Original smooth receiver operating characteristic curve estimation from continuous data: statistical methods for analyzing the predictive value of spiral CT of ureteral stones.
OBJECTIVE
Diagnostic studies such as spiral computed tomography (CT) in patients with obstructing ureteral calculi often necessitate the analysis of continuous test data (e.g., stone sizes). The accuracy of a test can be summarized by using a receiver operating characteristic (ROC) curve. The authors developed and compared three methods for constructing a smooth ROC curve from continuous diagnostic data.


METHODS
Nonparametric, semiparametric, and parametric smooth ROC curve analyses were applied to data from 100 unenhanced spiral CT scans of patients with proved obstructing ureteral stones. Accuracy in using stone size to predict the need for intervention was evaluated by means of these methods. Characteristics and summary measures of the resulting ROC curves were estimated.


RESULTS
All methods fit the data well. The nonparametric method followed the details of the empiric data. The semiparametric and parametric methods yielded similar estimates of the ROC curve parameters. Areas under the ROC curves were 0.807, 0.821, and 0.814 for nonparametric, semiparametric, and parametric methods, respectively, in comparison with 0.811 for the empiric method.


CONCLUSIONS
The parametric method is preferred for constructing a smooth ROC curve with available stone-size data derived from spiral CT. The analyses confirm the predictive value of stone size in determining the need for intervention.
Zou
K H
KH
Department of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA.
Tempany
C M
CM
Fielding
J R
JR
Silverman
S G
SG
D006801:Humans; D011237:Predictive Value of Tests; D012372:ROC Curve; D014057:Tomography, X-Ray Computed / Q000379:methods / Q000706:statistics & numerical data*; D014514:Ureteral Calculi / Q000000981:diagnostic imaging* / Q000453:epidemiology