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Nonlinear response of mid-latitude weather to the changing Arctic
Overland, James E.,Dethloff, Klaus,Francis, Jennifer A.,Hall, Richard J.,Hanna, Edward,Kim, Seong-Joong,Screen, James A.,Shepherd, Theodore G.,Vihma, Timo Nature Publishing Group, a division of Macmillan P 2016 Nature climate change Vol.6 No.11
<P>Are continuing changes in the Arctic influencing wind patterns and the occurrence of extreme weather events in northern mid-latitudes? The chaotic nature of atmospheric circulation precludes easy answers. The topic is a major science challenge, as continued Arctic temperature increases are an inevitable aspect of anthropogenic climate change. We propose a perspective that rejects simple cause-and-effect pathways and notes diagnostic challenges in interpreting atmospheric dynamics. We present a way forward based on understanding multiple processes that lead to uncertainties in Arctic and mid-latitude weather and climate linkages. We emphasize community coordination for both scientific progress and communication to a broader public.</P>
Interpretive Performance and Inter-Observer Agreement on Digital Mammography Test Sets
Sung Hun Kim,Eun Hye Lee,Jae Kwan Jun,You Me Kim,Yun-Woo Chang,Jin Hwa Lee,Hye-Won Kim,Eun Jung Choi,the Alliance for Breast Cancer Screening in Korea (ABCS-K) 대한영상의학회 2019 Korean Journal of Radiology Vol.20 No.2
Objective: To evaluate the interpretive performance and inter-observer agreement on digital mammographs among radiologists and to investigate whether radiologist characteristics affect performance and agreement. Materials and Methods: The test sets consisted of full-field digital mammograms and contained 12 cancer cases among 1000 total cases. Twelve radiologists independently interpreted all mammograms. Performance indicators included the recall rate, cancer detection rate (CDR), positive predictive value (PPV), sensitivity, specificity, false positive rate (FPR), and area under the receiver operating characteristic curve (AUC). Inter-radiologist agreement was measured. The reporting radiologist characteristics included number of years of experience interpreting mammography, fellowship training in breast imaging, and annual volume of mammography interpretation. Results: The mean and range of interpretive performance were as follows: recall rate, 7.5% (3.3–10.2%); CDR, 10.6 (8.0–12.0 per 1000 examinations); PPV, 15.9% (8.8–33.3%); sensitivity, 88.2% (66.7–100%); specificity, 93.5% (90.6–97.8%); FPR, 6.5% (2.2–9.4%); and AUC, 0.93 (0.82–0.99). Radiologists who annually interpreted more than 3000 screening mammograms tended to exhibit higher CDRs and sensitivities than those who interpreted fewer than 3000 mammograms (p = 0.064). The inter-radiologist agreement showed a percent agreement of 77.2–88.8% and a kappa value of 0.27–0.34. Radiologist characteristics did not affect agreement. Conclusion: The interpretative performance of the radiologists fulfilled the mammography screening goal of the American College of Radiology, although there was inter-observer variability. Radiologists who interpreted more than 3000 screening mammograms annually tended to perform better than radiologists who did not.
김영중,이은혜,전재관,신동락,박영미,김혜원,김유미,김금원,임효순,박정선,김혜정,조혜미,the Alliance for Breast Cancer Screening in Korea (ABCS-K) 대한영상의학회 2017 Korean Journal of Radiology Vol.18 No.4
Objective: To analyze participant factors that affect the diagnostic performance of screening mammography. Materials and Methods: We enrolled 128756 cases from 10 hospitals between 2005 and 2010. We analyzed recall rate, cancer detection rate (CDR) per 1000 examinations, positive predictive value (PPV), sensitivity, specificity, false positive rate (FPR), and interval cancer rate (ICR) per 1000 negative examinations according to participant factors including age, breast density, and number of visit to the same institution, and adjusted for confounding variables. Results: Increasing age improved recall rates (27.4% in 40’s, 17.5% in 50’s, 11.1% in 60’s, and 8.6% in 70’s), CDR (2.7, 3.2, 2.0, and 2.4), PPV (1.0, 1.8, 1.8, and 2.8%), sensitivity (81.3, 88.8, 90.3, and 94.7%), specificity (72.7, 82.7, 89.0, and 91.7%), and FPR (27.3, 17.3, 11.0, and 8.4%) (p < 0.05). Higher breast density impaired recall rates (4.0% in P1, 9.0% in P2, 28.9% in P3, and 27.8% in P4), PPV (3.3, 2.3, 1.2, and 1.3%), specificity (96.1, 91.2, 71.4, and 72.5%), and FPR (3.9, 8.9, 28.6, and 27.6%) (p < 0.001). It also increased CDR (1.3, 2.1, 3.3, and 3.6) and ICR (0.2, 0.3, 0.6, and 1.6) (p < 0.05). Successive visits to the same institution improved recall rates (20.9% for one visit, 10.7% for two visits, 7.7% for more than three visits), PPV (1.6, 2.8, and 2.7%), specificity (79.4, 89.6, and 92.5%), and FPR (20.6, 10.4, and 7.5%) (p < 0.001). Conclusion: Young age and dense breasts negatively affected diagnostic performance in mammography screening, whereas successive visits to the same institution had a positive effect. Examinee education for successive visits to the same institution would improve the diagnostic performance.