Hello, my name is Sudha Sundar. I'm the professor of gynaecological cancer and a consultant gynaecological oncologist at Birmingham in the United Kingdom. I'm also the lead for the National Ovarian Cancer Audit in the UK. Today I'm going to talk to you about symptom trigger testing for ovarian cancer. So these are my conflicts of interest. None are related to this work. Today I'd like to discuss a little bit about the background of symptom trigger testing, the symptoms associated with ovarian cancer, the evidence for symptom awareness and the impact on the outcomes of patients who've been diagnosed through symptom awareness and also highlight areas of discussion and further research. So we know internationally that we have sadly over 300,000 women diagnosed with ovarian cancer each year. We know that about 200,000, 206,000 women will die of ovarian cancer each year. And therefore, and the incidents of ovarian cancer is expected to rise over the next decade or so. This is data from England, but it would be very similar to data from any other country. And that is that if a woman is diagnosed at stage one ovarian cancer, then her one year survival, which is in the pink and the more fuchsia pink five year survival is actually extremely high. As the stage of diagnosis advances, then both one year survival as well as five year survival drops to the extent where five year survival for stage four, for women diagnosed at stage four, ovarian cancer will be around 15%. So this is a very significant difference in outcome by stage of diagnosis. And I think if there was anything we took away from this, it is that stage of diagnosis at ovarian cancer really does matter. So there've been a number of trials, there've been two pivotal trials that have investigated the role of screening, which is to say, using tests to investigate asymptomatic women to try and diagnose ovarian cancer earlier. Both trials have pivotal papers, and I've referenced a couple of them. UKC talks recruited women between 2001 to 2005. PLCO recruited in the US at around the same time. So these trials predate what we currently know of ovarian cancer in our understanding of high grade serious ovarian cancer arising predominantly from the fallopian tube. They predate BRCA testing, the centralization of care in the UK, extensive surgery, as well as PARP inhibitors. And I think that provides some context. Both trials sadly demonstrated that there was no difference, no reduction in mortality in the screen down. UKC talks demonstrated that it was possible through screening, using a multimodal algorithm, which involved serial increases in CA125, and triggered ultrasound. When this was used, they were able to diagnose ovarian cancer earlier. So they were able to identify greater proportion of women with stage one, stage two ovarian cancer. But this did not translate overall into a mortality benefit. More recently, their manuscript in Lancet Oncology published last year has shown for high grade serious tube ovarian cancer that they were able to identify women at earlier stage. These patients also had higher complete cytoreduction rates, more proportion of primary surgery rates, and also a small but significant improvement in survival. This was the first paper from the UKC talks trial that has actually demonstrated that screening can detect high grade serious ovarian cancer earlier. And the authors conclude that newer technologies that can detect more women with high grade serious ovarian cancer earlier, when coupled with treatment improvements and better understanding of tumor biology, has potential to improve outcomes. And this is really quite a much more optimistic place for us to be in. Ovarian cancer used to be considered a silent killer. Now we know that ovarian cancer is actually has got symptoms, but these symptoms are quite nonspecific, and they're quite vague abdominal symptoms. And these are a small selection of papers, and I put them down because actually these were seminal papers of their time, demonstrating in predominantly case controlled studies conducted in hospital as well as in community care, that women with symptoms, women with ovarian cancer had symptoms that predated their diagnosis by some months. So there was a lot of work to investigate what these symptoms would be, and what combination of symptoms could be used as predictive tools for the diagnosis of ovarian cancer. So what are these symptoms? As I said, these symptoms are quite vague and nonspecific. The symptoms that appear to have the highest positive predictive value, each of these symptoms on their own, actually have a relatively small probability of meaning that a woman with these symptoms has ovarian cancer. So quite small individual positive predictive values, but when you put them together, they're a lot better. The symptoms with the highest PPV look like abdominal distention, bloating, and pain. When you start adding additional symptoms, it improves sensitivity, so more women with cancer get diagnosed, but it reduces the specificity, so more women without cancer also get flagged up with these symptoms. The acronyms that are most commonly used are BEAT, bloating, early satiety, which is that you feel full quickly. Abdominal pain, A stands for abdominal pain. And C stands for change in bowel habit or change in urinary habit. T stands for tiredness. So these are really helpful acronyms to remember when we're assessing women with vague nonspecific symptoms. There are four symptom-based tools, the GOF symptom index, the STO consensus criteria, the Q cancer ovarian, that have all shown independent external validation. But to take them forward to clinical practice, much, much more work would need to have been done. More recently, the UK CTOX group published that women with early stage ovarian cancer appeared to have more change in GI habit and tiredness than women with more advanced stage ovarian cancer who tended to present with bloating and distention. So there's work to be done about what symptoms more typically characterize stage of cancer, but it's nevertheless quite interesting work. So we know that screening doesn't show a survival benefit. We know that women with ovarian cancer have symptoms. So the move then was how can we make sure that women