Challenges of early renal cancer detection: symptom patterns and incidental diagnosis rate in a multicentre prospective UK cohort of patients presenting with suspected renal cancer. Issue 5 (11th May 2020) - Vasudev, Naveen S; Wilson, Michelle; Stewart, Grant D; Adeyoju, Adebanji; Cartledge, Jon; Kimuli, Michael; Datta, Shibendra; Hanbury, Damian; Hrouda, David; Oades, Grenville; Patel, Poulam; Soomro, Naeem; et al.
Abstract : Objectives: To describe the frequency and nature of symptoms in patients presenting with suspected renal cell carcinoma (RCC) and examine their reliability in achieving early diagnosis. Design: Multicentre prospective observational cohort study. Setting and participants: Eleven UK centres recruiting patients presenting with suspected newly diagnosed RCC. Symptoms reported by patients were recorded and reviewed. Comprehensive clinico-pathological and outcome data were also collected. Outcomes: Type and frequency of reported symptoms, incidental diagnosis rate, metastasis-free survival and cancer-specific survival. Results: Of 706 patients recruited between 2011 and 2014, 608 patients with a confirmed RCC formed the primary study population. The majority (60%) of patients were diagnosed incidentally. 87% of patients with stage Ia and 36% with stage III or IV disease presented incidentally. Visible haematuria was reported in 23% of patients and was commonly associated with advanced disease (49% had stage III or IV disease). Symptomatic presentation was associated with poorer outcomes, likely reflecting the presence of higher stage disease. Symptom patterns among the 54 patients subsequently found to have a benign renal mass were similar to those with a confirmed RCC. Conclusions: Raising public awareness of RCC-related symptoms as a strategy to improve early detection rates is limited by the fact that related symptoms are relatively uncommon and often associated with advanced disease. Greater attention must be paid to the feasibility of screening strategies and the identification of circulating diagnostic biomarkers.