Symptom Triggered Testing for Ovarian Cancer-Recording

Video Transcription

Video Summary

Professor Sudha Sundar discusses symptom trigger testing for ovarian cancer, emphasizing the importance of early diagnosis. With over 300,000 women diagnosed annually worldwide and high mortality rates, identifying ovarian cancer at an early stage is crucial. Early-stage diagnosis significantly improves survival rates, highlighting the criticality of stage at diagnosis.<br /><br />Two major trials (UKC talks and PLCO) explored screening but showed no mortality benefit. Despite this, the UKC talks trial demonstrated that using a multimodal algorithm could diagnose ovarian cancer earlier. Recent findings have shown potential improvements in outcomes when newer detection methods are coupled with advanced treatments.<br /><br />Common ovarian cancer symptoms, such as bloating, abdominal pain, and changes in bowel or urinary habits, often go unnoticed due to their vague nature. Tools like symptom-based indices and studies like the DOVE and ROCKETS (which emphasize symptom awareness and rapid diagnostic pathways) show promise in diagnosing low-volume and early-stage disease.<br /><br />However, the challenge remains balancing early detection with avoiding unnecessary testing and related anxiety. Advances in digital technologies, AI, and genomic research are promising for future diagnostic improvements, potentially leading to better survival outcomes. Professor Sundar stresses the significant impact gynecological oncologists can have on patient outcomes by ensuring timely and accurate diagnosis.

Keywords

ovarian cancer

early diagnosis

symptom trigger testing

multimodal algorithm

diagnostic pathways

digital technologies

genomic research