Genetic Testing and Pharmacogenomics in Psychiatry

Ever since I studied Shannon and Weavers's classic paper on information theory and studied entropy as a chemistry major - I have been interested in the flow of information in biological systems.  With the advent of modern techniques it is now possible to study the DNA of entire organisms (genomics), the collection of all RNA gene readouts in a cell (transcriptomics), the resulting protein locations, concentrations, turnover and post translation modifications (proteomics), and all of the small molecules within these systems (metabolomics).  There are a large number of studies in all of these areas across medicine in general but also psychiatry and addiction.  Before I launch into some of these studies I thought I would address a basic question I get from colleagues that looks at basically the genomic approach to drug metabolism.   

One of the most common questions I get from colleagues and online is: "Do you think that genetic testing is necessary?  Do you think it is useful?"  My standard response has been that in some cases it is but most of the time it is unnecessary.  I also point out that I am old school  and that plasma levels of antidepressants seem to be more of an accurate approach to antidepressant therapy.  The debate at the about plasma levels is always whether there is a known therapeutic level or not.  A lot of that debate dates back to the 1980s when we were using tricyclic antidepressants.  Psychiatrists typically used nortriptyline because the therapeutic levels were well defined.  Clinical trials data at the time provided therapeutic levels for all of the major tricyclics (amitriptyline, imipramine, desipramine).  Clinical chemistry companies also provided levels for less commonly used tricyclics like doxepin and trimipramine quoting smaller trials or observational studies for the therapeutic levels.   All of these drugs had toxic levels because of studies done on drug overdoses using these drugs.   A psychiatrist would typically get back a report with a quoted therapeutic level (or proposed levels), active metabolite levels, and toxicity levels.  In the case of a drug with no metabolites like nortriptyline the report would give the level, the range, and a much higher toxicity range.

When we entered the human genomics era there was expanded interest in the genetic bases of the pharmacokinetics (PK) and pharmacodynamics (PD) of psychiatric drugs.  That involved understanding the genetics of the hepatic cytochromes that metabolize most drugs and the genetics of the protein targets (reuptake proteins and receptor sites) where the drugs had their purported effects. Most of the pharmacogenomics of drug metabolism is focused on PK rather than PD.

One of the best independent reviews of the issue of genetic testing can be found in reference 3 below.  The authors do a systematic review looking at the question and come away with 5 clinical trials that look at the efficacy of commercially available pharmacogenomic testing and 5 studies that look at the issue of cost-effectiveness.   

     

Test	Type
GeneSight	Combinatorial
Genecept Assay	Combinatorial
CNSDose	Combinatorial

Combinatorial in this case means testing for multiple genes and it has been shown to currently be more predictive of antidepressant response than any single test.  Each of the assays typically looks at gene loci involved in drug metabolism and flags markers at that site.  For example,  I took my 23&Me data and ran it through a second software site that yielded the following analysis:

The CYP pharmacogenes on the left are associated with drug metabolism.  The rsID in column 2 designates the single nucleotide polymorphism noted in that gene.   Alleles are just different gene forms based on the difference at a single locus.   In this chart nucleotide bases (A.T,G,C) are designated. The result column notes if the genes have mutations (+) or not (-) and are homozygous (+/+, -/-) or heterozygous (-/+).  The red color code is homozygous for the mutation and the yellow color code is heterozygous.

In the above chart. red color codes for deficiencies in drug metabolism.  For example, the
rs1799853 on the pharmacogene CYP2C9*2 C430T (TT) is associated with a 40% reduction in warfarin metabolism and a greater risk for NSAID metabolism.  In fact, I was treated briefly with warfarin - had a difficult time with dose adjustments and was physically ill from the medication.

What about the common drug metabolizing genes?  In the case of common genes like CYP2C19 and CYP2D6 several variants are flagged and none of the variants are detected.  In terms of drug metabolism, the following results could be expected if they were found:

CYP2C19*17 (rs12248560) CC - normal genotype, CT - ultrafast metabolizer, TT - ultrafast metabolizer

CYP2D6 S486T  (rs1135840) CC - normal variant studied in clozapine metabolism

CYP2D6 100C>T  (rs1065852) GG - variant (C;T)(T;T) variants are associated with non functioning CYP2D6

CYP2D6 2850C>T  (rs16947) GG - normal variant - other variants may be associated with ultra-rapid CYP2D6 metabolism

These examples illustrate that SNPs can result in non-functioning CYP enzymes that would lead to an accumulation of the target drug or in some cases ultra-metabolism of the target drug with lower than expected plasma levels or in some cases physical effects from rapidly decreasing plasma levels.  There are a finite number of SNPs studied in this approach and a relevant question is what is the total universe of clinically relevant SNPs for a particular pharmacogene.  For example, in the PharmVar database database tables are available for CYP2D6 that give the frequencies of 113 alleles across all major race and ethnic groups.  A separate table lists 140 haplotypes with 993 variants.  39% of the variants are decreased function or no function alleles (54/140), 20% were normal (28/140), and 34% were unknown (48/140).

A recent study (4) looks at the practical aspects of predicting drug metabolizing phenotype from available CYP2D6 genotypes.  This is essentially the task of consumer pharmacogenomic testing. Thuis study has the additional advantage  of applying uniform methodologies across a large number of samples (N=104,509) instead of the small samples and non-uniform methodologies often used in typical databases.  They looked at both single nucleotide variants (SNVs) and copy number variants (CNVs) like gene duplications, deletions of entire CYP2D6 genes, and gene rearrangements.  CYP2D6 copy numbers of 0, 1, 2, 3 or > 3 were assigned.  Metabolizer status was assigned based on copy number with: Ultrarapid metabolize (UM ≥ 3 normal functioing gene copies); normal metabolizer (NM, 1 or 2 normal functioing alleles), intermediate metabolizer (IM, ≥  2 decreased functioing alleles), and poor metabolizer (PM, ≥  2 no function alleles).

37 CYP2D6 alleles were detected in the sample including 23 structural variants.  13.1% of the sample had copy number variants (CNVs).  The majority of structural variants had no function due to CYP2D6*5 gene deletion.  93% of the alleles were single copy variants with normal function (62%).  Based on the above convention phenotypic predictions were 2.2% Ultrarapid Metabolizers (UM), 81.4% Normal Metabolizers (NM), 10.7% intermediate metabolizers (IM), and 5.7% poor metabolizers (PM).  The authors point out that copy number variants (CNVs) contribute to significant variance in drug metabolism and may be underestimated in a number of studies.  They also point out that there are no current standards to predict genotypes from phenotypes.  The importance of CNVs in phenotypic variation is captured by this graphic from the original reference (4):

Figure 6. Contribution of structural variants and single copy variants to predicted phenotypes. Proportion of individuals in each predicted phenotype that had at least one structural variant is shown (from reference 4).

