Consider two random times $\tau_{1}$ and $\tau_{2}$ defined on a common probability space $\left(\Omega, \mathcal{G}, \mathbb{Q}\right)$ with $\mathbb{Q}(\tau_{k}=0)=0$ and $\mathbb{Q}(\tau_{k}>t)>0$ for $k=1,2$ and all $t >0$. We also include a reference filtration, $\mathbb{F}=\left\{ \mathcal{F}_{t}\right\}_{t\geq0}$, say, on the probability space mentioned above.
For the random time $\tau_{1}$, its cumulative distribution function is denoted by $F_{\tau_{1}}(t) \left(=\mathbb{Q}(\tau_{1}\leq t) \right)$.
I would like to formally prove (using measure-theoretic arguments) the following equality:
$$ \mathbb{E}_{\mathbb{Q}} \left[ \mathbb{Q}\left\{ \tau_{1} < \tau_{2} , \tau_{1} \leq T \mid \mathcal{F}_{t}\right\} \right] = \mathbb{E}_{\mathbb{Q}} \left[ \int_{0}^{T} \mathbb{Q}\left\{ u < \tau_{2} \mid \mathcal{F}_{t}\right\} dF_{\tau_{1}}(u.) \right]$$
Remark: Intuitively this equality seems to make sense, as you "freeze" the random time $\tau_{2}$, and "integrate over the values of $\tau_{1}$". I would like to formalise this using theorems/lemmas, etc. of measure/probability-theory.
Thanks in advance.