Designing a simpler high blood cholesterol case detection strategy: are the advantages of the NCEP protocol worth the complexity?
OBJECTIVE
To determine whether the complex strategy of lipid measurements for the detection of patients with high blood cholesterol levels proposed by the first Expert Panel of the National Cholesterol Education Panel (NCEP) could be simplified without significant loss of accuracy.


METHODS
Decision-analysis-based model of competing case detection strategies as compared with the NCEP strategy. A Markov model was used to estimate numbers of people treated over ten years as a result of the different classification strategies.


METHODS
Conditional probabilities for the decision trees were derived from cholesterol distributions in national population-based surveys. Parameters for the Markov model were from published major epidemiologic studies and clinical trials.


METHODS
Misclassification to treatment vs non-treatment as a continuous function of the distribution of true low-density lipoprotein (LDL).


RESULTS
A simplified strategy was designed that screens high-risk persons with two LDL measurements and low-risk people with one cholesterol measurement followed by two LDL measurements if the initial value is high. This algorithm requires 37% fewer measurements to classify a population. The overall accuracy of classification to treatment based on the NCEP I cutoff points is high, with a positive predictive value of 95% and a negative predictive value of 87% (relative to 97% and 80%, respectively, for the NCEP I protocol). This strategy is very similar to published NCEP II guidelines. A strategy that recommends an LDL determination for everyone, as a recent NIH consensus panel suggested, also significantly reduces the number of measurements required by 48%. The positive predictive value is 93%, vs 97% for the NCEP I protocol. The negative predictive value is 92%, vs 80% for the NCEP I.


CONCLUSIONS
The complex measurement strategy initially proposed in the NCEP I guidelines did not improve accuracy of classification over the simpler and more convenient strategies that the authors evaluated and that have been substantially adopted in the NCEP II guidelines.
Hofer
T
T
Division of General Internal Medicine, University of Michigan, Ann Arbor.
Weissfeld
J
J
D000328:Adult; D002784:Cholesterol / Q000097:blood; D016001:Confidence Intervals; D003362:Cost-Benefit Analysis; D003663:Decision Trees; D006801:Humans; D006937:Hypercholesterolemia / Q000097:blood / Q000175:diagnosis / Q000517:prevention & control*; D008077:Lipoproteins, LDL / Q000097:blood; D008297:Male; D008390:Markov Chains; D008403:Mass Screening / Q000191:economics / Q000379:methods*; D008875:Middle Aged; D015233:Models, Statistical; D011159:Population Surveillance; D011237:Predictive Value of Tests; D012307:Risk Factors; D014481:United States
D008077:Lipoproteins, LDL; D002784:Cholesterol