With a very large sample size, a statistical test can detect very small differences with significance. As stated earlier, that significant difference might be trivially small and not of practical significance to you. To make what a significance test can detect the same as what you deem practical, you need to choose the sample size for the study. This can be done using PROC POWER.
For these results, you would probably would prefer to estimate the difference between the genders and get a confidence interval for that difference. The following code does that. Notice that the tiny difference (0.0047) has a very tight confidence interval (0.0046,0.0048) because of the enormous sample size. If you add the CHISQ option to test the gender difference, it is highly significant also because of the huge sample size. The estimate of the difference is probably more useful in this case.
data a;
do diag='y','n';
do gender='m','f';
input count @@;
output;
end; end;
datalines;
374332 438832
11966192 16665875
;
proc freq;
weight count;
table gender*diag / riskdiff;
run;
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