[No SPF Record] Re: [IMPROVEDX] The role of experience in hypothesis verification phase of diagnosis

Peggy Zuckerman peggyzuckerman at GMAIL.COM
Wed Jun 27 21:44:26 UTC 2018


Rory Jaffe's last comment as to the 'correct course of action for the
patient' is interesting to me in my role as patient, trying kicking and
screaming into this fray.  He does not say what the role the patient would
be in the determining the 'correct course of action for the patient'.  I
shall assume that Jaffe thinks that patients, given credible and accessible
information could have a say, and also would acknowledge that there may NOT
be a single 'correct' course of action" and certainly not for every
patient.

Peggy Zuckerman

Peggy Zuckerman
www.peggyRCC.com

On Wed, Jun 27, 2018 at 10:03 AM, Rory Jaffe <rjaffe at chpso.org> wrote:

> I agree. I’m not a defeatist regarding this complexity: as complicated as
> a correct model would be, we can construct simplified models that, at a
> specific point in time (e.g., initial presentation), provide a starting
> point for a well-informed assessment of the situation—e.g., using QALYs to
> produce the optimal model solution. We can even provide algorithms for
> common initial presentations that would be particularly useful when
> potentially urgent issues arise (e.g., the emergency department).
>
>
>
> I’ll add one more piece to the complexity picture: utility. In a number of
> common circumstances, pursuing a correct diagnosis is harmful. For example,
> low-risk prostate cancer, where the cure is worse than the disease. By the
> way, this is why I don’t like the NAM definition of diagnostic error—it
> focuses on correct diagnosis, not the correct course of action for the
> patient, which I believe is more important than the diagnosis itself.
>
> *From:* John Brush <jebrush at me.com>
> *Sent:* Wednesday, June 27, 2018 4:29 AM
> *To:* Society to Improve Diagnosis in Medicine <IMPROVEDX at LIST.
> IMPROVEDIAGNOSIS.ORG>; Rory Jaffe <rjaffe at chpso.org>
> *Subject:* Re: [IMPROVEDX] [No SPF Record] Re: [IMPROVEDX] The role of
> experience in hypothesis verification phase of diagnosis
>
>
>
>             I think this is why physicians almost all choose to use
> subjective probabilities, rather than pulling out a nomogram or calculator
> to compute post-test probabilities. They intuitively take into account the
> probability and relative strength of a test result, but also the potential
> consequences of making/missing a particular diagnosis. Still, I think that
> we can calibrate our intuition with some simple numbers derived from
> clinical epidemiology that will help us avoid common fallacies. We can’t
> just wing it. We need to apply the science of medicine to individual
> patients and there are ways to do that.
>
>             It is important to remember two potential pitfalls: base-rate
> neglect and spectrum bias. It would be foolish to test for pheochromocytoma
> every time you see a patient with newly diagnosed hypertension. Persistence
> and follow up allows recognition of patients with refractory hypertension,
> weight loss, orthostatic hypotension, tachycardia, and other clues where
> pheochromocytoma may be a plausible diagnosis, but screening up front would
> be a false-positive-test generating strategy.
>
>             Spectrum bias occurs when you define the sensitivity and
> specificity of a test in one setting and use the test in a different
> setting with a lower prevalence of disease. Most people think that the
> operating characteristics of a test are fixed characteristics of the test
> itself, but as Alvin Feinstein showed a long time ago, they are not. If you
> subsequently use a test in a setting where the prevalence of disease is
> lower, your false positive rate goes up, decimating your specificity. Your
> positive likelihood ratio (true positive rate/false positive rate, or hit
> rate/miss rate) plummets. It’s no wonder that we don’t believe troponin
> levels anymore. They are sent off on everyone who comes through the door,
> regardless of pre-test probability.
>
>             There is a science to the art of medicine.
>
> John
>
>
>
> John E. Brush, Jr., M.D., FACC
>
> Professor of Medicine
>
> Eastern Virginia Medical School
>
> Sentara Cardiology Specialists
>
> 844 Kempsville Road, Suite 204
> <https://maps.google.com/?q=844+Kempsville+Road,+Suite+204+%0D%0A+%0D%0A+%0D%0A+Norfolk,+VA+23502+%0D%0A+%0D%0A+%0D%0A+757&entry=gmail&source=g>
>
> Norfolk, VA 23502
> <https://maps.google.com/?q=844+Kempsville+Road,+Suite+204+%0D%0A+%0D%0A+%0D%0A+Norfolk,+VA+23502+%0D%0A+%0D%0A+%0D%0A+757&entry=gmail&source=g>
>
> 757
> <https://maps.google.com/?q=844+Kempsville+Road,+Suite+204+%0D%0A+%0D%0A+%0D%0A+Norfolk,+VA+23502+%0D%0A+%0D%0A+%0D%0A+757&entry=gmail&source=g>
> -261-0700
>
> Cell: 757-477-1990
>
> jebrush at me.com
>
>
