Showing posts sorted by relevance for query genetic tests. Sort by date Show all posts
Showing posts sorted by relevance for query genetic tests. Sort by date Show all posts

February 25, 2014

The hole for genetic testing market entry

Technology Assessment on Genetic Testing or Molecular Pathology Testing of Cancers with Unknown Primary Site to Determine Origin
Update on Emerging Genetic Tests Currently Available for Clinical Use in Common Cancers

AHRQ has just published two reports of interest. The first is devoted  to assess the evidence on the analytical validity, clinical validity, and clinical utility of commercially available genetic tests for identifying the tissue of origin (TOO) of the cancer in patients with cancer of unknown primary (CUP) site. The second describes genetic tests that have applications in the common solid tumors (breast, lung, colorectal, pancreas, etc.) as well as tests that are used in hematologic cancers (leukemia, lymphoma) and are already available in clinical practice.While the first is an assessment, the second is informative.
There is still a third report to be released and meanwhile NRD explains its conclusions. Having selected 11 prognostic tests, only around half had evidence supporting their prognostic accuracy or clinical validity. Therefore the question is always the same: why these tests without evidence are on the market? Why have they been approved by the FDA?. There is a big regulatory hole to fill in.

February 6, 2015

The hype over genetic tests

Implementation of a companion diagnostic in the clinical laboratory:The BRAF example in melanoma

Analytical validity is one of the three steps for any assessment of genetic tests, combined with clinical validity and clinical utility. Understanding how this process affects specific tests is not that easy.Fortunately you can find a detailed explanation of one of them:the BRAF genotype analysis in tumor tissue samples for identification of melanoma patients that can benefit treatment with BRAF inhibitors.
Once you begin to read the article you'll understand the complexity of being precise in a test. This is the reason why if specificity and sensibility is uncertain, different methodologies are needed (check Figure 1).
But how to do it?. How to set up external controls of quality?. All these issues are covered in this article, that explains what's going on in practical terms. I'm concerned if due to such complexity, all "genetic test talent" is not concentrated in one site of the organization-hospital, and many departments and services -oncology or cardiology- are developing their own genetic tests. Somebody should block this option before it is too late.

March 14, 2011

Veure-les passar

El tema segueix sobre la taula. El debat sobre les proves genètiques i com regular-les preocupa a la FDA i encara que ja ha dit que cal aplicar els mateixos criteris que als subministraments mèdics (medical devices), hi ha molts dubtes sobre els detalls.

Els de Genomics Law Report expliquen el que ha passat a les compareixences recents. Si n'esteu interessats feu-hi una ullada.
Les preguntes clau:
Should the agency require proof of analytical validity, clinical validity and/or clinical utility prior to approving a particular test and, if so, what standards of proof should be required?
Should the agency regulate tests SNP-by-SNP, claim-by-claim or test-by-test, and what should be done to prepare for the inevitable arrival of tests based on whole-genome sequence data?
Should the agency oversee the labeling and advertising claims offered by companies in association with such tests?
Should the agency require companies to collect and submit data regarding the post-test benefits and harms and the actual (as compared to intended) uses of their tests?
Should the agency impose requirements on companies to prevent unauthorized testing, protect data privacy and limit companies’ ability to share genetic information without their customers’ consent?

While these questions, and countless more, will be critical to the development of sensible genetic testing regulation, one question clearly generates more and more emotional responses than any other:

Should regulators require some or all genetic tests to be routed through a clinician, or should tests be made available directly to consumers who desire them?
I mentrestant per aquí, les veiem passar...i ens costen una pasta...

PD. El gran Ferran Torrent representa una alenada d'aire fresc els diumenges, tant en directe a Rac1 com els comentaris a ARA. Cita Josep Renau: "Quan arribes a València i et menges una paella o una sípia t'oblides de la lluita de classes". I mentrestant els de FT ens recorden que "Valencia is burning"

April 7, 2017

When science and regulation don't talk to each other

An Evidence Framework for Genetic Testing

National Academy of Sciences and Food and Drug Administration don't talk to each other. At the same time that NASEM publishes a report on how to assess genetic testingFDA clears genetic testing for 23andme without any precise assessment, for the following tests:

  • Parkinson’s disease, a nervous system disorder impacting movement
  • Late-onset Alzheimer’s disease, a progressive brain disorder that destroys memory and thinking skills
  • Celiac disease, a disorder resulting in the inability to digest gluten
  • Alpha-1 antitrypsin deficiency, a disorder that raises the risk of lung and liver disease
  • Early-onset primary dystonia, a movement disorder involving involuntary muscle contractions and other uncontrolled movements
  • Factor XI deficiency, a blood clotting disorder
  • Gaucher disease type 1, an organ and tissue disorder
  • Glucose-6-Phosphate Dehydrogenase deficiency, also known as G6PD, a red blood cell condition
  • Hereditary hemochromatosis, an iron overload disorder
  • Hereditary thrombophilia, a blood clot disorder
Meanwhile NASEM recommends a decision framework for the use of genetic tests in clinical care:
1. Define genetic test scenarios on the basis of the clinical setting, the purpose of the test, the population, the outcomes of interest, and comparablealternative methods.
2. For each genetic test scenario, conduct an initial structured assessment to determine whether the test should be covered, denied, or subject to additional evaluation.
3. Conduct or support evidence-based systematic reviews for genetic test scenarios that require additional evaluation.
4. Conduct or support a structured decision process to produce clinical guidance for a genetic test scenario.
5. Publicly share resulting decisions and justification about evaluated genetic test scenarios, and retain decisions in a repository.
6. Implement timely review and revision of decisions on the basis of new data.
7. Identify evidence gaps to be addressed by research.
If you want further details, check Mathew Herper blog. My first impression after reading it is that this move, paves the way for recreational genetic testing. An approach that should be completely banned by legislation. If FDA has done so, let's wait for what it may happen in Europe where the regulator is still planning a change of the regulation in 2022!!! Meanwhile, the door is open (to the worst for citizens).

August 26, 2014

The uncertainty over genomics sequencing value in clinical decision making

Assessing Genomic Sequencing Information for Health Care Decision Making: Workshop Summary

"The value of genetic sequence information will depend on how it is used in the clinic", key statement that needs some elaboration. This is precisely what the IOM report does, you'll find in their pages the current situation about how genomics may impact in decision making. In chapter 5 you'll understand how an insurer decides about coverage of such tests according to 5 criteria:
1. The test or treatment must have final approval from appropriate governmental regulatory bodies, where required;
2. scientific evidence must permit conclusions about its effect on medical outcomes;
3. technology must improve net health outcomes;
4. the technology must provide as much health benefit as established alternatives; and
5. the improvement in health must be attainable outside investigational settings.
Unfortunately, if you start from the first one, you'll find a complete lack of references by governmental bodies on the approval of such tests. Therefore, I can't understand from the chapter how successful they are on such process.
While reading the book you'll increase your uncertainty about outcomes and value of genomic tests instead of reducing it. This was my impression. Let's wait for future good news, again.

PS. Summary of the report:
"Clinical use of DNA sequencing relies on identifying linkages between diseases and genetic variants or groups of variants. More than 140,000 germline mutations have been submitted to the Human Gene Mutation Database and almost 12,000 single nucleotide polymorphisms have currently been associated with various diseases, including Alzheimer’s and type 2 diabetes, but the majority of associations have not been rigorously confirmed and may play only a minor role in disease. Because of the lack of evidence available for assessing variants, evaluation bodies have made few recommendations for the use of genetic tests in health care."

December 12, 2021

The value of direct-to-consumer tests

 Direct-to-Consumer Tests on the Market Today. Identifying Valuable Tests from Those with Limited Utility

For health care professionals, the analytical validity of DTC tests is a primary concern. Analytical validity of DTC genetic testing can be defined by analytical sensitivity and specificity whereby analytical sensitivity is defined as how often a test is positive when the genetic variant of interest is present in the tested sample, and the analytical specificity is defined as how often a test result is negative when the tested sample does not contain the genetic variant of interest.18 A recent study by Tandy-Connor and colleagues19 “indicated that 40% of variants in a variety of genes reported in DTC raw data were false positives” when compared with clinical confirmatory testing. This study highlights the need to scrutinize the analytical validity of DTC genetic testing and consider confirmatory testing in a clinical diagnostic genetics laboratory. 

Per the American Society of Human Genetics, “companies offering DTC genetic testing should disclose the sensitivity, specificity and predictive value of the test, and the populations for the information is known, in a readily understandable and accessible fashion.”

Unfortunately, nobody cares about it, and the regulator is still on vacation.

