Ovarian Cancer: Closing Gaps and Advancing Care with RWD
Key Takeaways
- Population burden persists: ~21,000 U.S. diagnoses and >12,000 deaths projected for 2026, with Black women more often presenting Stage III/IV than White women.
- Funding and capacity constraints limit progress: only ~4% of global R&D targets women’s cancers, while 1,300–1,500 gynecologic oncologists leave rural patients reliant on non-specialists.
Amidst this backdrop of challenges, one area of promise for closing gaps and advancing ovarian cancer care is the growing availability of high-quality, research-ready, real-world data.
Gynecological cancers impact all of us. According to the American Cancer Society, approximately 21,000 women will be diagnosed1 with ovarian cancer in the U.S. in 2026. While the rate of death has decreased 45% since 1976, more than 12,000 women in the country will die from ovarian cancer this year.
The high death rate is in large part due to a lack of effective screening techniques, often leading to advanced-stage diagnoses. This issue is compounded by substantial care gaps, notably a racial disparity where Black women are disproportionately diagnosed at later stages (Stage III or IV) compared to White women (77% vs. 70%). Additionally, ovarian cancer has a high recurrence rate and treatment resistance.
Despite the significant disease burden and devastating impacts that gynecological and breast cancers have on patients and their loved ones, only four percent2 of global R&D funding focuses on women’s cancers.
Meanwhile, a critical workforce shortage of gynecologic oncologists—estimated at only 1300 to 1500 practicing in the U.S.—is worsening, especially in rural areas.
This shortage is exacerbated by an overall trending decline in obstetrics-gynecology residency applications, shifting the burden of early detection onto primary care providers and complex surgical treatment onto general oncologists who may not be specialty-trained.
The Good News
Amidst this backdrop of challenges, one area of promise for closing gaps and advancing ovarian cancer care is the growing availability of high-quality, research-ready, real-world data (RWD).
RWD is a crucial tool for researchers and clinicians for delivering more precise care in alignment with patients’ individual characteristics. Unlike data from traditional clinical trials, which have a tendency to enroll younger, healthier, and less diverse patient cohorts, RWD is captured from electronic health records (EHRs), registries, and claims data across the country, and more accurately reflects the journey of patients in the diverse population.
Aided by sophisticated artificial intelligence (AI) tools, teams of professionals with disease-specific expertise are able to curate unstructured RWD including the clinician notes in EHRs and rapidly generate databases drawn from the real-world experiences and care patterns of ovarian cancer patients from academic and community cancer centers throughout the U.S.
The most advanced of these databases deliver high completeness across critical clinical variables that drive research and treatment decision-making, including molecular testing, treatment sequencing, disease state, and outcomes across diverse populations. They include key data elements, such as platinum resistance classification (defined as cancer that recurs within 6 months of completing platinum-based chemotherapy, e.g., cisplatin or carboplatin) and are curated and structured to support regulatory and development use.
In this way, RWD is now offering comprehensive longitudinal insights into disease detection, treatment, and patient outcomes, allowing researchers to gain a richer understanding of ovarian cancer in wider populations, see where gaps in care exist, better understand what treatments are working, and improve studies seeking new treatments.
Addressing Care Gaps
In the case of ovarian cancer, RWD can help identify disparities in care, treatment, and outcomes, and enable researchers to better understand why they exist, by examining differences in treatment settings and proximity to care facilities for different racial groups.
To inform clinical decisions, oncologists can review RWD trends and outcomes for patients similar to their own to inform treatment strategies.
Importantly, the development of extensive data partnerships is also making it easier for clinicians and researchers to link ovarian cancer EHR data with other sources including complete genomics data, enabling more precise care and opening the door to improved outcomes.
Designing Better Studies
For clinical studies, life science teams can use RWD to design smarter, more efficient clinical trials, ensuring findings are applicable to broad populations. This includes accelerating R&D and replacing traditional placebo arms with external control arms when appropriate.
RWD is also helping to successfully support equitable enrollment in trials. A combination of RWD and AI-driven tools can help researchers identify and enroll patients of diverse backgrounds who are currently underrepresented in clinical studies, improving the external validity and generalizability of new studies.
Measured Progress
Significant gaps in care continue to exist in ovarian cancer, and addressing the underlying lack of access to care and shortage of gynecologic oncologists remain as important problems to address.
Against this backdrop, sophisticated real-world databases are providing a more accurate view of ovarian cancer journeys. Real world ovarian cancer data is letting researchers ask better questions, design smarter trials, and act on data that reflects real life, not just ideal scenarios.
It’s a critical step to helping providers, payers, and researchers to begin to address inequities and close the gaps that affect too many women today.
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