?Datamining for pernicious anemia?

Janel Hopper janelhopper at COMCAST.NET
Mon Dec 9 19:02:23 UTC 2013


Thank you all for your thought-provoking remarks. In my secondary research, I have only come across mention of percentages on one occasion and that is Dr. Patrick C.J. Ward’s paper cited below that links pernicious anemia with Eaton Lambert myasthenic syndrome. As Dr. Hoffer mentions, perhaps Mayo is a promising repository of such information.

 

Clin Lab Med. 2002 Jun;22(2):435-45.

Modern approaches to the investigation of vitamin B12 deficiency.

Ward PC.

Source

Department of Pathology and Laboratory Medicine, University of Minnesota, Duluth School of Medicine, 10 University Drive, Duluth, MN 55812, USA. path at d.umn.edu

 

I was found to have the Eaton Lambert antibodies. Eaton Lambert is mentioned in Dr. Ward’s paper as overlapping 20% of the time with pernicious anemia. It was not felt that I exhibited the characteristics of autoimmune Eaton Lambert, and instead, I received intensive cancer screening that lasted several years due to the known association 50% of the time of those calcium channel autoantibodies being associated with lung or other organ cancers.

 

Throughout the literature, there are mentions of “known” associations between thyroid disease and pernicious anemia. Old textbooks, such as Francis S. Greenspan, “Basic and Clinical Endocrinology,” Third Edition, copyright 1983/1991, cites four mechansims of known anemia in thyroid patients, with the fourth being pernicious anemia. Subsequent editions of this textbook that I could point you to on Google books do not note this association. Perhaps since it failed quantification, it is simply being deleted from our knowledge base. So, because we could not previously quantify this information, it is being lost. I propose that the research seek to quantify it.

 

I quote from the Third Edition textbook that I have here beside me: “The pernicious anemia is often part of a spectrum of autoimmune diseases: myxedema due to chronic thryoiditis, with thyroid autoantibodies present; pernicious anemia with parietal cell autoantibodies present; diabetes mellitus with islet cell autoantibodies present; adrenal insufficiency with adrenal autoantibodies present; etc (see Chapter 28).

 

If one searches the term “thyrogastric,” you will uncover a body of research where the known thyroid/pernicious anemia association was developed.

 

I am fairly certain that there is another body of literature linking diabetes and pernicious anemia. From my participation on a pernicious anemia newsgroup, I am aware that there is an overlap with celiac disease. I am one of the 5% without proper celiac blood autoantibodies, but who has a celiac diagnosis for a prominent institution.

 

I would think that a non-profit such as Kaiser Permanente which has leadership in electronic records and an interest in correctly identifying and treating pernicious anemia (which is very cheap to treat if caught early) would be an ideal institution to undertake this project. Perhaps Dr. Kanter would be so kind as to give his opinion. I would be very happy to see it undertaken anywhere.

 

Janel

On Dec 9, 2013, at 6:44 AM, Hoffer, Edward P.,M.D. wrote:

