The positive predictive value of the new test is 0.571. The positive predictive value is the probability that a patient with a positive test result actually has the disease. In order to calculate the positive predictive value, a 2 x 2 contingency table needs to be constructed first. The probability of a fetus having the variant is 40%, which in theory means that 40 fetuses out of 100 will have the variant and 60 (100 − 40) will not have it. The sensitivity, which represents the true positives, is 80%, meaning that 80% of the 40 fetuses with the variant (32 fetuses) will test positive and 8 fetuses (40 − 32) will have the variant but will test negative (false negatives). The specificity is 60%, and that represents the true negatives. Therefore, similarly, 36 fetuses (60% of 60) will not have the variant and will test negative, while 24 fetuses (60 − 36) will not have the variant but will test positive (false positives). Finally, we can calculate that a total of 56 fetuses (32 + 24) will test positive, and a total of 44 (8 + 36) will test negative. The positive predictive value is equal to true positives/(true positives + false positives) or true positives/total positives, therefore, 32/56 = 0.571.

The false-positive rate of this test is 0.4 (A), which is equal to 1 − specificity. The negative predictive value is 0.818 (C), which is equal to true negatives/(true negatives + false negatives) or true negatives/total negatives. The likelihood ratio is 2 (D), which is equal to sensitivity/false-positive rate.