See here. To cite:
"El Emam and his colleagues repeated some of those experiments using bivariate analysis so that they could allocate a share of the blame to code size (measured by number of lines) and the metric in question. It turned out that code size accounted for all of the significant variation: in other words, the object-oriented metrics they looked at didn’t have any actual predictive power once they normalized for the number of lines of code. Herraiz and Hassan’s chapter in Making Software, which reports on an even larger study using open source software, reached the same conclusion:
'…for non-header files written in C language, all the complexity metrics are highly correlated with lines of code, and therefore the more complex metrics provide no further information that could not be measured simply with lines of code… In our opinion, there is a clear lesson from this study: syntactic complexity metrics cannot capture the whole picture of software complexity. Complexity metrics that are exclusively based on the structure of the program or the properties of the text…do not provide information on the amount of effort that is needed to comprehend a piece of code—or, at least, no more information than lines of code do.'"