El valor de les proves diagnòstiques genètiques

Economic evaluation of next-generation sequencing techniques in diagnosis of genetic disorders: A systematic review

Supporting Biomarker-Driven Therapies in Oncology: A Genomic Testing Cost Calculator 

Aquest és un tema amb moltes singularitats i cal estar atents als detalls. Entendre el cost-efectivitat de les proves diagnòstiques obliga a precisar molt què es pretén i com la prova diagnòstica modifica la decisió clínica. És per això que s'hauria d'aplicar el cost per persona identificada correctament com a punt de referència clau. Ara bé això no és senzill de calcular.

Ara tots els ulls estan posats en seqüenciar l'exoma, i un article recent arriba a aquesta conclusió:

On the basis of the available evidence and present findings, exome sequencing as a cost-effective option could have the potential to be used as a genomic test to diagnose suspected genetic disorders. However, there is still no consensus among studies on performing the exome sequencing test as a first- or second-line diagnostic test. While NGS methods are usually implemented as the last diagnostic test by reason of their relatively high cost, a number of recent studies have indicated that when exome sequencing is  implemented as a first-line test, extra examinations avoided for diagnosed patients may amply compensate for the cost of the test.

Per tant deixa oberta la qüestió i no respon a la pregunta.  Jo crec que és qüestió de dies, seqüenciar l'exoma es convertirà en l'estandard.

PS. Més material.

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.

World Press Photo BCN

Bioethics for lab medicine

 Ethics for Laboratory Medicine

Key issues:

Table 1.Ethical Issues of particular importance in Laboratory medicine.

Informed consent 

Use of leftover specimens 

Biobanking 

Genetic testing 

Equity and access to laboratory testing 

Incidental findings and medically actionable results 

DTC testing 

Transfusion medicine and religious or ethical restrictions 

Disclosing medical error 

Emerging infectious diseases 

Test utilization 

The unique role of laboratorians, who care for patients but interact mainly with their samples rather than the person, creates distinct ethical dilemmas. In addition, laboratories function as critical parts of complex health systems, and the interaction of the laboratory with the greater healthcare system creates additional points of ethical friction (45). Clinical laboratory professionals are ethically bound to use our voices to advocate for excellence in patient care in the realms of respect for persons, beneficence, and justice, even in the face of technological, administrative, and, perhaps, clinical pressures to do otherwise.

Ethics represents moral principles based on cultural norms and values. Sometimes these moral values have been turned into federal or state laws or into local rules and regulations. However, laws and rules may be absent or difficult to apply to a given situation. When faced with ethical decisions, laboratorians should seek the input from other clinicians and laboratory colleagues. In addition, most hospitals have ethics boards comprising multidisciplinary teams of clinicians, lay people, and clergy to help guide decision-making.

 

Clinical utility of genomic sequencing

 Clinical utility of genomic sequencing: a measurement toolkit

From Genomic Medicine:

For a diagnostic test such as WGS (whole genome sequencing) to be accepted into practice, commissioned in a health system, or receive coverage and reimbursement through health insurance, evidence of clinical utility and cost-effectiveness is generally required. Unlike prospective clinical research where the ‘effectiveness’ of an intervention can be easily tied to a predefined health outcome, the concept of clinical utility in genetic medicine is rarely uniformly defined nor necessarily directly tied to a specific health outcome. As such, generating and evaluating evidence of clinical utility is complex. The challenge in defining clinical utility today is compounded by the extraordinary heterogeneity of rare diseases, as well as the polygenic nature of more common conditions for which WGS is expected to be relevant. In this paper, we aim to extend earlier conceptualizations of clinical utility as applied to the diagnostic use of WGS and suggest that this framework not only be used as a tool for evidence review

 The application of this model to WGS includes six levels of efficacy: technical efficacy, diagnostic accuracy efficacy, diagnostic thinking efficacy, therapeutic efficacy, patient outcome efficacy, and societal efficacy (Table 1, Fig. 1). The model is hierarchical; achieving a given level of efficacy is often but not always contingent upon a demonstration of efficacy at the preceding level. As described in Fig. 1, levels 1–3 are necessarily contingent but beyond level 3, a genetic test can achieve therapeutic, patient outcome, and/or societal impact in ways that are contingent upon one another or independent of one another. We retain the levels of technical and diagnostic accuracy efficacy (i.e., levels 1 and 2) as essential starting points in our guiding framework as they are fundamental precursors to achieving clinical utility. However, since these laboratory-based components of efficacy are well-debated and described in the WGS literature and in recent guidelines published by members of our group27, we focus here on four levels of the efficacy model (i.e., levels 3–6) that align most directly with a broad definition of clinical utility and extend beyond laboratory-based components of efficacy. In emphasizing these four levels of efficacy as components of clinical utility, our intent is to encourage the use of a broad set of health and non-health-related indicators of value to bolster the state of evidence in this area, rather than to convey that all aspects of clinical utility need to be achieved for WGS adoption and reimbursement.

 

 

The time to stop recreational testing has come

 Direct-to-Consumer Genetic Testing: Value and Risk

Piecing together information from a variety of sources, one reporter concluded that by early 2019, more than 26 million people worldwide had been tested by the four leading companies, 23andMe, Ancestry, Gene By Gene, and MyHeritage (1). That volume was fueled by aggressive marketing, including discounts in the lead-up to major holidays to promote gifting of test kits. As of May 2020, the  undiscounted price of the basic test offered by the leading companies was $59–$99.