Getting back to the study in reference 3, the authors looked at what genes were studied in the commercial tests. Genesight looked at 6 genes (CYP2D6, CYP2C19, CYP1A2, CYP2C9, serotonin transporter gene (SLC6A4) and serotonin 2A receptor gene (HTR2A). The authors review 2 unrandomized studies of major depression by the same primary author comparing a group guided by the Genesight to a group that was not. There were increased improvement in depression scores in the Genesight guided group. A separate randomized study of Genesight guidance versus treatment as usual showed greater improvement in depression scores but no statistical significance.

Genecept was another commercially available studied product that was used 2 clinical trials. Genecept looks at CYP2D6, CYP2C19, CYP3A4, SLC6A4, 5HT2C, DRD2 (dopamine-2receptor), CACNA1C (L-type voltage gated calcium channel), ANK-3 (ankyrin g, COMT (catechol-O-methyl transferase, and MTHFR (methylenetetrahydrofolate reductase). The first was a naturalistic study with no control group (N=685) and all subjects got genetic testing. 77% of participants improved - 39% with improved scores and 38% with remitted depression.

CNSDose was the final assay that was studied clinically. This assay looks at CYP2D6, CYP2C19, and ABCC1 and ABCB1 (blood brain barrier transporters). This was a prospective double blind randomized guided versus unguided study (N=148). Guided subjects had a 72% remission rate compared with the 28% remission rate in the unguided group or a 2.52-fold greater chance of recovery. It was unclear how the guidance resulted in such high remission rates and the study has not been replicated.

The authors go on to review similar problems with cost-effectiveness analysis applied to the currently available genetic tests. They also review the methodological limitations of the current studies and conclude that pharmacogenomic testing is generally not ready for prime time at this point for most clinical psychiatrists. That is what I have been saying for years - along with advocating for plasma levels of antidepressants and antipsychotics when they are available. That said - I have done pharmacogenomic testing for patients who do not tolerate antidepressant medications or seem to be experiencing atypical side effects - like discontinuation symptoms the same day from SSRI or SNRI antidepressants that usually do not cause those symptoms.

Striking features from this brief review include the apparent lack of standard rules on interpreting drug metabolizing phenotype from genotypes and the importance of copy number variants in predicting phenotype. If clinicians are getting genotyping for genotyping predictions it is a good idea to make sure that these genotypes are also determined in addition to the single nucleotide variants. Specific genes in reports can all be looked up for specifics based on the rsID located in this post.

Given these constraints, I think that commercially available pharmacogenomics assays need to be very explicit on how they determine drug metabolizing phenotypes, what genetic information they are actually measuring, and what might be missed.  The ultimate clinical trial would be to look at a group of patients who did not tolerate specific antidepressants and see if higher than expected abnormal drug metabolizer frequencies could be detected.



George Dawson, MD, DFAPA




References:

1: Weinshilboum RM, Wang L. Pharmacogenomics: Precision Medicine and Drug Response. Mayo Clin Proc. 2017 Nov;92(11):1711-1722. doi: 10.1016/j.mayocp.2017.09.001. Epub 2017 Nov 1. Review. PubMed PMID: 29101939.

2: Wang L, McLeod HL, Weinshilboum RM. Genomics and drug response. N Engl J Med. 2011 Mar 24;364(12):1144-53. doi: 10.1056/NEJMra1010600. Review. PubMed PMID: 21428770.

3: Rosenblat JD, Lee Y, McIntyre RS. Does Pharmacogenomic Testing Improve Clinical Outcomes for Major Depressive Disorder? A Systematic Review of Clinical Trials and Cost-Effectiveness Studies. J Clin Psychiatry. 2017 Jun;78(6):720-729. doi: 10.4088/JCP.15r10583. Review. PubMed PMID: 28068459.

4: Del Tredici AL, Malhotra A, Dedek M, Espin F, Roach D, Zhu G, Voland J and Moreno TA (2018) Frequency of CYP2D6 Alleles Including Structural Variants in the United States. Front. Pharmacol. 9:305. doi: 10.3389/fphar.2018.00305




Relevant Databases:

1: Transformer Database (formerly Super CYP Database).

Michael F. Hoffmann, Sarah C. Preissner, Janette Nickel, Mathias Dunkel, Robert Preissner and Saskia Preissner. The Transformer database: biotransformation of xenobiotics.  Nucleic Acids Res. 2014 Jan 1;42(1):D1113-7. doi: 10.1093/nar/gkt1246. Epub 2013 Dec 10.

Preissner S, Kroll K, Dunkel M, Senger C, Goldsobel G, Kuzman D, Guenther S, Winnenburg R, Schroeder M, Preissner R. SuperCYP: a comprehensive database on Cytochrome P450 enzymes including a tool for analysis of CYP-drug interactions. Nucleic Acids Res. 2010 Jan;38(Database issue):D237-43. doi: 10.1093/nar/gkp970. Epub 2009 Nov 24. PubMed PMID: 19934256

2: Pharmacogene Variation (PharmVar) Consortium (formerly Human Cytochrome P450 (CYP) Allele Nomenclature Database).

PharmVar Genes


3: FDA:

Table of pharmacogenomic markers in drug labeling.

Other FDA resources related to pharmacogenomics.

FDA Precision Medicine site.


4: CPIC (The Clinical Pharmacogenetics Implementation Consortium) web site.

CPIC Alleles

CPIC Genes-Drugs




Graphics Credit:

Structural Variant versus Predicted Phenotype graphic is from reference 4 above and is unaltered. It is used per the Creative Commons Attribution 4.0 International Public License.

Drug Outbreak Testing Service (DOTS)

I wanted to get this information out as soon as I saw it. It is a service that offers free testing for drug outbreaks that are occurring more frequently as the pendulum swings to more acceptance of using various intoxicants.  This is a valuable service because many of these outbreaks occur so rapidly and with an unknown compound that leads to a sudden burst of morbidity and mortality and the medical systems in some towns are ill equipped to identify the offending agent.  I have posted about an epidemic of synthetic cannabinoids that required an intensive effort to look identify the compound being used.

