to counteract the demand of objective diagnosis. This cost-of-illness study is considered an essential evaluation technique in health care, helping health-care decision-makers to set up and prioritize health-care policies and interventions. Therefore, this well written manuscript is worth being published.

We thank the Reviewer for the positive and very kind feedback.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

17 Jun 2021

PONE-D-21-03912R1

The invisible costs of obstructive sleep apnea (OSA): Systematic review and cost-of-illness analysis

PLOS ONE

Dear Dr. Borsoi,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we have decided that your manuscript does not meet our criteria for publication and must therefore be rejected.

Specifically:

Based on the reviewer comments, which were quite different and based on the diversity of comments, in conclusion, we like to follow the more critical decision. May be a more specialized journal will appreciate more your specific work.

I am sorry that we cannot be more positive on this occasion, but hope that you appreciate the reasons for this decision.

Yours sincerely,

Thomas Penzel

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

Dear authors, we acknowledge the large amount of data. This is exceptional. We also acknowledge the hard work provided. However regarding a cost-of-illness analysis, our knowledgeable reviewers remain to be very critical. Therefore we decided to reject the manuscript.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #4: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #4: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #4: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #4: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #4: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #4: Enormous amount of data, and hardworking, sophisticated approach to a very complex topic, revealing many levels of socio-economic approach to health economy.

Well realized literature update, text, and data ameliorations according to the first couple of reviews!

The country preference (Italy) in view of this reviewer seems of minor relevance, because data mainly rely on costs, and prevalence of diverse illnesses in relation to OSA. The latter are rather independant of country.

Thus the elaborate methods are developed originally, and compiled in a concise way, presented in relatively brief descriptions.

The presentation of results mainly rely on the population attributable fraction (PAF), which is enhanced by use of numerous specific variables of health economy (OR, RR, HR, QALY, WTP, and different measures of OSA-probability). The reason for this elaborated development of PAF remains unclear (in the methods description). Moreover it is not discussed or critically reflected in the discussion/conclusions part. These methods are an innovative approach to the complex topic of compiling the "invisible" (indirect) costs of OSA. Because of reasons of this intelligent, unique approach to specific topics of socio-economy, it becomes clear that the article does not completely fulfill the criteria of PLOS.

A journal of health economy seems appropriate for publication (e.g. Eur. J Health Econ., Health Economics, J Health Economics).

Their readers are suggested to be customized to the methodological approach.

Thus reviewer encourages the authors to publish in one of these lines of business.

With respect to the many additional S1-9 files it seems rather difficult to understand data processing completely.

In relation to this, the length of the manuscript is rather brief, but overcrowded by the many assumptions (partly from literature) to implement the various items and methodological techniques of health economy.

Question: Female sexual dysfunction for development of PAF data in OSA is well accepted. But what is the contribution of Caesarean delivery to PAF in OSA?

General discussion: Aren't the variables used rather part of indirect costs instead of invisible (intangible) costs used in the title?

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #4: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

- - - - -

For journal use only: PONEDEC3

15 Feb 2022

Dear Academic Editor and Reviewer,

Please find below our answers to your valuable comments.

Academic Editor

1. Based on the reviewer comments, which were quite different and based on the diversity of comments, in conclusion, we like to follow the more critical decision. May be a more specialized journal will appreciate more your specific work.

I am sorry that we cannot be more positive on this occasion, but hope that you appreciate the reasons for this decision.

Additional Editor Comments :

Dear authors, we acknowledge the large amount of data. This is exceptional. We also acknowledge the hard work provided. However regarding a cost-of-illness analysis, our knowledgeable reviewers remain to be very critical. Therefore we decided to reject the manuscript.

The Academic Editor's decision appears to be in contrast with the comments received by the majority of reviewers in both rounds of revision and is also manifestly inconsistent with the points on which the Editor asked the authors to intervene on. In fact, in the first round of revision (mainly favorable, as two of the reviewers outlined the importance of the topic, and one of them explicitly underlined that the manuscript was worth being published), the Editor asked us to update the systematic review in order to "allow an up-to-date view of the topic". Following the Editors' comment, we updated the literature review, that required a substantial work. However, in the second round of revision, despite having acknowledged "the large amount of data", "the hard work provided" and the rigor of the methods used (reviewer's comment: "Enormous amount of data, and hardworking, sophisticated approach to a very complex topic", "Well realized literature update, text, and data ameliorations", "methods are developed originally, and compiled in a concise way"), the Editor decided that the cost-of-illness was not of interest of the journal ("a more specialized journal will appreciate more your specific work"). Moreover, we would like to underline that PLOS ONE has published several cost-of-illness studies over the last years, and some of them have used methods similar to those presented in our paper. We include here a non-exhaustive but exemplary list of cost-of-illness analyses published on the journal, some of which are very recent:

• Armour, Mike, et al. "The cost of illness and economic burden of endometriosis and chronic pelvic pain in Australia: A national online survey." PloS one 14.10 (2019): e0223316.

