Menopausal Status and Ovarian Cancer Risk

Back to overview

Ovarian Cancer Risk Factors

Over the past few years, efforts have been implemented to identify risk factors associated with epithelial ovarian cancer (EOC).

According to the American Cancer Society, women with a family history of ovarian cancer (OC) are at a higher risk of developing the disease. Specifically, women with a first-degree relative with ovarian cancer have an approximately three times higher risk compared to women with no affected relatives1. A high proportion of hereditary cancers include mutations in the BRCA1 (40-50% risk of developing OC by the age of 70) and BRCA2 genes (10-20% risk)2.

Both BRCA1 and BRCA2 genes encode for tumor suppressive proteins, that help repair damaged DNA, and therefore play a key role in ensuring cell genetic stability3. Therefore inheriting one of these mutations may increase the chances of developing breast, ovarian and other cancers4. Other nongenetic risk factors for the onset of EOC are associated with aging, weight or obesity, and female reproductive history.

The risk of ovarian cancer increases with age, with a predominance of disease occurrence/diagnosis in the 5th and 6th decades of life5. Also, obesity (BMI ≥ 30) has been linked to a higher risk of ovarian cancer, but not necessarily the most aggressive types, such as high-grade serous cancer6,7.

As for reproductive history, many epidemiological studies have consistently reported a strong link between ovarian cancer onset and important reproductive characteristics, that can either reduce or increase the risk of ovarian cancer8,9.

Specifically, factors that appear to reduce the risk of ovarian cancer are: multiple full-term pregnancies (~50% risk reduction in multiparous women)10, nursing or breastfeeding (~8% decrease for every 5-month increase)11, medical sterilization, such as tubal ligation and salpingectomy (13 to >50% risk reduction in a nationwide study from Denmark)12, and years of oral contraceptive use (a study from 2008 showed that the overall relative risk of ovarian cancer decreased by 20% for each 5 years of oral contraceptive use)13.

Alternatively, risk factors that are known to increase the risk of ovarian cancer include early age at menarche14, late age at menopause5, Polycystic ovarian syndrome (PCOS)15, endometriosis16 and the use of hormone replacement therapy (HRT) in menopause, which has been related to increased risk in ovarian cancer by 50% for 5 years of use17.

Taken together, although the likelihood to develop ovarian cancer may increase when women have one or more of the above mentioned risk factors, the most significant factors are age and menopausal status11. It has been shown that ovarian cancer affects only 10% to 15% of premenopausal women18, and that the median age for diagnosis of epithelial ovarian cancer, the most common histologic type, is between 60 and 65 years19.

Menopause stages, and hormonal changes

Menopause is the physiological, natural transition, experienced each year by 1.5 million women, and it often includes vasomotor symptoms, vaginal dryness, decreased libido, insomnia, fatigue and joint pain20. During this transition, the ovaries become smaller and stop producing two key hormones, progesterone and estrogen that regulate the menstrual cycle, leading to fertility decline.

During menopause, the number of ovarian follicles decline, which results in

  • ovaries becoming less responsive to the Luteinizing Hormone (LH) and Follicle-Stimulating Hormone (FSH) (which are therefore no longer able to regulate estrogen, progesterone and testosterone levels).
  • a reduction in anti-Mullerian hormone (AMH) and early follicular inhibin B levels.

Menopause can be divided into three specific stages:

Perimenopause: entailing a 3 to 5-year period before the onset of menopause, where the menstrual cycle becomes irregular. It typically begins towards the end of the 4th decade of life. During this time, women can still be fertile

Menopause: it affects women with an average age of 51 in western countries11, and is characterized by the lack of menses for 12 straight months, without experiencing other causes such as pregnancy, breastfeeding or the onset of diseases

Postmenopause: beginning 1 year after the last menstrual cycle and characterized by a decrease in estrogen levels that might lead to an increased risk of developing heart diseases, osteopenia and osteoporosis21,22

During the perimenopausal period and for up to 2 years after menopause, the reduction in Inhibin B levels results in an increase in FSH levels, which regulates estradiol (E2) concentrations. Thus, in postmenopause, FSH levels are high, E2 levels decline23, while Inhibin B and AMH are, at this point, undetectable18. This entire transition from perimenopause to postmenopause can take up to 3 years.

Hormonal changes during menopause and their effect on carcinogenesis

These inevitable changes in hormone levels during this transition, including the natural decline of estrogen levels during menopause, can significantly affect women’s health.

