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PubMed2005

Language of publication restrictions in systematic reviews gave different results depending on whether the intervention was conventional or complementary.

OBJECTIVE: To assess whether language of publication restrictions impact the estimates of an intervention's effectiveness, whether such impact is similar for conventional medicine and complementary medicine interventions, and whether the results are influenced by publication bias and statistical heterogeneity. STUDY DESIGN AND SETTING: We set out to examine the extent to which including reports of randomized controlled trials (RCTs) in languages other than English (LOE) influences the results of systematic reviews, using a broad dataset of 42 language-inclusive systematic reviews, involving 662 RCTs, including both conventional medicine (CM) and complementary and alternative medicine (CAM) interventions. RESULTS: For CM interventions, language-restricted systematic reviews, compared with language-inclusive ones, did not introduce biased results, in terms of estimates of intervention effectiveness (random effects ration of odds rations ROR=1.02; 95% CI=0.83-1.26). For CAM interventions, however, language-restricted systematic reviews resulted in a 63% smaller protective effect estimate than language-inclusive reviews (random effects ROR=1.63; 95% CI=1.03-2.60). CONCLUSION: Language restrictions do not change the results of CM systematic reviews but do substantially alter the results of CAM systematic reviews. These findings are robust even after sensitivity analyses, and do not appear to be influenced by statistical heterogeneity and publication bias.

Complementary Therapies↗
PubMed1992

Evaluation of a 3D reconstruction algorithm for multi-slice PET scanners.

A fully 3D reconstruction algorithm based on filtered backprojection was evaluated for the reconstruction of data obtained with multi-slice positron emission tomography (PET) scanners which have had the septa removed. This algorithm uses forward-projection through the reconstructed images of a 2D subset of the data to complete the 3D dataset thus satisfying the condition of shift invariance. This is followed by 3D filtered backprojection. Axial sampling was doubled by combining adjacent polar angles, thus improving reconstructed axial resolution. The algorithm was tested using real and simulated datasets and gave high quality reconstructions without artifacts over a wide range of imaging conditions. Events are placed accurately throughout the imaging volume as determined by measurements with a MRI/PET registration phantom. The forward-projection step leads to degradation in image resolution due to insufficient axial and transaxial sampling. This effect is amplified if multiple iterations of the algorithm are used, with little decrease in image noise. Changing the filter employed in the initial 2D reconstruction can be used to alter the noise and resolution characteristics of the 3D images. This algorithm has proved very robust at reconstructing 3D PET data and is relatively fast. Those small problems which exist can be attributed to detector sampling problems, especially in the axial direction, which is a consequence of the geometry of these scanners, which are designed primarily for 2D data acquisition.

Algorithms↗
PubMed2001

Determinants of patient recruitment in a multicenter clinical trials group: trends, seasonality and the effect of large studies.

BACKGROUND: We examined whether quarterly patient enrollment in a large multicenter clinical trials group could be modeled in terms of predictors including time parameters (such as long-term trends and seasonality), the effect of large trials and the number of new studies launched each quarter. We used the database of all clinical studies launched by the AIDS Clinical Trials Group (ACTG) between October 1986 and November 1999. Analyses were performed in two datasets: one included all studies and substudies (n = 475, total enrollment 69,992 patients) and the other included only main studies (n = 352, total enrollment 57,563 patients). RESULTS: Enrollment differed across different months of the year with peaks in spring and late fall. Enrollment accelerated over time (+27 patients per quarter for all studies and +16 patients per quarter for the main studies, p < 0.001) and was affected by the performance of large studies with target sample size > 1,000 (p < 0.001). These relationships remained significant in multivariate autoregressive modeling. A time series based on enrollment during the first 32 quarters could forecast adequately the remaining 21 quarters. CONCLUSIONS: The fate and popularity of large trials may determine the overall recruitment of multicenter groups. Modeling of enrollment rates may be used to comprehend long-term patterns and to perform future strategic planning.

