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Rates of Newly Diagnosed Urological Malignancy in Patients Admitted with Haematuria: A Single-Centre Comparison with the IDENTIFY Study
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Talk Description

Institution: Fiona Stanley Hospital - Western Australia, Australia

Purpose Visible haematuria a strong predictor of urinary tract malignancy.1 The international IDENTIFY study reported new diagnoses of urinary tract cancer in approximately 28% of patients referred with haematuria, with bladder cancer most prevalent.1 However, limited data exist describing detection rates among patients admitted with haematuria in Australian tertiary hospitals. This study aimed to determine the local rate of newly diagnosed malignancy and compare findings with IDENTIFY data. Methodology A retrospective cohort study was conducted of adult patients admitted via the emergency department with visible haematuria at a single tertiary hospital between April 2024 and April 2025. Patients were identified using ICD-10 coding. Demographic data including age, gender, smoking history and subsequent diagnoses were recorded. The primary outcome was rate of newly diagnosed urological malignancy during admission or subsequent admission. Secondary outcomes included cancer type and associated risk factors. Local detection rates were compared with IDENTIFY study results. Results Fifty patients were admitted with visible haematuria during the study period. Three patients (6%) were diagnosed with a new urological malignancy, including two cases of bladder cancer and one renal cell carcinoma. Bladder cancer was diagnosed in older patients while renal cancer occurred in a younger patient. All patients diagnosed with malignancy had previous smoking history. Conclusion The observed malignancy rate was lower than that reported in the IDENTIFY study, likely reflecting the sample size and inpatient cohort. 1 However, the distribution of malignancy type and associated risk factors reflect published results, highlighting the importance of thorough investigation of all haematuria. The use of risk stratification tools such as the IDENTIFY urinary tract cancer prediction model, may assist in guiding appropriate investigations.1 1.Khadhouri S et al. IDENTIFY study. BJU Int. 2021.
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Dr Sophie Fang Lin - , Dr Devan Sandhu - , Dr Kevin Keane - , Prof Dickon Hayne -

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