> The task is daunting but at least partially doable.  When we began putting together the DXplain database in the mid-1980's, we found that textbooks were of limited use.  Textbook descriptions of diseases tend to use "weasel words" like "often" or "may be present."  The problem is that if you ask a group of doctors to quantify "often" you will get answers ranging from 20% to 80%.  For many conditions, valid numeric data is available in published case series.  We search hard for these and use them when available.  Of course, there is always the objection that these may be biased by geographic location, by coming from a referral center, etc, but at least 100 cases from the Mayo Clinic with precise quantification of findings is a big step up from "often."
> Edward Hoffer MD, MGH Lab of Computer Science
> 
> From: robert bell [mailto:rmsbell at ESEDONA.NET] 
> Sent: Sunday, December 08, 2013 9:33 PM
> To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
> Subject: Re: [IMPROVEDX] ?Datamining for pernicious anemia?
> 
> FOR POSTING TO THE LIST  
> 
> Thanks Janel,
> 
> You bring up the need of creating profiles for immune complex disease patients, with percentages for each symptom - when we get to computer use to better support diagnoses, we may be better to arrive at the answer more quickly.
> 
> How would we go about collecting such data. And who would do it?
> 
> And also percentages for the diagnose itself compared to all other diagnoses. 
> 
> For any diagnostic computer program to be reasonably accurate it would seem that % frequencies for symptoms and diagnoses would first be necessary.
> 
> It seems that we need better data on nearly everything, if significant progress is to be made in diagnostic accuracy.
> 
> Rob Bell
> 
> 
> 
> 
> On Dec 8, 2013, at 2:02 PM, Janel Hopper <janelhopper at COMCAST.NET> wrote:
> 
>> Hello All,
>> 
>> Thank you Dr. Kohn for bringing up my story of pernicious anemia again and giving me an opportunity to clarify a few things.  I just looked into Dr. Sanders book that you mention.  In the article excerpted from the same, she says:
>> 
>> "This patient’s hemogram would have shown anemia and almost certainly an elevated mean cell volume."
>> 
>> I had intermittent iron anemia for many years that was treated by my internist. I sometimes had a subnormal hematocrit that was attributed by a very well-known teaching hospital to be due to celiac and not investigated further at that time. I was taking high-dose vitamins, which was communicated to every physician.
>> 
>> A close examination of the medical literature will show that pernicious anemia can be doing neurologic, gastric and other tissue damage including bone, heart, and CNS without any overt macrocytosis necessarily appearing. A query into problems with B-12 blood testing, especially in cases of pernicious anemia, will retrieve a number of results in PubMed. If anyone is interested in links or further investigation into this, I would like to share more details. Any particulars of my experience needs to maintain the privacy of all the physicians and institutions along the way that certainly all did their best to help me.
>> 
>> When a patient keeps insisting that there is something physicially wrong but "the screen" (electronic medical record) already marginalizes a patient as having "imaginary pain," many subsequent physicians won't think anything needs re-thinking. I am lucky in that I could go for consultations across the country. I am also lucky that the national data record was not yet aggregated at that time.  Eventually (I had enough data points of my related autoimmune conditions), that I stumbled upon pernicious anemia as a related disease and possibility. I was lucky enough to be one with IF blocking antibodies, later also confirmed with parietal cell antibodies, elevated MMA and homocysteine. This simple, specific test (IF Blocking Antibody) that only cost me $35 has been available since 1983. In spite of numerous teaching hospital workups and awareness of my other autoimmune conditions, this test was never used until I requested it. After 40 years of work-ups, this was indeed a shocking finding.
>> 
>> Since decision support software is not widely adopted, a retrospective analysis of patients who have say known thyroid disease along with other, unclear diagnoses such as "fibromyalgia, chronic fatigue, irritable bowel syndrome, mitral valve prolapse, intention tremor, and somatic pain disorder" (all diagnoses I previously had), this population subset could be data-mined to sample test those who have a risk for undetected pernicious anemia.
>> 
>> I hope that some of you may be interested in learning from my experience. I am just a lucky layperson, so please correct me if I make errors. 
>> 
>> Janel
>> 
>> On Dec 7, 2013, at 10:23 PM, Kohn, Michael wrote:
>> 
>>> In sick (i.e. symptomatic) patients, there are two kinds of diagnostic error: we can fail to identify and treat the disease that is causing the illness or we can misdiagnose and inappropriately treat a disease that isn't causing the illness.
>>> 
>>> One of the participants on this thread mentioned pernicious anemia.  The Lisa Sanders book (Chapter 9) has an example of a delayed diagnosis of that disease.  I could see missing this as an explanation for chest pain in a busy ED and recommending outpatient evaluation, but it's hard to believe that it wouldn't be picked up eventually.    We also have to worry about overdiagnosis/misdiagnosis.  See Chapter 8 on chronic Lyme Disease.
>>> 
>>> Reducing both kinds of diagnostic error is a challenge.  Computerized decision support tools integrated into the EHR may be part of the answer, but we're not there yet.
>>> 
>>> MAK
>>> 
>>> Michael A. Kohn, MD, MPP
>>> 
>>> Associate Professor
>>> 
>>> Epidemiology and Biostatistics
>>> 
>>> Emergency Physician
>>> 
>>> Mills-Peninsula Medical Center
>>> 
>>> From: Alan Morris [Alan.Morris at IMAIL.ORG]
>>> Sent: Saturday, December 07, 2013 4:55 PM
>>> To: IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
>>> Subject: Re: [IMPROVEDX] Missed and Erroneous Diagnoses Common in Primary Care Visits
>>> 
>>> I propose that an error is any deviation from the intended, evidence-based, target decision.  Some errors are trivial and of little consequence.  Some carry a major risk to the patient. In an unusually tightly controlled ICU at the Hebrew University Hospital in Jerusalem, Gopher et al. reported about 174 clinician interactions/patient/day.  99% of these clinician interactions were performed correctly by RNs and MDs. (It is the rare, if any, clinical unit that can aspire to a 99% correct performance rate.)  However, the 1% error rate led to a major threat to life or limb per patient every other day, on average!  Most people think that technical rock climbing is a dangerous activity.  However, few climbers would ever tie onto a rope and climb, if they thought they would be subjected to a major threat to life or limb every other day because of error.
>>> 
>>> Surprising low clinician error rates associated with almost unachievable correct performance, can lead to unacceptable risks to patients.
>>> 
>>> Extrapolating these ICU data to the outpatient setting is difficult.  Nevertheless, I believe we should pay attention to all errors, and categorize them with respect to patient risk.
>>> 
>>> Have  a nice day.
>>> 
>>> Alan H. Morris, M.D.
>>> Professor of Medicine
>>> Adjunct Prof. of Medical Informatics
>>> University of Utah
>>> 
>>> Director of Research
>>> Director Urban Central Region Blood Gas and Pulmonary Laboratories
>>> Pulmonary/Critical Care Division
>>> Sorenson Heart & Lung Center - 6th Floor
>>> Intermountain Medical Center
>>> 5121 South Cottonwood Street
>>> Murray, Utah  84157-7000, USA
>>> 
>>> Office Phone: 801-507-4603
>>> Mobile Phone: 801-718-1283
>>> Fax: 801-507-4699
>>> e-mail: alan.morris at imail.org
>>> e-mail: alanhmorris at gmail.com
>>> 
>>> 
>>> 
>>> 
>>> 
>>> 
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>> 
>> 
>> 
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>> 
>> Moderator: Lorri Zipperer Lorri at ZPM1.com, Communication co-chair, Society for Improving Diagnosis in Medicine
>> 
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