L'assaig clínic mai vist per al cribratge del càncer

Li pregunto a Chat GPT sobre l'assaig clínic més gran en nombre de participants i em diu que és ASPREE, sobre l'aspirina i prevenció cardiovascular. I veig que Galleri, l'assaig clínic de GRAIL sobre cribratge de càncer al NHS hi ha 140.000 participants. I jo penso, això és molta gent i el Chat GPT4 no ho ha copsat. 

This is a trial in a large population in England to assess the performance and clinical utility of GRAIL’s multi-cancer early detection test when added to standard of care. Participants are randomized to either a test or control arm. The study teams remain blinded throughout the study. Participants who test positive will be referred for standard of care investigations and treatment in the National Health Service (NHS).

The study has enrolled approximately 140,000 people aged 50 to 77. Unless diagnosed with cancer, participants in both arms are asked to return for annual visits at approximately 12 and 24 months. All participants whether test positive, test negative or not tested will be followed for cancer and associated outcomes via linkage to NHS routine datasets.

Els detalls de l'assaig els trobareu aquí. I si voleu veure la validació, aquí. I mentrestant el regulador segueix pensant si autoritza la prova, resulta que ja es troba al mercat.

Health information, such as whether someone developed cancer and how it was treated, is collected from centrally held NHS records for up to 10 years after people’s first appointment. This allows the researchers to easily track people for whether they get cancer, even for people who may have moved home.

People who are diagnosed with cancer while they are taking part in the trial may not need to attend further trial appointments to give blood samples.

A quina data s'acaba l'assaig clínic no se sap del cert. Després de llegir tot això espero que se sàpiga quina és la sensibilitat i especificitat de la prova segons càncer detectat. Dic això perquè no he sabut veure com s'avaluen els falsos negatius, ni els falsos positius. I en un moment concret diuen que haurem d'esperar 10 anys. No ho sé, potser m'ha passat per alt.

Més detalls, aquí.

Mentrestant la Unió Europea ha prohibit la fusió Illumina-Grail, i ja veurem com acaba. Per ara els mesos passen i res de res...

Galleri, el test detecta (diuen) 50 tipus de càncer amb una gota de sang que cerca ADN circulant per 1.000€ (diuen, diuen).

Més d'un i més de dos volen saber si estem davant d'un nou cas Theranos, (jo vull pensar que no) i per això han començat aquest assaig clínic. A FT del dijous hi ha més detalls. I ho fan a UK perquè a Europa aquesta empresa hauria d'estar prohibida fins que no compleixi les resolucions de les autoritats.

Option value of healthcare technologies

 Broadening the Concept of Value: A Scoping Review on the Option Value of Medical Technologies

Key messages, 

Traditionally, cost-effectiveness analyses have been conducted from the payer perspective, although the question of whether they should be expanded to take a broader perspective continues to animate a lively debate. Lately, the attention has focused on wider components of benefits, including the so-called  option value. Our scoping review provides a comprehensive synthesis of conceptual and empirical aspects related to this topic recently introduced in the value assessment framework debate.

From a conceptual standpoint, the coexistence of 3 distinct definitions of option value in the literature emerging from our scoping review urges us to advocate for greater clarity of language in future research. We recommend using “insurance value” when referring to the utility of knowing that one may have access to a healthcare service should one need it in the future, as in definition A. Definition B mainly relates to decision making under uncertainty and specifically to the value of deferring uncertain unrecoverable decisions to a later time. In the evaluation of healthcare technologies and programs, this dimension of value originates from the possibility of delaying a reimbursement/adoption decision, if there is an expectation that better information on a technology’s (cost-) effectiveness will become  available in the future—for example, because a new clinical trial reports its results. Because this definition is rooted in financial options theory and its application to capital investment decisions, we recommend using the term “real option value,” consistently with the terminology used outside the healthcare sector 

According to the third definition, the claimed value does not originate from the uncertainty around a decision and the flexibility of deferring it, as in definition B, but rather it stems from the consideration that the value of a life-extending technology should also include the benefits of future treatments that otherwise would be precluded to patients if they did not benefit from improved survival. This definition of value pertains to the broader discussion on whether future costs and benefits not directly linked to the intervention being assessed should be accounted for when evaluating a technology.Therefore, we recommend that research related to this definition adopt the term “option value of survival.”

To date, no consensus has been reached yet

Les escaliers de la rue Chappe  à Montmartre.