are aware of these symptoms and that then those patients with symptoms are fast-tracked for diagnostics and for treatments in a more efficient way. So what data do we have on symptom awareness, symptom testing, followed by diagnostic testing and treatment? Well, there are two studies, the DOVE study led by Professor Lucy Gilbert in Canada, and then more recently, the ROCKET study, which I'm chief investigator of, that has started reporting from the UK. The DOVE study published a pilot in the Lancet Oncology in 2012. This was soon after the understanding of symptoms being associated with ovarian cancer, and it was in the first beginning phases of symptom awareness and symptom trigger testing. They reported on a community pilot where they assessed 1,455 women were assessed with these symptoms, and they compared this group of people to women who were diagnosed through routine clinics at the same time. What they identified was the women who were picked up in this pilot were diagnosed with lesser tumor burden than the 75 clinic patients. It would appear that the CA125 concentration was lower, 72 units per mil versus 888 units per mil. More patients were completely resectable, 73% of tumors were completely resectable in the DOVE pilot patients compared with 33, 44% in clinic patients. However, they also flagged that 78% of the patients who had high-grade serious ovarian cancer, relatively small numbers, had originated outside the ovaries. So what they did say was that this might not be ready for implementation because we may be able to identify women with symptoms, but then past that, you need to have good quality diagnostics to try and identify accurately the women with ovarian cancer. And rightly, they said, we aren't sure this is ready for implementation. Nevertheless, symptom trigger testing then became recommended in the UK and elsewhere. And this is where women with symptoms are encouraged to present to their family practitioner, or in the UK, they're called general practitioners. GPs are then encouraged to test these women with a sequential CA125 and then an ultrasound pathway. And if they find that their CA125 and ultrasound is abnormal, they then refer the patient to hospital through what's called a rapid access pathway. In a rapid access pathway referral, the hospitals are meant to diagnose and to, so it's a timed treatment pathway where there are targets for diagnosing the patient on time and also then starting treatment on time. So we conducted a study called the ROCKET study. The first, there've been a few manuscripts from this, but our first results is coming out in the Lancet Oncology in October, 2024. So in 10 days time. So ROCKET was conducted as a diagnostic test accuracy study, where we looked at all of the diagnostic tests that are commercially available for ovarian cancer and estimated the head-to-head comparison of ROMA versus aorta adnex versus the risk of malignancy index versus ORADS versus the aorta simple rules. And as I said, we're publishing on the diagnostic accuracy results shortly. However, this was also an opportunity for us to find out what the outcomes of women who'd been referred through this symptom triggered expedited pathway was. And so we conducted an opportunistic analysis of the study data. The link there gives you more information on ROCKETs as well as the protocols. So what we did was we looked at the patients who'd been recruited in ROCKETs and we asked whether symptom-based testing, this was an exploratory analysis, assess whether patients who were diagnosed through the rapid access route, which is that they had symptoms, they were tested by their GP, and then they were referred through an expedited referral and timely treatment pathway, what the outcomes of these women looked like. So were these women diagnosed with early stage ovarian cancer, particularly high-grade serious ovarian cancer? Did they have low volume disease? What were their cytoreduction rates looking like? Because one of the challenges, I think, for symptom-based testing is that often as gynae oncologists, we feel that if women have symptoms, they've probably got late stage disease, particularly for high-grade serious ovarian cancer, because we know it predominantly arises in the fallopian tube and it disseminates widely. So there has understandably been a concern that if we're diagnosing women based on symptoms, actually all we're doing is are we just picking up women with advanced stage disease, or if we're picking up early stage disease, are we just picking up pelvic confined patients with clear cell or mucinous ovarian cancer because they tend to pick up as ovarian cysts. So this is why we wanted to look at our patient cohort to see what the impact specifically on high-grade serious ovarian cancer was from this symptom-based testing followed by expedited referral and timely treatment pathway. So we looked at our data set. So these were patients recruited from 2015 to 2022. This was a series of studies funded by the National Institute of Health Research and then by Cancer Research UK. And essentially, patients were recruited at the clinic, and then within three months, they had either undergone surgery or biopsy, and they'd had all their tests done, and they completed a baseline questionnaire on their symptoms. If they didn't undergo surgery about within three months, we then evaluated how well they were doing through a structured questionnaire, a participant questionnaire, as well as an outcome questionnaire from the research nurse. So we really had quite detailed and granular symptom history as well as outcome history. And that's the reference. So of 2,596 women who were recruited into this study, we found that 1,741 were recruited through these, they're called two-week wait referrals in the UK. Essentially, it's women who have symptoms, who are expedited for diagnostic testing, and who are expedited for treatment. The majority of our patients were recruited through the two-week wait pathway. Of these, we found 215 women had primary ovarian cancer. Of these, 206 had epithelial ovarian cancer. And we looked at the outcomes from the 119 women with high-grade serious ovarian cancer. Now, it's really important to understand that all of these patients have had specialist