Clinical Trials as Topic↗
PubMed2005

Analysis of significance patterns identifies ubiquitous and disease-specific gene-expression signatures in patient peripheral blood leukocytes.

The utilization of gene-expression microarrays in patient-based research creates new prospects for the discovery of diagnostic biomarkers and the identification of genes or pathways linked to pathogenesis. Gene-expression signatures in peripheral blood mononuclear cells isolated from over one hundred patients with conditions presenting a strong immunological component (patient with autoimmune, graft versus host and infectious diseases, as well as immunosuppressed transplant recipients) were generated. This dataset provides the opportunity to carry out comparative analyses and define disease signatures in a broader context. Transcriptional changes of 22,283 probe sets were evaluated through statistical group comparison performed systematically for seven diseases versus their respective healthy control group. Patterns of significance were generated by hierarchical clustering of P-values. This approach led to the identification of a SLE-specific "diagnostic signature," formed by genes that did not change compared to healthy subjects in the other six diseases. Conversely, a "sentinel signature" that was common to all seven diseases was characterized. These findings bring new perspectives for the application of blood leukocyte expression signatures for diagnosis and early disease detection.

Adult↗
PubMedDate not supplied

MAP: an iterative experimental design methodology for the optimization of catalytic search space structure modeling.

One of the main problems in high-throughput research for materials is still the design of experiments. At early stages of discovery programs, purely exploratory methodologies coupled with fast screening tools should be employed. This should lead to opportunities to find unexpected catalytic results and identify the "groups" of catalyst outputs, providing well-defined boundaries for future optimizations. However, very few new papers deal with strategies that guide exploratory studies. Mostly, traditional designs, homogeneous covering, or simple random samplings are exploited. Typical catalytic output distributions exhibit unbalanced datasets for which an efficient learning is hardly carried out, and interesting but rare classes are usually unrecognized. Here is suggested a new iterative algorithm for the characterization of the search space structure, working independently of learning processes. It enhances recognition rates by transferring catalysts to be screened from "performance-stable" space zones to "unsteady" ones which necessitate more experiments to be well-modeled. The evaluation of new algorithm attempts through benchmarks is compulsory due to the lack of past proofs about their efficiency. The method is detailed and thoroughly tested with mathematical functions exhibiting different levels of complexity. The strategy is not only empirically evaluated, the effect or efficiency of sampling on future Machine Learning performances is also quantified. The minimum sample size required by the algorithm for being statistically discriminated from simple random sampling is investigated.

Algorithms↗
PubMed2000

Sample size calculations for cluster randomised trials. Changing Professional Practice in Europe Group (EU BIOMED II Concerted Action).

OBJECTIVES: Cluster randomised trials, in which groups of individuals are randomised, are increasingly being used in the health field. Adopting a clustered approach has implications for the design of such trials, and sample size calculations need to be inflated to accommodate for the clustering effect. Reliable estimates of intracluster correlation coefficients (ICCs) are required for robust sample size calculations to be made; however, little empirical evidence is available on their likely size, and on factors which influence their magnitude. The aim of this study was to generate empirical estimates of ICCs and to explore factors which may affect their magnitude. METHODS: Empirical estimates of ICCs were calculated for both process variables and patient outcomes from a number of datasets of primary and secondary care implementation studies. RESULTS: Estimates of ICCs varied according to setting and type of outcome. Estimates of ICCs for process variables were higher than those for patient outcomes, and estimates derived from secondary care were higher than those from primary care. ICCs for process variables in primary care were of the order of 0.05-0.15, whilst those in secondary care were of the order of 0.3. Estimates for patient outcomes in primary care were generally lower than 0.05. CONCLUSIONS: Adopting cluster randomisation has implications for the design, size and analysis of clinical trials. This study gives an insight into the potential size of ICCs in primary and secondary care, and provides a practical guide to researchers to aid the planning of future studies in this area.

Cluster Analysis↗
PubMed1996

Validation testing of the SEER real-time digital holter monitor.

