Why Hasn't Genomic Testing Changed the Landscape in Clinical Oncology?

2012 ◽  
pp. e52-e55 ◽  
Author(s):  
Daniel F. Hayes ◽  
Muin J. Khoury ◽  
David Ransohoff
Keyword(s):  
Clinical Utility ◽  
Computational Models ◽  
New Technologies ◽  
Clinical Care ◽  
Tumor Biomarker ◽  
False Discovery Rates ◽  
Patients With Cancer ◽  
Slow Progress ◽  
The Difference ◽  
Therapeutic Research

Overview: The “omics” revolution produced great optimism that tumor biomarker tests based on high-order analysis of multiple (sometimes thousands) of factors would result in truly personalized oncologic care. Unfortunately, 10 years into the revolution, the promise of omics-based research has not yet been realized. The factors behind the slow progress in omics-based clinical care are many. First, over the last 15 years, there has been a gradual recognition of the importance of conducting tumor biomarker science with the kind of rigor that has traditionally been used for therapeutic research. However, this recognition has only recently been applied widely, and therefore most tumor biomarkers have insufficiently high levels of evidence to determine clinical utility. Second, omics-based research offers its own particular set of concerns, especially in regard to overfitting computational models and false discovery rates. Researchers and clinicians need to understand the importance of analytic validity, and the difference between clinical/biologic validity and clinical utility. The latter is required to introduce a tumor biomarker test of any kind (single analyte or omics-based), and are ideally generated by carefully planned and properly conducted “prospective retrospective” or truly prospective clinical trials. Only carefully planned studies, which take all three of these into account and in which the investigators are aware and recognize the enormous risk of unintended bias and overfitting inherent in omics-based test development, will ultimately result in translation of the exciting new technologies into better care for patients with cancer.

scholarly journals Defining Clinical Utility of Tumor Biomarker Tests: A Clinician's Viewpoint

2020 ◽  
pp. JCO.20.01572
Author(s):  
Daniel F. Hayes
Keyword(s):  
Clinical Utility ◽  
The United States ◽  
Therapeutic Strategies ◽  
Risk Tolerance ◽  
Tumor Biomarker ◽  
End Points ◽  
Patients With Cancer ◽  
The Difference ◽  
Level I ◽  
Definition Of

Tumor biomarker tests (TBTs) are used to guide therapeutic strategies for patients with cancer. However, the regulatory environment for TBTs in the United States is inconsistent and, in general, TBTs are poorly valued. The National Academy of Medicine has recommended that TBTs should not be used in general practice until they are shown to have analytical validity and clinical utility. The latter term, first coined by the Evaluation of Genomic Applications in Practice and Prevention Initiative, has been widely stated but is indeterminately defined. In considering whether a TBT has clinical utility, several factors need to be considered: (1) What is the intended use of the TBT? (2) What are the end points that are used to determine clinical utility? (3) How substantial does the difference in end points between groups defined by the TBT need to be to determine therapeutic strategies? (4) What is the risk tolerance of the stakeholders? and (5) Who are the stakeholders that make the decision? For all these factors, the data used to consider clinical utility must be derived from level I evidence studies. In conclusion, there is no strict definition of clinical utility for a TBT. However, consideration of these factors will lead to more objective conclusions. Doing so will facilitate value-based decisions regarding whether a TBT should be used to guide patient care.

Considerations for Implementation of Cancer Molecular Diagnostics Into Clinical Care

2016 ◽  
pp. 292-296 ◽  
Author(s):  
Daniel F. Hayes
Keyword(s):  
Cancer Biology ◽  
Clinical Utility ◽  
Clinical Care ◽  
Quality Care ◽  
Tumor Biomarker ◽  
Personalized Care ◽  
Fda Approval ◽  
Improve Patient ◽  
Risk Categorization ◽  
Analytic Validity

Physicians have provided personalized care with as much precision as possible for several centuries. However, increasingly sophisticated understanding of the human genome and of cancer biology has permitted identification of genetic and phenotypic distinctions that might permit development of new tumor biomarker tests for risk categorization, screening, differential diagnosis, prognosis, prediction, and monitoring. Both commercial and academic laboratories are offering tests for single analytes, panels of tests of single analytes, multiparameter assays coalesced into a signature, and total genomic, transcriptomic, or proteomic analyses. However, the absence of a consistent regulatory environment has led to marketing of assays without proven analytic validity or clinical utility. U.S. Food and Drug Administration (FDA) approval or clearance does not necessarily imply that use of the test will improve patient outcomes, and FDA discretion to permit laboratory-developed tests results in unknown benefit, or harm, of others. In this regard, a “bad tumor marker is as bad as a bad drug.” Caveat emptor is not a satisfactory approach to delivering high-quality care. Rather, adoption of tumor biomarker tests should be based on high levels of evidence generated in scientifically rigorous studies that demonstrate both analytical validity and clinical utility. Doing so will ensure that clinicians and patients are confident that a tumor biomarker test is likely to improve their outcomes.

