 Conditional latent event-time density under competing risks

For independent continuous event times, conditioning on $T_A<T_B$ weights the density of $T_A$ by the survivor function of $T_B$. Conditioning on $T_B<T_A$ instead weights it by one minus that survivor function. These are distributions of the latent $T_A$, not the distribution of the observed first event in every case.