| Literature DB >> 31263587 |
Jungyeon Kim1, Markus Haacker1,2, Salmaan Keshavjee3, Rifat Atun1,4.
Abstract
BACKGROUND: The prices and the coverage of effective direct-acting antivirals (DAAs) to treat hepatitis C vary across countries. South Korea expanded DAAs coverage through national health insurance. This study aims to analyse the cost-effectiveness of scale-up of hepatitis C screening and treatment with DAAs in South Korea, a high-income country.Entities:
Keywords: health economics; health insurance; screening; treatment; viral hepatitis
Year: 2019 PMID: 31263587 PMCID: PMC6570985 DOI: 10.1136/bmjgh-2019-001441
Source DB: PubMed Journal: BMJ Glob Health ISSN: 2059-7908
Figure 1Hepatitis C model structure.
Key model parameters used for the projection analysis
| Value | Source | ||||
|
| |||||
| Hepatitis C prevalence | Male | Female | |||
| Antibody | 0.6% | 0.7% | KHNAES | ||
| HCV RNA | 0.3% | 0.4% |
| ||
| No of people on DAAs treatment | HIRA | ||||
| 2015 | 26K | 20K | |||
| 2016 | 23K | 31K | |||
|
| |||||
| Mortality from hepatitis C | HCV RNA | HCV antibody | |||
| Up to CC | 0 | 0 | |||
| HCC | 0.20 | 0.20 |
| ||
| DCC | 0.15 | 0.15 |
| ||
| Liver transplant | 0.10 | 0.10 |
| ||
| Mortality from other causes | Sex-specific and age-specific estimates and projections based on World Population Prospects 2017 |
| |||
| Incidence of hepatitis C | Constant ‘thrust of infection’ parameters, implying incidence rate of 0.06% in 2015. | Derived from national prevalence estimates | |||
| Spontaneous clearance | 0.45 | 0.45 | Set to match observed prevalence data | ||
| Hepatitis C disease progression | Male | Female | |||
| F0 to F1 | 0.181/0.000 | 0.061/0.000 | Average across ages | ||
| F0 to F2 | 0.132/0.000 | 0.044/0.000 | |||
| F2 to F3 | 0.186/0.000 | 0.063/0.000 | |||
| F3 to CC | 0.128/0.038 | 0.046/0.014 | |||
| F3 to HCC | 0.004/0.001 | 0.002/0.000 | |||
| CC to HCC | 0.052/0.016 | 0.029/0.009 | |||
| CC to DCC | 0.028/0.010 | 0.022/0.010 | |||
| Sustained virological response rates | Male | Female | WHO | ||
| 0.95 | 0.95 | ||||
| General health screening rate | Male | Female | NHIS | ||
| A | B | A | B | ||
| Age | |||||
| Under 20 years | 0 | 1.00 | 0 | 1.00 | |
| 20–29 years | 0.40 | 0.60 | 0.40 | 0.60 | |
| 30–39 years | 0.75 | 0.25 | 0.50 | 0.50 | |
| 40 years and over | 0.75 | 0.25 | 0.75 | 0.25 | |
| Transition rate between category A and B | From age 40, 5% from A to B, | Assumption (online supplementary | |||
|
| |||||
| Hepatitis C screening | |||||
| Antibody test | US$20 | Test |
| ||
| RNA test | US$150 | Test |
| ||
| Treatment costs | |||||
| Chronic hepatitis C | US$10 000 | Patient |
| ||
| CC | US$2064 | Patient |
| ||
| DC | US$6146 | Patient |
| ||
| HCC | US$8000 | Year |
| ||
| Liver transplant | US$35 000 | Case |
| ||
| Postliver transplant | US$5000 | Year |
| ||
CC, compensated cirrhosis; DAAs, direct-acting antivirals; DC, decompensated cirrhosis; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; HIRA, Health Insurance Review and Assessment Service; KHNAES, Korea National Health and Nutrition Examination Survey; NHIS, National Health Insurance Scheme; SVR, sustained virological response.
Figure 2Epidemiological figures of hepatitis C under different policy scenarios.
Figure 3Projected costs under different policy scenarios by year.
