Economic impact of metabolic dysfunction-associated steatotic liver (MASLD) in Italy. Analysis and perspectives

Economic impact of metabolic dysfunction-associated steatotic liver (MASLD) in Italy. 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Analysis and perspectives Enrico Torre, Sergio Di Matteo, Chiara Martinotti, Umberto Goglia, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3755157/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: MASLD constitutes the ominous shadow of obesity and diabetes mellitus, destined to become pandemics for the coming decades. MASLD is a multisystem disease presenting an increased risk of developing cardio-nephrometabolic complications, extrahepatic tumors, and the obvious liver-related complications. Aim of our study is to evaluate the economic impact of MASLD among Italian population from the Italian National Healthcare Service (NHS) perspective. Methods: MASLD economic impact was assessed developing a calculation model in Microsoft Excel®, from the Italian NHS perspective, considering healthcare resources and direct costs. Target population has been defined based on prevalence data. A literature search was conducted and the main MASLD-related complications were identified, corresponding to: MASH, with relative risk of evolution into CC, DCC, HCC, T2 diabetes mellitus, cardiovascular diseases, in particular MI and stroke, CKD, and CRC. It was chosen to evaluate the differential impact between complications development in the population with MASLD and in a same sample size population without-MASLD. Differential risk data, mortality rates and event unit costs were drawn from published international literature. Frequency and cost data were applied to the total target population, the total annual costs and mortality data, referring to the two arms, were then calculated and the differential value was obtained. Results: Overall, based on an estimated 11,546,370 MASLD target population, an annual illness impact of €12,251,631,822 was calculated, corresponding to a difference of €7,731,674,054 compared to the same sample size without MASLD. Moreover, MASLD population is expected to result in 13,126 annual additional deaths. Conclusion: The growing epidemiological impact of MASLD and its complications, will represent a huge economic burden for healthcare services worldwide. An holistic approach, mainly behaviors lifestyle change, to control the dramatic health and economic impact will be the first step to take. Specific drugs for MASLD are not yet available, but studies are underway, and combination pharmaceutical therapies may be an inevitable choice to achieve adequate control of MASLD and its complications in the future. metabolic associated fatty liver disease (MASLD) complications MASLD burden in Italy healthcare costs treatment and perspectives Figures Figure 1 Figure 2 Figure 3 Introduction If obesity and diabetes mellitus represent the pandemic giant worldwide for the next decades, definitely MASLD provides their ominous shadow. The term MASLD (Metabolic Dysfunction-Associated Steatotic Liver) was proposed in 2023 to better define the disease characterized by hepatic steatosis (verified through imaging techniques or liver biopsy) and at least one of the following conditions: obesity, metabolic dysregulation, type 2 diabetes mellitus (T2DM). ( 1 ) Metabolic dysregulation means the presence of at least two between the following conditions: waist circumference above 102/88 cm for Caucasian males/females, blood pressure above 130/85 or antihypertensive medication, plasma triglycerides above 150 mg/dl or related medication, HDL cholesterol under 40 mg/dl for men and 50 mg/dl for women, prediabetic condition (fasting plasma glucose between 100–125 mg/dl or 2 h post load between 140–199 mg/dl or glycosylated haemoglobin between 5.7–6.4%), homeostasis model assessment (HOMA) score > 2.5, high-sensitivity C-reactive protein levels above 2 mg/L.( 2 ) The old term NAFLD (Non-Alcoholic Fatty Liver Disease) remains confined to forms of steatosis (more than 5% of hepatocytes) not related to alcohol (less than 20/10 grams per day for males/females), viruses, genetic diseases, or toxic medications. ( 2 , 3 ) Therefore MASLD does not just represent the new term for NAFLD, but, together with its more aggressive form named MASH (Metabolic dysfunction-Associated Steato-Hepatitis, definition that, in turn, replaces NASH), involves the manifold ensemble of metabolic disorders and is steadily increasing worldwide and will be the main cause of chronic liver diseases in the coming decades: in USA only, the prevalence of MASLD increased from 28.4% in 1999–2002 to 35.8% in 2011–2016. ( 4 , 5 ) Moreover, compared to the diagnosis by exclusion in NAFLD, MASLD is a diagnosis of inclusion, studies have shown that a portion of the NAFLD population is excluded under the proposed MASLD definition. ( 6 ) A team of the University of Singapore elaborated a meta-analysis and systematic review in over 10 millions of individuals, documenting for the first time that global prevalence and clinical features of MASLD are very impressive: in pooled analysis of over 3,3 millions individuals, the overall prevalence of MASLD was found to be 38.77%, with significant differences in geographical regions: highest in Europe (55.33%), followed by Asia (36.31%) and the lowest in North America (35.99%, 95% CI 30.68–41.66%). ( 7 ) In the same work, in a pooled analysis of 4,09 millions patients with MASLD, the mean age of MASLD patients was 51.99 years, with an average BMI and waist circumference of 27.71 kg/m2 and 92.91 cm, respectively; 41.38% suffered from hypertriglyceridemia, 43.72% were hypertensive, and 22.79% (95% CI 19.42–26.55%) were diabetic. In the analysis of MASLD demographics, 27.51% were smokers, and 19.28% had excessive alcohol consumption. A pooled mean of liver function test shows the average AST, ALT, and GGT levels to be 35.08 U/L, 43.71 U/L, and 60.47 U/L, respectively. In Italy, the Diabetes Barometer Report 2023 documented a self-reported prevalence of diabetes of 3.9 millions (6.6% in general population), with an evident age-correlated gradient, achieving the prevalence of 18,7% in over 65 years subjects. ( 8 ) The prevalence of MASLD among diabetic patients in Italy amounts to 67.97%. ( 9 ) Therefore, the estimated prevalence of MASLD in Italy, calculated considering the presence of the disease in T2DM population (2,651 millions of T2DM patients present MASLD) and applying the above reported prevalence of 22.79% of T2DM among MASLD population, ( 7 ) amounts to approximately 11,6 millions out of a population of 58,85 millions in January 2023 (19,62%), (as shown in Methods).( 10 ) Thus, MASLD is a multisystem disease presenting an increased risk of developing not only diabetes itself, but also cardiovascular diseases (CVD), renal impairment (CKD), extrahepatic cancers (mainly colon-rectal), not forgetting the obvious liver-related complications heading towards MASH, cirrhosis (compensated, CC, and decompensated, DCC), and hepatocellular carcinoma (HCC). Not being available data about the incidence of diabetes in MASLD population, the risk of developing T2DM among subjects with MASLD can be estimated starting from the annual incidence of T2DM among Italian population: 350,000 new diagnosis per year.( 11 ) Knowing that the prevalence of MASLD among diabetic patients is 68%, as reported above, we can deduce that about 238,000 new T2DM are diagnosed per year among non-diabetic MASLD subjects, thus determining an annual incidence of 2.66%. If we consider also the T2DM related events, among MASLD complications the most common, as well as the major cause of death, is CVD, representing advanced liver disease the second item in order of relevance. A 2013 metanalysis reported several studies demonstrating an increased risk of CVD among patients with NAFLD, ( 12 ) but we had to wait for a paper published in 2021 to have an idea about the prevalence of myocardial infarction (MI) and stroke in USA adults, expressed as percentage of 10-year risk, for MASLD compared to non-MASLD subjects. ( 5 ) In the above cited work, which analyzed data from 19617 adults aged ≥ 20 years from the cross-sectional US National Health and Nutrition Examinations Survey periods ranging from 1999 to 2016, the estimated 10-year risk of MI and stroke ranged from 10.8 to 13.2% in MASLD subjects and from 6.6 to 7.1% in non-MASLD population; therefore, the highest prevalence presented by MASLD subjects ranges from 5.2 to 6.1% over a 10 years period. Applying these data to Italian population we therefore deduce that in the MASLD individuals, apart T2DM-related complications (included in the computation of its global costs), we can estimate a population presenting IMA or stroke over a 10-year period ranged between 465,000 to 545,000. Chronic kidney disease (CKD) is another very important and recognized complication of MASLD.( 13 ) In the main institutional document of Italian Ministry of Health about the management of CKD, defined as evaluated glomerular filtration rate (eGFR) < 60 mL/min/mq 1,73 and/or urinary albumin-to-creatinine ratio (ACR) ≥ 3 mg/mmol, the prevalence, based principally on the STUDIO CHARES, is 7,1% (7,5% in men and 6,5% in women), including 2,6% in Stage 3 (eGFR 30–59 mL/min/mq 1,73) and 0,3% in stage 4–5 (eGFR < 30 mL/min/mq 1,73).( 14 ) Considering these epidemiologic data, we can calculate renal impairment in general population amounting to about 4,18 million subjects, including 177,000 affected by stage 4–5 CKD. Another review reported that NAFLD patients presented a higher risk of incident CKD compared with those without NAFLD over a median follow-up of nearly 5 years (HR 1.37, 95% CI 1.20–1.50) ( 15 ), so, considering that MASLD individuals present a lower glomerular filtration rate and a greater prevalence of CKD than NAFLD individuals (29,6% vs 25.56%, P < 0,05), ( 16 ) even applying the previous and more conservative rate of 1.37 to Italian MASLD population, we can estimate at least 1,13 million subjects with CKD of which 47,600 presenting stage 4–5 CKD. Therefore, excluding MASLD patients with T2DM, which represent two-thirds of all diabetic patients, and considering that T2DM determines about 20% of all cases of CKD, ( 17 ) we can deduce about 590,000 not-T2DM MASLD subjects presenting CDK, and 24,600 with stage 4–5 CKD. Another important epidemiological association presented by MASLD subjects regards the increase in colorectal cancer (CRC) risk. A study starting from a nationwide health screening database including more than 8.9 million participants demonstrated that MASLD, more than NAFLD, was associated with a higher CRC risk, that, after multivariable adjustment for age, sex, household income quartile, residential area, CCI index (Charlson Comorbidity Index, which predicts 10-year survival in patients with multiple comorbidities), aspirin use, nonsteroidal anti-inflammatory drug use, tobacco smoke, exercise frequency, alcohol intake and concomitant liver diseases, was expressed as an HR of 1.16 (95% CI, 1.13–1.18).