Standard Decision Research Articles

Performing corneal crosslinking under local anaesthesia in patients with Down syndrome

PurposeTo report on the ability to perform corneal crosslinking (CXL) under local anaesthesia for the treatment of keratoconus in patients with Down syndrome.MethodsNine eyes of seven patients with both keratoconus and Down syndrome were scheduled for an epithelium-off CXL procedure under local anaesthesia. Exclusion criteria were a corneal thickness under 400 µm and the presence of corneal scars. A standardized clinical decision tool was used to estimate patient cooperation and the likelihood for a successful procedure under local rather than general anaesthesia.ResultsIn seven eyes, the CXL was completed successfully. The treatment was aborted in two eyes due to insufficient corneal thickness (<400 µm) prior to ultraviolet-A irradiation, even after employing hypoosmolar riboflavin. No adverse events occurred post-operatively, except for one case of delayed epithelial healing (23 days).ConclusionsWith a proper patient selection, CXL under local anaesthesia can be achieved in patients with Down syndrome.

The Cut-Score Operating Function: A New Tool to Aid in Standard Setting

In this essay, we describe the construction and use of the Cut-Score Operating Function in aiding standard setting decisions. The Cut-Score Operating Function shows the relation between the cut-score chosen and the consequent error rate. It allows error rates to be defined by multiple loss functions and will show the behavior of each loss function. One strength of the Cut-Score Operating Function is that it shows how robust error rates are to the choice of cut-score and identifies the regions of extreme sensitivity relative to that choice.

Emergency Department Triage of Traumatic Head Injury Using a Brain Electrical Activity Biomarker: A Multisite Prospective Observational Validation Trial.

A brain electrical activity biomarker for identifying traumatic brain injury (TBI) in emergency department (ED) patients presenting with high Glasgow Coma Scale (GCS) after sustaining a head injury has shown promise for objective, rapid triage. The main objective of this study was to prospectively evaluate the efficacy of an automated classification algorithm to determine the likelihood of being computed tomography (CT) positive, in high-functioning TBI patients in the acute state. Adult patients admitted to the ED for evaluation within 72 hours of sustaining a closed head injury with GCS 12 to 15 were candidates for study. A total of 720 patients (18-85 years) meeting inclusion/exclusion criteria were enrolled in this observational, prospective validation trial, at 11 U.S. EDs. GCS was 15 in 97%, with the first and third quartiles being 15 (interquartile range=0) in the study population at the time of the evaluation. Standard clinical evaluations were conducted and 5 to 10 minutes of electroencephalogram (EEG) was acquired from frontal and frontal-temporal scalp locations. Using an a priori derived EEG-based classification algorithm developed on an independent population and applied to this validation population prospectively, the likelihood of each subject being CT+ was determined, and performance metrics were computed relative to adjudicated CT findings. Sensitivity of the binary classifier (likely CT+ or CT-) was 92.3% (95% confidence interval[CI] = 87.8%-95.5%) for detection of any intracranial injury visible on CT (CT+), with specificity of 51.6% (95% CI= 48.1%-55.1%) and negative predictive value (NPV) of 96.0% (95% CI= 93.2%-97.9%). Using ternary classification (likely CT+, equivocal, likely CT-) demonstrated enhanced sensitivity to traumatic hematomas (≥1mL of blood), 98.6% (95% CI= 92.6%-100.0%), and NPV of 98.2% (95% CI= 95.5%-99.5%). Using an EEG-based biomarker high accuracy of predicting the likelihood of being CT+ was obtained, with high NPV and sensitivity to any traumatic bleeding and to hematomas. Specificity was significantly higher than standard CT decision rules. The short time to acquire results and the ease of use in the ED environment suggests that EEG-based classifier algorithms have potential to impact triage and clinical management of head-injured patients.

Consistent climate policies

What are the optimal climate policies when time preferences deviate from the standard exponential discounting and decision makers cannot commit to future policies? We show that, with time-declining discounting, the delay and persistence of climate impacts provide a commitment device to policy makers. We quantify the commitment value in a climate-economy model by solving time-consistent Markov equilibrium capital and emission taxes explicitly. The returns on capital and climate investments are no longer equal, leading to a large increase in the emission tax, compared to a benchmark with equalized returns. The commitment value increases the tax by a factor of 20 in our quantitative assessment.

