| Literature DB >> 27482709 |
Ying-Erh Chen1, Sung-Shuo Kao2, Ren-Hua Chung3.
Abstract
Patients with Lynch syndrome (LS) have a significantly increased risk of developing colorectal cancer (CRC) and other cancers. Genetic screening for LS among patients with newly diagnosed CRC aims to identify mutations in the disease-causing genes (i.e., the DNA mismatch repair genes) in the patients, to offer genetic testing for relatives of the patients with the mutations, and then to provide early prevention for the relatives with the mutations. Several genetic tests are available for LS, such as DNA sequencing for MMR genes and tumor testing using microsatellite instability and immunohistochemical analyses. Cost-effectiveness analyses of different genetic testing strategies for LS have been performed in several studies from different countries such as the US and Germany. However, a cost-effectiveness analysis for the testing has not yet been performed in Taiwan. In this study, we evaluated the cost-effectiveness of four genetic testing strategies for LS described in previous studies, while population-specific parameters, such as the mutation rates of the DNA mismatch repair genes and treatment costs for CRC in Taiwan, were used. The incremental cost-effectiveness ratios based on discounted life years gained due to genetic screening were calculated for the strategies relative to no screening and to the previous strategy. Using the World Health Organization standard, which was defined based on Taiwan's Gross Domestic Product per capita, the strategy based on immunohistochemistry as a genetic test followed by BRAF mutation testing was considered to be highly cost-effective relative to no screening. Our probabilistic sensitivity analysis results also suggest that the strategy has a probability of 0.939 of being cost-effective relative to no screening based on the commonly used threshold of $50,000 to determine cost-effectiveness. To the best of our knowledge, this is the first cost-effectiveness analysis for evaluating different genetic testing strategies for LS in Taiwan. The results will be informative for the government when considering offering screening for LS in patients newly diagnosed with CRC.Entities:
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Year: 2016 PMID: 27482709 PMCID: PMC4970721 DOI: 10.1371/journal.pone.0160599
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Flowchart for the four strategies evaluated in this study.
The numbers of mutations in the MMR genes reported by studies based on the Chinese population.
| Sample size | |||||
|---|---|---|---|---|---|
| Ni [ | 52 | 22 | NA | NA | 153 |
| Sheng et al. [ | 8 | 4 | 0 | NA | 21 |
| Yan et al. [ | NA | NA | 4 | NA | 39 |
| Sheng et al. [ | NA | NA | NA | 1 | 26 |
| Weighted proportion | 58% | 25% | 11% | 6% |
Numbers of LS probands and relatives and costs for the four strategies.
| Strategy 1 | Strategy 2 | Strategy 3 | Strategy 4 | |
|---|---|---|---|---|
| No. of LS probands | 176 | 177 | 184 | 259 |
| No. of relatives tested for LS | 366 | 369 | 384 | 539 |
| No. of relatives with LS mutations detected | 177 | 178 | 186 | 215 |
| Cost of detecting LS in newly diagnosed patients with CRC | $1,498,891 | $1,731,350 | $5,364,843 | $37,365,594 |
| Cost of detecting LS in relatives | $44,121 | $45,210 | $56,703 | $65,356 |
| Cost of surveillance and treatment for CRC for relatives with LS mutations | $2,716,955 | $2,712,672 | $2,909,862 | $2,666,703 |
| Total costs | $4,259,967 | $4,489,232 | $8,331,408 | $40,097,654 |
Cost-effectiveness analysis results based on ICER among different strategies.
| Strategy | Discounted LYs per person | Discounted cost per person | Incremental costs per LY gained (relative to Referent strategy) | Incremental costs per LY gained (relative to the previous strategy) |
|---|---|---|---|---|
| Referent | 21.551 | $4,032 | ||
| 1 | 21.834 | $5,735 | $6,025 | $6,025 |
| 2 | 21.835 | $6,044 | $7,088 | $260,824 |
| 3 | 21.852 | $11,217 | $23,872 | $302,129 |
| 4 | 21.895 | $53,985 | $145,110 | $988,217 |
Fig 2Cost-effectiveness acceptability curves for Strategies 1–4 relative to the Referent strategy.
Fig 3One-way sensitivity analysis results for Strategy 1.
The blue and green bars represent the changes of ICER using upper and lower bound values, respectively, in S1 Table.