Interpretting a chi-sq correctly I apologize for what may seem a very simple question. I can't seem to find an answer to how I can interpret chi-sq results other than rejecting the null hypothesis.
Pearson's Chi-squared test with Yates' continuity correction
X-squared = 5.2538, df = 1, p-value = 0.0219

I understand that I am able to reject the null hypothesis given the p-value. Can I also interpret the results saying that Procedure B is more likely to lead to a malignant result given the observed results are greater than expected?

For interpreting the test itself you should stick to interpreting the p-value, however nobody stops you from saying that Procedure B led to more malignant results than expected under the independence null hypotheses. You may even get away with the interpretation that you suggested, however this is not directly what the test says.
The test is defined by null and alternative hypothesis, test statistic and result (p-value). None of these says anything in particular about what results are "likely" with Procedure B. My point is that on top of that you can explain and interpret how your data led to this result. Nothing wrong with that, but don't mix the term "significant" in there; "likely" is kind of borderline and one can discuss for long whether this is justified. I wouldn't use it.
