Using Social Listening for Digital Public Health Surveillance of Human Papillomavirus Vaccine Misinformation Online: Exploratory Study

Despite challenges related to the data quality, representativeness, and accuracy of artificial intelligence-driven tools, commercially available social listening platforms have many of the attributes needed to be used for digital public health surveillance of human papillomavirus vaccination misinformation in the online ecosystem.

Abstract D059: Bridge to Good Living: Thriving beyond lung cancer in West Virginia

Introduction: The goal of the Bridge Program is to improve the overall coordination of care, increase quality of life, and decrease the consequences of treatment for patients diagnosed with lung cancer.

Brief Description: Patients diagnosed with late stage lung cancer are often referred to supportive or palliative care programs that provide symptom management, psychosocial support and follow up, as well as advanced planning. In contrast, the needs of patients diagnosed at a curable or early stage often go unaddressed. The focus of the Bridge Program is to develop and implement a comprehensive survivorship program for Stage 1-3 lung cancer patients completing curative treatment.

The Bridge Program enrolls and assesses patients at the end of cancer treatment utilizing a multidisciplinary team approach. The Program’s goal is to improve patient and caregiver quality of life in the major life domains of physical, social, psychological, and spiritual. We see this program bridging patients from active cancer care to the next step on their journey in life. Using a multidisciplinary team approach creates an opportunity for collaboration and information sharing that leads to the development of an enhanced survivorship care plan.

Summary of Data: Between March 2017 and June 2019, the Bridge Program enrolled 81 patients across three locations. At the end of cancer care, 100% of these patients had at least one unmet need and nearly half had seven or more. Assessment identified a total of 540 unmet needs which resulted in 132 clinician referrals. When categorizing unmet needs into physical, practical, and emotional domains, Bridge patients identified more unmet needs in the physical category than any other. The most common referrals were for Physical Therapy and Occupational Therapy. Following enrollment into the Program, 93% of Bridge patients showed a decrease in the number of unmet needs at their first recurrence and monitoring visit.

When comparing a cohort of Bridge enrolled verses non-Bridge patients, we found that prior to visiting the Emergency Department, Bridge patients contacted their treatment team at a higher rate than non-Bridge patients and that the completion of Survivorship Care Plans was 100% for Bridge patients and only 38% for non-Bridge patients.

Conclusion: Lung cancer patients have many unmet needs following active treatment for lung cancer. The Bridge Program addresses a cancer that is not frequently talked about in survivorship care: lung cancer. With increased screening and improvements in treatment, we can anticipate an increase in the number of lung cancer survivors. The Bridge Program provides a novel patient-centered model that addresses a cohort of patients that are often older and sicker than other cancer patients.

Note: This abstract was not presented at the conference.

Citation Format: Stephenie K Kennedy-Rea, Anne Swisher, Adrienne Duckworth, Tara Miller, Salman Osmon, Abby Starkey, Megan Burkart, Garth Graebe, Mary Anne Yanosik, Rachel Harper, Amy Allen. Bridge to Good Living: Thriving beyond lung cancer in West Virginia [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr D059.

Genome-wide prediction of stop codon readthrough during translation in the yeast Saccharomyces cerevisiae

In-frame stop codons normally signal termination during mRNA translation, but they can be read as 'sense' (readthrough) depending on their context, comprising the 6 nt preceding and following the stop codon. To identify novel contexts directing readthrough, under-represented 5' and 3' stop codon contexts from Saccharomyces cerevisiae were identified by genome-wide survey in silico. In contrast with the nucleotide bias 3' of the stop codon, codon bias in the two codon positions 5' of the termination codon showed no correlation with known effects on stop codon readthrough. However, individually, poor 5' and 3' context elements were equally as effective in promoting stop codon readthrough in vivo, readthrough which in both cases responded identically to changes in release factor concentration. A novel method analysing specific nucleotide combinations in the 3' context region revealed positions +1,2,3,5 and +1,2,3,6 after the stop codon were most predictive of termination efficiency. Downstream of yeast open reading frames (ORFs), further in-frame stop codons were significantly over-represented at the +1, +2 and +3 codon positions after the ORF, acting to limit readthrough. Thus selection against stop codon readthrough is a dominant force acting on 3', but not on 5', nucleotides, with detectable selection on nucleotides as far downstream as +6 nucleotides. The approaches described can be employed to define potential readthrough contexts for any genome.