Comparison of the Effects of a Pharmaceutical Industry Decision Guide and Decision Aids on Patient Choice to Intensify Therapy in Rheumatoid Arthritis.

Objective. To compare the effects a pharmaceutical industry decision guide and International Patient Decision Aids Standard (IPDAS) compliant patient decision aids (PtDA) on patient medication beliefs and choice to intensify therapy. Methods. Rheumatoid arthritis (RA) patients, who had never taken etanercept (Enbrel), took part in a mail survey. They were presented with a hypothetical decision scenario where they were asked to consider adding etanercept to their current regimen. Each patient was randomized to review 1 of 3 forms of an etanercept-specific decision support: a long PtDA (LONG DA), a short PtDA (SHORT DA), or the manufacturer’s Enbrel decision guide (Pharm Booklet). Results. We had 402 RA patients participate in the study (response rate, 52%). Of the patients randomized to the Pharm Booklet, 30.6% elected to initiate etanercept. Only 14.6% and 14.0% of patients who reviewed the LONG DA or SHORT DA choose to take etanercept (χ2 = 15.7; P < 0.001). Patients who reviewed the LONG DA or SHORT DA had a greater increase in knowledge about etanercept than those who reviewed the Pharm Booklet. There was no difference in decisional conflict among the groups. A logistic regression model explained 44.2% (R2 = 0.442) of patient choice to intensify therapy by initiating etanercept. The strongest predictor of choice to intensify therapy were beliefs about etanercept’s ability to improve symptoms (OR = 2.56, 96%CI [1.71, 3.80]), and its use by others like the respondent (OR = 2.24, 95%CI [1.49, 3.35]). Mediation analysis confirmed the presence of a partial mediating effect of decision support on patients’ intent to take etanercept (OR = 0.59, 95%CI [0.39, 0.89]). Conclusions. Patients supported by the Pharm Booklet were twice as likely to choose to intensify therapy. The Pharm Booklet’s effects are partially mediated through persuasive communication techniques that influence patients’ beliefs that symptoms will improve, and increase social normative beliefs, rather than by increasing the relevant knowledge, clarifying patient values about positive or negative treatment outcomes, or increasing their self-efficacy.

Abstract P5-03-07: The measurement of gait speed: An easy way to select older patients with breast cancer for an adapted therapeutic decision making

Abstract Background: Despite recommendations about the adaptation of therapeutic decision making by the International Society of Geriatric Oncology, there is no guidelines concerning breast cancer in older patients for whom a therapeutic decision making should be adapted. Currently, the G8 index ≤ 14/17 is recommended for patients aged 70 and over before a therapeutic decision making to select patients with a potential frailty. Moreover, gait speed (GS) at the threshold of 1 m/s has been reported in a recent review to identify complications associated with frailty in older outpatients. Indeed, these patients could experience poor outcomes with cancer treatments. For these patients, it is expected that they could not have a standardized decision. We aimed to assess the geriatric profil of older patients with breast cancer for whom a therapeutic decision making was adapted. Methods: 64 outpatients with breast cancer aged 65 and over were prospectively and consecutively included between November 2013 and April 2016, in two teaching hospitals in a Paris suburb (France). All patients had a G8 index, measurement of gait speed over a short distance (4m) and a multidimensional geriatric assessment before therapeutic decision making. An adapted therapeutic decision making was defined if it not followed treatment recommendations based on tumor characteristics (pTNM, grade, status of hormonal receptors, HER2 status, Ki67 index). A univariate and multivariate analysis by using a logistic regression with a stepwise procedure were performed in all patients with an adapted therapeutic decision. Two models were created to assess the value of G8 index and GS. All variables with P &amp;lt; 0.20 were included in both multivariate models. All tests were two sided significant at 0.05. Informed consent was obtained from studied patients prior inclusion. This study was approved by a local committee ethic. Results: 67% (n=43) of patients had an adapted treatment with a mean age of 82.6 +/- 5.7 years (67-95). Of these patients, 33 had an invasive ductal carcinoma, 23 lymph nod extension, 11 metastatic disease. The mean tumor size was 30.4 +/- 15.4mm. 37 patients had a SBR ≥ 2, 39 positive hormonal receptors, 5 positive HER2 status. The mean KI67 index was 24.2 +/- 20%. 37 received hormonotherapy, 18 surgery, 16 radiotherapy, 5 chemotherapy. Most of these patients (53.5%) had ECOG-PS ≤ 1, 39 G8 index ≤ 14 and 36 GS &amp;lt; 1 m/s. In the first model, GS &amp;lt; 1 m/s was the only variable significantly and independently associated with adapted treatment (aOR=5.65, 95%CI: 1.78-19.31, P=0.003). In the second model, at least one severe comorbidity (CIRSG grade III, aOR=4.52, 95%CI: 1.30-17.84, P=0.02) and cognitive impairment (MMSE&amp;lt;24/30, aOR=4.60, 95%CI: 1.32-17.97, P=0.01) were the only variables significantly and independently associated with adapted treatment. In the two models, G8 index was not significantly associated with adapted treatment. Conclusion: A slow gait speed &amp;lt; 1 m/s could be used as a screening test to select older patients with breast cancer for an adapted therapeutic decision making. Citation Format: Pamoukdjian F, Bricou A, Boudabous H, Sebbane G, Zelek L. The measurement of gait speed: An easy way to select older patients with breast cancer for an adapted therapeutic decision making [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-03-07.

