Population-Based Precision Cancer Screening: A Symposium on Evidence, Epidemiology, and Next Steps

Precision medicine, an emerging approach for disease treatment that takes into account individual variability in genes, environment, and lifestyle, is under consideration for preventive interventions, including cancer screening. On September 29, 2015, the National Cancer Institute sponsored a symposium entitled “Precision Cancer Screening in the General Population: Evidence, Epidemiology, and Next Steps”. The goal was two-fold: to share current information on the evidence, practices, and challenges surrounding precision screening for breast, cervical, colorectal, lung, and prostate cancers, and to allow for in-depth discussion among experts in relevant fields regarding how epidemiology and other population sciences can be used to generate evidence to inform precision screening strategies. Attendees concluded that the strength of evidence for efficacy and effectiveness of precision strategies varies by cancer site, that no one research strategy or methodology would be able or appropriate to address the many knowledge gaps in precision screening, and that issues surrounding implementation must be researched as well. Additional discussion needs to occur to identify the high priority research areas in precision cancer screening for pertinent organs and to gather the necessary evidence to determine whether further implementation of precision cancer screening strategies in the general population would be feasible and beneficial

Negative cancer beliefs: Socioeconomic differences from the awareness and beliefs about cancer survey

OBJECTIVE: Socioeconomic gaps in cancer mortality may be driven partially by poorer uptake of early detection behaviors among lower socioeconomic status (SES) groups. Lower SES groups may hold both fewer positive and more negative cancer beliefs that discourage these behaviors. We examined SES differences in positive and negative cancer beliefs in US adults. METHODS: We conducted telephone interviews with a population-representative sample, aged 50+, using the Awareness and Beliefs about Cancer (ABC) instrument (N=1,425). Cancer beliefs were measured using three positively and three negatively framed items. We used multivariable logistic regression models to examine associations between beliefs and education, which served as a marker of individual-level SES. RESULTS: Agreement with positive statements was high (>80%) and did not vary with education, while agreement with negative statements varied. Relative to adults with a bachelor's degree, adults with a high school degree or less were more likely to agree that "treatment is worse than cancer" (45.2% vs. 68.2%; adjusted odds ratio (aOR)=2.43, 99% confidence interval (CI)=1.50-3.94), cancer is "a death sentence" (17.4% vs. 33.2%; aOR=2.51, 99% CI=1.45-4.37), and they "would not want to know if I have cancer" (15.7% vs. 31.6%; aOR=2.88, 99% CI=1.54-5.36). CONCLUSIONS: Positive cancer statements were generally endorsed, but negative statements were more frequently endorsed by lower SES groups. Additional work is needed to understand how negative beliefs develop and coexist alongside positive beliefs. Interventions to improve detection behaviors targeting lower SES groups may benefit from focusing on reducing negative beliefs, rather than increasing positive beliefs. This article is protected by copyright. All rights reserved

Keen2Act: Activity recommendation in online social collaborative platforms

Social collaborative platforms such as GitHub and Stack Overflow have been increasingly used to improve work productivity via collaborative efforts. To improve user experiences in these platforms, it is desirable to have a recommender system that can suggest not only items (e.g., a GitHub repository) to a user, but also activities to be performed on the suggested items (e.g., forking a repository). To this end, we propose a new approach dubbed Keen2Act, which decomposes the recommendation problem into two stages: the Keen and Act steps. The Keen step identifies, for a given user, a (sub)set of items in which he/she is likely to be interested. The Act step then recommends to the user which activities to perform on the identified set of items. This decomposition provides a practical approach to tackling complex activity recommendation tasks while producing higher recommendation quality. We evaluate our proposed approach using two real-world datasets and obtain promising results whereby Keen2Act outperforms several baseline models.Comment: ACM Conference on User Modeling, Adaptation and Personalizatio

Cancer Symptom Recognition and Anticipated Delays in Seeking Care Among U.S. Adults

Introduction Early stage diagnosis strongly predicts cancer survival. Recognition of potential symptoms of cancer may improve survival by reducing time to seeking care. Methods Telephone interviews with a population-representative sample of English-speaking adults (aged ≥50 years) in the U.S. (N=1,425) were conducted in 2014 using an instrument adapted from the International Cancer Benchmarking Partnership Awareness and Beliefs about Cancer survey. Anticipated time to seeking care for four cancer symptoms (persistent cough, rectal bleeding, mole changes, and breast changes) was assessed, and delay was defined as waiting >2 weeks. Recognition of symptoms as potential cancer signs was assessed dichotomously. Multivariate logistic regression models were used to assess associations between symptom recognition and anticipated delay, adjusting for demographics, cancer experience, self-reported health, and healthcare access. Analyses were weighted and conducted in 2017. Results Symptom recognition varied but was relatively high across all symptoms (76.9%–95.5%). Anticipated delay varied by symptom and was highest for persistent cough (41.2%) and lowest for rectal bleeding (9.1%). For rectal bleeding (AOR=2.65, 95% CI=1.31, 5.36) and mole changes (AOR=3.30, 95% CI=1.48, 7.33), anticipated delay was more likely among individuals who did not recognize the symptom as a warning sign. Adults with lower education levels (p<0.05) and African Americans (p<0.05) were less likely to delay for some symptoms. Conclusions Lack of symptom recognition was associated with anticipated delay in seeking care for some cancer symptoms. Differences in recognition and delays by symptom could be driven partly by screening messaging or by ambiguity and functional impact of each symptom