The Martian: How much is a person worth?

The Martian: How much is a person worth?

Recently,  I saw The Martian, a movie about a man accidentally abandoned on Mars.  The movie is about the struggle for survival, the marshaling of forces to allow the survival of that one man,  the sacrifice of  compatriots and the politics of rescue .  

Cancer patients, and the people who care for them, can feel like they are abandoned on Mars. The feelings elicited by this movie are similar to those we, who care for cancer patient patients feel. When do we call the situation hopeless?  When do we give up?  How much can we put into the effort for one patient?  How much can we spend?

In the movie there is no limit. Billions of dollars are spent,  scores  of people work without rest, people give up years, in the prime of their lives, to attempt to rescue a single man.  In our real, medical world the money, the time, the energy are all limited,  The resources are shared by thousands of patients. This places every part of the medical system in the position of distributing a limited, precious resource.  The doctor must balance the chance of benefiting the patient against the cost to the system, which could mean denying another patient an equal or better chance.  Doctors differ in their approach to this problem.

How can we do any less than our best?   Our efforts are not like those in the movie.  They are not as good as they should be.. The basis for saving the Martian was adoption of a nonstandard strategy, a strategy that would work, in theory, but was not a usual approach.  A methodology that involved unanticipated expense and sacrifice.

Currently, the pressure to follow standard procedures is almost overwhelming.  Deviation from such standards  risks the label of malpractice.  Obtaining insurance coverage for a treatment that is not recommended in guidelines, or for a problem that deviates from the FDA  approval parameters is a Herculean task - and getting harder.  .

Knowledge and Resources are always limited. The Martian was rescued, he beat  the odds. It is very expensive and difficult to take on the odds... sometimes it works.

A better way to treat cancer patients

There is a better way to treat cancer patients

I am a practitioner of oncology.  When I am confronted with a treatment decision, I attempt to bring the best data to bear on the subject. I avail myself of resources: online text books, PubMed, Web of Science, Clinicaltrials.gov, Eviti advisor. I try to gather and compare  the options  I very much want to see which option will help my patient best (longest lasting, least toxic, most likely to be effective).

But the medical literature does not allow me access to detailed information.  It tells me the outcomes of large groups of patients, diverse in the details of their disease, expressed as probabilities over the whole group and sometimes subgroups, defined by the authors ,that are usually not helpful.  I think that the details may direct the treatment; but details are not available.

Instead of selecting patients who are suitable for clinical trials, we should be constantly improving our treatment, we should be using an iterative correction model,

Patients should be encouraged to consent to have  information that could be related to their disease and its treatment, stored and available for real-time analysis. The data should include a great depth of detail,   Every time a patient comes for treatment we should check the current,  updated  outcome  for that treatment in patients that are most similar to the one we propose to treat. That information should correct our initial proposal.  Once a final decision is made, that patients course becomes part of the growing, searchable and expandable database.  That patients course becomes part of the decision for the  next patient.

There are problems: privacy, accuracy, validity. These problems are the subject of current research [1]

This is a call  for revolution in how clinical data is reported and accessed. I want a  database of raw data, available for appropriate analysis along parameters relevant to  the patient at hand.  I would like to be able to collect information on patient's who are similar to the patient under my care.   The similarities would be defined by the current and emerging understanding of the disease and its treatment. 

The technology exists to start such a program.  As more as learned, the program will improve  Internet service providers already follow this model and the effectiveness of that effort is reflected in the fact that people pay for it and profit from it.  That same process should be used to help save lives.

Paradigm Shift in Genomics

The presumption  had been that the  genomic defects in cancer, revealed by sequencing data, would identify targets for treatment.  By virtue of the specificity of these targets, treatment would be more effective and less toxic. In a few situations, this has happened. The EGFR , ALK  ROS genes of lung cancer, the B RAF of melanoma, HEr2 in breast and esophageal, abl in chronic myelogenous leukemia are examples of the success of this approach ( N.B. all antedate widespread next generation sequencing.)  The estrogen receptor of breast cancers  and the androgen receptor of prostate cancers are therapy targets that are not correlated with sequencing data.

