| Literature DB >> 36249202 |
Xiaohui Zeng1, Zhen Zhou2, Xia Luo3, Qiao Liu3.
Abstract
Objective: To compare the cost-effectiveness of undertaking low-dose computed tomography (LDCT) screening for early detection of lung cancer (LC) with different frequencies within the healthcare system of China, and estimate the additional national healthcare expenditure and five-year LC mortality associated with different screening frequencies. Material and methods: A Markov model was established using national LC epidemiological data from the Chinese Center for Disease Control and Prevention, demographic data from the Chinese Statistical Yearbook, and cost and effectiveness data mainly from the Cancer Screening Program in China. The model included thirty sex-specific screening strategies, which were classified by initial screening age (30, 35, 40, 45, and 50), and screening intervals (intervals at single time point, 1, 2, 5, 10, and 20 years). The main model outputs were incremental cost-effectiveness ratios (ICERs), additional national healthcare expenditure and five-year LC mortality.Entities:
Keywords: China; LDCT; cost-effectiveness; five-year LC mortality; healthcare expenditures; lung cancer
Mesh:
Year: 2022 PMID: 36249202 PMCID: PMC9558698 DOI: 10.3389/fpubh.2022.977550
Source DB: PubMed Journal: Front Public Health ISSN: 2296-2565
Figure 1Diagram of Markov model. LC, lung cancer.
Model parameters and assumptions.
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| Health to death | Sex- and age-specific all-cause mortality | / | Chinese life table |
| Health to LC | Sex- and age-specific LC incidence | / | CDCP |
| Localized LC to localized LC | 0.094000 | Beta | CanSPUC |
| Localized LC to regional LC | 0.198000 | Beta | CanSPUC |
| Localized LC to distant LC | 0.631836 | Beta | CanSPUC |
| Localized LC to death | 0.076164 | Beta | CMIR |
| Regional LC to regional LC | 0.389000 | Beta | CanSPUC |
| Regional LC to distant LC | 0.418618 | Beta | CanSPUC |
| Regional LC to death | 0.192382 | Beta | CMIR |
| Distant LC to distant LC | 0.553606 | Beta | CanSPUC |
| Distant LC to death | 0.446394 | Beta | CMIR |
| Distribution of LC patients (%) | |||
| Localized LC in screening cohort | 91.6 | Beta | CanSPUC+RuraCSP |
| Regional LC in screening cohort | 7.6 | Beta | CanSPUC+RuraCSP |
| Distant LC in screening cohort | 1.1 | Beta | CanSPUC+RuraCSP |
| Localized LC in the non-screening cohort | 21.4 | Beta | CanSPUC+RuraCSP |
| Regional LC in the non-screening cohort | 26.3 | Beta | CanSPUC+RuraCSP |
| Distant LC in the non-screening cohort | 52.3 | Beta | CanSPUC+RuraCSP |
| Costs (US$) | |||
| Screening | 55.03 (44.02–66.03) | Gamma | CanSPUC |
| Confirmation test for positive cases | 180.40 (144.32–216.48) | Gamma | Local hospitals |
| LC treatments | |||
| Localized LC | 10264.91 (8211.93–12317.90) | Gamma | CanSPUC |
| Regional LC | 10795.86 (8636.69–12955.03) | Gamma | CanSPUC |
| Distant LC | 11857.74 (9486.20–14339.29) | Gamma | CanSPUC |
| Utilities | |||
| Localized LC | 0.823 (0.670–0.972) | Beta | ( |
| Regional LC | 0.772 (0.619–0.921) | Beta | ( |
| Distant LC | 0.573 (0.420–0.773) | Beta | ( |
| Other | |||
| Discount rate (%) | 5 (0–8) | Beta | Chinese Guidelines |
| Overdiagnosis rate (%) | 0 (0–3) | Beta | NLST |
| Sensitivity of LDCT screening (%) | 87.70 (71.80–100) | Beta | ( |
| Specificity of LDCT screening (%) | 90.60 (86.30–91.10) | Beta | ( |
LC, lung cancer; LDCT, Low-dose computed tomography; CDCP, Chinese Center for Disease Control and Prevention; canSPUC, Cancer Screening Program in Urban China; ruraCSP, Rural Cancer Screening Program; CMIR, Chinese multi-institutional registry; NLST, National Lung Screening Trial.
Cost-effectiveness analysis summary.
