How representative are insomnia clinical trials?

ObjectivesTo address the question of how representative subjects studied in hypnotic clinical trials are of the broader insomnia population, this study assessed initial contact rates and reasons for inclusion and exclusion during recruitment to an efficacy trial and to a safety trial of Food & Drug Administration (FDA) approved hypnotics.MethodsOtherwise heathy persons meeting Diagnostic Statistical Manual, Fourth Edition, Revised (DSM-IVR) criteria for insomnia were recruited. In one study, persons 32–65 yrs, were invited to a 12 month trial of nightly use of zolpidem or placebo. In the other, persons 21–64 yrs with driver's licenses were recruited to test the effects of a hypnotic on live on-the-road driving ability. In both studies screening was conducted through an initial telephone interview followed by a clinic visit.ResultsIn the United States (US) study 13% (n = 410) of 3180 initial contacts and in the Netherlands (NL) study 67% (n = 53) of the 79 initial contacts proceeded to the clinic visit. Of those at clinic 25% of US and 37% of NL participants failed to meet additional insomnia criteria. Mental health exclusions accounted for 24% of US and 23% of NL participants and medical problems accounted for 23% of US and 9% NL exclusions. Finally 20% of US and 26% of NL participants were excluded for drug use/abuse histories. After all screening 4% of the initial US contacts and 0% of the NL contacts entered the study.ConclusionsThese data suggest persons entering insomnia hypnotic clinical trials are a highly selected sample that is unlikely to be representative of the broad insomnia population or the population of potential medication users.     

Experimental therapeutics in Huntington's disease: are models useful for therapeutic trials?

PURPOSE OF REVIEW: Research conducted over the past 10 years has uncovered molecular mechanisms that are likely to be important in the early stages of Huntington's disease pathogenesis. This review summarizes the resources and strategies that are in place in order to exploit these new findings and use them to develop novel Huntington's disease therapeutics. The role that disease models will play in this process is discussed. RECENT FINDINGS: A wide variety of models of Huntington's disease have been developed including yeast, Caenorhabditis elegans, Drosophila melanogaster and mouse. These can be developed as screening assays for the identification of chemical compounds that show beneficial effects against a specific phenotype and for the cross validation of potential therapeutics. The first compounds arising through this drug development pipeline have been reported. Similarly, the preclinical screening of compounds in mouse models is being developed in a coordinated manner. SUMMARY: Our understanding of the molecular basis of Huntington's disease is increasing at an exponential rate. Over the next few years an increasing number of potential therapeutic compounds will have been identified. It will only be possible to take a small number of these through to phase III clinical trials. The challenge will be to use the in-vivo models of Huntington's disease to best predict which of these compounds should be pursued in the clinic, to avoid depleting the patient population willing to enter into trials, and demoralizing them by conducting repeated unsuccessful trials.     

Heart rate variability modification as a predictive factor of sudden unexpected death in epilepsy: How far are we? A systematic review and meta-analysis

Background

Sudden unexpected death in epilepsy (SUDEP) is a sudden, unexpected death in people with epilepsy, with or without evidence of an epileptic seizure. The pathophysiological mechanism underlying SUDEP appears to be partly associated with an autonomic nervous system (ANS) dysfunction. Heart rate variability (HRV) analysis is a reliable, non-invasive method for detecting fluctuations in the ANS. In this systematic review we analyzed the data available in the literature on changes in HRV parameters in patients with SUDEP.

Methods

We carried out a systematic search of the literature to identify the quantitative variations of HRV in epileptic patients with SUDEP. The following databases were used: Pubmed, Google Scholar, EMBASE, and CrossRef. A pooled analysis was carried out, and the results obtained were compared using mean difference (MD). The review was registered on the PROSPERO platform (CRD42021291586).

Results

Seven articles were included, with a total of 72 SUDEP cases associated with altered HRV parameters. Generally, a reduction of SDNN (standard deviation of the RR intervals) and RMSSD (root mean square differences of successive RR intervals) was reported in most SUDEP patients. According to MD, the SUDEP patients showed no differences in time and frequency domain parameters compared to controls. However, a trend toward increased low frequency and high frequency ratio (LF/HF) was observed in the SUDEP patients.

