The aim of the study was to examine the prevalence and amount of ( ), ( ) and ( ) in the saliva of colorectal cancer (CRC) patients and controls. PCR analyses performed in 71 CRC patients and 77 controls. Saliva samples of patients had higher amounts of (p = 0.001) and (p < 0.001) compared with controls. Amount of and were lower in the microsatellite instability (+) group. Evaluation of salivary amount by receiver operating characteristics analysis found to have diagnostic value for CRC (AUC: 0.84, 95% CI: 0.72–0.96). We found higher amounts of and in the saliva of CRC patients. Salivary could helpful in distinction of CRC.
This paper provides a comprehensive analysis of Australian net energy consumption between 2004–05 and 2014–15. Results from environmentally-extended input-output (EEIO) analysis show that the Transport sector has the largest direct effect on net energy consumption in industrial sectors, which decreased by about 35% for net energy consumption per million $AUD in the period. The Export sector has the largest direct net energy consumption while Households consumption results in the largest net energy consumption embodied in different categories of Final demand. The structural decomposition analysis (SDA) decomposes the change of net energy consumption into five drivers, in which net energy intensity mainly reduces Australian net energy consumption by about 8000 Petajoules, while the level effect of Final demand increases it by about 10,000 Petajoules. Analysis of forward and backward linkages highlights the Manufacturing sector as the key industrial sector with the largest energy consumption reduction potential via minor changes in its input and Final demand. This indicates that more attention should be given to the reduction of energy demand from the consumption patterns of Households consumption, the improvement of energy intensity, and the application of cleaner technologies in the Transport and Manufacturing sectors. The Australian Environmental-Economic Accounts is combined with Australian input-output tables to construct the EEIO tables for net energy consumption. The combination of economic and environmental data sets provides a depth of understanding their potential to inform environmental policy decisions. The novelty of the research is the combination of economic and energy data sets, the application of EEIO model, the implementation of the additive SDA method, and the use of forward and backward linkages for the Australian energy system.
There are numerous systemic medications in use for psoriasis, with additional investigational agents being studied. However, head-to-head, randomized clinical trials are rare and cannot feasibly compare all treatments. A network meta-analysis (NMA) synthesizes the available evidence to provide estimates for all pairwise comparisons. Here, we summarize and appraise two recent NMAs that assessed systemic therapies for moderate-to-severe psoriasis. Two systematic reviews searched databases and the grey literature to identify relevant randomized clinical trials. The reviews mostly included trials that involved adults with moderate-to-severe psoriasis. One of the reviews also included two trials involving children. Interventions common to both reviews include adalimumab, etanercept, infliximab, ustekinumab, ixekizumab, secukinumab and methotrexate. One of the reviews included additional interventions, primarily other biological agents along with new small-molecule treatments and systemic conventional treatments. One review focused on 'clear/nearly clear' and withdrawals from adverse events as study outcomes, while the second review focused on improvement of ≥ 90% measured on the Psoriasis Area and Severity Index (PASI 90) and serious adverse events. Additional outcomes included quality of life, PASI 75, Physician's Global Assessment of 0/1 and any adverse event. Overall, both NMAs are of high quality and provide a comprehensive summary of the evidence base and treatment effects. Results, in terms of both estimates and rankings, suggest that newer biologics targeting the interleukin (IL)-12/23 and IL-17 axes appear to be more effective than older biologics and oral agents. Patients, clinicians and policy makers can use the relative efficacy assessments of NMAs to inform decision making regarding the clearance of psoriasis skin lesions at relevant time points and improvement in quality of life.
