Dataset Information

Comparison of two methods for estimating absolute risk of prostate cancer based on single nucleotide polymorphisms and family history.

ABSTRACT: Disease risk-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies have the potential to be used for disease risk prediction. An important feature of these risk-associated SNPs is their weak individual effect but stronger cumulative effect on disease risk. Several approaches are commonly used to model the combined effect in risk prediction, but their performance is unclear. We compared two methods to model the combined effect of 14 prostate cancer risk-associated SNPs and family history for the estimation of absolute risk for prostate cancer in a population-based case-control study in Sweden (2,899 cases and 1,722 controls). Method 1 weighs each risk allele equally using a simple method of counting the number of risk alleles, whereas method 2 weighs each risk SNP differently based on its odds ratio. We found considerable differences between the two methods. Absolute risk estimates from method 1 were generally higher than those of method 2, especially among men at higher risk. The difference in the overall discriminative performance, measured by area under the curve of the receiver operating characteristic, was small between method 1 (0.614) and method 2 (0.618), P = 0.20. However, the performance of these two methods in identifying high-risk individuals (2- or 3-fold higher than average risk), measured by positive predictive values, was higher for method 2 than for method 1. These results suggest that method 2 is superior to method 1 in estimating absolute risk if the purpose of risk prediction is to identify high-risk individuals.

SUBMITTER: Hsu FC

PROVIDER: S-EPMC2852494 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature

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Comparison of two methods for estimating absolute risk of prostate cancer based on single nucleotide polymorphisms and family history.

Hsu Fang-Chi FC Sun Jielin J Zhu Yi Y Kim Seong-Tae ST Jin Tao T Zhang Zheng Z Wiklund Fredrik F Kader A Karim AK Zheng S Lilly SL Isaacs William W Grönberg Henrik H Xu Jianfeng J

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20100323 4

Disease risk-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies have the potential to be used for disease risk prediction. An important feature of these risk-associated SNPs is their weak individual effect but stronger cumulative effect on disease risk. Several approaches are commonly used to model the combined effect in risk prediction, but their performance is unclear. We compared two methods to model the combined effect of 14 prostate cancer risk- ...[more]

PMID: 20332264

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Project description:BACKGROUND:Since most prostatic diseases are associated with the organ's enlargement, evaluation of prostatic size is a main criterion in the diagnosis of prostatic state of health. While enlargement is a non-uniform process, volumetric measurements are believed to be advantageous to any single dimensional parameter for the diagnosis of prostatomegaly. In a previous study, volume was analysed with a slice addition technique (SAT), which was validated as highly accurate. Irrespective of high accuracy, SAT represents a complex and time-consuming procedure, which limits its clinical use. Thus, demand exists for more practical volume assessment methods. In this study, the prostatic volume of 95 canine patients (58 intact males, 37 neutered males) were analysed retrospectively by using the ellipsoid formula (Formula) and an imaging "wrap" function tool (Wrap) to help assess accuracy and applicability. Accuracy was checked against phantom measurements and results were compared to SAT measurements of the same patient pool obtained from a previously published paper. Patients were grouped according to prostatic structure (H?=?homogeneous, I?=?inhomogeneous, C?=?cystic) and volume using the SAT (volume group?=?vg: 1, 2 and 3). RESULTS:High correlation between the Formula or Wrap volume and the phantom volume was found, the values being higher for the Formula. Mean Formula volumes (vg 1: 2.2?cm3, vg 2: 14.5?cm3, vg 3: 109.4?cm3, respectively) were significantly underestimated, while mean Wrap volumes (vg 1: 3.8?cm3, vg 2: 19.5?cm3, vg 3: 159.2?cm3) were statistically equivalent to SAT measurements (vg 1: 3.1?cm3, vg 2: 18.6?cm3, vg 3: 157.2?cm3, respectively). Differences between Formula and SAT volumes ranged from 22.4-31.1%, while differences between Wrap and SAT volumes were highest in small prostates (vg 1: 22.1%) and fell with increasing prostatic size (vg 3: 1.3%). CONCLUSION:The Wrap function is highly accurate, less time-consuming and complex compared to SAT and could serve as beneficial tool for measuring prostatic volume in clinical routine after further validation in future studies. The Formula method cannot be recommended as an alternative for volumetric measurements of the prostate gland due to its underestimation of volumes compared to SAT results.

Dataset Information

Comparison of two methods for estimating absolute risk of prostate cancer based on single nucleotide polymorphisms and family history.

Publications

Comparison of two methods for estimating absolute risk of prostate cancer based on single nucleotide polymorphisms and family history.

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