Table 2.

Characteristics of reviewed articles

Author (Year)	Country (country income category)	Population description	Treatment strategy	Intervention VS comparison	Study design	Perspective	Time horizon	Cascade Testing	discount rate	Type of uncertainty analysis
Genetic testing for breast cancer only
Lim et al. (2018) [30]	Malaysia (UMIC)	Hypothetical cohort of 1000 patients who aged 40 years old with newly diagnosed as early stage (Stage1/2) unilateral BC.	risk-reducing mastectomy (RRM), risk-reducing bilateral salpingo-oophorectomy (RRBSO), tamoxifen chemoprevention, combination of these or neither	BRCA testing VS No testing, performed Routine clinical surveillance only	Decision tree and Markov Model (1 year length of cycle)	payer perspective	Lifetime	No	3% for costs and health outcomes	One way deterministic sensitivity analyses & probabilistic sensitivity analysis
Sun et al. (2022) [32]	China (UMIC)	All BC patients VS Family History/clinical-criteria-based testing	Prophylactic mastectomy and salpingo-oophorectomy	a)BRCA1/BRCA2/PALB2 testing for all BC patients b)BRCA1/BRCA2-testing for BC patients with FH/clinical criteria c) No testing	Microsimulation model at the individual level	Societal and Payer perspectives	Lifetime	Yes	3% for costs and health outcomes	One way deterministic sensitivity analyses & probabilistic sensitivity analysis
Wu et al. (2023) [29]	China (UMIC)	Patients with TNBC and hormone-receptor (HR)-positive and HER2-negative BC	Standard treatment with Olaparib and RRO as an adjuvant treatment	a) Universal gBRCAtesting for all TNBC and HR-positive HER2-negative BC patients b) No gBRCA testing c) Selected gBRCA testing	A decision tree analytic model based on transitional Markov Chain (1 year length of cycle)	Payer perspectives	20 years	No	3% for costs and health outcomes	One way deterministic sensitivity analyses & probabilistic sensitivity analysis
Genetic testing for breast cancer and ovarian cancer
Manchanda et al. (2020) [31]	China (UMIC) & Brazil (UMIC) & India (LMIC)	Population-based screening for all women ≥ 30 years old.	RRSO, MMRI/mammography screening, chemoprevention with SERM, RRM	Population-based BRCA1/BRCA2 testing VS clinical-criteria/FH-based testing	Markov Model	Societal and Payer perspectives	Lifetime (China = 48 cycles; Brazil = 49 cycles; India = 38 cycles)	No	3% for costs and health outcomes	One way deterministic sensitivity analyses & probabilistic sensitivity analysis
Simoes Correa-Galendi et al. (2021) [33]	Brazil (UMIC)	Healthy women aged 30 years with personal or family history of BRCA-associated cancer and meeting the clinical criteria for genetic testing according to the National Comprehensive Cancer Network (NCCN).	Intensified surveillance, risk-reducing bilateral mastectomy and bilateral salpingo-oophorectomy	BRCA1/BRCA2 testing and counselling VS no genetic testing and counselling	Markov Model	Payer perspectives	70 years	No	5% for costs and utilities	One way deterministic sensitivity analyses & probabilistic sensitivity analysis
Lourencao et al. (2022) [34]	Brazil (UMIC)	Healthy women aged 30 years with personal or family history of BRCA-associated cancer and meeting the clinical criteria for genetic testing according to the National Comprehensive Cancer Network (NCCN).	Intensified surveillance, risk-reducing bilateral mastectomy, bilateral salpingo-oophorectomy, both bilateral mastectomy and bilateral salpingo-oophorectomy	BRCA1/BRCA2 testing and counselling and with surgical/non-surgical preventive options VS No genetic testing and counselling (with standard care)	Markov Model	Payer perspectives	70 years	Yes	5% for costs and utilities	Deterministic sensitivity analyses & probabilistic sensitivity analysis