Thanthirige L. M. Ruberu, Danielle Braun, Giovanni Parmigiani, Swati Biswas
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引用次数: 0
Abstract
Multigene panel testing now allows efficient testing of many cancer susceptibility genes leading to a larger number of mutation carriers being identified. They need to be counseled about their cancer risk conferred by the specific gene mutation. An important cancer susceptibility gene is PALB2. Multiple studies reported risk estimates for breast cancer (BC) conferred by pathogenic variants in PALB2. Due to the diverse modalities of reported risk estimates (age-specific risk, odds ratio, relative risk, and standardized incidence ratio) and effect sizes, a meta-analysis combining these estimates is necessary to accurately counsel patients with this mutation. However, this is not trivial due to heterogeneity of studies in terms of study design and risk measure. We utilized a recently proposed Bayesian random-effects meta-analysis method that can synthesize estimates from such heterogeneous studies. We applied this method to combine estimates from 12 studies on BC risk for carriers of pathogenic PALB2 mutations. The estimated overall (meta-analysis-based) risk of BC is 12.80% (6.11%−22.59%) by age 50 and 48.47% (36.05%−61.74%) by age 80. Pathogenic mutations in PALB2 makes women more susceptible to BC. Our risk estimates can help clinically manage patients carrying pathogenic variants in PALB2.
期刊介绍:
Genetic Epidemiology is a peer-reviewed journal for discussion of research on the genetic causes of the distribution of human traits in families and populations. Emphasis is placed on the relative contribution of genetic and environmental factors to human disease as revealed by genetic, epidemiological, and biologic investigations.
Genetic Epidemiology primarily publishes papers in statistical genetics, a research field that is primarily concerned with development of statistical, bioinformatical, and computational models for analyzing genetic data. Incorporation of underlying biology and population genetics into conceptual models is favored. The Journal seeks original articles comprising either applied research or innovative statistical, mathematical, computational, or genomic methodologies that advance studies in genetic epidemiology. Other types of reports are encouraged, such as letters to the editor, topic reviews, and perspectives from other fields of research that will likely enrich the field of genetic epidemiology.