This service offers rapid testing for up to 240 prescription and primarily nonprescription street drugs.  In their first paper on methodology at the references below they describe the rationale and procedure.  To qualify as a DOTS site, there has to be an identifiable outbreak of intoxicant use that cannot be identified locally.  That site needs to be able to submit 20 identified urine samples for testing.  In the following references the patterns of detected drugs vary considerably by site and level of sophistication necessary to identify the compounds.  For example, the King County DOTS samples yielded bufotenine, cathinine, alpha-PVP, mitragynine/7-hydroxy mitragynine, and U-47700 - compounds that are unlikely to be picked up in standard testing even at most substance use treatment centers.  Their assays also have sensitivity enough to pick up compounds like fentanyl that may be missed with lower sensitivity assays.

A brief discussion of the sample sites is required.  Comparing the toxicology data shows considerable variation across the sites.  The first sample was from an emergency department (ED) at the University of Maryland looking at the question of agitated patients and suspecting the use of cathinones or Bath Salts.  There were only 8 samples submitted.  There was more evidence that fentanyl may have been involved but there were a wide variety of compounds noted including diphenhydramine.  The King County Medical Examiner samples were from 20 people who had died of drug overdoses. Fifteen of the 20 samples contained methamphetamine and 14/20 contained fentanyl or analogues.  None of the 20 sample contained 10 or more compounds showing a high degree of polysubstance use in this sample.  The Montgomery County Maryland site is 20 samples from an outpatient clinic treating uninsured or publicly insured patients. The majority (75%) contained THC with 6/20 containing cocaine and 3/20 containing methamphetamine.  The Recovery Research Network submitted 23 samples from patients who were all in voluntary outpatient treatment.  The samples show a high degree of polypharmacy with 35% containing 10 or more drugs and 91% containing 5 or more drugs.   Aspenti Health submitted 20 samples on outpatients and their interest was in detecting possible fentanyl use.  12/20 samples were positive for fentanyl even though the lab results from the originating facility were b=negative due to a higher detection limit on their assay.  90% were positive for buprenorphine and 53% contained naloxone.

All together there are 91 samples from the 5 sites.  There is a lot of information contained in that data.  There is more detailed toxicology here that is available on most reports that I have reviewed, although data is generally not presented well in electronic health records.  I have included the data form the King County Medical Examiner's Office because it is the most complex and because this appears to be a publicly funded document with no copyright constraints.  Click to enlarge the graphic.

 
This is the way the data is presented from all 5 sites.  Major drug categories are color coded across all of the sites and there are row and column sums.  Interesting observations can be made in the data, but incident and sampling heterogeneity precludes any scientific conclusions.  One of the first things I noticed was the low frequency of psychiatric medications 26/91 were on antidepressants. One sample contained haloperidol and there were no samples containing quetiapine - a medication commonly used in residential treatment centers for insomnia. This could mean that much of the psychiatric comorbidity in the sample was not addressed.  The autopsy samples contained the fewest antidepressants.  Despite the recent concerns about gabapentin it was found in 13 of 91 samples and 4/20 autopsy specimens.

The greatest totals were for THC (50/91) and fentanyl and fentanyl metabolites (46/91).  The fentanyl was overrepresented in the autopsy specimens where 11/20 were positive and the Recovery Research Network sample where 19/20 were positive for fentanyl.  More  concerning 5 or those samples were also positive for buprenorphine indicating that patient may have been on MAT for opioid use disorder (OUD).  A similar pattern exists in the Aspenti Health sample where  11/20 were positive for both fentanyl and buprenorphine.  That is not to say that MAT for OUD is not indicated, but it probably reflects that fact that a significant number of drug users are not risk averse and do not consider MAT as a way to help them avoid the risks of OUD.  It is consistent with a recent story I heard about a number of OUD patients leaving a residential treatment facility because they heard that fentanyl was available in that community.  Many of those patients were on buprenorphine at an appropriate maintenance dose.

In may last look at the DEA schedule of controlled substances it contained about 330 compounds and I am sure that number has grown by now.  DOTS tests for 240.  If you have an outbreak in your community and the sources are not clearly known and little toxicology is available - it might be worthwhile to give them a call.  This is a valuable service to provide insight into what intoxicants may be responsible.

Being an undergrad chemistry major, this project also lead me to think about why every metropolitan area with a university or college having a chemistry major and access to GC/Mass Spectrometry should not have similar testing services.  These departments could be subsidized or reimbursed for the testing, incentivized for quality, and train the next generation of analytical organic chemists all in the same process.



George Dawson, MD, DFAPA


References:

1:  DOTS Bulletin A Pilot Study of the National Drug Early Warning System (NDEWS) University of Maryland, College Park Drug Outbreak Testing Service July 2018. Issue 6 DOTS Web Site

The Problem With Checklists.....

I have critiqued the checklist approach to psychiatry in many posts on this blog.  Several like-mind psychiatrists have also added many comments in this area. I had recent experience with surgical checklists that leave a lot to be desired.  So much so that if I was not an MD - I might not be sitting here and typing this post right now.  For now, I will just post the bare bones sequence of events for illustrative purposes.  On April 14, I had an operative procedure that required antibiotic prophylaxis that consisted of a single intravenous dose of antibiotics given right before surgery. On July 31, I had a second operative procedure to address complications of the first procedure. Both procedures were done under general anesthesia (fentanyl and midazolam or Versed).  A laryngeal mask airway (LMA) was used instead of intubation.  The general sequence of events went like this.

1.  Preop physical exam - good for 1 month prior to surgery.  The exam is done by a primary care MD.  The surgery will not occur without it.  The goal is to identify and complicating or potentially contraindicating conditions.  Specific instructions are given to the surgeon and anesthesiologist based on this assessment.  Specific instructions are given to the patient about if they need to change up their medications at all prior to the surgery.  For example, it is common advice to hold aspirin and other anti-inflammatory medications (NSAIDs), and certain vitamin supplements for 1-2 weeks prior to the surgery.

2.  Hospital intake - over the hour or two before surgery there are intense meetings with a number of disciplines:

Pre-Op RN:  Reviews the medication list and confirms that all of the recommended medications and pre-op instructions were followed.  Assesses functional capacity as well as presence of eyeglasses, hearing aids, implants, pacemakers, CPAP mcahines and artificial joints.

