I agree that in general, P(y′t) ≠ P(y′|t) and P(y′c) ≠ P (y′|c). What is needed is an effect measure that is transportable from an RCT to day to day clinical settings. If the outcomes of day to day care are recorded carefully, they make up an observational study. The usual effect measures currently applied in this way are the risk ratio or odds ratio. In your example, you chose to use the risk difference. The risk of death on no drug in your RCT was 0.79 and with a drug it was 0.51. This gives a risk difference (RD) of 0.79-0.51 = 0.28, a risk ratio (RR) of 0.51/0.79 = 0.646 and an odds ratio (OR) of {(0.51/(1-0.51)} / {(0.79/(1-0.79)} = 0.277.
In the observational study, the expected risk of death after choosing no drug was 180/600 = 0.3. If we assume a transportable RD then the expected risk of death after choosing the drug was 0.3-0.28 = 0.02 or 2% (note that if the RD had been 0.4 then the expected risk of death on the drug would have been an absurd minus 0.1 so it is flawed). If we assume a transportable RR then the risk of death after choosing the drug was 0.3 x 0.646 = 0.194 or 19.4% (note that if the RR had been 4 then the expected risk of death after choosing the drug would have been an absurd 1.2 so it is flawed too). If we assume a transportable OR then the odds of death after choosing the drug would be 0.3/(1-0.3)x0.277 = 0.199, the risk of death being 0.199/(1+0.199) = 0.110 or 11.0%. However the OR always gives a result of at least zero and no more than 1, unlike the RD or RR. However, in an earlier post I cast doubt on the appropriateness of the OR too (Should one derive risk difference from the odds ratio? - #340 by HuwLlewelyn).
The overall risk of death after choosing the drug in the observation study was 0.73. If the expected death rate on choosing the drug by assuming a RD of 0.28 were 0.3-0.28 = 0.02, then the excess death rate would be 0.73-0.02 = 0.71 as already described in my earlier posts. If the expected death rate after choosing the drug by assuming a RR of 0.646 were 0.194, then the excess death rate would be 0.73-0.194 = 0.536. If the expected death rate on choosing the drug by assuming an OR of 0.277 were 0.110, then the excess death rate would be 0.73-0.110 = 0.61. It is clear from this that the assumption made when estimating the risk of death (i.e. transportable RD, RR or OR) give different results. Because choosing the drug in your observational study increases the risk of death whatever the assumption, then in the light of decrease risk of death in your RCT, this excess death rate has to be put down to an adverse effect of the drug.
In clinical practice we are always trying to balance the beneficial effects of drugs from disease amelioration due to one group of casual mechanisms with he harmful effects of drugs by different causal mechanisms resulting in adverse effects, as exemplified above. This balancing can be done with Decision Analysis. I therefore cannot understand how you can conclude in the light of your observational study result that females suffer no harm by choosing the drug and that a future patient could be advised to take it.