Comparison of Thrombelastography with Common Coagulation Tests

1981 ◽  
Vol 46 (04) ◽  
pp. 752-756 ◽  
Author(s):  
L Zuckerman ◽  
E Cohen ◽  
J P Vagher ◽  
E Woodward ◽  
J A Caprini
Keyword(s):  
Laboratory Tests ◽  
Clinical Utility ◽  
Blood Clotting ◽  
Strong Relationship ◽  
Relative Strength ◽  
Additional Information ◽  
Patients With Cancer ◽  
Two Samples ◽  
Coagulation Tests ◽  
Common Laboratory

SummaryThrombelastography, although proven as a useful research tool has not been evaluated for its clinical utility against common coagulation laboratory tests. In this study we compare the thrombelastographic measurements with six common tests (the hematocrit, platelet count, fibrinogen, prothrombin time, activated thromboplastin time and fibrin split products). For such comparisons, two samples of subjects were selected, 141 normal volunteers and 121 patients with cancer. The data was subjected to various statistical techniques such as correlation, ANOVA, canonical and discriminant analysis to measure the extent of the correlations between the two sets of variables and their relative strength to detect blood clotting abnormalities. The results indicate that, although there is a strong relationship between the thrombelastographic variables and these common laboratory tests, the thrombelastographic variables contain additional information on the hemostatic process.

Digital Transformation of the Service Sector

2021 ◽  
pp. 41-54
Author(s):  
D. Shevchenko ◽  
V. Mihaylov
Keyword(s):  
Business Model ◽  
Service Sector ◽  
New Technologies ◽  
Rapid Development ◽  
Digital Transformation ◽  
Services Sector ◽  
Remote Maintenance ◽  
New Business ◽  
The Difference ◽  
Cloud Technologies

The article is devoted to the problems of digital transformation of companies in the service sector. The article describes the concepts of "digitization", "digitalization", "digital transformation", "automation". The analysis of the main sectors of the public services sector, the processes of transformation into a new business model of their development is carried out. Specific examples show the role of digital technologies implemented by individual companies, the leaders of their industry: "Internet of Things" (IoT); virtual diagnostics of the service; mobile applications and portals; artificial intelligence and machine learning (AI / ML); remote maintenance; UX design; virtual reality; cloud technologies; online services and others. The authors proceed from understanding the difference between automation and digitalization, the strategic goal of which is to create a new digital business model that creates new value. The result of digital transformation is the reconfiguration of processes that change the business logic of the company and the process of creating value. The article concludes that the rapid development of new technologies leads to the fact that companies face not only a dilemma when choosing the most suitable technologies for investment, but also the problem of staffing and finding an adequate organizational structure to create and maintain a new business model of the company.

Evaluating prediction of continuous clinical values: a glucose case study (Preprint)

2021 ◽  
Author(s):  
George Hripcsak ◽  
David J Albers
Keyword(s):  
Predictive Models ◽  
Clinical Utility ◽  
Clinical Care ◽  
Glucose Measurement ◽  
Care Processes ◽  
Low Glucose ◽  
Potential Clinical Utility ◽  
Rms Error ◽  
Error Grid

BACKGROUND Background: It would be useful to be able to assess the utility of predictive models of continuous values before clinical trials are carried out. OBJECTIVE Objective: To compare metrics to assess the potential clinical utility of models that produce continuous value forecasts. METHODS Methods: We ran a set of data assimilation forecast algorithms on time series of glucose measurements from intensive care unit patients. We evaluated the forecasts using four sets of metrics: glucose root mean square error, a set of metrics on a transformed glucose value, the estimated effect on clinical care based on an insulin guideline, and a glucose measurement error grid (Parkes grid). We assessed correlation among the metrics and created a set of factor models. RESULTS Results: The metrics generally correlated with each other, but those that estimated the effect on clinical care correlated with the others the least and were generally associated with their own independent factors. The other metrics appeared to separate into those that emphasized errors in low glucose versus errors in high glucose. The Parkes grid was well correlated with the transformed glucose but not the estimation of clinical care. CONCLUSIONS Discussion: Our results indicate that we need to be careful before we assume that commonly used metrics like RMS error in raw glucose or even metrics like the Parkes grid that are designed to measure importance of differences will correlate well with actual effect on clinical care processes. A combination of metrics appeared to explain the most variance between cases. As prediction algorithms move into practice, it will be important to measure actual effects.

scholarly journals Digital Economy : A Journey Through 21st Century Towards 22nd Century with Respect to India

