Just did a podcast on the topic aimed towards clinicians, which should come out soon. Briefly, random sampling physically licenses the use of measures of uncertainty such as standard errors (SEs), confidence intervals (CIs) and p-values for (sub)groups of sampled patients. Conversely, random allocation physically licenses the use of measures of uncertainty for the differences between the allocated groups. Measures of uncertainty are used when we are making inferences. When those are not expected to be valid then we can use descriptive measures and not do inferences.
For example, in an RCT the random treatment allocation licenses the use of measures of uncertainty for hazard ratios, odds ratios, risk ratios, median/mean survival difference, absolute risk reduction etc that measure differences between groups. Because there is no random sampling, measures of uncertainty are not licensed by the randomization procedure for cohort-specific estimates such as the median survival observed in each treatment cohort. For those, we can use descriptive measures such as standard deviation (SD), interquartile range etc. Measures of uncertainty will require further assumptions to be considered valid. Further discussion here.