Regression models for analyzing radiological visual grading studies – an empirical comparison

Background: For optimizing and evaluating image quality in medical imaging, one can use visual grading experiments, where observers rate some aspect of image quality on an ordinal scale. To analyze the grading data, several regression methods are available, and this study aimed at empirically comparing such techniques, in particular when including random effects in the models, which is appropriate for observers and patients. Methods: Data were taken from a previous study where 6 observers graded or ranked in 40 patients the image quality of four imaging protocols, differing in radiation dose and image reconstruction method. The models tested included linear regression, the proportional odds model for ordinal logistic regression, the partial proportional odds model, the stereotype logistic regression model and rank-order logistic regression (for ranking data). In the first two models, random effects as well as fixed effects could be included; in the remaining three, only fixed effects. Results: In general, the goodness of fit (AIC and McFaddens Pseudo R-2) showed small differences between the models with fixed effects only. For the mixed-effects models, higher AIC and lower Pseudo R-2 was obtained, which may be related to the different number of parameters in these models. The estimated potential for dose reduction by new image reconstruction methods varied only slightly between models. Conclusions: The authors suggest that the most suitable approach may be to use ordinal logistic regression, which can handle ordinal data and random effects appropriately

Machine Learning Models that Remember Too Much

Machine learning (ML) is becoming a commodity. Numerous ML frameworks and services are available to data holders who are not ML experts but want to train predictive models on their data. It is important that ML models trained on sensitive inputs (e.g., personal images or documents) not leak too much information about the training data. We consider a malicious ML provider who supplies model-training code to the data holder, does not observe the training, but then obtains white- or black-box access to the resulting model. In this setting, we design and implement practical algorithms, some of them very similar to standard ML techniques such as regularization and data augmentation, that "memorize" information about the training dataset in the model yet the model is as accurate and predictive as a conventionally trained model. We then explain how the adversary can extract memorized information from the model. We evaluate our techniques on standard ML tasks for image classification (CIFAR10), face recognition (LFW and FaceScrub), and text analysis (20 Newsgroups and IMDB). In all cases, we show how our algorithms create models that have high predictive power yet allow accurate extraction of subsets of their training data

A Layered Architecture for Detecting Malicious Behaviors

We address the semantic gap problem in behavioral monitoring by using hierarchical behavior graphs to infer high-level behaviors from myriad low-level events that could be parts of many different kinds of behavior. Our experimental system traces the execution of a process, performing data-flow analysis to identify meaningful actions such as \u201cproxying\u201d, \u201ckeystroke logging\u201d, \u201cdata leaking\u201d, and \u201cdownloading and executing a program\u201d from complex combinations of rudimentary system calls. To preemptively address evasive malware behavior, our specifications are carefully crafted to detect alternate sequences of events that achieve the same high-level goal. We tested seven malicious bots and eleven benign programs and found that we were able to thoroughly identify high-level behaviors across this diverse code base. Moreover, we were able to distinguish malicious execution of high-level behaviors from benign by distinguishing remotely-initiated from locally-initiated actions

Treatment with disease-modifying drugs for people with a first clinical attack suggestive of multiple sclerosis