( 18 ) The study also detected that patients with fatty liver disease and advanced liver fibrosis were at higher CRC risk than those with simple steatosis, suggesting that an adequate intervention on the disease could reduce the overall risk. Considering that the incidence rate detected for individuals without MASLD was 57,5 per 100.000 person-years, the extra incidence attributable to MASLD can be quantified in 9,2 per 100.000 person-years. Applying this to the above defined Italian MASLD population (11,6 million) we can consider an extra incidence of CRC in MASLD subject of about 1067 patients per year. Last but not least, MASLD presents a higher risk of hepatic events, which incidence is related to the stage of fibrosis detected (F0-F2 versus F3 versus F4) as follows: variceal hemorrhage (0.00 versus 0.06 versus 0.70), ascites (0.04 versus 0.52 versus 1.20), encephalopathy (0.02 versus 0.75 versus 2.39), and hepatocellular carcinoma (HCC) (0.04 versus 0.34 versus 0.14) per 100 persons-year.( 19 ) Considering that the annual incidence of HCC in NAFLD (and moreover MASLD) patients is 0.44 per 1000 person-years (95% CI: 0.29–0.66) whereas for MASH is 5.29 per 1000 person-year and reminding also that approximately 41% (95% CI: 34.69–47.13) of MASH patients present a worsening of fibrosis with an annual progression rate of 0.09% (95% CI: 0.06–0.12), the development of HCC an mortality has been stratified by NAFLD/MASLD or MASH status, as shown in Material and Methods.( 20 ) Considering the constant growth of MASLD in terms of percentage of population concerned ( 21 ), aim of our study is to evaluate the economic impact of MASLD among Italian population from the Italian National Healthcare Service (NHS) perspective. Methods Study design MASLD economic impact was assessed developing a calculation model in Microsoft Excel®. The analysis was conducted from the Italian NHS perspective, considering healthcare resources and direct costs related to the clinical conditions management in the Italian setting. Target population has been defined based on prevalence data, to provide a snapshot of the current situation. Prior to the analysis, a literature search was conducted aimed at examining the MASLD clinical background and gathering evidence regarding the complications and possible specific clinical conditions evolution. Following the review, the main MASLD-related complications were identified, corresponding to: MASH, with relative risk of evolution into CC, DCC, HCC, T2 diabetes mellitus, cardiovascular diseases, in particular MI and stroke, CKD, and CRC. Since these complications, in turn, represent significant chronic, metabolic and worsening diseases, it was chosen to evaluate the differential impact between their development in the population with MASLD and in a same sample size population without-MASLD, to highlight the negative impact, still largely overlooked today, represented by the presence of MASLD. T2DM cardiovascular related events were included among the costs of the disease. Differential risk data, referring to these conditions development between the population affected by MASLD and non-MASLD population, were drawn from published international literature. Mortality rates associated with complications were also researched, with the aim of estimating the differential impact on patients destined to die between the two groups. Once the estimated event rates for the compared groups were obtained, the annual unit cost of each event was applied to these values. Also, annual unit costs per event were taken from the literature, adopting specific data for the Italian healthcare context. Frequency and cost data were applied to the total target population, the total annual costs and mortality data referring to the two arms were then calculated and the differential value was obtained. Target population MASLD target population was estimated by applying prevalence data and clinical characteristics obtained from international literature ( 7 , 9 ) to the Italian epidemiological context.( 8 , 10 ) Since no Italian studies on specific MASLD population are available, target population was obtained by extrapolation, starting from international data on the share of patients affected by MASLD among diabetics (67.75%) and the estimate of diabetic patients among the total patients with MASLD (22.79%). ( 7 , 9 ) Based on a total Italian population of 58,850,000 and a 6.6% diabetes prevalence, ( 8 , 10 ) a target population of 11,546,370 subjects in Italy was estimated, corresponding to approximately 19.6% of the total population, Table 1 . Our estimate of prevalence must be considered as a conservative one, presenting international literature higher estimates of prevalence worldwide. Table 1 Target population Population %/n Total Italian population 58,850,000 Diabetes % 6.60% Diabetes n. 3,884,100 Diabetes-MASLD % 67.75% Diabetes-MASLD n. 2,631,418 MASLD-Diabetes% 22.79% MASLD population 11,546,370 Event rate and unit costs Differential rates of complications occurrence in the MASLD target population and in a same sample size not affected by MASLD were obtained from a literature search regarding the main complications from MASLD (MASH and advanced stages of liver damage (CC, DCC, HCC), diabetes, cardiovascular diseases, including mainly myocardial infarction and stroke, CKD, and colorectal cancer). ( 7 , 11 , 5 , 12 , 13 , 15 , 18 , 19 , 20 , 22 , 23 ) For each complication, the unit cost was sought by referring to the relevant Italian literature ( 24 , 25 , 26 , 27 , 28 ), for steatosis evaluation, outpatient services tariff was adopted. ( 29 ) Table 2 shows the event occurrence rates and the related cost per event. Table 2 Event rate and unit cost MASLD % NO MASLD % Unit Costs Steatosis 76.00% 0.00% € 60 MASH MASH 22.43% 0.00% € 246 CC 1.02% 0.00% € 347 DCC 0.51% 0.00% € 5,465 HCC 0.04% 0.00% € 6,075 T2 diabetes mellitus 22.79% 6.60% € 2,589 MI and stroke 1.20% 0.69% € 13,206 Chronic kidney disease (CKD) 9.73% 7.10% Stage 1–2 5.75% 4.20% € 1,404 Stage 3 3.56% 2.60% € 2,122 Stage 4–5 0.41% 0.30% € 4,509 Colorectal cancer (CRC) 0.07% 0.06% € 4,300 Mortality To estimate the complications impact also on life expectancy, the mortality rate related to each complication was searched in the literature. ( 23 , 30 , 31 , 32 ) This further analysis was conducted to evaluate the differential impact between populations on deaths associated with the clinical condition of MASLD and related complications compared to the population without MASLD. Table 3 shows the mortality rates adopted. Table 3 Mortality rates Mortality% Steatosis 0,0% MASH MASH 0,0% CC 1,2% DCC 13,7% HCC 28,3% T2 diabetes mellitus 0,0% MI and stroke 2,3% Chronic kidney disease (CKD) Stage 1–2 0,0% Stage 3 0,0% Stage 4–5 0,0% Colorectal cancer (CRC) 45,1% Sensitivity analysis To assess the robustness of the results related to the main input adopted and assumptions considered, a one-way sensitivity analysis has been carried out, varying by ± 5% epidemiological data and by ± 10% event rates and costs input data. The simulation scenarios were developed compared to the base case, adopting as reference parameter the difference in total expenditure reported in the MASLD population and in the same sample without MASLD. Results The results have highlighted the differential impact, between the population with MASLD and without MASLD, on events occurrence, corresponding to the complications and disease evolutions to advanced stages, allowing the relative economic impact to be assessed as well, Table 4 . Comparing the two arms, based on disease prevalence data application, it is possible to grasp the significant impact related to the presence, in particular, of steatosis conditions and liver disease advanced stages, as a basic distinctive element between the two groups, resulting in an increase in costs of €528,826,092 for steatosis and €1,027,880,550 overall for liver disease advanced stages (MASH, CC, DCC, HCC). The impact of diabetes was particularly significant, resulting in an increase in expenditure of € 4.839.766.057, corresponding to the largest cost item, given the high prevalence within the population with MASLD, considering also the elevate rate of cardiovascular events. Moreover, to these major items, we have added the costs related to cardiovascular diseases (MI, stoke), CKD and colorectal cancer with an expense of € 785,274,445, € 545,359,165, and € 4,567,744, respectively. Overall, in consideration of a MASLD population estimate equal to €11,546,370, an annual illness impact of €12,251,631,822 was calculated, corresponding to a difference of €7,731,674,054 compared to the same sample size without MASLD. Table 4 Total events and related cost compared: MASLD versus without MASLD population MASLD (N) NO MASLD (N) DELTA (N) MASLD (€) NO MASLD (€) DELTA (€) Steatosis 8.775.740 0 8.775.740 € 528.826.092 € 0 € 528.826.092 MASH € 1.027.880.550 € 0 € 1.027.880.550 MASH 2.589.400 0 2.589.400 € 636.992.400 € 0 € 636.992.400 CC 117.700 0 117.700 € 40.841.900 € 0 € 40.841.900 DCC 58.850 0 58.850 € 321.615.250 € 0 € 321.615.250 HCC 4.680 0 4.680 € 28.431.000 € 0 € 28.431.000 T2 Diabetes 2.631.418 762.060 1.869.357 € 6.812.740.485 € 1.972.974.427 € 4.839.766.057 MI and stroke 138.556 79.093 59.464 € 1.829.765.697 € 1.044.491.252 € 785.274.445 Chronic kidney disease (CKD) 1.123.115 819.792 303.323 € 2.019.302.854 € 1.473.943.689 € 545.359.165 Stage 1–2 664.378 484.948 179.431 € 932.585.208 € 680.719.130 € 251.866.078 Stage 3 411.282 300.206 111.076 € 872.739.766 € 637.036.326 € 235.703.440 Stage 4–5 47.456 34.639 12.816 € 213.977.879 € 156.188.233 € 57.789.646 Colorectal cancer (CRC) 7.701 6.639 1.062 € 33.116.144 € 28.548.400 € 4.567.744 TOTAL € 12.251.631.822 € 4.519.957.768 € 7.731.674.054 The different impact in terms of costs of diabetes, MASH, MI and stroke, CKD, steatosis, and colorectal cancer in MASLD and non-MASLD is reported in Fig. 1 . The analysis also allowed to estimate the number of deaths attributable to the two populations and the relative difference, Table 5 . The presence of MASLD has shown a greater number of deaths, in particular, due to advanced liver diseases, colorectal cancer and cardiovascular disease, Table 5 . Overall, the MASLD population is expected to result in 13,126 annual additional deaths, Fig. 2 . Table 5 Impact of disease on mortality: MASLD versus without MASLD population Death number disease-related MASLD N NO MASLD N DELTA N DCC + CC 9.391 0 9.391 HCC 1.325 0 1.325 CRC 3.474 2.995 479 MI and stroke 3.210 1.833 1.378 T2DM 747 216 531 CKD 80 59 22 TOTAL 18.229 5.103 13.126 The sensitivity analysis has shown the robustness of the results. Actually, the main input data and assumptions variation has not resulted in significant deviations from base case findings, as shown in Fig. 3 . Compared to an increase in cost for MASLD versus non-MASLD population reported for the base case equal to €7.7 million, the sensitivity analysis documented a maximum value corresponding to a 10% event rates increase, with a result equal to € 8.8 million and a minimum value corresponding to a 10% event rates reduction equal to 6.7 million. Discussion In a previous paper we