I do not want to be overly cynical about the value of sequencing.  The the technique, as clinical art and science, has not matured.  Development often  produces surprises.  When the surprise  leads to  a broader model, the  original idea needs to be placed in the new perspective.

Recent discoveries have broadened the meaning of  NG sequenced data.  Rivzi, et al  have shown that response to immunomodulatory, PD-1, directed therapy correlates with overall mutational burden. A tumor in which a large number of mutations is identified by NG sequencing tends to respond more favorably to an agent ( monclonal antibody) that blocks an "off switch" for immune reaction ( PD-1).   It is the mutable tendency, not the actual mutation that determines responsiveness to this (class of) agent(s).  The observations of Le, et al, that mismatch repair, a phenotype that would be expected to increase the mutation rate, signals sensitivity of cancers to  PD-1 blockade seems to be a complementary  finding.

These findings imply that the mechanism underlying the cancer, tolerance of mutation, rather than the mutations themselves,  can be a target for treatment.  This particular mechanism also intimates that the immunologic treatment will eventually fail since mutations will continue to occur, and be tolerated.  in the malignant cell population.

The utility of PARP inhibitors in BRCA and PALB2 mutated tumors is a corollary to these ideas.  The PARP inhibitors target the mechanism of mutational generation in these selected cases.

Understanding optimizes hope

The practical use of clinical trials

Clinical trials are very expensive.  Current funding from the NIH for clinical trials is : $7,327,474,432 (7 billion dollars) I do not think we are getting our money's worth.

When I treat a patient, I want to know the best treatment for my patient, not the best treatment for a population of patients who have (what the trialists have called) the same disease, and who fit the criteria for the trial ( i.e. no other major problems). I need to optimize the outcome of the patient as I see her.  But the reporting of clinical trials obscures the information I need to make the best decision. The details are sacrificed to an illusion of statistical accuracy.

I have a patient who was treated for "multple myeloma."  He has the characteristic abnormal antibody product ( monoclonal spike) resulting from a cancer of plasma cells( the immune cells that produce antibodies),  Chromosome analysis   demonstrates a translocation (4;14)  This chromosomal abnormality identifies a disease that has an inferior outcome with (old) standard therapy.   There is evidence that newer treatment  ( boretzimib)  produces a better outcome.  The patient had standard therapy including a stem cell   (autologous) transplant.  What should the mainteneane therapy be?

The studes demonstrate an advatage for mainetenace therapy,  But the results are expressed without regard to the chromosomal abnormality. At best, this chromosomal abnormality is lumped with others that define "risk"  But risk is a function of treatment!.  To make maters worse, the risk classification of his chromosomal abnormality varies among authors!  Some call it high, other intermediate.

If the raw  data were available, if the clinician could aggregate and analize the raw data, and then submit the data on his patient into the pool, we would have afar more efficient and productive  process.  Instead of basing decisions upon random data, we would base decisions upon outcomes that were also based upon constant correction,  The search for optimization would be  organic, ever improving.. Conceptually this approaches grows out of Bayes ( using the pretest assumption)  and Hayek ( the wisdom of the market).   This is an optimization algorithm,  Why shouldn't each successive treatment attempt be corrected for the past treatment attempts? 

targets and genes

 The purpose of the medical enterprise is to improve the life of the patient. The process is diagnosis and treatment.  Diagnosis should steer the case toward the most beneficial treatment.  Even when the diagnosis identifies a condition for which no effective treatment is known, an accurate diagnosis is very beneficial, allowing  the avoidance of ineffective therapy and redirecting the situation. 

