The yield of long-term electrocardiographic recordings in refractory focal epilepsy

OBJECTIVE: To determine the incidence of clinically relevant arrhythmias in refractory focal epilepsy and to assess the potential of postictal arrhythmias as risk markers for sudden unexpected death in epilepsy (SUDEP). METHODS: We recruited people with refractory focal epilepsy without signs of ictal asystole and who had at least one focal seizure per month and implanted a loop recorder with 2-year follow-up. The devices automatically record arrhythmias. Subjects and caregivers were instructed to make additional peri-ictal recordings. Clinically relevant arrhythmias were defined as asystole ≥ 6 seconds; atrial fibrillation 200 bpm and duration > 30 seconds; persistent sinus bradycardia < 40 bpm while awake; and second- or third-degree atrioventricular block and ventricular tachycardia/fibrillation. We performed 12-lead electrocardiography (ECG) and tilt table testing to identify non-seizure-related causes of asystole. RESULTS: We included 49 people and accumulated 1060 months of monitoring. A total of 16 474 seizures were reported, of which 4679 were captured on ECG. No clinically relevant arrhythmias were identified. Three people had a total of 18 short-lasting (<6 seconds) periods of asystole, resulting in an incidence of 2.91 events per 1000 patient-months. None of these coincided with a reported seizure; one was explained by micturition syncope. Other non-clinically relevant arrhythmias included paroxysmal atrial fibrillation (n = 2), supraventricular tachycardia (n = 1), and sinus tachycardia with a right bundle branch block configuration (n = 1). SIGNIFICANCE: We found no clinically relevant arrhythmias in people with refractory focal epilepsy during long-term follow-up. The absence of postictal arrhythmias does not support the use of loop recorders in people at high SUDEP risk

Multivariate random effects meta-analysis of diagnostic tests with multiple thresholds

Background. Bivariate random effects meta-analysis of diagnostic tests is becoming a well established approach when studies present one two-by-two table or one pair of sensitivity and specificity. When studies present multiple thresholds for test positivity, usually meta-analysts reduce the data to a two-by-two table or take one threshold value at a time and apply the well developed meta-analytic approaches. However, this approach does not fully exploi

Enhanced secondary analysis of survival data: reconstructing the data from published Kaplan-Meier survival curves

<p>Abstract</p> <p>Background</p> <p>The results of Randomized Controlled Trials (RCTs) on time-to-event outcomes that are usually reported are median time to events and Cox Hazard Ratio. These do not constitute the sufficient statistics required for meta-analysis or cost-effectiveness analysis, and their use in secondary analyses requires strong assumptions that may not have been adequately tested. In order to enhance the quality of secondary data analyses, we propose a method which derives from the published Kaplan Meier survival curves a close approximation to the original individual patient time-to-event data from which they were generated.</p> <p>Methods</p> <p>We develop an algorithm that maps from digitised curves back to KM data by finding numerical solutions to the inverted KM equations, using where available information on number of events and numbers at risk. The reproducibility and accuracy of survival probabilities, median survival times and hazard ratios based on reconstructed KM data was assessed by comparing published statistics (survival probabilities, medians and hazard ratios) with statistics based on repeated reconstructions by multiple observers.</p> <p>Results</p> <p>The validation exercise established there was no material systematic error and that there was a high degree of reproducibility for all statistics. Accuracy was excellent for survival probabilities and medians, for hazard ratios reasonable accuracy can only be obtained if at least numbers at risk or total number of events are reported.</p> <p>Conclusion</p> <p>The algorithm is a reliable tool for meta-analysis and cost-effectiveness analyses of RCTs reporting time-to-event data. It is recommended that all RCTs should report information on numbers at risk and total number of events alongside KM curves.</p

Bivariate random-effects meta-analysis and the estimation of between-study correlation

BACKGROUND: When multiple endpoints are of interest in evidence synthesis, a multivariate meta-analysis can jointly synthesise those endpoints and utilise their correlation. A multivariate random-effects meta-analysis must incorporate and estimate the between-study correlation (ρ(B)). METHODS: In this paper we assess maximum likelihood estimation of a general normal model and a generalised model for bivariate random-effects meta-analysis (BRMA). We consider two applied examples, one involving a diagnostic marker and the other a surrogate outcome. These motivate a simulation study where estimation properties from BRMA are compared with those from two separate univariate random-effects meta-analyses (URMAs), the traditional approach. RESULTS: The normal BRMA model estimates ρ(B )as -1 in both applied examples. Analytically we show this is due to the maximum likelihood estimator sensibly truncating the between-study covariance matrix on the boundary of its parameter space. Our simulations reveal this commonly occurs when the number of studies is small or the within-study variation is relatively large; it also causes upwardly biased between-study variance estimates, which are inflated to compensate for the restriction on [Formula: see text] (B). Importantly, this does not induce any systematic bias in the pooled estimates and produces conservative standard errors and mean-square errors. Furthermore, the normal BRMA is preferable to two normal URMAs; the mean-square error and standard error of pooled estimates is generally smaller in the BRMA, especially given data missing at random. For meta-analysis of proportions we then show that a generalised BRMA model is better still. This correctly uses a binomial rather than normal distribution, and produces better estimates than the normal BRMA and also two generalised URMAs; however the model may sometimes not converge due to difficulties estimating ρ(B). CONCLUSION: A BRMA model offers numerous advantages over separate univariate synthesises; this paper highlights some of these benefits in both a normal and generalised modelling framework, and examines the estimation of between-study correlation to aid practitioners