Conclusions

HRV analysis is a valuable method for assessing cardiovascular risk and cardioautonomic impairment. Although a possible association between HRV variation and SUDEP has been reported, further studies are needed to assess the potential role of HRV modifications as a SUDEP biomarker.     

How effective are second-generation antipsychotic drugs? A meta-analysis of placebo-controlled trials

We conducted a systematic review and meta-analysis of randomized controlled trials that compared second-generation antipsychotic (SGA) drugs with placebo in schizophrenic patients and which considered 13 different outcome measures. Thirty-eight randomized controlled trials with 7323 participants were included. All SGA drugs were more effective than placebo, but the pooled effect size (ES) for overall symptoms (primary outcome) was moderate (-0.51). The absolute difference (RD) in responder rates was at 18% (41% responded to drug compared with 24% to placebo, number needed to treat=6). Similar ESs were found for the other efficacy parameters: negative symptoms (ES=-0.39), positive symptoms (ES=-0.48), depression (ES=-0.26), relapse (RD 20%) and discontinuation due to inefficacy (RD 17%). Curiously, the efficacy of haloperidol for negative and depressive symptoms was similar to that of the SGA drugs. In contrast to haloperidol, there was no difference in terms of EPS between any SGA drugs and placebo, and there was also no difference in terms of dropouts due to adverse events. Meta-regression showed a decline in treatment response over time, and a funnel plot suggested the possibility of publication bias. We conclude that the drug versus placebo difference of SGA drugs and haloperidol in recent trials was moderate, and that there is much room for more efficacious compounds. Whether methodological issues account in part for the relatively low efficacy ESs and the scarcity of adverse event differences compared with placebo needs to be established.     

How accurate is ICD coding for epilepsy?

Purpose:   Assess the validity of ICD-9-CM and ICD-10 epilepsy coding from an emergency visit (ER) and a hospital discharge abstract database (DAD).
Methods:   Two separate sources of patient records were reviewed and validated. (1) Charts of patients admitted to our seizure monitoring unit over 2 years (n = 127, ICD-10 coded records) were reviewed. Sensitivity (Sn), specificity (Sp), and positive and negative predictive values (PPV and NPV) were calculated. (2) Random sample of charts for patients seen in the ER or admitted to hospital under any services, and whose charts were coded with epilepsy or an epilepsy-like condition, were reviewed. Two time-periods were selected to allow validation of both ICD-9-CM (n = 486) and ICD-10 coded (n = 454) records. Only PPV and NPV were calculated for these records. All charts were reviewed by two physicians to confirm the presence/absence of epilepsy and compare to administrative coding.
Results:   Sample 1: Sn, Sp, PPV, and NPV of ICD-10 epilepsy coding from the seizure monitoring unit (SMU) chart review were 99%, 70%, 85%, and 97% respectively. Sample 2: The PPV and NPV for ICD-9-CM coding from the ER database were, respectively, 99% and 97% and from the DAD were 98% and 99%. The PPV and NPV for ICD-10 coding from the ER database were, respectively, 100% and 90% and from the DAD were 98% and 99%. The epilepsy subtypes grand mal status and partial epilepsy with complex partial seizures both had PPVs >75% (ICD-9-CM and ICD-10 data).
Discussion:   Administrative emergency and hospital discharge data have high epilepsy coding validity overall in our health region.     

How representative of everyday clinical populations are schizophrenia patients enrolled in clinical trials?