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

Clinical utility of genetic testing for breast cancer

 Breast Cancer Risk Genes — Association Analysis in More than 113,000 Women

Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

However,

 We found strong evidence of an association with breast cancer risk (Bayesian false-discovery probability, <0.05) for protein-truncating variants in 9 genes, with a P value of less than 0.0001 for 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) and a P value of less than 0.05 for the other 4 genes (BARD1, RAD51C, RAD51D, and TP53).

  None of the other 25 genes in the panel had a Bayesian false-discovery probability of less than 0.10. Of note, 19 genes had an upper limit of the 95% confidence interval of the odds ratio of less than 2.0, with 2.0 representing a proposed threshold for “pathogenic, moderate risk alleles”9; we therefore conclude that these genes are not informative for the prediction of breast cancer risk. We confirmed that missense variants in BRCA1, BRCA2, and TP53 that would be classified as pathogenic according to clinical guidelines are indeed associated with clinically significant risks. We also found that rare missense variants in CHEK2 overall, as well as variants in specific domains in ATM, are associated with moderate risk.

The summary:

 Variants in 8 genes — BRCA1, BRCA2, PALB2, BARD1, RAD51C, RAD51D, ATM, and CHEK2 — had a significant association with breast cancer risk.

 

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.

 

 

Risks and benefits of self-testing (2)

 Direct to Consumer Testing: The Role of Laboratory Medicine

A specific issue on the topic has been released in Clinics in Laboratory Medicine. Inside the issue, you'll find this article: Direct-to-Consumer Tests on the Market Today: Identifying Valuable Tests from Those with Limited Utility 13. This is a key topic. It says:

Debate exists between the consumer and the health care provider when it comes to the value of direct-to-consumer (DTC) testing. At the heart of the issue is the observation that consumers are identifying value in DTC testing as evidenced by an expanding market, and health care providers are skeptical of their value from an analytical and clinical utility perspective. The aim of this article is to briefly review the subject of DTC testing with a specific focus on value from the perspective of the consumer and the health care provider.

 Paul Strand at KBr Barcelona

 

NGS: from research to clinical use

 Expanding Use of Clinical Genome Sequencing and the Need for More Data on Implementation

During the past 5 years, next-generation sequencing (NGS) has transitioned from research to clinical use.At least 14 countries have created initiatives to sequence large populations (eg, All of Us, Genomics England), and it is projected that more than 60 million people worldwide will have their genome  sequenced by 2025.

If this is so,

 Understanding how NGS is being used and paid for is critical for determining its clinical and economic benefits and addressing current and future challenges to appropriate implementation.

 Without consistent information on clinical utility and how NGS tests are implemented in clinical care, it is not possible to develop an understanding of benefits and harms associated with NGS. It is not always the case that evidence of clinical utility leads to improved outcomes, and evidence about implementation is required to complete the assessment of the effects on population health. Implementation science is intended to support the integration of findings from scientific evidence to uptake in routine clinical care in the ongoing cycle of a learning health care system.

This is clearly a call for action. However, in my country the call is for both developing NGS  (nothing has started) and asessing implementation. Is there anybody in the room?

Hockney

To test or not to test (for coronavirus) (2)

Escaping epidemics through migration? Quarantine measures under incomplete

information about infection risk

Some days ago I was explaining the rationale for coronavirus testing regarding clinical decision making. However, as we all know, individual behavior is also capable to produce health and disease contagion. Therefore, in case of coronavirus, behavioral externalities are crucial and nowadays we have denominated them "social distancing". 

Having said that, there is an additional behavioral value from testing to take into account. If all individuals in a population have access to the test, maybe everybody is aware of social distancing than in a situation than only suspected cases receive the test. Behaviors may change, and quarantine strategies more successful. In such situation it is much more feasible to restrict mobility. Let's take for example what this article explains:

This paper studies the effect of public policies to restrict migration by individuals suspected of carrying disease, when those individuals do not know for certain whether they have the disease but may have more information than the authorities about their probability of being carriers. It has long been known that migration affects the spread of
disease, and this influence has for centuries been used to justify placing restrictions on the movement of individuals suspected of carrying infections.

 Epidemiological studies have addressed how individual behaviour, among other factors, affects the spread of infections. However, the study of how individual behaviour in turn
changes in response to the new incentives created by the occurrence of a disease is much less developed. The principal contribution of our paper is to bring the study of strategic behavior under uncertainty into the domain of epidemiology, and to analyze its impact, in interaction with public policies, on the overall impact of epidemic disease.

