Dataset Information

An absolute risk model to identify individuals at elevated risk for pancreatic cancer in the general population.

ABSTRACT:

Purpose

We developed an absolute risk model to identify individuals in the general population at elevated risk of pancreatic cancer.

Patients and methods

Using data on 3,349 cases and 3,654 controls from the PanScan Consortium, we developed a relative risk model for men and women of European ancestry based on non-genetic and genetic risk factors for pancreatic cancer. We estimated absolute risks based on these relative risks and population incidence rates.

Results

Our risk model included current smoking (multivariable adjusted odds ratio (OR) and 95% confidence interval: 2.20 [1.84-2.62]), heavy alcohol use (>3 drinks/day) (OR: 1.45 [1.19-1.76]), obesity (body mass index >30 kg/m(2)) (OR: 1.26 [1.09-1.45]), diabetes >3 years (nested case-control OR: 1.57 [1.13-2.18], case-control OR: 1.80 [1.40-2.32]), family history of pancreatic cancer (OR: 1.60 [1.20-2.12]), non-O ABO genotype (AO vs. OO genotype) (OR: 1.23 [1.10-1.37]) to (BB vs. OO genotype) (OR 1.58 [0.97-2.59]), rs3790844(chr1q32.1) (OR: 1.29 [1.19-1.40]), rs401681(5p15.33) (OR: 1.18 [1.10-1.26]) and rs9543325(13q22.1) (OR: 1.27 [1.18-1.36]). The areas under the ROC curve for risk models including only non-genetic factors, only genetic factors, and both non-genetic and genetic factors were 58%, 57% and 61%, respectively. We estimate that fewer than 3/1,000 U.S. non-Hispanic whites have more than a 5% predicted lifetime absolute risk.

Conclusion

Although absolute risk modeling using established risk factors may help to identify a group of individuals at higher than average risk of pancreatic cancer, the immediate clinical utility of our model is limited. However, a risk model can increase awareness of the various risk factors for pancreatic cancer, including modifiable behaviors.

SUBMITTER: Klein AP

PROVIDER: S-EPMC3772857 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Publications

An absolute risk model to identify individuals at elevated risk for pancreatic cancer in the general population.

Klein Alison P AP Lindström Sara S Mendelsohn Julie B JB Steplowski Emily E Arslan Alan A AA Bueno-de-Mesquita H Bas HB Fuchs Charles S CS Gallinger Steven S Gross Myron M Helzlsouer Kathy K Holly Elizabeth A EA Jacobs Eric J EJ Lacroix Andrea A Li Donghui D Mandelson Margaret T MT Olson Sara H SH Petersen Gloria M GM Risch Harvey A HA Stolzenberg-Solomon Rachael Z RZ Zheng Wei W Amundadottir Laufey L Albanes Demetrius D Allen Naomi E NE Bamlet William R WR Boutron-Ruault Marie-Christine MC Buring Julie E JE Bracci Paige M PM Canzian Federico F Clipp Sandra S Cotterchio Michelle M Duell Eric J EJ Elena Joanne J Gaziano J Michael JM Giovannucci Edward L EL Goggins Michael M Hallmans Göran G Hassan Manal M Hutchinson Amy A Hunter David J DJ Kooperberg Charles C Kurtz Robert C RC Liu Simin S Overvad Kim K Palli Domenico D Patel Alpa V AV Rabe Kari G KG Shu Xiao-Ou XO Slimani Nadia N Tobias Geoffrey S GS Trichopoulos Dimitrios D Van Den Eeden Stephen K SK Vineis Paolo P Virtamo Jarmo J Wactawski-Wende Jean J Wolpin Brian M BM Yu Herbert H Yu Kai K Zeleniuch-Jacquotte Anne A Chanock Stephen J SJ Hoover Robert N RN Hartge Patricia P Kraft Peter P

PloS one 20130913 9

<h4>Purpose</h4>We developed an absolute risk model to identify individuals in the general population at elevated risk of pancreatic cancer.<h4>Patients and methods</h4>Using data on 3,349 cases and 3,654 controls from the PanScan Consortium, we developed a relative risk model for men and women of European ancestry based on non-genetic and genetic risk factors for pancreatic cancer. We estimated absolute risks based on these relative risks and population incidence rates.<h4>Results</h4>Our risk ...[more]

PMID: 24058443

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Project description:Lung cancer is the leading cause of cancer-related death globally. An improved risk stratification strategy can increase efficiency of low-dose CT (LDCT) screening. Here we assessed whether individual's genetic background has clinical utility for risk stratification in the context of LDCT screening. On the basis of 13,119 patients with lung cancer and 10,008 controls with European ancestry in the International Lung Cancer Consortium, we constructed a polygenic risk score (PRS) via 10-fold cross-validation with regularized penalized regression. The performance of risk model integrating PRS, including calibration and ability to discriminate, was assessed using UK Biobank data (N = 335,931). Absolute risk was estimated on the basis of age-specific lung cancer incidence and all-cause mortality as competing risk. To evaluate its potential clinical utility, the PRS distribution was simulated in the National Lung Screening Trial (N = 50,772 participants). The lung cancer ORs for individuals at the top decile of the PRS distribution versus those at bottom 10% was 2.39 [95% confidence interval (CI) = 1.92-3.00; P = 1.80 × 10-14] in the validation set (P trend = 5.26 × 10-20). The OR per SD of PRS increase was 1.26 (95% CI = 1.20-1.32; P = 9.69 × 10-23) for overall lung cancer risk in the validation set. When considering absolute risks, individuals at different PRS deciles showed differential trajectories of 5-year and cumulative absolute risk. The age reaching the LDCT screening recommendation threshold can vary by 4 to 8 years, depending on the individual's genetic background, smoking status, and family history. Collectively, these results suggest that individual's genetic background may inform the optimal lung cancer LDCT screening strategy. SIGNIFICANCE: Three large-scale datasets reveal that, after accounting for risk factors, an individual's genetics can affect their lung cancer risk trajectory, thus may inform the optimal timing for LDCT screening.

Dataset Information

An absolute risk model to identify individuals at elevated risk for pancreatic cancer in the general population.

Purpose

Patients and methods

Results

Conclusion

Publications

An absolute risk model to identify individuals at elevated risk for pancreatic cancer in the general population.

Similar Datasets

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