September 18, 2016

The anxiety of inaccuracy

Conflicting Interpretation of Genetic Variants and Cancer Risk by Commercial Laboratories as Assessed by the Prospective Registry of Multiplex Testing

What happens if "one quarter of the clinical genetic results from commercially available multiplex cancer panels and reported at the PROMPT registry had conflicting interpretations" and if "36% of conflicting genetic tests results appeared to be clinically relevant, because they were either reported as pathogenic/likely pathogenic"? Does anybody care about it?.
I would suggest today you have a look at this article and your level of anxiety will increase suddenly.
Clinical data and genetic testing results were gathered from1,191 individuals tested for inherited cancer susceptibility and self-enrolled in PROMPT between September 2014 and October 2015. Overall,participants (603 genetic variants) had a result interpreted by more than one laboratory, including at least one submitted to ClinVar, and these were used as the final cohort for the current analysis.

Of the 603 variants, 221 (37%) were classified as a variant of uncertain significance (VUS), 191 (32%) as pathogenic, and 34 (6%) as benign. The interpretation differed among reporting laboratories for 155 (26%). Conflicting interpretations were most frequently reported for CHEK2 and ATM, followed by RAD51C, PALB2, BARD1, NBN, and BRIP1. Among all participants, 56 of 518 (11%) had a variant with conflicting interpretations ranging from pathogenic/likely pathogenic to VUS, a discrepancy that may alter medical management.
Clinical interpretation of genetic testing for increased cancer susceptibility as assessed by multiplex panels hinges on accurate curation and interpretation of variants. Discrepant interpretation of some genetic variants appears to be common.
Take care. The regulator remains on vacation, a never ending vacation.

PS. On genetic testing 

December 14, 2017

The urgent need to define delivery models for genetic testing

Identification of Delivery Models for the Provision of Predictive Genetic testing in Europe: Protocol for a Multicentre Qualitative study and a systematic review of the literature

The increasing role of genomics in medical decision making requires a review on how services should be organised. Unless this effort is taken promptly, it will be much more difficult to adapt the messy organization to an efficient model for the delivery of services. This issues are explained in a recent article. The ten questions:

 The transfer of genomic technologies from research to clinical application is influenced not only by several factors inherent to research goals and delivery of healthcare but also by external and commercial interests that may cause the premature introduction of genetic tests in the public or private sector (i.e., introduction of a test despite insufficient evidence regarding its analytical validity, clinical validity, and utility). Furthermore, current genetic services are delivered without a standardized set of process and outcome measures, which are essential for the evaluation of healthcare services. It is important that only genetic/genomic applications with proven efficacy and effectiveness are delivered to populations, and particularly that technologies have favorable cost-effectiveness ratios

May 10, 2013

Economics of genomics

The Economics of Genomic Medicine - Workshop Summary

Just imagine for a while that you are concerned about economic implications of genomics and you invite a distinguished professor of genetic medicine - James Evans- to the introduction of a workshop at IOM. Instead of more is better, he sends a cautious message to the audience. And beyond the potential and valuable applications for those that are already ill,  he openly critizises the current trend towards the use of genetic tests for the healthy:
Assessing the risk of common diseases through whole genome analysis of a healthy person has received the most attention, but this attention “is somewhat misplaced,” Evans said. Currently, assessment of genetic risk alleles has “rather feeble predictive power” because the increased risks tend to be small. “From a clinical standpoint I don’t know what to do with patients who are at a 1.3 relative risk for colon cancer,” said Evans. “Am I going to hurt them by doing more intensive screening, or am I going to help them?”
"I know what almost everybody in this room is going to die of,” said Evans. “We are going to die of heart disease or cancer. . . . We are all at high risk for these maladies regardless of our [genomically determined] risk. And many at decreased risk for heart disease will still die of heart disease. So we are all going to benefit from interventions that lower heart disease. We don’t really need to target people. It doesn’t do anyone much good to tweak our estimation of an individual’s relative risk for common diseases which we are all at high absolute risk of developing anyway."
 “The old adage that an elephant for a nickel is only a bargain if you have a nickel and you need an elephant applies here. I am not sure most of us need that elephant. Even if free, perceived low cost is an illusion, because the misapplication of medical tests—and make no mistake, whole genome sequencing is a medical test—is very expensive,”
A clear message for geneto-enthusiasts and marketeers. Cost-effectiveness of genetic testing starts with assessing if they are effective. If not, any economic analysis is useless . This is obvious, but we do need to repeat it, just in case.

PS. Must read, Reinhardt's blog.

PS. A report to understand the financial markets' mess and why recovery is far by now.