Migration as a form of preventive behaviour has received very little attention, although evidence has accumulated that migration behaviour and epidemics are intrinsically linked. Migration behaviour can respond very rapidly to changes in the health  environment, in particular when it suddenly deteriorates through epidemics.

In our model we show that:
• First, when the disease is concentrated in one place (the epicentre of an epidemic for instance), a decision to migrate away from the epicentre brings a potentially infected individual in contact with more uninfected individuals than she would have met had she
remained where she was. Thus the typical migrant imposes a net negative externality as a result of her decision to migrate, and the marginal migrant (for whom, by definition, private benefits of migrating just equal the private costs of doing so) has a negative
impact on social welfare. Laissez faire will therefore lead to excessive migration. This provides a rationale for the frequent (and frequently justified) public policy response to epidemics, which is to attempt to restrict migration away from the epicentre by those who may be infected.
• Secondly, and less obviously, not all policies that aim to restrict migration in fact do so. In particular, we distinguish two effects of quarantine policies. The first is that they raise migration costs, which lowers migration. For example, mandatory health certificates or test results may be required by health authorities to leave the epicentre of the disease.We call this a “type 1” effect of quarantine measures. The second effect is that they impose a utility cost on individuals of remaining in the city where quarantine measures are effective, since they face a chance of being subjected to awkward and possibly
dangerous restrictions on their movements. We call this a “type 2” effect of quarantine measures. Such measures impose a welfare cost on those who suffer them, which tends to increase migration by those who are not currently subject to quarantine but fear they may  become so if they remain where they are. Policies implemented without taking type 2 effects into account may therefore have results that are opposite from those intended.
• Thirdly, even policies that actually reduce migration may have an adverse impact on social welfare if they reduce migration “too much”, and specifically if they discourage those intra-marginal migrants whose private benefits from migration substantially
exceed their private costs of migration, by enough to outweigh the negative externality they impose on others. Overall disease prevalence may even increase if in the name of avoiding negative externalities the authorities discourage relatively low-risk individuals
from escaping the epicentre of the disease, thereby increasing the probability that they will catch the disease there from infected individuals.

When people have imperfect information about their own infection status, migration imposes net negative externalities by increasing the rate of exposure faced by the uninfected outside the epicentre of the epidemic. In and of itself, this our paper has highlighted the fact that although quarantine of individuals who have been identified as sick reduces (obviously) the propensity of these individuals to migrate and spread the disease, the threat of quarantine increases the propensity to migrate of other individuals who have not yet been fallen sick but who know themselves to be at risk.

Quarantine measures have all these effects. However, if information about contagion is confirmed, then behaviors may change, and mandatory health certificates can be issued. The case of the italian village of Vò confirms that population screening has been successful in stopping the outbreak. This could have been done at the beginning if diagnostics kits had been available. Right now it seems an unfeasible strategy. We know now that there is a behavioral value of test information, beyond the clinical value. And in the case of coronavirus, confirmatory tests provide only partial information. In case of non infection, incubation period is uncertain, and some days after can be confirmed. Therefore, quarantine measures have to be mandatory and strict for the whole population and for specific areas.

To test or not to test (for coronavirus)

A Framework for Comprehensive Assessment of the Value of Diagnostic Test

The Value of Diagnostic Information A comprehensive concept of “Value” for diagnostics

A framework to understand value of lab tests is the following one:

Key principles:

• Apply broad array of patient centric value drivers from various perspectives (Comprehensiveness principle)
• Utilize appropriate range of available evidence, reflecting test type and potential risks-benefits (Evidentiary principle)
• Consider reporting direct and indirect costs incurred and avoided over timeframe appropriate for the test (Cost principle)
• Account for immediate and longer-term test impact and patient benefits in representative patient populations (Specificity principle)
• Include quantified estimates as well as qualitative analyses as appropriate (Flexibility principle)
• Incorporate multiple stakeholders’ perspectives (Engagement principle)
• Disclose why the assessment was initiated, who was involved, its purpose, and the decision-making process (Transparency principle)
• Update assessments regularly to keep up with the rapid technological and clinical changes (Relevancy principles)

 Value drivers can come from four major sources:

• Clinical impact: clinical utility and health outcomes associated with the diagnostic technology. The test needs to measure accurately and reliably the analyte/biomarker of interest (analytical validity); detect, predict the outcomes of interest in a patient population (clinical validity) and inform an appropriate clinical decision (clinical utility). Improved patient safety, tolerability, compliance and physical and psychological wellbeing shall be also taken into account.
• Non clinical patient impact breaks down to patient experience, and patient economics, such as proximity of test delivery, reduced follow-up visits, repeat procedures, improved care plan compliance and reduced burden on care givers.
• Care delivery revenue, and cost impact mostly refer to quality of care metrics and more efficient resource utilization (e.g. readmissions; follow-ups, length of stay, wait times)
• Public and population impact refer to macro implications mainly from population health, burden of disease, patient and caregiver productivity perspectives

AdvaMedDx’s Approach for Effective Value Assessment

Source: A Framework for Comprehensive Assessment of the Value of Diagnostic Tests, AdvaMed, 2017

And clinical impact depends on analytical validity, clinical validity, clinical utility, patient safety and patient response. If you have only one strategy for all the patients, like social distancing in the case of coronavirus, then the information post-test will not change the therapeutic strategy. If the test tries to prevent contagion when social distancing can't be applied (health professionals, politicians, journalists, executives, essential services), than you have to test them if there are symptoms. If the test will add information to existing comorbidities to differentiate from other symptoms, then it makes sense. Therefore, this is the current situation in my country. Test, test, test when it adds value.

Improving the pharmaceutical regulation production function

Using Routinely Collected Data to Inform Pharmaceutical Policies

With the broadening of data available for officials to regulate markets, things could change. The issue is specially relevant for pharmaceuticals. Up to now if you want information about the market you have to use IMS data. Now governments that pay the drugs bill can use their own data to improve regulation. Better knowledge could represent better regulation if it is performed appropriately and on a timely basis. The OECD report tries to put all these elements together and highlight the opportunities ahead.

This report provides an overview of patient-level data on medicines routinely collected in health systems from administrative sources, e.g. pharmacy records, electronic health records and insurance claims. In total 26 OECD and EU member countries responded to a survey addressing the availability and accessibility of routinely collected data on medicines and their applicability to developing evidence. The report further explores the utility of evidence from clinical practice, looking at experiences and initiatives across the OECD and EU.

Governments will have to improve big data capabilities and add new talent.

Sorolla right now in London

Genome sequencing, what's it worth?

Evaluating the Outcomes Associated with Genomic Sequencing: A Roadmap for Future Research

The health economic evidence base for WES -whole exome sequencing- and WGS -whole genome sequencing- is very limited . A recent literature review identified just eight economic evaluations of either WGS or WES, six of which were cost-effectiveness analyses using diagnostic yield as the outcome measure. Only two publications presented cost-utility analyses using quality-adjusted life-years (QALYs) as the measure of health outcomes, as recommended by most health technology assessment (HTA) agencies. However, neither of these cost-utility analyses provides information on health outcomes that HTA agencies can use to inform the translation of NGS technologies into clinical practice for specific disorders.

Last May I wrote a post on this topic. Now James Buchanan and Sarah Wordsworth provide a roadmap for future research with three steps.

First, it is crucial that health economists generate evidence on the clinical utility of genomic sequencing using the methods and metrics that are recommended by HTA agencies. Here, we are primarily referring to the use of preference-based HRQoL instruments such as EQ-5D questionnaires to generate utility weights that can be used to calculate QALYs 

If there is reason to believe that patient wellbeing will change after undergoing genomic sequencing (for example, supportive qualitative evidence), but commonly used HRQoL instruments show no effect, a second step would be to explore the use of alternative health-state valuation techniques to generate utility weights within the QALY framework. The time-trade-off (TTO) technique is one such approach

A third step would be to make full use of existing evidence on the diagnostic yield of WGS and WES. Studies that link this evidence to patient survival and quality of life (for example, trials or observational studies with long-term follow-up), could inform decision making regarding the translation of these technologies into clinical practice.

Unfortunately, it is easier said than done. I'm dubious regarding the potential of QALYs on assessing value of such technology, despite I have no alternative solutions right now.

