Screening for Ovarian Cancer: Helpful or Harmful?

By Molly A. Brewer, DVM, MD, MS
Professor and Chair, Department of Obstetrics and Gynecology
Division of Gynecologic Oncology
University of Connecticut Health Center, Farmingham

SOURCE: Jacobs IJ, Menon U, Ryan A, et al. Ovarian cancer screening and mortality in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS): A randomised controlled trial. Lancet 2016; 387(10022):945-956.

Ovarian cancer has the highest mortality of any of the gynecologic cancers. Due to the poor prognosis associated with this disease, researchers have been searching for 50 years for an early detection tool. Most women diagnosed with high-grade epithelial ovarian cancer will be diagnosed with Stage III or IV disease with a mortality of at least 70% over five years. The mortality has not changed appreciably in 50 years, despite multiple studies testing treatment combinations of surgery, chemotherapy, and newer targeted therapies. The first screening tool, CA125, a glycoprotein that is secreted by ovarian cancer cells and can be detected in serum, initially was described in 1983 by Robert Bast, MD, as a tool to monitor response to treatment for ovarian cancer and not as a screening tool for the detection of early cancer.¹ Soon physicians extrapolated the use of serum CA125 for screening, and they paired this with pelvic ultrasound. However, in 1994, a National Institutes of Health consensus statement cautioned against routine use of CA125 and pelvic ultrasound in the general population and recommended using these tests for screening only in high-risk women.² Despite the lack of evidence that screening saves lives or alters disease prognosis in low-risk women, there have been multiple studies evaluating serum markers with or without ultrasound in women with a pelvic mass,³ premenopausal women,⁴ and postmenopausal women.^5-7 Given that the baseline lifetime risk for a low-risk woman to develop ovarian cancer is 1.5-1.7%, the positive predictive value (the probability that a positive test could predict the presence of disease) of any screening test will be low. In the case of ovarian cancer screening, a low positive predictive value would result in many unnecessary surgeries.

In 2015, Jacobs et al published results of the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), which enrolled 202,638 low-risk postmenopausal women who were randomized to multimodal screening (MMS), ultrasound alone, or no screening.⁸ The primary outcome of the trial was the comparison of mortality from ovarian cancer between the three cohorts. The researchers had planned to stop the study seven years after randomization, but the mortality in the no-screening group was lower than expected, so they extended the study to 14 years. Using their initial statistical approach, the authors found no statistically significant difference between the groups when MMS was compared to no screen or ultrasound alone was compared to no screen. Given that they assumed a 30% difference in mortality a priori and failed to see this difference initially suggests that they were underpowered to detect a difference and overestimated the screening potential of MMS. When they removed the cases of ovarian cancer that were present at the time of randomization (prevalent cases), there was 28% less mortality in the MMS group compared to the no screen group in years 7-14, which was a statistically significant difference. It is not clear what the improvement in mortality would be if women were screened their entire postmenopausal lifetime. To translate these data into real numbers, of the approximately 200,000 women screened during 14 years, there were 1,025 ovarian cancers. They reduced the mortality from 580/100,000 women in the no-screen group to 390/100,000 women in the MMS group prior to removing the prevalent cases, a difference of 180 women. After the prevalent cancer cases were removed, the mortality was reduced from 450/100,000 women to 250/100,000 women, a difference of 200 women over 14 years. There were 483/50,000 unnecessary surgeries in the MMS group and 1,638/50,000 unnecessary surgeries in the ultrasound group.

COMMENTARY

So how do we interpret these data, and how should we incorporate these results into our practice? This is the first ovarian cancer screening study to show a reduction in mortality with screening. The Prostate, Lung, Colorectal and Ovarian (PLCO) study showed no change in mortality with screening low-risk postmenopausal women for ovarian cancer.⁹ However, there were significant differences in these two studies: The PLCO study only used a CA125 cutoff, and the UKCTOCS used their Risk of Ovarian Cancer Algorithm (ROCA) in the MMS group. This group has worked for more than 20 years to understand trends in CA125 and to mathematically describe the pattern of CA125 variability in postmenopausal women that predicts ovarian cancer. That being said, the question must be posed: Should we be screening low-risk women for ovarian cancer?

