Identification of the best complete blood count-based predictors for bladder cancer outcomes in patients undergoing radical cystectomy

BACKGROUND: We sought to determine which parsimonious combination of complete blood count (CBC)-based biomarkers most efficiently predicts oncologic outcomes in patients undergoing radical cystectomy (RC) for bladder cancer (BC). METHODS: Using our institutional RC database (1992–2012), nine CBC-based markers (including both absolute cell counts and ratios) were evaluated based on pre-treatment measurements. The outcome measures were recurrence-free survival (RFS), cancer-specific survival (CSS), and overall survival (OS). Time-dependent receiver-operating characteristics curves were used to characterise each biomarker. The CBC-based biomarkers, along with several clinical predictors, were then considered for inclusion in predictive multivariable Cox models based on the Akaike Information Criterion. RESULTS: Our cohort included 418 patients. Neutrophil–lymphocyte ratio (NLR) was the only biomarker satisfying criteria for inclusion into all models, independently predicting RFS (HR per 1-log unit=1.52, 95% CI=1.17–1.98, P=0.002), CSS (HR=1.47, 95% CI=1.20–1.80, P<0.001), and OS (HR=1.56, 95% CI=1.16–2.10, P=0.004). Haemoglobin was also independently predictive of CSS (HR per 1 g/dl=0.91, 95% CI=0.86–0.95, P<0.001) and OS (HR=0.90, 95% CI=0.88–0.93, P<0.001), but not RFS. CONCLUSIONS: Among CBC biomarkers studied, NLR was the most efficient marker for predicting RFS, whereas NLR and haemoglobin were most efficient in predicting CSS and OS. NLR and haemoglobin are promising, cost-effective, independent biomarkers for predicting oncologic BC outcomes following RC. CONDENSED ABSTRACT: Various CBC-based biomarkers have separately been shown to be predictive of oncologic outcomes in patients undergoing cystectomy for BC. Our study evaluated these biomarkers, and determined that NLR is the best CBC-based biomarker for predicting RFS, whereas NLR and haemoglobin are most efficient for predicting CSS and OS.