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

Abstract 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

iPrevent®: a tailored, web-based, decision support tool for breast cancer risk assessment and management

We aimed to develop a user-centered, web-based, decision support tool for breast cancer risk assessment and personalized risk management. Using a novel model choice algorithm, iPrevent® selects one of two validated breast cancer risk estimation models (IBIS or BOADICEA), based on risk factor data entered by the user. Resulting risk estimates are presented in simple language and graphic formats for easy comprehension. iPrevent® then presents risk-adapted, evidence-based, guideline-endorsed management options. Development was an iterative process with regular feedback from multidisciplinary experts and consumers. To verify iPrevent®, risk factor data for 127 cases derived from the Australian Breast Cancer Family Study were entered into iPrevent®, IBIS (v7.02), and BOADICEA (v3.0). Consistency of the model chosen by iPrevent® (i.e., IBIS or BOADICEA) with the programmed iPrevent® model choice algorithm was assessed. Estimated breast cancer risks from iPrevent® were compared with those attained directly from the chosen risk assessment model (IBIS or BOADICEA). Risk management interventions displayed by iPrevent® were assessed for appropriateness. Risk estimation model choice was 100% consistent with the programmed iPrevent®logic. Discrepant 10-year and residual lifetime risk estimates of >1% were found for 1 and 4 cases, respectively, none was clinically significant (maximal variation 1.4%). Risk management interventions suggested by iPrevent® were 100% appropriate. iPrevent® successfully integrates the IBIS and BOADICEA risk assessment models into a decision support tool that provides evidence-based, risk-adapted risk management advice. This may help to facilitate precision breast cancer prevention discussions between women and their healthcare providers

Cancer risk in 680 000 people exposed to computed tomography scans in childhood or adolescence: Data linkage study of 11 million Australians

Objective To assess the cancer risk in children and adolescents following exposure to low dose ionising radiation from diagnostic computed tomography (CT) scans. Design Population based, cohort, data linkage study in Australia. Cohort members 10.9 million people identified from Australian Medicare records, aged 0-19 years on 1 January 1985 or born between 1 January 1985 and 31 December 2005; all exposures to CT scans funded by Medicare during 1985-2005 were identified for this cohort. Cancers diagnosed in cohort members up to 31 December 2007 were obtained through linkage to national cancer records. Main outcome Cancer incidence rates in individuals exposed to a CT scan more than one year before any cancer diagnosis, compared with cancer incidence rates in unexposed individuals. Results 60 674 cancers were recorded, including 3150 in 680 211 people exposed to a CT scan at least one year before any cancer diagnosis. The mean duration of follow-up after exposure was 9.5 years. Overall cancer incidence was 24% greater for exposed than for unexposed people, after accounting for age, sex, and year of birth (incidence rate ratio (IRR) 1.24 (95% confidence interval 1.20 to 1.29); P<0.001). We saw a dose-response relation, and the IRR increased by 0.16 (0.13 to 0.19) for each additional CT scan. The IRR was greater after exposure at younger ages (P<0.001 for trend). At 1-4, 5-9, 10-14, and 15 or more years since first exposure, IRRs were 1.35 (1.25 to 1.45), 1.25 (1.17 to 1.34), 1.14 (1.06 to 1.22), and 1.24 (1.14 to 1.34), respectively. The IRR increased significantly for many types of solid cancer (digestive organs, melanoma, soft tissue, female genital, urinary tract, brain, and thyroid); leukaemia, myelodysplasia, and some other lymphoid cancers. There was an excess of 608 cancers in people exposed to CT scans (147 brain, 356 other solid, 48 leukaemia or myelodysplasia, and 57 other lymphoid). The absolute excess incidence rate for all cancers combined was 9.38 per 100 000 person years at risk, as of 31 December 2007. The average effective radiation dose per scan was estimated as 4.5 mSv. Conclusions The increased incidence of cancer after CT scan exposure in this cohort was mostly due to irradiation. Because the cancer excess was still continuing at the end of follow-up, the eventual lifetime risk from CT scans cannot yet be determined. Radiation doses from contemporary CT scans are likely to be lower than those in 1985-2005, but some increase in cancer risk is still likely from current scans. Future CT scans should be limited to situations where there is a definite clinical indication, with every scan optimised to provide a diagnostic CT image at the lowest possible radiation dose

The use of a risk assessment and decision support tool (CRISP) compared with usual care in general practice to increase risk-stratified colorectal cancer screening: study protocol for a randomised controlled trial.