evaluated the epidemiologic and economic burden of NAFLD/MASH among T2DM population, ( 33 ) while in this study we have further expanded the magnifying glass on the huge social issue of MASLD in Italian general population, a condition involving a multi-organ impairment and strictly associated to individual behaviors. Starting from this point of view, T2DM represents the main complication as well as the main cost item of MASLD, with about two thirds of all cases of diabetes generated by it. In Italy, the estimated population suffering from MASLD, amounts to 11,546,370 individuals, corresponding to 19.6% of the general population. The annual burden of MASLD disease in terms of mortality and healthcare expenses, as resulting from the Italian NHS perspective adoption, is very impressive: total direct healthcare costs amount to € 7.731.674.054, which correspond to 5.68% of national healthcare expenditure expected for 2023; in addition, MASLD accounts for 13,126 deaths per year. Among the estimated population suffering from MASLD, amounting to 11,546,370, we count 22.79% of subjects presenting T2DM and, considering the annual incidence of T2DM − 350,000 new diagnosis per year- and the prevalence of MASLD among T2DM, we can deduce that 238,000 patients shift from MASLD to T2DM every year. ( 10 ) T2DM represents the first and preponderant cost item among MASLD (4,839,766,057 €/yr), producing 62.6% of the total expenditure of this metabolic disease, so interventions aiming to reduce the economic burden of MASLD must be targeted mainly to the prevention of its development towards diabetes. Considering the overall MASLD individuals, 72,37% are affected by hepatic steatosis, 22,43% present MASH, and a minimal share of subjects suffer from HCC (0.80%), severe chronic kidney disease (Stage IV-V: 0,41%) and colorectal cancer (0,07%). Liver impairment represents a lower burden in terms of costs (€ 1.573.239.715, 20,4% of total costs, adding steatosis and MASH), but the highest in terms of lethality, accounting for 9.391 deaths per year, equal to 71,5% of the annual MASLD related mortality. Cardiovascular complications (MI and stroke), accounting for € 785.274.445 and 1378 deaths per year, rank third considering the combinations of cost and lethality, but they would probably come first if we also considered the CV events already included among the complications of T2DM-MASLD subjects. And also, CV related lethality could increase if we consider also T2DM related CV deaths, which are often not attributed to diabetes in Italian death statistical reports. ( 8 ) Chronic kidney disease remains above half a billion in annual costs (€ 545.359.165) and MASLD-related colorectal cancer is responsible of 479 deaths per year (3.6% of total MASLD-related deaths). Therefore, cost analysis of MASLD complications showed a frank predominant burden of chronic metabolic and hepatic illnesses: in fact T2DM and Steatosis-MASH produce 62,5% and 20,4% of overall health spending, respectively, whereas acute cardiovascular complications (MI and stroke) and renal impairment are separately responsible of 10,16% and 7,05% of cost weight; last but not least, minor cost is associated to colorectal cancer (0,06%), due to lower incidence and higher mortality. Beyond the evaluation of the global economic burden of the disease, it is interesting to highlight that the differential pro-capita cost related to MASLD subjects amounts to € 670 per year. This figure could therefore be taken as reference for assessing the cost-effectiveness of treatments aimed at stopping the evolution of MASLD disease. Sensitivity analysis showed that hypothetical variation of ± 5% regarding population data input and ± 10% regarding costs and MASLD related events could result in a range of global direct cost varying from € 6.7 billion to € 8.8 billion, corresponding respectively to 4.85% and 6.47% of annual global sanitary expenditure. It remains to evaluate the entity of the time lag necessary to develop an effective reduction of the incidence of MASLD related complications after starting an effective therapeutic measure. During this period, the costs of the treatment will be superimposed to the costs of the disease, but we have considered that our study did not include neither the estimate of indirect costs, nor its impact in terms of impairment of national GDP. Limitations of our study lie in the lack of a direct estimate of the real prevalence of MASLD among Italian population, and for this reason we preferred to underestimate the possible prevalence, and in the necessity of maximizing the simplicity of our model. Finally, our study has adopted international data when national ones were not available. Points of strength of our work correspond to the first study to have evaluated the economic burden of MASLD among Italian population as well as to have analyzed in an innovative way MASLD related diseases, so that T2DM can be, at least partially, seen as a complication of the hepatic disease. Conclusion Data emerging from our study are impressive, both in terms of the number of subjects involved, amounting to about one fifth of Italian population, and of the economic burden (€ 7,73 billion per year). A recent study evaluating the economic burden of obesity in Italy documented a similar direct cost profile (€ 7.89 billion), with the higher impact of cardiovascular diseases (€ 6.66 billion).( 34 ) Even if the two populations are largely overlapping, we believe that the basic behavioral and pharmacological treatment could be the same, reserving more targeted interventions, regarding MASLD subject, for prevention of new cases of T2DM and for prevention and early treatment of MASH. Therefore, the growing epidemiological impact of MASLD, obesity and its complications, associated with the related cardiovascular diseases, will represent a huge economic burden for healthcare services worldwide for the next decades, and a holistic approach to the person (mainly behaviors lifestyle changes) to control the dramatic health and economic impact will be the first step to take. Specific drugs for MASLD are not yet available, but studies are underway on many molecules, and combination pharmaceutical therapies may be an inevitable choice to achieve adequate control of MASLD and its complications in the future. Declarations Ethics approval and consent to participate For the development of this study it was not necessary to proceed with the request for ethics approval and consent to participate; previously published and validated literature sources were adopted. Consent for publication Not applicable Availability of data and materials The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors Competing interests This study was funded by unconditional and exclusive grant from NovoNordisk, Italy. The authors report no other conflicts of interest in this work. Funding This study was funded by unconditional and exclusive grant from NovoNordisk, Italy Authors' contributions E.T. and S.D. defined the rationale for the study and the original model framework. G.L.C. and C.M. reviewed and validated the model adaptation and wrote the manuscript. U.G., A.R., L.C.B. and G.T. interpreted data and supported clinical data research. G.M.B. and C.L.C. supervised the project and decided on manuscript content and structure. All authors contributed toward data analysis, drafting and revising the paper and agree to be accountable for all aspects of the work. Acknowledgments Not applicable References De A, Bhagat N, Mehta M, Taneja S, Duseja A. Metabolic dysfunction-associated steatotic liver disease (MASLD) definition is better than MAFLD criteria for lean patients with NAFLD. J Hepatol 2023 Aug 7:S0168-8278(23)05044-4. Boccatonda A, Andreetto L, D’Ardes D, Cocco G, et al. From NAFLD to MAFLD: Definition, Pathophysiologcal Basis and Cardiovascular Implications. Biomedicines. 2023;11:883. Chalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018;67:328–57. Eslam M, Sanyal AJ, George J. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology. 2020;158(7):1999–2014. e1991. Zhang HJ, Wang YY, Chen C, Lu YL, Wang NJ. Cardiovascular and renal burdens of metabolic associated fatty liver disease from serial US national surveys, 1999–2016. Chin Med J. 2021;134(13):1593–601. Lim GEH, Tang A, Ng CH et al. March. An Observational Data Meta-analysis on the Differences in Prevalence and Risk Factors Between MAFLD vs NAFLD. Volume 21, Issue 3, 2023, Pages 619–629.e7. Chan KE et al. Tiffany Jia Ling Koh, Ansel Shao Pin Tang Global Prevalence and Clinical Characteristics of Metabolic-associated Fatty Liver Disease: A Meta-Analysis and Systematic Review of 10 739 607 Individuals. The Journal of Clinical Endocrinology & Metabolism, 2022, 107, 2691–2700. 16th Italian Barometer Diabetes Report, Diabetes Monitor Journal., 2023, IBDO Foundation, 67–72. Younossi ZM, Golabi P, De Avila L, et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis. J Hepatol. 2019;71:793–801. http://dx.doi.org/10.1016/j.jhep.2019.06.021 . ISTAT. Popolazione residente 1° gennaio 2023. Available at: https://demo.istat.it/app/?i=POS&l=it Bonora E. La pandemia di diabete in Italia. L’Endocrinologo. 2022;23:337–44. Anstee QM, Targher G, Day CP. Progression of NAFLD to diabetes mellitus, cardiovascular disease or cirrhosis. Nat Rev Gastroenterol Hepatol. 2013;10:330–44. 10.1038/nrgastro.2013.41 . Mantovani A, Lombardi R, Cattazzo F, et al. MAFLD and CKD: An Updated Narrative Review. Int J Mol Sci. 2022;23:7007. De Nicola L, Donfrancesco C, Minutolo R, et al. Epidemiologia della MRC in Italia: stato dell’arte e contributo dello studio CHARES. G Ital Nefrol. 2011;28(4):401–7. Mantovani A, Zaza G, Byrne CD, et al. Nonalcoholic fatty liver disease increases risk of incident chronic kidney disease: A systematic review and meta-analysis. Metabolism. 2018;79:64–76. Sun DQ, Jin Y, Wang T, et al. MAFLD and risk of CKD. Metabolism. 2021;115:154433. SNLG-Regioni. La nefropatia diabetica: linee guida diagnostiche e terapeutiche Zadig- Milano., 2016, 23. Lee H, Lee HW, Kim SU, Kim HC. Metabolic Dysfunction-associated Fatty Liver Disease Increases Colon hiips:77 doi.org/10.14309/ctg.0000000000000435 . Pipitone RM, Ciccioli C, Infantino G, et al. MAFLD: a multisystem disease. Ther Adv Endocrinol Metab. 2023;14:1–23. 10.1177/20420188221145549 . Younossi ZM, Koenig AB, Abdelatif D, et al. Global epidemiology of nonalcoholic fatty liver disease—meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64:73–84. Ferrarese A, Battistella S, Germani G. Nash Up, Virus Down: How the waiting list Is Changing for Liver Tranplantation: a Single Center Experience from Italy. Medicina. 2022;58:290: 1–8. Estes C, Anstee QM, Arias-Loste MT, et al. Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016–2030. J Hepatol. 2018;69(4):896–904. AIOM. I numeri del cancro in Italia 2022. Intermedia Editore. Available at: https://www.aiom.it/wp-content/uploads/2022/12/2022_AIOM_NDC-web.pdf . AISF, Libro bianco AISF. 2011. Proposta per un piano nazionale per il controllo delle malattie epatiche. Available at: https://www.webaisf.org/wp-content/uploads/2019/01/libro-bianco-aisf-2011.pdf . Lucioni C, Mazzi S, Rossi S, et al. Percorsi terapeutici e costi sanitari di pazienti ricoverati per un evento cardiovascolare in Italia. Global & Regional Health Technology Assessment. 