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 testing, FDA 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).

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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

La petja que traginem

A Survey of UK Public Interest in Internet-Based Personal Genome Testing 

The Behavioral Response to Personalized Genetic Information:Will Genetic Risk Profiles Motivate Individuals and Families to Choose More Healthful Behaviors?

L'interès per la informació genòmica creix, però ja va sent hora de preguntar-se si serveix. Dues publicacions han analitzat quina és l'actitud envers aquestes proves i si això els faria canviar el seus hàbits de salut. Al Plos One trobareu l'article. Un resum en un paràgraf:

One in twenty participants (5%) were potentially interested at current prices (£250), however this proportion rose to half (50%) if the test was free of charge. Nearly all respondents who were interested in free PGT reported they would take the test to encourage them to adopt a healthier lifestyle if found to be at high genetic risk of a disease (93%). Around 4 in 5 respondents would have the test to convey genetic risk information to their children and a similar proportion felt that having a PGT would enable their doctor to monitor their health more closely.

I a l'Annual Review of Public Health, un altre:

To conclude, personalized genetic information has its greatest impact on behavior when disease risks are appreciable. Genetic information based on single-gene variants with low risk  probabilities has little impact—either positive or negative—on emotions, cognitions, or behavior. The difficulty of health behavior change, the rapid pace of technology in the areas of genetics (68), environmental assessment (20), and communication modalities (65) suggest the need to accelerate research in evaluating whether new understandings of genetic risk can favorably influence health behavior,

 Ja cal que augmentem l'esforç per a comprendre com l'allau de noves tecnologies tindran un impacte en la salut. L'impacte en el cost ja podem anar descomptant-lo (si és que el podem pagar algun dia).

Challenges in Cost-Effectiveness Analysis of genomic tests

From: Cost-effectiveness analyses of genetic and genomic diagnostic tests (Must read)

Type of challenge	Example of challenge	Description of challenge
Methodological	Selecting the appropriate evaluative framework	Is 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 perspective	Is 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 horizon	Is 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 population	Is 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 consequences	Is identifying and measuring the impact on health status alone sufficient to capture the (good and bad) consequences of a genomic-targeted diagnostic test?
Technical	Variation in the individual characteristics of the relevant study population	The 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 pathways	The 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 diagnosis	The 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 constraints	Decision 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
Practical	Availability of data	There is often a lack of data available to populate decision analytic model-based CEA
	National tariff of test cost	No national tariff for genomic-targeted tests exist
Organizational	Complex health-care systems	Decision 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 results	Decision 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 assessment	Decision 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.