SP5.1.12 Discrete Event Micro Simulation Modeling for the Treatment of Resectable Malignancy of the Oesophagus and Gastrooesophageal Junction

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Alison Bradley ◽  
Leo Brown
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Simulation Modeling ◽  
Discrete Event ◽  
Neoadjuvant Chemoradiotherapy ◽  
Treatment Strategies ◽  
Statistical Modelling ◽  
Markov Modelling ◽  
Treatment Pathways ◽  
Sequence Of Events

Abstract Aims To assist decision-making by creation of a statistical model that simulates treatment pathways and subsequent outcomes for the management of resectable malignancy of the oesophagus and gastrooesophageal junction. Methods: Discrete Event Simulation (DES) modelling is a statistical modelling technique that models the operation of a system as a sequence of events in time to support decision-making. This approach lends itself well to disease modelling by incorporating different treatment strategies targeted at different groups. It offers an advantage over previous decision analysis studies that have relied on Markov modelling which can have reduced accuracy due to lack of memory within the Markov model, the effect of depletion of susceptibles, and the timing of transitioning within the model. This simulation model was populated with data from best available evidence from contemporary randomised controlled trials and ran over 100,000 iterations. Results Neoadjuvant chemoradiotherapy was the superior treatment pathway with superior pathway selection frequency of 87.16%. For squamous cell carcinoma neoadjuvant chemoradiotherapy was the superior treatment option with 73.30 months survival time (65.60 QALMs) and had a superior pathway selection frequency of 100%. Conclusions DES simulation modeling for decision analysis in treatment of resectable malignancy of the oesophagus and gastrooesophageal junction supports the use of neoadjuvant chemoradiotherapy.

scholarly journals BJS.03Markov Decision Analysis of Treatment Pathways for Resectable Malignancy of the Oesophagus or Gastrooesophageal Junction

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Alison Bradley ◽  
Leo Brown
Keyword(s):  
Sensitivity Analysis ◽  
Overall Survival ◽  
Monte Carlo ◽  
Decision Analysis ◽  
Randomised Controlled Trials ◽  
Gastroesophageal Junction ◽  
Neoadjuvant Chemoradiotherapy ◽  
Controlled Trials ◽  
Treatment Pathways ◽  
Randomised Controlled

Abstract Aims To perform decision-analysis of treatment options for resectable malignancy of the oesophagus or gastroesophageal junction including: surgery alone, neoadjuvant chemoradiotherapy, neoadjuvant chemotherapy and surgery followed by adjuvant therapy based on current highest-level evidence. Methods A Markov decision analysis model in an advanced decision-tree format was constructedand populated with data from existing randomised controlled trials. Markov model transition probabilities were based on weighted pooled estimates of proportions from included studies, calculated using Freeman-Tukey arcsine square root transformation under random effects model to account for heterogeneity.Each Markov cycle equated with one month and Markov states within the model included: alive without disease, alive with disease and dead. Extensive deterministic and Monte Carlo probabilistic sensitivity analysis was performed to test all parameters contained within the model. Results 23 randomised controlled trials were included. Intention-to-treat analysis of the treatment pathways showed that neoadjuvant chemoradiotherapy was the superior pathway with an overall survival time of 50.52 months (42.26 QALMs). Monte Carlo sensitivity analysis run over 10000 iterations showed that neoadjuvant chemoradiotherapy was selected as the superior treatment pathway at a frequency of 93.21% followed by surgery followed by adjuvant therapy with a frequency of 6.79%. Subgroup analysis of only squamous cell carcinomas demonstrated that neoadjuvant chemoradiotherapy was the superior pathway with an overall survival time of 62.67 months (55.22 QALMs). Conclusions Based on current best available evidence this decision analysis supports neoadjuvant chemoradiotherapy as the treatment strategy of choice for resectable malignancy of the oesophagus or gastroesophageal junction.

Neurobiological Reward-Related Abnormalities Across Mood Disorders

2019 ◽  
pp. 222-238
Author(s):  
Alexis E. Whitton ◽  
Michael T. Treadway ◽  
Manon L. Ironside ◽  
Diego A. Pizzagalli
Keyword(s):  
Decision Making ◽  
Mood Disorders ◽  
Treatment Strategies ◽  
Reward Processing ◽  
Reward Learning ◽  
Symptom Presentation ◽  
Psychiatric Symptomatology ◽  
Symptom Dimensions ◽  
Psychotherapeutic Interventions ◽  
Primary Focus

