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With the development of biomedical science, researchers have increasingaccess to an abundance of studies focusing on similar research questions. Thereis a growing interest in the integration of summary information from thosestudies to enhance the efficiency of estimation in their own internal studies.In this work, we present a comprehensive framework on integration of summaryinformation from external studies when the data are modeled by semiparametricmodels. Our novel framework offers straightforward estimators that updateconventional estimations with auxiliary information. It addresses computationalchallenges by capitalizing on the intricate mathematical structure inherent tothe problem. We demonstrate the conditions when the proposed estimators aretheoretically more efficient than initial estimate based solely on internaldata. Several special cases such as proportional hazards model in survivalanalysis are provided with numerical examples.

Integration of Summary Information from External Studies for Semiparametric Models