Belief, Knowledge and Expertise. The emergence of the lay expert in medical sociology

The paper has three main aims. First, to trace – through the pages of the Journal – the changing ways in which lay understandings of health and illness have been represented during the 1979-2002 period. Second, to say something about the limits of lay knowledge (and particularly lay expertise) in matters of health and medicine. Third, to call for a re-assessment of what lay people can offer to a democratised and customer sensitive system of health care and to attempt to draw a boundary around the domain of expertise. In following through on those aims, the author calls upon data derived from three current projects. These latter concern the diagnosis of Alzheimer’s disease in people with Down’s syndrome; the development of an outcome measure for people who have suffered a traumatic brain injury; and a study of why older people might reject annual influenza vaccinations. Key words: Lay health beliefs, lay expertise, Alzheimer’s, Traumatic Brain Injury, Vaccinations

Robust fuzzy Gustafson-Kessel clustering for nonlinear system identification

This paper deals with Takagi-Sugeno (TS) fuzzy model identification of nonlinear systems using fuzzy clustering. In particular, an extended fuzzy Gustafson-Kessel (EGK) clustering algorithm, using robust competitive agglomeration (RCA), is developed for automatically constructing a TS fuzzy model from system input-output data. The EGK algorithm can automatically determine the 'optimal' number of clusters from the training data set. It is shown that the EGK approach is relatively insensitive to initialization and is less susceptible to local minima, a benefit derived from its agglomerate property. This issue is often overlooked in the current literature on nonlinear identification using conventional fuzzy clustering. Furthermore, the robust statistical concepts underlying the EGK algorithm help to alleviate the difficulty of cluster identification in the construction of a TS fuzzy model from noisy training data. A new hybrid identification strategy is then formulated, which combines the EGK algorithm with a locally weighted, least-squares method for the estimation of local sub-model parameters. The efficacy of this new approach is demonstrated through function approximation examples and also by application to the identification of an automatic voltage regulation (AVR) loop for a simulated 3 kVA laboratory micro-machine system.

Introduction to Domain-Driven Data Mining Special Section

In the last decade, data mining has emerged as one of the most dynamic and lively areas in information technology. Although many algorithms and techniques for data mining have been proposed, they either focus on domain independent techniques or on very specific domain problems. A general requirement in bridging the gap between academia and business is to cater to general domain-related issues surrounding real-life applications, such as constraints, organizational factors, domain expert knowledge, domain adaption, and operational knowledge. Unfortunately, these either have not been addressed, or have not been sufficiently addressed, in current data mining research and development.Domain-Driven Data Mining (D3M) aims to develop general principles, methodologies, and techniques for modeling and merging comprehensive domain-related factors and synthesized ubiquitous intelligence surrounding problem domains with the data mining process, and discovering knowledge to support business decision-making. This paper aims to report original, cutting-edge, and state-of-the-art progress in D3M. It covers theoretical and applied contributions aiming to: 1) propose next-generation data mining frameworks and processes for actionable knowledge discovery, 2) investigate effective (automated, human and machine-centered and/or human-machined-co-operated) principles and approaches for acquiring, representing, modelling, and engaging ubiquitous intelligence in real-world data mining, and 3) develop workable and operational systems balancing technical significance and applications concerns, and converting and delivering actionable knowledge into operational applications rules to seamlessly engage application processes and systems.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.

EXPERT-SYSTEM SUPPORT USING BAYESIAN BELIEF NETWORKS IN THE DIAGNOSIS OF FINE-NEEDLE ASPIRATION BIOPSY SPECIMENS OF THE BREAST

Aim-To develop an expert system model for the diagnosis of fine needle aspiration cytology (FNAC) of the breast.

Methods-Knowledge and uncertainty were represented in the form of a Bayesian belief network which permitted the combination of diagnostic evidence in a cumulative manner and provided a final probability for the possible diagnostic outcomes. The network comprised 10 cytological features (evidence nodes), each independently linked to the diagnosis (decision node) by a conditional probability matrix. The system was designed to be interactive in that the cytopathologist entered evidence into the network in the form of likelihood ratios for the outcomes at each evidence node.

Results-The efficiency of the network was tested on a series of 40 breast FNAC specimens. The highest diagnostic probability provided by the network agreed with the cytopathologists' diagnosis in 100% of cases for the assessment of discrete, benign, and malignant aspirates. A typical probably benign cases were given probabilities in favour of a benign diagnosis. Suspicious cases tended to have similar probabilities for both diagnostic outcomes and so, correctly, could not be assigned as benign or malignant. A closer examination of cumulative belief graphs for the diagnostic sequence of each case provided insight into the diagnostic process, and quantitative data which improved the identification of suspicious cases.