Screening for type 2 diabetes makes economic sense, given the frequency of this disease. Based on CDC data, the prevalence is approximately 9.3% or 29.1 million people in the United States and is as high as 25% in people older than 60 years of age.¹⁰ The incidence in the population older than 20 years of age is 7.8%/1,000 people screened. Many of the complications of type 2 diabetes can be managed with interventions such as diet, exercise, and hypoglycemic medication. Ovarian cancer is a much rarer disease and is less amenable to prevention. It affects approximately 25,000 women/year in the United States. Given that it will take 7-10 years of yearly or more frequent screening of postmenopausal women to see a reduction in mortality, universal screening may not be a reasonable approach. The counter-argument is that ovarian cancer is a deadly and poorly understood disease.

Should we use our diminishing resources to screen all postmenopausal women for a rare disease, albeit a deadly one? Should we screen 200,000 to save 200 lives? There are approximately 40 million women older than 50 years of age in the United States, based on the 2014 census bureau data. To screen all of those women at $1,000/year would be conservatively $39.9 billion per year to find 15,942 cancers or approximately $2.5 million per cancer detected. In addition, approximately 398,571 women would undergo an unnecessary surgery. Assuming the cost of each unnecessary surgery was $10,000/person, the screening would result in an additional cost of almost $4 billion. Of those 15,942 cancers detected, this study suggests that without screening, 41% would survive five years, compared to 64% if they had been screened with the MMS approach. This would be a real number of 9,405 deaths instead of 5,739 deaths, a survival benefit for 3,666 women. The cost per patient who survived because of the MMS screening would be approximately $2.2 billion. This number sounds like a preposterous amount of money and may be overstated given estimates of the population > 50 years of age. Even if one assumes that only 50% of the population would be screened, this amount still would be an enormous cost for medical care to improve survival by 23% for a rare disease.

From the perspective of a screening test, focusing on women at higher risk than the general population would identify at least 25%, or more, of the cases of ovarian cancer and may allow intervention before cancer occurs by identifying these women and offering them prophylactic strategies. Using oral contraceptives for more than 10 years would reduce the incidence of ovarian cancer by more than 50% and may be a more reasonable approach for low-risk women when they are premenopausal. Spending an extra $1,000 (the cost of MMS screening) for screening over a woman’s postmenopausal lifetime may not be worth considering, given that at least half of the population with diabetes are not being screened and, therefore, not diagnosed with a treatable disease that has high prevalence.

There have been significant questions about the role of screening for many diseases in terms of lead-time bias, cost, false-positive and false-negative tests, and whether screening actually saves lives. The cost always must be balanced against the potential benefit, and it isn’t clear that we should choose universal screening for postmenopausal women in lieu of other more effective interventions.

REFERENCES

1. Bast RC Jr, Menon U, Ryan A, et al. A radioimmunoassay using a monoclonal antibody to monitor the course of epithelial ovarian cancer. N Engl J Med 1983; 309:883-887.
2. Ovarian cancer: Screening, treatment, and follow-up. NIH Consens Statement 1994;12:1-30.
3. Longoria TC, Ueland FR, Zhang Z, et al. Clinical performance of a multivariate index assay for detecting early-stage ovarian cancer. Am J Obstet Gynecol 2014; 210:78.e1-9.
4. DePriest PD, Gallion HH, Pavlik EJ, et al. Transvaginal sonography as a screening method for the detection of early ovarian cancer. Gynecol Oncol 1997; 65:408-414.
5. Skates SJ, Xu FJ, Yu YH, et al. Toward an optimal algorithm for ovarian cancer screening with longitudinal tumor markers. Cancer 1995; 76(10 Suppl):2004-2010.
6. Jacobs I, Oram D, Fairbanks J, 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 1990; 97:922-929.
7. Menon U, Gentry-Maharaj A, Hallett R, et al. Sensitivity and specificity of multimodal and ultrasound screening for ovarian cancer, and stage distribution of detected cancers: Results of the prevalence screen of the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Lancet Oncol 2009; 10:327-340.
8. Jacobs IJ, et al. Ovarian cancer screening and mortality in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS): A randomised controlled trial. Lancet 2016; 387(10022):945-956.
9. Buys SS, Partridge E, Black A, et al. Effect of screening on ovarian cancer mortality: The Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening randomized controlled trial. JAMA 2011; 305:2295-2303.
10. Centers for Disease Control and Prevention. National Diabetes Statistics Report, 2014. Accessed at http://1.usa.gov/1HtvctB.