Pharmacist:  Reviews the detailed list of medications and looks for potential drug-drug interactions as well as drug-anesthesia interactions.

Anesthesiologist:  Reviews the detailed list of medications and rationale.  Takes a detailed cardiovascular history. Examines heart and lungs.  Asks detailed family history and personal history for anesthesia interactions particularly malignant hyperthermia. In both cases this hospital trained nurse anesthetists who asked the same questions and administered the pre-op midazolam before leaving the pre-op area.

 OR Nurse:  Also interviews patient about concerns over the surgery and assures that all intravenous lines and devices that will be in the operating room (OR) are present and working.

That is the overall sequence of events.  Each of these team members has specific jobs and checklists that were entered into an EHR.  The primary care physician handed me a copy of my pre-op exam to take with me in case the faxed version was lost.  It was printed out from a well known enterprise wide EHR.

I have a condition called lone atrial fibrillation that is commonly seen in middle-aged (and now old) men who exercise too much.  It was originally thought to be associated with high levels of dynamic exercise like cycling and running, but epidemiological studies suggest it may also be associated with jobs that require a lot of heavy lifting - like furniture and piano moving.  I have also talked to power lifters in the gym who developed it when they continued the lifting into their 50s and 60s.  I take flecainide and it keeps me in a steady sinus rhythm and that has worked well for the past 8 years.  The problem with flecainide is that it is a fairly toxic medication if you have the wrong biological substrate or if you mix it with the wrong medications. A trial of flecainide in ventricular tachycardia was halted because of increased fatalities in the treatment group compared to placebo.  The last electrophysiologist I talked with suggested that I needed to get an exercise stress test done every year to make sure that the QRS interval was not widening due to the drug.  For the purpose of these surgeries my primary concern was not getting a medication that would interact with flecainide and result in a fatal arrhythmia.  I knew that this surgical specialty used fluoroquinolones preoperatively and if you search that interaction in any database this is a typical result.           

"Moderate risk - can cause QTc prolongation and should be avoided when possible. Increased risk for torsades de pointes and other significant ventricular arrhythmias.  Other factors (old age, female sex, bradycardia, hypokalemia, hypomagnesemia, and higher concentrations of the interacting drugs can increase risk for potential life-threatening arrhythmias."

I naturally wanted to avoid the fatal arrhythmia.

At every step in the above chain, I explained this drug interaction and advised the team members that I can safely take cephalosporins.  And here is what happened.

In both cases I had the same primary care MD doing the pre-op physical exam.  He was very focused on the pre-op checklist and in fact the rooming medical assistance reviewed the med list, vital signs, and review of systems that was entered into the EHR checklist before I saw the physician.  When he was done he asked me if I had any concern and I told him "Any antibiotic or anesthesia agent that interacts with flecainide - I do not want to take. I know that I can take fentanyl and Versed for general anesthesia so those are the preferred agents if they can use them for this surgery."  The first time he pulled up the interaction in the EHR, agreed and said - "I will flag this in my assessment so they see it."  The second time he said the same thing but reviewing the H & P he handed me it was not present.  It is possible it was transmitted on another form.

And so it went with every members of the preop team.  They all seemed surprised every time I brought it up.  They thought I was talking about an allergy as opposed to a drug-drug interaction. One of the pharmacists looked it up on her Smartphone app and confirmed.  There was a lot of confusion about the preop antibiotic right up until the time of administration.  Was there another drug that could be used? Would the doctor change the standard orders to administer another drug?  For the past surgery - I had to tell them to look up the April record and confirm that I was given 2 grams of IV cefazolin and not levofloxacin.

When it was finally clarified, it took two nurses to figure out how the levofloxacin could be discontinued from the standard order in the EHR so that the cefazolin could be given.  I was finally given the cefazolin, operated on and so far (barring another complication) things are going well.

The lessons:

1.  Almost everything you hear about the EHR and checklists increasing safety is a myth -  

In this case all of the professionals were using state of the art (and extremely expensive) EHRs containing checklists and forms that were dutifully completely and the ultimate check here was the patient who happened to be a physician who compulsively studies drug interactions and cardiac complications.  That is not a level of safety that I want to see for any of my family members or patients who are undergoing surgery.

2.  Patients or competent family members are the best safeguards for safety at this point -     

I have worked with very bright and insightful nurses who told me that they have a rule that they accompany hospitalized colleagues and check everything that is going to happen to them as well as what medications are administered to them.  On the other hand I have asked patients what medications they take and been told: "You tell me doc.  I just put them in a pill container.  I don't know the names, doses or what they do."

There is a lot of talk about patient empowerment, but it has to be built on a solid foundation of patient literacy.  I certainly realize that a lot of people do not want to know, but I have also talked with many people having less than a high school education who could tell me every drug they took during a complicated course of cancer treatment that included a bone marrow transplant.  Reading and understanding the pharmacy printout given with a medication is a basic prerequisite for the literacy I am talking about. 

3.  This is a systems problem and not a personnel problem -  

Let's face it - all of the personnel in the system are highly competent licensed professionals. They are all focused on their tasks and they do a good job of it.  The problem is that all of these very competent individual assessments are not synthesized into a useful safety plan.  Experts have been writing about the importance of checklists in industry (like the airline and automotive industries) for decades but medical information is individualized complex, and not redundant.  Any adverse outcome of the sequence of events that I described is likely to be something like this:

"Well Dr./Nurse X - did you fail to read all of the narratives in the chart and the patient stating that he had concerns about drug interactions with flecainide?"

Any response to the effect that the EHR is difficult to read and in some cases incoherent and should have flagged this concern automatically is likely to be met with:

"Well that's our EHR and we have to live with it. Our focus groups with the nurses and the manufacturer have been working on fixes for the past 5 years."

Translation:  somebody has to take the blame and it won't be the EHR.

