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The aim of this work was to assess the relationship between the absolute lymphocyte count (ALC), and disability (as measured by the Expanded Disability Status Scale [EDSS]) and occurrence of relapses, 2 efficacy endpoints, respectively, in patients with remitting-relasping multiple sclerosis. Data for ALC, EDSS, and relapse rate were available from 1319 patients receiving placebo and/or cladribine tablets. Pharmacodynamic models were developed to characterize the time course of the endpoints. ALC-related measures were then evaluated as predictors of the efficacy endpoints. EDSS data were best fitted by a model where the logit-linear disease progression is affected by the dynamics of ALC change from baseline. Relapse rate data were best described by the Weibull hazard function, and the ALC change from baseline was also found to be a significant predictor of time to relapse. Presented models have shown that once cladribine exposure driven ALC-derived measures are included in the model, the need for drug effect components is of less importance (EDSS) or disappears (relapse rate). This simplifies the models and theoretically makes them mechanism specific rather than drug specific. Having a reliable mechanism-specific model would allow leveraging historical data across compounds, to support decision making in drug development and possibly shorten the time to market. © 2018, The American College of Clinical Pharmacology.
Accurate time series representation of paleoclimatic proxy records is challenging because such records involve dating errors in addition to proxy measurement errors. Rigorous attention is rarely given to age uncertainties in paleoclimatic research, although the latter can severely bias the results of proxy record analysis. Here, we introduce a Bayesian approach to represent layer-counted proxy records - such as ice cores, sediments, corals, or tree rings - as sequences of probability distributions on absolute, error-free time axes. The method accounts for both proxy measurement errors and uncertainties arising from layer-counting-based dating of the records. An application to oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record reveals that the counting errors, although seemingly small, lead to substantial uncertainties in the final representation of the oxygen isotope ratios. In particular, for the older parts of the NGRIP record, our results show that the total uncertainty originating from dating errors has been seriously underestimated.
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