2021 ◽  
pp. 85-94
Author(s):  
Dr. Pradipta Mukhopadhyay
Keyword(s):  
New Technologies ◽  
Research Work ◽  
Big Data Analytics ◽  
Digital Economy ◽  
Modern World ◽  
Economic Activities ◽  
22Nd Century ◽  
The World ◽  
The Difference ◽  
To Come

Digital Economy refers to an economy which is based on digital computing technologies and can also be referred to as internet economy or web economy as the business activities are conducted through markets based on the internet or the World Wide Web. A Digital Economy also refers to the usage of various digitised information and knowledge to perform various economic activities and uses various new technologies like Internet, Cloud Computing, Big Data Analytics to collect, store and analyse information digitally. This way the modern digital economies are helping the local and regional business organisations to come out of their local boundaries and step into the global scenario to take advantages of the modern liberalisation policies of the governments along with reduced trade barriers throughout the world. This paper will study the importance of digital economy in the modern world along with the difference between the traditional economy and the digital economy and the current state of digital economy in India. This Study has been casual, exploratory and empirical in nature and the data needed for research work has been collected by using both direct and indirect method of data collection.

scholarly journals ACADEMIA’S ROLE TO DRIVE CHANGE IN THE ORTHOTICS AND PROSTHETICS PROFESSION

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Géza Kogler ◽  
Christopher Hovorka
Keyword(s):  
Technology Use ◽  
Clinical Training ◽  
Clinical Decision Making ◽  
New Technologies ◽  
Clinical Care ◽  
Clinical Decision ◽  
The United States ◽  
Academic Program ◽  
Number Of Patients ◽  
Curricular Emphasis

This position paper outlines the important role of academia in shaping the orthotics and prosthetics (O&P) profession and preparing for its future. In the United States, most healthcare professions including O&P are under intense pressure to provide cost effective treatments and quantifiable health outcomes. Pivotal changes are needed in the way O&P services are provided to remain competitive. This will require the integration of new technologies and data driven processes that have the potential to streamline workflows, reduce errors and inform new methods of clinical care and device manufacturing. Academia can lead this change, starting with a restructuring in academic program curricula that will enable the next generation of professionals to cope with multiple demands such as the provision of services for an increasing number of patients by a relatively small workforce of certified practitioners delivering these services at a reduced cost, with the expectation of significant, meaningful, and measurable value. Key curricular changes will require replacing traditional labor-intensive and inefficient fabrication methods with the integration of newer technologies (i.e., digital shape capture, digital modeling/rectification and additive manufacturing). Improving manufacturing efficiencies will allow greater curricular emphasis on clinical training and education – an area that has traditionally been underemphasized. Providing more curricular emphasis on holistic patient care approaches that utilize systematic and evidence-based methods in patient assessment, treatment planning, dosage of O&P technology use, and measurement of patient outcomes is imminent. Strengthening O&P professionals’ clinical decision-making skills and decreasing labor-intensive technical fabrication aspects of the curriculum will be critical in moving toward a digital and technology-centric practice model that will enable future practitioners to adapt and survive. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/36673/28349 How To Cite: Kogler GF, Hovorka CF. Academia’s role to drive change in the orthotics and prosthetics profession. Canadian Prosthetics & Orthotics Journal. 2021; Volume 4, Issue 2, No.21. https://doi.org/10.33137/cpoj.v4i2.36673 Corresponding Author: Géza F. KoglerOrthotics and Prosthetics Unit, Kennesaw State University.E-Mail: [email protected] ID: https://orcid.org/0000-0003-0212-5520

scholarly journals Contrasting Medical and Legal Standards of Evidence: A Precision Medicine Case Study

2016 ◽  
Vol 44 (1) ◽  
pp. 194-204 ◽  
Author(s):  
Gary E. Marchant ◽  
Kathryn Scheckel ◽  
Doug Campos-Outcalt
Keyword(s):  
Precision Medicine ◽  
New Technologies ◽  
Clinical Care ◽  
Large Body ◽  
Standard Of Care ◽  
Genetic Profile ◽  
Legal Standards ◽  
Standards Of Evidence ◽  
The Individual

As the health care system transitions to a precision medicine approach that tailors clinical care to the genetic profile of the individual patient, there is a potential tension between the clinical uptake of new technologies by providers and the legal system's expectation of the standard of care in applying such technologies. We examine this tension by comparing the type of evidence that physicians and courts are likely to rely on in determining a duty to recommend pharmacogenetic testing of patients prescribed the oral anti-coagulant drug warfarin. There is a large body of inconsistent evidence and factors for and against such testing, but physicians and courts are likely to weigh this evidence differently. The potential implications for medical malpractice risk are evaluated and discussed.

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