2016;3(2):80–91. Pagano E, De Rosa M, Rossi E, Cinconze E, Marchesini G, Miccoli R, Vaccaro O, Bonora E, Bruno G. The relative burden of diabetes complications on healthcare costs: The population-based CINECA-SID ARNO Diabetes Observatory. Nutr Metab Cardiovasc Dis. 2016;26(10):944–50. Jommi C, Armeni P, Battista M, IRIDE Study Group, et al. The Cost of Patients with Chronic Kidney Failure Before Dialysis: Results from the IRIDE Observational Study. Pharmacoecon Open. 2018;2(4):459–67. Francisci S, Guzzinati S, Mezzetti M, et al. Cost profiles of colorectal cancer patients in Italy based on individual patterns of care. BMC Cancer. 2013;13:329. Tariffe delle prestazioni di assistenza specialistica ambulatoriale. 2013 Allegato 3 Ministero della Salute - Direzione generale della programmazione sanitaria. Supplemento ordinario n. 8 alla Gazzetta Ufficiale. Serie generale - n. 23. ISTAT. Il diabete in Italia. https://www.istat.it/it/files/2017/07/REPORT_DIABETE.pdf . Saglietto A, Manfredi R, Elia E, D'Ascenzo F, DE Ferrari GM, Biondi-Zoccai G, Munzel T. Cardiovascular disease burden: Italian and global perspectives. Minerva Cardiol Angiol. 2021;69(3):231–240. 10.23736/S2724-5683.21.05538-9 . Epub 2021 Mar 11. PMID: 33703858. Mortalità per insufficienza renale cronica. Available at: https://www.ars.toscana.it/banche-dati/dettaglio_indicatore-1329-mortalita-insufficienza-renale-cronica?provenienza=dettaglio_indicatore_consigliati &par_top_geografia=090&dettaglio=ric_anno_geo_ausl. Torre E, Di Matteo S, Bruno GM, et al. Economic Burden of Non-Alcoholic Steatohepatitis (NASH) Among Diabetic Population in Italy: Analysis and Perspectives. Clinicoecon Outcomes Res. 2022;14:607–18. D’Errico M, Pavlova M, Spandonaro F. The economic burden of obesity in Italy: a cost-of-illness study. Eur J Health Econ. 2022;23:177–92. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3755157","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":264081338,"identity":"b86dae38-c59e-414e-b8f8-2fa4d42b5024","order_by":0,"name":"Enrico Torre","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Enrico","middleName":"","lastName":"Torre","suffix":""},{"id":264081342,"identity":"cf2bca26-6372-4f13-97fa-1654c776dbd4","order_by":1,"name":"Sergio Di 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Goglia","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Umberto","middleName":"","lastName":"Goglia","suffix":""},{"id":264081345,"identity":"ff9ae05b-88f5-423c-87ce-15bc0e843414","order_by":4,"name":"Giacomo Matteo Bruno","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Giacomo","middleName":"Matteo","lastName":"Bruno","suffix":""},{"id":264081346,"identity":"2adbc38c-e621-4cb2-a792-ff00ae9004d1","order_by":5,"name":"Gianni Testino","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Gianni","middleName":"","lastName":"Testino","suffix":""},{"id":264081347,"identity":"f241f846-273c-43a6-a36d-b214b27ae1bd","order_by":6,"name":"Alberto Rebora","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Alberto","middleName":"","lastName":"Rebora","suffix":""},{"id":264081348,"identity":"2c1ecb81-dee6-4603-859a-b8c56d1f7998","order_by":7,"name":"Luigi Carlo Bottaro","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Luigi","middleName":"Carlo","lastName":"Bottaro","suffix":""},{"id":264081349,"identity":"ded8bc66-98c9-485f-b098-6856d333c3da","order_by":8,"name":"Giorgio Lorenzo Colombo","email":"","orcid":"","institution":"University of Pavia","correspondingAuthor":false,"prefix":"","firstName":"Giorgio","middleName":"Lorenzo","lastName":"Colombo","suffix":""}],"badges":[],"createdAt":"2023-12-14 19:29:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3755157/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3755157/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49070103,"identity":"7f3b44c3-da39-4e73-8687-bb762e2649e6","added_by":"auto","created_at":"2024-01-02 16:41:25","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":46069,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall difference in total costs: MASLD \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eversus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e without MASLD population\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3755157/v1/e7aa95e296b72f25b6d13aa5.jpg"},{"id":49069869,"identity":"3ec049af-fc94-4e61-8637-46722ab6b0c2","added_by":"auto","created_at":"2024-01-02 16:33:25","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35576,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTotal deaths: MASLD versus without MASLD population\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3755157/v1/fec7a2636ab1b27386b75992.jpg"},{"id":49069871,"identity":"565d64c9-e77f-4069-9e57-f0c4330b2db8","added_by":"auto","created_at":"2024-01-02 16:33:25","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38455,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSensibility analysis results\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3755157/v1/adcbb50dc5d060d258ee9e10.jpg"},{"id":49304213,"identity":"11556e85-284f-44ef-8307-fb7048b51f72","added_by":"auto","created_at":"2024-01-08 10:52:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":579955,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3755157/v1/bb55d3f3-f20e-4a23-b351-43d649f549c0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Economic impact of metabolic dysfunction-associated steatotic liver (MASLD) in Italy. Analysis and perspectives","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIf obesity and diabetes mellitus represent the pandemic giant worldwide for the next decades, definitely MASLD provides their ominous shadow. The term MASLD (Metabolic Dysfunction-Associated Steatotic Liver) was proposed in 2023 to better define the disease characterized by hepatic steatosis (verified through imaging techniques or liver biopsy) and at least one of the following conditions: obesity, metabolic dysregulation, type 2 diabetes mellitus (T2DM). (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Metabolic dysregulation means the presence of at least two between the following conditions: waist circumference above 102/88 cm for Caucasian males/females, blood pressure above 130/85 or antihypertensive medication, plasma triglycerides above 150 mg/dl or related medication, HDL cholesterol under 40 mg/dl for men and 50 mg/dl for women, prediabetic condition (fasting plasma glucose between 100\u0026ndash;125 mg/dl or 2 h post load between 140\u0026ndash;199 mg/dl or glycosylated haemoglobin between 5.7\u0026ndash;6.4%), homeostasis model assessment (HOMA) score\u0026thinsp;\u0026gt;\u0026thinsp;2.5, high-sensitivity C-reactive protein levels above 2 mg/L.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The old term NAFLD (Non-Alcoholic Fatty Liver Disease) remains confined to forms of steatosis (more than 5% of hepatocytes) not related to alcohol (less than 20/10 grams per day for males/females), viruses, genetic diseases, or toxic medications. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Therefore MASLD does not just represent the new term for NAFLD, but, together with its more aggressive form named MASH (Metabolic dysfunction-Associated Steato-Hepatitis, definition that, in turn, replaces NASH), involves the manifold ensemble of metabolic disorders and is steadily increasing worldwide and will be the main cause of chronic liver diseases in the coming decades: in USA only, the prevalence of MASLD increased from 28.4% in 1999\u0026ndash;2002 to 35.8% in 2011\u0026ndash;2016. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Moreover, compared to the diagnosis by exclusion in NAFLD, MASLD is a diagnosis of inclusion, studies have shown that a portion of the NAFLD population is excluded under the proposed MASLD definition. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eA team of the University of Singapore elaborated a meta-analysis and systematic review in over 10 millions of individuals, documenting for the first time that global prevalence and clinical features of MASLD are very impressive: in pooled analysis of over 3,3 millions individuals, the overall prevalence of MASLD was found to be 38.77%, with significant differences in geographical regions: highest in Europe (55.33%), followed by Asia (36.31%) and the lowest in North America (35.99%, 95% CI 30.68\u0026ndash;41.66%). (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) In the same work, in a pooled analysis of 4,09 millions patients with MASLD, the mean age of MASLD patients was 51.99 years, with an average BMI and waist circumference of 27.71 kg/m2 and 92.91 cm, respectively; 41.38% suffered from hypertriglyceridemia, 43.72% were hypertensive, and 22.79% (95% CI 19.42\u0026ndash;26.55%) were diabetic. In the analysis of MASLD demographics, 27.51% were smokers, and 19.28% had excessive alcohol consumption. A pooled mean of liver function test shows the average AST, ALT, and GGT levels to be 35.08 U/L, 43.71 U/L, and 60.47 U/L, respectively.\u003c/p\u003e \u003cp\u003eIn Italy, the Diabetes Barometer Report 2023 documented a self-reported prevalence of diabetes of 3.9 millions (6.6% in general population), with an evident age-correlated gradient, achieving the prevalence of 18,7% in over 65 years subjects. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) The prevalence of MASLD among diabetic patients in Italy amounts to 67.97%. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) Therefore, the estimated prevalence of MASLD in Italy, calculated considering the presence of the disease in T2DM population (2,651 millions of T2DM patients present MASLD) and applying the above reported prevalence of 22.79% of T2DM among MASLD population, (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) amounts to approximately 11,6 millions out of a population of 58,85 millions in January 2023 (19,62%), (as shown in Methods).(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThus, MASLD is a multisystem disease presenting an increased risk of developing not only diabetes itself, but also cardiovascular diseases (CVD), renal impairment (CKD), extrahepatic cancers (mainly colon-rectal), not forgetting the obvious liver-related complications heading towards MASH, cirrhosis (compensated, CC, and decompensated, DCC), and hepatocellular carcinoma (HCC).\u003c/p\u003e \u003cp\u003eNot being available data about the incidence of diabetes in MASLD population, the risk of developing T2DM among subjects with MASLD can be estimated starting from the annual incidence of T2DM among Italian population: 350,000 new diagnosis per year.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Knowing that the prevalence of MASLD among diabetic patients is 68%, as reported above, we can deduce that about 238,000 new T2DM are diagnosed per year among non-diabetic MASLD subjects, thus determining an annual incidence of 2.66%.