Measuring Surgical Outcomes in Cervical Spondylotic Myelopathy Patients Undergoing Anterior Cervical Discectomy and Fusion: Assessment of Minimum Clinically Important Difference

Object

The concept of minimum clinically important difference (MCID) has been used to measure the threshold by which the effect of a specific treatment can be considered clinically meaningful. MCID has previously been studied in surgical patients, however few studies have assessed its role in spinal surgery. The goal of this study was to assess the role of MCID in patients undergoing anterior cervical discectomy and fusion (ACDF) for cervical spondylotic myelopathy (CSM).

Methods

Data was collected on 30 patients who underwent ACDF for CSM between 2007 and 2012. Preoperative and 1-year postoperative Neck Disability Index (NDI), Visual-Analog Scale (VAS), and Short Form-36 (SF-36) Physical (PCS) and Mental (MCS) Component Summary PRO scores were collected. Five distribution- and anchor-based approaches were used to calculate MCID threshold values average change, change difference, receiver operating characteristic curve (ROC), minimum detectable change (MDC) and standard error of measurement (SEM). The Health Transition Item of the SF-36 (HTI) was used as an external anchor.

Results

Patients had a significant improvement in all mean physical PRO scores postoperatively (p<0.01) NDI (29.24 to 14.82), VAS (5.06 to 1.72), and PCS (36.98 to 44.22). The five MCID approaches yielded a range of values for each PRO: 2.00–8.78 for PCS, 2.06–5.73 for MCS, 4.83–13.39 for NDI, and 0.36–3.11 for VAS. PCS was the most representative PRO measure, presenting the greatest area under the ROC curve (0.94). MDC values were not affected by the choice of anchor and their threshold of improvement was statistically greater than the chance of error from unimproved patients.

Conclusion

SF-36 PCS was the most representative PRO measure. MDC appears to be the most appropriate MCID method. When MDC was applied together with HTI anchor, the MCID thresholds were: 13.39 for NDI, 3.11 for VAS, 5.56 for PCS and 5.73 for MCS.     

Comparison and evaluation of lupus nephritis response criteria in lupus activity indices and clinical trials

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with diverse manifestations. Although the approval of new therapies includes only one agent in 50 years, a number of promising new drugs are in development. Lupus nephritis is a dreaded complication of SLE as it is associated with significant morbidity and mortality. Advancing the treatment of lupus nephritis requires well-designed clinical trials and this can be challenging in SLE. The major obstacles involve identifying the correct population of patients to enroll and ensuring that a clinically appropriate and patient-centered endpoint is being measured. In this review, we will first discuss the clinical utility of endpoints chosen to represent lupus nephritis in global disease activity scales. Second, we will review completed and active trials focused on lupus nephritis and discuss the endpoints chosen. There are many important lessons to be learned from existing assessment tools and clinical trials. Reviewing these points will help ensure that future efforts will yield meaningful disease activity measures and well-designed clinical trials to advance our understanding of lupus management.     

The future of aging therapies

Advances in understanding aging processes and their consequences are leading to the development of therapies to slow or reverse adverse changes formerly considered to be "normal" aging and processes that underlie multiple age-related conditions. Estimating the effectiveness of candidate aging therapies, whose effects on human aging may require many years to determine, is a particular challenge. Strategies for identifying candidate interventions can be developed through multiple approaches, including the screening of molecular targets and pathways in vitro and in animal models, informed as well by evidence from human genetic and epidemiologic data. A number of recently established programs and networks can serve as resources for such research. For all these research approaches, from in vitro molecular studies to clinical trials, contributions of cell and molecular biology are crucial and offer the prospect of therapeutic advances that address fundamental biological processes as well as the clinically important challenges of aging.     

An overview of statistical approaches for adaptive designs and design modifications

With adaptive design methods for clinical trials, design elements such as sample size or further interim sample sizes may be changed during the course of the trial depending on all previously collected data. The focus of the overview is on group sequential approaches where the types of adaptations need not be specified in advance. An overview of the different statistical approaches for adaptive design methods proposed in the literature is given, relations between these methods are described and some perspectives of application and for future research are discussed.     