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| / | Non-screening | 270 | 43.05266 | / | / | / | 129 | 46.17236 | / | / | / |
| 30 | One-off | 342 | 43.05268 | 72 | 0.00002 | 3,675,491 | 201 | 46.17238 | 72 | 0.00001 | 5,943,556 |
| Every 20 years | 377 | 43.05451 | 107 | 0.00185 | 57,834 | 237 | 46.17322 | 108 | 0.00085 | 126,419 | |
| Every 10 years | 437 | 43.05549 | 166 | 0.00283 | 58,864 | 298 | 46.17366 | 168 | 0.00129 | 130,062 | |
| Every 5 years | 559 | 43.05746 | 289 | 0.00480 | 60,192 | 422 | 46.17455 | 292 | 0.00218 | 133,908 | |
| Every 2 years | 939 | 43.06433 | 669 | 0.01167 | 57,354 | 810 | 46.17779 | 681 | 0.00543 | 125,453 | |
| Every year | 1,571 | 43.07713 | 1,301 | 0.02447 | 53,171 | 1,452 | 46.18374 | 1,322 | 0.01138 | 116,205 | |
| 35 | One-off | 326 | 43.05270 | 56 | 0.00004 | 1,422,171 | 186 | 46.17239 | 56 | 0.00002 | 2,285,082 |
| Every 20 years | 347 | 43.05327 | 77 | 0.00061 | 126,449 | 207 | 46.17263 | 77 | 0.00027 | 285,300 | |
| Every 10 years | 393 | 43.05464 | 122 | 0.00197 | 62,093 | 253 | 46.17325 | 124 | 0.00089 | 139,506 | |
| Every 5 years | 487 | 43.05744 | 217 | 0.00478 | 45,368 | 350 | 46.17453 | 220 | 0.00217 | 101,469 | |
| Every 2 years | 769 | 43.06359 | 499 | 0.01093 | 45,663 | 639 | 46.17742 | 510 | 0.00506 | 100,774 | |
| Every year | 1,244 | 43.07702 | 974 | 0.02436 | 39,994 | 1,124 | 46.18368 | 995 | 0.01131 | 87,967 | |
| 40 | One-off | 314 | 43.05274 | 44 | 0.00008 | 568,259 | 173 | 46.17241 | 44 | 0.00005 | 888,447 |
| Every 20 years | 330 | 43.05364 | 59 | 0.00098 | 60,810 | 190 | 46.17280 | 60 | 0.00044 | 137,146 | |
| Every 10 years | 365 | 43.05547 | 94 | 0.00281 |
| 226 | 46.17365 | 96 | 0.00128 | 75,089 | |
| Every 5 years | 431 | 43.05740 | 161 | 0.00474 |
| 293 | 46.17451 | 164 | 0.00215 | 76,373 | |
| Every 2 years | 642 | 43.06419 | 371 | 0.01153 |
| 511 | 46.17770 | 382 | 0.00534 | 71,531 | |
| Every year | 990 | 43.07681 | 720 | 0.02415 |
| 869 | 46.18354 | 739 | 0.01118 | 66,138 | |
| 45 | One-off | 304 | 43.05281 | 34 | 0.00015 | 228,027 | 164 | 46.17244 | 34 | 0.00008 | 425,637 |
| Every 20 years | 316 | 43.05403 | 46 | 0.00137 |
| 176 | 46.17298 | 47 | 0.00062 | 75,611 | |
| Every 10 years | 337 | 43.05460 | 66 | 0.00193 |
| 197 | 46.17323 | 68 | 0.00086 | 78,277 | |
| Every 5 years | 387 | 43.05733 | 117 | 0.00466 |
| 249 | 46.17446 | 120 | 0.00210 | 57,155 | |
| Every 2 years | 537 | 43.06332 | 267 | 0.01066 |
| 406 | 46.17725 | 276 | 0.00489 | 56,545 | |
| Every year | 792 | 43.07639 | 522 | 0.02373 |
| 669 | 46.18327 | 539 | 0.01091 | 49,447 | |
| 50 | One-off | 297 | 43.05297 | 26 | 0.00031 | 85,716 | 156 | 46.17251 | 27 | 0.00015 | 179,626 |
| Every 20 years | 305 | 43.05449 | 35 | 0.00183 |
| 165 | 46.17321 | 36 | 0.00084 | 42,714 | |
| Every 10 years | 321 | 43.05539 | 51 | 0.00273 |
| 181 | 46.17360 | 52 | 0.00123 | 42,338 | |
| Every 5 years | 353 | 43.05718 | 83 | 0.00451 |
| 215 | 46.17438 | 85 | 0.00202 | 42,372 | |
| Every 2 years | 462 | 43.06367 | 191 | 0.01100 |
| 329 | 46.17739 | 200 | 0.00503 | 39,685 | |
| Every year | 639 | 43.07558 | 369 | 0.02292 |
| 513 | 46.18283 | 383 | 0.01046 |
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QALY, quality-adjusted life-year; ICER, incremental cost-effectiveness ratio.
The incremental personal cost for each screening strategy was calculated as the cost different between the screening strategy and the non-screening strategy.
The incremental personal QALY for each screening strategy was calculated as the QALY different between the screening strategy and the non-screening strategy.
ICER values below the willingness-to-pay threshold of $37,654 per QALY are shown in bold and italic font.
Figure 2Cost-effectiveness plane for all screening strategies in the male cohort. QALY, quality-adjusted life-year; WTP, willingness-to-pay. The screening strategies represented by the point below the WTP threshold of $37,654 per QALY are considered to be cost-effective; Otherwise they are not cost-effective.