Although estrogen levels are reduced during menopause, this hormone appears to play an important role in breast and ovarian carcinogenesis. The mechanistic details are still unclear, especially considering that ovarian carcinogenesis is predominantly seen in menopausal women, when estrogen levels are lower5. Estrogen increases ovarian tumor cell proliferation by interacting with the estrogen receptor ERα, while its interaction with ERβ is known to have an antiproliferative effect5. In the breast, fallopian tube and ovary, the expression levels of these receptors may contribute to tumorigenesis, and therefore the gradual loss of ERβ expression that occurs during the progression of ovarian cancer24. This postulated to be an important component of tumorigenesis25.

Estrogen is also known to enhance vascular supply to the tumor, and also to promote an immunosuppressive environment26,27.

Progesterone and progestins, on the other hand, are known to play a protective role against the onset of ovarian cancer. Specifically, reduced levels of progesterone due to aging and infertility have been linked to an increased risk of ovarian cancer28. In contrast, increased progesterone levels during pregnancy are known to be protective, and thus reduce the risk of developing ovarian cancer29. Progesterone is also known to promote apoptosis mediated by induction of TGF-β and cell cycle arrest in G0/G130.
Additionally, high levels of gonadotropins (FSH and LH) during ovulation, and the loss of gonadal feedback that occurs during menopause, are all important contributing risk factors for the onset of ovarian cancer31.

Trends in diagnostic approaches: the development of algorithms

In the past decade, major efforts have been made to improve the diagnosis of pelvic masses.

The current approach for the diagnosis of ovarian mass is based on laparoscopy or laparotomy, pelvic examination, transvaginal ultrasonography, and serum biomarkers. Currently, Cancer antigen 125 (CA125) and Human epididymis secretory protein E4 (HE4) are the only two markers available in the US for monitoring disease progression and detecting disease recurrence.

CA125 is the most widely used tumor marker in ovarian cancer, but presents some limitations in terms of sensitivity and specificity that negatively affect its performance as a useful biomarker for ovarian cancer32,33.

HE4, on the other hand, appears to be superior to CA125 for diagnostic accuracy in distinguishing ovarian cancer from benign gynecological diseases34, and has been shown to better identify early-stage EOCs 35.

Interestingly, HE4 levels have been shown to increase in post-menopausal women36, and in older women, reaching their highest levels in the 8th and 9th decade of life33.
However, over the past few years, the introduction of multimarker tests and algorithms (that combine the use of biomarker(s) panels, age, menopausal status and imagining into a single index), have dramatically improved the performance of ovarian cancer diagnosis, compared to the use of single biomarkers37.

Biomarker-based algorithms that include menopausal status

The Risk of Malignancy Index (RMI) was developed by combining ultrasound scan findings (expressed as a score of 0, 1 or 3), menopausal status (1 if premenopausal and 3 if postmenopausal), and serum CA125 levels (U/ml)38. Using an RMI threshold of 200, the sensitivity was 85% and the specificity was 97%39. A study from 2013 that aimed to test the reliability of RMI to differentiate benign from malignant adnexal masses, found that RMI was reliable in 84.6% of all patients; in 77% of premenopausal patients and in 81.1% of postmenopausal patients. Notably, in the overall population, RMI had a sensitivity of 83.81%; and a specificity of 77.24%, whereas in postmenopausal women, the sensitivity and specificity were respectively 83.78% and 68.18%40.

OVA1 is a multivariate index assay calculated by combining data from imaging, menopausal status, and 5 biomarkers including CA125, ApoA1, TTR, Tf and β2-macroglobulin. This algorithm helps assess malignancy risk of an ovarian pelvic mass upon surgery, thus allowing an appropriate referral to a gynecologist or to a gynecologic oncologist for initial surgery41. OVA1 provided 94.8% sensitivity at 32.7% specificity in postmenopausal women (NPV= 90.0%) and 86.7% sensitivity at 51.6% specificity for premenopausal women (NPV= 94.2%)42,43.

Finally, the Risk of Ovarian Malignancy Algorithm (ROMA), combines serum levels of CA125 and HE4 along with menopausal status, to classify patients with an ovarian pelvic mass into a high or low risk group for finding malignancy upon surgery44. In premenopausal women, the ROMA score provided 75.0% sensitivity and 74.5% specificity (NPV= 98.2%), while in postmenopausal women, the ROMA score had a sensitivity and a specificity of 84.8% 76.8% respectively (NPV= 97.0%)45.

The ROMA score had a sensitivity of 94% compared to a sensitivity of 84.6% for RMI at a set specificity of 75% in distinguishing benign status from EOC, and 85% sensitivity to identify early stage I and II disease44, outperforming the RMI (that detected 65% of cases)41.
A head to head comparison of ROMA and OVA1 in post-menopausal women showed comparable sensitivities, OVA1 having non-significant greater diagnostic sensitivity (96.1% vs 88.5%) and ROMA having significantly greater diagnostic specificity (76.0% vs 42.0%)46. Thus, here we will focus on the performance of ROMA in post-menopausal populations.