BAFF and innate immunity: new therapeutic targets for systemic lupus erythematosus

Recently, the B cell has emerged as a cornerstone of systemic lupus erythematosus (SLE) pathogenesis. This has been highlighted by studies of the cytokine B-cell-activating factor of the tumour necrosis factor (TNF) family (BAFF), a crucial factor regulating B-cell maturation, survival and function. Overexpression of BAFF in mice leads to the development of an SLE-like disease, independent of T cells but instead relying on innate immunity mechanisms. Moreover, BAFF has been shown to be elevated in the serum of patients suffering from autoimmune conditions, especially SLE, and may correlate with disease activity. These findings challenge the previous notion that T:B-cell collaboration is the sole driver of SLE. In recent years, controlled trials have for the first time tested targeted therapeutics for SLE. However, agents designed to target B cells failed to meet primary endpoints in clinical trials in SLE, suggesting that a more complex role for B cells in SLE awaited elucidation. By contrast, on 9 March 2011, the US Food and Drug Administration approved belimumab, a fully human anti-BAFF monoclonal antibody, as a new B-cell-specific treatment for SLE. This article will review over 10 years of research on the BAFF system, key findings that led to this recent positive clinical outcome and propose a model potentially explaining why this B-cell-specific therapy has yielded positive results in clinical trials. We will also review promising therapies presently in clinical trials targeting innate immunity, which are likely to revolutionize SLE management towards a personalized and targeted therapy approach.     

Joint monitoring and prediction of accrual and event times in clinical trials

In many clinical trials, the primary endpoint is time to an event of interest, for example, time to cardiac attack or tumor progression, and the statistical power of these trials is primarily driven by the number of events observed during the trials. In such trials, the number of events observed is impacted not only by the number of subjects enrolled but also by other factors including the event rate and the follow‐up duration. Consequently, it is important for investigators to be able to monitor and predict accurately patient accrual and event times so as to predict the times of interim and final analyses and enable efficient allocation of research resources, which have long been recognized as important aspects of trial design and conduct. The existing methods for prediction of event times all assume that patient accrual follows a Poisson process with a constant Poisson rate over time; however, it is fairly common in real‐life clinical trials that the Poisson rate changes over time. In this paper, we propose a Bayesian joint modeling approach for monitoring and prediction of accrual and event times in clinical trials. We employ a nonhomogeneous Poisson process to model patient accrual and a parametric or nonparametric model for the event and loss to follow‐up processes. Compared to existing methods, our proposed methods are more flexible and robust in that we model accrual and event/loss‐to‐follow‐up times jointly and allow the underlying accrual rates to change over time. We evaluate the performance of the proposed methods through simulation studies and illustrate the methods using data from a real oncology trial.     

Effect of European Clinical Trials Directive on academic drug trials in Denmark: retrospective study of applications to the Danish Medicines Agency 1993-2006

Objective To determine the impact of the European Union’s Clinical Trials Directive on the number of academic drug trials carried out in Denmark.Design Retrospective review of applications for drug trials to the Danish Medicines Agency, 1993-2006.Review methods Applications for drug trials for alternate years were classified as academic or commercial trials. A random subset of academic trials was reviewed for number of participants in and intended monitoring of the trials.Results Academic and commercial drug trials showed an identical steady decline from 1993 to 2006 and no noticeable change after 2004 when good clinical practice became mandatory for academic trials.Conclusion The Clinical Trials Directive introduced in May 2004 to ensure good clinical practice for academic drug trials was not associated with a decline in research activity in Denmark; presumably because good clinical practice units had already been in place in Danish universities since 1999. With such an infrastructure academic researchers can do drug trials under the same regulations as drug companies.     

Adaptive treatment assignment methods and clinical trials.

