Here is the question. Suppose we have a drug `A`, and we have conducted a RCT evaluating the risk of death in patients randomised to receive `A` or not. The results of a Cox-regression model shows HR: 0.60 (95%CI: 0.50-0.70) (please don't focus on the numbers, this is only for demonstrative purposes).

Then we want to explore whether there is an interaction between `sex` and the effect of `A`. Females were approximately 35% of the cohort.
We therefore perform a Cox-Regression including an interaction term:

`outcome~(Sex*A)+A+Sex`

and the results are the following:

```
                   coef exp(coef) p
A               -0.6733    0.5100 0.0032
sexFemale       -0.2543    0.7754 0.2834
A:sexFemale      0.2689    1.3085 0.4503

```

Manipulating the coefficients, we can have:

`A*sex=Female`: HR: 0.67 (95%CI: 0.40-1.20)

`A*sex=Male`: HR: 0.51 (95%CI: 0.43-0.82) [again, don't focus on the number]

`interaction p`: 0.450

Now, here's the question, related to the interpretation of the results presented: I think one can conclude that no statistically significant interaction was observed between males and females for the effect of `A` (with effect being broadly consistent?). However, how can one interpret the non-statistically significant results observed for females, while the effect remained statistically significant in males?
My guess is that one should not speculate onto this, given that this is mainly due to the reduced sample size in females group, but I'd like to hear more expert opinions.