INTRODUCTION: There has been considerable discussion whether clinical trials accurately depict everyday practice. Restrictive inclusion/exclusion criteria, ethical considerations, differences in the severity of psychopathology between clinical and trial patients, or safety issues may bias results, which in turn may rather represent outcome for the "ideal" than for the "average"patient. Therefore, translation into psychiatric practice may be difficult. METHODS: A retrospective case-control study was performed. Schizophrenia inpatients at the LMU Department of Psychiatry, Munich, Germany, who had participated in clinical trials were compared to regular patients serving as controls. Probands and controls were matched by DSM-IV diagnosis, gender and age. The AMDP module, CGI and GAF were used to compare psychopathology. In addition, charts were reviewed for medication dosages, concurrent medical and neurological illness, and clinical history such as age of onset or family history. RESULTS: A total of 200 probands (100/100) were enrolled in the study. With respect to psychopathology, formally thought disordered or suicidal patients were significantly less likely to be study participants (n = 3) than controls (n = 22; p < or = 0.05). Similarly, negative schizophrenia symptoms were significantly less often present in study participants (n = 17) than in controls (n = 38; p < or = 0.05). Study participants were also medically and neurologically healthier than controls. (p = 0.05 respectively). No differences in overall illness severity as depicted by CGI and GAF were observed. CONCLUSION: We found the patients included in our clinical trials representative of the patient encountered in routine clinical practice. Adherence to inclusion and exclusion criteria prevents inclusion of severely ill (e. g. suicidal) patients requiring a more intensive treatment setting. Illness severity was found to be similar in trial participants and controls, and indicates an overall comparably severe psychopathology. The more chronic, rather treatment refractory patients were also not reflected in the trial participant pool; this population may arguably not represent the average clinical patient either. A more careful administration of antipsychotic medication was found in trial participants and may effectively be considered "good clinical practice".     

Prevention of epilepsy: Should we be avoiding clinical trials?

Epilepsy prevention is one of the great unmet needs in epilepsy. Approximately 15% of all epilepsy is caused by an acute acquired CNS insult such as traumatic brain injury (TBI), stroke or encephalitis. There is a latent period between the insult and epilepsy onset that presents an opportunity to intervene with preventive treatment that is unique in neurology. Yet no phase 3 epilepsy prevention studies, and only 2 phase 2 studies have been initiated in the last 16 years. Current prevailing opinion is that the research community is not ready for clinical preventive epilepsy studies, and that animal models should first be refined and biomarkers of epileptogenesis and of epilepsy discovered before clinical studies are embarked upon. We review data to suggest that there is basis to do epilepsy prevention studies now with the current knowledge and available drugs, and that those studies are feasible with currently available tools. We suggest that a different approach is needed from the past in order to maximize chances of success, minimize the cost, and set up platform for future preventive treatment development. That approach should include close coordination of preclinical and clinical development programs in a combined PTE prevention strategy, consideration of polytherapy, and simultaneous, combined clinical development of preventive treatment and of biomarker discovery. We argue that the currently favored approach of eschewing clinical studies until biomarkers are available will delay the discovery of epilepsy prevention treatment by at least 10 years and significantly increase the cost of such discovery.     

How predictive is the MMSE for cognitive performance after stroke?

Cognitive deficits are commonly observed in stroke patients. Neuropsychological testing is time-consuming and not easy to administer after hospital discharge. Standardised screening measures are desirable. The Mini-Mental State Examination (MMSE) is the test most widely applied to screen for cognitive deficits. Despite its broad use, its predictive characteristics after stroke have not been exhaustively investigated. The aim of this study was to determine whether the MMSE is able to adequately screen for cognitive impairment and dementia after stroke and whether or not the MMSE can predict further deterioration or recovery in cognitive function over time. To this end, we studied 194 first-ever stroke patients without pre-stroke cognitive deterioration who underwent MMSEs and neuropsychological test batteries at 1, 6, 12, and 24 months after stroke. The MMSE score 1 month after stroke predicted cognitive functioning at later follow-up visits. It could not predict deterioration or improvement in cognitive functioning over time. The cut-off score in the screening for 1 cognitive disturbed domain was 27/28 with a sensitivity of 0.72. The cut-off score in the screening for at least 4 impaired domains and dementia were 26/27 and 23/24 with a sensitivity of 0.82 and 0.96, respectively. The results indicated that the MMSE has modest qualities in screening for mild cognitive disturbances and is adequate in screening for moderate cognitive deficits or dementia in stroke patients 1 month after stroke. Poor performance on the MMSE is predictive for cognitive impairment in the long term. However, it cannot be used to predict further cognitive deterioration or improvement over time.     