\u003c/p\u003e \u003cp\u003eIf we consider also the T2DM related events, among MASLD complications the most common, as well as the major cause of death, is CVD, representing advanced liver disease the second item in order of relevance.\u003c/p\u003e \u003cp\u003eA 2013 metanalysis reported several studies demonstrating an increased risk of CVD among patients with NAFLD, (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) but we had to wait for a paper published in 2021 to have an idea about the prevalence of myocardial infarction (MI) and stroke in USA adults, expressed as percentage of 10-year risk, for MASLD compared to non-MASLD subjects. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) In the above cited work, which analyzed data from 19617 adults aged\u0026thinsp;\u0026ge;\u0026thinsp;20 years from the cross-sectional US National Health and Nutrition Examinations Survey periods ranging from 1999 to 2016, the estimated 10-year risk of MI and stroke ranged from 10.8 to 13.2% in MASLD subjects and from 6.6 to 7.1% in non-MASLD population; therefore, the highest prevalence presented by MASLD subjects ranges from 5.2 to 6.1% over a 10 years period. Applying these data to Italian population we therefore deduce that in the MASLD individuals, apart T2DM-related complications (included in the computation of its global costs), we can estimate a population presenting IMA or stroke over a 10-year period ranged between 465,000 to 545,000.\u003c/p\u003e \u003cp\u003eChronic kidney disease (CKD) is another very important and recognized complication of MASLD.(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) In the main institutional document of Italian Ministry of Health about the management of CKD, defined as evaluated glomerular filtration rate (eGFR)\u0026thinsp;\u0026lt;\u0026thinsp;60 mL/min/mq 1,73 and/or urinary albumin-to-creatinine ratio (ACR)\u0026thinsp;\u0026ge;\u0026thinsp;3 mg/mmol, the prevalence, based principally on the STUDIO CHARES, is 7,1% (7,5% in men and 6,5% in women), including 2,6% in Stage 3 (eGFR 30\u0026ndash;59 mL/min/mq 1,73) and 0,3% in stage 4\u0026ndash;5 (eGFR\u0026thinsp;\u0026lt;\u0026thinsp;30 mL/min/mq 1,73).(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) Considering these epidemiologic data, we can calculate renal impairment in general population amounting to about 4,18\u0026nbsp;million subjects, including 177,000 affected by stage 4\u0026ndash;5 CKD. Another review reported that NAFLD patients presented a higher risk of incident CKD compared with those without NAFLD over a median follow-up of nearly 5 years (HR 1.37, 95% CI 1.20\u0026ndash;1.50) (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), so, considering that MASLD individuals present a lower glomerular filtration rate and a greater prevalence of CKD than NAFLD individuals (29,6% vs 25.56%, P\u0026thinsp;\u0026lt;\u0026thinsp;0,05), (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) even applying the previous and more conservative rate of 1.37 to Italian MASLD population, we can estimate at least 1,13\u0026nbsp;million subjects with CKD of which 47,600 presenting stage 4\u0026ndash;5 CKD. Therefore, excluding MASLD patients with T2DM, which represent two-thirds of all diabetic patients, and considering that T2DM determines about 20% of all cases of CKD, (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) we can deduce about 590,000 not-T2DM MASLD subjects presenting CDK, and 24,600 with stage 4\u0026ndash;5 CKD.\u003c/p\u003e \u003cp\u003eAnother important epidemiological association presented by MASLD subjects regards the increase in colorectal cancer (CRC) risk. A study starting from a nationwide health screening database including more than 8.9\u0026nbsp;million participants demonstrated that MASLD, more than NAFLD, was associated with a higher CRC risk, that, after multivariable adjustment for age, sex, household income quartile, residential area, CCI index (Charlson Comorbidity Index, which predicts 10-year survival in patients with multiple comorbidities), aspirin use, nonsteroidal anti-inflammatory drug use, tobacco smoke, exercise frequency, alcohol intake and concomitant liver diseases, was expressed as an HR of 1.16 (95% CI, 1.13\u0026ndash;1.18).(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) The study also detected that patients with fatty liver disease and advanced liver fibrosis were at higher CRC risk than those with simple steatosis, suggesting that an adequate intervention on the disease could reduce the overall risk. Considering that the incidence rate detected for individuals without MASLD was 57,5 per 100.000 person-years, the extra incidence attributable to MASLD can be quantified in 9,2 per 100.000 person-years. Applying this to the above defined Italian MASLD population (11,6\u0026nbsp;million) we can consider an extra incidence of CRC in MASLD subject of about 1067 patients per year.\u003c/p\u003e \u003cp\u003eLast but not least, MASLD presents a higher risk of hepatic events, which incidence is related to the stage of fibrosis detected (F0-F2 versus F3 versus F4) as follows: variceal hemorrhage (0.00 versus 0.06 versus 0.70), ascites (0.04 versus 0.52 versus 1.20), encephalopathy (0.02 versus 0.75 versus 2.39), and hepatocellular carcinoma (HCC) (0.04 versus 0.34 versus 0.14) per 100 persons-year.(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) Considering that the annual incidence of HCC in NAFLD (and moreover MASLD) patients is 0.44 per 1000 person-years (95% CI: 0.29\u0026ndash;0.66) whereas for MASH is 5.29 per 1000 person-year and reminding also that approximately 41% (95% CI: 34.69\u0026ndash;47.13) of MASH patients present a worsening of fibrosis with an annual progression rate of 0.09% (95% CI: 0.06\u0026ndash;0.12), the development of HCC an mortality has been stratified by NAFLD/MASLD or MASH status, as shown in Material and Methods.(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eConsidering the constant growth of MASLD in terms of percentage of population concerned (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), aim of our study is to evaluate the economic impact of MASLD among Italian population from the Italian National Healthcare Service (NHS) perspective.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eMASLD economic impact was assessed developing a calculation model in Microsoft Excel\u0026reg;. The analysis was conducted from the Italian NHS perspective, considering healthcare resources and direct costs related to the clinical conditions management in the Italian setting. Target population has been defined based on prevalence data, to provide a snapshot of the current situation. Prior to the analysis, a literature search was conducted aimed at examining the MASLD clinical background and gathering evidence regarding the complications and possible specific clinical conditions evolution. Following the review, the main MASLD-related complications were identified, corresponding to: MASH, with relative risk of evolution into CC, DCC, HCC, T2 diabetes mellitus, cardiovascular diseases, in particular MI and stroke, CKD, and CRC. Since these complications, in turn, represent significant chronic, metabolic and worsening diseases, it was chosen to evaluate the differential impact between their development in the population with MASLD and in a same sample size population without-MASLD, to highlight the negative impact, still largely overlooked today, represented by the presence of MASLD. T2DM cardiovascular related events were included among the costs of the disease.\u003c/p\u003e \u003cp\u003eDifferential risk data, referring to these conditions development between the population affected by MASLD and non-MASLD population, were drawn from published international literature. Mortality rates associated with complications were also researched, with the aim of estimating the differential impact on patients destined to die between the two groups. Once the estimated event rates for the compared groups were obtained, the annual unit cost of each event was applied to these values. Also, annual unit costs per event were taken from the literature, adopting specific data for the Italian healthcare context. Frequency and cost data were applied to the total target population, the total annual costs and mortality data referring to the two arms were then calculated and the differential value was obtained.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eTarget population\u003c/h2\u003e \u003cp\u003eMASLD target population was estimated by applying prevalence data and clinical characteristics obtained from international literature (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) to the Italian epidemiological context.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) Since no Italian studies on specific MASLD population are available, target population was obtained by extrapolation, starting from international data on the share of patients affected by MASLD among diabetics (67.75%) and the estimate of diabetic patients among the total patients with MASLD (22.79%). (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) Based on a total Italian population of 58,850,000 and a 6.6% diabetes prevalence, (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) a target population of 11,546,370 subjects in Italy was estimated, corresponding to approximately 19.6% of the total population, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Our estimate of prevalence must be considered as a conservative one, presenting international literature higher estimates of prevalence worldwide.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTarget population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%/n\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Italian population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58,850,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes n.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,884,100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes-MASLD %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes-MASLD n.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,631,418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMASLD-Diabetes%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.79%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMASLD population\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11,546,370\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eEvent rate and unit costs\u003c/h2\u003e \u003cp\u003eDifferential rates of complications occurrence in the MASLD target population and in a same sample size not affected by MASLD were obtained from a literature search regarding the main complications from MASLD (MASH and advanced stages of liver damage (CC, DCC, HCC), diabetes, cardiovascular diseases, including mainly myocardial infarction and stroke, CKD, and colorectal cancer). (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eFor each complication, the unit cost was sought by referring to the relevant Italian literature (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), for steatosis evaluation, outpatient services tariff was adopted. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the event occurrence rates and the related cost per event.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEvent rate and unit cost\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMASLD %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO MASLD %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnit Costs\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSteatosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMASH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMASH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 347\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.51%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 5,465\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.04%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 6,075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT2 diabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 2,589\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMI and stroke\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.69%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 13,206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic kidney disease (CKD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.75%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 1,404\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.56%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 2,122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 4,509\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eColorectal cancer (CRC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.07%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026euro; 4,300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMortality\u003c/h2\u003e \u003cp\u003eTo estimate the complications impact also on life expectancy, the mortality rate related to each complication was searched in the literature. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThis further analysis was conducted to evaluate the differential impact between populations on deaths associated with the clinical condition of MASLD and related complications compared to the population without MASLD. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the mortality rates adopted.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMortality rates\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMortality%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSteatosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMASH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMASH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13,7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28,3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT2 diabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMI and stroke\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic kidney disease (CKD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0,0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eColorectal cancer (CRC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45,1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analysis\u003c/h2\u003e \u003cp\u003eTo assess the robustness of the results related to the main input adopted and assumptions considered, a one-way sensitivity analysis has been carried out, varying by \u0026plusmn;\u0026thinsp;5% epidemiological data and by \u0026plusmn;\u0026thinsp;10% event rates and costs input data. The simulation scenarios were developed compared to the base case, adopting as reference parameter the difference in total expenditure reported in the MASLD population and in the same sample without MASLD.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe results have highlighted the differential impact, between the population with MASLD and without MASLD, on events occurrence, corresponding to the complications and disease evolutions to advanced stages, allowing the relative economic impact to be assessed as well, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eComparing the two arms, based on disease prevalence data application, it is possible to grasp the significant impact related to the presence, in particular, of steatosis conditions and liver disease advanced stages, as a basic distinctive element between the two groups, resulting in an increase in costs of \u0026euro;528,826,092 for steatosis and \u0026euro;1,027,880,550 overall for liver disease advanced stages (MASH, CC, DCC, HCC). The impact of diabetes was particularly significant, resulting in an increase in expenditure of \u0026euro; 4.839.766.057, corresponding to the largest cost item, given the high prevalence within the population with MASLD, considering also the elevate rate of cardiovascular events.\u003c/p\u003e \u003cp\u003eMoreover, to these major items, we have added the costs related to cardiovascular diseases (MI, stoke), CKD and colorectal cancer with an expense of \u0026euro; 785,274,445, \u0026euro; 545,359,165, and \u0026euro; 4,567,744, respectively.\u003c/p\u003e \u003cp\u003eOverall, in consideration of a MASLD population estimate equal to \u0026euro;11,546,370, an annual illness impact of \u0026euro;12,251,631,822 was calculated, corresponding to a difference of \u0026euro;7,731,674,054 compared to the same sample size without MASLD.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTotal events and related cost compared: MASLD \u003cem\u003eversus\u003c/em\u003e without MASLD population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMASLD (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO MASLD (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDELTA (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMASLD\u003c/p\u003e \u003cp\u003e(\u0026euro;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNO MASLD (\u0026euro;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDELTA\u003c/p\u003e \u003cp\u003e(\u0026euro;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSteatosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.775.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8.775.740\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 528.826.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 528.826.092\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMASH\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 1.027.880.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 1.027.880.550\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMASH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.589.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.589.400\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 636.992.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 636.992.400\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e117.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e117.700\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 40.841.900\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 40.841.900\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e58.850\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 321.615.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 321.615.250\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4.680\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 28.431.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 28.431.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT2 Diabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.631.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e762.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.869.357\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 6.812.740.485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 1.972.974.427\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 4.839.766.057\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMI and stroke\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e138.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e59.464\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 1.829.765.697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 1.044.491.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 785.274.445\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic kidney disease (CKD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.123.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e819.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e303.323\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 2.019.302.854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 1.473.943.689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 545.359.165\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1\u0026ndash;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e664.378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e484.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e179.431\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 932.585.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 680.719.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 251.866.078\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e411.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e111.076\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 872.739.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 637.036.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 235.703.440\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 4\u0026ndash;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e12.816\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 213.977.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 156.188.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 57.789.646\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eColorectal cancer (CRC)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.062\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 33.116.144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 28.548.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 4.567.744\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTOTAL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026euro; 12.251.631.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026euro; 4.519.957.