The nature of diagnosis is  evolving. We have long  gone beyond the era  of the  hematoxylin - eosin stained  specimens. Almost every biopsy is now analyzed by an array of immune reagents, identifying particular antigens, which define subsets. of pathological  categories.  usually the immunologic analysis leads only to a grouping of the diagnosis, it allows a smaller biopsy to suffice for a diagnosis.  Rarely, the immunophenotype  identifies a therapeutic target: CD20, Her2, ER,  are currently  "targeted"  therapeutically.

More recently, genetic sequencing has a joined the effort to better define the nature of malignancies. This information has been accompanied by the development of targeted agents, medicines that are marketed as being specific to particular signal transduction pathways. The failure to identify actionable gene mutations has led to cynicism  concerning the value of next generation sequencing. 

The association between diagnosis, including  diagnosis guided by genomic sequencing, and therapy, remains loose. Often, the relationship between the mutation identified and the cancer phenotype is loose. It is unclear if the mutation is a driver or a passenger.  Patterns of mutations and their correlation with cell behavior  is in its infancy. NEJM. , Ortmann et al. 

http://upload.wikimedia.org/wikipedia/commons/thumb/b/b0/Signal_transduction_pathways.svg/550px-Signal_transduction_pathways.svg.png

 Scientists are trying to keep the pictures neat.  I do not believe that the pathways that are so neatly described are so well behaved.  I think that it is very likely that there is more overlap among pathways than is commonly described.The cell is not a set transistors, it is organelles swimming is a pool of chemical reactions,each organelle with its own chemical reaction pool .  Thus, interfering  with the implicated pathway,(the intervention that is often recommended by the sequencing pathologist) is not likely to be effective

If one wanted to test for the target, one should look at the pattern of protein phosphorylation and other signaling chemical  modifications.  Looking at the DNA is relatively easy. But it is not the right place to look.  The activity of the drugs involves the chemical pathways, not the genes involved in making components of the pathway. 

Ultimately, a diagnosis should identify the pathway to disrupt, and therapy should disrupt the pathway  with minimum of side sffects, 

Diagnosis and outcome

Medical knowledge, all scientific knowledge, is statistical. Even in the simplest, most straightforward experiment, there is some level of imprecision, some degree of unavoidable ambiguity ( error). All results are expressed some margin of error.

Medical data often has a very wide margin of error. Reasons for this include the heterogeneity of the population studied. Often, what we call a “diagnosis” can be resolved into more than one disease entity. Until we knew better, no distinction was made between estrogen receptor positive estrogen receptor negative breast cancer.Now, these different entities are often treated in different ways. sometimes, a new treatment defines a new subgroup. tratuzamab makes Her2 expression important in breast and stomach cancers, Rituximab makes the CD 20 a critical factor in the treatment of lymphoma.
In my opinion, the true value of a diagnosis is how it defines treatment. The diagnosis and treatment outcome are inseparable. If a diagnosis gives a 30% response rate to treatment, it is a poor diagnosis. A diagnosis of lung cancer, in the absence of molecular definition,  is hardly more than a guess, regardless of the details appended. A diagnosis of CML, with a bcr-abl translocation is a strong statement that leads to a near 100% probability of response.

Response is not the point. People living better and longer is the point. Response is a useful measure that hints that a treatment is on the right track. The documentation and publication of a response is a public service, but, aside from the psychological lift, it does not necessarily benefit the patient.

There are unfounded beliefs in the practice of ooncology Probably the most destructive of these is the idea that efficacy is a function of toxicity. The more toxic the therapy, the more powerful it is, the more cancer it kills. This is an unfounded belief, not evidence based and not scientific.
It is true that some cancers can be cured by very toxic treatment, and at this time, extremely dangerous and toxic treatment is the only known way to reliably treat many leukemias, certain lymphomas, etc. But oral, low side effective  tyrosine kinase inhibitors, like imatinib, are more effective in the treatment of chronic myelogenous leukemia than a life endangering, life altering bone marrow transplant.