This paper provides a general review of adaptive experimental designs which utilize accumulating information for assigning the best treatment to the most patients in clinical trials. The historical development of such methods is traced. Though the statistical literture on adaptive designs has developed rapidly and continues to grow, the methods are almost totally unused in practice. An extensive evaluation of why adaptive designs are rarely used in clinical trials is presented. It is asserted that most published methods have important deficiencies that render them unsuitable for application. Suggestions are offered for reorienting this area of research into directions that are potentially more useful for clinical trials.     

Validation of a parent-proxy, obesity-specific quality-of-life measure: sizing them up

The aims of the present study were to develop and validate a new obesity-specific, parent-proxy measure of health-related quality of life (HRQOL), Sizing Them Up. Participants included 220 obese youth (M(age) = 11.6 years, 68% female, 53% African American, M(BMI) = 36.7) and their primary caregivers (88% mothers). Primary caregivers completed a demographics questionnaire and two HRQOL measures: Sizing Them Up (obesity-specific) and PedsQL (generic). Youth height and weight were measured. Psychometric evaluation of Sizing Them Up was completed by conducting a factor analysis and determining internal consistency coefficients, test-retest reliability, convergent and discriminant validity, predictive validity, responsiveness to change, and minimal clinically important difference (MCID) scores. Sizing Them Up is a 22-item measure with six scales (i.e., Emotional Functioning, Physical Functioning, Teasing/Marginalization, Positive Social Attributes, Mealtime Challenges, and School Functioning) that account for 66% of the variance. The measure also includes an Adolescent Developmental Adaptation module. Sizing Them Up had internal consistency coefficients ranging from 0.59 to 0.91 and test-retest reliabilities ranging from 0.57 to 0.80. Validity was demonstrated by significant relations between a majority of Sizing Them Up scales and BMI z-scores. Sizing Them Up also demonstrated good convergent validity with other HRQOL measures and responsiveness to change related to weight loss for adolescents who had undergone bariatric surgery. Overall, Sizing Them Up is a reliable and valid parent-proxy measure of obesity-specific HRQOL that can be used in both clinical and research settings.     

Analyzing paired diagnostic studies by estimating the expected benefit

When the efficacy of a new medical drug is compared against that of an established competitor in a randomized controlled trial, the difference in patient‐relevant outcomes, such as mortality, is usually measured directly. In diagnostic research, however, the impact of diagnostic procedures is of an indirect nature as test results do influence downstream clinical decisions, but test performance (as characterized by sensitivity, specificity, and the predictive values of a procedure) is, at best, only a surrogate endpoint for patient outcome and does not necessarily translate into it. Not many randomized controlled trials have been conducted so far in diagnostic research, and, hence, we need alternative approaches to close the gap between test characteristics and patient outcomes. Several informal approaches have been suggested in order to close this gap, and decision modeling has been advocated as a means of obtaining formal approaches. Recently, the expected benefit has been proposed as a quantity that allows a simple formal approach, and we take up this suggestion in this paper. We regard the expected benefit as an estimation problem and consider two approaches to statistical inference. Moreover, using data from a previously published study, we illustrate the possible insights to be gained from the application of formal inference techniques to determine the expected benefit.     

Do stroke models model stroke?

Stroke is one of the leading causes of death worldwide and the biggest reason for long-term disability. Basic research has formed the modern understanding of stroke pathophysiology, and has revealed important molecular, cellular and systemic mechanisms. However, despite decades of research, most translational stroke trials that aim to introduce basic research findings into clinical treatment strategies – most notably in the field of neuroprotection – have failed. Among other obstacles, poor methodological and statistical standards, negative publication bias, and incomplete preclinical testing have been proposed as ‘translational roadblocks’. In this article, we introduce the models commonly used in preclinical stroke research, discuss some of the causes of failed translational success and review potential remedies. We further introduce the concept of modeling ‘care’ of stroke patients, because current preclinical research models the disorder but does not model care or state-of-the-art clinical testing. Stringent statistical methods and controlled preclinical trials have been suggested to counteract weaknesses in preclinical research. We conclude that preclinical stroke research requires (1) appropriate modeling of the disorder, (2) appropriate modeling of the care of stroke patients and (3) an approach to preclinical testing that is similar to clinical testing, including Phase 3 randomized controlled preclinical trials as necessary additional steps before new therapies enter clinical testing.     