Background: The treatment of multiple sclerosis has changed over the last 20 years. The advent of disease-modifying drugs in the mid-1990s heralded a period of rapid progress in the understanding and management of multiple sclerosis. With the support of magnetic resonance imaging early diagnosis is possible, enabling treatment initiation at the time of the first clinical attack. As most of the disease-modifying drugs are associated with adverse events, patients and clinicians need to weigh the benefit and safety of the various early treatment options before taking informed decisions. Objectives: 1. to estimate the benefit and safety of disease-modifying drugs that have been evaluated in all studies (randomised or non-randomised) for the treatment of a first clinical attack suggestive of MS compared either with placebo or no treatment; 2. to assess the relative efficacy and safety of disease-modifying drugs according to their benefit and safety; 3. to estimate the benefit and safety of disease-modifying drugs that have been evaluated in all studies (randomised or non-randomised) for treatment started after a first attack ('early treatment') compared with treatment started after a second attack or at another later time point ('delayed treatment'). Search methods: We searched the Cochrane Multiple Sclerosis and Rare Diseases of the CNS Group Trials Register, MEDLINE, Embase, CINAHL, LILACS, clinicaltrials.gov, the WHO trials registry, and US Food and Drug Administration (FDA) reports, and searched for unpublished studies (until December 2016). Selection criteria: We included randomised and observational studies that evaluated one or more drugs as monotherapy in adult participants with a first clinical attack suggestive of MS. We considered evidence on alemtuzumab, azathioprine, cladribine, daclizumab, dimethyl fumarate, fingolimod, glatiramer acetate, immunoglobulins, interferon beta-1b, interferon beta-1a (Rebif®, Avonex®), laquinimod, mitoxantrone, natalizumab, ocrelizumab, pegylated interferon beta-1a, rituximab and teriflunomide. Data collection and analysis: Two teams of three authors each independently selected studies and extracted data. The primary outcomes were disability-worsening, relapses, occurrence of at least one serious adverse event (AE) and withdrawing from the study or discontinuing the drug because of AEs. Time to conversion to clinically definite MS (CDMS) defined by Poser diagnostic criteria, and probability to discontinue the treatment or dropout for any reason were recorded as secondary outcomes. We synthesized study data using random-effects meta-analyses and performed indirect comparisons between drugs. We calculated odds ratios (OR) and hazard ratios (HR) along with relative 95% confidence intervals (CI) for all outcomes. We estimated the absolute effects only for primary outcomes. We evaluated the credibility of the evidence using the GRADE system. Main results: We included 10 randomised trials, eight open-label extension studies (OLEs) and four cohort studies published between 2010 and 2016. The overall risk of bias was high and the reporting of AEs was scarce. The quality of the evidence associated with the results ranges from low to very low. Early treatment versus placebo during the first 24 months' follow-up There was a small, non-significant advantage of early treatment compared with placebo in disability-worsening (6.4% fewer (13.9 fewer to 3 more) participants with disability-worsening with interferon beta-1a (Rebif®) or teriflunomide) and in relapses (10% fewer (20.3 fewer to 2.8 more) participants with relapses with teriflunomide). Early treatment was associated with 1.6% fewer participants with at least one serious AE (3 fewer to 0.2 more). Participants on early treatment were on average 4.6% times (0.3 fewer to 15.4 more) more likely to withdraw from the study due to AEs. This result was mostly driven by studies on interferon beta 1-b, glatiramer acetate and cladribine that were associated with significantly more withdrawals for AEs. Early treatment decreased the hazard of conversion to CDMS (HR 0.53, 95% CI 0.47 to 0.60). Comparing active interventions during the first 24 months' follow-up Indirect comparison of interferon beta-1a (Rebif®) with teriflunomide did not show any difference on reducing disability-worsening (OR 0.84, 95% CI 0.43 to 1.66). We found no differences between the included drugs with respect to the hazard of conversion to CDMS. Interferon beta-1a (Rebif®) and teriflunomide were associated with fewer dropouts because of AEs compared with interferon beta-1b, cladribine and glatiramer acetate (ORs range between 0.03 and 0.29, with substantial uncertainty). Early versus delayed treatment We did not find evidence of differences between early and delayed treatments for disability-worsening at a maximum of five years' follow-up (3% fewer participants with early treatment (15 fewer to 11.1 more)). There was important variability across interventions; early treatment with interferon beta-1b considerably reduced the odds of participants with disability-worsening during three and five years' follow-up (OR 0.52, 95% CI 0.32 to 0.84 and OR 0.57, 95% CI 0.36 to 0.89). The early treatment group had 19.6% fewer participants with relapses (26.7 fewer to 12.7 fewer) compared to late treatment at a maximum of five years' follow-up and early treatment decreased the hazard of conversion to CDMS at any follow-up up to 10 years (i.e. over five years' follow-up HR 0.62, 95% CI 0.53 to 0.73). We did not draw any conclusions on long-term serious AEs or discontinuation due to AEs because of inadequacies in the available data both in the included OLEs and cohort studies. Authors' conclusions: Very low-quality evidence suggests a small and uncertain benefit with early treatment compared with placebo in reducing disability-worsening and relapses. The advantage of early treatment compared with delayed on disability-worsening was heterogeneous depending on the actual drug used and based on very low-quality evidence. Low-quality evidence suggests that the chances of relapse are less with early treatment compared with delayed. Early treatment reduced the hazard of conversion to CDMS compared either with placebo, no treatment or delayed treatment, both in short- and long-term follow-up. Low-quality evidence suggests that early treatment is associated with fewer participants with at least one serious AE compared with placebo. Very low-quality evidence suggests that, compared with placebo, early treatment leads to more withdrawals or treatment discontinuation due to AEs. Difference between drugs on short-term benefit and safety was uncertain because few studies and only indirect comparisons were available. Long-term safety of early treatment is uncertain because of inadequately reported or unavailable data

