Dynamic prediction of recurrent events data by landmarking with application to a follow-up study of patients after kidney transplant.

This paper extends dynamic prediction by landmarking to recurrent event data. The motivating data comprised post-kidney transplantation records of repeated infections and repeated measurements of multiple markers. At each landmark time point ts, a Cox proportional hazards model with a frailty term was fitted using data of individuals who were at risk at landmark s. This model included the time-updated marker values at ts as time-fixed covariates. Based on a stacked data set that merged all landmark data sets, we considered supermodels that allow parameters to depend on the landmarks in a smooth fashion. We described and evaluated four ways to parameterize the supermodels for recurrent event data. With both the study data and simulated data sets, we compared supermodels that were fitted on stacked data sets that consisted of either overlapping or non-overlapping landmark periods. We observed that for recurrent event data, the supermodels may yield biased estimates when overlapping landmark periods are used for stacking. Using the best supermodel amongst the ones considered, we dynamically estimated the probability to remain infection free between ts and a prediction horizon thor, conditional on the information available at ts.

Immunization after renal transplantation: current clinical practice.

BACKGROUND: The use of potent immunosuppressive drugs and increased travel by renal transplant recipients (RTR) has augmented the risk for infectious complications. Immunizations and changes in lifestyle are protective. The Kidney Disease: Improving Global Outcomes (KDIGO) Transplant Work Group has developed guidelines on vaccination following solid organ transplantation. The degree of adherence to these guidelines is unknown, as is which barriers must be overcome to improve adherence. METHODS: We performed a cross-sectional national survey among Dutch nephrologists to assess vaccination policy and adherence to the KDIGO guidelines. In addition, to investigate awareness and attitude of RTR regarding their risk of infection, we performed a cross-sectional survey of RTR in our outpatient clinic. RESULTS: A total of 132 (63%) nephrologists completed the survey. Reported immunization rates were 90.8% for influenza and 27.3% for hepatitis B. However, pneumococcal, tetanus toxoid, and meningococcal immunization rates were low. Twenty-seven percent of respondents were familiar with the guideline contents. The most frequent perceived barrier to guideline adherence was expectation of low effectiveness. A total of 403 RTR (62%) completed the survey. Sixty-eight percent perceived more risk for complicated infection. A significant correlation was found between education level and variables concerning awareness and attitude toward risk of infection. CONCLUSIONS: Our results show that nephrologists' knowledge of and adherence to the recommendations regarding immunization after renal transplantation is suboptimal. Most Dutch RTR are aware of their increased risk and the possible seriousness of infectious complications. However, their behavior does not match their awareness. This disparity points to an important role for nephrologists in providing adequate counseling.