Promote community engagement in participatory research for improving breast cancer prevention: The P.I.N.K. study framework

Simple Summary More than 50% of breast cancers may be preventable with adherence to healthy lifestyle practices, but the influences of each single preventive/predisposing behaviour and the effects of their combination are still widely debated. The aim of our study was to identify combinations of non-modifiable and lifestyle-related factors that could influence the chance of having breast cancer in post-menopausal women. We used a twofold strategy of analysis that combines traditional statistical methods and innovative data-driven approaches. We identified some combination of women's features and habits at higher risk for breast cancer occurrence. These preliminary findings could be used to inform tailored prevention policy and health education programs for improving communities' self-empowerment. Breast cancer (BC) has overtaken lung cancer as the most common cancer in the world and the projected incidence rates show a further increase. Early detection through population screening remains the cornerstone of BC control, but a progressive change from early diagnosis only-based to a personalized preventive and risk-reducing approach is widely debated. Risk-stratification models, which also include personal lifestyle risk factors, are under evaluation, although the documentation burden to gather population-based data is relevant and traditional data collection methods show some limitations. This paper provides the preliminary results from the analysis of clinical data provided by radiologists and lifestyle data collected using self-administered questionnaires from 5601 post-menopausal women. The weight of the combinations of women's personal features and lifestyle habits on the BC risk were estimated by combining a model-driven and a data-driven approach to analysis. The weight of each factor on cancer occurrence was assessed using a logistic model. Additionally, communities of women sharing common features were identified and combined in risk profiles using social network analysis techniques. Our results suggest that preventive programs focused on increasing physical activity should be widely promoted, in particular among the oldest women. Additionally, current findings suggest that pregnancy, breast-feeding, salt limitation, and oral contraception use could have different effects on cancer risk, based on the overall woman's risk profile. To overcome the limitations of our data, this work also introduces a mobile health tool, the Dress-PINK, designed to collect real patients' data in an innovative way for improving women's response rate, data accuracy, and completeness as well as the timeliness of data availability. Finally, the tool provides tailored prevention messages to promote critical consciousness, critical thinking, and increased health literacy among the general population.