>
>
>
>
>
> On Jun 26, 2018, at 4:59 PM, Rory Jaffe <rjaffe at CHPSO.ORG
> <rjaffe at chpso.org>> wrote:
>
>
>
> This discussion illustrates the general weakness of simple mathematical
> models for diagnosis. Prioritization is not just on raw likelihood (see
> Peter’s excellent discussion)—time and severity play major factors, as well
> as reversibility of changes not caught beforehand (e.g., the implications
> of an abdominal aortic aneurysm that may rupture vs a herniated disc
> protruding that may threaten to press on the cauda equina vs poor lifting
> habits causing chronic muscle injuries). And common sense needs to be used,
> as no model can be comprehensive enough to always produce a reasonable
> prior probability, though I would hope that sex-specific diagnoses
> would—but even there, you could be fooled if the patient’s current
> identified sex (e.g., female) is different than the one she was born
> with—she may still get prostate cancer.
>
>
>
> Models are still useful if sophisticated enough to include these
> considerations, and statistical analysis of a patient’s probabilities is
> still useful, but comparing simple odds, whether using Bayesian or
> frequentist methods, is not.
>
>
>
> Rory
>
>
>
> *From:* Sittig, Dean F <Dean.F.Sittig at UTH.TMC.EDU
> <Dean.F.Sittig at uth.tmc.edu>>
> *Sent:* Tuesday, June 26, 2018 11:06 AM
> *To:* IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
> <IMPROVEDX at list.improvediagnosis.org>
> *Subject:* [No SPF Record] Re: [IMPROVEDX] The role of experience in
> hypothesis verification phase of diagnosis
>
>
>
> The power of the Bayesian method is in helping put the evidence into
> context. If we would take your example say of a positive pregnancy test
> which I would venture carries a likelihood ratio of 10 or more. If your
> patient and the purported source of the sample is a male then the a priori
> probability of a positive pregnancy test is zero. Therefore using bayes’
> formula one should treat the positive pregnancy result as most likely an
> error rather than the first case of male pregnancy in the history of
> mankind.
>
> Dean
>
> Sent from my iPhone
>
>
> On Jun 26, 2018, at 10:34 AM, Jain, Bimal P.,M.D. <BJAIN at PARTNERS.ORG>
> wrote:
>
> Thanks Dr. Elias for your comments.
>
> I agree in general with your description of the diagnostic process in an
> office setting.
>
> The point I am making in my hypothesis verification paper is that if a
> highly informative test result with likelihood ratio greater  than 10 is
> observed in a patient, then the definitive diagnosis of a disease in this
> patient is validated by our experience of the accuracy of this diagnosis in
> practically every patient seen by us regardless of prior probability.
>
> For example, if we suspect hypothyroidism  in a patient with fatigue seen
> in office and find elevated TSH, the definitive diagnosis of hypothyroidism
> would be validated by our experience of the accuracy of this diagnosis in
> other patients regardless of prior probability seen by us in the past.
>
> I would like to point out the correct technical meaning of the term
> ‘likely’ employed in your opening sentence by substituting ‘disease’ for
> ‘hypothesis’ and ‘test result’ for evidence.
>
> The likelihood of a disease given a test result is proportional to the
> probability of a test result given the disease.
>
> For example, the likelihood of acute MI given acute EKG changes is
> proportional to the probability of acute EKG changes given acute MI.
>
> Thus it is customary to speak of how likely acute MI is, given acute EKG
> changes.
>
> As far as I know, the term likely or likelihood is not used to refer to
> frequency of a test result given a disease.
>
> The correct term would be probability of test result given a disease.
>
> In Bayesian analysis, we are assessing probability of a disease given the
> test result.
>
> The likelihood of a disease given the test result is known to us which is
> employed as part of likelihood ratio in Bayesian analysis.
>
>
>
> Bimal
>
>
>
> *From:* Elias Peter [mailto:pheski69 at GMAIL.COM <pheski69 at GMAIL.COM>]
> *Sent:* Wednesday, June 20, 2018 9:07 PM
> *To:* IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
> *Subject:* Re: [IMPROVEDX] The role of experience in hypothesis
> verification phase of diagnosis
>
>
>
> *        External Email - Use Caution        *
>
> I have several comments to make.
>
>
>
> First, I see Bayesian assessments as telling us how likely it would be for
> that evidence given a hypothesis, not how likely the hypothesis is given
> the evidence. A recent article offered a wonderful analogy I wish I had
> heard years ago: given a dog (test result) we can be pretty certain there
> are four legs (the evidence), but given four legs (the evidence) we need
> much more information to know if we are dealing with a dog, camel, or