A related, unfounded belief is that the microscopic appearance of a tumor, and the pathologist’s impression of its aggressiveness should determine the toxicity of the therapy; The most primitive of cancer, testicular cancer, is among the most reliably curable. And it is the most normal appearing elements of that cancer ( teratoma) that is the most difficult to eliminate. The microscopic “aggressiveness” estimate of the pathologist is an aggregate of the number of cells in mitosis ( the act of division), how bizarre the cells look, how different from normal they are, etc. These parameters do not correlate with outcome. A high mitotic rate could confer increased susceptibility to treatment ( even treatment that is not directed at mitosis). Bizarre appearing cells may be programmed for death under certain conditiona

Traditional Forces in Medical Decisions

Medicine is both the beneficiary and victim of traditions.

The benefit comes from the credibility afforded to medicine, translated into the respect afforded  doctors.  There is a tradition of professional excellence, enforced by a licensing mechanism and a legal system that monitors quality.

Traditional  forces are  conservative,  They encourage the continuation of "standard practice." Usually that is a good thing.  Standard practice is usually the best available course. But the tradition is a force that retards change, and sometimes change means improvement.

All traditions, medical or otherwise, are the products of history, and as such, preserve a wisdom and perpetuate myths.

A core tradition in medical  oncology is that more toxic treatment is more effective treatment.  This stems form the history of the field (  see: The Emperor  of all Maladies) .  The first  successes in treatment of cancer  were seen when therapy was brought to an intensity that  carried a significant chance of toxic death, death from the treatment itself     ( not the disease).  That  tradition carries through to the present.  When cancer  cases are discussed in conference,  the question of dose   is always raised.

But the notion that higher dose yields better results, has often  not  been  tested in most circumstances.  The dosage of drugs is established in  Phase I clinical trials, These trials include desperate, heavily pre-treated patients with clearly heterogeneous primary and secondary problems.  These trials usually assume the optimal dose is  at or near the maximum tolerated dose .  Once that dose is established, it becomes cowardly  to   reduce the dose, unless forced to do so by toxicity. I am not sure that the approach is globally  valid.

The classification and  treatment of cancers based upon microscpic appearance,  That  is a tradition.  The appearance of cells in the microscope and the impression of analogy to aberrant normal tissue dates from Virchow  (1821-1902). This approach organizes the treatment of cancer, but it has other consequences.

There is currently a battle between the microscope and molecular biology for the orimacy  in diagnosis. The  molecular biology sometimes identifies mutations that may be fundamental to the cancer process and these  mutated gene products can be the targets of therapy.  Frequently, neither of these  happens. The mutations are of unknown significance and the targeted agents work poorly, or not at all ( at $10,000 per month).  But even when clear targets emerge, they struggle against the tradition of the microscope  for recognition.

Sometimes, treatment does not change despite a  better understanding of the disease process.  Lymphocyte predominant Hodgkin disease is an example.  Hodgkin Diseases is a set of lymphomas that are caused by a very distinctive appearing cell: the Reed Sternberg cell.  Cells with a similar appearance are  characteristic of a disease called Lymphocyte Predominance Hodgkin Disease, but it has been known for 30 years that this is a  non-Hodgkin lymphoma.

The traditional treatment for Hodgkin  is ABVD, a mixture of toxic  medicines that can damage the heart, lungs, nerves and immune system.  This combination is not standard for Non Hodgkin lymphoma....except for lymphocyte predominant Hodgkin Disease, because that is the tradition.  ( I do not follow this tradition). Continuing to use a regimen that has worked in the past  is a very reasonable approach, but the Hodgkin Disease regimen has considerable long term toxicity.

Tradition is a reasonable fall back position, especially when it has a good  track record.   It should not stand in the way of progress. There is value in tracing  how we come to treat certain diseases in certain ways. Often, there is no basis at all.

Tradition has a role, but it must be subject to scrutiny.