Was Angelina Jolie Right? Optimizing Cancer Prevention Strategies Among BRCA Mutation Carriers

Nohdurft, Eike; Long, Elisa F; Spinler, Stefan

doi:10.1287/deca.2017.0352

Cited by 11 publications

(4 citation statements)

References 75 publications

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“…Clinical data was taken from randomized control trials and case studies of 23andMe which fulfilled ethics approval. (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13) Qualitative sources such as newspaper articles and surveys were also used. (14)(15)(16)(17)(18) The sources were retrieved through a query search on Google Scholar and PubMed in November 2020.…”

Section: Methodsmentioning

confidence: 99%

Epistemic and ethical considerations in the direct-to-consumer health and ancestry genetic testing process

Huerne

2021

MJM

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Background: Direct-to-consumer genetic testing (DTC-GT) is a popular and fast-growing field within the healthcare industry. Consumers often pursue DTC-GT without a clear understanding of its epistemic and medical limitations. This report will present the current state of DTC-GT technology, and highlight the ethical, legal and social issues of DTC-GT. Methods: Quantitative methods such as systematic reviews were used to evaluate the field of DTC-GT. Experimental data was taken from randomized control trials and case studies of 23andMe. Qualitative methods such as newspaper articles and surveys were also used. Relevant policies and regulatory information were analyzed in the context of 23andMe. Broader ethical issues are analyzed from the social disability model and feminist ethics frameworks. Results: Several aspects of direct-to-consumer genetic testing are outlined: (i) regulatory and legal distinctions of DTC-GT that separate its use from conventional genetic testing, (ii) epistemic issues of the genetic testing process within the direct-to-consumer context, and (iii) ethical considerations of DTC-GT in regard to genetic health and genetic ancestry. Conclusion: This report does not take a position for or against the use of DTC-GT; rather, it highlights the key ethical issues often missed in the DTC-GT process. There is no perfect method for understanding genetic health and race. DTC-GT offer consumers the ease and power of taking genetic data ‘in their own hands’, at the cost of exacerbating geneticization and race essentialism. Until further work is done to address the epistemic, regulatory and legal issues, ethical implications of DTC-GT usage will continue to exist.

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Section: Methodsmentioning

confidence: 99%

Epistemic and ethical considerations in the direct-to-consumer health and ancestry genetic testing process

Huerne

2021

MJM

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“…Markov decision processes (MDPs) and POMDPs are the methodological tools of choice for sequential decision‐making problems in healthcare, especially for chronic diseases such as diabetes (e.g., Hoerger et al., 2004, Santoso and Mareels 2001, Shih et al., 2007), HIV/AIDS (e.g., Garg et al., 2012, Lee et al., 2014, Shechter et al., 2008), and cancer (e.g., Ahsen and Burnside 2018, Ayer et al., 2012, Chhatwal et al., 2010, Maillart et al., 2008, Nohdurft et al., 2017, Petousis et al., 2019, Zhang et al., 2012a). MDPs and POMDPs have also been employed to obtain optimal policies in other settings, such as to design therapeutic regimens for hypertension (Zargoush et al., 2018), develop personalized treatments (Ibrahim et al., 2016), and address emergency room congestion (Patrick 2011).…”

Section: Literature Reviewmentioning

confidence: 99%

An Analytics‐Driven Approach for Optimal Individualized Diabetes Screening

Kamalzadeh

Ahuja

Hahsler

et al. 2021

Production and Operations Management

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T ype 2 diabetes is a chronic disease that affects millions of Americans and puts a significant burden on the healthcare system. The medical community sees screening patients to identify and treat prediabetes and diabetes early as an important goal; however, universal population screening is operationally not feasible, and screening policies need to take characteristics of the patient population into account. For instance, the screening policy for a population in an affluent neighborhood may differ from that of a safety-net hospital. The problem of optimal diabetes screening-whom to screen and when to screen-is clearly important, and small improvements could have an enormous impact. However, the problem is typically only discussed from a practical viewpoint in the medical literature; a thorough theoretical framework from an operational viewpoint is largely missing. In this study, we propose an approach that builds on multiple methods -partially observable Markov decision process (POMDP), hidden Markov model (HMM), and predictive risk modeling (PRM). It uses available clinical information, in the form of electronic health records (EHRs), on specific patient populations to derive an optimal policy, which is used to generate screening decisions, individualized for each patient. The POMDP model, used for determining optimal decisions, lies at the core of our approach. We use HMM to estimate the cohort-specific progression of diabetes (i.e., transition probability matrix) and the emission matrix. We use PRM to generate observations-in the form of individualized risk scores-for the POMDP. Both HMM and PRM are learned from EHR data. Our approach is unique because (i) it introduces a novel way of incorporating predictive modeling into a formal decision framework to derive an optimal screening policy; and (ii) it is based on real clinical data. We fit our model using data on a cohort of more than 60,000 patients over 5 years from a large safety-net health system and then demonstrate the model's utility by conducting a simulation study. The results indicate that our proposed screening policy outperforms existing guidelines widely used in clinical practice. Our estimates suggest that implementing our policy for the studied cohort would add one quality-adjusted life year for every patient, and at a cost that is 35% lower, compared with existing guidelines. Our proposed framework is generalizable to other chronic diseases, such as cancer and HIV.

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“…However, this trend was driven by the nature of the submissions received and should not be taken as a limitation on the types of papers that can succeed in Decision Analysis. Examples of other applied topics of interest to the journal include entrepreneurship (Bodily 2016), insurance (Meeker et al 2015, Bodily andFurman 2016), and medical decision making (Alagoz et al 2013, Nohdurft et al 2017.…”

Section: Applications and Case Studiesmentioning

confidence: 99%

From the Editors: Decision Analysis Focus and Trends

Bier

French

2020

Decision Analysis

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Please scroll down for article-it is on subsequent pages With 12,500 members from nearly 90 countries, INFORMS is the largest international association of operations research (O.R.) and analytics professionals and students. INFORMS provides unique networking and learning opportunities for individual professionals, and organizations of all types and sizes, to better understand and use O.R. and analytics tools and methods to transform strategic visions and achieve better outcomes. For more information on INFORMS, its publications, membership, or meetings visit http://www.informs.org

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Was Angelina Jolie Right? Optimizing Cancer Prevention Strategies Among BRCA Mutation Carriers

Cited by 11 publications

References 75 publications

Epistemic and ethical considerations in the direct-to-consumer health and ancestry genetic testing process

Epistemic and ethical considerations in the direct-to-consumer health and ancestry genetic testing process

An Analytics‐Driven Approach for Optimal Individualized Diabetes Screening

From the Editors: Decision Analysis Focus and Trends

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