gynae pathology review. That's part of routine NHS, National Health Service care in the UK. So when we characterize the women with high-grade serious ovarian cancer diagnosed through the rapid access pathway in ROCKiTS, we find that the majority of them, the overwhelming majority of them, in fact, had a performance status of 0 to 1. We found that one in four women with high-grade serious ovarian cancer were diagnosed with stage 1 and 2. Whilst we don't have a comparator cohort for this, in fact, being able to identify one in four women with high-grade serious ovarian cancer just on the basis of symptoms is really results that we were quite pleased with because it's quite clear that we're actually able to identify women with high-grade serious ovarian cancer using symptom trigger testing. Importantly, when we characterize the disease distribution, this was low to moderate. So we characterized whether they had the highest extent of disease with pelvic or mid-abdominal or upper abdominal. So two-thirds of these women with high-grade serious ovarian cancer were picked up with low to moderate disease and complete or optimal cytoreduction was achieved in the majority of women. So 61% complete and optimal in 15%. So the next set of results is about the extent of disease. And two-thirds of women underwent primary debulking surgery, a third received neoadjuvant chemotherapy, and five of these women did not undergo surgery. So these results are the first results, I think, for women who have come through symptom trigger testing and rapid diagnostics and rapid treatment pathways that demonstrates early-stage diagnosis at a good performance status and with good cytoreduction. So in conclusion, we demonstrated that one in four women diagnosed with high-grade serious ovarian cancer via the two-week wait pathway had stage 1 to 2 disease. We say that symptom-based testing facilitates detection of low-volume disease, and we were able to get complete cytoreduction rates. And expedited investigation and treatment may be associated with improved outcomes at better performance status. Now, there are limitations of this study, and they are a few. Firstly, we have not so far published on survival. This is something that we are acutely doing, and we have individual-level patient consent for both three-year and five-year survival outcomes, and we're working on this to see what the survival of these patients actually looks like. The second criticism that is a very reasonable one is to say, well, this was a trial that you were recruiting patients to. Therefore, you were probably more likely to recruit women who were fitter, who had better performance status because these patients also recruited into the study, and we know trial generally, study recruitment tends to be patients with better performance status. The one thing I would point out specifically for the histology distribution is that this study was a portfolio study. So in the UK, we have what's called the clinical research portfolio, which is delivered by research nurses. So essentially, they were agnostic. Knowledge of histology was a exclusion criteria for the study, and so patients with a biopsy result, patients with the research nurse could not recruit. So you couldn't recruit a patient after the patient had had a biopsy and after the results were known. So it's highly unlikely that the results that we are seeing is due to a systematic bias in recruitment for the diagnosis of high-grade serious ovarian cancer specifically. So this is, I think, really important to understand. However, I think the issue about performance status could well be trial-related. And as I said, it would be really important for us to look at what the survival outcomes of these patients is in order to further clarify the question as to whether symptom-based awareness is of use to these patients because cytoreduction rates and treatment rates are at the end of the day surrogate outcomes for survival. So what are the harms associated with symptom-triggered testing and rapid access pathways? And again, this is something we've published on because whilst we encourage women to report symptoms and whilst we encourage awareness of symptoms both amongst patients as well as among healthcare practitioners, we have to understand that the more women we test on the basis of symptoms, we also increase patients being tested unnecessarily, patients being diagnosed with false positives like benign tumors and borderline tumors that may cause harm by additional surgery, additional imaging. This has a cost to the individual, but it also has a cost to the health system. So when we looked at the proportion of women with ovarian cancer, so the prevalence of ovarian cancer in women who are referred through these pathways, you see that about 97 premenopausal women are referred to hospital to diagnose three women with ovarian cancer in the premenopausal group. The postmenopausal group, interestingly, the prevalence of ovarian cancer in women referred is quite high, and possibly we ought to be doing... We definitely, on the basis of this data, it would suggest that we need to really be improving the awareness of women in the postmenopausal group as well as through our family practitioners and our general practitioners and our colleagues in gynecology to increase awareness in women who are older and to ensure that they are tested because 18.5% means essentially one in five women you would see in that clinic would have ovarian cancer. Often, testing results in many women being tested inappropriately, so we found a group of women being tested under the age of 40 where you have really less than 1% risk of ovarian cancer, and that's often germ cell, so we're testing very young women with the wrong tests, and then that's not potentially good at all for the patients. So we need to really make sure that whilst we don't miss women who are premenopausal with ovarian cancer, we concentrate our efforts on women who are more at risk of ovarian cancer, which is the older age group. We know that the incidence of anxiety and distress in women who are tested for ovarian cancer is significantly higher in younger women, and as I said, that's the citation for this, and it does mean that there is a workload implication