Background: Optimal hepatitis B virus (HBV) screening strategies for patients with cancer awaiting chemotherapy are unknown. We aimed to identify predictors of HBV infection in a large cohort of patients with cancer who were systematically screened for HBV before chemotherapy. Methods: In this prospective observational study, patients with cancer at MD Anderson Cancer Center awaiting first administration of chemotherapy in an outpatient chemotherapy unit were identified and approached for HBV screening. Enrolled patients completed a CDC risk survey and had blood tests to screen for HBV (HBsAg, anti-HBc) and hepatitis C virus (anti-HCV) infection. We developed a logistic regression model to identify clinical predictors of either chronic (HBsAg+/anti-HBc+) or past (HBsAg-/anti-HBc+) HBV infection. Model fit was assessed using the Hosmer-Lemeshow goodness-of-fit test. We present results from year 1 of our ongoing 2-year study. Results: From July 2013 to June 2014, 1176 patients (mean [SD] age, 58 [13] years) have completed the risk survey and HBV screening. Of these, 54% were women, 84% white, 9% black, 4% Asian, and nearly 11% Hispanic. Over 20% had a hematologic malignancy, 1% liver cancer, and 77% a solid tumor other than liver cancer. Almost 12% of patients were born outside the US. Three patients (0.26%) had chronic and 84 (7%) had past HBV infection. Among the latter, 9 patients were also anti-HCV+. Predictors (odds ratio [OR]; 95% CI) of having either HBsAg+ or anti-HBc+ result included black race (4; 2-7), Asian race (4; 2-9), birthplace outside the US (5; 3-10), and having lived with someone with HBV (3; 2-7). Patients who reported ever injecting drugs (OR 7; 2-24) or being a man currently having sex with another man (OR 42; 6-277), or who were anti-HCV+ (OR 5; 1-16) had high risk of HBsAg+ or anti-HBc+ result. Conclusions: Known HBV risk factors are predictive of chronic or past HBV infection in patients with cancer. These results can assist in the development and testing of risk-based screening strategies to enhance accurate and cost-effective identification of patients with HBV infection.