Specific power calculations for magnetic resonance imaging (MRI) in monitoring active relapsing-remitting multiple sclerosis (MS): implications for phase II therapeutic trials

MRI-based clinical trials in relapsing-remitting MS: new sample size calculations based on a longitudinal model

BACKGROUND

Sample sizes for magnetic resonance imaging (MRI)-based clinical trials in multiple sclerosis (MS) generally assume that lesion counts are reasonably described by the negative binomial (NB) model.

OBJECTIVE

This study aimed to assess the appropriateness of the NB model for lesion count data and to provide sample sizes for placebo-controlled, MRI-based clinical trials in relapsing-remitting MS using a more realistic model.

METHODS

The fit of the NB model in each arm of five MS clinical trials was assessed using Pearson's chi-squared statistic. Required sample sizes associated with various tests of treatment effect were estimated by simulating data from a new, longitudinal model for repeated lesion count data on individual patients.

RESULTS

Evidence (p < 0.05) against the NB model was found in at least one arm of four of the five trials. If a trial is designed using this model but the resulting clinical data do not follow its assumptions then this trial can be seriously under-powered for assessing differences in mean lesion counts.

CONCLUSION

Sample sizes based on the longitudinal model are more realistic and often smaller than those previously reported using the NB model.

Inferences and Power Analysis Concerning Two Negative Binomial Distributions with An Application to MRI Lesion Counts Data

In comparing the mean count of two independent samples, some practitioners would use the t-test or the Wilcoxon rank sum test while others may use methods based on a Poisson model. It is not uncommon to encounter count data that exhibit overdispersion where the Poisson model is no longer appropriate. This paper deals with methods for overdispersed data using the negative binomial distribution resulting from a Poisson-Gamma mixture. We investigate the small sample properties of the likelihood-based tests and compare their performances to those of the t-test and of the Wilcoxon test. We also illustrate how these procedures may be used to compute power and sample sizes to design studies with response variables that are overdispersed count data. Although methods are based on inferences about two independent samples, sample size calculations may also be applied to problems comparing more than two independent samples. It will be shown that there is gain in efficiency when using the likelihood-based methods compared to the t-test and the ilcoxon test. In studies where each observation is very costly, the ability to derive smaller sample size estimates with the appropriate tests is not only statistically, but also financially, appealing.

Glial toxicity in urine and multiple sclerosis

The biochemical and biological characterization of a cytotoxic activity targeting macroglial cells (oligodendrocytes and astrocytes), in moncyte cultures and in CSF of a patient with multiple sclerosis, has previously been described. In further studies, cell-based tests have shown a good correlation between this glial cytotoxic (gliotoxic) activity, in CSF or in urine, and MS. We now present results obtained with urine samples from 102 MS patients, 51 patients with other neurological disease and 35 healthy subjects using a bioassay set up for the detection of an apoptosis-like effect induced in a glial cell-line. Significant gliotoxicity was detected in urine from 74/102 MS patients while only 4/51 neurological controls (P>0.001) and never in healthy subjects (P>0.001). Given the statistical tendency provided by this bioassay and its technical limitations for routine testing, it is now used for monitoring the molecular characterization of this 'gliotoxic factor'. Its replacement by a specific immunoassay could provide more accurate routine techniques for the detection of this biological marker in MS.

Modelling new enhancing MRI lesion counts in multiple sclerosis

Magnetic resonance imaging (MRI) has been established as the most relevant paraclinical tool for diagnosing and monitoring multiple sclerosis (MS). In this context, counting the number of new enhancing lesions on monthly MRI scans is widely used as a surrogate marker of MS activity when evaluating the effect of treatments. In this study, we investigated whether parametric models based on mixed Poisson distributions (the Negative Binomial (NB) and the Poisson-Inverse Gaussian (P-IG) distributions) were able to provide adequate fitting of new enhancing lesion counts in MS. We found that the NB model gave good approximations in relapsing-remitting and secondary progressive MS patients not selected for baseline MRI activity, whereas the P-IG distribution modelled better new enhancing lesion counts in relapsing-remitting MS patients selected for baseline activity. This study shows that parametric modelling for MS new enhancing lesion counts is feasible. This approach should provide more targeted tools for the design and the analysis of MRI monitored clinical trials in MS.