This is an example of what should not had happened. Recreative genomics doesn't add value and increases uncertainty and anxiety. 

Although many consumers of DTCgenetic testing express an intention to modify their lifestyle to address risk factors, studies typically show no changes at follow-up (15, 30). In the PGen Study, 59% of participants said that test results would influence their management of their health (31). However, an analysis of the 762 participants who had complete cancer-related data found that those who received elevated risk estimates were not significantly more likely to change lifestyle or engage in cancer screening than those who received average or below-average risk estimates (44). It may be relevant that no participants tested positive for pathogenic variants in highly penetrant cancer susceptibility genes. As for population health, the Centers for Disease Control and Prevention identify three conditions—hereditary breast and ovarian cancer syndrome,Lynch syndrome, and familial hypercholesterolemia—that are poorly ascertained despite the potential for early detection and intervention to significantly reduce morbidity and mortality (45). The hope is that DTC genetic testing could improve the situation (15). However,DTC genetic testing as currently carried out is likely to fill gaps in haphazard fashion, given the characteristics of purchasers, the scope of available products, and integration issues.

One message. Right now and until we don't know the implications of recreational genetic testing, direct to consumers testing should stop.

Banksy

 

The long and bumpy road to CRISPR (2)

 Editing Humanity. The CRISPR Revolution and the New Era of Genome Editing

In 2017 I wrote a post about the book by Jennifer Doudna, A Crack in Creation, now Kevin Davies, the editor of the CRISPR journal has published a new book on CRISPR. It is an effort to put all the information and details about CRISPR in one book. Therefore, if you want to now the whole story (or close to) this is the book to read. If you are interested in a general approach, then the Doudna book is better.

It is quite relevant the chapter that explains the role of Francis Mojica in CRISPR (chapter 3), and the chapter 18, on crossing the germline and what happened about the scandal of genome editing by JK.

“When science moves faster than moral understanding,” Harvard philosopher Michael Sandel wrote in 2004, “men and women struggle to articulate their own unease.” The genomic revolution has induced “a kind of moral vertigo.”49 That unease has been triggered numerous times before and after the genetic engineering revolution—the structure of the double helix, the solution of the genetic code, the recombinant DNA revolution, prenatal genetic diagnosis, embryonic stem cells, and the cloning of Dolly. “Test tube baby” was an epithet in many circles but five million IVF babies are an effective riposte to critics of assisted reproductive technology.

With CRISPR, history is repeating itself,

That's it, great book.

 

Cost-effectiveness of genome sequencing (3)

Application of next-generation sequencing to improve cancer management: A review of the clinical effectiveness and cost-effectiveness

Once again, there is no need for cost-effectiveness if there is not a clear message on the analytical validity, clinical validity and utility of a diagnostic test.
A new article want to shed light on cancer and NGS, and says:

Our search for cost‐effectiveness studies on NGS in cancer care yielded 2037 articles. Only 6 articles included cost‐effectiveness studies of the application of NGS (targeted gene panel) in cancer

The 6 selected reports could be separated into 2 types. Three of the articles assessed the cost‐effectiveness of recommending patients receiving targeted therapy matching their genetic mutation identified via NGS; and the remaining 3 articles assessed the cost‐effectiveness of using NGS as part of the screening program to direct patients or high risk family members into prophylactic treatment

Two out of 3 articles in the “targeted therapy” group reported that NGS and targeted therapy was not cost-effective (Table 3A), using an ICER threshold of US$100 000 per Quality Adjusted Life
Year (QALY) gained. An ICER of less than US$100 000/QALYs gained is generally considered favourable for funding in the United States

Two out of the 3 articles in the “screening” group reported that the use of NGS was cost‐effective (Table 3B), that is, under US$100 000 per QALY gained.loser surveillance.

 In our evaluation of the effectiveness of NGS, we found that NGS is effective at identifying mutations in cancer patients, and we reported that 37% of the diagnosed patients proceeded to receive therapy matching their genetic profile. However, with only 6 articles available that assess the cost-effectiveness of NGS in various settings, it remains an area for future research to determine whether the technology is cost-effective in routine cancer management

Summary: the message is that there is no message with such a few observations!


Something is being missed...

Guillem Roma and Marta Roma

Integrating genome and epigenome studies

The Key Role of Epigenetics in Human Disease Prevention and Mitigation

I've said it many times: beware of snake-oil sellers. Nowadays you may find it everywhere, specially on internet. You may get a genetic test for a disease that creates a false illusion of safety, or another that provides an unnecessary and avoidable concern. Only evidence based prescribed tests can be considered appropriate.
Therefore, if you want to confirm that genome is not enough, you have to check the review at NEJM on epigenetics. At the end of the article you'll find the explanation on why we do need integrated genome and epigenome association studies. You'll understand that cancer is fundamentally an epigenetic disease.
The current knowledge is changing quickly some conventional truths and "known unknowns" that we've had for years. This is good news for citizens, and bad news for snake-oil sellers if detected. Governments should help citizens on this screening effort, and protect citizens from fake medical information.

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.