November 6, 2013

Courts as market makers

Recent decision invalidating Myriad patents has had immediate results. The market of genetic tests on breast and ovarian cancer has new entrants. The price of the test has decreased 40% (!) in just four months after the resolution. More entrants are expected in the next future for more tests.
The question is still the same, is there any clear cost-effectiveness analysis available for such tests? Why homebrew tests (LDT) are beyond any regulation? Does any regulator care about all this issues?. The answer is: up to now, we can't see any efforts. Patents create artificial monopolies, courts may create markets when invalidate patents,  but patients are concerned about health improvement and value. In an asymetric information environment, the regulator can't take permanent holidays. Overdiagnosed population doesn't necessarily mean healthier population.

 Forbes Healthcare Summit 2013
Insurance Companies Enter A New World

December 23, 2014

European health regulator on holiday

After Canada, the first european country that has allowed recreational genetic testing is UK. Some weeks ago the Ethics Research Committee approved the commercialisation of 23andme test that provides 100 genetic reports. Wired says:
The £125 spit test kit is not a diagnostic test, but instead identifies genes that are associated with inherited conditions including cystic fibrosis, Alzheimer's disease, Parkinson's disease and sickle cell anaemia. It's not just health information that can be discovered within the results of the test though -- there is also the opportunity for customers to learn more about their inherited traits and genetic ancestry.
Why has the UK approved it and the FDA has restricted the same test in the US?.  Some months ago I explained that european legislation was outdated. Now the genetic testing firm has profited from bad regulation to enter into european market with CE mark. Does anybody know where the regulator is spending their holiday?

PS. While being  so easy to regulate recreational genetic testing under current false advertising rules, why is only the US doing that?. You should know that closer than you think similar tests are available for you. Where is the catalan health regulator?

PS. Why is the tax regulator not on vacation?

Emile Claire Barlow - Jardin d'Hiver

January 24, 2018

Challenges in Cost-Effectiveness Analysis of genomic tests

Type of challengeExample of challengeDescription of challenge
MethodologicalSelecting the appropriate evaluative frameworkIs the standard extra-welfarist view and use of CEA appropriate, or should the distinct theoretical approach reflecting the welfarist view and use of CBA be adopted to allow consequences other than health gain, such as the value of diagnostic information from the genomic-targeted diagnostic test, to be valued?
Relevant study perspectiveIs the standard recommendation to focus on the use of health-care services appropriate when the genomic-targeted diagnostic test may provide information that affects the use of other services, such as education or employment?
Relevant time horizonIs a lifetime sufficient when the impact of a genomic-targeted diagnostic test may extend to infinite time horizons that are not limited by the lifespan of one individual?
Defining the relevant study populationIs the standard definition of a patient (the person receiving the technology) appropriate when there could be spillover effects to family members (currently alive or to be born) as a result of information from a genomic-targeted diagnostic test?
Valuing consequencesIs identifying and measuring the impact on health status alone sufficient to capture the (good and bad) consequences of a genomic-targeted diagnostic test?
TechnicalVariation in the individual characteristics of the relevant study populationThe use of cohort state transition Markov models, sometimes combined with decision trees, cannot easily capture the impact of individual patient variation within a population with different genotypes and phenotypes
Number of diagnostic and, if appropriate, subsequent treatment pathwaysThe use of cohort state transition Markov models, sometimes combined with decision trees, cannot easily account for multiple comparators often needed when evaluating a new genomic-targeted diagnostic test
Capturing impact of reduced time to diagnosisThe use of cohort state transition Markov models, sometimes combined with decision trees, cannot account for the impact of reduced time to achieve a diagnosis, which is often a proposed benefit of a genomic-targeted diagnostic test
Capturing impact of capacity constraintsDecision analytic model-based CEA currently assumes limitless capacity within health-care systems, which is often not a reasonable assumption when introducing a genomic-targeted diagnostic test to populations for whom a diagnosis was not previously available
PracticalAvailability of dataThere is often a lack of data available to populate decision analytic model-based CEA
National tariff of test costNo national tariff for genomic-targeted tests exist
OrganizationalComplex health-care systemsDecision analytic model-based CEA assumes that money saved and benefits accrued are transferable, but this is often challenging in complex health-care systems that comprise an overarching funding mechanism (public, private, insurance), a service and staffing model for providing care for different sectors (community, general practice, hospital, specialist) and a means of allocating funding to these different sectors
Generalizability of resultsDecision analytic model-based CEA is relevant only to the defined decision problem, and decision-makers who want to use the results must decide whether the focus of the analysis is relevant to their own jurisdiction
Expensive nature of health technology assessmentDecision analytic model-based CEA conducted within national health technology assessment processes requires considerable funding and expertise that are not available to all, which may contribute to the inequity in access to new genomic-targeted diagnostic tests across the world
  1. CBA, cost-benefits analysis; CEA, cost-effectiveness analysis.