Chapter 8: Meta-analysis of Test Performance When There is a “Gold Standard”

Synthesizing information on test performance metrics such as sensitivity, specificity, predictive values and likelihood ratios is often an important part of a systematic review of a medical test. Because many metrics of test performance are of interest, the meta-analysis of medical tests is more complex than the meta-analysis of interventions or associations. Sometimes, a helpful way to summarize medical test studies is to provide a “summary point”, a summary sensitivity and a summary specificity. Other times, when the sensitivity or specificity estimates vary widely or when the test threshold varies, it is more helpful to synthesize data using a “summary line” that describes how the average sensitivity changes with the average specificity. Choosing the most helpful summary is subjective, and in some cases both summaries provide meaningful and complementary information. Because sensitivity and specificity are not independent across studies, the meta-analysis of medical tests is fundamentaly a multivariate problem, and should be addressed with multivariate methods. More complex analyses are needed if studies report results at multiple thresholds for positive tests. At the same time, quantitative analyses are used to explore and explain any observed dissimilarity (heterogeneity) in the results of the examined studies. This can be performed in the context of proper (multivariate) meta-regressions

Chapter 12: Systematic Review of Prognostic Tests

A number of new biological markers are being studied as predictors of disease or adverse medical events among those who already have a disease. Systematic reviews of this growing literature can help determine whether the available evidence supports use of a new biomarker as a prognostic test that can more accurately place patients into different prognostic groups to improve treatment decisions and the accuracy of outcome predictions. Exemplary reviews of prognostic tests are not widely available, and the methods used to review diagnostic tests do not necessarily address the most important questions about prognostic tests that are used to predict the time-dependent likelihood of future patient outcomes. We provide suggestions for those interested in conducting systematic reviews of a prognostic test. The proposed use of the prognostic test should serve as the framework for a systematic review and to help define the key questions. The outcome probabilities or level of risk and other characteristics of prognostic groups are the most salient statistics for review and perhaps meta-analysis. Reclassification tables can help determine how a prognostic test affects the classification of patients into different prognostic groups, hence their treatment. Review of studies of the association between a potential prognostic test and patient outcomes would have little impact other than to determine whether further development as a prognostic test might be warranted

Chromosomal amplifications, 3q gain and deletions of 2q33-q37 are the frequent genetic changes in cervical carcinoma

BACKGROUND: Carcinoma of uterine cervix is the second most common cancers among women worldwide. Combined radiation and chemotherapy is the choice of treatment for advanced stages of the disease. The prognosis is poor, with a five-year survival rate ranging from about 20–65%, depending on stage of the disease. Therefore, genetic characterization is essential for understanding the biology and clinical heterogeneity in cervical cancer (CC). METHODS: We used a genome-wide screening method – comparative genomic hybridization (CGH) to identify DNA copy number changes in 77 patients with cervical cancer. We applied categorical and survival analyses to analyze whether chromosomal changes were related to clinico-pathologic characteristics and patients survival. RESULTS: The CGH analysis revealed a loss of 2q33-q37 (57.1%), gain of 3q (54.5%) and chromosomal amplifications (20.77%) as frequent genetic changes. A total of 15 amplified chromosomal sites were detected in 16 cases that include 1p31, 2q32, 7q22, 8q21.2-q24, 9p22, 10q21, 10q24, 11q13, 11q21, 12q15, 14q12, 17p11.2, 17q22, 18p11.2, and 19q13.1. Recurrent amplified sites were noted at 11q13, 11q21, and 19q13.1. The genomic alterations were further evaluated for prognostic significance in CC patients, and we did not find any correlation with a number of clinical or histological parameters. The tumors harboring HPV18 exhibited higher genomic instability compared to tumors with HPV 16. CONCLUSIONS: This study demonstrated that 2q33-q37 deletions, 3q gains and chromosomal amplifications as characteristic changes in invasive CC. These genetic alterations will aid in the identification of novel tumor suppressor gene(s) at 2q33-q37 and oncogenes at amplified chromosomal sites. Molecular characterization of these chromosomal changes utilizing the current genomic technologies will provide new insights into the biology and clinical behavior of CC