Differences in biomarker performance in postmenopausal women with ovarian cancer

In recent years, efforts have been made to validate the differences in biomarker performance to differentiate between benign and malignant processes based on menopausal status.

Table 1: Performance of CA 125, HE4, and ROMA in the overall population (pre and post menopause combined)

Table 2 Performance of CA 125_ HE4_ROMA in the postmenopausal population.pdf

A study published in 2011 revealed that ROMA had a sensitivity for EOC of 93.8%, a specificity of 74.9% and NPV of 99.0% in the overall population (pre- and postmenopausal combined) (Table 1). When assessing the postmenopausal group alone, the sensitivity was 92.3% and the specificity 76.0%44 (Table 2).

A meta-analysis from 2014 indicated that in the overall population, HE4, CA125 and ROMA had similar performance in diagnosing ovarian cancer. In this population ROMA appeared to be more sensitive (85.3%) than HE4 and CA125 (76.3% and 79.2%) while HE4 yielded the highest specificity at 93.6% (Table 1).

When stratifying the analysis based on menopausal status, HE4 had similar diagnostic value both in premenopausal and postmenopausal women whereas CA125 and ROMA performed significantly better in the postmenopausal subgroup than in the premenopausal one (Table 2)47.

Interestingly, in recent years many studies have suggested that ROMA performs better than CA125 and HE4 alone in differentiating between benign and malignant masses in the postmenopausal population. Specifically, a meta-analysis from 2016, highlighted the superiority of the ROMA score in the postmenopausal population (AUC ROMA = 0.917, CA125= 0.894 and HE4= 0.873) (Table 2), while indicating similar performance of ROMA to CA125 and HE4 in the premenopausal population (AUC= 0.844, 0.822 and 0.843 respectively)48.

In the same year, Wei and colleagues also found that in the postmenopausal subgroup, ROMA once again outperformed both HE4 and CA125 scores, showing higher sensitivity (91.89%), PPV (97.14%) and NPV (91.43%), while sharing the same specificity as HE4 (96.97%)49 (Table 2).
Another study from 2019 also found that in the postmenopausal patient group ROMA had the highest AUC value of 0.935, and it was significantly higher than CA 125 (0.889, P = 0.0231)) (Table 2)50.

In contrast to the previous studies, in 2019 Choi and colleagues found that the ROMA score was superior to CA125 in differentiating EOC in premenopausal women with adnexal mass, while performing similarly to CA125 in the postmenopausal group. In postmenopausal women CA125 overall performance was comparable to ROMA (Sensitivity: 0.821 vs 0.829, P=0.774; Specificity: 0.949 vs 0.974, P=0.500; NPV: 0.622 vs 0.639, P=0.376; and Accuracy: 0.852 vs 0.864, P=0.285 respectively) (Table 2)51.

Taken together these studies show ROMA can be a useful tool in the management of ovarian cancer especially in the postmenopausal population.

Conclusions: the importance of including menopausal status in the management of EOC

The most significant factors influencing the risk of developing ovarian cancer are age and menopausal status11.

Specifically, the risk of developing ovarian cancer significantly increases in peri-menopausal and in immediate postmenopausal stages, and continues to rise as the ovary ages52. This makes the need for understanding how biomarker expression changes as women age critical in aiding in the diagnosis of ovarian cancer.
As seen in the studies presented, the integration of menopausal status in the development of algorithms can benefit performance of diagnostics for ovarian cancer.