Background: Combination therapy based on epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) is an emerging trend in cancer treatment, but the clinical value of EGFR-TKIs combination therapy remains controversial. Thus, we conducted a comprehensive analysis of randomized controlled trials (RCTs) comparing EGFR-TKIs combination therapies with monotherapies, aiming to evaluate the safety and efficacy of EGFR-TKIs based combination therapy and to find a more beneficial combination strategy. Methods: We searched for clinical studies that evaluated EGFR-TKIs combination therapy in cancer. We extracted data from these studies to evaluate the relative risk (RR) of overall response rate (ORR) and grade 3/4 treatment-related adverse events (AEs), the hazard ratios (HRs) of overall survival (OS), and progression-free survival (PFS). Results: Fourteen RCTs were identified (n=3774). Treatments included combinations of EGFR-TKIs and chemotherapy, combinations of EGFR-TKIs and radiotherapy, and combinations of EGFR-TKIs and bevacizumab. EGFR-TKIs combination therapies showed higher ORR [RR: 1.62; 95% confidence interval (95% CI): 1.16-2.26; P=.005], PFS (HR: 0.76; 95% CI: 0.64-0.89; P=.001), and OS (HR: 0.88; 95% CI: 0.79-0.97; P=.013) values than monotherapies. However, higher grade 3/4 treatment-related AEs (RR: 1.79; 95% CI: 1.02-3.15; P=.000) were observed in combination therapy than in monotherapy. Conclusion: Our pooled analysis and subgroup analysis results showed that the addition of chemotherapy to EGFR-TKIs better benefits PFS and safety. Adding bevacizumab was associated with better ORR and OS. The efficacy and safety of a bevacizumab-EGFR-TKIs-chemotherapy combination should be investigated further.
The present study involved segmental testing of hair in two clinical cases with known dosage histories. Hair analysis confirmed the first patient's exposure to the prescribed sertraline and citalopram for several months. Citalopram was generally distributed along the hair shaft in accordance with the drug ingestion period. By contrast, “false” positive results were observed for sertraline in distal hair segments, corresponding to a period of no sertraline exposure, which may indicate incorporation from sweat or sebum, which transport the drugs along the hair surface. The second patient received various drugs during her treatment for brain cancer. Metoclopramide, morphine, oxazepam, paracetamol, sumatriptan, tramadol, and zopiclone, which had been part of the therapy, were all detected in the proximal hair segment. The results of these two cases indicated that results—especially concerning the time of drug intake—must be interpreted with caution and allow for the possibility of incorporation from sweat or sebum.
Estimation of the true prevalence of infected individuals involves the application of a diagnostic test to a population and adjusting according to test performance, sensitivity and specificity. Bayesian latent class analysis for the estimation of herd and animal-level true prevalence, has become increasingly used in veterinary epidemiology and is particularly useful in incorporating uncertainty and variability into analyses in a flexible framework. However, the approach has not yet been evaluated using simulated data where the true prevalence is known. Furthermore, using this approach, the within-herd true prevalence is often assumed to follow a beta distribution, the parameters of which may be modelled using hyperpriors to incorporate both uncertainty and variability associated with this parameter. Recently however, the authors of the current study highlighted a potential issue with this approach, in particular, with fitting the distributions and a tendency for the resulting distribution to invert and become clustered at zero. Therefore, the objective of the present study was to evaluate commonly specified models using simulated datasets where the herd-level true prevalence was known. The specific purpose was to compare findings from models using hyperpriors to those using a simple beta distribution to model within-herd prevalence. A second objective was to investigate sources of error by varying characteristics of the simulated dataset. subspecies infection was used as an example for the baseline dataset. Data were simulated for 1000 herds across a range of herd-level true prevalence scenarios, and models were fitted using priors from recently published studies. The results demonstrated poor performance of these latent class models for diseases characterised by poor diagnostic test sensitivity and low within-herd true prevalence. All variations of the model appeared to be sensitive to the prior and tended to overestimate herd-level true prevalence. Estimates were substantially improved in different infection scenarios by increasing test sensitivity and within-herd true prevalence. The results of this study raise questions about the accuracy of published estimates for the herd-level true prevalence of paratuberculosis based on serological testing, using latent class analysis. This study highlights the importance of conducting more rigorous sensitivity analyses than have been carried out in previous analyses published to date.