OBJECTIVES: Perioperative myocardial ischemia, detected by off-line Holter ST-segment monitoring, has been associated with adverse cardiac outcome. Technical advances in digital signal processing have facilitated development of digital Holter recorders that allow 24- to 48-hour recording, full disclosure storage, and "real-time" quantitative analysis of ST-segment levels. These recorders may be useful for "on-line" clinical detection of perioperative ischemia. However, little data are available, independent of manufacturers' claims, to validate their accuracy. Using a previously validated digital electrocardiogram (ECG) simulator, a commercially available device was evaluated. DESIGN: Laboratory bench study. SETTING: Not applicable. PARTICIPANTS: Not applicable. INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: Custom digital ECG waveform templates were programmed for use with a commercially available ECG simulator (M311 ECG simulator; Fogg Systems, Inc, Aurora, CO). For each template, ST-segment morphology (horizontal elevation or depression, downsloping depression), QRS duration (80 v 120 msec) and the presence or absence of a P wave were manipulated, yielding six unique QRS shapes. For each shape, the degree of ST-segment deviation was altered over a wide range. ST-segment values from the simulator (measured at 60 msec after the J point) ranged from +10 to -18 mm. The SEER digital Holter recorder (Marquette Electronics, Milwaukee, WI) was tested. One hundred twenty-six measurements of ST-segment deviation were input to the SEER at each of two testing sessions. The ST-segment value from the recorder in the "noninteractive" analysis mode was obtained, and the two results averaged for comparison with the expected simulator value. Variability of ST-segment measurement over a continuous 1-hour period of simulator input was also assessed. Sixty-seven percent of measurements were within 95% to 100% of expected, whereas 90% were within 90% to 110%. The regression equation for the complete dataset was SEER output (mm) = -0.47 + 1.015 * simulator input, R2 = 0.99. The mean observed-to-expected value ratio was 100% +/- 6% (+/-SD), range 80% to 114%. The mean deviation in millimeters from expected for all measurements was 0.10 +/- 0.20 mm, median 0.05 mm, range -0.25 to +0.60 mm. For the 72 measurements obtained by 5-minute sampling over 1 hour of continuous simulator input for each of the six QRS shapes, the mean percent difference between observed and expected values was 0.5% +/- 4.5%, median 0.0%, with a mean coefficient of variation of 2.7% (median 1.9%). CONCLUSIONS: Using a digital ECG simulator, it was found that the SEER recorder analyzed ST-segment deviation with a high degree of accuracy. These findings, along with its full disclosure reporting capabilities, suggest it may be useful in perioperative risk stratification. However, accuracy in the clinical setting remains to be validated.

Electrocardiography, Ambulatory↗
PubMed2005

Temporal trends on the risk of arrhythmic vs. non-arrhythmic deaths in high-risk patients after myocardial infarction: a combined analysis from multicentre trials.