Exhibition at Saatchi gallery

Clinical utility of genomic sequencing

The Path to Routine Genomic Screening in Health Care

Now that whole genome sequencing is knocking at the door of the clinician, it is the time to ask for clinical utility. The understanding of how such information will change diagnostic and therapy is paramount. There is still no need for cost-effectiveness, clinical utility comes first.
And the editorial at Annals explains exactly this issue, highly recommended:

There should be little doubt that individually tailored health care management plans based on DNA analysis are coming, but the timing of their introduction into routine clinical care is contingent on further demonstrations of clinical utility and proven implementation models.

My impression: let's wait for epigenetic biomarkers, beyond whole genome sequencing that provides less than 100 actionable genes out of 20.000. Though,

 The fact that only a small percentage of people would benefit from GS today is counterbalanced by growing evidence that the benefit could be significant, and perhaps even life saving

 

Pepe Castellanos at Barnadas Gallery

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

Cost-effectiveness of genome sequencing

Are whole-exome and whole-genome sequencing approaches cost-effective? A systematic review of the literature

It is quite difficult to talk about value in genetic tests without any reference to analytical validity, clinical validity and clinical utility. Once these three issues are appropriately solved, then we need to assess costs. Cost effectivenes makes sense once this three steps are covered successfully.
An analysis of cost-effectiveness of whole genome/exome sequencing it sounds too generic if there is no reference to specific baseline that allows to estimate incremental cost-effectiveness ratios.
That's the reason why a recent article trying to review existing studies fails to achieve any conclusion.

The current health economic evidence base to support the more widespread use of WES and WGS in clinical practice is very limited. Studies that carefully evaluate the costs,
effectiveness, and cost-effectiveness of these tests are urgently needed to support their translation into clinical practice.

 Let's start focusing on the assessment of three key perspectives before entering into a black hole.

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

A new missed opportunity

After all these years, a new proposal for regulating in vitro diagnostics and medical devices in EU is available. Current regulation was enacted in 1998, and this one could be applicable in 2022, 24 years after, pas mal for the busy politicians!.
And this is a proposal, there were previous unapproved proposals, and this one has to pass the Council and the Parliament. I will not enter into the details.
It was supposed to increase safety and efficacy, but the main problem remains with who has to enforce them. Notified bodies, a subcontracting regulatory firms network, with vested interests with industry can't claim independence. And specifically, the methods for evaluate the analytical validity, clinical validity and utility is uncertain. No regulator will confirm us that the cut-off values of diagnostic tests are set according to the best evidence and greatest benefit. In US, FDA is the responsible.
In summary, a new missed opportunity for european citizens. A greater risk and uncertain effectiveness in diagnostic tests and medical devices.

PS. The latest known example of the impact of wrong regulation is this one. Those affected can't read this blog, they are blind.

Josep Moscardó

What clinicians do and why they do it

The Nature of Clinical Medicine. The return of the clinician

Nowadays, technology pervades media and our live. This is a good moment to rethink the basics, the foundations of medicine, its values and goals. Eric Cassell contributes decisively to this aim with his new book, a must read at least for physicians and all professionals related with medicine.
Health economists should be aware of better understanding  about the goals of medicine and purposes of physicians. They reflect the true "production function".
Here is a brief summary of the book and afterwards its goals and purposes:

Clinical medicine, as a thinking discipline, is concerned not only with what clinicians do, but why. When physicians act in medicine they have some purpose or goal in mind. What they actually do and how they go about it is in the service of their purposes and their goals. Such goals cover a wide range of topics centering on patients, the doctor-patient relationship, the acts of doctoring patients, and the goals involved in being a physician among other physicians working within the institutions of medicine.

The Nature of Clinical Medicine takes its direction from a catalog of goals of medicine that range from the expected diagnosis and treatment of diseases to wider concerns for patients, for physicians, and for medicine itself. The chapters are specific in teaching the kinds of knowledge that clinicians require in order to be able to achieve these goals. The central focus of the clinician and of this book is the patient. According to Eric Cassell, everything else, including the disease, is secondary.

Summary of the Goals of Medicine

A. Patient-centered goals

1. Save life.
2. Prolong life.
3. Cure disease.
4. Prevent suffering.
5. Relieve suffering.
6. Do no harm.
7. Protect the patient from danger.
8. Do not frighten the patient.
9. Relieve the patient’s fears.
10. Make the patient better in the patient’s terms.
11. Do nothing unnecessary (or more than necessary). B. Goals related to the physician–patient relationship
12. Develop and maintain a good relationship.
13. Be trustworthy.
14. Tell the truth.
15. Be reliable.
16. Be constant.
17. Be there when needed.
18. Make a difference.

