diagnostic versus classification criteria: a continuum

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1 Diagnostic versus Classification Criteria: a continuum Hasan Yazıcı University of Istanbul

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Diagnostic versus Classification Criteria: a continuum. Hasan Yazıcı University of Istanbul. 1. I have no conflicts of interest. Plan & Summary. Pre-test disease odds. Diagnosis. Classification. Ottawa Ankle Rules. IG Stiell et al. Ann Emerg Med 1992 . - PowerPoint PPT Presentation

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Page 1: Diagnostic  versus Classification Criteria: a continuum

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Diagnostic versus

Classification Criteria:a continuum

Hasan YazıcıUniversity of Istanbul

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I have no conflicts of interest.

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Plan & Summary

Pre-test disease odds

Classification Diagnosis

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Ottawa Ankle Rules

IG Stiell et al. Ann Emerg Med 1992

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EULAR/ACR Vasculitis Criteria Group (2008)

“Perhaps the most robust criteria pertain to Behçet’s disease, where international collaboration has led to a validated proposal effective for both clinical and research purposes.”

“The challenge of producing validated diagnostic criteria for these heterogeneous diseases that are suitable for use in clinical research as a classification tool, is a formidable one. However, as the international community has exemplified with Behçet’s disease, it is achievable.”

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International Study Group Diagnostic Criteria (Lancet, 1990)

Oral ulcers (~100%) +

Two of below: a. Genital ulcers (80%)b. Skin lesions (80%)c. Eye lesions (50 %)d. Pathergy (50 %)

Classification

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Methods 914 unselected (366 from Iran..... 9 from France) patients with

BS from 12 centers in 7 countries 28 BS patients without OU excluded Control group: 308 patients with connective tissue diseases,

including 97 with OU only Study questionnaire based on previously published BS criteria

sets Individual disease features of a random sample (60%) were

compared with those in the control group. Sensitivities, specificities, log likelihood ratios and expected weights of evidence were calculated for each symptom or sign.

Features were added to the criteria set up to the point at which there was no further contribution to the criteria by the expected weight of evidence of a particular disease feature.

The new criteria set were further validated in the 40% sample.

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Turing’s expected weight of evidence

It is the sum of the individual weights of evidence (logeLR).

It represents the weight of a question while the answers make up individual weights of evidence.

DJ Spiegelhalter Clin Gastroenterol 1985

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Issuesapart from the – by definition- circular nature of the

exercise The initial internal validation was, in

fact, an internal check of the initial randomization.

The questionnaire did not seek for the frequency of various features of diseases that made up the control group, among the BS patients.

All work and validations were retrospective.

No attempt at confidence intervals.

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ACR Vasculitis Criteria*CHCC Vasculitis Criteria **

Among 198 patients (51 with vasculitis) the positive predictive value of ACR criteria ranged 17% - 29% (JK Rao et al Ann Int Med 1998)

CHCC criteria correctly identifed 8/27 patients with Wegener’s and 4/12 with MPA (SF Sorensen et al Ann Rheum Dis 2000)

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Hunder GG. The Use and Misuse of Classification and Diagnostic Criteria for Complex Diseases. Ann Intern Med 1998

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ACR Classification criteria RA SLE Sjogren Vasculitis Fibromyalgia JRA Osteoarthritis Scleroderma

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The “circular” logic in diagnostic/classification criteria for conditions which lack a specific laboratory or a histological feature

JF Fries Arch Intern Med 1984

A perpetual motion machine, 1660Wikipedia

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Pre-test disease odds

Classification Diagnosis

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Bayes theorem in c/d

post-test odds = pre-test odds x LR

LR = likelihood ratio

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Bayes theorem in c/d

post-test odds = pre-test odds x LR

LR = likelihood ratio

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Bayes theorem in c/dPre-test odds

post-test odds = pre-test odds x LR

actual disease prevalance (when c/d) or

frequency of disease manifestations in the disease studied vs. in diseases that come into the differential diagnosis (when formulating LR’s)

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Bayes theorem in c/d

post-test odds = pre-test odds x LR

LR = likelihood ratio

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Bayes theorem in c/d

post-test odds = pre-test odds x LR

LR = likelihood ratioc/d criteria

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Bayes theorem in c/dLikelihood ratio (LR)

post-test odds = pre-test odds x LR

+ LR = sensitivity/1-specificity or % true positives/% false positives - LR = 1-sensitivity or % true negatives/% false negatives

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The Circular Nature We use elements of pre-test odds (es)

to estimate the LR’s. From these LR’s we estimate the

classification LR (criteria). We use another (but related!) pre-test

odds to estimate the post-test odds (c/d).

