Studies of the effects of exposures after cancer diagnosis on cancer recurrence and survival can provide important information to the growing group of cancer survivors. Observational studies that address this issue generally fall into one of two categories: 1) those using health plan automated data that contain "continuous" information on exposures, such as studies that use pharmacy records; and 2) survey or interview studies that collect information directly from patients once or periodically postdiagnosis. Reverse causation, confounding, selection bias, and information bias are common in observational studies of cancer outcomes in relation to exposures after cancer diagnosis. We describe these biases, focusing on sources of bias specific to these types of studies, and we discuss approaches for reducing them. Attention to known challenges in epidemiologic research is critical for the validity of studies of postdiagnosis exposures and cancer outcomes.