Clinical trials of multiple sclerosis monitored with enhanced MRI: new sample size calculations based on large data sets

OBJECTIVE

A new parametric simulation procedure based on the negative binomial (NB) model was used to evaluate the sample sizes needed to achieve optimal statistical powers for parallel groups (with (PGB) and without (PG) a baseline correction scan). It was also used for baseline versus treatment (BVT) design clinical trials in relapsing-remitting (RR) and secondary progressive (SP) multiple sclerosis (MS), when using the number of new enhancing lesions seen on monthly MRI of the brain as the measure of outcome.

METHODS

MRI data obtained from 120 untreated patients with RRMS selected for the presence of MRI activity at baseline, 66 untreated and unselected patients with RRMS, and 81 untreated and unselected patients with SPMS were fitted using an NB distribution. All these patients were scanned monthly for at least 6 months and were all from the placebo arms of three large scale clinical trials and one natural history study. The statistical powers were calculated for durations of follow up of 3 and 6 months.

RESULTS

The frequency of new enhancing lesions in patients with SPMS was lower, but not significantly different, from that seen in unselected patients with RRMS. As expected, enhancement was more frequent in patients with RRMS selected for MRI activity at baseline than in the other two patient groups. As a consequence, the estimated sample sizes needed to detect treatment efficacy in selected patients with RRMS were smaller than those of unselected patients with RRMS and those with SPMS. Baseline correction was also seen to reduce the sample sizes of PG design trials. An increased number of scans reduced the sample sizes needed to perform BVT trials, whereas the gain in power was less evident in PG and PGB trials.

CONCLUSION

This study provides reliable estimates of the sample sizes needed to perform MRI monitored clinical trials in the major MS clinical phenotypes, which should be useful for planning future studies.

Enhanced magnetic resonance imaging in multiple sclerosis

Gadolinium-enhanced magnetic resonance imaging (MRI) is very sensitive in the detection of active lesions of multiple sclerosis (MS) and has become a valuable tool to monitor the evolution of the disease either natural or modified by treatment. In the past few years, several studies, on the one hand, have assessed several ways to increase the sensitivity of enhanced MRI to disease activity and, on the other, have investigated in vivo the nature and evolution of enhancing lesions using different non-conventional MR techniques to better define the relationship between enhancement and tissue loss in MS. The present review is a summary of these studies whose results are discussed in the context of MS clinical trial planning and monitoring. Multiple Sclerosis (2000) 6 320 - 326

MRI in multiple sclerosis: correlation with expanded disability status scale (EDSS)

Magnetic resonance (MR) imaging is very sensitive in showing disseminated MS lesions. Subclinical MR progression occurs frequently, explaining why MR is now used to monitor treatment, even without measurable consequences, of new MR lesions to the patient at this moment. In the light of this clinico-radiological paradox, the significance of MR in MS is discussed, particularly in relation with the expanded disability status scale (EDSS). Gadolinium-enhancing lesions correlate with the occurrence of relapses, CSF myelin breakdown products and, in patients with relapsing-remitting disease, with higher EDSS. However, the predictive value of the frequency of enhancement for changes in EDSS is only weak. For conventional T2-weighted MR imaging, the cross-sectional correlation with EDSS varies between 0.15 and 0.60, and is limited mainly by the inherent lack of tissues specificity of T2-weighted images. Both T1 black holes and magnetisation transfer (MT) parameters show a better correlation with EDSS; it should be noted that lesions in which those abnormalities are found go through an initial phase of enhancement as well. For T1 black holes, a correlation up to 0.81 has been reported for SP patients. Post-mortem studies show that black holes and low MT ratios are in vivo markers of axonal loss. Preliminary data indicate that progressive atrophy also correlates with progression on the EDSS scale. More should be learned about the fate of new MR lesion with regards to development of axonal loss, which at present is difficult to predict in the enhancing stage. The existence of escape mechanisms, including remyelination, make a simple correlation with EDSS extremely unlikely, and perhaps not even desirable. Nevertheless, while the clinical effect of a given new lesion may be difficult to ascertain, the absence of (new) MR lesions is prognostically favourable, as will be the degree to which new lesions are prevented by treatment.

Statistical power of MRI monitored trials in multiple sclerosis: new data and comparison with previous results

OBJECTIVES

To evaluate the durations of the follow up and the reference population sizes needed to achieve optimal and stable statistical powers for two period cross over and parallel group design clinical trials in multiple sclerosis, when using the numbers of new enhancing lesions and the numbers of active scans as end point variables.

