Citations 3
Cohort Profile: The Colon Cancer Family Registry Cohort (CCFRC)
Jenkins, Mark A. , Win, Aung Ko , Templeton, Allyson , Angelakos, Maggie S, Buchanan, Daniel D. , Cotterchio, Michelle , Figueiredo, Jane C. , Thibodeau, Stephen N. , Gallinger, Steven, Lindor, Noralane M. , Haile, Robert W. , Investigators, Colon Cancer Family Registry Cohort, Ahnen, Dennis J. , Anton, Kristen , Arnold, Julie, Aronson, Melyssa , Aujard, Kelly, Bapat, Bharati , Barker, Melissa, Bickerstaffe, Adrian , Burnett, Terrilea, Daftary, Darshana, DeRycke, Melissa S. , Dicks, Elizabeth , Diep, Anh, Duggan, Dave , Fisher, Douglass, Fox, Samantha , French, Amy J. , Glanz, Karen, Goldblatt, Jack, Goldberg, Richard M. , Goode, Ellen L. , Greenberg, Cary, Green, Jane , Green, Roger, Grove, John H. , Gryfe, Robert, Harmon, Patricia, Holowaty, Eric J., Holter, Spring, Kim, Hyeja, Kirk, Judy, Lance, Peter , Laurino, Mercy , Leggett, Barbara , Levine, A. Joan, Lowery, Jan T. , Lydum, Laurie, Madlensky, Lisa , Makar, Karen , Maskiell, Judi, McAllister, Pamela K., McGannon, Ellen, McKeown‐Eyssen, Gail, McLaughlin, John, Miller-Pakvasa, Heide, Nguyen, Nathalie , Nigon, Sandy, Parafrey, Patrick, Parry, Susan, Peterson, Susan K. , Phipps, Amanda I. , Redston, Mark , Rogers, Scott O., Schully, Sheri D. , Selander, Teresa, Seminara, Daniella, Shiovitz, Stacey, Siegmund, Kim, Smyrk, Thomas C. , Snazel, Douglas, Stubbs, John, Suthers, Graeme , Thomas, Duncan C. , West, D. P., Woods, Michael O. , Younghusband, Ban, Young, Joanne , Buchanan, Daniel D , Win, Aung K , Jenkins, Mark A , Haile, Robert W , Baron, John A. , Potter, John D. , Hopper, John L. , Casey, Graham , Marchand, Loı̈c Le , Newcomb, Polly A. , Investigators, Colon Cancer Family Registry Cohort, Cheng, Iona C. , Church, James M. , Church, Timothy R. , Clendenning, Mark , Esplen, Mary Jane , Giles, Graham G. , Grady, William M. , Keogh, Louise Anne , Limburg, Paul J. , Macrae, Finlay , Malen, Rachel C. , McLaughlin, John, Möslein, Gabriela , Pollett, Aaron F. , Sandler, Robert David , Southey, Melissa C. , Tucker, Kathy
International Journal of Epidemiology | January 16, 2018 | Volume: 47 | Issue: 2 | Pages: 387-388i
Association of the Colorectal CpG Island Methylator Phenotype with Molecular Features, Risk Factors, and Family History
Weisenberger, Daniel J. , Levine, A. Joan, Long, Tiffany I. , Buchanan, Daniel D. , Walters, Rhiannon, Rosty, Christophe , Joshi, Amit D. , Lindor, Noralane M. , Daftary, Darshana, Gallinger, Steven , Selander, Teresa, Bapat, Bharati , Ahnen, Dennis J. , Haile, Robert W. , Young, Joanne , Haile, Robert W. , Clendenning, Mark , Stern, Mariana Carla , Marchand, Loı̈c Le , Newcomb, Polly A. , Campbell, Peter T. , Casey, Graham , Baron, John A. , Hopper, John L. , Laird, Peter W. , Siegmund, Kimberly D. , Buchanan, Daniel D , Haile, Robert W , Rosty, Christophe
Cancer Epidemiology, Biomarkers & Prevention | January 13, 2015 | Volume: 24 | Issue: 3 | Pages: 512-519
Abstract Background: The CpG island methylator phenotype (CIMP) represents a subset of colorectal cancers characterized by widespread aberrant DNA hypermethylation at select CpG islands. The risk factors and environmental exposures contributing to etiologic heterogeneity between CIMP and non-CIMP tumors are not known. Methods: We measured the CIMP status of 3,119 primary population-based colorectal cancer tumors from the multinational Colon Cancer Family Registry. Etiologic heterogeneity was assessed by a case–case study comparing risk factor frequency of colorectal cancer cases with CIMP and non-CIMP tumors using logistic regression to estimate the case–case odds ratio (ccOR). Results: We found associations between tumor CIMP status and MSI-H (ccOR = 7.6), BRAF V600E mutation (ccOR = 59.8), proximal tumor site (ccOR = 9; all P < 0.0001), female sex [ccOR = 1.8; 95% confidence interval (CI), 1.5–2.1], older age (ccOR = 4.0 comparing over 70 years vs. under 50; 95% CI, 3.0–5.5), and family history of CRC (ccOR = 0.6; 95% CI, 0.5–0.7). While use of NSAIDs varied by tumor CIMP status for both males and females (P = 0.0001 and P = 0.02, respectively), use of multivitamin or calcium supplements did not. Only for female colorectal cancer was CIMP status associated with increased pack-years of smoking (Ptrend < 0.001) and body mass index (BMI; Ptrend = 0.03). Conclusions: The frequency of several colorectal cancer risk factors varied by CIMP status, and the associations of smoking and obesity with tumor subtype were evident only for females. Impact: Differences in the associations of a unique DNA methylation–based subgroup of colorectal cancer with important lifestyle and environmental exposures increase understanding of the molecular pathologic epidemiology of this heavily methylated subset of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 24(3); 512–9. ©2015 AACR.
Accuracy of Colorectal Polyp Self-Reports: Findings from the Colon Cancer Family Registry
Madlensky, Lisa , Daftary, Darshana, Burnett, Terrilea, Harmon, Patricia, Jenkins, Mark A. , Maskiell, Judi, Nigon, Sandra, Phillips, Kerry, Templeton, Allyson , Haile, Robert W. , Potter, John D. , Gallinger, Steven, Limburg, Paul J. , Baron, John A. , Jenkins, Mark A , Haile, Robert W , Potter, John D
Cancer Epidemiology, Biomarkers & Prevention | September 13, 2007 | Volume: 16 | Issue: 9 | Pages: 1898-1901
Abstract Introduction: Colorectal adenomas and other types of polyps are commonly used as end points or risk factors in epidemiologic studies. However, it is not known how accurately patients are able to self-report the presence or absence of adenomas following colonoscopy. Methods: Participants in the Colon Cancer Family Registry provided self-reports of recent colorectal cancer (CRC) screening activity, and whether or not they had ever been told they had a polyp. Positive and negative predictive values for polyp self-report were calculated by comparing medical records with self-reports from 488 participants. Results: The positive predictive value for self-reported polyp was 80.9%, and the negative predictive value was 85.8%. The predictive values did not differ by age group or sex, but participants with a previous diagnosis of CRC had a lower negative predictive value (76.2%) than participants with no personal history of CRC (89.0%; P = 0.04). Conclusions: Predictive values for self-reports of polyps are fairly high, but researchers needing accurate polyp data should obtain medical record confirmation. Pursuing medical records on only those participants self-reporting a polyp could result in an underestimation of the polyp prevalence in a study population. (Cancer Epidemiol Biomarkers Prev 2007;16(9):1898–901)