1. Stratton, J. F., Pharoah, P., Smith, S. K., Easton, D. & Ponder, B. A. J. A systematic review and meta-analysis of family history and risk of ovarian cancer. BJOG An Int. J. Obstet. Gynaecol. 105, 493–499 (1998).
2. Boyd, J. Specific Keynote: Hereditary Ovarian Cancer: What We Know. Gynecol. Oncol. 88, S8–S10 (2003).
3. NIH. What are BRCA1 and BRCA2?
4. CDC. The BRCA1 and BRCA2 Genes.….
5. Gharwan, H., Bunch, K. P. & Annunziata, C. M. The role of reproductive hormones in epithelial ovarian carcinogenesis. Endocr. Relat. Cancer 22, R339–R393 (2015).
6. Leitzmann, M. F. et al. Body mass index and risk of ovarian cancer. Cancer 115, 812–822 (2009).
7. American Cancer Society. Ovarian Cancer Risk Factors. causes-risks-prevention/risk-factors.html.
8. La Vecchia, C. Ovarian cancer: Epidemiology and risk factors. Eur. J. Cancer Prev. 26, 55–62 (2017).
9. Webb, P. M. & Jordan, S. J. Epidemiology of epithelial ovarian cancer. Best Pract. Res. Clin. Obstet. Gynaecol. 41, 3–14 (2017).
10. Chiaffarino, F. et al. Reproductive and hormonal factors and ovarian cancer. Ann. Oncol. Off. J. Eur. Soc. Med. Oncol. 12, 337–341 (2001).
11. Rampersad, A. C., Wang, Y., Smith, E. R. & Xu, X. Menopause and ovarian cancer risk : mechanisms and experimental support. 2, 14–23 (2015).
12. Madsen, C., Baandrup, L., Dehlendorff, C. & Kjaer, S. K. Tubal ligation and salpingectomy and the risk of epithelial ovarian cancer and borderline ovarian tumors: a nationwide case-control study. Acta Obstet. Gynecol. Scand. 94, 86–94 (2015).
13. Beral, V. et al. Ovarian cancer and oral contraceptives: collaborative reanalysis of data from 45 epidemiological studies including 23 257 women with ovarian cancer and 87 303 controls. Lancet 371, 303–314 (2008).
14. Gong, T.-T., Wu, Q.-J., Vogtmann, E., Lin, B. & Wang, Y.-L. Age at menarche and risk of ovarian cancer: A meta-analysis of epidemiological studies. Int. J. Cancer 132, 2894–2900 (2013).
15. Schildkraut, J. M., Schwingl, P. J., Bastos, E., Evanoff, A. & Hughes, C. Epithelial ovarian cancer risk among women with polycystic ovary syndrome. Obstet. Gynecol. 88, 554–559 (1996).
16. Brinton, L. A. et al. Ovarian cancer risk associated with varying causes of infertility. Fertil. Steril. 82, 405–414 (2004).
17. La Vecchia, C. Estrogen-progestogen replacement therapy and ovarian cancer: an update. Eur. J. cancer Prev. Off. J. Eur. Cancer Prev. Organ. 15, 490–492 (2006).
18. Ranaee, M., Yazdani, S., Modarres, S. R. & Rajabi-Moghaddam, M. Two cases of clear cell ovarian cancer in young patients. Casp. J. Intern. Med. 7, 228–231 (2016).
19. Berek, J. & Bast, R. Epithelial Ovarian Cancer. (2003).
20. Nanette Santoro, MD, C. Neill Epperson, MD, and Sarah B. Mathews, M. Menopausal Symptoms and Their Management. Endocrinol Metab Clin North Am 44, 497–515 (2015).
21. Ji, M.-X. & Yu, Q. Primary osteoporosis in postmenopausal women. Chronic Dis. Transl. Med. 1, 9– 13 (2015).
22. Sherman, S. Defining the menopausal transition. Am. J. Med. 118, 3–7 (2005).
23. Potter, B., Schrager, S., Dalby, J., Torell, E. & Hampton, A. Menopause. Prim. Care - Clin. Off. Pract. 45, 625–641 (2018).
24. Lazennec, G. Estrogen receptor beta, a possible tumor suppressor involved in ovarian carcinogenesis. Cancer Lett. 231, 151–157 (2006).
25. Schüler-Toprak, S., Weber, F., Skrzypczak, M., Ortmann, O. & Treeck, O. Estrogen receptor β is associated with expression of cancer associated genes and survival in ovarian cancer. BMC Cancer 18, 981 (2018).
26. Rothenberger, N. J., Somasundaram, A. & Stabile, L. P. The Role of the Estrogen Pathway in the Tumor Microenvironment. Int. J. Mol. Sci. 19, 611 (2018).
27. Filardo, E. J. A role for G-protein coupled estrogen receptor (GPER) in estrogen-induced carcinogenesis: Dysregulated glandular homeostasis, survival and metastasis. J. Steroid Biochem. Mol. Biol. 176, 38–48 (2018).
28. Edmondson, R. J. & Monaghan, J. M. The epidemiology of ovarian cancer. Int. J. Gynecol. cancer Off. J. Int. Gynecol. Cancer Soc. 11, 423–429 (2001).
