Ovarian cancer is the most lethal gynecological malignancy, posing a significant threat to women's health. In 2020, approximately 314,000 new cases and 207,000 deaths worldwide were attributed to this disease [1]. One of the primary reasons for its high mortality rate is the insidious onset, which makes early diagnosis challenging. Therefore, identifying high-risk groups for ovarian cancer is crucial for preventing the disease and ensuring early diagnosis, which can significantly reduce the burden of this illness.

Given the hereditary predisposition of ovarian cancer, approximately 20 % of cases are attributable to hereditary factors [2,3]. Consequently, first-degree relatives of ovarian cancer patients represent a critical segment of the population at increased risk for this malignancy. The relative risk of ovarian cancer development among these first-degree relatives is estimated to be 2.0 to 4.0 times greater compared to the general population [4,5]. Following the identification of BRCA1/2 in the 1990s, deleterious mutations in other genes such as BRIP1, RAD51C, RAD51D, and PALB2 have been recognized, significantly elevating ovarian cancer risk [6]. However, approximately 50 % of familial ovarian cancers are still not explained by single gene variants, suggesting the involvement of other genetic or nongenetic factors [7]. Relying solely on genetic testing may miss high-risk familial ovarian cancer cases. Therefore, a more comprehensive method to identify these high-risk individuals is essential for early screening and intervention, which is vital to reducing ovarian cancer incidence and mortality.

Several tools and models have been developed to predict the risk of ovarian cancer, utilizing various methodologies and data sources [[8], [9], [10]]. However, their discriminative ability remains limited, and they often require genetic, lifestyle, hormonal, and numerous clinical information, which poses challenges for their application in primary healthcare settings [11]. Given that China accounts for a notable one-fifth of new ovarian cancer cases worldwide, and most existing prediction models are primarily based on European and American population cohorts, there is an urgent need to develop prediction tools specifically tailored to the Chinese population [12,13].

We established a bidirectional multicenter cohort of hereditary ovarian cancer in China (NCT06564428). In this study, we examined tumor incidence patterns within the pedigrees of ovarian cancer patients in the Chinese population. Based on family history and fundamental clinical characteristics, we constructed and validated an evaluation tool to assess the risk of ovarian cancer among first-degree relatives.