The 'Huawei v. ZTE' Judgement and Follow-On Application of Article 102 TFEU in the Light of this Judgement by German Courts

This paper discusses a judgement of the Court of Justice in re Huawei v. ZTE rendered on 16 July 2015 providing binding interpretation of Article 102 TFEU. This judgement concerns an abuse of dominant position by bringing an action for injunctive relief and/or the recall of goods from distribution by an owner of a standard essential patent who made prior FRAND commitment. Many controversies in the ICT industry as well as in Academia appeared on how to approach the interpretation of this groundbreaking judgement. The author suggests interpretation capturing a broad spectre of anti-competitive effects and thus make the best use of this judgement in the interest of prevention of stakeholders' opportunistic behaviour. A key part of this paper is formed by an analysis of German follow-on case-law applying Article 102 TFEU in the light of the Huawei v. ZTE judgement. The author concludes, inter alia, that German courts´ assessment of an abuse of dominant position is strongly focused on application of the so-called Huawei steps. For the future, the author advices to base the decisions more on persuasive theory of harm and support them by evidence of (potential) anti-competitive effects. As for the practical implications of the German follow-on case-law, one may observe a shift from the previous case-law based on the Orange Book Standard decision in some aspects. Since Germany is an important patent litigation destination, stakeholders from the ICT industry will attentively follow the development of FRAND-related case-law originating from German courts and possibly adapt their behaviour accordingly.

The Benefit in Free Information Disclosure When Selling Information to People

This paper studies the benefit for information providers in free public information disclosure in settings where the prospective information buyers are people. The underlying model, which applies to numerous real-life situations, considers a standard decision making setting where the decision maker is uncertain about the outcomes of her decision. The information provider can fully disambiguate this uncertainty and wish to maximize her profit from selling such information. We use a series of AMT-based experiments with people to test the benefit for the information provider from reducing some of the uncertainty associated with the decision maker's problem, for free. Free information disclosure of this kind can be proved to be ineffective when the buyer is a fully-rational agent. Yet, when it comes to people we manage to demonstrate that a substantial improvement in the information provider's profit can be achieved with such an approach. The analysis of the results reveals that the primary reason for this phenomena is people's failure to consider the strategic nature of the interaction with the information provider. Peoples' inability to properly calculate the value of information is found to be secondary in its influence.

Decision rule approximations for the risk averse reservoir management problem

This paper presents a new formulation for the risk averse stochastic reservoir management problem. Using recent advances in robust optimization and stochastic programming, we propose a multi-stage model based on minimization of a risk measure associated with floods and droughts for a hydro-electrical complex. We present our model and then identify approximate solutions using standard affine decision rules commonly found in the literature as well as lifted decision rules. Finally, we conduct thorough numerical experiments based on a real river system in Western Québec and conclude on the relative performance of families of decision rules.

