The CRISP colorectal cancer risk prediction tool: an exploratory study using simulated consultations in Australian primary care

BACKGROUND: In Australia, screening for colorectal cancer (CRC) with colonoscopy is meant to be reserved for people at increased risk, however, currently there is a mismatch between individuals' risk of CRC and the type of CRC screening they receive. This paper describes the development and optimisation of a Colorectal cancer RISk Prediction tool ('CRISP') for use in primary care. The aim of the CRISP tool is to increase risk-appropriate CRC screening. METHODS: CRISP development was informed by previous experience with developing risk tools for use in primary care and a systematic review of the evidence. A CRISP prototype was used in simulated consultations by general practitioners (GPs) with actors as patients. GPs were interviewed to explore their experience of using CRISP, and practice nurses (PNs) and practice managers (PMs) were interviewed after a demonstration of CRISP. Transcribed interviews and video footage of the 'consultations' were qualitatively analyzed. Themes arising from the data were mapped onto Normalization Process Theory (NPT). RESULTS: Fourteen GPs, nine PNs and six PMs were recruited from 12 clinics. Results were described using the four constructs of NPT: 1) Coherence: Clinicians understood the rationale behind CRISP, particularly since they were familiar with using risk tools for other conditions; 2) Cognitive participation: GPs welcomed the opportunity CRISP provided to discuss healthy and unhealthy behaviors with their patients, but many GPs challenged the screening recommendation generated by CRISP; 3) Collective Action: CRISP disrupted clinician-patient flow if the GP was less comfortable with computers. GP consultation time was a major implementation barrier and overall consensus was that PNs have more capacity and time to use CRISP effectively; 4) Reflexive monitoring: Limited systematic monitoring of new interventions is a potential barrier to the sustainable embedding of CRISP. CONCLUSIONS: CRISP has the potential to improve risk-appropriate CRC screening in primary care but was considered more likely to be successfully implemented as a nurse-led intervention.This study was funded by a National Health and Medical Research Council (NHMRC) Centre for Research Excellence grant (APP1042021). M Pirotta is supported by an NHMRC Career Development Fellowship. JD Emery is supported by an NHMRC Practitioner Fellowship. FM Walter is supported by a NIHR Clinician Scientist award

Testing for Gene-Environment Interactions Using a Prospective Family Cohort Design: Body Mass Index in Early and Later Adulthood and Risk of Breast Cancer

The ability to classify people according to their underlying genetic susceptibility to a disease is increasing with new knowledge, better family data, and more sophisticated risk prediction models, allowing for more effective prevention and screening. To do so, however, we need to know whether risk associations are the same for people with different genetic susceptibilities. To illustrate one way to estimate such gene-environment interactions, we used prospective data from 3 Australian family cancer cohort studies, 2 enriched for familial risk of breast cancer. There were 288 incident breast cancers in 9,126 participants from 3,222 families. We used Cox proportional hazards models to investigate whether associations of breast cancer with body mass index (BMI; weight (kg)/height (m)$^2$ ) at age 18–21 years, BMI at baseline, and change in BMI differed according to genetic risk based on lifetime breast cancer risk from birth, as estimated by BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) software, adjusted for age at baseline data collection. Although no interactions were statistically signifi- cant, we have demonstrated the power with which gene-environment interactions can be investigated using a cohort enriched for persons with increased genetic risk and a continuous measure of genetic risk based on family history.The Australian Breast Cancer Family Registry (ABCFR) was supported in Australia by the National Health and Medical Research Council, the New South Wales Cancer Council, the Victorian Health Promotion Foundation, the Victorian Breast Cancer Research Consortium, Cancer Australia, and the National Breast Cancer Foundation. The ABCFR was also supported by the National Cancer Institute, US National Institutes of Health, under Request for Application CA-06-503 and through cooperative agreements with members of the Breast Cancer Family Registry: the University of Melbourne (Melbourne, Victoria, Australia) (grant U01 CA69638); the Fox Chase Cancer Center (Philadelphia, Pennsylvania) (grant U01 CA69631); the Huntsman Cancer Institute (Salt Lake City, Utah) (grant U01 CA69446); Columbia University (New York, New York) (grant U01 CA69398); the Cancer Prevention Institute of California (Fremont, California) (grant U01 CA69417); and Cancer Care Ontario (Toronto, Ontario, Canada) (grant U01 CA69467). The Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) was supported by a grant from the Australian National Breast Cancer Foundation and previously by the National Health and Medical Research Council, the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and the Cancer Foundation of Western Australia. The Australasian Colorectal Cancer Family Registry (ACCFR) was supported by grant UM1 CA167551 from the National Cancer Institute, US National Institutes of Health, and through cooperative agreements with the members and Principal Investigators of the ACCFR (grants U01 CA074778 and U01/U24 CA097735). A.K.W. is a National Health and Medical Research Council Early Career Fellow. M.A.J. is a National Health and Medical Research Council Senior Research Fellow. K.A.P. is an Australian National Breast Cancer Foundation Fellow

