Let $X\sim N(\mu,\sigma^2I)\in \mathbb{R}^n$ be a non-centered ($\mu\neq 0$) Gaussian vector with independent coordinates. I'm wondering if there is any sharp lower bound of the following probability: $$\mathbb{P}\left(X^TAX - \mathbb{E}(X^TAX) \geq \delta\right)$$ where $A$ is a symmetric matrix and $\delta>0$.

I know that when $X$ is centered, the upper bound is well-known, which is the Hanson-Wright inequality. However, in my case, $X$ is not centered and I'm interested in the lower bound.