AIMS: An understanding of the temporal trends on the risks of arrhythmic death (AD) vs. non-arrhythmic deaths (NAD) after myocardial infarction (MI) is crucial in deciding the optimal timing for risk stratification and treatment window for prophylactic antiarrhythmic treatment. However, contemporary data on such information is lacking. METHODS AND RESULTS: Individual patient data were pooled from the placebo arms of EMIAT, CAMIAT, SWORD, TRACE, and DIAMOND-MI who had a recent MI and left ventricular ejection fraction (LVEF) <40% or frequent ventricular premature beats (VPBs). Temporal trends were investigated for all studies from day 45 after acute myocardial infarction (AMI) to account for different recruitment periods between trials, and then from the onset of MI for TRACE and DIAMOND-MI that recruited patients within 2 weeks after MI. In total, 3104 patients (median age 65, range: 23-92; 2471 males) were pooled from all five studies, with a total of 487 deaths at 2-year follow-up; 220 deaths were ADs and 172 were NADs. The risks of both AD and NAD were highest in the first 6 months but the risk of AD was consistently higher than that of NAD throughout the 2-year period [rate of death/100 person-year at risk (AD/NAD): 8.09/6.07 (45 days to 6 months), 4.07/3.35 (>6-12 months), 4.34/3.60 (>12-18 months), 3.76/2.77 (>18-24 months)]. There were significant interactions between the temporal trends of mortalities and gender (P=0.03) and history of hypertension (P=0.04). A similar trend was observed when mortality was measured from time of onset of MI from the combined TRACE and DIAMOND-MI dataset. CONCLUSION: Our study provided the first contemporary evidence that in high-risk post-MI patients with LVEF <40% or frequent VPBs, the risk of AD was higher than that of NAD for up to 2 years although in female patients, they became increasingly more likely to die from NAD after 6 months. Therefore, risk stratification of post-MI patient at high risk of AD remains a worthwhile exercise. However, the risks of AD (and NAD) were highest in the first 6 months after AMI and level-off thereafter, suggesting that the optimal window period for risk stratification for implantable cardioverter defibrillator after AMI is in the first 6 months.

Adult↗
PubMed2005

Predicting skin permeability from complex chemical mixtures.

Occupational and environmental exposure to topical chemicals is usually in the form of complex chemical mixtures, yet risk assessment is based on experimentally derived data from individual chemical exposures from a single, usually aqueous vehicle, or from computed physiochemical properties. We present an approach using hybrid quantitative structure permeation relationships (QSPeR) models where absorption through porcine skin flow-through diffusion cells is well predicted using a QSPeR model describing the individual penetrants, coupled with a mixture factor (MF) that accounts for physicochemical properties of the vehicle/mixture components. The baseline equation is log k(p) = c + mMF + a sigma alpha2(H) + b sigma beta2(H) + s pi2(H) + rR2 + vV(x) where sigma alpha2(H) is the hydrogen-bond donor acidity, sigma beta2(H) is the hydrogen-bond acceptor basicity, pi2(H) is the dipolarity/polarizability, R2 represents the excess molar refractivity, and V(x) is the McGowan volume of the penetrants of interest; c, m, a, b, s, r, and v are strength coefficients coupling these descriptors to skin permeability (k(p)) of 12 penetrants (atrazine, chlorpyrifos, ethylparathion, fenthion, methylparathion, nonylphenol, rho-nitrophenol, pentachlorophenol, phenol, propazine, simazine, and triazine) in 24 mixtures. Mixtures consisted of full factorial combinations of vehicles (water, ethanol, propylene glycol) and additives (sodium lauryl sulfate, methyl nicotinate). An additional set of 4 penetrants (DEET, SDS, permethrin, ricinoleic acid) in different mixtures were included to assess applicability of this approach. This resulted in a dataset of 16 compounds administered in 344 treatment combinations. Across all exposures with no MF, R2 for absorption was 0.62. With the MF, correlations increased up to 0.78. Parameters correlated to the MF include refractive index, polarizability and log (1/Henry's Law Constant) of the mixture components. These factors should not be considered final as the focus of these studies was solely to determine if knowledge of the physical properties of a mixture would improve predicting skin permeability. Inclusion of multiple mixture factors should further improve predictability. The importance of these findings is that there is an approach whereby the effects of a mixture on dermal absorption of a penetrant of interest can be quantitated in a standard QSPeR model if physicochemical properties of the mixture are also incorporated.

Algorithms↗
PubMed2006

Comparative study of morphological and time-frequency ECG descriptors for heartbeat classification.