for health systems in seeing these patients, in undergoing testing, and there is a health economic implication, particularly for public health-funded systems, of this diagnostic testing. So in summary, the implications of this evidence for practice are that we are waiting for our understanding of ovarian cancer to leap forward for the development of effective screening and prevention strategies. In the meantime, symptom awareness and rapid diagnostic pathways certainly seems to result in women being diagnosed with low-volume disease and early-stage disease for high-grade serious ovarian cancer. At the moment, we don't know whether that translates into survival outcome and survival benefit or not, but this is actively what we're looking at in our dataset. The issue about what tests are the best tests, I presented this at SGO in March for postmenopausal women. I'm presenting the premenopausal results, which will be very interesting, at the International Gynae Cancer Society Conference in Dublin, and our manuscript for postmenopausal women will be out in 10 days' time. Beyond all of this, there's also what we can do in the future. So this is research that I've been very privileged to be part of. It's led from Imperial by a colleague of mine, Professor James Flanagan and Dr. Yasmin Hurst, and we looked at supermarket loyalty cards. So you know when you go to supermarkets, you have a loyalty card, so each time you purchase something, you ping your, you swipe your supermarket loyalty card, and it gives you points for future purchases, but also collects your shopping. What we've been able to demonstrate was that if you look at the loyalty card data from women with ovarian cancer compared to healthy women, actually women are purchasing medication for these symptoms eight months before a diagnosis of ovarian cancer. So in fact, if you consider the date of diagnosis as D-Day, zero day, it would appear that they're visiting their family practitioner or their GP about three months prior to that diagnosis. They can recall the first symptom about four and a half months before a diagnosis, but in fact, they've been purchasing eight months prior to diagnosis, and I'm talking about pain medication, indigestion medication, and this is potentially really exciting because with all of the data that's available, and we did, the team did a lot of work on privacy concerns and the willingness to share shopping data. There's various different ways in which these symptoms could be triggered to women that could through apps that we're using, smartphones that we're using. So over-the-counter medications, there's a spike in over-the-counter medications approximately eight to nine months before a diagnosis, and that makes perfect sense. So when I have a symptom, I try and self-medicate before I say, okay, let me ask a colleague in primary care, in my family physician. So potentially there's lots of different ways in which we can understand and really elicit these symptoms so that women can be tested better and diagnosed better. And a lot of my research program has centered around, how can we find better diagnostic tests for ovarian cancer? There's lots of scope for further research. One is the study that I have cited here, which is an amazing piece of work from the UKC DOCKS trial, looking to see whether the symptoms of women with early stage ovarian cancer are different from the symptoms for women with preclinical invasive epithelial ovarian cancer, specifically they've called it, where they found that women with gastrointestinal symptoms tend to be more associated with preclinical, before this presented clinically, compared to women who presented clinically with ovarian cancer, who tended to have more bloating. But it's also true that we don't quite know what these symptoms mean across different languages and across different nationalities. Does bloating mean the same in Pakistan or Bangladesh as it does in Western Europe? I don't know. We need to find out. The evidence of survival outcomes is a point I've made. We need to identify what the best strategies for symptom awareness is and how we can communicate these to women at scale. There's lots of opportunity for detection by digital technologies. And I still remain optimistic that with the huge advances we're seeing in digital technologies, with genomics, with multi-omics, with AI, with complex ultrasound, that we will get to a point where we will have much better diagnostic tests for ovarian cancer. And that overall, that along with the fundamental improvement in our understanding of ovarian cancer biology, will mean that we will get to a better place for our patients with better diagnosis and quicker diagnosis and better outcomes, better survival. So in summary, ovarian cancer is associated with symptoms. Our work shows that testing and rapid referral triggered by symptoms is associated with diagnosis at early stage and at disease, at low to moderate disease distribution and good performance status. I'd like to end with a message, which is that often gynecological oncologists don't actually think that they have a remit to be part of the diagnostic journey at all. But in fact, for the vast majority of women, the diagnostic journey has not been straightforward. In the UK, women visit their family practitioner three times at least before they get tested. The story is similar in other parts of the world. If you're a gynecological oncologist in an area, in fact, the best way you can impact on outcomes is making sure that people are diagnosed in good performance status, where they can then go on to have extensive treatments. So I would suggest that whilst we are, of course, committed to high quality surgery and ever more increasing and complex treatment paradigms, the single biggest thing we can do for our colleagues, for our patients is to ensure that those of us who are involved in the diagnostic pathway are aware of the implications of the symptoms for these patients. Thank you. This is a really nice picture from St. Michael's Mount in the UK. Nice place to visit. And with that, I will say thank you for your time.

ovarian cancer

early diagnosis

symptom trigger testing

multimodal algorithm

diagnostic pathways

digital technologies

genomic research