@article { ISI:000354249800006,
	title = {A flexible mixed-effect negative binomial regression model for detecting unusual increases in MRI lesion counts in individual multiple sclerosis patients},
	journal = {Statistics in Medicine},
	volume = {34},
	number = {13},
	year = {2015},
	pages = {2165-2180},
	publisher = {WILEY-BLACKWELL},
	address = {111 RIVER ST, HOBOKEN 07030-5774, NJ USA},
	abstract = {<p>We develop a new modeling approach to enhance a recently proposed method to detect increases of contrast-enhancing lesions (CELs) on repeated magnetic resonance imaging, which have been used as an indicator for potential adverse events in multiple sclerosis clinical trials. The method signals patients with unusual increases in CEL activity by estimating the probability of observing CEL counts as large as those observed on a patient{\textquoteright}s recent scans conditional on the patient{\textquoteright}s CEL counts on previous scans. This conditional probability index (CPI), computed based on a mixed-effect negative binomial regression model, can vary substantially depending on the choice of distribution for the patient-specific random effects. Therefore, we relax this parametric assumption to model the random effects with an infinite mixture of beta distributions, using the Dirichlet process, which effectively allows any form of distribution. To our knowledge, no previous literature considers a mixed-effect regression for longitudinal count variables where the random effect is modeled with a Dirichlet process mixture. As our inference is in the Bayesian framework, we adopt a meta-analytic approach to develop an informative prior based on previous clinical trials. This is particularly helpful at the early stages of trials when less data are available. Our enhanced method is illustrated with CEL data from 10 previous multiple sclerosis clinical trials. Our simulation study shows that our procedure estimates the CPI more accurately than parametric alternatives when the patient-specific random effect distribution is misspecified and that an informative prior improves the accuracy of the CPI estimates. Copyright (c) 2015 John Wiley \&amp; Sons, Ltd.</p>
},
	keywords = {Dirichlet process, Longitudinal data, meta-analysis, Negative binomial, nonparametric Bayesian procedures, safety monitoring in clinical trials},
	doi = {10.1002/sim.6484},
	author = {Kondo, Y and Zhao, Y and Petkau, J}
}
@article {zhao_personalized_2015,
	title = {Personalized activity index, a new safety monitoring tool for multiple sclerosis clinical trials},
	journal = {Multiple Sclerosis Journal {\textendash} Experimental, Translational and Clinical},
	volume = {1},
	year = {2015},
	pages = {1-15},
	abstract = {<p>Background An abnormal increase of contrast-enhancing lesion (CEL) counts on frequent MRIs is interpreted as a signal of potential worsening in multiple sclerosis (MS) clinical trials. We demonstrate the utility of the MR personalized activity index (MR-pax) to identify such increases. Methods We analyzed a previous Phase II study in relapsing patients (n = 167) with MRIs at screening, baseline and months 1{\textendash}6. We performed five consecutive reviews at 90-day intervals. At each review, we evaluate the MR-pax for each patient and also identify those who meet the rule-of-five (an ad-hoc guideline currently in use). To evaluate its clinical relevance, we assess the relation between having a small MR-pax (<=0.05; indicating an unexpected CEL increase) and relapse status in the 12 weeks post-review. Results Of the 399 patient reviews, 35 cases met the rule-of-five; 35 had an MR-pax <= 0.05; 18 met both criteria. The proportions experiencing clinical relapse are 63\% among those meeting the rule-of-five, 61\% among those with MR-pax <=0.05, and 83\% for those meeting both criteria, more than double the rate of those meeting neither criterion (40\%). Conclusion A guideline combining this new personalized index and the existing threshold-based criterion is able to better identify patients with a higher risk of experiencing relapses.</p>
},
	keywords = {contrast-enhancing lesions, MRI, multiple sclerosis, safety monitoring in clinical trials},
	doi = {10.1177/2055217315577829},
	url = {http://mso.sagepub.com/content/1/2055217315577829},
	author = {Zhao, Y and Kondo, Y and Traboulsee, A and Li, DKB and Riddehough, A and Petkau, A.John}
}
