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Dear all, maybe anybody has an idea to solve the following survival analysis problem. I have a large breast cancer dataset. In the metastacic stadium of breast cancer the oncologists tried a lot of treatments using the "play the winner drop the loser strategy". The aim of the study having survival time since metastases as the primary outcome should be to find the "optimal treatment sequence" which maximizes the survival time. The data situation is the following: In addition to all well known prognostic factors, the ordering, the duration and the success of the different treatments each patient received during metastatic stadium was documented. Most of the patients received between three and five treatments. in detail: first-line therapie: t1: from .. to ..., th. success (PD;NC;PR;CR) second-line th.: t2: from .. to ..., ts2 third-line th. t3: from .. to, ts3 ... ... I want to find a method which uses the whole information from the dataset and evaluates the effects of the different treatment sequences on the individual's survival time. Maybe an approach with Markov chains and cox-ph with time-dependent variables would be successful. Any hints, suggestions, comments or references would be greatly appreciated!.. Thanks Bernd Genser