A computer vision approach to improving cattle digestive health by the monitoring of faecal samples.

The digestive health of cows is one of the primary factors that determine their well-being and productivity. Under- and over-feeding are both commonplace in the beef and dairy industry; leading to welfare issues, negative environmental impacts, and economic losses. Unfortunately, digestive health is difficult for farmers to routinely monitor in large farms due to many factors including the need to transport faecal samples to a laboratory for compositional analysis. This paper describes a novel means for monitoring digestive health via a low-cost and easy to use imaging device based on computer vision. The method involves the rapid capture of multiple visible and near-infrared images of faecal samples. A novel three-dimensional analysis algorithm is then applied to objectively score the condition of the sample based on its geometrical features. While there is no universal ground truth for comparison of results, the order of scores matched a qualitative human prediction very closely. The algorithm is also able to detect the presence of undigested fibres and corn kernels using a deep learning approach. Detection rates for corn and fibre in image regions were of the order 90%. These results indicate the potential to develop this system for on-farm, real time monitoring of the digestive health of individual animals, allowing early intervention to effectively adjust feeding strategy.

Predictors of the placebo analgesia response in randomized controlled trials of chronic pain: a meta-analysis of the individual data from nine industrially sponsored trials.

A large number of analgesics have failed to prove superiority over placebo in randomized controlled trials (RCTs), and as this has been related to increasing placebo responses, there is currently an interest in specifying predictors of the placebo response. The literature on placebo mechanisms suggests that factors related to patients' expectations of treatment efficacy are pivotal for the placebo response. Also, general characteristics of RCTs have been suggested to influence the placebo response. Yet, only few meta-analyses have directly tested these hypotheses. Placebo data from 9 industrially sponsored, randomized, double-blind, placebo-controlled, multicenter phase III trials in 2017 adult patients suffering from chronic painful osteoarthritis (hip or knee) or low back pain were included. The primary outcome was pain intensity. Based on previous studies, we chose 3 expectancy-related primary predictors: type of active medication, randomization ratio, and number of planned face-to-face visits. In addition, explorative analyses tested whether RCT and patients' characteristics predicted the placebo response. Opioid trials, a high number of planned face-to-face visits, and randomization ratio predicted the magnitude of the placebo response, thereby supporting the expectancy hypothesis. Exploratory models with baseline pain intensity, age, washout length, and discontinuation because of adverse events accounted for approximately 10% of the variability in the placebo response. Based on these results and previous mechanisms studies, we think that patients' perception of treatment allocation and expectations toward treatment efficacy could potently predict outcomes of RCTs.

Multiplicity: discussion points from the Statisticians in the Pharmaceutical Industry multiplicity expert group.

In May 2012, the Committee of Health and Medicinal Products issued a concept paper on the need to review the points to consider document on multiplicity issues in clinical trials. In preparation for the release of the updated guidance document, Statisticians in the Pharmaceutical Industry held a one-day expert group meeting in January 2013. Topics debated included multiplicity and the drug development process, the usefulness and limitations of newly developed strategies to deal with multiplicity, multiplicity issues arising from interim decisions and multiregional development, and the need for simultaneous confidence intervals (CIs) corresponding to multiple test procedures. A clear message from the meeting was that multiplicity adjustments need to be considered when the intention is to make a formal statement about efficacy or safety based on hypothesis tests. Statisticians have a key role when designing studies to assess what adjustment really means in the context of the research being conducted. More thought during the planning phase needs to be given to multiplicity adjustments for secondary endpoints given these are increasing in importance in differentiating products in the market place. No consensus was reached on the role of simultaneous CIs in the context of superiority trials. It was argued that unadjusted intervals should be employed as the primary purpose of the intervals is estimation, while the purpose of hypothesis testing is to formally establish an effect. The opposing view was that CIs should correspond to the test decision whenever possible.

Preliminary assessment of safety and efficacy in proof-of-concept, randomized clinical trial of tanezumab for chronic prostatitis/chronic pelvic pain syndrome.

OBJECTIVE: To assess the efficacy and safety of tanezumab, a humanized monoclonal antibody directed against the pain-mediating neurotrophin, nerve growth factor, to treat pain and other symptoms of chronic prostatitis/chronic pelvic pain syndrome in a Phase IIa, proof-of-concept clinical trial powered to provide 2-sided 90% confidence interval around the primary endpoint. METHODS: Patients received a single intravenous dose of tanezumab (20 mg) or placebo. The primary efficacy endpoint was the change from baseline to week 6 in average daily numerical rating scale pain score. The secondary endpoints included the change from baseline to week 6 in the National Institutes of Health Chronic Prostatitis Symptom Index and urinary symptoms. Safety was also assessed. RESULTS: Overall, 62 patients were randomized (30 to tanezumab and 32 to placebo). At week 6, tanezumab marginally improved the average daily pain (least-squares mean difference from placebo -0.47, 90% confidence interval -1.150-0.209) and urgency episode frequency (least-squares mean difference from placebo -1.37, 90% confidence interval -3.146-0.401). No difference was seen in the National Institutes of Health chronic prostatitis symptom index total score or micturition frequency at week 6. The most common adverse events were paresthesia and arthralgia. The odds of having a ≥ 30% reduction in pain were 1.75-fold greater (90% confidence interval 0.65-4.69) for patients receiving tanezumab versus placebo. CONCLUSION: Tanezumab might improve symptoms for some patients with chronic prostatitis/chronic pelvic pain syndrome. Although proof of concept was not demonstrated in the present study, additional studies with larger populations and stricter inclusion criteria according to patient phenotype might identify populations in which antinerve growth factor treatment will provide clinical benefit.