Treatment with disease modifying drugs for people with a first clinical attack suggestive of multiple sclerosis

This is the protocol for a review and there is no abstract. The objectives are as follows: To estimate the benefit and safety of all DMDs that have been evaluated in all studies (randomised and non-randomised) for early treatment. We will employ novel, high-quality methods for systematic reviews and network meta-analysis in collaboration with the Cochrane Multiple Interventions Group. To evaluate the quality of the evidence provided by existing studies. We will consider the credibility of included studies and other characteristics of the evidence base as we characterise conclusions pertaining to high, low or very low quality of evidence. We will undertake this review in accordance with the methods described by the template protocol published online and will use this template as we prepare the review

Brief International Cognitive Assessment for MS (BICAMS): International Standards for Validation

An international expert consensus committee recently recommended a brief battery of tests for cognitive evaluation in multiple sclerosis. The Brief International Cognitive Assessment for MS (BICAMS) battery includes tests of mental processing speed and memory. Recognizing that resources for validation will vary internationally, the committee identified validation priorities, to facilitate international acceptance of BICAMS. Practical matters pertaining to implementation across different languages and countries were discussed. Five steps to achieve optimal psychometric validation were proposed. In Step 1, test stimuli should be standardized for the target culture or language under consideration. In Step 2, examiner instructions must be standardized and translated, including all information from manuals necessary for administration and interpretation. In Step 3, samples of at least 65 healthy persons should be studied for normalization, matched to patients on demographics such as age, gender and education. The objective of Step 4 is test-retest reliability, which can be investigated in a small sample of MS and/or healthy volunteers over 1–3 weeks. Finally, in Step 5, criterion validity should be established by comparing MS and healthy controls. At this time, preliminary studies are underway in a number of countries as we move forward with this international assessment tool for cognition in MS

Metabolically exaggerated cardiac reactions to acute psychological stress: The effects of resting blood pressure status and possible underlying mechanisms

The study aimed to: confirm that acute stress elicits metabolically exaggerated increases in cardiac activity; test whether individuals with elevated resting blood pressure show more exaggerated cardiac reactions to stress than those who are clearly normotensive; and explore the underlying mechanisms. Cardiovascular activity and oxygen consumption were measured pre-, during, and post- mental stress, and during graded submaximal cycling exercise in 11 young men with moderately elevated resting blood pressure and 11 normotensives. Stress provoked increases in cardiac output that were much greater than would be expected from contemporary levels of oxygen consumption. Exaggerated cardiac reactions were larger in the relatively elevated blood pressure group. They also had greater reductions in total peripheral resistance, but not heart rate variability, implying that their more exaggerated cardiac reactions reflected greater β-adrenergic activation