The prompt and adequate detection of abnormal cardiac conditions by computer-assisted long-term monitoring systems depends greatly on the reliability of the implemented ECG automatic analysis technique, which has to discriminate between different types of heartbeats. In this paper, we present a comparative study of the heartbeat classification abilities of two techniques for extraction of characteristic heartbeat features from the ECG: (i) QRS pattern recognition method for computation of a large collection of morphological QRS descriptors; (ii) Matching Pursuits algorithm for calculation of expansion coefficients, which represent the time-frequency correlation of the heartbeats with extracted learning basic waveforms. The Kth nearest neighbour classification rule has been applied for assessment of the performances of the two ECG feature sets with the MIT-BIH arrhythmia database for QRS classification in five heartbeat types (normal beats, left and right bundle branch blocks, premature ventricular contractions and paced beats), as well as with five learning datasets-one general learning set (GLS, containing 424 heartbeats) and four local sets (GLS+about 0.5, 3, 6, 12 min from the beginning of the ECG recording). The achieved accuracies by the two methods are sufficiently high and do not show significant differences. Although the GLS was selected to comprise almost all types of appearing heartbeat waveforms in each file, the guaranteed accuracy (sensitivity between 90.7% and 99%, specificity between 95.5% and 99.9%) was reasonably improved when including patient-specific local learning set (sensitivity between 94.8% and 99.9%, specificity between 98.6% and 99.9%), with optimal size found to be about 3 min. The repeating waveforms, like normal beats, blocks, paced beats are better classified by the Matching Pursuits time-frequency descriptors, while the wide variety of bizarre premature ventricular contractions are better recognized by the morphological descriptors.

Algorithms↗
PubMed1997

Statistical analysis of highly skewed immune response data.

This paper considers methods of statistical analysis for highly skewed immune response data. Observations from population studies of immunological variables are rarely normally distributed between individuals; typically the distribution shows extreme levels of skewness. In some situations, skewness remains considerable even after transforming the data. Using resampling techniques, applied to several actual datasets of ELISA assay data, we consider the robustness of normal parametric methods, e.g. t tests and linear regression. Despite the skewness of the transformed data, we demonstrate that such methods are quite robust depending on the number of observations, type of analysis and severity of skewness. We also illustrate how bootstrap resampling can be used to provide a valid alternative method of analysis that can be used either for checking normal parametric analysis or as a direct method of analysis. We illustrate this combined approach by analysing real data to test for association between human serum antibodies to malaria merozoite surface proteins, MSP1 and MSP2, and resistance to clinical malaria, and confirm the protective effect of antibodies to MSP1 and demonstrated a similar protective effect for some antibodies to MSP2.

Animals↗
PubMed2003

Classifying the estrogen receptor status of breast cancers by expression profiles reveals a poor prognosis subpopulation exhibiting high expression of the ERBB2 receptor.

Recent work using expression profiling to computationally predict the estrogen receptor (ER) status of breast tumors has revealed that certain tumors are characterized by a high prediction uncertainty ('low-confidence'). We analyzed these 'low-confidence' tumors and determined that their 'uncertain' prediction status arises as a result of widespread perturbations in multiple genes whose expression is important for ER subtype discrimination. Patients with 'low-confidence' ER+ tumors exhibited a significantly worse overall survival (P=0.03) and shorter time to distant metastasis (P=0.004) compared with their 'high-confidence' ER+ counterparts, indicating that the 'high-' and 'low-confidence' binary distinction is clinically meaningful. We then discovered that elevated expression of the ERBB2 receptor is significantly correlated with a breast tumor exhibiting a 'low-confidence' prediction, and this association was subsequently validated across multiple independently derived breast cancer expression datasets employing a variety of different array technologies and patient populations. Although ERBB2 signaling has been proposed to inhibit the transcriptional activity of ER, a large proportion of the perturbed genes in the 'low-confidence'/ERBB2+ samples are not known to be estrogen responsive, and a recently described bioinformatic algorithm (DEREF) was used to demonstrate the absence of potential estrogen-response elements (EREs) in their promoters. We propose that a significant portion of ERBB2's effects on ER+ breast tumors may involve ER-independent mechanisms of gene activation, which may contribute to the clinically aggressive behavior of the 'low-confidence' breast tumor subtype.

Algorithms↗
PubMed2004

Using simulation-based inference with panel data in health economics.

