Ovarian cancer (OC) is the most lethal gynecological cancer in the developed world. Most cases are diagnosed at late stage III-IV with a very low 5-year overall survival rate. Several studies revealed an elevated risk of OC in users of hormone treatment (HT) compared with non-users. The extended duration of HT is a statistically significant risk factor. Carbohydrate antigen or cancer antigen 125 (CA-125) remains the best screening tool for OC; however, its value is limited due to low specificity, leading to unnecessary interventions, surgeries, and psychological harm. Additionally, the variability of ultrasound interpretation highlights the urgent need to develop a univariate index with higher sensitivity and specificity for early diagnosis of OC in women under HT. Herein we critically review the limitations of biomarkers for the detection of OC aiming to suggest an accurate and cost-effective diagnostic ratio that eliminates the impact of body mass index, age, HT, smoking, and benign ovarian diseases on measurements. Numerous studies combine biomarkers such as CA-125, human epididymis protein 4, and thymidine kinase 1 into diagnostic algorithms. Data suggest that the expression of estrogen receptors may have diagnostic and prognostic value, as the estrogen receptor α (ERα):estrogen receptor β (ERβ) ratio is significantly higher in OC than in normal tissue due to ERβ downregulation. A high positive correlation between expression of CA-125 and carbohydrate antigen or cancer antigen 72 − 4 (CA72-4) with ERα and ERβ, respectively, poses that a novel ratio CA-125:CA72-4 could be nodal for monitoring post-menopausal women under HT.