At the beginning

All entries one this page are numbers between 0 and 1.

Do you want confidence intervals?
If yes, you will have to enter either the number of cases for each statistic or its standard deviation.
If no, click on the box named "NO" above.

Pretest probability is the probability of the disease for the patient before performing any tests.
Enter the pretest data, and calculate the standard deviation and initial 95%-confidence interval for the pre-test probability. If you don't want to calculate confidence interval, leave the number of cases box empty.

If you don't want to calculate pretest and posttest probabilities, i.e.,
if you want to calculate only thresholds, uncheck the following box:

Enter the following data:

Pretest Probability: Number of Cases:
Standard Deviation for pretest probability:
Confidence interval for pretest probability: [ , ]
or in percentages: [ % , % ]

Do you want to use test in these calculations:

Now enter the data for the test:
  • Sensitivity (the conditional probability of positive test result, given presence of the disease),
  • Specificity (the conditional probability of negative test result, given absence of the disease), and
  • The Risk of the test Rt
  • the number of cases on which the data is based for both of them.
The program will calculate Standard Deviation for Specificity and Sensitivity.
If you wish to use your own estimate of the error, check the box located next to the desired standard deviation entry and enter your estimate into the box. If you want to evaluate error instead, don't forget to uncheck the box and enter the number of cases.
Enter the following data:
No. of Patients:
No. of Patients:
Risk of the Test:
Std. Dev. for Sensitivity: Std. Dev. for Specificity:
False Negative: False Positive:
Positive Likelihood Ratio LR+:
Negative Likelihood Ratio LR-:
Std. Dev. for LR+: Std. Dev. for LR-:

Posttest Probabilities

Conditional probability of the disease, given that the test result is positive.
P ( D+ | T+ ) =
95% confidence interval : [ , ]
or in percentages: [ % , % ]
Conditional probability of the disease, given that the test result is negative.
P ( D+ | T- ) =
95% confidence interval : [ , ]
or in percentages: [ % , % ]

Morbidity (Mortality) of the disease, and Efficacy and Risks of the Treatment

To calculate the thresholds, we have to enter the Risk of the treatment and the Morbidity (Mortality) of the disease. If you know the standard error of any of these parameters, enter it. If you know the number of cases (patients) your estimate is based on, enter that number in the corresponding box.

Required Data

Morbidity (Mortality) (M) without the treatment:
St. Err. For M:
No. of cases:
Risk (Rrx):
St. Err. For Risk:
No. of cases:

To calculate the rest of the parameters, enter at least one of the following: Efficacy (E), Morbidity (Mortality) under treatment (Mrx), and the Number Needed to Treat (NNT).
If you want to calculate an entry, leave its' box empty.

Enter One of the Following

Efficacy (E):
St. Err. for Efficacy:
No. of cases:
Morbidity (Mortality) with the treatment (Mrx):
St. Err. For Mrx:
No. of cases:
Number Needed to Treat (NNT):
St. Err. For NNT:

The risk of the treatment and the mortality/morbidity of the disease under treatment occur simultaneously in your calculations. Select your option if you don't agree with this statement.


Finally, we will calculate the thresholds and their confidence intervals:
  • The testing threshold: if the probability of the disease in the patient is below this number, do not administer test, and continue observing the patient.
  • The treatment threshold: if the probability of the disease in the patient is above this number, administer the treatment.
Testing Threshold:
= %
Treatment Threshold:
= %
Confidence Interval:
[ , ]
or in percents: [ % , % ]
Confidence Interval:
[ , ]
or in percents: [ % , % ]

In order to run this program correctly you should use Nestcape 3.0 or higher, or Microsoft Explorer 3.0 or higher

"These are theoretical calculations. Any clinician seeking to apply or consult these calculations is expected to use independent medical judgement in the context of individual clinical circumstances to determine applicability of derived calculations".