Panel datasets provide a rich source of information for health economists, offering the scope to control for individual heterogeneity and to model the dynamics of individual behaviour. However the qualitative or categorical measures of outcome often used in health economics create special problems for estimating econometric models. Allowing a flexible specification of the autocorrelation induced by individual heterogeneity leads to models involving higher order integrals that cannot be handled by conventional numerical methods. The dramatic growth in computing power over recent years has been accompanied by the development of simulation-based estimators that solve this problem. This review uses binary choice models to show what can be done with conventional methods and how the range of models can be expanded by using simulation methods. Practical applications of the methods are illustrated using data on health from the British Household Panel Survey (BHPS).

Bayes Theorem↗
PubMed2000

Clinical and economic outcomes assessment in nuclear cardiology.

The future of nuclear medicine procedures, as understood within our current economic climate, depends upon its ability to provide relevant clinical information at similar or lower comparative costs. With an ever-increasing emphasis on cost containment, outcome assessment forms the basis of preserving the quality of patient care. Today, outcomes assessment encompasses a wide array of subjects including clinical, economic, and humanistic (i.e., quality of life) outcomes. For nuclear cardiology, evidence-based medicine would require a threshold level of evidence in order to justify the added cost of any test in a patient's work-up. This evidence would include large multicenter, observational series as well as randomized trial data in sufficiently large and diverse patient populations. The new movement in evidence-based medicine is also being applied to the introduction of new technologies, in particular when comparative modalities exist. In the past 5 years, we have seen a dramatic shift in the quality of outcomes data published in nuclear cardiology. This includes the use of statistically rigorous risk-adjusted techniques as well as large populations (i.e., > 500 patients) representing multiple diverse medical care settings. This has been the direct result of the development of multiple outcomes databases that have now amassed thousands of patients worth of data. One of the benefits of examining outcomes in large patient datasets is the ability to assess individual endpoints (e.g., cardiac death) as compared with smaller datasets that often assess combined endpoints (e.g., death, myocardial infarction, or unstable angina). New technologies for the diagnosis of coronary artery disease have contributed to the rising costs of care. In the United States and in Europe, costs of care have risen dramatically, consuming an ever-increasing amount of available resources. The overuse of diagnostic angiography often leads to unnecessary revascularization that does not lead to improvement in outcome. Thus, the potential exists that stress SPECT imaging, a highly effective diagnostic tool, could effect substantial change in reducing inappropriate use of an invasive procedure resulting in cost effective cardiac care. A synthesis of current economic evidence in gated SPECT imaging will be presented. In conclusion, a current state of the evidence review is presented on the clinical and economic data using nuclear cardiology imaging.

Angiography↗
PubMed2002

A latent autoregressive model for longitudinal binary data subject to informative missingness.

Longitudinal clinical trials often collect long sequences of binary data. Our application is a recent clinical trial in opiate addicts that examined the effect of a new treatment on repeated binary urine tests to assess opiate use over an extended follow-up. The dataset had two sources of missingness: dropout and intermittent missing observations. The primary endpoint of the study was comparing the marginal probability of a positive urine test over follow-up across treatment arms. We present a latent autoregressive model for longitudinal binary data subject to informative missingness. In this model, a Gaussian autoregressive process is shared between the binary response and missing-data processes, thereby inducing informative missingness. Our approach extends the work of others who have developed models that link the various processes through a shared random effect but do not allow for autocorrelation. We discuss parameter estimation using Monte Carlo EM and demonstrate through simulations that incorporating within-subject autocorrelation through a latent autoregressive process can be very important when longitudinal binary data is subject to informative missingness. We illustrate our new methodology using the opiate clinical trial data.

Algorithms↗
PubMed1996

Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors.

