No abstract

Despite considerable research efforts, pancreatic cancer is associated with a dire prognosis and a 5-year survival rate of only 10%. Early symptoms of the disease are mostly nonspecific. The premise of improved survival through early detection is that more individuals will benefit from potentially curative treatment. Artificial intelligence (AI) methodology has emerged as a successful tool for risk stratification and identification in general health care. In response to the maturity of AI, Kenner Family Research Fund conducted the 2020 AI and Early Detection of Pancreatic Cancer Virtual Summit ( www.pdac-virtualsummit.org ) in conjunction with the American Pancreatic Association, with a focus on the potential of AI to advance early detection efforts in this disease. This comprehensive presummit article was prepared based on information provided by each of the interdisciplinary participants on one of the 5 following topics: Progress, Problems, and Prospects for Early Detection; AI and Machine Learning; AI and Pancreatic Cancer—Current Efforts; Collaborative Opportunities; and Moving Forward—Reflections from Government, Industry, and Advocacy. The outcome from the robust Summit conversations, to be presented in a future white paper, indicate that significant progress must be the result of strategic collaboration among investigators and institutions from multidisciplinary backgrounds, supported by committed funders.

No abstract

The IHPBA/AHPBA-sponsored 2016 minimally invasive pancreatic resection (MIPR) conference held on April 20th, 2016 included a session designed to evaluate what would be the most appropriate scientific contribution to help define the increasing role of MIPR internationally. Participants in the conference reviewed the assessment of numerous pertinent scientific designs including randomized controlled trial (RCT), pragmatic international RCT, registry-RCT, non-RCT with propensity matching, and various types of clinical registries including those aiming to create a quality improvement data system or a learning health care system. The strengths and weaknesses of each of these designs, the status of trials which are currently recruiting patients, and pragmatic considerations were evaluated. A recommendation was made to establish a clinical registry to collect data prospectively from around the world to assess current practices and provide a framework for future studies in MIPR.

2016-12-23T18:52:10

Supplemental digital content is available in the text.

ObjectivesPatient education and resources that address barriers to health literacy to improve understanding in pancreatic cancer are limited. We evaluated the impact and outcomes benefits of Animated Pancreas Patient (APP) cancer educational modules (APP website and YouTube).MethodsA retrospective study of APP metrics and utilization data from September 2013 to February 2021 was conducted. We evaluated audience reach and calculated top views by media type (animation/expert video/patient video/slideshow) and top retention videos from the modules.ResultsDuring the study period, APP had 4,551,079 views worldwide of which 2,757,064 unique visitors or 60% were from the United States. Of these, 54% were patients, 17% were family members or caregivers, 16% were health care providers, and 13% were other. The most popular topic viewed among the animations was “Understanding Clinical Trials” (n = 182,217), and the most common expert video viewed was “What are the different stages of pancreatic cancer?” (n = 15,357).ConclusionsPancreatic cancer patient education using APP's visual formats of learning demonstrated a wide reach and had a significant impact on improved understanding among patients, families, and caregivers. Continued efforts should be made to provide patient resources that address health literacy, better quality of life and improved health outcomes in pancreatic cancer.

No abstract