We constructed a novel risk model to predict recurrence by classifying patients into two groups using ten independent prognostic factors [bladder cancer-specific nuclear matrix protein 4 (BLCA-4), bladder tumour antigen (BTA), nuclear matrix protein 22 (NMP22), carcinoembryonic antigen (CEA), body mass index, smoking, family history of bladder cancer, occupational exposure to aromatic amine chemicals, number of tumours, bladder instillation of chemotherapeutic agents] to predict tumour recurrence based on logistic regression analyses (testing group). Here, CEACAM5 is linked to urinary bladder cancer.