Analysis of the predictive value of clinical data in patients with suspected colonic disease.
OBJECTIVE
To develop guidelines for predicting colonic disease on the basis of clinical parameters.


METHODS
A prospective study of the clinical data prior to colonoscopy. On the basis of the endoscopic findings, the patients were divided into three diagnostic groups: absence of significant disease, significant benign disease and malignant disease. The patient population was divided randomly into two subgroups. The clinical data from one of them was used to build a database which, using Bayes' theorem, was compared with the variables from the other subgroup to predict the diagnosis for each patient.


METHODS
A total of 336 patients (170 males and 166 females; mean age: 58 years; range: 15 to 87 years) were evaluated.


RESULTS
When the endoscopic findings were grouped on the basis of their clinical importance, 211 patients (63%) belonged to the group without significant disease, 60 patients (18%) had significant benign disease and 65 (19%) presented a neoplastic disease. Of the 21 variables selected for use in the database, 6 showed statistically significant differences in terms of the absence or presence of malignant disease: age, absence of previous similar episodes, weight loss, rectal bleeding, lack of improvement and the presence of a mass on digital rectal examination. The predictive model differentiated patients with neoplasm from those without malignant disease, but was not capable of identifying differences among the latter. The model was useful for assessing the risk of malignant disease for each patient.


CONCLUSIONS
The predictive model obtained is a useful tool for establishing the diagnosis and the priority in the performance of colonoscopy.
Siles
S
S
Service of Digestive Medicine, Hospital La Fé, Valencia, Spain.
Garrigues
V
V
Ponce
J
J
Gálvez
C
C
Berenguer
J
J
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003108:Colonic Diseases / Q000175:diagnosis*; D003113:Colonoscopy; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests