As I understand it, the fundamental question is whether tests A & B agree better than tests A & C, beyond a minor improvement that could just be due to chance (or agree worse, depending on how the tests B and C are labelled). The null hypothesis is that the agreement between A & B is equal to the agreement between A & C.
The most straightforward test for this case is the chi-square test for independence. Imagine the data summarized in a 2x2 table like this:
with total N's of 74 in the first group and 43 in the second group. MATLAB's 'crosstab' command will compute that chi-square test for you. See this answer for an explanation of how to format the data and run the test.
Cohen's Kappa is a useful numerical measure of the extent of agreement, but it isn't really optimal for deciding whether the levels of agreement are different for the two pairs of tests.