Patient-Derived Xenograft Models of Non-Small Cell Lung Cancer and Their Potential Utility in Personalized Medicine.

Traditional preclinical studies of cancer therapeutics have relied on the use of established human cell lines that have been adapted to grow in the laboratory and, therefore, may deviate from the cancer they were meant to represent. With the emphasis of cancer drug development shifting from non-specific cytotoxic agents to rationally designed molecularly targeted therapies or immunotherapy comes the need for better models with predictive value regarding therapeutic activity and response in clinical trials. Recently, the diversity and accessibility of immunodeficient mouse strains has greatly enhanced the production and utility of patient-derived xenograft (PDX) models for many tumor types, including non-small cell lung cancer (NSCLC). Combined with next-generation sequencing, NSCLC PDX mouse models offer an exciting tool for drug development and for studying targeted therapies while utilizing patient samples with the hope of eventually aiding in clinical decision-making. Here, we describe NSCLC PDX mouse models generated by us and others, their ability to reflect the parental tumors’ histomorphological characteristics, as well as the effect of clonal selection and evolution on maintaining genomic integrity in low-passage PDXs compared to the donor tissue. We also raise vital questions regarding the practical utility of PDX and humanized PDX models in predicting patient response to therapy and make recommendations for addressing those questions. Once collaborations and standardized xenotransplantation and data management methods are established, NSCLC PDX mouse models have the potential to be universal and invaluable as a preclinical tool that guides clinical trials and standard therapeutic decisions.

Defending Against Advanced Persistent Threats Using Game-Theory.

Advanced persistent threats (APT) combine a variety of different attack forms ranging from social engineering to technical exploits. The diversity and usual stealthiness of APT turns them into a central problem of contemporary practical system security, since information on attacks, the current system status or the attacker’s incentives is often vague, uncertain and in many cases even unavailable. Game theory is a natural approach to model the conflict between the attacker and the defender, and this work investigates a generalized class of matrix games as a risk mitigation tool for an advanced persistent threat (APT) defense. Unlike standard game and decision theory, our model is tailored to capture and handle the full uncertainty that is immanent to APTs, such as disagreement among qualitative expert risk assessments, unknown adversarial incentives and uncertainty about the current system state (in terms of how deeply the attacker may have penetrated into the system’s protective shells already). Practically, game-theoretic APT models can be derived straightforwardly from topological vulnerability analysis, together with risk assessments as they are done in common risk management standards like the ISO 31000 family. Theoretically, these models come with different properties than classical game theoretic models, whose technical solution presented in this work may be of independent interest.

Viewers’ understanding of The Marketing Communication through Media Advertisements of FMCG brands and its Impact on buying behaviour

Media advertisements are the major source of disseminating information regarding quality, product features, etc. to the consumers and thus posses a high level of brand awareness followed by a standardized decision making capacity. With the basis on a suitable impact index, this study aims to observe the communication content that the advertisers wish to project through the advertisements and the level of understanding of the viewers of a small district in India towards the communication content shown in media advertisements of Fast Moving Consumer Goods (FMCG) brands. First objective reveals that the advertising agencies maintain enough space while designing an advertisement in order to communicate the message to the viewers. An equal balance of the criteria’s like; advertising appeals, communication content and frequency results in a more attractive, entertaining and informative advertisement creating an optimistic attitude among the viewers’ towards the advertised brand. The second objective shows that, there exists a fair impact of marketing communication through media advertisements on the viewers. The results of third objective reveals that, there doesn’t exists a significant difference in the contribution of the communication content through media advertisements of the selected FMCG brands on the buying behaviour of the urban-rural matrix.