METHODS

The statistical power was calculated by means of computer simulations performed using MRI data obtained from 65 untreated relapsing-remitting or secondary progressive patients who were scanned monthly for 9 months. The statistical power was calculated for follow up durations of 2, 3, 6, and 9 months and for sample sizes of 40-100 patients for parallel group and of 20-80 patients for two period cross over design studies. The stability of the estimated powers was evaluated by applying the same procedure on random subsets of the original data.

RESULTS

When using the number of new enhancing lesions as the end point, the statistical power increased for all the simulated treatment effects with the duration of the follow up until 3 months for the parallel group design and until 6 months for the two period cross over design. Using the number of active scans as the end point, the statistical power steadily increased until 6 months for the parallel group design and until 9 months for the two period cross over design. The power estimates in the present sample and the comparisons of these results with those obtained by previous studies with smaller patient cohorts suggest that statistical power is significantly overestimated when the size of the reference data set decreases for parallel group design studies or the duration of the follow up decreases for two period cross over studies.

CONCLUSIONS

These results should be used to determine the duration of the follow up and the sample size needed when planning MRI monitored clinical trials in multiple sclerosis.

Predictive value of gadolinium-enhanced magnetic resonance imaging for relapse rate and changes in disability or impairment in multiple sclerosis: a meta-analysis. Gadolinium MRI Meta-analysis Group

BACKGROUND

Reliable prognostic factors are lacking for multiple sclerosis (MS). Gadolinium enhancement in magnetic resonance imaging (MRI) of the brain detects with high sensitivity disturbance of the blood-brain barrier, an early event in the development of inflammatory lesions in MS. To investigate the prognostic value of gadolinium-enhanced MRI, we did a meta-analysis of longitudinal MRI studies.

METHODS

From the members of MAGNIMS (European Magnetic Resonance Network in Multiple Sclerosis) and additional centres in the USA, we collected data from five natural-course studies and four placebo groups of clinical trials completed between 1992 and 1995. We included a total of 307 patients, 237 with relapsing disease course and 70 with secondary progressive disease course. We investigated by regression analysis the relation between initial count of gadolinium-enhancing lesions and subsequent worsening of disability or impairment as measured by the expanded disability status scale (EDSS) and relapse rate.

FINDINGS

The relapse rate in the first year was predicted with moderate ability by the mean number of gadolinium-enhancing lesions in monthly scans during the first 6 months (relative risk per five lesions 1.13, p=0.023). The predictive value of the number of gadolinium-enhancing lesions in one baseline scan was less strong. The best predictor for relapse rate was the variation (SD) of lesion counts in the first six monthly scans which allowed an estimate of relapse in the first year (relative risk 1.2, p=0.020) and in the second year (risk ratio=1.59, p=0.010). Neither the initial scan nor monthly scans over six months were predictive of change in the EDSS in the subsequent 12 months or 24 months. The mean of gadolinium-enhancing-lesion counts in the first six monthly scans was weakly predictive of EDSS change after 1 year (odds ratio=1.34, p=0.082) and 2 years (odds ratio=1.65, p=0.049).

INTERPRETATION

Although disturbance of the blood-brain barrier as shown by gadolinium enhancement in MRI is a predictor of the occurrence of relapses, it is not a strong predictor of the development of cumulative impairment or disability. This discrepancy supports the idea that variant pathogenetic mechanisms are operative in the occurrence of relapses and in the development of long-term disability in MS.

Modelling MRI enhancing lesion counts in multiple sclerosis using a negative binomial model: implications for clinical trials

In multiple sclerosis (MS) the number of new enhancing lesions seen on monthly magnetic resonance imaging (MRI) scans is the most widely used response variable in MRI-monitored studies of experimental treatments. However, no statistical model has been proposed to describe the distribution of the number of such lesions across MS patients. This article briefly summarizes the statistical models for counted data. The negative binomial (NB) model is proposed to fit the number of new enhancing lesions counted in a set of 56 untreated MS patients followed for 9 months. It is shown that the large variability present in this data set is better addressed by the NB model (residual deviance=66.6, 54 degrees of freedom) than by the Poisson model (residual deviance=1830.1, 55 degrees of freedom). Applications of the parametrization of lesion counts are discussed, and an example related to computer simulations for the sample size estimation is presented.