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The one-sample log-rank test is the preferred method for analysing the outcome of single-arm survival trials. It compares the survival distribution of patients with a prefixed reference survival curve that usually represents the expected outcome under standard of care. However, classical one-sample log-rank tests assume that the reference curve is known, ignoring that it is frequently estimated from historical data and therefore susceptible to sampling error. Neglecting the variability of the reference curve can lead to an inflated type I error rate, as shown in a previous paper. Here, we propose a new survival test that allows to account for the sampling error of the reference curve without knowledge of the full underlying historical survival time data. Our new test allows to perform a valid historical comparison of patient survival times when only a historical survival curve rather than the full historic data is available. It thus applies in settings where the two-sample log-rank test is not applicable as method of choice due to non-availability of historic individual patient survival time data. We develop sample size calculation formulas, give an example application and study the performance of the new test in a simulation study.

The one-sample log-rank test is the method of choice for single-arm Phase II trials with time-to-event endpoint. It allows to compare the survival of patients to a reference survival curve that typically represents the expected survival under standard of care. The one-sample log-rank test, however, assumes that the reference survival curve is known. This ignores that the reference curve is commonly estimated from historic data and thus prone to sampling error. Ignoring sampling variability of the reference curve results in type I error rate inflation. We study this inflation in type I error rate analytically and by simulation. Moreover we derive the actual distribution of the one-sample log-rank test statistic, when the sampling variability of the reference curve is taken into account. In particular, we provide a consistent estimate of the factor by which the true variance of the one-sample log-rank statistic is underestimated when reference curve sampling variability is ignored. Our results are further substantiated by a case study using a real world data example in which we demonstrate how to estimate the error rate inflation in the planning stage of a trial.

Young children with brain tumours are at high risk of developing treatment-related sequelae. We aimed to assess neuropsychological outcomes 5 years after treatment. This cross-sectional study included children under 4 years of age with medulloblastoma (MB) or ependymoma (EP) enrolled in the German brain tumour trials HIT2000 and HIT-REZ2005. Testing was performed using the validated Wuerzburg Intelligence Diagnostics (WUEP-D), which includes Kaufman-Assessment-Battery, Coloured Progressive Matrices, Visual-Motor Integration, finger tapping "Speed", and the Continuous Performance Test. Of 104 patients in 47 centres, 72 were eligible for analyses. We assessed whether IQ was impacted by disease extent, disease location, patient age, gender, age at surgery, and treatment (chemotherapy with our without craniospinal irradiation [CSI] or local radiotherapy [LRT]). Median age at surgery was 2.3 years. Testing was performed at a median of 4.9 years after surgery. Patients with infratentorial EPs (treated with LRT) scored highest in fluid intelligence (CPM 100.9±16.9, mean±SD); second best scores were achieved by patients with MB without metastasis treated with chemotherapy alone (CPM 93.9±13.2), followed by patients with supratentorial EPs treated with LRT. In contrast, lowest scores were achieved by patients that received chemotherapy and CSI, which included children with metastasised MB and those with relapsed MB M0 (CPM 71.7±8.0 and 73.2±21.8, respectively). Fine motor skills were reduced in all groups. Multivariable analysis revealed that type of treatment had an impact on IQ, but essentially not age at surgery, time since surgery or gender. Our results confirm previous reports on the detrimental effects of CSI in a larger cohort of children. Comparable IQ scores in children with MB treated only with chemotherapy and in children with EP suggest that this treatment strategy represents an attractive option for children who have a high chance to avoid application of CSI. Longitudinal follow-up examinations are warranted to assess long-term neuropsychological outcomes.

The 'weekend effect' describes increased adverse outcomes after weekend hospitalization. We examined weekend-weekday differences in the outcome of 580 patients following renal transplantation (RTx, brain dead donors) between January 2007 and December 2014 at our center. 3-year patient and graft survival, incidence of delayed graft function (DGF), acute rejections and estimated glomerular filtration rate (eGFR, CKD-EPI) at 1 year as well as surgical complications were assessed. Of all 580 transplants, 416 (71.7%) were performed on weekdays (Monday-Friday) and 164 (28.3%) on weekends (Saturday-Sunday). 3-year patient and graft survival, frequencies of DGF, acute rejections and 1-year eGFR as well as length of hospital stay were similar between RTx patients transplanted on weekdays or weekends, respectively. However, a noticeable difference was detected with regard to surgical complications which were more frequent in RTx patients transplanted on weekends. All results remained consistent across all definitions of weekend status. Our results suggest that weekend transplant status does not affect functional short-term and long-term outcomes after RTx. The standardized protocols and operationalized processes applied in RTx might contribute to this finding and may provide a model for other medical procedures that are performed on weekends to improve efficiency and outcomes. The higher rate of surgical complications after weekend RTx needs further elaboration to fully assess the presence of a weekend effect in RTx.

Cardiovascular disease (CVD) is the leading cause of death after renal transplantation with a high prevalence in dialysis patients. It is still a matter of debate how to assess the cardiovascular risk in kidney transplant candidates. Several approaches and scores exist and found their way into the guidelines.We herein assessed PROCAM, Framingham, ESC-SCORE and our own dedicated algorithm in patients applying for renal transplantation at our transplantation center between July 2006 and August 2009. Data of 347 consecutive patients were recorded at baseline and during a follow-up of 4.1 years regarding cardiovascular (CV) events and event-free and overall survival. During follow-up 31 (8.9%) patients died, 24 (6.9%) myocardial infarctions occurred and 19 (5.5%) patients received a new diagnosis of cerebrovascular disease. Predictors for event-free survival identified by univariable Cox regression analysis were age at start of dialysis, ESC-SCORE as well as our own score. Final multivariable model with a stepwise model building procedure revealed age at start of dialysis and smoking to be prognostic for event-free (hazard ratio 1.07/year and 2.15) and overall survival (1.10/year and 3.72).Comparison of CV risk assessment scores showed that ESC-SCORE most robustly predicted event-free and overall survival in our cohort. We conclude that CV risk assessment by ESC-SCORE can be reasonably performed in kidney transplant candidates.