Background: Identifying Lynch syndrome (LS) in patients with colorectal cancer (CRC) and monitoring their relatives can increase the life expectancy of these patients. Objectives: The aim of this study was to analyze the cost-effectiveness of 5 molecular testing strategies to screen LS among patients with newly diagnosed CRC and to conduct preventive surveillance in their first-degree relatives. Methods: A decision tree model was designed to identify the number of LS mutations and the related costs in the CRC patients. Five strategies were modeled, i.e., Amsterdam II criteria, microsatellite instability (MSI) testing, immunohistochemistry (IHC), and next-generation sequencing (NGS). A Marko model was also used to estimate the long-term outcome of monitoring (including colonoscopy and taking aspirin) among relatives of those patients with CRC who carried LS. Results: All strategies were cost-effective compared with no testing condition. The 2 most cost-effective strategies were strategy 2 (IHC testing followed by NGS testing) and strategy 4 (MSI testing followed by NGS testing), with the ICER of 4,604$ and 4,748$ per quality-adjusted life year (QALY), respectively. Based on one-way sensitivity analysis of IHC sensitivity, the Cost of colonoscopy, MSI sensitivity, and the number of families who inherited LS had the most effect on the results. Conclusions: The findings suggested that from an Iranian health care system perspective, IHC testing followed by NGS testing could be regarded as the most cost-effective strategy compared to the other strategies. These results can be useful in offering to screen LS in newly diagnosed CRC patients.

morphology and another for proposed referral pathway using flow cytometry were developed in Microsoft Excel. Budget impact analysis was conducted comparing cost outcomes of the two decision trees. Due to the lack of publicly available data, local oncology and pathology experts were interviewed for proportion of patients going through the referral pathway, diagnosis accuracy of morphology (78%) and flow cytometry (95%), treatment response rates (60-80%), test cost (morphology: Rp450,000; flow cytometry: Rp933,300) and treatment cost (acute myeloid leukemia: Rp100 million; acute lymphocytic leukemia: Rp60 million). Global peerreviewed data were used for classification accuracy of both tests. Outcomes estimated and compared include patients accurately diagnosed, average time to diagnosis, average prognosis and costs. Results: With the adoption of flow cytometry, for 100,000 symptomatic patients, the model estimated 25,000 more patients receiving accurate diagnosis; average time to diagnosis can be shortened by one week and average probability of death can be reduced by 9%. Total diagnostics and treatment cost is estimated to be Rp25 billion lower. Rp17 million can be avoided from unnecessary treatment due to morphological inaccuracies. On average, additional Rp453,000 may be required for each patient's diagnosis but Rp439,000 can be saved from treatment. Conclusions: With flow cytometry, more patients can be diagnosed accurately and treated appropriately earlier, thus improving acute leukemia survival. Cost savings can be expected due to reduction of unnecessary treatment.