29. Diep CH, Daniel AR, Mauro LJ, Knutson TP, and L. C. Progesterone action in breast, uterine, and ovarian cancers. 54, R31–R53 (2015).
30. Temkin, S. M., Mallen, A., Bellavance, E., Rubinsak, L. & Wenham, R. M. The role of menopausal hormone therapy in women with or at risk of ovarian and breast cancers: Misconceptions and current directions. Cancer 125, 499–514 (2019).
31. Feng, D. et al. Gonadotropins promote human ovarian cancer cell migration and invasion via a cyclooxygenase 2-dependent pathway. Oncol. Rep. 38, 1091–1098 (2017).
32. Kumarasamy, C. et al. Diagnostic and prognostic role of HE4 expression in multiple carcinomas. Medicine (Baltimore). 98, e15336 (2019).
33. Nowak, M., Janas, Ł., Stachowiak, G., Stetkiewicz, T. & Wilczyński, J. R. Current clinical application of serum biomarkers to detect ovarian cancer. Prz. Menopauzalny 14, 254–259 (2015).
34. Zhen, S., Bian, L.-H., Chang, L.-L. & Gao, X. Comparison of serum human epididymis protein 4 and carbohydrate antigen 125 as markers in ovarian cancer: A meta-analysis. Mol. Clin. Oncol. 2, 559– 566 (2014).
35. Nguyen, L. et al. Biomarkers for early detection of ovarian cancer. Women’s Heal. 9, 171–187 (2013).
36. Cheng, H.-Y. et al. Age and menopausal status are important factors influencing the serum human epididymis secretory protein 4 level. Chin. Med. J. (Engl). 0, 1 (2020).
37. Whitwell, H. J. et al. Improved early detection of ovarian cancer using longitudinal multimarker models. Br. J. Cancer 122, 847–856 (2020).
38. Jacobs, I. et al. A risk of malignancy index incorporating CA 125, ultrasound and menopausal status for the accurate preoperative diagnosis of ovarian cancer. Br. J. Obstet. Gynaecol. 97, 922–929 (1990).
39. Dochez, V. et al. Biomarkers and algorithms for diagnosis of ovarian cancer: CA125, HE4, RMI and ROMA, a review. J. Ovarian Res. 12, 1–9 (2019).
40. Terzic, M. et al. Risk of malignancy index validity assessment in premenopausal and postmenopausal women with adnexal tumors. Taiwan. J. Obstet. Gynecol. 52, 253–257 (2013).
41. Wei-Lei Yang and Robert C. Bast Jr., Z. L. The role of Biomarkers in the Management of Epithelial Ovarian Cancer. Expert Rev Mol Diagn. 17, 577–591 (2017).
42. Ueland, F. R. et al. Effectiveness of a multivariate index assay in the preoperative assessment of ovarian tumors. Obstet. Gynecol. 117, 1289–1297 (2011).
43. Bristow, R. E. et al. Ovarian malignancy risk stratification of the adnexal mass using a multivariate index assay. Gynecol. Oncol. 128, 252–259 (2013).
44. Moore, R. et al. Evaluation of the Diagnostic Accuracy of the Risk of Ovarian Malignancy Algorithm in Women With a Pelvic Mass. Obs. Gynecol 118, 280–288 (2011).
45. ROMA (Risk of Ovarian Malignancy Algorithm) – 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY. k103358. vol. 510 1–25.
46. Grenache, D. G., Heichman, K. A., Werner, T. L. & Vucetic, Z. Clinical performance of two multimarker blood tests for predicting malignancy in women with an adnexal mass. Clin. Chim. Acta 438, 358–363 (2015).
47. Wang, J. et al. Diagnostic accuracy of serum HE4, CA125 and ROMA in patients with ovarian cancer: a meta-analysis. Tumour Biol. 35, 6127–38 (2014).
48. Dayyani, F. et al. Diagnostic Performance of Risk of Ovarian Malignancy Algorithm Against CA125 and HE4 in Connection With Ovarian Cancer: A Meta-analysis. Int. J. Gynecol. Cancer (2016)
49. Wei, S., Li, H. & Zhang, B. The diagnostic value of serum HE4 and CA-125 and ROMA index in ovarian cancer. Biomed. Reports 5, 41–44 (2016).
50. Kim, B. et al. Diagnostic performance of CA 125, HE4, and risk of Ovarian Malignancy Algorithm for ovarian cancer. J. Clin. Lab. Anal. 33, 1–8 (2019).
51. Choi, H. et al. Comparison of CA 125 alone and risk of ovarian malignancy algorithm ( ROMA ) in patients with adnexal mass : A multicenter study. Curr. Probl. Cancer 100508 (2019) doi:10.1016/j.currproblcancer.2019.100508.
52. Yancik, R. Ovarian cancer: Age contrasts in incidence, histology, disease stage at diagnosis, and mortality. Crit. Rev. Oncol. Hematol. 71, 517–523 (1993).

FDI-600 11/20