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026euro; 7.731.674.054\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe different impact in terms of costs of diabetes, MASH, MI and stroke, CKD, steatosis, and colorectal cancer in MASLD and non-MASLD is reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe analysis also allowed to estimate the number of deaths attributable to the two populations and the relative difference, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The presence of MASLD has shown a greater number of deaths, in particular, due to advanced liver diseases, colorectal cancer and cardiovascular disease, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eOverall, the MASLD population is expected to result in 13,126 annual additional deaths, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImpact of disease on mortality: MASLD versus without MASLD population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath number disease-related\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMASLD N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNO MASLD N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDELTA N\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDCC\u0026thinsp;+\u0026thinsp;CC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e479\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMI and stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.378\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2DM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e531\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCKD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTOTAL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e18.229\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5.103\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e13.126\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe sensitivity analysis has shown the robustness of the results. Actually, the main input data and assumptions variation has not resulted in significant deviations from base case findings, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eCompared to an increase in cost for MASLD \u003cem\u003eversus\u003c/em\u003e non-MASLD population reported for the base case equal to \u0026euro;7.7\u0026nbsp;million, the sensitivity analysis documented a maximum value corresponding to a 10% event rates increase, with a result equal to \u0026euro; 8.8\u0026nbsp;million and a minimum value corresponding to a 10% event rates reduction equal to 6.7\u0026nbsp;million.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn a previous paper we evaluated the epidemiologic and economic burden of NAFLD/MASH among T2DM population, (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) while in this study we have further expanded the magnifying glass on the huge social issue of MASLD in Italian general population, a condition involving a multi-organ impairment and strictly associated to individual behaviors. Starting from this point of view, T2DM represents the main complication as well as the main cost item of MASLD, with about two thirds of all cases of diabetes generated by it.\u003c/p\u003e \u003cp\u003eIn Italy, the estimated population suffering from MASLD, amounts to 11,546,370 individuals, corresponding to 19.6% of the general population. The annual burden of MASLD disease in terms of mortality and healthcare expenses, as resulting from the Italian NHS perspective adoption, is very impressive: total direct healthcare costs amount to \u0026euro; 7.731.674.054, which correspond to 5.68% of national healthcare expenditure expected for 2023; in addition, MASLD accounts for 13,126 deaths per year.\u003c/p\u003e \u003cp\u003eAmong the estimated population suffering from MASLD, amounting to 11,546,370, we count 22.79% of subjects presenting T2DM and, considering the annual incidence of T2DM \u0026minus;\u0026thinsp;350,000 new diagnosis per year- and the prevalence of MASLD among T2DM, we can deduce that 238,000 patients shift from MASLD to T2DM every year. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eT2DM represents the first and preponderant cost item among MASLD (4,839,766,057 \u0026euro;/yr), producing 62.6% of the total expenditure of this metabolic disease, so interventions aiming to reduce the economic burden of MASLD must be targeted mainly to the prevention of its development towards diabetes.\u003c/p\u003e \u003cp\u003eConsidering the overall MASLD individuals, 72,37% are affected by hepatic steatosis, 22,43% present MASH, and a minimal share of subjects suffer from HCC (0.80%), severe chronic kidney disease (Stage IV-V: 0,41%) and colorectal cancer (0,07%). Liver impairment represents a lower burden in terms of costs (\u0026euro; 1.573.239.715, 20,4% of total costs, adding steatosis and MASH), but the highest in terms of lethality, accounting for 9.391 deaths per year, equal to 71,5% of the annual MASLD related mortality.\u003c/p\u003e \u003cp\u003eCardiovascular complications (MI and stroke), accounting for \u0026euro; 785.274.445 and 1378 deaths per year, rank third considering the combinations of cost and lethality, but they would probably come first if we also considered the CV events already included among the complications of T2DM-MASLD subjects. And also, CV related lethality could increase if we consider also T2DM related CV deaths, which are often not attributed to diabetes in Italian death statistical reports. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eChronic kidney disease remains above half a billion in annual costs (\u0026euro; 545.359.165) and MASLD-related colorectal cancer is responsible of 479 deaths per year (3.6% of total MASLD-related deaths).\u003c/p\u003e \u003cp\u003eTherefore, cost analysis of MASLD complications showed a frank predominant burden of chronic metabolic and hepatic illnesses: in fact T2DM and Steatosis-MASH produce 62,5% and 20,4% of overall health spending, respectively, whereas acute cardiovascular complications (MI and stroke) and renal impairment are separately responsible of 10,16% and 7,05% of cost weight; last but not least, minor cost is associated to colorectal cancer (0,06%), due to lower incidence and higher mortality. Beyond the evaluation of the global economic burden of the disease, it is interesting to highlight that the differential pro-capita cost related to MASLD subjects amounts to \u0026euro; 670 per year. This figure could therefore be taken as reference for assessing the cost-effectiveness of treatments aimed at stopping the evolution of MASLD disease.\u003c/p\u003e \u003cp\u003eSensitivity analysis showed that hypothetical variation of \u0026plusmn;\u0026thinsp;5% regarding population data input and \u0026plusmn;\u0026thinsp;10% regarding costs and MASLD related events could result in a range of global direct cost varying from \u0026euro; 6.7\u0026nbsp;billion to \u0026euro; 8.8\u0026nbsp;billion, corresponding respectively to 4.85% and 6.47% of annual global sanitary expenditure.\u003c/p\u003e \u003cp\u003eIt remains to evaluate the entity of the time lag necessary to develop an effective reduction of the incidence of MASLD related complications after starting an effective therapeutic measure. During this period, the costs of the treatment will be superimposed to the costs of the disease, but we have considered that our study did not include neither the estimate of indirect costs, nor its impact in terms of impairment of national GDP.\u003c/p\u003e \u003cp\u003eLimitations of our study lie in the lack of a direct estimate of the real prevalence of MASLD among Italian population, and for this reason we preferred to underestimate the possible prevalence, and in the necessity of maximizing the simplicity of our model.\u003c/p\u003e \u003cp\u003eFinally, our study has adopted international data when national ones were not available. Points of strength of our work correspond to the first study to have evaluated the economic burden of MASLD among Italian population as well as to have analyzed in an innovative way MASLD related diseases, so that T2DM can be, at least partially, seen as a complication of the hepatic disease.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eData emerging from our study are impressive, both in terms of the number of subjects involved, amounting to about one fifth of Italian population, and of the economic burden (\u0026euro; 7,73\u0026nbsp;billion per year). A recent study evaluating the economic burden of obesity in Italy documented a similar direct cost profile (\u0026euro; 7.89\u0026nbsp;billion), with the higher impact of cardiovascular diseases (\u0026euro; 6.66\u0026nbsp;billion).(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e) Even if the two populations are largely overlapping, we believe that the basic behavioral and pharmacological treatment could be the same, reserving more targeted interventions, regarding MASLD subject, for prevention of new cases of T2DM and for prevention and early treatment of MASH.\u003c/p\u003e \u003cp\u003eTherefore, the growing epidemiological impact of MASLD, obesity and its complications, associated with the related cardiovascular diseases, will represent a huge economic burden for healthcare services worldwide for the next decades, and a holistic approach to the person (mainly behaviors lifestyle changes) to control the dramatic health and economic impact will be the first step to take.\u003c/p\u003e \u003cp\u003eSpecific drugs for MASLD are not yet available, but studies are underway on many molecules, and combination pharmaceutical therapies may be an inevitable choice to achieve adequate control of MASLD and its complications in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the development of this study it was not necessary to proceed with the request for ethics approval and consent to participate; previously published and validated literature sources were adopted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by unconditional and exclusive grant from NovoNordisk, Italy. The authors report no other conflicts of interest in this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by unconditional and exclusive grant from NovoNordisk, Italy\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eE.T. and S.D. defined the rationale for the study and the original model framework. G.L.C. and C.M. reviewed and validated the model adaptation and wrote the manuscript. U.G., A.R., L.C.B. and G.T. interpreted data and supported clinical data research. G.M.B. and C.L.C. supervised the project and decided on manuscript content and structure. All authors contributed toward data analysis, drafting and revising the paper and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDe A, Bhagat N, Mehta M, Taneja S, Duseja A. Metabolic dysfunction-associated steatotic liver disease (MASLD) definition is better than MAFLD criteria for lean patients with NAFLD. J Hepatol 2023 Aug 7:S0168-8278(23)05044-4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoccatonda A, Andreetto L, D\u0026rsquo;Ardes D, Cocco G, et al. From NAFLD to MAFLD: Definition, Pathophysiologcal Basis and Cardiovascular Implications. Biomedicines. 2023;11:883.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChalasani N, Younossi Z, Lavine JE, Charlton M, Cusi K, Rinella M, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology. 2018;67:328\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEslam M, Sanyal AJ, George J. MAFLD: A Consensus-Driven Proposed Nomenclature for Metabolic Associated Fatty Liver Disease. Gastroenterology. 2020;158(7):1999\u0026ndash;2014. e1991.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang HJ, Wang YY, Chen C, Lu YL, Wang NJ. Cardiovascular and renal burdens of metabolic associated fatty liver disease from serial US national surveys, 1999\u0026ndash;2016. Chin Med J. 2021;134(13):1593\u0026ndash;601.