PURPOSE: The present systematic review aimed to identify prognostic values of blood-based biomarkers in patients treated with neoadjuvant chemotherapy (NAC) for urothelial carcinoma of the bladder (UCB). MATERIAL AND METHODS: The PubMed, Web of Science, and Scopus databases were searched in August 2020 according to the PRISMA statement. Studies were deemed eligible if they compared oncological outcomes in patients treated with NAC for UCB with and without pretreatment laboratory abnormalities. RESULTS: Overall, ten studies, including 966 patients who underwent NAC, met our eligibility criteria. Six studies provided data on pretreatment neutrophil to lymphocyte ratio (NLR) with contradicting results on its association with pathologic response (PR) and complete pathologic response (pCR); some studies reported a strong association between a high level of pretreatment NLR and worse survival outcomes. Two studies reported that higher pretreatment platelet-lymphocyte ratio (PLR) is associated with a lower likelihood of achieving PR and/or pCR, while lymphocyte count alone had the opposite association. One study reported a negative association between pretreatment blood-based myeloid-derived suppressors cells and pCR. Patients who experienced a remission have been reported to have higher level of lymphocyte subsets (CD3+, CD4+, CD57+ cells, the ratio of CD4+/CD8+) compared to those who had progression. One study found that low pretreatment blood-based human chorionic gonadotrophin b subunit (hCGβ) was associated with improved overall survival (OS). High levels of epithelial tumor markers (CA-125, CA 19-9) were also associated with worse OS and recurrence-free survival in the NAC setting. CONCLUSION: Current evidence suggests that several readily available, easy measurable blood-based biomarkers hold promise to improve our selection of UCB patients who are likely benefit from NAC. However, their role as an adjunct to established histopathologic characteristics for clinical decision-making requires further validation along the biomarker phased approach.