In terms of working-age deaths (<65 years), there were 19 889 deaths related to HCV between 2007 and 2011. 1270 of these deaths were recorded because of hepatitis C, 4336 because of HCC, 6796 because of cirrhosis, 2208 because of other HCV-associated liver diseases and 5279 because of HIV–HCV coinfection (Table 2). After adjusting for the attribution of risks, deaths in the population under 65 years decreased to 8707 (baseline case); 1270 of them were directly attributable to hepatitis C, 2602 to HCC 2718 to cirrhosis, 1325 to other hepatic diseases and 792 to HIV/AIDS (Table 3). The highest death incidence in individuals younger than 65 years of age occurred in 2007 (1814 deaths) and the lowest incidence occurred in 2011 (1647 deaths).
The translation of these deaths to YPLL resulted in 279 135 YPPLL; 18 160 of these were attributable to hepatitis C, 44 378 to HCC, 78 971 to cirrhosis and 28 238 to other HCV-related hepatic disorders and 109 388 to HIV/AIDS (Table 2). Once the risk factors were applied, YPPLL related to hepatitis C decreased sharply to 109 726 (baseline case); 18 160 of these were directly because of hepatitis C, 26 627 because of HCC, 31 588 because of cirrhosis, 16 943 because of other liver disorders and 16 408 because of HIV/AIDS. The year with the highest incidence of YPPLL was 2007 (23 975 YPPLL), whereas the lowest incidence occurred in 2011 (19 706) (Table 3).
Once correction factors were applied to labour loss attributable to HCV infection (baseline case) between 2007 and 2011, the productivity losses caused by premature deaths associated with hepatitis C in Spain have been estimated at 1054.7 million euros, ranging from 243.4 million euros in 2007 to 177.6 million euros in 2011 (Table 4). Of the total loss estimated, 18.6% were recorded because of hepatitis C, 24.6% because of HCC, 30.1% because of cirrhosis, 15.9% because of other liver diseases and 10.7% because of HIV–HCV coinfection.
Two sensitivity analyses were carried out to observe how the results varied on changing the most relevant parameters of the model. In the first analysis, the rates of attributable risk were modified as described in methods (see Table 1 Supplementary data, Supplemental digital content 1, http://links.lww.com/EJGH/A21). According to the percentages of attributable risk described in scenario 2, the labour productivity losses directly or indirectly attributable to hepatitis C between 2007 and 2011 amounted to up to 1243 million euros, ranging from 287.3 million in 2007 to 209.3 million in 2011 (Table 5). 15.8% of the total losses were because of hepatitis C, 24.4% because of HCC, 32% because of cirrhosis, 15.7% because of other hepatic diseases and 12.1% because of HIV–HCV coinfection. Using percentages of attributable risk described in scenario 3, labour losses would increase 906.0 million euros over the entire period analysed, ranging from 208.9 million in 2007 to 152.7 million euros in 2011. 21.7% of the total losses corresponded to hepatitis C, 23.9% to HCC, 30.7% to cirrhosis, 15.4% to other liver diseases and 8.3% to HIV–HCV coinfection.
The average productivity loss per HCV premature death is up to 120 000 euros in the period analysed. Comparing this figure with the current treatment cost of HCV in Spain (which may range from 25 700 from 50 400 euros) or with the estimated cost of a liver transplant (above 70 000 euros, only in-patient healthcare resources, excluding the after-treatment monitoring and review), the huge impact that premature deaths have on the total costs attributable to HCV infection is clear. New oral drugs for hepatitis C have completed interferon-free phase III clinical trials and several phase II clinical trials of new interferon-free regimes are ongoing. All these drugs have shown better efficacy in clearing the virus, are better tolerated and require shorter treatments than the current standard of care. Some of these new drugs have recently been approved in the USA and in the EU 33–44. Many new interferon-free regimens achieve rates of sustained virological response ranging from 88 to 100% 45. However, the foreseeable scenario for these therapies is uncertain as accessibility to treatment, even in many developed countries, might be restricted 46. In this sense, not taking account of the nonhealth costs in the economic evaluations of new treatments may have important consequences on the final decision on public financing, pricing and rational use of public resources. In this respect, resources should not be allocated solely according to the burden of a specific disease, but according to where the greatest benefits in terms of health intervention occur; studies on the cost of disease allow to reveal a relevant dimension of a health problem and provide valuable information for society and decision-makers on the relative and absolute importance of the disease and therefore help to design and implement health policies.
Despite the constraints of these types of analysis, governments of many countries and regions continue to promote this work 30 because public decision makers consider information on the economic impact caused by chronic diseases and public-health problems as a valuable tool for the planning and evaluation of their policies 47–49. However, this information does not replace, but can be complementary to epidemiological data on morbidity and mortality and disabilities caused by a disease. In this sense, cost of illness is one indicator of the consequences of an illness, expressed in monetary terms. These non-healthcare costs are not decorative embellishments in obscure academic studies. They reflect real burdens that have to be carried by specific individuals or by society 50. Therefore, the usefulness of a cost study is to identify the economic impact of a particular disease, showing those costs that were not visible or known.
This work has some limitations. The first is that our analysis is based on data provided by the Official Register of Deaths, which in turn relies on death certificates, and HCV infection may be under-reported on death certificates 60. An ideal study design would be to follow a cohort of HCV patients over an extended period of time using a control group to identify differences in effects on healthcare costs, productivity losses and health indicators. Thus, we would observe the differences in costs (health and nonhealth) and health effects directly instead of applying the method of fractional attributable risk, which may incur bias arising from the presence of multiple risk factors. Nevertheless, the fractional attributable risk approach is epidemiologically oriented, and was chosen in the light of the available data 23.
A second limitation that should be pointed out is the fact that we have used the wages and employment rates in the general population (except for HIV/HCV). Although some studies did not detect a lower employment rate in some communities with HCV infection 61, it could be argued that IDU is the predominant route of transmission in some countries, and consequently, the employment rate of populations infected by IDU might be lower than the employment rate of the general population. Nevertheless, blood transfusions, intravenous drug use and hospitalizations have been associated independently with HCV infection in Spain 62, and no evidence on the mode of infection could be identified in nearly 40% of HCV 63. This limitation suggests that more research needs to be developed to gain in-depth knowledge of the labour status (employment and wages) of individuals with HCV.
The theoretical approach used in the study is the human capital theory. This is the most commonly used method to carry out cost-of-illness studies in the health economics literature. However, this method has received some criticisms and there are alternative approaches that can be used for the analyses such as the friction cost method 65. The methodological differences between the two approaches are discussed in detail in other articles 66–69, and the methodological discussion of the suitability of one method versus the alternative is far from being resolved in the health economics literature 67,70,71. We will not repeat it here, but it should be noted that the two approaches produce very different results, with lower values in the friction costs method.
The authors thank Sandra Lucia Vidal Perez-Campoamor and María Costi their support and help.
This study was funded by a research grant from Abbvie.
There are no conflicts of interest.
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