The scope of mycoplasma contamination within the biopharmaceutical industry

Mycoplasma is well recognized as one of the most prevalent and serious microbial contaminants encountered within the manufacturing of biopharmaceuticals from the research phase to clinical development and production. The potential for mycoplasma contamination within cell culture systems was first identified by Robinson et al. in 1956 [1]. Presently, contamination rates in established cell cultures have been reported between 15 and 35% with considerably higher occurrence cited in certain selected populations [2]. In the last few years, there has been an expansion of diagnostic approaches for mycoplasma detection with the development and validation of rapid microbiological methods. The objective of this study was to determine current levels of mycoplasma infection of cell cultures, cell substrates and biologicals within a client based population. Retrospective comparison of 40,000 sample results was done to determine total contaminations rates amongst four (4) individual analytical assays. The establishment of reference data, such as existing contamination rates, becomes important in the critical appraisal of rapid microbiological methods for the detection of mycoplasma.     

Do we need new autoantibodies in lupus?

Systemic lupus erythematosus (SLE) is a clinically and serologically complex disease that demonstrates clinical, epidemiological and genetic differences among racial and ethnic groups. Some autoantibodies are useful for diagnosis of the illness. Others are clinically important because of associations with a particular manifestation of SLE. Antibodies to RNA helicase A (anti-RHA) comprise a newly described class of SLE autoantibodies. These antibodies have so far been found only in SLE patients and differ substantially in prevalence and nature between Mexican and white American SLE patients. Study of anti-RHA may provide insights into the origin of population differences in SLE.     

Gene therapy. Therapeutic approaches and implications

The present article is an overview of gene therapy with an emphasis on different approaches and its implications in the clinic. Genetic interventions have been applied to the diagnosis of and therapy for an array of human diseases. The initial concept of gene therapy was focused on the treatment of genetic diseases. Subsequently, the field of gene therapy has been expanded, with a major focus on cancer. Although the results of early gene therapy-based clinical trials have been encouraging, there is a need for gene delivery vectors that feature reduced immunogenicity and improved targeting ability. The results of phases I/II clinical trials have suggested the important role of gene therapy as a versatile and powerful treatment tool, especially for human cancers. One reasonable expectation is that performing gene therapy at an earlier stage in the disease process or for minimal residual disease may be more advantageous.     

Opening the black box: an encounter in the corridors of health services research.

Health services research has become more prominent as a result of the NHS reforms. Both providers and purchasers want to know exactly where the money is spent and how it could be used more effectively. How best to obtain information about health services is the subject of some debate within and between disciplines engaged in such research. Because of their training doctors are often sceptical of anything other than formal clinical trials and research which produces statistical data. Some sociologists argue that another way to find out what is actually happening in the NHS is to observe people at work and talk to them. This article debates these differing views of research methods. For effective research both quantitative and qualitative approaches need to be used.     

Prentice's approach and the meta-analytic paradigm: a reflection on the role of statistics in the evaluation of surrogate endpoints

We put a perspective on the strengths and limitations of statistical methods for the evaluation of surrogate endpoints. Whereas using several trials overcomes some of the limitations of a single-trial framework (Prentice, 1989, Statistics in Medicine 8, 431-440), arguably the evaluation of surrogate endpoints can never be done using only statistical evidence but such evidence should be seen as but one component in a decision-making process that involves, among others, a number of clinical and biological considerations. We briefly present a hierarchical framework that incorporates ideas from Prentice's work and is uniformly applicable to different types of surrogate and true clinical outcomes.     