• Curado, Daniel da Silva Pereira, et al. "Direct cost of systemic arterial hypertension and its complications in the circulatory system from the perspective of the Brazilian public health system in 2019." PloS one 16.6 (2021): e0253063.

• de Oliveira, Michele Lessa, Leonor Maria Pacheco Santos, and Everton Nunes da Silva. "Direct healthcare cost of obesity in Brazil: an application of the cost-of-illness method from the perspective of the public health system in 2011." PloS one 10.4 (2015): e0121160.

• Ernstsson, Olivia, et al. "Cost of illness of multiple sclerosis-a systematic review." PloS one 11.7 (2016): e0159129.

• Ilboudo, Patrick G., et al. "Cost-of-illness of cholera to households and health facilities in rural Malawi." PloS one 12.9 (2017): e0185041.

• Javanbakht, Mehdi, et al. "Cost-of-illness analysis of type 2 diabetes mellitus in Iran." PloS one 6.10 (2011): e26864.

• Jo, Minkyung, et al. "The cost-of-illness trend of schizophrenia in South Korea from 2006 to 2016." PloS one 15.7 (2020): e0235736.

• Matsumoto, Kunichika, et al. "Cost of illness of hepatocellular carcinoma in Japan: A time trend and future projections." Plos one 13.6 (2018): e0199188.

• Moran, Patrick S., et al. "Economic burden of maternal morbidity–A systematic review of cost-of-illness studies." PloS one 15.1 (2020): e0227377.

• Oliveira, Luana Nice da Silva, Alexander Itria, and Erika Coutinho Lima. "Cost of illness and program of dengue: A systematic review." PloS one 14.2 (2019): e0211401.

• Pares-Badell, Oleguer, et al. "Cost of disorders of the brain in Spain." PloS one 9.8 (2014): e105471.

• Steinke, Sabine IB, et al. "Cost-of-illness in psoriasis: comparing inpatient and outpatient therapy." PLoS One 8.10 (2013): e78152.

Based on the positive comments on the methodological quality and relevance of results and on the fact that this kind of studies has been often published in this journal, we believe that this manuscript could be relevant for PLOS ONE.

Reviewer #4:

1. Enormous amount of data, and hardworking, sophisticated approach to a very complex topic, revealing many levels of socio-economic approach to health economy.

Well realized literature update, text, and data ameliorations according to the first couple of reviews!

The country preference (Italy) in view of this reviewer seems of minor relevance, because data mainly rely on costs, and prevalence of diverse illnesses in relation to OSA. The latter are rather independent of country.

Thus the elaborate methods are developed originally, and compiled in a concise way, presented in relatively brief descriptions.

We thank the reviewer for the positive feedback.

2. The presentation of results mainly rely on the population attributable fraction (PAF), which is enhanced by use of numerous specific variables of health economy (OR, RR, HR, QALY, WTP, and different measures of OSA-probability). The reason for this elaborated development of PAF remains unclear (in the methods description). Moreover it is not discussed or critically reflected in the discussion/conclusions part.

These methods are an innovative approach to the complex topic of compiling the "invisible" (indirect) costs of OSA. Because of reasons of this intelligent, unique approach to specific topics of socio-economy, it becomes clear that the article does not completely fulfill the criteria of PLOS.

A journal of health economy seems appropriate for publication (e.g. Eur. J Health Econ., Health Economics, J Health Economics).

Their readers are suggested to be customized to the methodological approach.

Thus reviewer encourages the authors to publish in one of these lines of business.

We thank the reviewer for the comments. As regards the PAF, as explained in the methods section, we had to rely on different formulae as the measures of association of OSA with other conditions found in the meta-analyses included were heterogeneous (i.e., relative risk, odds ratio or hazard ratio) and required different approaches. In the manuscript, we have clearly specified the references we relied on in order to select the most appropriate formulae on the basis of association data.

As regards the adherence of our manuscript with the journal's scope, we would like to underline that PLOS ONE has published several cost-of-illness studies over the last years, and some of them have used methods similar to those presented in our paper. Therefore, we believe that our manuscript could be relevant for the journal and its audience. Please find below some examples of cost-of-illness studies published on PLOS ONE:

• Armour, Mike, et al. "The cost of illness and economic burden of endometriosis and chronic pelvic pain in Australia: A national online survey." PloS one 14.10 (2019): e0223316.

• Curado, Daniel da Silva Pereira, et al. "Direct cost of systemic arterial hypertension and its complications in the circulatory system from the perspective of the Brazilian public health system in 2019." PloS one 16.6 (2021): e0253063.

