Changing the production function of diagnostic tests

Next-generation diagnostics with CRISPR

Last week while reading Science I noticed a short and crucial article. Up to now CRISPR technology was focused on gene editing, now we can say that its usefulness is widening into diagnostics. It may change completely molecular diagnostics of "infectious diseases through detection of Zika virus (ZIKV), Dengue virus (DENV), and human papillomavirus (HPV) in human  samples, and noninfectious diseases, such as detection of gene mutations in circulating cell-free DNA from lung cancer patients." The production founction of lab testing would change completely.
Several articles explain details about it. The fight for patents is going to start again on CRISPR diagnostics. And this are unfortunately bad news.
Anyway, Science article reminds us:

These emerging diagnostic tools will by necessity be compared to standard diagnostics to ensure sensitivity and specificity and will need to be field-tested to guarantee performance in patient care settings, as environmental conditions and end-user application might affect performance. Proven assays, if affordable, promise to improve care in resource-limited settings where undifferentiated febrile illness is the norm and where gaps or delays in diagnosis, targeted care, and infection control contribute to infectious disease mortality and spread.

More details in The Verge.

Cost-effectiveness of genome sequencing (2)

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

If you want to go deeper on the issue, have a look at this article. It is focused on one disease, cancer and tries to combine clinical effectiveness and cost effectiveness. Sounds good. At the end you'll see that the number of available studies is limited (6), but that's the situation and these are the conclusions:

We report the rate of successfully detecting mutations from the clinical studies. The incremental cost-effectiveness ratio and sensitivity analysis outcomes are reported for the cost-effectiveness articles. Fifty-six articles reported that sequencing patient samples using targeted gene panels, and 83% of the successfully sequenced patients harboured at least 1 mutation.

 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.

PS. Today this blog has surpassed its 200.000 visits. That's great! Thank you for your loyalty.

Sally Mann, On the Maury, 1992, gelatin silver print, Private collection.

Washington National Gallery, current exhibition

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.

Diagnosing diseases and editing genes

CRISPR: The gene-editing tool revolutionizing biomedical research
The WIRED Guide to Crispr
A New Startup Wants to Use Crispr to Diagnose Disease

Take your time and read Wired and watch CBSNews. It will provide an exciting perspective of CRISPR. And just to end, imagine that diagnostic tests could be based on CRISPR while you read the last piece of WIRED.
We are closer than you may think.

Mental health: the problem and what can be done

THRIVE: How Better Mental Health Care Transforms Lives and Saves Money

I have to recognise it. Mental health is a difficult issue, and all the efforts to decrease its impact on individual and social welfare are not enough by now. The book by Layard and Clark is a useful reference. I had to read it since long time. It says:

Mental illness is the great hidden problem in our societies, so most people are amazed when they hear the scale of it. In the Western world today one in six of all adults suffers from depression or a crippling anxiety disorder. Roughly a third of households currently include someone who is mentally ill.

I don't know the exact figure, but I agree with the statement.

Mental illness is not just a problem for those it affects directly. It also imposes huge costs on the rest of society. So the case for tackling the problem is not just humanitarian—it is also a matter of plain economics. Mental health problems diminish work, increase crime, and make additional demands on physical health care.

So, what is the cost? The answer is huge. Layard and Clark provide some figures. And in the second part of the book, they review the alternative approaches to the issue. A highly recommended book by one of the greatest economists of our time.

PS Great Tribute to Uwe Reinhardt in NYT by Paul Krugman.

Medicine as a data science (2)

The Evolution of Patient Diagnosis: From Art to Digital Data-Driven Science

Currently medical diagnosis is driven by a standard way to proceed. We could say that the pattern of the decision flow has not changed for years.

A physician takes a history, performs an examination, and matches each patient to the traditional taxonomy of medical conditions. Symptoms, signs, family history, and laboratory reports are interpreted in light of clinical experience and scholarly interpretation of the medical literature.

Data availability, and specifically genetic data could change completely diagnostic process.

Initiatives to develop genetic reference data at the population level could be grouped into 3 categories.First are well-known databases of genotype-phenotype relationships
as observed and submitted by researchers (eg, Online Mendelian Inheritance in Man, ClinVar, and the National Human Genome Research Institute’s Genome-Wide Association Study [GWAS] Catalog). Second are databases, such as the Genome Aggregation Database (gnomAD), the next iteration of the ExomeAggregation Consortium (ExAC) database, and the 1000 Genomes Project, that aggregate sequences
collected from other studies for secondary use. Third, patients and other study participants are invited to donate data to registries like GenomeConnect or enroll
in cohorts like the National Institutes of Health All of Us initiative, which is recruiting 1 million patients to contribute biological samples and EHR data for research.

The reference to these databases is crucial to understand what's going on in US medicine, and how european medicine stands behind.
JAMA article develops the concept of Clinical Information Commons:

There should be a new compact between patients and the health system, such that captured data and biospecimen by- products of the care deliverysystem should be aggregated and linked to build a clinical information commons (CIC) to aid diagnosis

I agree. Saluscoop started as an alternative focused in this approach. As usual, the big question is: who is going to invest in a digital commons?. Unless governments take this initiative as a whole, the future of a data driven medicine is uncertain.