Persistent Controversy in Statistical Approaches in Wildlife Sciences: A Perspective of Students

ABSTRACT The controversy over the use of null hypothesis statistical testing (NHST) has persisted for decades, yet NHST remains the most widely used statistical approach in wildlife sciences and ecology. A disconnect exists between those opposing NHST and many wildlife scientists and ecologists who conduct and publish research. This disconnect causes confusion and frustration on the part of students. We, as students, offer our perspective on how this issue may be addressed. Our objective is to encourage academic institutions and advisors of undergraduate and graduate students to introduce students to various statistical approaches so we can make well-informed decisions on the appropriate use of statistical tools in wildlife and ecological research projects. We propose an academic course that introduces students to various statistical approaches (e.g., Bayesian, frequentist, Fisherian, information theory) to build a foundation for critical thinking in applying statistics. We encourage academic advisors to become familiar with the statistical approaches available to wildlife scientists and ecologists and thus decrease bias towards one approach. Null hypothesis statistical testing is likely to persist as the most common statistical analysis tool in wildlife science until academic institutions and student advisors change their approach and emphasize a wider range of statistical methods.     

Ways of measuring rates of recurrent events.

Recurrent events are common in medical research, yet the best ways to measure their occurrence remain controversial. Moreover, the correct statistical techniques to compare the occurrence of such events across populations or treatment groups are not widely known. In both observational studies and randomised clinical trials one natural and intuitive measure of occurrence is the event rate, defined as the number of events (possibly including multiple events per person) divided by the total person-years of experience. This is often a more relevant and clinically interpretable measure of disease burden in a population than considering only the first event that occurs. Appropriate statistical tests to compare such event rates among treatment groups or populations require the recognition that some individuals may be especially likely to experience recurrent events. Straightforward approaches are available to account for this tendency in crude and stratified analyses. Recently developed regression models can appropriately examine the association of several variables with rates of recurrent events.     

BAFF/BLyS inhibitors: A new prospect for treatment of systemic lupus erythematosus

In November 2009, Human Genome Sciences and Glaxo-Smith Kline [HGS (Rockville, Maryland) and GSK, respectively] announced that Belimumab, a neutralizing antibody to the tumour necrosis factor (TNF)-like ligand, B-cell activating factor (BAFF belonging to the TNF family, also named BLyS), met the primary endpoints in two phase III clinical trials in systemic lupus erythematosus (SLE, lupus). In March 2011, Belimumab was approved by the US Federal Drug Agency for treatment of SLE patients; this was followed in May with approval by the European Medicines Agency for use in the European Union. This is an exciting development as it is the first successful late-stage clinical trial in SLE in over 40 years. In the light of this breakthrough, we review the key data and research outcomes and examine how blocking BAFF in patients with SLE significantly improves clinical outcomes.     

Reexamining Sample Size Requirements for Multivariate,Abundance-Based Community Research: When Resources are Limited,the Research Does Not Have to Be

Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, oversampling (too many individuals counted per sample) also comes at a cost, particularly for ecological systems in which identification and quantification is substantially more resource consuming than the field expedition itself. In such systems, an increasingly larger sample size will eventually result in diminishing returns in improving any pattern or gradient revealed by the data, but will also lead to continually increasing costs. Here, we examine 396 datasets: 44 previously published and 352 created datasets. Using meta-analytic and simulation-based approaches, the research within the present paper seeks (1) to determine minimal sample sizes required to produce robust multivariate statistical results when conducting abundance-based, community ecology research. Furthermore, we seek (2) to determine the dataset parameters (i.e., evenness, number of taxa, number of samples) that require larger sample sizes, regardless of resource availability. We found that in the 44 previously published and the 220 created datasets with randomly chosen abundances, a conservative estimate of a sample size of 58 produced the same multivariate results as all larger sample sizes. However, this minimal number varies as a function of evenness, where increased evenness resulted in increased minimal sample sizes. Sample sizes as small as 58 individuals are sufficient for a broad range of multivariate abundance-based research. In cases when resource availability is the limiting factor for conducting a project (e.g., small university, time to conduct the research project), statistically viable results can still be obtained with less of an investment.