Body mass index in early adulthood and colorectal cancer risk for carriers and non-carriers of germline mutations in DNA mismatch repair genes

BACKGROUND: Carriers of germline mutations in DNA mismatch repair (MMR) genes have a high risk of colorectal cancer (CRC), but the modifiers of this risk are not well established. We estimated an association between body mass index (BMI) in early adulthood and subsequent risk of CRC for carriers and, as a comparison, estimated the association for non-carriers. METHODS: A weighted Cox regression was used to analyse height and weight at 20 years reported by 1324 carriers of MMR gene mutations (500 MLH1, 648 MSH2, 117 MSH6 and 59 PMS2) and 1219 non-carriers from the Colon Cancer Family Registry. RESULTS: During 122,304 person-years of observation, we observed diagnoses of CRC for 659 carriers (50%) and 36 non-carriers (3%). For carriers, the risk of CRC increased by 30% for each 5 kg m(-2) increment in BMI in early adulthood (hazard ratio, HR: 1.30; 95% confidence interval, CI: 1.08-1.58; P=0.01), and increased by 64% for non-carriers (HR: 1.64; 95% CI: 1.02-2.64; P=0.04) after adjusting for sex, country, cigarette smoking and alcohol drinking (and the MMR gene that was mutated in carriers). The difference in HRs for carriers and non-carriers was not statistically significant (P=0.50). For MLH1 and PMS2 (MutLα heterodimer) mutation carriers combined, the corresponding increase was 36% (HR: 1.36; 95% CI: 1.05-1.76; P=0.02). For MSH2 and MSH6 (MutSα heterodimer) mutation carriers combined, the HR was 1.26 (95% CI: 0.96-1.65; P=0.09). There was no significant difference between the HRs for MutLα and MutSα heterodimer carriers (P=0.56). CONCLUSION: Body mass index in early adulthood is positively associated with risk of CRC for MMR gene mutation carriers and non-carriers

Body mass index in early adulthood and colorectal cancer risk for carriers and non-carriers of germline mutations in DNA mismatch repair genes

BACKGROUND: Carriers of germline mutations in DNA mismatch repair (MMR) genes have a high risk of colorectal cancer (CRC), but the modifiers of this risk are not well established. We estimated an association between body mass index (BMI) in early adulthood and subsequent risk of CRC for carriers and, as a comparison, estimated the association for non-carriers. METHODS: A weighted Cox regression was used to analyse height and weight at 20 years reported by 1324 carriers of MMR gene mutations (500 MLH1, 648 MSH2, 117 MSH6 and 59 PMS2) and 1219 non-carriers from the Colon Cancer Family Registry. RESULTS: During 122,304 person-years of observation, we observed diagnoses of CRC for 659 carriers (50%) and 36 non-carriers (3%). For carriers, the risk of CRC increased by 30% for each 5 kg m(-2) increment in BMI in early adulthood (hazard ratio, HR: 1.30; 95% confidence interval, CI: 1.08-1.58; P=0.01), and increased by 64% for non-carriers (HR: 1.64; 95% CI: 1.02-2.64; P=0.04) after adjusting for sex, country, cigarette smoking and alcohol drinking (and the MMR gene that was mutated in carriers). The difference in HRs for carriers and non-carriers was not statistically significant (P=0.50). For MLH1 and PMS2 (MutLα heterodimer) mutation carriers combined, the corresponding increase was 36% (HR: 1.36; 95% CI: 1.05-1.76; P=0.02). For MSH2 and MSH6 (MutSα heterodimer) mutation carriers combined, the HR was 1.26 (95% CI: 0.96-1.65; P=0.09). There was no significant difference between the HRs for MutLα and MutSα heterodimer carriers (P=0.56). CONCLUSION: Body mass index in early adulthood is positively associated with risk of CRC for MMR gene mutation carriers and non-carriers

PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

Background: The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.Methods: We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T&gt;G and c.3113G&gt;A, CHEK2c.349A&gt;G, c.538C&gt;T, c.715G&gt;A, c.1036C&gt;T, c.1312G&gt;T, and c.1343T&gt;G and ATM c.7271T&gt;G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.Results: For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G&gt;A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T&gt;G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A&gt;G OR 2.26 (95% CI 1.29 to 3.95), c.1036C&gt;T OR 5.06 (95% CI 1.09 to 23.5) and c.538C&gt;T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T&gt;G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G&gt;T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.Conclusions: This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.</p