External validation of outcome prediction model for ureteral/renal calculi.
OBJECTIVE
We externally validated a previously designed neural network model to predict outcome and duration of passage for ureteral/renal calculi. The model was also evaluated using a 6 mm largest stone dimension cutoff in predicting stone outcome.


METHODS
The model was previously designed on 301 patients at Albany Medical Center (free shareware from www.uroengineering.com). The model had a prediction accuracy of 86% for passage outcome and 87% for passage duration. In this study we tested the model on a separate 384 patients from 6 different external institutions to assess the prediction accuracy. All patients had a single renal/ureteral calculus by evaluation in an emergency room setting or by primary physicians and were then referred for further treatment. Model accuracy was also compared to using a 6 mm largest stone dimension cutoff in predicting the need for intervention.


RESULTS
Testing on the 384 patients from all 6 external institutions revealed an outcome prediction accuracy of 88%. The area under the ROC curve was 0.9. Using a 6 mm stone size cutoff provided 79% (ROC 0.8) accuracy. The model duration of passage prediction accuracy was 80% (133 patients passed the stone, area under ROC of 0.8).


CONCLUSIONS
The model provided high stone outcome prediction accuracy (ROC of 0.9 and 0.8) at the 6 external institutions, comparable to that of the design institution. The model provided higher accuracy than using only the largest stone dimension as a cutoff. Increasing experience will further assess the model's accuracy.
Parekattil
Sijo J
SJ
Cleveland Clinic Foundation, Cleveland, Ohio, USA. sijo_p@hotmail.com
Kumar
Udaya
U
Hegarty
Nicholas J
NJ
Williams
Clay
C
Allen
Tara
T
Teloken
Patrick
P
Leitão
Victor A
VA
Netto
Nelson R
NR
Haber
Georges-Pascal
GP
Ballereau
Charles
C
Villers
Arnauld
A
Streem
Stevan B
SB
White
Mark D
MD
Moran
Michael E
ME
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D005260:Female; D006801:Humans; D007669:Kidney Calculi / Q000628:therapy; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012075:Remission, Spontaneous; D015203:Reproducibility of Results; D014514:Ureteral Calculi / Q000628:therapy