Purpose: Most patients with cancer are not screened for hepatitis B virus (HBV) infection before undergoing anticancer therapy, and optimal screening strategies are unknown. We sought to develop selective HBV screening strategies for patients who require systemic anticancer therapy.
Methods: This prospective cohort study included adults age ≥ 18 years with solid or hematologic malignancies who received systemic anticancer therapy at a comprehensive cancer center during 2013 and 2014. Patients underwent hepatitis B surface antigen, hepatitis B core antibody, and hepatitis B surface antibody testing, and completed a 19-question modified Centers for Disease Control and Prevention (CDC) HBV survey. Multivariable models that predict chronic or past HBV infection were developed and validated using bootstrapping.
Results: A total of 2,124 patients (mean age, 58 ± 13 years) completed the risk survey and HBV testing. Of these, 54% were women; 77% were non-Hispanic white, 11% Hispanic, 8% black, and 4% Asian; and 20% had a hematologic malignancy and 80% a solid tumor. Almost 12% were born outside the United States. The prevalence was 0.3% for chronic HBV infection and 6% for past HBV infection. Significant predictors of positive hepatitis B surface antigen or hepatitis B core antibody tests were as follows: men who had sex with men, black or Asian race, birthplace outside the United States, parent's birthplace outside the United States, household exposure to HBV, age ≥ 50 years, and history of injection drug use. The area under the receiver operating characteristic curve of the model on the basis of these seven predictors was 0.79 (95% CI, 0.73 to 0.82). The modified CDC survey and brief tools with fewer than seven questions yielded similar false-negative rates (0% and 0% to 0.7%, respectively).
Conclusion: An internally validated risk tool performed as well as the modified CDC survey; however, more than 90% of patients who completed the tool would still require HBV testing. Universal HBV testing is more efficient than risk-based screening.