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Trait ERK1/2 signaling characteristics differentiates necroptosis via apoptosis.
BACKGROUND Adaptive design methodology has been well studied for continuous, binary, and survival outcomes for decades. However, for complicated endpoints such as recurrent hospitalization in the joint frailty setting and composite endpoint in the win-ratio setting, adaptive design is not intuitive because of sophistication in existing methods to perform sample size re-estimation. METHODS The objective of this paper is to propose a practical generalized approach to implement the above activities at the interim stage through approximation so that sample size re-estimation becomes easily understood and readily amenable. RESULTS Through simulations on representative complex situations, the proposed method can maintain the planned statistical power by sample size re-estimation while controlling the type I error. CONCLUSION The proposed adaptive approach is easy to implement in general sample size re-estimation situations. Its validity can be verified through simulation under varying scenarios. In summary, this approach offers a transparent communication channel with regulatory agencies to facilitate clinical trial development regardless of the complexity of the underlying situations.Inconsistent results across regions have been reported in a number of recent large trials. In this research, by reviewing results from studies that showed inconsistent treatment effects, and summarizing lessons learned, we provide some recommendations for minimizing the chance of inconsistency and allowing more accurate interpretation when such signs of heterogeneity arise, for example keep the number of regions for consistency evaluation at a minimum to avoid observing false inconsistency signals; proactively address in the protocol the differences in culture, medical practices, and other factors that are potentially different across regions; closely monitor the blinded data from early-enrolled patients to more effectively identify and address issues such as imbalance of baseline covariates or inconsistency of primary outcome rates across regions. For treatments of life-threatening conditions, the stakes for accurate interpretation of MRCT results are high; the criteria for decisions warrant careful consideration.BACKGROUND Delays in clinical trial enrollment and difficulties enrolling representative samples continue to vex sponsors, sites, and patient populations. Here we investigated use of an artificial intelligence-powered technology, Mendel.ai, as a means of overcoming bottlenecks and potential biases associated with standard patient prescreening processes in an oncology setting. METHODS Mendel.ai was applied retroactively to 2 completed oncology studies (1 breast, 1 lung), and 1 study that failed to enroll (lung), at the Comprehensive Blood and Cancer Center, allowing direct comparison between results achieved using standard prescreening practices and results achieved with Mendel.ai. selleck chemicals llc Outcome variables included the number of patients identified as potentially eligible and the elapsed time between eligibility and identification. RESULTS For each trial that enrolled, use of Mendel.ai resulted in a 24% to 50% increase over standard practices in the number of patients correctly identified as potentially eligible. No patients correctly identified by standard practices were missed by Mendel.ai. For the nonenrolling trial, both approaches failed to identify suitable patients. An average of 19 days for breast and 263 days for lung cancer patients elapsed between actual patient eligibility (based on clinical chart information) and identification when the standard prescreening practice was used. In contrast, ascertainment of potential eligibility using Mendel.ai took minutes. CONCLUSIONS This study suggests that augmentation of human resources with artificial intelligence could yield sizable improvements over standard practices in several aspects of the patient prescreening process, as well as in approaches to feasibility, site selection, and trial selection.BACKGROUND Non-alcoholic fatty liver disease (NAFLD) is the liver manifestation of metabolic syndrome, a risk factor for mortality and cardiovascular morbidity, but we ignore the role of steatosis per se in survival, and there is very little information about this condition in the geriatric patient. AIMS With the present study, we investigated the independent prognostic value of NAFLD on overall mortality in the elderly. METHODS Within the Pianoro Project, involving people ≥ 65 years, anamnestic, clinical and laboratoristic data related to NAFLD, insulin resistance, diabetes/hyperglycemia, hypertension, obesity and dyslipidemia were collected in 804 subjects (403 male, 401 female). These subjects were followed up for mortality for a median time of 12.6 years. A multivariate analysis was performed to evaluate the prognostic value of the covariates. RESULTS At Kaplan-Meier estimator the presence of NAFLD seems to be associated to a lower mortality, and survival tends to increase with the increasing of steatosis grade. Cox's analysis found that survival is increased for subjects having hypercholesterolemia (RR = 0.565), NAFLD (RR = 0.777), hypertension (RR = 0.711) and in female (RR = 0.741), while it is decreased for the older subjects (RR = 3.046), in patients with hypertriglyceridemia (RR = 1.699) and for diabetics (RR = 1.797). The variables BMI and HDL-cholesterol have no role. CONCLUSION The data obtained in our study show that NAFLD is not associated to overall mortality in the elderly population.BACKGROUND Older adults experience greater cognitive motor interference (CMI) due to declines in cognitive and physical function. Although aerobic fitness has beneficial effects on cognition, its association with CMI is not clear. AIMS This study aims to investigate the effects of aerobic fitness on CMI during self-paced treadmill walking in older adults. METHODS Thirty participants (67.6 ± 10.34 years, 21 females) were included in a 2-day cross-sectional design study. Aerobic fitness was assessed with the Rockport 1-mile test. The dual-task paradigm consisted of walking only, and dual-task standing and dual-task walking (i.e., standing/walking while performing the Modified Stroop color word test) on a treadmill. To assess CMI, gait speed and accuracy rate were measured to later calculate the dual-task cost for each parameter. RESULTS Individuals with low aerobic fitness exhibited significantly greater gait speed dual-task cost than individuals with high aerobic fitness (p  less then  0.05). There were no significant findings for accuracy rate dual-task cost.
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