Multigene panels in prostate cancer risk assessment: a systematic review

Abstract

Prostate cancer is the fourth most common malignancy worldwide, and the second most common among men.1 In 2014, it was estimated that more than a quarter of a million new cases were diagnosed in North America and that the disease accounted for more than 33,000 deaths. 2,3 These numbers are likely to increase with the aging of the population. On the basis of data from the Surveillance, Epidemiology, and End Results program, more men were diagnosed with prostate cancer at a younger age and earlier stage in 2004-2005 than in the mid-late 1990s, and disparity between ethnic groups in cancer stage at diagnosis decreased. 4 Apart from age, 5 ethnic group, 5,6 and family history, 7-9 the risk factors associated with prostate cancer are unclear, 5 making primary prevention difficult. Prostate cancer is currently considered to be a complex, multifactorial disease, and the vast majority of familial clustering is attributed to the interaction of multiple shared susceptibility genes with moderate to low penetrance and shared environmental factors within these families.The natural history of prostate cancer is highly variable. 10 In a large proportion of men the disease is indolent, and it is difficult to predict which tumors will be aggressive. The value of aggressive management for localized prostate cancer is debated, [11][12][13][14] and only a small proportion of men with early-stage prostate cancer die from the disease within 10 to 15 years of diagnosis. Developing tools to differentiate aggressive and indolent disease is of key importance.Prostate-specific antigen (PSA) screening was introduced in the late 1980s.15 Meta-analyses of seven randomized controlled trials (RCTs) of screening using PSA testing alone or in combination with digital rectal examination suggested no evidence of benefit in reducing mortality 16,17 and some evidence of harm from overdiagnosis.17 Amid substantial debate, 18-20 the argument has been made for developing more accurate screening tests, including possible genetic markers. Purpose: Single-nucleotide polymorphism (SNP) panel tests have been proposed for use in the detection of, and prediction of risk for, prostate cancer and as prognostic indicator in affected men. A systematic review was undertaken to address three research questions to evaluate the analytic validity, clinical validity, clinical utility, and prognostic validity of SNP-based panels.Methods: Data sources comprised MEDLINE, Cochrane CEN-TRAL, Cochrane Database of Systematic Reviews, and EMBASE; these were searched from inception to April 2013. The gray-literature searches included contact with manufacturers. Eligible studies included English-language studies evaluating commercially available SNP panels. Study selection and risk of bias assessment were undertaken by two independent reviewers. Results:Twenty-one studies met eligibility criteria. All focused on clinical validity and evaluated 18 individual panels with 2 to 35 SNPs.All had poor discriminative ability (overall area under receiver-operator characteristic curves, 5...

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“…In particular, there have been concerns on the impact of genetic screening in clinical decision-making. For example, in a previous review, 58 genetic screening was discussed using commercially available SNP panel tests in prostate cancer. Conclusions were that the investigated SNP panels had poor discriminative ability and clinical validity.…”

Exome-based genome-wide association study and risk assessment using genetic risk score to prostate cancer in the Korean population

“…Cancer risk prediction by genetic risk scores (GRS) have been designed as an efficient and effective approach in terms of clinical utility [ 9 ]. Recently, genetic risk assessment studies have been reported evaluating the cumulative genetic scores for PCa risk [ 10 , 11 ].…”

Incorporation of Personal Single Nucleotide Polymorphism (SNP) Data into a National Level Electronic Health Record for Disease Risk Assessment, Part 1: An Overview of Requirements

“…Modest value of clinicogenomic associations does not mean negligible, and some researchers try to develop polygenic risk models or panels assigning values for various SNP alleles, and calculate the total risk of disease for more effective risk prediction [ 75 ]. In the literature, several cumulative prediction models have been proposed, but most of these are criticized regarding comprehensive evaluation, especially for clinical utility [ 76 ].…”