Association of baseline absolute neutrophil counts and survival in patients with metastatic colorectal cancer treated with second-line antiangiogenic therapies : exploratory analyses of the RAISE trial and validation in an electronic medical record data set

In the RAISE trial, ramucirumab+leucovorin/fluorouracil/irinotecan (FOLFIRI) improved the median overall survival (mOS) of patients with previously treated metastatic colorectal cancer versus patients treated with placebo+FOLFIRI but had a higher incidence of neutropaenia, leading to more chemotherapy dose modifications and discontinuations. Thus, we conducted an exploratory post-hoc analysis of RAISE and a retrospective, observational analysis of electronic medical record (EMR) data to determine and verify the association of neutropaenia, baseline absolute neutrophil count (ANC) and survival. The RAISE analysis used the study safety population (n=1057). IMS Health Oncology Database (IMS EMR) was the source for the real-world data set (n=617). RAISE patients with treatment-emergent neutropaenia had improved mOS compared with those without (ramucirumab arm: 16.1 vs 10.7 months, HR=0.57, p<0.0001; placebo arm: 12.7 vs 10.7 months, HR=0.76, p=0.0065). RAISE patients with low ANC versus high baseline ANC also had longer mOS (ramucirumab arm: 15.2 vs 8.9 months, HR=0.49, p<0.0001; placebo arm: 13.2 vs 7.3 months, HR=0.50, p<0.0001). The results were similar for IMS EMR low versus high baseline ANC (bevacizumab+FOLFIRI patients: 14.9 vs 7.7 months, HR=0.59, p<0.0001; FOLFIRI alone: 14.6 vs 5.4 months, HR=0.37, p<0.0001). Patients in the RAISE trial with low baseline ANC were more likely to develop neutropaenia (OR: ramucirumab arm=2.62, p<0.0001; placebo arm=2.16, p=0.0003). Neutropaenia during treatment, and subsequent dose modifications or discontinuations, do not compromise treatment efficacy. Baseline ANC is a strong prognostic factor for survival and is associated with treatment-emergent neutropaenia in the analysed population. , Results

Application of a generalized random effects regression model for cluster-correlated longitudinal data to a school-based smoking prevention trial

In cluster-randomized trials, groups of subjects (clusters) are assigned to treatments, whereas observations are taken on the individual subjects. Since observations on subjects in the same cluster are typically more similar than observations from different clusters, analyses of such data must take intracluster correlation into account rather than assuming independence among all observations. Random effects models are useful for this purpose. The problem becomes more complicated if, in addition, repeated observations are taken on subjects over time. This introduces intraindividual correlation, which is typical for longitudinal studies. The Waterloo Smoking Prevention Project, study 3 (WSPP3), 1989-1996, is a study giving rise to cluster-correlated longitudinal data, where schools were randomized to either a smoking intervention program or to a control condition. Smoking status was assessed on grade 6 students in these schools, with annual follow-up observations throughout elementary and high school years. The authors illustrate the use of a generalized random effects model for analyzing this type of data. This model obtains appropriate estimates and standard errors for both individual-level covariates and those at the level of the cluster

On the correspondence between population-averaged models and a class of cluster-specific models for correlated binary data

The relationship between marginal (population-averaged) models for cluster-correlated binary data, and a class of cluster-specific, logistic-normal random effects models is discussed. We show that random effects models can accomplish the same end as a more direct modelling of intra-cluster correlation, as in GEE.Clustered data Cluster-specific models Correlated binary responses Population-averaged models, Random effects models