Is a McNemar's test appropriate in this setting?

I wrote a scientific paper on the use of two different surgical techniques on two organs in the same subject: technique A for one ovary and technique B for the contralateral ovary on 51 subjects.
Cure rates for technique A was 48 out of 51, and 50 out of 51 for technique B. To evaluate these results, I used a 2x2 contingency table (Fisher's exact test), which yielded a p value of 0.6175, non significant.
After submitting the paper to a scientific journal, one of the reviewers of the paper suggests that I should use a McNemar's test as a more appropriate test. Is this true? If not, how can I answer to this suggestion?


TS Contributor
Observations are paired (2 outcomes from each subject).
You don't have 102 independent data points, but 51 paired
observations. Therefore McNemars ist perfectly right. It
won't change the conclusions, but it is nevertheless the
appropriate test.

With kind regards



Less is more. Stay pure. Stay poor.
Further explanation, the two values from the same person are not two random observations. There is an inherent deppendency, that is why this design is used, to be able to say you are kind of controlling for the uniqueness of the person by performing both interventions on them.