An investigation of the impact of using different methods for network meta-analysis: A protocol for an empirical evaluation

BACKGROUND: Network meta-analysis, a method to synthesise evidence from multiple treatments, has increased in popularity in the past decade. Two broad approaches are available to synthesise data across networks, namely, arm- and contrast-synthesis models, with a range of models that can be fitted within each. There has been recent debate about the validity of the arm-synthesis models, but to date, there has been limited empirical evaluation comparing results using the methods applied to a large number of networks. We aim to address this gap through the re-analysis of a large cohort of published networks of interventions using a range of network meta-analysis methods. METHODS: We will include a subset of networks from a database of network meta-analyses of randomised trials that have been identified and curated from the published literature. The subset of networks will include those where the primary outcome is binary, the number of events and participants are reported for each direct comparison, and there is no evidence of inconsistency in the network. We will re-analyse the networks using three contrast-synthesis methods and two arm-synthesis methods. We will compare the estimated treatment effects, their standard errors, treatment hierarchy based on the surface under the cumulative ranking (SUCRA) curve, the SUCRA value, and the between-trial heterogeneity variance across the network meta-analysis methods. We will investigate whether differences in the results are affected by network characteristics and baseline risk. DISCUSSION: The results of this study will inform whether, in practice, the choice of network meta-analysis method matters, and if it does, in what situations differences in the results between methods might arise. The results from this research might also inform future simulation studies

Challenges in Estimating Insecticide Selection Pressures from Mosquito Field Data

Insecticide resistance has the potential to compromise the enormous effort put into the control of dengue and malaria vector populations. It is therefore important to quantify the amount of selection acting on resistance alleles, their contributions to fitness in heterozygotes (dominance) and their initial frequencies, as a means to predict the rate of spread of resistance in natural populations. We investigate practical problems of obtaining such estimates, with particular emphasis on Mexican populations of the dengue vector Aedes aegypti. Selection and dominance coefficients can be estimated by fitting genetic models to field data using maximum likelihood (ML) methodology. This methodology, although widely used, makes many assumptions so we investigated how well such models perform when data are sparse or when spatial and temporal heterogeneity occur. As expected, ML methodologies reliably estimated selection and dominance coefficients under idealised conditions but it was difficult to recover the true values when datasets were sparse during the time that resistance alleles increased in frequency, or when spatial and temporal heterogeneity occurred. We analysed published data on pyrethroid resistance in Mexico that consists of the frequency of a Ile1,016 mutation. The estimates for selection coefficient and initial allele frequency on the field dataset were in the expected range, dominance coefficient points to incomplete dominance as observed in the laboratory, although these estimates are accompanied by strong caveats about possible impact of spatial and temporal heterogeneity in selection

Canalization and developmental stability in the Brachyrrhine mouse

The semi-dominant Br mutation affects presphenoid growth, producing the facial retrognathism and globular neurocranial vault that characterize heterozygotes. We analysed the impact of this mutation on skull shape, comparing heterozygotes to wildtype mice, to determine if the effects are skull-wide or confined to the sphenoid region targeted by the mutation. In addition, we examined patterns of variability of shape for the skull as a whole and for three regions (basicranium, face and neurocranium). We found that the Br mice differed significantly from wildtype mice in skull shape in all three regions as well as in the shape of the skull as a whole. However, the significant increases in variance and fluctuating asymmetry were found only in the basicranium of mutant mice. These results suggest that the mutation has a significant effect on the underlying developmental architecture of the skull, which produces an increase in phenotypic variability that is localized to the anatomical region in which the mean phenotype is most dramatically affected. These results suggest that the same developmental mechanisms that produce the change in phenotypic mean also produce the change in variance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75710/1/j.1469-7580.2006.00527.x.pd

Highly Efficient Amplification of Chronic Wasting Disease Agent by Protein Misfolding Cyclic Amplification with Beads (PMCAb)

Protein misfolding cyclic amplification (PMCA) has emerged as an important technique for detecting low levels of pathogenic prion protein in biological samples. The method exploits the ability of the pathogenic prion protein to convert the normal prion protein to a proteinase K-resistant conformation. Inclusion of Teflon® beads in the PMCA reaction (PMCAb) has been previously shown to increase the sensitivity and robustness of detection for the 263 K and SSLOW strains of hamster-adapted prions. Here, we demonstrate that PMCAb with saponin dramatically increases the sensitivity of detection for chronic wasting disease (CWD) agent without compromising the specificity of the assay (i.e., no false positive results). Addition of Teflon® beads increased the robustness of the PMCA reaction, resulting in a decrease in the variability of PMCA results. Three rounds of serial PMCAb allowed detection of CWD agent from a 6.7×10−13 dilution of 10% brain homogenate (1.3 fg of source brain). Titration of the same brain homogenate in transgenic mice expressing cervid prion protein (Tg(CerPrP)1536+/− mice) allowed detection of CWD agent from the 10−6 dilution of 10% brain homogenate. PMCAb is, thus, more sensitive than bioassay in transgenic mice by a factor exceeding 105. Additionally, we are able to amplify CWD agent from brain tissue and lymph nodes of CWD-positive white-tailed deer having Prnp alleles associated with reduced disease susceptibility

Homing and Long-Term Engraftment of Long- and Short-Term Renewal Hematopoietic Stem Cells