How should efficacy be evaluated in randomized clinical trials of treatments for depression?

The present system of conducting studies of promising antidepressant therapies has evolved through the collaborative efforts of government, industry, and academicians and is costly and inefficient. At least one third of the published clinical trials of approved antidepressants are negative for efficacy, which can be partly explained by the clinical and neurobiological heterogeneity of the depressive disorder and partly because of methodological inadequacies. Unfortunately, too little attention is given to ensuring the reliability of diagnoses and dependent measures, sample sizes are seldom large enough to detect modest yet honestly significant differences, and too many trials are pursued before dose-response characteristics are fully understood. At present, the only data beyond 1 year of treatment--and the only evidence about protection against recurrent depression--come during postmarketing or phase 4 of the drug development process. Moreover, efficacy data for depressed children and adolescents, bipolar depression, psychotic depression, dysthymia, and frail or medically ill elderly patients are rarely available at the time a drug is introduced. Thus, it is remarkable how little clinicians know about a new antidepressant at the time it is first approved for general use. Within a research strategy, tactics that ensure reliability, encourage attention to adherence, and lessen attrition at the outset of a study will increase the power and design sensitivity of a particular trial. Additionally, the issues of research funding-including division of the research pie-and the relationship of the Food and Drug Administration and investigators to the pharmaceutical industry and the National Institute of Mental Health need to be revisited. Finally, extension of a compound's patent life might be considered to expand the necessary postmarketing research. This article describes the process of conducting the clinical trials that support a New Drug Application, discusses issues in evaluating efficacy, and offers suggestions for modifying and improving the drug development process so that clinicians can better judge new drugs.     

Animal models of addiction: models for therapeutic strategies?

Summary. When having a continuous free choice in their home cages between water and alcohol- or drug-containing drinking solutions, rats first develop a controlled consumption of the psychotropic compound and, after several months, lose their control over drug taking. After a long period of abstinence, they reveal an excessive, compulsive drug intake. Adulteration of the drug-containing solutions reduces the doses taken by controlled consumers, but not those of the excessive drinkers, they can therefore be regarded as addicted. These animals show a pre-intake motor restlessness that may be related to craving. In two studies with putative anti-craving agents (the dopamine D₂ receptor agonist lisuride and the D₂ receptor antagonist flupentixol) we treated alcohol-addicted and non-addicted rats and observed the effects on alcohol taking, alcohol seeking and brain neurotransmission. These two investigations paralleled clinical studies, in both cases the results could be predicted correctly (“pro-craving” effect of both pharmaceutics). Differences between “symptomatic” and possible “causal” therapies are discussed, approaches towards a causal therapy according to an "imprinting"-model of an addition are suggested. Received August 18, 1999; accepted November 3, 1999     

Geographic variation of epilepsy for older Americans: How close to the geographic variation of stroke?

Purpose: Given the strong association of stroke and epilepsy in older persons, and the existence of a Stroke Belt in the United States, we hypothesized that geographic variation in epilepsy prevalence would follow geographic patterns similar to stroke. Methods: We used a 2005 5% random sample of Medicare beneficiaries 65 and older in 48 U.S. contiguous states. Epilepsy was identified from claims for physician visits, hospitalizations, and outpatient procedures. Prevalence was obtained by state and county. Logistic regressions determined the independent association of the likelihood of epilepsy (prevalent or new case) and residence in Stroke Belt states, controlling for residence in highest epilepsy prevalence states, demographics (race, age, gender), comorbid conditions, cerebrovascular disease, dementia, and county characteristics. Key Findings: Of 1,212,015 beneficiaries, 11.9 per 1,000 had prevalent and 2.9 new cases of epilepsy. Nine of 11 Stroke Belt states were among the 20 states with the highest epilepsy prevalence. Counties in the 10 highest epilepsy prevalence states were more likely to be large urban counties with a higher number of neurologists or neurosurgeons per capita. The higher likelihood of prevalent epilepsy cases associated with Stroke Belt residence was explained by beneficiaries’ race; that associated with residence in high epilepsy prevalence states was not. The likelihood of new epilepsy cases was negatively associated with Stroke Belt residence when controlling for covariates. Significance: The geographic variation in epilepsy prevalence is not explained by variations in known risk factors. Further research should investigate why eastern U.S. states have higher frequency of epilepsy.     