Adapted pruning scheme for the framework of imbalanced data-sets

Learning from imbalanced data is attracting an increasing interest by the machine learning community. This is mainly due to the high number of real applications that are affected by this situation. The adaptation of the standard decision trees to deal with imbalanced data represents one of the important number of approaches that have been developed to address this problem. This adaptation has been proposed under three different perspectives: splitting criterion, assignment rule and pruning. In this paper, we focus our attention to the pruning of decision trees. We propose an adaptation of the standard pruning algorithm MCCP to address the skewed-data problem. Our contribution affects two levels: adaption of the metric used in selecting nodes to be firstly pruned and change of the evaluation measure used in selecting the best decision-tree through the pruning set. Our goal is to show that, contrary to the popular belief in the literature enquiring into the uselessness of decision tree pruning, an adaptive pruning technique for imbalanced situations is more efficient and more accurate towards the minority class. A total of twelve binary class data-sets having different imbalance ratio are used to test the performance of the proposed method. Experimental results show that the proposed post-pruning approach can increase the performance of imbalanced decision trees in terms of evaluation measures that are recent and appropriate for the context of imbalanced classification.

‘Prescribing’ coercive healthcare: documentary accounts of coercive healthcare decisions regarding persons with intellectual disabilities

There is limited knowledge of how health professionals document decisions to provide coercive medical and dental healthcare for persons with intellectual disabilities. Drawing on sociological perspectives, we analysed 28 Norwegian decision documents to explore how professionals account for coercive healthcare decisions. The professionals presented clear-cut medicalized and morally neutral ‘coercive healthcare cases’ in favour of coercion. They typically emphasized the medical necessity of healthcare provision to prevent damage to the patient’s health. However, professional and ethical judgments of the necessity of coercion in individual cases were largely obscured. Professionals’ case presentation was facilitated by a standardized decision form. We suggest that professionals’ documentary accounts constitute a routinized ‘prescriptive’ practice that expresses the ‘voice of medicine’. We question whether the current practice promotes the rule of law or in the worst case may serve to legitimize unlawful use of coercion in healthcare.

Validation of a method for sedatives and β-blockers determination in swine, bovine and equine kidney using liquid chromatography coupled with tandem mass spectrometry

ABSTRACTA method for the determination of five sedatives and 14 β-blocker residues in swine, bovine and equine kidney was validated. Samples were extracted with acetonitrile and purified using dispersive solid phase extraction (d-SPE) with Celite 545 with subsequent analysis by LC-MS/MS. A simplified protocol was applied to validate the method scope extension to include new matrices. Parameters such as recovery, trueness, linearity (r2), relative standard deviation (RSD), decision limit (CCα) and method capability (CCβ) were measured for the bovine and equine kidney matrices. The method was applied to the analysis of more than 300 real samples and is currently included in the Brazilian National Residue Control Plan.

The Effect of Sustainability Standard Uncertainty on Certification Decisions of Firms in Emerging Economies

Voluntary sustainability standards that establish global rules for firms’ environmental and/or social conduct and allow for verification of firm compliance via third-party certification hold the promise to govern firms’ sustainability conduct in a globalizing world economy. However, the recent proliferation of competing and overlapping global sustainability standards that have been developed by various stakeholders with different agendas, creates uncertainties for firms that likely reduce their propensity to adopt any standard. Without widespread adoption these standards cannot effectively govern firm conduct and in contrast create barriers for firms’ access to export markets. We suggest that the uncertainties associated with competing standards and the effect of these uncertainties on standard certification decisions are especially large for firms in emerging economies because these firms lack access to information about current and future standards and the resources to obtain certifications to multiple standards. We theoretically propose and empirically identify three distinct sources of sustainability standard uncertainty: (i) diversity of customer requirements, (ii) dynamism of customer requirements, and (iii) the unpredictability of the future evolution of standard and propose that each of these sources reduces firms’ propensity to obtain certification to any standard. Our empirical results based on certifications to food safety standards by a sample of 97 Mexican food exporting firms confirm that three distinct sources of sustainability standard uncertainty exist and that all of them negatively impact certification. We discuss ethical implications and offer recommendations for both suppliers as well as standard setting organizations.

A new framework for the documentation and interpretation of oral food challenges in population-based and clinical research.