4.  Why doesn't the EHR/checklist approach work? 

It failed miserably - not just once but twice in my case and I was advocating at every level to flag flecainide and not give me any interacting drug.  Having worked with EHRs now for nearly 20 years I can speculate on a few things.  First, there is very little intelligence built into EHRs.  In this case the EHR will do a comprehensive drug interaction search on the current list.  But there is probably not an automatic search on the standard preop antibiotic.  If there is - physicians are numbed to dismissing so many false positive drug interactions that could have happened as well. Second, any discussion of the patients concern or doctors advice is buried in documentation that is prioritized for billing, rarely read, and not translated into any rational action. An intelligent EHR would convert the concern about flecainide interactions into what is called a hard stop. That means the potentially offending drug could not be ordered until some further action was taken - like a discussion between the physician, pharmacist, and patient.  In this case, my discussion with 10 people was not beneficial and the only reason I did not get levofloxacin was that I was in a hospital bed about 6 feet away from where the nurse was working and I was a physician who has worked for years to prevent these kinds of problems.

It is hard to believe that such extremely expensive and heavily lobbied systems can't provide a basic level of safety.  I was not surprised to read that having the same primary care physician for years is probably a better assurance of longevity.

For the non-medical person reading this - know your medications, what they do, and what the potential safety concerns are when you are in a situation where those medications are being changed. Ask your pharmacist and physician to do a drug interaction search to make sure these transitions can be safely made. Refuse any medication unless a sound rationale can be provided to you about why you are taking the drug and how safe it is to take with your current prescriptions.

George Dawson, MD, DFAPA

     
Graphics Credit - the graphic at the top is from Shutterstock per their standard licensing agreement.

Is AHRQ's National Guideline Clearinghouse disappearing for good tomorrow?

The AHRQ was started 30 years ago in 1999 when it was renamed from the Agency for Health Care Policy and Research (AHCPR) to the Agency for Healthcare Research and Quality (AHRQ) by legislative action.  I have referenced their guidelines on this blog for ADHD and depression.  The post on the depression guideline illustrated that AHCPR guidelines were generally of higher quality than the current managed care guidelines and screening guidelines.

Even looking at the web site today before it is taken down illustrates the depth of research and recommendation on the site.  A search for psychiatry yields 600 references including research and policy recommendations.  Interesting the guidelines at guidelines.gov has 74 psychiatric guidelines ranging from depression in children and adolescents to a guideline for CYP2D6 and CYP2C19 genotypes and dosing of tricyclic antidepressants.  A wide number of physician and nonphysician organizations have produced the guidelines.  These are unique sites with few comparable sites in the world.  Only the National Institute for Health and Care Excellence (NICE) in the UK seems similar.  The NICE guidelines are produced by a more uniform methodology rather than disparate organizations.

When the current administration announced it was defunding AHRQ guidelines, there was some hope that someone else would take it over - at least the existing databases.  Some physician professional organizations were suggested.  Given the government's shaky history of ancient information technology and dubious failed upgrades, I am speculating that would be the reason why nobody else would want to take that on.  Clearly nobody in the administration is interested in a smooth transition.  The smoothest transition I can think of would be to make the data available through the National Library of Medicine and their collection of databases.  But as I type this there are about 8 hours to make that transition.

There are several serious questions for the Trump administration.  Some are speculative, but when people question how doctors are influenced by a slice of pizza, I think it is reasonable to ask about health care corporations that are influenced by tens to hundreds of billions of dollars and how they influence politicians.

1.  How does it make sense to take this data and these initiatives offline when the costs are trivial compared to other government projects?

Cost analyses have been done showing not much of a price increase corrected for inflation.  Various analyses have been suggested such as this one pointed out the agency's role in reducing hospital infections resulting in 124,000 fewer fatalities per year a cost saving of about $28 billion.


2.  And possibly even more important - what are the conflicts of interest involved?

The most significant one that I can see is that industry guidelines and standards go unchecked.  There are any number of groups that are primarily comprised of health care executives that are producing standards of care that have nothing to do with medical practice or standards.  Review practices by pharmaceutical benefit managers come under the same category.  These physician intimidation strategies have nothing to do the scientific evidence or quality of care. In this regard the wholesale suspension of guidelines that counter industry practices are suddenly gone.  It is far easier to do than reverse Environmental Protection Agency (EPA) regulations - but the zeitgeist is the same.

Taking down AHRQ means there is one less place in government healthcare sites with the word quality.  I don't think that is an accident either.  Today's healthcare industry would rather advertise how they are the best without using the quality word or any scientifically valid metrics.

3.  As a corollary to the above - what about the professional guidelines that are collated and listed on the site?

I don't have the time to follow other physician professional organizations but the American Psychiatric Association has fallen off greatly over the years.  Critical issues have not been addressed in some cases for decades.  The commonest cause for this problem is cited as the expense it takes to collect all of the experts and data, but in the information age it would seem to be easier than ever.  I speculate the the real reason is that these guidelines are just ignored.  Why produce a hundred page guideline on all the aspects of the treatment of depression when the dominant managed care standard is a 2 minute screening exam and an antidepressant prescription?  Why produce that document when it affects only 5% of the work force for mental disorders?  Why produce that document when the psychiatrists involved have so little political leverage against the industry and the government that they can never use it. 

AHRQ at least provided a broader forum for discussion.

4.  Why the minimal notification and lack of feedback?  

There are so many guidelines and so much information available on this site, it is impossible to know who is using it all and for what purpose.  Unilaterally taking down a resource like this with 4 months notice has to be considered nothing more than a political decision at this point.  If the number of people and organizations accessing this site was published somewhere - I have never seen it.

5.  What about the Centers for Medicare and Medicaid services, the CMS web site?

Since CMS is essentially the billing and regulatory web site for Medicare - I don't think it is any danger of being shut down.  But it does promote and spread a lot of unscientific information that is biased toward running the business side of health care at the expense of the medical side.  It is a massive bureaucracy that is responsible for the bulk of physicians paperwork burden every day. Some clear evidence for the lack of science is psychiatric diagnosis related groups and how they don't accurately reflect diagnoses or the expected course of treatment for hospitalized psychiatric patients.  The most recent post on this blog looks at the rationing of inpatient psychiatric services and how a lot of that has resulted from CMS regulation.  Just a few years ago, I wrote a blog piece about a 55 page CMS document about what psychiatrists would have to do to document the diagnosis and treatment of depression.  That was subsequently taken down.     

6.  Finally what does this imply for other federally funded information programs?

My biggest concern in this era of massive profits for publishers is the National Library of Medicine (NLM) - commonly used by physicians offices on a daily basis.  It is a major resource for researchers, but it is also becoming a competitor for profitable online publishers.  If research is publicly funded - a copy is accessible without charge on the PubMed web site.  Will the day come when for profit medical publishers have enough leverage to put the NLM out of business?  Stranger things have happened.  

