The Ark: a customizable web-based data management tool for health and medical research.

Summary: The Ark is an open-source web-based tool that allows researchers to manage health and medical research data for humans and animals without specialized database skills or programming expertise. The system provides data management for core research information including demographic, phenotype, biospecimen and pedigree data, in addition to supporting typical investigator requirements such as tracking participant consent and correspondence, whilst also being able to generate custom data exports and reports. The Ark is 'study generic' by design and highly configurable via its web interface, allowing researchers to tailor the system to the specific data management requirements of their study. Availability and Implementation: Source code for The Ark can be obtained freely from the website https://github.com/The-Ark-Informatics/ark/ . The source code can be modified and redistributed under the terms of the GNU GPL v3 license. Documentation and a pre-configured virtual appliance can be found at the website http://sphinx.org.au/the-ark/ . Contact: adrianb@unimelb.edu.au. Supplementary information: Supplementary data are available at Bioinformatics online.

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.

Benefits and harms of aspirin to reduce colorectal cancer risk: a cross-sectional study of methods to communicate risk in primary care.

BACKGROUND: New Australian guidelines recommend that GPs actively consider prescribing low-dose aspirin to patients aged 50-70 years to reduce their risk of developing colorectal cancer (CRC). Patients and GPs need to understand the relative benefits and harms to support informed decision making. AIM: To develop and examine different methods to communicate the benefits and harms of taking aspirin for CRC prevention. DESIGN AND SETTING: A cross-sectional, vignette study with patients aged 50-70 years consecutively recruited from general practices in Melbourne, Australia, between July and August 2018. METHOD: Summary estimates from meta-analyses of the effects of aspirin on the incidence of CRC, cardiovascular disease, gastrointestinal bleeding, and incidence rates in the Australian population to estimate outcomes in a hypothetical population of 10 000 people aged 50-70 years. These estimates were presented using four different risk communication formats. Participants were shown these different formats and asked if they would take aspirin to prevent CRC. RESULTS: A total of 313 participants were recruited (95.1% recruitment rate), of whom 304 completed the study. Most participants (71.7-75.3%) reported they would take aspirin irrespective of risk format presented. Bar charts (odds ratio [OR] 1.20, 95% confidence intervals [CI] = 1.01 to 1.44) and expected frequency trees (OR 1.18, 95% CI = 0.99 to 1.41) were more strongly associated with the intentions to take aspirin compared with icon arrays. Bar charts were most preferred for presenting risk information. CONCLUSION: A large proportion of participants in this study intended to take aspirin to reduce their CRC risk regardless of risk communication format. Bar charts and expected frequency trees were the preferred methods to present the benefits and harms of taking aspirin to prevent CRC.