Multivariable regression models are powerful tools that are used frequently in studies of clinical outcomes. These models can use a mixture of categorical and continuous variables and can handle partially observed (censored) responses. However, uncritical application of modelling techniques can result in models that poorly fit the dataset at hand, or, even more likely, inaccurately predict outcomes on new subjects. One must know how to measure qualities of a model's fit in order to avoid poorly fitted or overfitted models. Measurement of predictive accuracy can be difficult for survival time data in the presence of censoring. We discuss an easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities. Both types of predictive accuracy should be unbiasedly validated using bootstrapping or cross-validation, before using predictions in a new data series. We discuss some of the hazards of poorly fitted and overfitted regression models and present one modelling strategy that avoids many of the problems discussed. The methods described are applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes. Methods are illustrated with a survival analysis in prostate cancer using Cox regression.

Clinical Trials as Topic↗
PubMed2001

Comparison of cellulose, modified cellulose and synthetic membranes in the haemodialysis of patients with end-stage renal disease.

BACKGROUND: When the kidney fails the blood borne metabolites of protein breakdown and water cannot be excreted. The principle of haemodialysis is that such substances can be removed when blood is passed over a semipermeable membrane. Natural membrane materials can be used including cellulose or modified cellulose, more recently various synthetic membranes have been developed. Synthetic membranes are regarded as being more "biocompatible" in that they incite less of an immune response than cellulose-based membranes. OBJECTIVES: To assess the effects of different haemodialysis membrane material in patients with end-stage renal disease (ESRD). SEARCH STRATEGY: We searched Medline (1966 to December 2000), Embase (1981 to November 2000), PreMedline (29 November 2000), HealthStar (1975 to December 2000), Cinahl (1982 to October 2000), The Cochrane Controlled Trials Register (Issue 1, 1996), Biosis (1989 to June 1995), Sigle (1980 to June 1996), Crib (10th edition, 1995), UK National Research Register (September 1996), and reference lists of relevant articles. We contacted biomedical companies, investigators and we hand searched Kidney International (1980 to 1997). Date of the most recent searches: November 2000. SELECTION CRITERIA: All randomised or quasi-randomised clinical trials comparing different haemodialysis membrane material in patients with ESRD. DATA COLLECTION AND ANALYSIS: Two reviewers independently assessed the methodological quality of studies. Data was abstracted from included studies onto a standard form by one reviewer and checked by another. MAIN RESULTS: Twenty seven studies met our inclusion criteria and where possible data from these were summated by meta-analyses (Peto's odds ratio (OR) and weighted mean difference (WMD) with 95% confidence intervals (CI)). Twenty two outcome measures were sought in 10 broad areas. For two (number of episodes of significant infection per year and quality of life) no data were available. For the comparison of cellulose with synthetic membranes, data for 12/20 outcome measures were available in only a single trial. For modified cellulose and synthetic membranes, data for three outcome measures were available in one trial only and for 12 of the outcomes no data were found, crossover studies were analysed separately and studies which randomised by patient yet analysed by dialysis sessions adjusted for clustering. Pre-dialysis beta2 microglobulin concentrations were significantly lower at the end of the studies in patients treated with synthetic membranes (WMD - 14.5; 95% CI -17.4 to -11.6). One crossover study showed a lowering of beta2 microglobulin when low flux synthetic membranes were used. When analysed for a change in beta2 microglobulin across a trial a fall was only noted when high flux membranes were used. In one very small study the incidence of amyloid was less in patients who were dialysed for six years with high flux synthetic membranes (OR 0.05; 95% CI 0.01 to 0.18). In the single study which measured triglyceride values there was a significant difference in favour of the synthetic (high flux) membrane (WMD -0.66; 95% CI -1.18 to -0.14). Serum albumin was higher in patients treated with synthetic membranes (both low and high flux) although this just bordered statistical significance (WMD -0.09; 95% CI -0.18 to 0.00). Dialysis adequacy measured by Kt/V was marginally higher when cellulose membranes were used (WMD 0.10; 95% CI 0.04 to 0.16). There was no significant difference between these membranes for any of the other clinical outcomes measures but confidence intervals were generally wide. No differences were found between modified cellulose and synthetic membranes although many fewer trials were carried out for this comparison. REVIEWER'S CONCLUSIONS: For clinical practice This systematic literature review has generated no evidence of benefit when synthetic membranes were used compared with cellulose/modified cellulose membranes in terms of reduced mortality nor reduction in dialysis related adverse symptoms. Despite the relatively large number of RCTs undertaken in this area none of the included studies reported any measures of quality of life. End-of-study beta2 microglobulin values, and possibly the development of amyloid disease, were less in patients treated with synthetic membranes compared with cellulose membranes. Plasma triglyceride values were also lower with synthetic membranes in the single study that measured this outcome. Differences in these outcomes may have reflected the high flux of the synthetic membrane. Serum albumin was higher when synthetic membranes of both high and low flux were used. Kt/V and urea reduction ratio were higher when cellulose or modified cellulose membranes were used in the few studies that measured these outcomes. We are hesitant to recommend the universal use of synthetic membranes for haemodialysis in patients with ESRD because of; the small number of trials (particularly for modified cellulose membranes, most with low patient numbers), the heterogeneity of many of the trials compared, the variations in membrane flux, the differences in exclusion criteria, particularly relating to comorbidity and the relative lack of patient-centred outcomes studied. Such evidence as we have favours synthetic membranes but even if we assume extra benefit it may be at considerable cost, particularly if high flux synthetic membranes were to be used. For further research A further systematic review of RCTs comparing high and low flux haemodialysis membranes, subgrouped according to membrane composition (cellulose, modified cellulose, synthetic) and reporting clinical outcomes of major importance to patients needs to be undertaken. Further pragmatic RCTs are required to compare the different dialysis membranes available. We recommend that they: - Take into account other properties including flux as well as the material from which the membrane is made and test modified cellulose membranes as well as standard ones. - Record an agreed minimum dataset on primary outcomes of major importance to patients. - Explicitly record whether symptoms are patient- or staff-reported recognising that generally patient reporting will be more appropriate for evaluating effectiveness but staff reported data may be necessary for calculating the cost of treating complications. - Be multi-centre (and possibly multinational) to have sufficient patients to complete the study to allow for a considerable number of withdrawals and dropouts. - Have sufficient length of follow up to draw conclusions for important clinical outcome measures and continue to follow patients who have renal transplants. - Include older patients and those with comorbid illnesses and take into account age and comorbidity when assessing outcomes (possibly by stratification at trial entry). - Carry out, in parallel, an economic evaluation of the different policies being compared in the trial.