BACKGROUND: Australia and New Zealand have the highest incidence rates of colorectal cancer worldwide. In Australia there is significant unwarranted variation in colorectal cancer screening due to low uptake of the immunochemical faecal occult blood test, poor identification of individuals at increased risk of colorectal cancer, and over-referral of individuals at average risk for colonoscopy. Our pre-trial research has developed a novel Colorectal cancer RISk Prediction (CRISP) tool, which could be used to implement precision screening in primary care. This paper describes the protocol for a phase II multi-site individually randomised controlled trial of the CRISP tool in primary care. METHODS: This trial aims to test whether a standardised consultation using the CRISP tool in general practice (the CRISP intervention) increases risk-appropriate colorectal cancer screening compared to control participants who receive standardised information on cancer prevention. Patients between 50 and 74 years old, attending an appointment with their general practitioner for any reason, will be invited into the trial. A total of 732 participants will be randomised to intervention or control arms using a computer-generated allocation sequence stratified by general practice. The primary outcome (risk-appropriate screening at 12 months) will be measured using baseline data for colorectal cancer risk and objective health service data to measure screening behaviour. Secondary outcomes will include participant cancer risk perception, anxiety, cancer worry, screening intentions and health service utilisation measured at 1, 6 and 12 months post randomisation. DISCUSSION: This trial tests a systematic approach to implementing risk-stratified colorectal cancer screening in primary care, based on an individual's absolute risk, using a state-of-the-art risk assessment tool. Trial results will be reported in 2020. TRIAL REGISTRATION: Australian and New Zealand Clinical Trial Registry, ACTRN12616001573448p . Registered on 14 November 2016

Accuracy of Risk Estimates from the iPrevent Breast Cancer Risk Assessment and Management Tool.

BACKGROUND: iPrevent is an online breast cancer (BC) risk management decision support tool. It uses an internal switching algorithm, based on a woman's risk factor data, to estimate her absolute BC risk using either the International Breast Cancer Intervention Study (IBIS) version 7.02, or Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm version 3 models, and then provides tailored risk management information. This study assessed the accuracy of the 10-year risk estimates using prospective data. METHODS: iPrevent-assigned 10-year invasive BC risk was calculated for 15 732 women aged 20-70 years and without BC at recruitment to the Prospective Family Study Cohort. Calibration, the ratio of the expected (E) number of BCs to the observed (O) number and discriminatory accuracy were assessed. RESULTS: During the 10 years of follow-up, 619 women (3.9%) developed BC compared with 702 expected (E/O = 1.13; 95% confidence interval [CI] =1.05 to 1.23). For women younger than 50 years, 50 years and older, and BRCA1/2-mutation carriers and noncarriers, E/O was 1.04 (95% CI = 0.93 to 1.16), 1.24 (95% CI = 1.11 to 1.39), 1.13 (95% CI = 0.96 to 1.34), and 1.13 (95% CI = 1.04 to 1.24), respectively. The C-statistic was 0.70 (95% CI = 0.68 to 0.73) overall and 0.74 (95% CI = 0.71 to 0.77), 0.63 (95% CI = 0.59 to 0.66), 0.59 (95% CI = 0.53 to 0.64), and 0.65 (95% CI = 0.63 to 0.68), respectively, for the subgroups above. Applying the newer IBIS version 8.0b in the iPrevent switching algorithm improved calibration overall (E/O = 1.06, 95% CI = 0.98 to 1.15) and in all subgroups, without changing discriminatory accuracy. CONCLUSIONS: For 10-year BC risk, iPrevent had good discriminatory accuracy overall and was well calibrated for women aged younger than 50 years. Calibration may be improved in the future by incorporating IBIS version 8.0b