A method for systematic assessment of the relative prognostic significance of symptoms and signs in patients with a chronic disease II. Analysis of validity of model and derivation of major prognostic stages

Winkel, Per; Lyngborg, K; Olesen, Knud H.; Meibom, J; Hansen, Pia Skov

doi:10.1016/0010-4809(73)90078-5

Cited by 1 publication

(1 citation statement)

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“…Should two more available or quicker tests be substituted? Decision analysis methods may be useful in addressing this class of questions [12, 14, 19, 22J. Secondly, the physician typically seeks answers to more than one question when investigating a patient and is thus interested in the observations necessary and sufficient to answer a set of questions [26,27]. Although this problem is not discussed above, such a feature could be added as a relatively simple extension, if demand warranted.…”

Section: Discussionmentioning

confidence: 99%

Determining the Most Valuable Clinical Variables : a Stepwise Multiple Logistic Regression Program

Coles¹,

Brown²,

Engelhard³

et al. 1980

Methods Inf Med

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In solving a clinical problem of diagnosis, prognosis, or treatment choice, a physician must select from among a large group of possible tests. In general, an ordering exists specifying which tests are most valuable in providing relevant information concerning the problem on hand. The computer program package to be described (MW) extracts appropriate data from the ARAMIS data banks and then analyzes the data by stepwise logistic regression. A binary outcome (diagnosis, prognostic event, or treatment response) is sequentially associated with possible tests, and the most powerful combination of tests is identified. For example, the most valuable predictor variable of early mortality in SLE is proteinuria, followed sequentially by anemia and absence of arthritis. Experience with these techniques suggests : 1. optimal certainty is usually reached after only three or four tests; 2. several different test sequences may lead to the same level of certainty; 3. diagnosis may usually be ascertained with greater certainty than prognosis; 4. many medical problems contain considerable non-reducible uncertainty; 5. a relatively small group of tests are typically found among the most powerful; 6. results are consistent across several patient populations; 7. results are largely independent of the particular statistic employed. These observations suggest strategies for maximizing information while minimizing risk and expense.

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Section: Discussionmentioning

confidence: 99%