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Fulfilling the ISBD Criteria: What does it mean? (sensitivity = 90%; specificity =95%)

Criteria + (+LR) : 0.90/1-0.95 = 18 x pre-test odds Criteria - (-LR) :

1 - 0.90 /0.95 = 0.10 x pre-test odds

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Sensitivity = 0.95 (0.90)Specificity = 0.95

+ LR Sensitivity/1-Specificity = 19 (18)

- LR1- Sensitivity/Specificity = 0.05 (10)

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Sensitivity = 0.90Specificity = 0.97 (0.95)

+ LR Sensitivity/1-Specificity = 30 (18)

- LR1- Sensitivity/Specificity = 0.10 (10)

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90 92 94 96 980

102030405060708090

100

(+) LR(-) LR

95 96 97 98 990

102030405060708090

100

(+) LR(-) LR

Sensitivity constantIncreasing specificity

Specificity constantIncreasing sensitivity

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“Diagnostic criteria apply to individual persons rather than groups. In order to establish a correct diagnosis and to ensure that cases are not missed, such criteria should have a high sensitivity (especially for early cases of a particular disease, e.g. early ankylosing spondylitis) and will often include items that are present already early in the disease course. Such an approach will reduce specificity, which means that more false positives might be expected. Diagnostic criteria are mainly applied in clinical practice, an environment in which, at least for a limited follow-up period, a false-positive diagnosis is considered more acceptable than a false-negative rejection of a diagnosis.”

Rheumatology 4 Ed. 2008

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Classification vs. Diagnostic Criteria ???Classification

For groups

High specificity

Diagnosis

For individuals

High sensitivity

Rheumatology 4 Ed. 2008

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“With this adaptation the sensitivity increased from 76% for the original New York criteria to 83% for the modified New York criteria, whereas the specificity only decreased from 99% to 98%.”

Rheumatology 4 Ed. 2008

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LR’s and Odds of disease (assuming 1/100 frequency of AS)

Original NY criteria

Sensitivity: 76% Specificity: 99% + LR: 0.76/1-0.99= 76 (3.2:1)- LR: 1-0.76/0.99= 0.24 (500:1)

Modified NY criteria

Sensitivity: 83% Specificity: 98% + LR: 0.83/1-0.98= 42 (0.7:1)- LR: 1-0.83/0.98= 0.17 (588:1)

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Diagnosis is classification of the individual patient.

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What to do?

Define well your pre-test odds.

Go to well defined practices (subspecialties).

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Ann Intern Med 1999

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Causes of Uveitis (%) in Japan* & USA**

Japan (3060) USA (1237)Idiopathic 38.9 34.9B27 assoc. 1.5 10.4Sarcoidosis 13.3 9.6JRA 0.5 5.6SLE 1.0 4.8Behçet 6.2 2.5HIV 0 2.4

* H Goto et al. Jpn J Ophtalmol 2007; ** A Rodriquez et al. Arch Ophthalmol 1996

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Conclusions There are no separate classification or

diagnostic criteria but c/d criteria.

Classification and diagnosis are components of a continuum of which epidemiology is a most integral part.

To make a diagnosis is not an art but science backed by experience and arithmetic.

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A Proposal Avoid attempts for “universal” disease

criteria and

Aim for classification/diagnostic criteria for subspecialties

H Yazici et al. Arthritis Rheum, 2008

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Proposed Scheme of Preparing c/d Criteria in a Subspecialty Setting Retrospective tabulation of demography and

diagnoses (old & new pts.; 6 mo.) Same on new patients with checklists

(crossed) of symptoms/findings /lab./rad./hist. (6 mo.)

Estimation of clinical prediction rules and classification criteria after selecting the comparator groups

Internal and external validation of the criteria in the same and different settings (new patients; 6 mo.)

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9/10 = 900/1000

MC Reid, MS Lachs, AR Feinstein JAMA 1995

9/10 ≠ 900/1000

Confidence Intervals