• de Oliveira, Michele Lessa, Leonor Maria Pacheco Santos, and Everton Nunes da Silva. "Direct healthcare cost of obesity in Brazil: an application of the cost-of-illness method from the perspective of the public health system in 2011." PloS one 10.4 (2015): e0121160.

• Ernstsson, Olivia, et al. "Cost of illness of multiple sclerosis-a systematic review." PloS one 11.7 (2016): e0159129.

• Ilboudo, Patrick G., et al. "Cost-of-illness of cholera to households and health facilities in rural Malawi." PloS one 12.9 (2017): e0185041.

• Javanbakht, Mehdi, et al. "Cost-of-illness analysis of type 2 diabetes mellitus in Iran." PloS one 6.10 (2011): e26864.

• Jo, Minkyung, et al. "The cost-of-illness trend of schizophrenia in South Korea from 2006 to 2016." PloS one 15.7 (2020): e0235736.

• Matsumoto, Kunichika, et al. "Cost of illness of hepatocellular carcinoma in Japan: A time trend and future projections." Plos one 13.6 (2018): e0199188.

• Moran, Patrick S., et al. "Economic burden of maternal morbidity–A systematic review of cost-of-illness studies." PloS one 15.1 (2020): e0227377.

• Oliveira, Luana Nice da Silva, Alexander Itria, and Erika Coutinho Lima. "Cost of illness and program of dengue: A systematic review." PloS one 14.2 (2019): e0211401.

• Pares-Badell, Oleguer, et al. "Cost of disorders of the brain in Spain." PloS one 9.8 (2014): e105471.

• Steinke, Sabine IB, et al. "Cost-of-illness in psoriasis: comparing inpatient and outpatient therapy." PLoS One 8.10 (2013): e78152.

3. With respect to the many additional S1-9 files it seems rather difficult to understand data processing completely.

In relation to this, the length of the manuscript is rather brief, but overcrowded by the many assumptions (partly from literature) to implement the various items and methodological techniques of health economy.

We thank the reviewer for the comments. The structure of our manuscript is the result of a clear and reasoned choice. In the main text, indeed, we provide information on the most relevant methodological aspects that allow the reader to understand the results presented. Through the supplementary materials, instead, we aimed at providing additional information on some methodological steps that, despite not being fundamental to understand the concepts discussed in the main text, are deemed useful in order to fully grasp the results obtained and ensure transparency of our work.

We acknowledge that we relied on some assumptions in order to develop our analyses, but we thoroughly justified and referenced them throughout the text.

4. Female sexual dysfunction for development of PAF data in OSA is well accepted. But what is the contribution of Caesarean delivery to PAF in OSA?

We thank the reviewer for the question. There are several studies, included in the meta-analysis by Liu et al (2019), which demonstrated that OSA is related to an increased risk for Caesarean delivery. Therefore, as our study aims at estimating the economic burden influenced by OSA, i.e. the proportion of the cost-of-illness of conditions for which OSA is a proven risk factor that can be attributed to OSA itself, we included this maternal-related outcome in our analyses.

5. General discussion: Aren't the variables used rather part of indirect costs instead of invisible (intangible) costs used in the title?

We thank the reviewer for the question. When we talk about the "invisible costs" of OSA in the title, we are not referring to a specific cost category (e.g. indirect costs), but rather to the fact that the burden generated by OSA is somehow hidden (thus "invisible") behind the cost of other conditions for which it is a risk factor.

Submitted filename: Response to Reviewers_round2.docx

Click here for additional data file.

6 May 2022

The invisible costs of obstructive sleep apnea (OSA): Systematic review and cost-of-illness analysis

PONE-D-21-03912R2

Dear Dr. Borsoi,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Tai-Heng Chen, M.D.

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

Reviewer #6: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #4: The value of this review is the approach to give numbers to invisible health care costs, especially the consideration in relation to various diseases!

But things for CPAP may change very fast: preferred mode of therapy, additional kinds of other therapies, patient's adherence, national healthcare conditions, etc. This will have enormous impact on costs. Could you briefly refer to such developments?

Reviewer #5: The authors have well answered to most of queries.

This is an important topic to consider in beween medecine and economics.

Reviewer #6: After the previous revisions of the text, I suggest that the manuscript is ready for the publication.

I think it is interesting for the Plos One Journal.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #4: No

Reviewer #5: No

Reviewer #6: No

12 May 2022

PONE-D-21-03912R2

The invisible costs of obstructive sleep apnea (OSA): Systematic review and cost-of-illness analysis

Dear Dr. Borsoi:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Tai-Heng Chen

Academic Editor

PLOS ONE