A trial reports a relative effect, such as a relative risk reduction, that is roughly constant across risk levels. The absolute benefit your patient can expect is that relative effect multiplied by the patient's own baseline risk. Because the relative effect is fixed, the absolute benefit scales directly with baseline risk: a patient at twice the risk of the trial average stands to gain roughly twice the absolute benefit, and a patient at half the risk stands to gain roughly half.
This is why the same trial result can justify treatment in one patient and not another. The number needed to treat is the reciprocal of the absolute risk reduction, so it falls as baseline risk rises. The simulation lets you set the trial's relative risk reduction and your patient's baseline risk, then read the resulting absolute risk reduction and number needed to treat. The relationship is linear in baseline risk, and the practical question is whether the patient's risk is high enough that the absolute benefit outweighs the harms and burden of treatment.