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Saliva microRNA signature to diagnose endometriosis: A cost-effectiveness evaluation of the Endotest?

BJOG: An International Journal of Obstetrics & Gynaecology(2023)

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摘要
ObjectiveTo evaluate a saliva diagnostic test (Endotest (R)) for endometriosis compared with the conventional algorithm. DesignA cost-effectiveness analysis with a decision-tree model based on literature data. SettingFrance. PopulationWomen with chronic pelvic pain. MethodsStrategy I is the French algorithm, representing the comparator. For strategy II, all patients have an Endotest (R). For strategy III, patients undergo ultrasonography to detect endometrioma and patients with no endometrioma detected have an Endotest (R). For strategy IV, patients with no endometrioma detected on ultrasonography undergo pelvic magnetic resonance imaging (MRI) to detect endometrioma and/or deep endometriosis. An Endotest (R) is then performed for patients with a negative result on MRI. Main outcomes measuresCosts and accuracy rates and incremental cost-effectiveness ratios (ICERs). Three analyses were performed with an Endotest (R) priced at euro500, euro750, and euro1000. Probabilistic sensitivity analysis was conducted with Monte Carlo simulations. ResultsWith an Endotest (R) priced at euro750, the cost per correctly diagnosed case was euro1542, euro990, euro919 and euro1000, respectively, for strategies I, II, III and IV. Strategy I was dominated by all other strategies. Strategies IV, III and II were, respectively, preferred for a willingness-to-pay threshold below euro473, between euro473 and euro4670, and beyond euro4670 per correctly diagnosed case. At a price of euro500 per Endotest (R), strategy I was dominated by all other strategies. At euro1000, the ICERs of strategies II and III were euro724 and euro387 per correctly diagnosed case, respectively, compared with strategy I. ConclusionThe present study demonstrates the value of the Endotest (R) from an economic perspective.
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关键词
cost-effectiveness analysis,diagnosis,endometriosis,health economics,saliva miRNA signature
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