This chapter provides a critical review of recent behavioral and neuroimaging evidence of reward processing abnormalities in mood disorders. The primary focus is on the neural mechanisms underlying disruption in approach motivation, reward learning, and reward-based decision-making in major depression and bipolar disorder. Efforts focused on understanding how reward-related impairments contribute to psychiatric symptomatology have grown substantially in recent years. This has been driven by significant advances in the understanding of the neurobiology of reward processing and a growing recognition that disturbances in motivation and hedonic capacity are poorly targeted by current pharmacological and psychotherapeutic interventions. As a result, numerous studies have sought to test the presence of reward circuit dysfunction in psychiatric disorders that are marked by anhedonia, amotivation, mania, and impulsivity. Moreover, as the field has increasingly eschewed categorical diagnostic boundaries in favor of symptom dimensions, there has been a parallel rise in studies seeking to identify transdiagnostic neural markers of reward processing dysfunction that may transcend disorders. The thesis of this chapter is twofold: First, evidence indicates that specific subcomponents of reward processing map onto partially distinct neurobiological pathways. Second, specific subcomponents of reward processing, including reward learning and effort-based decision-making, are impaired across different mood disorder diagnoses and may point to dimensions in symptom presentation that possess more reliable behavioral and neural correlates. The potential for these findings to inform the development of prevention and treatment strategies is discussed.

scholarly journals An Innovative Grey Approach for Group Multi-Criteria Decision Analysis Based on the Median of Ratings by Using Python

Axioms ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 124
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Florentin Smarandache ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Likert Scale ◽  
Decision Makers ◽  
Interval Numbers ◽  
Multi Criteria Decision Analysis

Some decision-making problems, i.e., multi-criteria decision analysis (MCDA) problems, require taking into account the attitudes of a large number of decision-makers and/or respondents. Therefore, an approach to the transformation of crisp ratings, collected from respondents, in grey interval numbers form based on the median of collected scores, i.e., ratings, is considered in this article. In this way, the simplicity of collecting respondents’ attitudes using crisp values, i.e., by applying some form of Likert scale, is combined with the advantages that can be achieved by using grey interval numbers. In this way, a grey extension of MCDA methods is obtained. The application of the proposed approach was considered in the example of evaluating the websites of tourism organizations by using several MCDA methods. Additionally, an analysis of the application of the proposed approach in the case of a large number of respondents, done in Python, is presented. The advantages of the proposed method, as well as its possible limitations, are summarized.

The Application of Multicriteria Decision Analysis Methods in Health Care: A Literature Review

2021 ◽  
pp. 0272989X2110190
Author(s):  
Ilyas Khan ◽  
Liliane Pintelon ◽  
Harry Martin
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Decision Analysis ◽  
Medical Devices ◽  
Hybrid Methods ◽  
Multicriteria Decision Analysis ◽  
Multicriteria Decision ◽  
Health Care Decision ◽  
Wide Range ◽  
Care Decision

Objectives The main objectives of this article are 2-fold. First, we explore the application of multicriteria decision analysis (MCDA) methods in different areas of health care, particularly the adoption of various MCDA methods across health care decision making problems. Second, we report on the publication trends on the application of MCDA methods in health care. Method PubMed was searched for literature from 1960 to 2019 in the English language. A wide range of keywords was used to retrieve relevant studies. The literature search was performed in September 2019. Articles were included only if they have reported an MCDA case in health care. Results and Conclusion The search yielded 8,318 abstracts, of which 158 fulfilled the inclusion criteria and were considered for further analysis. Hybrid methods are the most widely used methods in health care decision making problems. When it comes to single methods, analytic hierarchy process (AHP) is the most widely used method followed by TOPSIS (technique for order preference by similarity to ideal solution), multiattribute utility theory, goal programming, EVIDEM (evidence and value: impact on decision making), evidential reasoning, discrete choice experiment, and so on. Interestingly, the usage of hybrid methods has been high in recent years. AHP is most widely applied in screening and diagnosing and followed by treatment, medical devices, resource allocation, and so on. Furthermore, treatment, screening and diagnosing, medical devices, and drug development and assessment got more attention in the MCDA context. It is indicated that the application of MCDA methods to health care decision making problem is determined by the nature and complexity of the health care problem. However, guidelines and tools exist that assist in the selection of an MCDA method.

scholarly journals MULTIPLE CRITERIA DECISION ANALYSIS USING PRIORITISED INTERVAL TYPE-2 FUZZY AGGREGATION OPERATORS AND ITS APPLICATION TO SITE SELECTION

2017 ◽  
Vol 23 (1) ◽  
pp. 1-21 ◽  
Author(s):  
Ting-Yu CHEN
Keyword(s):  
Decision Making ◽  
Decision Analysis ◽  
Site Selection ◽  
Aggregation Operator ◽  
Multiple Criteria ◽  
Multiple Criteria Decision Analysis ◽  
Landfill Site Selection ◽  
Fuzzy Aggregation ◽  
Interval Type

The theory of interval type-2 fuzzy sets provides an intuitive and computationally feasible method of addressing uncertain and ambiguous information in decision-making fields. This paper aims to develop a prioritised interval type-2 fuzzy aggregation operator and apply it to multiple criteria decision analysis with prioritised criteria. This paper considers situations in which a relationship between the criteria exists such that a lack of satisfaction by the higher priority criteria cannot be readily compensated by the satisfaction of lower priority criteria. This paper introduces the developed prioritised interval type-2 fuzzy aggregation operator to address the problem of criteria aggregation in this environment. To demonstrate the feasibility of the proposed operator, this paper provides a multiple criteria decision-making method that uses the prioritised interval type-2 fuzzy aggregation operator, and the method is illustrated with a practical application to landfill site selection.

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