Transgender people comprise a diverse group of individuals whose gender identity or expression differs from that originally assigned to them at birth. Some, but not all, transgender people elect to undergo medical gender affirmation, which may include therapy with cross-sex hormones and/or surgical change of the genitalia and other sex characteristics. As cross-sex hormones administered for the purposes of gender affirmation may be delivered at high doses and over a period of decades, the carcinogenicity of hormonal therapy in transgender people is an area of considerable concern. In addition, concerns about cancer risk in transgender patients have been linked to sexually transmitted infections, increased exposure to well-known risk factors such as smoking and alcohol use, and the lack of adequate access to screening. Several publications have identified cancer as an important priority in transgender health research and called for large-scale studies. The goals of this article are to summarize the evidence on factors that may differentially affect cancer risk in transgender people, assess the relevant cancer surveillance and epidemiologic data available to date, and offer an overview of possible methodological considerations for future studies investigating cancer incidence and mortality in this population.

Background:We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles. Methods:We aimed to reproduce the literature searches of published systematic reviews and meta-analyses and assess whether CoCites retrieves all eligible articles while screening fewer titles. Results: A total of 250 reviews were included. CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less. Conclusions: CoCites is an efficient and accurate method for finding relevant related articles. The method uses the expert knowledge of authors to rank related articles, does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible.

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Objective: We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles. Materials and Methods: We aimed to reproduce the literature searches of published systematic reviews and meta-analyses (n=250) and assess whether CoCites retrieves all eligible articles while screening fewer titles. Results: CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less. Discussion: CoCites uses the expert knowledge of authors to rank related articles. The method does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible. Conclusion: CoCites is an efficient and accurate method for finding relevant related articles.

Objective: We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles. Materials and Methods: We aimed to reproduce the literature searches of published systematic reviews and meta-analyses (n=250) and assess whether CoCites retrieves all eligible articles while screening fewer titles. Results: CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less. Discussion: CoCites uses the expert knowledge of authors to rank related articles. The method does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible. Conclusion: CoCites is an efficient and accurate method for finding relevant related articles.