Pregnancy and Breast Cancer: when They Collide

Women of childbearing age experience an increased breast cancer risk associated with a completed pregnancy. For younger women, this increase in breast cancer risk is transient and within a decade after parturition a cross over effect results in an ultimate protective benefit. The post-partum peak of increased risk is greater in women with advanced maternal age. Further, their lifetime risk for developing breast cancer remains elevated for many years, with the cross over to protection occurring decades later or not at all. Breast cancers diagnosed during pregnancy and within a number of years post-partum are termed pregnancy-associated or PABC. Contrary to popular belief, PABC is not a rare disease and could affect up to 40,000 women in 2009. The collision between pregnancy and breast cancer puts women in a fear-invoking paradox of their own health, their pregnancy, and the outcomes for both. We propose two distinct subtypes of PABC: breast cancer diagnosed during pregnancy and breast cancer diagnosed post-partum. This distinction is important because emerging epidemiologic data highlights worsened outcomes specific to post-partum cases. We reported that post-partum breast involution may be responsible for the increased metastatic potential of post-partum PABC. Increased awareness and detection, rationally aggressive treatment, and enhanced understanding of the mechanisms are imperative steps toward improving the prognosis for PABC. If we determine the mechanisms by which involution promotes metastasis of PABC, the post-partum period can be a window of opportunity for intervention strategies

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Virtual external implementation facilitation: successful methods for remotely engaging groups in quality improvement

BACKGROUND: Relatively little guidance exists on how to use virtual implementation facilitation to successfully implement evidence-based practices and innovations into clinical programs. Yet virtual methods are increasingly common. They have potentially wider reach, emergent public health situations necessitate their use, and restrictions on resources can make them more attractive. We therefore outline a set of principles for virtual external implementation facilitation and a series of recommendations based on extensive experience successfully using virtual external implementation facilitation in a national program. MODEL AND RECOMMENDATIONS: Success in virtual external implementation facilitation may be achieved by facilitators applying three overarching principles: pilot everything, incorporate a model, and prioritize metacognition. Five practical principles also help: plan in advance, communicate in real time, build relationships, engage participants, and construct a virtual room for participants. We present eight concrete suggestions for enacting the practical principles: (1) assign key facilitation roles to facilitation team members to ensure the program runs smoothly; (2) create small cohorts of participants so they can have meaningful interactions; (3) provide clarity and structure for all participant interactions; (4) structure program content to ensure key points are described, reinforced, and practiced; (5) use visuals to supplement audio content; (6) build activities into the agenda that enable participants to immediately apply knowledge at their own sites, separate from the virtual experience; (7) create backup plans whenever possible; and (8) engage all participants in the program. These principles represent a novel conceptualization of virtual external implementation facilitation, giving structure to a process that has been, to date, inadequately described. The associated actions are demonstrably useful in supporting the principles and offer teams interested in virtual external implementation facilitation concrete methods by which to ensure success. Our examples stem from experiences in healthcare. But the principles can, in theory, be applied to virtual external implementation facilitation regardless of setting, as they and the associated actions are not setting specific