Cost and health impacts of different policy options 2017–2050
| Accumulated costs and impacts until | |||||
| 2018 | 2020 | 2030 | 2040 | 2050 | |
|
| |||||
| Status quo | 203 | 689 | 5148 | 10 019 | 13 690 |
| Screening from 60 | 434 | 1259 | 6475 | 11 516 | 15 231 |
| Screening from 40 | 707 | 1936 | 8197 | 13 561 | 17 374 |
| Screening from 20 | 784 | 2129 | 8685 | 14 146 | 17 992 |
|
| |||||
| Status quo | 21 | 84 | 1194 | 3168 | 4913 |
| Screening from 60 | 33 | 128 | 1456 | 3536 | 5310 |
| Screening from 40 | 38 | 144 | 1616 | 3888 | 5798 |
| Screening from 20 | 38 | 144 | 1623 | 3908 | 5835 |
|
| |||||
| Status quo | 202 | 373 | 954 | 1252 | 1386 |
| Screening from 60 | 451 | 603 | 1141 | 1427 | 1558 |
| Screening from 40 | 795 | 926 | 1409 | 1670 | 1789 |
| Screening from 20 | 965 | 1091 | 1558 | 1815 | 1931 |
|
| |||||
| Status quo | 998 170 | 540 669 | 185 297 | 124 948 | 101 208 |
| Screening from 60 | 1 039 029 | 478 851 | 176 287 | 123 948 | 102 276 |
| Screening from 40 | 1 124 565 | 478 359 | 171 848 | 123 177 | 102 971 |
| Screening from 20 | 1 230 596 | 512 246 | 179 437 | 128 302 | 107 320 |
|
| |||||
| Status quo | 9 867 435 | 4 456 291 | 799 119 | 395 182 | 282 029 |
| Screening from 60 | 13 498 659 | 4 720 165 | 783 710 | 403 650 | 293 380 |
| Screening from 40 | 21 007 361 | 6 420 448 | 871 637 | 429 658 | 308 537 |
| Screening from 20 | 25 439 608 | 7 536 489 | 960 442 | 464 426 | 330 929 |
|
| |||||
|
| |||||
| Status quo | 203 | 689 | 5148 | 10 019 | 13 690 |
| Screening from 60 | 231 | 570 | 1326 | 1497 | 1541 |
| Screening from 40 | 273 | 677 | 1723 | 2046 | 2143 |
| Screening from 20 | 78 | 193 | 488 | 585 | 618 |
|
| |||||
| Status quo | 21 | 84 | 1194 | 3168 | 4913 |
| Screening from 60 | 13 | 44 | 263 | 368 | 397 |
| Screening from 40 | 4 | 16 | 160 | 352 | 489 |
| Screening from 20 | 0 | 0 | 6 | 20 | 36 |
|
| |||||
| Status quo | 202 | 373 | 954 | 1252 | 1386 |
| Screening from 60 | 248 | 230 | 187 | 176 | 172 |
| Screening from 40 | 344 | 323 | 267 | 243 | 231 |
| Screening from 20 | 170 | 164 | 150 | 144 | 142 |
|
| |||||
| Status quo | 998 170 | 540 669 | 185 297 | 124 948 | 101 208 |
| Screening from 60 | 1 074 867 | 404 093 | 141 311 | 117 260 | 111 770 |
| Screening from 40 | 1 260 665 | 477 442 | 155 163 | 118 834 | 107 909 |
| Screening from 20 | 2 197 194 | 852 683 | 306 943 | 247 192 | 229 604 |
|
| |||||
| Status quo | 9 867 435 | 4 456 291 | 799 119 | 395 182 | 282 029 |
| Screening from 60 | 19 277 053 | 5 220 339 | 713 661 | 476 444 | 433 832 |
| Screening from 40 | 77 654 439 | 19 588 848 | 1 673 009 | 691 156 | 473 235 |
| Screening from 20 | Dominated | Dominated | 23 046 095 | 7 199 017 | 3 903 209 |
Table shows difference between scenarios in the accumulated costs and health impacts from 2017 until year indicated. We used the 2016 year-average exchange rate29 to convert Korean won to US dollars (KRW 1160) and a discount rate of 3%.30
Returns to hepatitis C treatment of 100 persons in 2017 for the period 2017–2050 by sex and age
| (1) Costs | (2) Savings | Net cost | Averted | Cost per | |||||
| Total | Hepatitis C treatment | Cirrhosis and liver cancer treatment | Total | (1) minus | Infection | Death | Infection averted | Death averted | |
| Male | |||||||||
| 20–29 | 1 039 000 | 872 874 | 190 650 | 1 063 524 | −24 524 | 17.0 | 1.67 | −1440 | −14 680 |
| 30–39 | 1 039 000 | 856 106 | 299 994 | 1 156 100 | −117 100 | 17.7 | 3.48 | −6609 | −33 695 |
| 40–49 | 1 039 000 | 851 311 | 501 489 | 1 352 800 | −313 800 | 15.8 | 7.82 | −19 866 | −40 136 |
| 50–59 | 1 039 000 | 836 151 | 331 947 | 1 168 098 | −129 098 | 13.4 | 8.90 | −9606 | −14 500 |
| 60–69 | 1 039 000 | 778 178 | 207 695 | 985 874 | 53 126 | 11.1 | 11.21 | 4791 | 4737 |
| 70+ | 1 039 000 | 606 893 | 56 394 | 663 287 | 375 713 | 8.1 | 8.09 | 46 303 | 46 441 |
| 20+ | 1 039 000 | 812 871 | 311 702 | 1 124 573 | −85 573 | 13.6 | 8.14 | −6278 | −10,512 |
| Female | |||||||||
| 20–29 | 1 039 000 | 844 363 | 18 545 | 862 908 | 176 092 | 19.1 | 0.23 | 9216 | 764 891 |
| 30–39 | 1 039 000 | 829 795 | 39 472 | 869 267 | 169 733 | 20.0 | 0.42 | 8492 | 399 695 |
| 40–49 | 1 039 000 | 818 503 | 95 966 | 914 469 | 124 531 | 21.0 | 1.17 | 5944 | 106 531 |
| 50–59 | 1 039 000 | 824 358 | 156 745 | 981 103 | 57 897 | 19.2 | 2.38 | 3022 | 24 323 |
| 60–69 | 1 039 000 | 802 704 | 207 761 | 1 010 464 | 28 536 | 16.9 | 3.90 | 1685 | 7326 |
| 70+ | 1 039 000 | 634 720 | 120 913 | 755 633 | 283 367 | 12.0 | 3.26 | 23 614 | 86 936 |
| 20+ | 1 039 000 | 758 304 | 141 486 | 900 666 | 138 334 | 16.5 | 2.76 | 8367 | 50 177 |
Table shows costs and consequences of placing an additional 100 individuals on treatment, evaluated around the status quo scenario. Costs of testing are subsumed under treatment costs, and it is assumed that 12 individuals are tested for each person progressing to treatment. All totals are through 2050, and we used the 2016 year-average exchange rate29 to convert Korean won to US dollars (KRW 1160) and a discount rate of 3%.30