By: Natalie Johnson
Ovarian cancer remains the deadliest gynecological cancer, and the reason has less to do with the ferocity of the disease than with the moment it gets caught. Most women are diagnosed at an advanced stage, when treatment options narrow and quality of life collapses. The standard explanation blames biology. Emily Campbell, who leads work at These Ovaries, points somewhere far more uncomfortable: there is no screening test for ovarian cancer in general use, nothing a primary care physician or gynecologist can order during a routine visit to rule it out. The entire system waits for a woman to notice something is wrong and say so. That design flaw, not the tumor, is where the research gap bites hardest.
The Detection Problem Nobody Has Solved
Campbell is direct about where the hole is. “The most critical unmet need right now around real-world patient solutions is screening,” she says. “Understanding how to detect the disease, how to test for it.” Blood tests already in circulation get a lot of attention, and she is careful not to dismiss them. They are useful tools. They are not screens. “People who say that there are other blood tests that are available right now, those are good for maybe recurrence once we’ve already established that the patient is sensitive to the data in this blood test. But there is no definitive screen for the general population.”
That absence forces ovarian cancer into a category of its own. There is no self-exam. No mass a woman can feel at home. The disease is symptomatic, but it tends to announce itself late, and when it does, the symptoms impersonate ordinary gastrointestinal complaints. So the burden of detection falls on the patient, who has to raise her hand, then navigate a chain of referrals that may or may not land her in front of the right specialist. “There are a lot of cancer screens that are proactive,” Campbell says. “Unfortunately, ovarian cancer is reactive because it’s symptomatic.” A simple, routine screen would flip that order. Campbell sees real movement here, possibly more than on the treatment side, where first-line care still leans on platinum-based chemotherapy that has barely changed in three decades and fails outright in patients who are platinum-resistant.
Misinformation Travels Downhill
The second failure is informational, and it starts above the patient. Campbell describes misinformation around women’s health as systemic, then narrows it: postmenopausal care, menopausal care, gynecologic cancers, PCOS, and endometriosis to name a few. “There are misunderstandings around endometriosis, which is an extremely common disease for many young women, and there are still no answers to really anything about it.” Confusion at the clinical level does not stay there. It gets handed to patients, who are left without the vocabulary to describe what they are experiencing or the framework to know what their tests covered.
Her sharpest example is the one most women would never question. A Pap smear comes back negative, the doctor says you are good to go, and a woman walks out believing she has been cleared. She has been screened for cervical cancer. Nothing else. “That does not translate to endometrial cancer, uterine cancer, or ovarian cancer,” Campbell calls it a false sense of security, and the consequence is a population that misreads its own risk profile and delays acting on symptoms. The genetic conversation compounds it. Inherited mutations such as BRCA and Lynch syndrome create a high-risk group that gets monitored, but Campbell estimates roughly 75 percent of ovarian cancers are not tied to those mutations at all. Those women were never flagged as high risk to begin with, which means a risk-based model leaves most cases uncovered. There is a research consequence too. Because the disease kills so efficiently, Campbell notes, there are not enough survivors to advocate and generate research dollars, and funding tends to follow the loudest constituencies.
Why Access Decides Who Benefits
On artificial intelligence (AI), Campbell refuses the easy claim. Asked whether AI-driven biomarker work is reshaping treatment pipelines, she says plainly that it is not, not yet. What she sees is promise rather than delivery. The potential sits in reading what current tools cannot. In low-grade serous ovarian cancer, the subtype her work focuses on, she describes biomarkers within the tumor that remain poorly understood, with the full genetic chain still unread. Traditional platinum-based chemotherapy has historically underperformed in that subtype because of its distinct molecular structure. Campbell believes an effective treatment exists but has not been identified. AI’s real contribution, in her reading, would be foundational: understanding the tumor well enough to match patients to therapies that work.
None of that matters if patients cannot reach a doctor. Campbell estimates there are only about 1,200 to 1,500 gynecologic oncologists in a country of roughly 300 million people, and they cluster at research institutions: New York, Houston, Los Angeles, Chicago, and Miami. For women in rural counties, the barrier is literal. No specialist within reach, no resources to travel, no time off work, and children or parents to care for. Layer on recent federal funding cuts to disease management and healthcare, and Campbell expects ripple effects that will not be fully understood for decades. Reversing them will take time, she says, but it needs to happen. This is precisely why a routine blood test is not merely a scientific milestone but an access strategy. It moves detection to the primary care office a woman can reach, turns a reactive system proactive, and gives patients options while options still exist.
Follow Emily Campbell on LinkedIn for more insights on ovarian cancer research, early detection, and patient advocacy.
Disclaimer: This article is intended for informational and educational purposes only and does not constitute medical advice, diagnosis, or treatment. Readers should consult a qualified healthcare professional regarding ovarian cancer screening, risk factors, symptoms, and treatment options. Medical research and recommendations may evolve, and individual healthcare decisions should be based on professional medical guidance.