> turtle.
>
>
>
> Second, I think it is a mistake - or at least, too narrow a framing - to
> see diagnosis as an event rather than a process. This may reflect my 40
> years in primary care, as I have noticed during my career that clinicians
> who work in settings like intensive care units or acute trauma centers have
> a very different process when caring for undiagnosed patients. In primary
> care (and in many specialties that deal mostly with chronic illness) it is
> often that one is best and most efficient making a diagnosis over time
> rather than during a single encounter. In this setting, it is unusual to be
> in the position of having a patient with a clinical snapshot (I don’t say
> picture, because it really IS a snapshot, obtained relatively quickly and
> in a limited context) and then having to make a diagnosis based on a test
> result.
>
>
>
> Third, at least in primary care, a very substantial number of diagnoses
> are made by a clinical picture over time (natural history). We don’t have a
> diagnostic ‘test’ for anxiety, depression, most of the causes of low back
> pain, most of the causes of headache, most of the causes of fatigue…   In
> these settings the process is something like this:
>
> ?         Are there any things I can’t miss, right now, in this visit,
> without putting the patient at immediate risk?
>
> o    If so, what can I do to determine their presence or absence.
>
> o    If not, how do I remember this list and refer back to it if the
> picture changes?
>
> ?         What are the most likely causes of what I am seeing and hearing?
>
> ?         Are there any likely causes of what I am seeing and hearing
> that I can easily and efficiently prove or disprove?
>
> ?         Have a conversation with the patient about the diagnostic
> possibilities, the degree of certainty and uncertainty.
>
> ?         Ascertain what part of the clinical picture the patient is most
> concerned about. (Some patients want a diagnosis and some want treatment
> and some want both, depending on the setting.)
>
> ?         Given that we have a collection of possibilities of varying
> severity and frequency and likelihood and we know what the patient’s
> preferences are (because we asked her and listened), what is a reasonable
> approach to managing the problem, including but not limited to:
>
> o    Work on diagnosis, hold off on treatment?
>
> o    Work on diagnosis, treat symptoms?
>
> o    Treat symptoms and observe the course. (Here natural history is ‘the
> test’ we are using, but it doesn’t have a ‘result’ in the sense of Q waves
> or blood sugar or potassium.)
>
> o    Not treat symptoms and observe the course.
>
> o    Trial and error - treat something and see if it works.
>
>
>
> Very few of my patients with back pain or headaches or fever have any
> ‘tests’ done. In primary care, depending on the patient context, fatigue
> may be best diagnosed by history and a brief exam - though there are
> settings where tests are clearly essential. I doubt that more than 2
> patients a day needed a ’test’ in the sense that is being discussed in
> these threads. (My daily volume was 18-20 on a bad day, 16 on a good day.)
>
>
>
>
>
> My point here is that framing the diagnostic process around how one
> interprets a test result considers a very limited piece of the diagnostic
> universe. It is important when it is germane - when I present to an ED
> poorly responsive and hypotensive, I want the test results to be properly
> and quickly evaluated. However, from my PCP, patient, and caregiver
> perspectives I think this is a tiny part of the diagnostic universe and not
> easily generalized across the broad landscape of medicine. I am much more
> interested in and concerned about ways to improve the diagnostic process in
> the 90% (or more) of circumstances where the results of ‘a test’ are
> unlikely to be definitive. Of course, that reflects my 40 years in the
> primary care front line where ambiguity is part of the air we breathe.
>
>
>
> Peter
>
>
>
>
>
>
>
>
>
>
>
>
>
> On 2018.06.20, at 12:46 PM, Jain, Bimal P.,M.D. <BJAIN at PARTNERS.ORG>
> wrote:
>
>
>
> In this attached paper, I discuss that experience plays an important role
> in validating the verification of a diagnostic hypothesis by a test result.
> As our experience is gained from a heterogenous population of patients with
> varying prior probabilities, this validation is represented by a confidence
> and not by a Bayesian argument.
>
> Please review and comment on this paper.
>
> Thanks.
>
>
>
> Bimal
>
>
>
> Bimal P Jain MD
>
> Northshore Medical Center
>
> Lynn MA 01904.
>
>
>
>
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Moderator: David Meyers, Board Member, Society to Improve Diagnosis in Medicine


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