Conclusion-The further development of such a system will have three important roles in breast cytodiagnosis: (1) to aid the cytologist in making a more consistent and objective diagnosis; (2) to provide a teaching tool on breast cytological diagnosis for the non-expert; and (3) it is the first stage in the development of a system capable of automated diagnosis through the use of expert system machine vision.

Tools for Assessing Outcomes in Studies of Chronic Cough: CHEST Guideline and Expert Panel Report

BACKGROUND: Since the publication of the 2006 American College of Chest Physicians (CHEST) cough guidelines, a variety of tools has been developed or further refined for assessing cough. The purpose of the present committee was to evaluate instruments used by investigators performing clinical research on chronic cough. The specific aims were to (1) assess the performance of tools designed to measure cough frequency, severity, and impact in adults, adolescents, and children with chronic cough and (2) make recommendations or suggestions related to these findings.

METHODS: By following the CHEST methodologic guidelines, the CHEST Expert Cough Panel based its recommendations and suggestions on a recently published comparative effectiveness review commissioned by the US Agency for Healthcare Research and Quality, a corresponding summary published in CHEST, and an updated systematic review through November 2013. Recommendations or suggestions based on these data were discussed, graded, and voted on during a meeting of the Expert Cough Panel.

RESULTS: We recommend for adults, adolescents (≥ 14 years of age), and children complaining of chronic cough that validated and reliable health-related quality-of-life (QoL) questionnaires be used as the measurement of choice to assess the impact of cough, such as the Leicester Cough Questionnaire and the Cough-Specific Quality-of-Life Questionnaire in adult and adolescent patients and the Parent Cough-Specific Quality of Life Questionnaire in children. We recommend acoustic cough counting to assess cough frequency but not cough severity. Limited data exist regarding the performance of visual analog scales, numeric rating scales, and tussigenic challenges.

CONCLUSIONS: Validated and reliable cough-specific health-related QoL questionnaires are recommended as the measurement of choice to assess the impact of cough on patients. How they compare is yet to be determined. When used, the reporting of cough severity by visual analog or numeric rating scales should be standardized. Previously validated QoL questionnaires or other cough assessments should not be modified unless the new version has been shown to be reliable and valid. Finally, in research settings, tussigenic challenges play a role in understanding mechanisms of cough.

Methodologies for the Development of the Management of Cough: CHEST Guideline and Expert Panel Report

BACKGROUND: This series of guidance documents on cough, which will be published over time, is a hybrid of two processes: (1) evidence-based guidelines and (2) trustworthy consensus statements based on a robust and transparent process.

METHODS: The CHEST Guidelines Oversight Committee selected a nonconflicted Panel Chair and jointly assembled an international panel of experts in each clinical area with few, if any, conflicts of interest. PICO (population, intervention, comparator, outcome)-based key questions and parameters of eligibility were developed for each clinical topic to inform the comprehensive literature search. Existing guidelines, systematic reviews, and primary studies were assessed for relevance and quality. Data elements were extracted into evidence tables and synthesized to provide summary statistics. These, in turn, are presented to support the evidence-based graded recommendations. A highly structured consensus-based Delphi approach was used to provide expert advice on all guidance statements. Transparency of process was documented.

RESULTS: Evidence-based guideline recommendations and consensus-based suggestions were carefully crafted to provide direction to health-care providers and investigators who treat and/or study patients with cough. Manuscripts and tables summarize the evidence in each clinical area supporting the recommendations and suggestions.

CONCLUSIONS: The resulting guidance statements are based on a rigorous methodology and transparency of process. Unless otherwise stated, the recommendations and suggestions meet the guidelines for trustworthiness developed by the Institute of Medicine and can be applied with confidence by physicians, nurses, other health-care providers, investigators, and patients.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

Somatic Cough Syndrome (Previously Referred to as Psychogenic Cough) and Tic Cough (Previously Referred to as Habit Cough) in Adults and Children: CHEST Guideline and Expert Panel Report

BACKGROUND: We conducted a systematic review on the management of psychogenic cough, habit cough, and tic cough to update the recommendations and suggestions of the 2006 guideline on this topic.

METHODS: We followed the American College of Chest Physicians (CHEST) methodologic guidelines and the Grading of Recommendations, Assessment, Development, and Evaluation framework. The Expert Cough Panel based their recommendations on data from the systematic review, patients' values and preferences, and the clinical context. Final grading was reached by consensus according to Delphi methodology.

