Predicting the On-Study Relapse Rate for Multiple Sclerosis Patients in Clinical Trials

Background: The annual relapse rate has been commonly used as a primary efficacy endpoint in phase III multiple sclerosis (MS) clinical trials. The aim of this study was to determine the relative contribution of different possible prognostic factors available at baseline to the on-study relapse rate in MS. Methods: A total of 821 patients from the placebo arms of the Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) database were available for this analysis. The univariate relationships between on-study relapse rate and the baseline demographic, clinical, and MRI-based predictors were assessed. The multiple relationships were then examined using a Poisson regression model. Two predictor subsets were selected. Subset 1 included age at disease onset, disease duration, gender, Expanded Disability Status Scale (EDSS) at baseline, number of relapses in the last 24 months prior to baseline, and the disease course (RR and SP). Subset 2 consisted of Subset 1 plus gadolinium enhancement status in MRI. The number of patients for developing the models with no missing values was 727 for Subset 1 and 306 for Subset 2. Results:The univariate relationships show that the on-study relapse rate was higher for younger and for female patients, for RR patients than for SP patients, and for patients with positive enhancement status at entry (Wilcoxon test, p<0.05). A higher on-study relapse rate was associated with a shorter disease duration, lower entry EDSS, more pre-study relapses and more enhancing lesions in T1 at entry. The fitted Poisson model shows that disease duration (estimate=-0.02) and previous relapse number (estimate=0.59 for 1, 0.91 for 2 and 1.45 for 3 or more relapses vs 0 relapse) remain. We were able to confirm these findings in a second, independent dataset. Conclusions: The relapse number prior to entry into clinical trials together with disease duration are the best predictors for the on-study relapse rate. Disease course and gadolinium enhancement status, given the other covariates, have no significant influence on the on-study relapse rate

Border, Border, Wide and Far, How We Wonder What You Are

This paper exploits a three-dimensional panel data set of prices on 27 traded goods, over 88 quarters, across 96 cities in the U.S. and Japan. We present evidence that the distribution of intra-national real exchange rates is substantially less volatile and on average closer to zero, than the comparable distribution for international relative prices. We also show that an equally-weighted average of good-level real exchange rates tracks the nominal exchange rate well, suggesting strong evidence of sticky prices. We turn next to economic explanations for the dynamics of this so-called "Border" effect. Focusing on dispersion in prices between city pairs, we confirm previous findings that crossing national borders adds significantly to price dispersion. Using our point estimates crossing the U.S.-Japan "Border" is equivalent to adding between 2.5 and 13 million miles to the cross-country volatility of relative prices. We make a direct and explicit inference on the influence of shipping costs, distance, exchange rate and relative wage variability on the "Border" effect. In our calculations, the "Border" effect disappears after controlling for these additional variables.

The Micro-foundations of Big Mac Real Exchange Rates

The real exchange rate is said to be the single most important price in an economy. While we used to think that we knew what explained its movements (e.g., the Balassa-Samuelson effect), the recent much-cited result by Engel (1999) proposes a serious reinterpretation – i.e., nearly 100% of the movements in the U.S. real exchange rate are explained by deviations from the law of one price. Engel’s finding holds even in the medium run, when movements in the relative price of non-tradables between countries, were thought to be of paramount importance. In this project, we study the movement of real exchange rates based on the prices of Big Macs (which we show are highly correlated with the CPIbased real exchange rates). Our main innovation is to match these prices to the prices of individual ingredients (ground beef, bread, lettuce, labor cost, rent, etc.) in 34 countries during 1990–2002. There are a number of advantages associated with our approach. First, unlike the CPI real exchange rate, we can measure the Big Mac real exchange rate in levels in an economically meaningful way. Second, unlike the CPI real exchange rate for which the attribution to tradable and non-tradable components involves assumptions on the weights and the functional form, we (almost) know the exact composition of a Big Mac, and can estimate the tradable and non-tradable components relatively precisely. Third, we can study the dynamics of the real exchange rate in a setting that is free of the productaggregation bias (argued by Imbs, Mumtaz, Ravn, and Rey, 2002, to be important in studies on CPI real exchange rates), the temporal aggregation bias (argued to be important by Taylor, 2001), or the bias generated by non-compatible consumption baskets across countries. Fourth, we show that Engel's result that deviation from the law of one price is all that matters does not hold generally. Furthermore, deviations from his result can be systematically explained.Real exchange rates; TAR models

Insignificant and Inconsequential Hysteresis: The Case of the U.S. Bilateral Trade

This paper casts doubt on the validity of the hysteresis hypothesis as an explanation of the persistent U.S. trade deficits in the 1980s. We propose two tests to investigate two different implications of the hypothesis. The first implication is that cumulative changes in exchange rates, in addition to current exchange rate levels, are important determinants of trade flows. The second implication is that foreign exporting firms' perceptions of exchange rate volatility will affect their decisions to enter or exit the market. We find little support for either aspect of the hysteresis hypothesis.

Increasing occurrence of cold and warm extremes during the recent global warming slowdown.

The recent levelling of global mean temperatures after the late 1990s, the so-called global warming hiatus or slowdown, ignited a surge of scientific interest into natural global mean surface temperature variability, observed temperature biases, and climate communication, but many questions remain about how these findings relate to variations in more societally relevant temperature extremes. Here we show that both summertime warm and wintertime cold extreme occurrences increased over land during the so-called hiatus period, and that these increases occurred for distinct reasons. The increase in cold extremes is associated with an atmospheric circulation pattern resembling the warm Arctic-cold continents pattern, whereas the increase in warm extremes is tied to a pattern of sea surface temperatures resembling the Atlantic Multidecadal Oscillation. These findings indicate that large-scale factors responsible for the most societally relevant temperature variations over continents are distinct from those of global mean surface temperature