How to measure fatigue in epilepsy? The validation of three scales for clinical use

Fatigue can be defined as extreme and persistent tiredness, weakness or exhaustion that could be mental, physical or both. The main objective of this study is to validate three instruments to measure fatigue (Fatigue Symptom Inventory--FSI, Fatigue Assessment Instrument--FAI, Fatigue Severity Scale--FSS) in patients with epilepsy (PWE). We used concurrent validity as a method of validation. Reliability of the fatigue scales was assessed in PWE. We applied the three selected questionnaires plus the Beck Depression Inventory (BDI) in PWE, healthy volunteers (HV) and patients with other neurological conditions. We studied 67 PWE, 34 HV and 56 patients with different neurological conditions. The mean fatigue scores in each group were as follows: (a) for the FSS, the score in HV was 2.6±1.1, in PWE 4.2±1.5, in Patients with multiple Sclerosis (PMS) 4.8±1.4, in Patients with Migraine (PWM) 4.4±1.9, in Patients with radiculopathy (PR) 4.5±0.9. (b) For the FSI, the score in HV was 2.2±1.3, in PWE 3.9±2.3, in PMS 4.1±1.9, in PWM 4.5±2.5, and in PR 5.4±1.4. (c) For the FAI in HV was 3.0±1.1, in PWE 4.2±1.3, in PMS 4.5±0.9, PWM 4.3±1.5, and in PR 4.4±1.4. The correlation between the BDI and the FSS was 0.52 (p<0.001), between the BDI and the FSI was 0.62 (p<0.001), and between the BDI and the FAI was 0.54 (p<0.001). Patients with epilepsy have consistently higher fatigue scores compared healthy controls, and scores that are comparable with other neurological conditions. The FSI, FAI and FSS display concurrent validity and high intra-observer reliability in PWE, indicating that these scales could be utilized for further study of fatigue in epilepsy.     

How common are complications of Parkinson's disease?

Background Parkinson's disease (PD) can be associated with a wide range of complications of advancing disease and treatment. However, it is unclear how often these occur in the overall population of patients with PD. Objective To assess the prevalence of disease and treatment complications and their clinical correlates in a community-based sample of 124 patients with PD. Results Average current age was 72 (SD 10.9) and mean disease duration 6 (SD 4.3) years. Falls with postural instability and other axial features were among the most common complications of advancing disease in this population (64 %). Motor fluctuations and dyskinesias affected approximately 30 and 20 % of the overall sample respectively, and changes in mental state such as dementia, depression and hallucinations each affected approximately one fifth of patients. Symptoms of autonomic nervous system dysfunction occurred in the great majority of patients, but were not associated with greater disease severity, disease duration or overall disability. Conclusion In contrast to clinic-based samples, the most frequently occurring complications of PD in this community-based sample were axial features such as postural instability with falls. These factors should be more taken into account in the allocation of health care resources and the treatment of symptoms of patients with PD in the community. Received: 31 January 2001, Received in revised form: 8 August 2001, Accepted: 21 August 2001     

Perspectives of zebrafish models of epilepsy: What,how and where next?

Epilepsy is a complex brain disorder with multiple underlying causes and poorly understood pathogenetic mechanisms. Animal models have been indispensable tools in experimental epilepsy research. Zebrafish (Danio rerio) are rapidly emerging as a promising model organism to study various brain disorders. Seizure-like behavioral and neurophysiological responses can be evoked in larval and adult zebrafish by various pharmacological and genetic manipulations, collectively emphasizing the growing utility of this model for studying epilepsy. Here, we discuss recent developments in using zebrafish models to study the seizure-like behavior involved in epilepsy, outlining current challenges and strategies for further translational research in this field.