RESULTS: The results of the systematic review revealed only low-quality evidence to support how to define or diagnose psychogenic or habit cough with no validated diagnostic criteria. With respect to treatment, low-quality evidence allowed the committee to only suggest therapy for children believed to have psychogenic cough. Such therapy might consist of nonpharmacologic trials of hypnosis or suggestion therapy, or combinations of reassurance, counseling, and referral to a psychologist, psychotherapy, and appropriate psychotropic medications. Based on multiple resources and contemporary psychologic, psychiatric, and neurologic criteria (Diagnostic and Statistical Manual of Mental Disorders, 5th edition and tic disorder guidelines), the committee suggests that the terms psychogenic and habit cough are out of date and inaccurate.

CONCLUSIONS: Compared with the 2006 CHEST Cough Guidelines, the major change in suggestions is that the terms psychogenic and habit cough be abandoned in favor of somatic cough syndrome and tic cough, respectively, even though the evidence to do so at this time is of low quality.

Defining the content and delivery of an intervention to Change AdhereNce to treatment in BonchiEctasis (CAN-BE): a qualitative approach incorporating the Theoretical Domains Framework, behavioural change techniques and stakeholder expert panels

Background
Low patient adherence to treatment is associated with poorer health outcomes in bronchiectasis. We sought to use the Theoretical Domains Framework (TDF) (a framework derived from 33 psychological theories) and behavioural change techniques (BCTs) to define the content of an intervention to change patients’ adherence in bronchiectasis (Stage 1 and 2) and stakeholder expert panels to define its delivery (Stage 3).

Methods
We conducted semi-structured interviews with patients with bronchiectasis about barriers and motivators to adherence to treatment and focus groups or interviews with bronchiectasis healthcare professionals (HCPs) about their ability to change patients’ adherence to treatment. We coded these data to the 12 domain TDF to identify relevant domains for patients and HCPs (Stage 1). Three researchers independently mapped relevant domains for patients and HCPs to a list of 35 BCTs to identify two lists (patient and HCP) of potential BCTs for inclusion (Stage 2). We presented these lists to three expert panels (two with patients and one with HCPs/academics from across the UK). We asked panels who the intervention should target, who should deliver it, at what intensity, in what format and setting, and using which outcome measures (Stage 3).

Results
Eight TDF domains were perceived to influence patients’ and HCPs’ behaviours: Knowledge, Skills, Beliefs about capability, Beliefs about consequences, Motivation, Social influences, Behavioural regulation and Nature of behaviours (Stage 1). Twelve BCTs common to patients and HCPs were included in the intervention: Monitoring, Self-monitoring, Feedback, Action planning, Problem solving, Persuasive communication, Goal/target specified:behaviour/outcome, Information regarding behaviour/outcome, Role play, Social support and Cognitive restructuring (Stage 2). Participants thought that an individualised combination of these BCTs should be delivered to all patients, by a member of staff, over several one-to-one and/or group visits in secondary care. Efficacy should be measured using pulmonary exacerbations, hospital admissions and quality of life (Stage 3).

Conclusions
Twelve BCTs form the intervention content. An individualised selection from these 12 BCTs will be delivered to all patients over several face-to-face visits in secondary care. Future research should focus on developing physical materials to aid delivery of the intervention prior to feasibility and pilot testing. If effective, this intervention may improve adherence and health outcomes for those with bronchiectasis in the future.

Treatment of Unexplained Chronic Cough: CHEST Guideline and Expert Panel Report

Background: Unexplained chronic cough (UCC) causes significant quality of life impairment. There is a need to identify effective assessment and treatment approaches for UCC.

Methods: This systematic review of randomized controlled clinical trials asked: What is the efficacy of treatment compared to usual care on cough severity, cough frequency, and cough-related quality of life in patients with unexplained chronic cough (UCC)? Studies of adults and adolescents >12 years with a chronic cough of >8 weeks duration that was unexplained after systematic investigation and treatment were included and assessed for relevance and quality. Based upon the systematic review, guideline suggestions were developed and voted upon using CHEST organization methodology.

Results: 11 RCTs and 5 systematic reviews were included. The 11 RCTs reported data on 570 participants with chronic cough who received a variety of interventions. Study quality was high in 10 RCTs. The studies used a variety of descriptors and assessments to identify unexplained chronic cough. While gabapentin and morphine showed positive effects on cough-related quality of life, only gabapentin was supported as a treatment recommendation. Studies of inhaled corticosteroids (ICS) suffered from intervention fidelity bias, and when this was addressed, ICS were not found to be effective for UCC. Esomeprazole was not effective for UCC without features of gastroesophageal acid reflux. Studies addressing non-acid gastroesophageal reflux were not identified. A multimodality speech pathology intervention improved cough severity.

Conclusions: The evidence supporting the diagnosis and management of UCC is limited. UCC requires further study to establish agreed terminology and the optimal methods of investigation using established criteria for intervention fidelity. Speech pathology based cough suppression is suggested as a treatment option for UCC. This guideline presents suggestions for diagnosis and treatment based on the best available evidence and identifies gaps in our knowledge and areas for future research.