Adrian Piper: A Synthesis of Intuitions, 1965–2016

MoMA, New York, New York

Sat 31 Mar 2018 to Sun 22 Jul 2018

Equity and QALYs, terra ignota

Incorporating equity in economic evaluations: a multi-attribute equity state approach

Ptolemy used the term terra ignota for regions that have not been mapped or documented. QALYs were born for maximizing health, without any distributive considerations. All the efforts to introduce equity in QALYs have failed up to now. The cartography of QALYs has a pending dimension.
Maybe this dimension is not possible to be defined under a technical perspective, its a societal and policy issue. And at this level decisions are difficult to take.
Anyway, after reading this article you may reach a similar conclusion than mine, or otherwise you can be optimistic about it. It's up to you.

PS. Today I'll give the kenote speech at Col.legi d'Economistes de Catalunya: "La producció eficient i equitativa de salut".

Ai Weiwei

DROPPING A HAN DYNASTY URN

Man and machine, sharing the decision making effort

Big Data and Machine Learning in Health Care

From JAMA article

It is perhaps more useful to imagine an algorithm as existing along a continuum between fully human-guided vs fully machine-guided data analysis. To understand the degree to which a predictive or diagnostic algorithm can said to be an instance of machine learning requires understanding how much of its structure or parameters were predetermined by humans. The trade-off between human specification of a predictive algorithm’s properties vs learning those properties from data is what is known as the machine learning spectrum

 Higher placement on the machine learning spectrum does not imply superiority, because different tasks require different levels of human involvement. While algorithms high on the spectrum are often very flexible and can learn many tasks, they are often uninterpretable and function mostly as “black boxes.” In contrast, algorithms lower on the spectrum often produce outputs that are easier for humans to understand and interpret.

The meta-informational challenge of molecular data

The future of DNA sequencing

Where does DNA sequencing goes from here?. Nowadays, this is an appropriate question to pose.  The answer appears in an article in an interesting article in Nature.

Now, geneticists would like to have DNA sequences for everyone on Earth, and from every cell in every tissue at every developmental stage (including epigenetic modifications), in health and in disease. They would also like to get comprehensive gene-expression patterns by sequencing the complementary DNA copies of messenger RNA molecules.

In a mere 40 years, the central goal of putting molecular data about cells to practical use has changed from an informational challenge to a meta-informational one. Take clinical applications of genome-sequence data. It may soon be possible to use DNA sequencing routinely to analyse body fluids obtained for any clinical purpose. But only a vast amount of well-organized data about the multi-year medical histories of millions of people will provide the meta-information needed to establish when to ignore such data and when to act on them.

The uncertain cost of clinical trials

How much do clinical trials cost?

A research on seven top pharmaceutical companies has provided fresh data about costs of clinical trials:

For the trials in the data set, the median cost of conducting a study from protocol approval to final clinical trial report was US$3.4 million for phase I trials involving patients, $8.6 million for phase II trials and $21.4 million for phase III trials.

If you compare these data with the total drug costs (2.6 billion), you may ask yourself how all these costs are estimated. Maybe all this information is wrong and useless.

PS. Waiting for the new book on Theranos scandal

Pharma sales 2017

Kupka au Grand Palais

Why is it so difficult to implement policies?

Governance and the Law

If you want to know an updated approach to policy reforms, then you have to read the World Development Report 2017
The main messages:

• Successful reforms are not just about “best practice.” To be effective, policies must guarantee credible commitment, support coordination, and promote cooperation.
• Power asymmetries can undermine policy effectiveness. The unequal distribution of power in the policy arena can lead to exclusion, capture, and clientelism.
• Change is possible. Elites, citizens, and international actors can promote change by shifting incentives, reshaping preferences and beliefs, and enhancing the contestability of the decision making process.
• Three guiding principles for rethinking governance for development are:
• Think not only about the form of institutions, but also about their functions.
• Think not only about capacity building, but also about power asymmetries.
• Think not only about the rule of law, but also about the role of law

You'll understand that the key element of any reform goes beyond evidence on what works and consensus. It should be clearly designed following specific steps. I suggest you have a look at it.

El gran Guillem Roma amb Alessio Arena

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.

Practice makes perfect (2)

The Volume–Outcome Relationship Revisited: Practice Indeed Makes Perfect

Why is it so difficult to accept it? There is wide "evidence for the practice-makes-perfect hypothesis by showing that volume is a driving factor for quality". Unfortunately, the opportunities for the health system are still larger than it should be. There is a resistance in organizations, there is inertia, and all these drivers play a role. In planned health systems, there is no reason to be strict on it.
Just for those that are dubious, I would suggest a look at this article and to my former post.

Parov Stelar

The smart money in tech would not have made this mistake

It's about Theranos. You may find my previous posts in this link. Now SEC has confirmed that was a "massive fraud". That's it. If you want a good analysis check FT.
Microfluidics is not an easy prêt-à-porter technology. Many people knew it but Mrs Holmes has been selling it as snake-oil. And as usual in these cases, the end of the film is already written. She can't go to the lab for the next 10 years, a fine, and the company may be closed. All started with and article by Mathew Herper in WSJ. An innocent article with an innocent question that she couldn't answer. That's all. Silicon valley smart money would not have made this mistake.

Modigliani exhibition in Tate Gallery now