C. Goals related directly to doctoring the patient

19. Make a diagnosis (where pertinent make a tissue diagnosis).
20. Decide what the problem is.
21. Obtain the necessary information.
22. Make sense of the case (in pathophysiological, anatomical, psychological, and social terms).
23. Decide the correct treatment and its timing.

D. Goals related to being a physician among other physicians

24. Seek and maintain comprehensive knowledge.
25. Maintain the standards of medicine.
26. See that things are done right.
27. Protect the patient from bad medicine and incompetent physicians.
28. Behave in a proper, doctorly manner.
29. Look good to other physicians and the patient and family.
30. Avoid error.
31. Avoid blame.
32. Maintain relationships with peers.
33. Stay alive in the institution (hospital or medical school) and community

The relationship between purposes or goals and values (p.166). Five kind of goals:

1. Specific obligations to other people or institutions—patients, other caregivers, or the hospital
2. Responses to rights that everybody has, for example, the right to refuse treatment, or to freedom from assault or coercion.
3. Purposes based in what might be called utility. Things pursued because of the benefit to the patient, or the avoidance of injury. Also purposes directed at general benefit, like the advance of medical knowledge.
4. Purposes related to what might be called self-development values. Here, there is intrinsic value in acquiring a particular piece of knowledge or skill because it is believed to be part of the general good if even one person has special knowledge. The goal of acquiring a particular knowledge or ability lies in this arena of values.
5. Purposes related to one’s own project in life, like becoming a good clinician apart from, for example, the acquisition of a specific skill  or the general advance of medical knowledge

Genetic testing: a knotty problem

Food and Drug Administration. Optimizing FDA's regulatory oversight of next generation sequencing diagnostic tests — preliminary discussion paper

Cutting the Gordian Helix — Regulating Genomic Testing in the Era of Precision Medicine

"Scientific progress alone won't guarantee that the public reaps the full benefits of precision medicine, an achievement that will also require advancing the nation's regulatory frameworks"

This strong statement reflects a wider concern on the implementation of precision medicine or stratified medicine. I have commented before on this issue, the NEJM article of this week clarifies the last attempt by FDA to shed some light and a specific approach to disentangle the current challenges. FDA has submitted a document for comments just to start a new era of regulation in health, a "collaborative framework" for creating reliable databases of genes and genetic variants underlying disease, and provide a "safe harbor" for the interpretation of genomic tests.
This is exactly the right direction. As long as, information is a public good, genetic testing -clinical validity and utility- should be provided only by the regulator.  Professionals and citizens need to trust in precision medicine and avoid snake-oil sellers.
Having said that, today I'm more concerned than yesterday on how our government is delaying to start such effort. Today is one more day lost.

Dufy at Thyssen Museum right now

PS. Somebody should think twice about the style of health policy debates in public TV.

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.

Enough is enough

If there is a grey area in medical devices and services regulation, this is the Laboratory Developed Tests one. Up to now, FDA has refused to define the rules of the game for 11,000 diagnostic tests performed at 2,000 labs in USA. This means that no official or external reviewer has analysed the clinical validity and clinical utility as it is done in any reagent and instrument. I can't understand why we have arrived at such a situation.
Fortunately NYT reports that on July 31st, FDA announced that this will change.

The agency said on Thursday that such discretion must end because circumstances had changed. Lab-developed tests once were fairly simple, often developed by a hospital for tests on its own patients. Now the tests can be complex and are being developed by  companies and marketed widely.

Some widely used commercial tests have never had to be reviewed by the agency. These include Myriad Genetics’ breast cancer risk test, the subject of a Supreme Court patent decision last year; the Oncotype DX test from Genomic Health, which is used to determine if women with early-stage breast cancer need chemotherapy; and noninvasive prenatal tests for Down syndrome that are rapidly catching on.

In this blog I have supported several times for a clear regulation of these tests . Just the other day when looking at the statements of FDA commissioner, I was astonished:

Just as drugs need to be safe and effective for treating diseases, medical devices used to help diagnose disease and direct therapy also need to be safe and effective, Faulty test results could lead patients to seek unnecessary treatment or to delay or to forgo treatment altogether.

These statement raise more concerns about what US regulator has done after all these years. And european regulation is still worse in this sense. I have explained such disaster previously and up to now there is no news. Some times I wonder why do we pay taxes, why do we have to be part of Europe. Enough is enough.