It is easy to blame that President Trump.  He is heading the first blatantly anti-science and pro-business administration that I can recall in my decades of existence.  But the reality is that the American healthcare system has been designed by an endless stream of bad decisions for the past 30 years all occurring in the confluence of special interest politics and massive special interest money with a little medical science (and a few doctors) sprinkled in. The press seems to focus on the influence of pharmaceutical companies, but the bulk of those bad decisions have been rationing decisions by the managed care industry.

George Dawson, MD, DFAPA

References:

1:  Heslin KC (AHRQ), Weiss AJ (Truven Health Analytics). Hospital Readmissions Involving Psychiatric Disorders, 2012. HCUP Statistical Brief #189. May 2015. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb189-Hospital-Readmissions-Psychiatric-Disorders-2012.pdf.

Supplementary:

I pulled the following figures on lengths of stay for mood disorders and schizophrenia out of the above article.  If the site goes down at midnight this may be the only place that you can find it and any paper referencing it may lead to a dead end.

Updates:

07/16/2018: 3:30 PM  AHRQ.gov web site is up and running at this point but guidelines.gov is not found.

Governments and Psychiatric Beds

I read a paper yesterday (1) on psychiatric bed policy with a focus on OECD (Organisation for Economic Cooperation and Development) nations.  The OECD has extensive data collection on their member nations and one of the metrics they collect is the number of psychiatric beds per 100,000 inhabitants.  I have demonstrated some of this data before.  For the purpose of this post I downloaded it to create the two graphs above that were used in the paper. One of the authors main points was transinstitutionalization - in this case sending people with serious mental illnesses to jails rather than psychiatric hospitals.  They demonstrate the rough inverse correlation between psychiatric beds and the rate of incarceration.  Throughout my career available psychiatric beds has always been a problem.  It has been a favorite topic on this blog.  I was interested in whether or not this group of authors had anything new to say.

In their introductory section, they provide the back drop with the numbers.  The American state hospital psychiatric beds fell 97% from 558,922 in 1955 to 37,679 in 2016.  In Minnesota, the drop was about 98.5% from 11,449 in 1955 to 175 currently.  Using the OECD data, the average was about 99 beds per 100,000 population in 1998 to 71 per 100,000 in 2015.  Only Germany trended in the other direction by increasing the number of beds.

They do a fairly good job of analyzing the risks of the bed shortage.  They cite rehospitalizations, prolonged stay in emergency departments, pressure to discharge patients from inpatient setting, more frequent involuntary treatment, and associated staff burnout.  They make the argument that higher rates of suicide are noted in community treatment compared to hospitals where suicide is less likely.  They believe acute inpatient care is less available to the acutely suicidal patient and that may account for some increase in the suicide rate. Scandinavian registry studies are cited as providing some confirmatory data with one group of authors stating that the reduction in beds was the "most probable explanation for the rising mortality."  A similar study in Finland where more community resources were available and the beds were at OECD averages described fewer suicides.

Community treatment is typically cited as a reason for the bed reduction.  In the USA, rationing is more clearly the reason since the community resources are rarely developed to compensate for the bed loss.  It is also unstated that the two treatments are not equivalent.  They cite the UK as having extensive community resources that were not enough to overcome the drop in beds leading to higher rates of suicide, transfers out of the area where the patient lives, and involuntary treatment. From the graph, the UK has more beds than the OECD average.

The history of transinstitutionalization is briefly discussed.  The Penrose Hypothesis was developed by Lionel Penrose who pointed out the inverse relationship between mental hospital and prison populations in 1939.  Other authors like Harcourt look at historical data and note the same relationship but discuss it from the perspective of the institutionalized population.  At one point in his book Harcourt suggests that people in the military and in nursing homes may need to be counted as being institutionalized.  Inspection of the bar graphs at the top of this page does illustrate some clear trends but it also illustrates that the relationship is complex and not all of the variables have been studied.  They include a third graph of the Gini coefficient that I did not include.  The Gini coefficient is a measure of income disparity (approaching 0 means less disparity).  The 10/17 countries with Gini coefficients  > 0.3 had the lowest number of psychiatric beds. In other words, more income disparity translates to fewer psychiatric beds.

The statistics about the incarcerated mentally ill in the USA are reviewed and the numbers are significant.  Twenty percent of the incarcerated population or 350,000 people per day are estimated to have serious mental illness.

The problems that I have written about on this blog for years are highlighted including the declining length of stay and what the authors called revolving door admissions.  They point out that schizophrenia has the second highest readmission rate at 1 month compared with any other diagnosis (congestive heart failure is first).  The lengths of stay are not generally long enough to allow for adequate stabilization of severe psychiatric disorders and they provide the references.  I see this population of people as a steady state group that goes from jail to homelessness to a short stay in the hospital.  Substance use disorders are generally not addressed or treated in a cursory manner. 

The paper's strength is that they provide an estimate of what a reasonable number of psychiatric beds is for a given populations.  The Royal College of Psychiatrists established a standard that would give psychiatric patients the same access to high quality medical care as medical and surgical patients.  That includes 4 hour maximum time to wait for admission.  They also said that bed occupancy should not exceed 85% to allow for emergency admissions and the length of stay figure should be 2-4 weeks to allow for real improvement.  Using those parameters a US expert consensus group estimated that 50-60 publicly funded beds per 100,000 population were necessary. In case there is any difficulty reading the above graph, the point plotted was 25 beds per 100,000 US inhabitants - well below the estimated number.  In my home state of Minnesota, that number falls off the precipice to 3 publicly funded beds per 100,000!

A closing example is given of the situation in South Australia.  Hospital beds were closed to a level of 32 per 100,000.  Acute care occupancy exceeded 100%, emergency departments waits went up, acuity increased with increasing risk of the need for physical restraint, and the burden of care was often transferred to relatives and friends.  Reforms were enacted that led to an increase to 35 beds per 100,000 with associated 2 week lengths of stay and decreased rates of suicide.

This is an excellent paper for psychiatric societies and psychiatrists to read.  It documents the problems that we all see on a daily basis and provides some clear answers. The answer does not lie with continued or more perfect rationing.  Unfortunately the people who run these systems - largely bureaucrats in large state human services departments, the politicians who influence those bureaucrats, and administrators of most health care systems all see rationing as their only solution to the problem.  They are incentivized to ration and we (and our patients) are left picking up the pieces.

