Significantly different survival can be expected depending on individual tumor histopathology, tumor size, age at diagnosis, and treatment modality.

Objective Hepatitis B virus (HBV) infection remains a significant public health challenge, particularly for immunocompromised patients. Our aim was to evaluate the serologic immunity in immunocompromised rheumatology and inflammatory bowel disease (IBD) patients, assess factors for serologic non-immunity and evaluate their response to one HBV booster dose. Methods Immunocompromised rheumatology and IBD patients with completed HBV screening were identified. A chart review was performed to collect demographics, clinical information, baseline HBV serology results, and serologic response to booster vaccination. Serologic nonimmunity was defined as a negative/indeterminate hepatitis B surface antibody (anti-HBs) level. Results Among 580 patients, 71% were non-immune. The highest portion of non-immune patients were 11-18 years old (p 0.004). There was no significant difference between immune and non-immune patients with regards to diagnosis (p 0.342), age at diagnosis (p 0.639), duration of treatment (p 0.069) or type of medications (p 0.080). Sixty-two percent of those who received a booster vaccine were re-screened, and most (68%) seroconverted. In those 18 years or older, only half seroconverted. Conclusion Results of this study support the benefit of HBV screening in immunosuppressed patients. Beginning at age 11 years most patients lacked serologic immunity to HBV. Seroconversion for most patients 11-18 years occurred after one booster vaccine. Thus, for immunocompromised patients without recent HBV serologic data, obtaining the HBV serology beginning at age 11 years might be considered. Those 18 years and older were least likely to seroconvert after one booster, indicating that they may benefit from receiving the three-dose HBV vaccine series.

This study proposes a Bayesian joint model with extended random effects structure that incorporates nested repeated measures and provides simultaneous inference on treatment effects over time and drop-out patterns. The proposed model includes flexible splines to characterize the circadian variation inherent in blood pressure sequences, and we assess the effectiveness of an intervention to resolve pediatric obstructive sleep apnea. We demonstrate that the proposed model and its conventional two-stage counterpart provide similar estimates of nighttime blood pressure but estimates on the mean evolution of daytime blood pressure are discrepant. Our simulation studies tailored to the motivating data suggest reasonable estimation and coverage probabilities for both fixed and random effects. Computational challenges of model implementation are discussed.