Recent Advances and Future Directions of Diagnostic and Prognostic Prediction Models in Ovarian Cancer

Ovarian cancer has one of the highest mortality rates among gynecological malignancies. This disease has a low early detection rate, a high postoperative recurrence rate, and a 5-year survival rate of only 40%. Hence, there is an urgent need to improve the early diagnosis and prognosis of ovarian cancer. Prediction models can effectively estimate the risk of disease occurrence, as well as its prognosis. Recently, many studies have established multiple ovarian cancer prediction models based on different regions and populations. These models can improve the detection rate and optimize the prognosis management to a certain extent. Herein, the construction principle of the ovarian cancer risk prediction model and its validation are summarized; furthermore, comprehensive reviews and comparisons of the different types of these models are made. Therefore, our review may be of great significance for the whole course of ovarian cancer management.