We finally have a paper that is making a stand against all of this rationing.     
     

George Dawson, MD, DFAPA




Supplementary 1: Data for the top graph was downloaded directly from the OECD and accessed today (July 12, 2018).

Supplementary 2: Data on incarceration rates was taken from the Prison Policy Initiative and accessed today (July 12, 2018).

For both graphs click on them for expanded and improved resolution.




References:

1:  Allison S, Bastiampillai T, Licinio J, Fuller DA, Bidargaddi N, Sharfstein SS. When should governments increase the supply of psychiatric beds? Mol Psychiatry. 2018 Apr;23(4):796-800. doi: 10.1038/mp.2017.139. Epub 2017 Jul 11. PubMed PMID: 28696434.

2:  Osby U, Correia N, Brandt L, Ekbom A, Sparén P. Mortality and causes of death in schizophrenia in Stockholm county, Sweden. Schizophr Res. 2000 Sep 29;45(1-2):21-8. PubMed PMID: 10978869.

3: Bernard E. Harcourt, "From the Asylum to the Prison: Rethinking the Incarceration Revolution," 84 Texas Law Review 1751 (2005). Link

4:  Royal College of Psychiatrists. The Commission to review the provision of acute inpatient psychiatric care for adults.  OLD PROBLEMS, NEW SOLUTIONS: Improving acute psychiatric care for adults in England.  February 2016.  Link  This is a detailed look at bed capacity including current estimates and what can be done to improve it.

Nocebo - Part 2

I have been waiting for this paper (1) to come out for the past 6 months.  I posted on the very interesting nocebo effect in antidepressant trials and why it was so interesting and in the process learned that the lead author - Seetal Dodd had a paper being reviewed on the nocebo effect in bipolar trials.  That paper finally came out and I had the pleasure of reading it and presenting it here.

As a brief refresher, the nocebo effect is an adverse drug experience or worsening based on taking placebo or inactive medication in a clinical trial.  At the clinical level, it can also be an unrealistic reaction to a medication based on  similar response.  Any researcher who has participated in clinical trials that all breaking the protocol and allow the subject to be informed about whether they were taking active drug or placebo has probably observed this effect.  Clinicians commonly see it as an improbable reaction to a medication or in some cases multiple medications.  It is an important phenomenon because it blurs the results of clinical trials by making it seem that there is less difference between placebo and the active drug being studied.  It also may lead to the rate of actual adverse events due to the study drug being underestimated.

For the purpose of this study the nocebo response is defined as any a treatment emergent adverse events (TEAE) or clinical worsening in people treated with a placebo. That involves collecting data on both TEAEs and rating mania and depression.

The data used in this study was from a randomized placebo controlled clinical trial of olanzapine monotherapy for bipolar disorder versus placebo and several comparators (haloperidol, valproate, olanzapine-fluoxetine combination [OFC]).  The trials occurred between 1996 and 2007.  There were a total of 9 studies and 7 were published.

Only data for the patients randomized to placebo (N = 1185/4680) were used for the purpose of this study and meta-analysis.  866/1185 or 68% experienced  (TEAE) and 4.6% discontinued the study due to a TEAE.  Typical rating scales for mania and depression were used to rate symptoms. TEAEs were significant ranging from 3% to 11.8% of the placebo treated group.  Headache, insomnia , somnolence, anxiety, nausea, diarrhea, irritability, and agitation all occurred in over 5% of the placebo treated patients.  Median time to report the TEAE was 16 days with the longest time of 37 days.

Apart from the TEAEs, a significant number of the placebo treated patients experienced clinical worsening as noted on the rating scales for depression (321 or 27%), mania (585 or 49%), or global function (278 or 23%).

The 806 patients reporting TEAEs reported a total of 1,119 nocebo events.

TEAEs were associated with not being treatment naive, being obese, being located in the US, and participating in an earlier study.  There were no significant difference based on gender or smoking status.

A major limitation of the study is that it is not possible to detect if clinical worsening is a nocebo effect or and the effect of worsening illness.

In their discussion the authors point out that the evidence is that the nocebo effect is significant in clinical trials.  Of all of the possible correlates they studied they di not find any that were useful to predict who might be a nocebo responder.   They discussed some psychological theories and in a couple of additional papers discuss the putative neurobiological underpinnings of both the placebo and nocebo effect.  Certainly any effect that leads to 4.5% or placebo treated patients discontinuing the study is significant.  Until the nocebo effect is better characterized we probably do not have an adequate estimate of the side effect profiles.  The authors describe is as similar to the placebo response as "an expected consequence of exposure to therapy."

The nocebo response may be less clear in looking at the therapeutic effects of medication.  I think it is good to remember that true nocebo/placebo effects are estimated on the placebo response.  In other words a 20% placebo response rate means that 20% of the actively treated group also responded to placebo.  Hence, if 68% of the placebo treated group experience TEAEs and 4.5% discontinue the study on that basis - what happened when those number are applied to the actively treated group?  It would generally mean less subject carried forward in an intent-to-treat analysis and and a more favorable side effect profile if the nocebo responders could be accurately identified. A good place to start to look for more accurate numbers and methods of identification may be in large scale medicine studies looking at an identifiable quantitative endpoint like blood pressure.  The nocebo effect is easier to sort out with a medication that has a clear effect on a more easily measured parameter.

Clinicians are left with estimating the likelihood of a TEAE or nocebo response based on the likelihood of a patient exhibiting a particular side effect.  A low likelihood of a particular presentation is fairly frequent in clinical practice and continuing the medication in those circumstances often comes down to clinical necessity.  As an example, the patient has a vague TEAE, but learns from the physician that there are no other medications that can be prescribed for the problem.

Nocebo responses are certainly out there.  Clinically we can be more specific until there is better research guidance on what to do about it.  I have had conversations with many people who were interested in the placebo response or why a particular pattern of responding to a therapeutic intervention may have been established.     



George Dawson, MD, DFAPA


References:

1: Dodd S, Walker AJ, Brnabic AJM, Hong N, Burns A, Berk M. Incidence and characteristics of the nocebo response from meta-analyses of the placebo arms of clinical trials of olanzapine for bipolar disorder. Bipolar Disord. 2018 Jun 21. doi: 10.1111/bdi.12662. [Epub ahead of print] PubMed PMID: 29926533.