Cellulose↗
PubMed2004

Association of common T cell activation gene polymorphisms with multiple sclerosis in Australian patients.

Susceptibility to multiple sclerosis (MS) may be influenced by the interaction of several genes within a biological pathway. T cell activation and costimulation may be potentially important in MS pathogenesis. We have therefore investigated associations between MS and polymorphisms in the CD152 (CTLA-4), CD28, CD80 and CD86 genes in Australian patients. We found no significant MS association with CTLA-4 exon 1 +49 alleles, and meta-analysis showed no significant association across nine comparable datasets (OR=1.04, p=0.54), nor with primary progressive MS across seven datasets (OR=1.19, p=0.21). Haplotype analysis showed a trend towards a decrease of the CTLA-4-1722C, -1577G, +49G haplotype in +49 G positive MS patients compared with controls (p=0.06). Screening of CD28, CD80 and CD86 genes identified novel polymorphisms in the putative promoter regions of CD28 (-372 G/A) and CD86 (exon 2 -359 deletionAAG). There was a significant increase of the CD28 -372 G allele frequency in MS patients vs. controls (p=0.045) and a trend towards a significant interaction between this allele and the CTLA-4 +49 G allele (OR=4.00, p=0.058). Our results suggest that the CTLA-4 +49 alone is not associated with overall susceptibility to MS, but may be important in clinical subsets of patients and/or may interact epistatically with other gene polymorphisms.

Antigens, CD↗