Assessment of Intervention Fidelity and Recommendations for Researchers Conducting Studies on the Diagnosis and Treatment of Chronic Cough in the Adult: CHEST Guideline and Expert Panel Report

BACKGROUND: Successful management of chronic cough has varied in the primary research studies in the reported literature. One of the potential reasons relates to a lack of intervention fidelity to the core elements of the diagnostic and/or therapeutic interventions that were meant to be used by the investigators.

METHODS: We conducted a systematic review to summarize the evidence supporting intervention fidelity as an important methodologic consideration in assessing the effectiveness of clinical practice guidelines used for the diagnosis and management of chronic cough. We developed and used a tool to assess for five areas of intervention fidelity. Medline (PubMed), Scopus, and the Cochrane Database of Systematic Reviews were searched from January 1998 to May 2014. Guideline recommendations and suggestions for those conducting research using guidelines or protocols to diagnose and manage chronic cough in the adult were developed and voted upon using CHEST Organization methodology.

RESULTS: A total of 23 studies (17 uncontrolled prospective observational, two randomized controlled, and four retrospective observational) met our inclusion criteria. These articles included 3,636 patients. Data could not be pooled for meta-analysis because of heterogeneity. Findings related to the five areas of intervention fidelity included three areas primarily related to the provider and two primarily related to the patients. In the area of study design, 11 of 23 studies appeared to be underpinned by a single guideline/protocol; for training of providers, two of 23 studies reported training, and zero of 23 reported the use of an intervention manual; and for the area of delivery of treatment, when assessing the treatment of gastroesophageal reflux disease, three of 23 studies appeared consistent with the most recent guideline/protocol referenced by the authors. For receipt of treatment, zero of 23 studies mentioned measuring concordance of patient-interventionist understanding of the treatment recommended, and zero of 23 mentioned measuring enactment of treatment, with three of 23 measuring side effects and two of 23 measuring adherence. The overall average intervention fidelity score for all 23 studies was poor (20.74 out of 48).

CONCLUSIONS: Only low-quality evidence supports that intervention fidelity strategies were used when conducting primary research in diagnosing and managing chronic cough in adults. This supports the contention that some of the variability in the reporting of patients with unexplained or unresolved chronic cough may be due to lack of intervention fidelity. By following the recommendations and suggestions in this article, researchers will likely be better able to incorporate strategies to address intervention fidelity, thereby strengthening the validity and generalizability of their results that provide the basis for the development of trustworthy guidelines.

HER2 in high-risk rectal cancer patients treated in EXPERT-C, a randomized phase II trial of neoadjuvant capecitabine and oxaliplatin (CAPOX) and chemoradiotherapy (CRT) with or without cetuximab.

BACKGROUND: HER2 is an established therapeutic target in breast and gastric cancers. The role of HER2 in rectal cancer is unclear, as conflicting data on the prevalence of HER2 expression in this disease have been reported. We evaluated the prevalence of HER2 and its impact on the outcome of high-risk rectal cancer patients treated with neoadjuvant CAPOX and CRT±cetuximab in the EXPERT-C trial. PATIENTS AND METHODS: Eligible patients with available tumour tissue for HER2 analysis were included. HER2 expression was determined by immunohistochemistry (IHC) in pre-treatment biopsies and/or surgical specimens (score 0-3+). Immunostaining was scored according to the consensus panel recommendations on HER2 scoring for gastric cancer. Tumours with equivocal IHC result (2+) were tested for HER2 amplification by D-ISH. Tumours with IHC 3+ or D-ISH ratio ≥2.0 were classified as HER2+. The impact of HER2 on primary and secondary end points of the study was analysed. RESULTS: Of 164 eligible study patients, 104 (63%) biopsy and 114 (69%) surgical specimens were available for analysis. Only 3 of 104 (2.9%) and 3 of 114 (2.6%) were HER2+, respectively. In 77 patients with paired specimens, concordance for HER2 status was found in 74 (96%). Overall, 141 patients were assessable for HER2 and 6 out of 141 (4.3%) had HER2 overexpression and/or amplification. The median follow-up was 58.6 months. HER2 was not associated with a difference in the outcome for any of the study end points, including in the subset of 90 KRAS/BRAF wild-type patients treated±cetuximab. CONCLUSIONS: Based on the low prevalence of expression as recorded in the EXPERT-C trial, HER2 does not appear to represent a useful therapeutic target in high-risk rectal cancer. However, the role of HER2 as a potential predictive biomarker of resistance to anti-EGFR-based treatments and a therapeutic target in anti-EGFR refractory metastatic colorectal cancer (CRC) warrants further investigation. TRIAL REGISTRATION: ISRCTN Register: 99828560.