Attributions:

Figure at the top is stock photo from Shutterstock per their licensing agreement by kasezo entitled:

Stock illustration ID: 284558927 conceptual 3d design of false pill.( placebo and nocebo effect.red and green colored version)

A Stress Test.... Free Associations

I was just starting to breathe a little heavier.  The nurse running the test has been talking to me - continuously for the last nine minutes.  She was bright, pleasant, a great conversationalist but more to the point - everything she said seemed highly relevant. From time to time she would ask how I was doing, check my blood pressure and tell me what my heart rate was.  Some time at about the 9 minute mark she said that I might need to break into a jog for the next level.  It was a 16% grade at 4.1 mph.  The treadmill tilted up and it was a smooth transition.  I was still walking at a fast pace.  "Your heart rate is 160 are you OK?"  I was feeling very good.  Still talking in full sentences and not feeling stressed at all.  My left knee was sore and I said: "My knee is sore and I don't want to break into a jog.  I will complete this stage and call it a day."

I did have room at the end and am fairly confident I could have knocked off the next stage.  I have done it many times in the past starting with a test at about ago 42.  There were a number of considerations holding me back.  The knee.  It was nothing big.  When you exercise a lot as an adult - episodic knee pain is all part of it.  Secondly, a history of paroxysmal atrial fibrillation.  I probably got it in the first place from running heart rates too high for my age.  I did not want to flip into another episode of atrial fibrillation.  Third, the target rate.  Before starting, the supervising nurse told me that the target heart rate for a guy my age was 140 bpm and I was over that with no signs of ischemia or more importantly a widening QRS interval (I take flecainide).  Fourth, I was just happy to be there.  Even though I have had 5 exercise stress tests over the last 25 years, the last one was at the Mayo Clinic about 10 years ago.  These things are a lot less certain with age. As I was on the treadmill, I kept thinking of a review I read in the Medical Clinics of North America many years ago: "40% of 85 year olds have significant coronary artery disease".  Of course those are the 85 year olds who survived to that age.

I had other associations while I was walking and talking. I take a cardiac history on every person I talk with. Some are more detailed than others. I know a number of ways that stress tests can be failed. I know from talking with people what happens when your ECG suddenly shows signs of ischemia. Generally the next step is a Cardiologist spraying nitro into your mouth.  I also know that passing a stress test is a generally a good sign, but it is not a guarantee. Nothing in medicine is.  Too many people have told me about cardiac problems in the absence of a positive stress test, including an infarction in the absence of any occlusions.  Irrespective of the result, I would maintain humility and strive even more to avoid the trans fats that are quantitatively too low to make it on the food label.  And of course all of that bakery with thick frosting - the first display you encounter in any supermarket.           

I had the exercise stress test two weeks ago.  Four days earlier I was doing my usual dictation of an assessment in my office and as I stretched back - I experienced an intense sharp burning pain going down the left side of my sternum.  It lasted about 5- 10 seconds.  I have been having this pains for at least a year all over the chest, left shoulder and back.  At one point they were clearly musculoskeletal in origin and I could replicate them by certain movements or flexing certain muscles.  But then the discriminatory ability was gone.  All of the tricks I learned in medical school and residency about the  difference between musculoskeletal pain and true cardiac pain or angina did not apply.  One of the things they never teach you is that when you get old - all of the routine pains that you live with every day meld into vague pains all over your torso.  Was that chest pain or did it originate in my back, neck or shoulder?  Arthritic pain or pain from trying to do too many pull ups last night?  At some point I just decided to go in to see my internist to see if we could figure it out.

My internist has known me for 30 years.  Any chest pain in the early part of that period was immediately dismissed as musculoskeletal pain.  He knew I was a compulsive exercise fanatic and between the ages of 30 and 55 probably cycled 200 miles per week or the equivalent. In the winter, I would speedskate as much as possible.  My goal was to end the season by doing as many laps as possible in an hour on the John Rose Oval - one of the few refrigerated speedskating outdoor tracks in North America.  Doing that kind of exercise gets the heart rate up to very high levels.  During interval training up to 190+ beats per minute.  Whenever the subject came up during those years my internist would say: "You do a stress test every time you exercise".

That all changed at age 55.  I was out doing a warm up on the speed skating track.  I looked down at my heart rate monitor and it read 170 bpm.  One lap later it was chirping loudly and now it read 240 bpm.  I felt my carotid pulse and it was the irregularly irregular rhythm of atrial fibrillation.  That led to 2 hospital admissions, 2 cardioversions, 2 consultations with a sports cardiologist at the Mayo Clinic and 2 exercise stress tests on a bicycle at Mayo.  I ended up on flecainide  with the advice to consider an ablation procedure at some point in the future as long as the flecainide continued to work and "if the technology improves".  That is a direct quote from one of my electrophysiologists.

During the bicycle stress tests, I ran my heart rate up to 170 bpm and could have gone higher, but was concerned about triggering another episode of atrial fibrillation that would no longer respond to flecainide.  On echocardiography, I have features that are seen in some series of cyclists who do high levels of dynamic exercise - primarily an large left atrium and a slightly enlarged aortic root.  During dynamic exercise, there is a steady increase in blood pressure despite the fact that stroke volume peaks at about 120 bpm and main contributor after that point is heart rate and sympathetic nervous system output.  My adaptation was to try to keep my heart rate at 140 bpm or lower when exercising and lately 130 bpm.  It is good to know I can go higher even for brief periods of time.

So the coronary arteries may be OK, but that leaves paroxysmal afib and the enlarged aortic root/aorta.  We have only recently discovered the role of the layered extracellular matrix in aortic anatomy. Like most of these structures disruption of those layers can result in permanent weakness.  It is also known that high levels of dynamic exercise results in aortic enlargement.  I have not seen any outcome studies of those individuals - but it would be useful to find an expert. 

My next step is to see a Sports Cardiologist about the afib and aorta.  I anticipate that he or she will wonder about why there is an old man in the examination room trying to get as much performance as possible out of an aging cardiovascular system.  If that question comes up, the response is simple:

"I don't want to die on the side of the road from a blown aorta because I tried to race a 40 year old up a hill.  I need your most conservative estimate on how I can prevent that."

And so it goes......


George Dawson, MD, DFAPA


Supplemental:

Previous exercise stress test done on a bike at the Mayo Clinic in 2012 showed a similar result (possibly low BP and heart rate this time but I find that it is easy to over rev on a bike as opposed to a treadmill).