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLim GEH, Tang A, Ng CH et al. March. An Observational Data Meta-analysis on the Differences in Prevalence and Risk Factors Between MAFLD vs NAFLD. Volume 21, Issue 3, 2023, Pages 619\u0026ndash;629.e7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChan KE et al. Tiffany Jia Ling Koh, Ansel Shao Pin Tang Global Prevalence and Clinical Characteristics of Metabolic-associated Fatty Liver Disease: A Meta-Analysis and Systematic Review of 10 739 607 Individuals. The Journal of Clinical Endocrinology \u0026amp; Metabolism, 2022, 107, 2691\u0026ndash;2700.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e16th Italian Barometer Diabetes Report, Diabetes Monitor Journal., 2023, IBDO Foundation, 67\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYounossi ZM, Golabi P, De Avila L, et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis. J Hepatol. 2019;71:793\u0026ndash;801. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.jhep.2019.06.021\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2019.06.021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eISTAT. Popolazione residente 1\u0026deg; gennaio 2023. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://demo.istat.it/app/?i=POS\u0026amp;l=it\u003c/span\u003e\u003cspan address=\"https://demo.istat.it/app/?i=POS\u0026amp;l=it\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonora E. La pandemia di diabete in Italia. L\u0026rsquo;Endocrinologo. 2022;23:337\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnstee QM, Targher G, Day CP. Progression of NAFLD to diabetes mellitus, cardiovascular disease or cirrhosis. Nat Rev Gastroenterol Hepatol. 2013;10:330\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nrgastro.2013.41\u003c/span\u003e\u003cspan address=\"10.1038/nrgastro.2013.41\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMantovani A, Lombardi R, Cattazzo F, et al. MAFLD and CKD: An Updated Narrative Review. Int J Mol Sci. 2022;23:7007.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Nicola L, Donfrancesco C, Minutolo R, et al. Epidemiologia della MRC in Italia: stato dell\u0026rsquo;arte e contributo dello studio CHARES. G Ital Nefrol. 2011;28(4):401\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMantovani A, Zaza G, Byrne CD, et al. Nonalcoholic fatty liver disease increases risk of incident chronic kidney disease: A systematic review and meta-analysis. Metabolism. 2018;79:64\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun DQ, Jin Y, Wang T, et al. MAFLD and risk of CKD. Metabolism. 2021;115:154433.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSNLG-Regioni. La nefropatia diabetica: linee guida diagnostiche e terapeutiche Zadig- Milano., 2016, 23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee H, Lee HW, Kim SU, Kim HC. Metabolic Dysfunction-associated Fatty Liver Disease Increases Colon hiips:77\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003edoi.org/10.14309/ctg.0000000000000435\u003c/span\u003e\u003cspan address=\"10.14309/ctg.0000000000000435\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePipitone RM, Ciccioli C, Infantino G, et al. MAFLD: a multisystem disease. Ther Adv Endocrinol Metab. 2023;14:1\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/20420188221145549\u003c/span\u003e\u003cspan address=\"10.1177/20420188221145549\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYounossi ZM, Koenig AB, Abdelatif D, et al. Global epidemiology of nonalcoholic fatty liver disease\u0026mdash;meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64:73\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerrarese A, Battistella S, Germani G. Nash Up, Virus Down: How the waiting list Is Changing for Liver Tranplantation: a Single Center Experience from Italy. Medicina. 2022;58:290: 1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEstes C, Anstee QM, Arias-Loste MT, et al. Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016\u0026ndash;2030. J Hepatol. 2018;69(4):896\u0026ndash;904.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAIOM. I numeri del cancro in Italia 2022. Intermedia Editore. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.aiom.it/wp-content/uploads/2022/12/2022_AIOM_NDC-web.pdf\u003c/span\u003e\u003cspan address=\"https://www.aiom.it/wp-content/uploads/2022/12/2022_AIOM_NDC-web.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAISF, Libro bianco AISF. 2011. Proposta per un piano nazionale per il controllo delle malattie epatiche. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.webaisf.org/wp-content/uploads/2019/01/libro-bianco-aisf-2011.pdf\u003c/span\u003e\u003cspan address=\"https://www.webaisf.org/wp-content/uploads/2019/01/libro-bianco-aisf-2011.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLucioni C, Mazzi S, Rossi S, et al. Percorsi terapeutici e costi sanitari di pazienti ricoverati per un evento cardiovascolare in Italia. Global \u0026amp; Regional Health Technology Assessment. 2016;3(2):80\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePagano E, De Rosa M, Rossi E, Cinconze E, Marchesini G, Miccoli R, Vaccaro O, Bonora E, Bruno G. The relative burden of diabetes complications on healthcare costs: The population-based CINECA-SID ARNO Diabetes Observatory. Nutr Metab Cardiovasc Dis. 2016;26(10):944\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJommi C, Armeni P, Battista M, IRIDE Study Group, et al. The Cost of Patients with Chronic Kidney Failure Before Dialysis: Results from the IRIDE Observational Study. Pharmacoecon Open. 2018;2(4):459\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrancisci S, Guzzinati S, Mezzetti M, et al. Cost profiles of colorectal cancer patients in Italy based on individual patterns of care. BMC Cancer. 2013;13:329.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTariffe delle prestazioni di assistenza specialistica ambulatoriale. 2013 Allegato 3 Ministero della Salute - Direzione generale della programmazione sanitaria. Supplemento ordinario n. 8 alla Gazzetta Ufficiale. Serie generale - n. 23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eISTAT. Il diabete in Italia. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.istat.it/it/files/2017/07/REPORT_DIABETE.pdf\u003c/span\u003e\u003cspan address=\"https://www.istat.it/it/files/2017/07/REPORT_DIABETE.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaglietto A, Manfredi R, Elia E, D'Ascenzo F, DE Ferrari GM, Biondi-Zoccai G, Munzel T. Cardiovascular disease burden: Italian and global perspectives. Minerva Cardiol Angiol. 2021;69(3):231\u0026ndash;240. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.23736/S2724-5683.21.05538-9\u003c/span\u003e\u003cspan address=\"10.23736/S2724-5683.21.05538-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2021 Mar 11. PMID: 33703858.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMortalit\u0026agrave; per insufficienza renale cronica. Available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ars.toscana.it/banche-dati/dettaglio_indicatore-1329-mortalita-insufficienza-renale-cronica?provenienza=dettaglio_indicatore_consigliati\u003c/span\u003e\u003cspan address=\"https://www.ars.toscana.it/banche-dati/dettaglio_indicatore-1329-mortalita-insufficienza-renale-cronica?provenienza=dettaglio_indicatore_consigliati\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u0026amp;par_top_geografia=090\u0026amp;dettaglio=ric_anno_geo_ausl.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTorre E, Di Matteo S, Bruno GM, et al. Economic Burden of Non-Alcoholic Steatohepatitis (NASH) Among Diabetic Population in Italy: Analysis and Perspectives. Clinicoecon Outcomes Res. 2022;14:607\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eD\u0026rsquo;Errico M, Pavlova M, Spandonaro F. The economic burden of obesity in Italy: a cost-of-illness study. Eur J Health Econ. 2022;23:177\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"metabolic associated fatty liver disease (MASLD), complications, MASLD burden in Italy, healthcare costs, treatment and perspectives","lastPublishedDoi":"10.21203/rs.3.rs-3755157/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3755157/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eMASLD constitutes the ominous shadow of obesity and diabetes mellitus, destined to become pandemics for the coming decades. MASLD is a multisystem disease presenting an increased risk of developing cardio-nephrometabolic complications, extrahepatic tumors, and the obvious liver-related complications. Aim of our study is to evaluate the economic impact of MASLD among Italian population from the Italian National Healthcare Service (NHS) perspective.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eMASLD economic impact was assessed developing a calculation model in Microsoft Excel®, from the Italian NHS perspective, considering healthcare resources and direct costs. \u0026nbsp;Target population has been defined based on prevalence data. A literature search was conducted and the main MASLD-related complications were identified, corresponding to: MASH, with relative risk of evolution into CC, DCC, HCC, T2 diabetes mellitus, cardiovascular diseases, in particular MI and stroke, CKD, and CRC. It was chosen to evaluate the differential impact between complications development in the population with MASLD and in a same sample size population without-MASLD. Differential risk data, mortality rates and event unit costs were drawn from published international literature. Frequency and cost data were applied to the total target population, the total annual costs and mortality data, referring to the two arms, were then calculated and the differential value was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOverall, based on an estimated 11,546,370 MASLD target population, an annual illness impact of €12,251,631,822 was calculated, corresponding to a difference of €7,731,674,054 compared to the same sample size without MASLD. Moreover, MASLD population is expected to result in 13,126 annual additional deaths.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The growing epidemiological impact of MASLD and its complications, will represent a huge economic burden for healthcare services worldwide. An holistic approach, mainly behaviors lifestyle change, to control the dramatic health and economic impact will be the first step to take. Specific drugs for MASLD are not yet available, but studies are underway, and combination pharmaceutical therapies may be an inevitable choice to achieve adequate control of MASLD and its complications in the future.\u003c/p\u003e","manuscriptTitle":"Economic impact of metabolic dysfunction-associated steatotic liver (MASLD) in Italy. Analysis and perspectives","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-02 16:33:21","doi":"10.21203/rs.3.rs-3755157/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"23d1bdd0-d978-4030-b834-bf02965bc2b4","owner":[],"postedDate":"January 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-08T10:44:16+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-02 16:33:21","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3755157","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3755157","identity":"rs-3755157","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}