Long-term hematopoietic stem cells (LT-HSC) and short-term hematopoietic stem cells (ST-HSC) have been characterized as having markedly different in vivo repopulation, but similar in vitro growth in liquid culture. These differences could be due to differences in marrow homing. We evaluated this by comparing results when purified ST-HSC and LT-HSC were administered to irradiated mice by three different routes: intravenous, intraperitoneal, and directly into the femur. Purified stem cells derived from B6.SJL mice were competed with marrow cells from C57BL/6J mice into lethally irradiated C57BL/6J mice. Serial transplants into secondary recipients were also carried out. We found no advantage for ST-HSC engraftment when the cells were administered intraperitoneally or directly into femur. However, to our surprise, we found that the purified ST-HSC were not short-term in nature but rather gave long-term multilineage engraftment out to 387 days, albeit at a lower level than the LT-HSC. The ST-HSC also gave secondary engraftment. These observations challenge current models of the stem cell hierarchy and suggest that stem cells are in a continuum of change

Utilisation of an operative difficulty grading scale for laparoscopic cholecystectomy

Background A reliable system for grading operative difficulty of laparoscopic cholecystectomy would standardise description of findings and reporting of outcomes. The aim of this study was to validate a difficulty grading system (Nassar scale), testing its applicability and consistency in two large prospective datasets. Methods Patient and disease-related variables and 30-day outcomes were identified in two prospective cholecystectomy databases: the multi-centre prospective cohort of 8820 patients from the recent CholeS Study and the single-surgeon series containing 4089 patients. Operative data and patient outcomes were correlated with Nassar operative difficultly scale, using Kendall’s tau for dichotomous variables, or Jonckheere–Terpstra tests for continuous variables. A ROC curve analysis was performed, to quantify the predictive accuracy of the scale for each outcome, with continuous outcomes dichotomised, prior to analysis. Results A higher operative difficulty grade was consistently associated with worse outcomes for the patients in both the reference and CholeS cohorts. The median length of stay increased from 0 to 4 days, and the 30-day complication rate from 7.6 to 24.4% as the difficulty grade increased from 1 to 4/5 (both p < 0.001). In the CholeS cohort, a higher difficulty grade was found to be most strongly associated with conversion to open and 30-day mortality (AUROC = 0.903, 0.822, respectively). On multivariable analysis, the Nassar operative difficultly scale was found to be a significant independent predictor of operative duration, conversion to open surgery, 30-day complications and 30-day reintervention (all p < 0.001). Conclusion We have shown that an operative difficulty scale can standardise the description of operative findings by multiple grades of surgeons to facilitate audit, training assessment and research. It provides a tool for reporting operative findings, disease severity and technical difficulty and can be utilised in future research to reliably compare outcomes according to case mix and intra-operative difficulty

Women Have Higher Protein Content of β-Oxidation Enzymes in Skeletal Muscle than Men

It is well recognized that compared with men, women have better ultra-endurance capacity, oxidize more fat during endurance exercise, and are more resistant to fat oxidation defects i.e. diet-induced insulin resistance. Several groups have shown that the mRNA and protein transcribed and translated from genes related to transport of fatty acids into the muscle are greater in women than men; however, the mechanism(s) for the observed sex differences in fat oxidation remains to be determined. Muscle biopsies from the vastus lateralis were obtained from moderately active men (N = 12) and women (N = 11) at rest to examine mRNA and protein content of genes involved in lipid oxidation. Our results show that women have significantly higher protein content for tri-functional protein alpha (TFPα), very long chain acyl-CoA dehydrogenase (VLCAD), and medium chain acyl-CoA dehydrogenase (MCAD) (P<0.05). There was no significant sex difference in the expression of short-chain hydroxyacyl-CoA dehydrogenase (SCHAD), or peroxisome proliferator activated receptor alpha (PPARα), or PPARγ, genes potentially involved in the transcriptional regulation of lipid metabolism. In conclusion, women have more protein content of the major enzymes involved in long and medium chain fatty acid oxidation which could account for the observed differences in fat oxidation during exercise

Translating Clinical Findings into Knowledge in Drug Safety Evaluation - Drug Induced Liver Injury Prediction System (DILIps)

Drug-induced liver injury (DILI) is a significant concern in drug development due to the poor concordance between preclinical and clinical findings of liver toxicity. We hypothesized that the DILI types (hepatotoxic side effects) seen in the clinic can be translated into the development of predictive in silico models for use in the drug discovery phase. We identified 13 hepatotoxic side effects with high accuracy for classifying marketed drugs for their DILI potential. We then developed in silico predictive models for each of these 13 side effects, which were further combined to construct a DILI prediction system (DILIps). The DILIps yielded 60–70% prediction accuracy for three independent validation sets. To enhance the confidence for identification of drugs that cause severe DILI in humans, the “Rule of Three” was developed in DILIps by using a consensus strategy based on 13 models. This gave high positive predictive value (91%) when applied to an external dataset containing 206 drugs from three independent literature datasets. Using the DILIps, we screened all the drugs in DrugBank and investigated their DILI potential in terms of protein targets and therapeutic categories through network modeling. We demonstrated that two therapeutic categories, anti-infectives for systemic use and musculoskeletal system drugs, were enriched for DILI, which is consistent with current knowledge. We also identified protein targets and pathways that are related to drugs that cause DILI by using pathway analysis and co-occurrence text mining. While marketed drugs were the focus of this study, the DILIps has a potential as an evaluation tool to screen and prioritize new drug candidates or chemicals, such as environmental chemicals, to avoid those that might cause liver toxicity. We expect that the methodology can be also applied to other drug safety endpoints, such as renal or cardiovascular toxicity