BackgroundThe conduct of oral food challenges as the preferred diagnostic standard for food allergy (FA) was harmonized over the last years. However, documentation and interpretation of challenge results, particularly in research settings, are not sufficiently standardized to allow valid comparisons between studies. Our aim was to develop a diagnostic toolbox to capture and report clinical observations in double‐blind placebo‐controlled food challenges (DBPCFC).MethodsA group of experienced allergists, paediatricians, dieticians, epidemiologists and data managers developed generic case report forms and standard operating procedures for DBPCFCs and piloted them in three clinical centres. The follow‐up of the EuroPrevall/iFAAM birth cohort and other iFAAM work packages applied these methods.RecommendationsA set of newly developed questionnaire or interview items capture the history of FA. Together with sensitization status, this forms the basis for the decision to perform a DBPCFC, following a standardized decision algorithm. A generic form including details about severity and timing captures signs and symptoms observed during or after the procedures. In contrast to the commonly used dichotomous outcome FA vs no FA, the allergy status is interpreted in multiple categories to reflect the complexity of clinical decision‐making.ConclusionThe proposed toolbox sets a standard for improved documentation and harmonized interpretation of DBPCFCs. By a detailed documentation and common terminology for communicating outcomes, these tools hope to reduce the influence of subjective judgment of supervising physicians. All forms are publicly available for further evolution and free use in clinical and research settings.

Standard Bearers: Qualitative Sociologists’ Experiences with IRB Regulation

In response to the system for regulating research with human subjects, researchers have raised two apparently contradictory concerns: that IRBs are excessively inconsistent (often raised by biomedical researchers), and that they are excessively standardizing (often raised by qualitative interview researchers). Why does standardization appear as the dominant theme in qualitative researchers’ experiences with their IRBs? And how do qualitative researchers experience standardization in their IRB encounters? We focus on IRBs role as regulatory bureaucracies, which typically rely heavily on standardized communication and decisions to process information and make large numbers of decisions in a timely manner. We explore the role of standardization in IRB regulation of qualitative research in an analysis of semi-structured interviews with 26 qualitative sociologists from six research universities and three liberal arts colleges in the Northeastern United States. In a regulatory regime oriented toward the norms of experimental research, these frictions resulted partly from a lack of appropriate standardized language and decision-templates, but also from the inherent difficulties of applying standardized decisions to work that is unpredictable, unique, and difficult to routinize.

Canonical utility functions and continuous preference extensions

I define canonical utility functions via an explicit formula that inherits semicontinuity, continuity, Cauchy continuity, and uniform continuity from preferences. This construction is used to (i)show Rader’s and Debreu’s theorems in a fast and transparent way,(ii)refine these results for Cauchy and uniformly continuous preferences on a metric space X,(iii)extend such preferences from X to any larger metric domain Y⊃X, while preserving Cauchy and uniform continuity respectively. By contrast, regular continuity does not guarantee that continuous preference extensions should exist even in standard decision theoretic frameworks. For example, continuous preferences over simple lotteries or finite menus need not have continuous extensions to Borel distributions or compact menus respectively.

A fast malware feature selection approach using a hybrid of multi‐linear and stepwise binary logistic regression

SummaryMalware replicates itself and produces offspring with the same characteristics but different signatures by using code obfuscation techniques. Current generation anti‐virus engines employ a signature‐template type detection approach where malware can easily evade existing signatures in the database. This reduces the capability of current anti‐virus engines in detecting malware. In this paper, we propose a stepwise binary logistic regression‐based dimensionality reduction techniques for malware detection using application program interface (API) call statistics. Finding the most significant malware feature using traditional wrapper‐based approaches takes an exponential complexity of the dimension (m) of the dataset with a brute‐force search strategies and order of (m‐1) complexity with a backward elimination filter heuristics. The novelty of the proposed approach is that it finds the worst case computational complexity which is less than order of (m‐1). The proposed approach uses multi‐linear regression and the p‐value of each individual API feature for selection of the most uncorrelated and significant features in order to reduce the dimensionality of the large malware data and to ensure the absence of multi‐collinearity. The stepwise logistic regression approach is then employed to test the significance of the individual malware feature based on their corresponding Wald statistic and to construct the binary decision the model. When the selected most significant APIs are used in a decision rule generation systems, this approach not only reduces the tree size but also improves classification performance. Exhaustive experiments on a large malware data set show that the proposed approach clearly exceeds the existing standard decision rule, support vector machine‐based template approach with complete data and provides a better statistical fitness. Copyright © 2016 John Wiley &amp; Sons, Ltd.