Impact of convexity under different changes of variables for different parts of optimization

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Let $$ \min_x f(x)$$ such that $$ C(x) \le 0$$ where $C$, and $f$ each are convex under respective changes of variables.

How does that impact the optimization? If standard algorithms are sensitive to this, would it be possible to exploit the convexity nonetheless?