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High-depth African genomes inform human migration and health (vol 586, pg 741, 2020)

NATURE 2021年第7856期592卷 E26-E26页

作者： Choudhury, Ananyo Aron, Shaun Botigue, Laura R. Sengupta, Dhriti Botha, Gerrit Bensellak, Taoufik Wells, Gordon Kumuthini, Judit Shriner, Daniel Fakim, Yasmina J. Ghoorah, Anisah W. Dareng, Eileen Odia, Trust Falola, Oluwadamilare Adebiyi, Ezekiel Hazelhurst, Scott Mazandu, Gaston Nyangiri, Oscar A. Mbiyavanga, Mamana Benkahla, Alia Kassim, Samar K. Mulder, Nicola Adebamowo, Sally N. Chimusa, Emile R. Muzny, Donna Metcalf, Ginger Gibbs, Richard A. Matovu, Enock Bucheton, Bruno Hertz-Fowler, Christiane Koffi, Mathurin Macleod, Annette Mumba-Ngoyi, Dieudonne Noyes, Harry Nyangiri, Oscar A. Simo, Gustave Simuunza, Martin Rotimi, Charles Ramsay, Michele Choudhury, Ananyo Choudhury, Ananyo Aron, Shaun Botigue, Laura Sengupta, Dhriti Botha, Gerrit Bensellak, Taoufik Wells, Gordon Kumuthini, Judit Shriner, Daniel Fakim, Yasmina J. Ghoorah, Anisah W. Dareng, Eileen Odia, Trust Falola, Oluwadamilare Adebiyi, Ezekiel Hazelhurst, Scott Mazandu, Gaston Nyangiri, Oscar A. Mbiyavanga, Mamana Benkahla, Alia Kassim, Samar K. Mulder, Nicola Adebamowo, Sally N. Chimusa, Emile R. Rotimi, Charles Ramsay, Michele Adeyemo, Adebowale A. Lombard, Zane Hanchard, Neil A. Adebamowo, Clement Agongo, Godfred Boua, Romuald P. Oduro, Abraham Sorgho, Hermann Landoure, Guida Cisse, Lassana Diarra, Salimata Samassekou, Oumar Anabwani, Gabriel Matshaba, Mogomotsi Joloba, Moses Kekitiinwa, Adeodata Mardon, Graeme Mpoloka, Sununguko W. Kyobe, Samuel Mlotshwa, Busisiwe Mwesigwa, Savannah Retshabile, Gaone Williams, Lesedi Wonkam, Ambroise Moussa, Ahmed Adu, Dwomoa Ojo, Akinlolu Burke, David Salako, Babatunde O. Matovu, Enock Bucheton, Bruno Hertz-Fowler, Christiane Koffi, Mathurin Macleod, Annette Mumba-Ngoyi, Dieudonne Noyes, Harry Nyangiri, Oscar A. Simo, Gustave Simuunza, Martin Awadalla, Philip Bruat, Vanessa Gbeha, Elias Adeyemo, Adebowale A. Lombard, Zane Hanchard, Neil A. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa School of Electrical and Information Engineering University of the Witwatersrand Johannesburg South Africa Division of Human Genetics National Health Laboratory Service and School of Pathology Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa Navrongo Health Research Centre Navrongo Ghana Clinical Research Unit of Nanoro Institut de Recherche en Sciences de la Sante Bobo-Dioulasso Burkina Faso Center for Research in Agricultural Genomics (CRAG) Plant and Animal Genomics Program CSIC-IRTA-UAB-UB Barcelona Spain Computational Biology Division and H3ABioNet Department of Integrative Biomedical Sciences IDM University of Cape Town Cape Town South Africa System and Data Engineering Team Abdelmalek Essaadi University ENSA Tangier Morocco Centre for Proteomic and Genomic Research (CPGR) Cape Town South Africa South African National Bioinformatics Institute University of the Western Cape Bellville South Africa Africa Health Research Institute Durban South Africa Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA Department of Agriculture and Food Science Faculty of Agriculture University of Mauritius Reduit Mauritius Department of Digital Technologies Faculty of Information Communication & Digital Technologies University of Mauritius Reduit Mauritius Department of Public Health and Primary Care University of Cambridge Cambridge UK Institute of Human Virology Nigeria Abuja Nigeria Department of Epidemiology and Public Health University of Maryland School of Medicine University of Maryland Baltimore Baltimore MD USA University of Maryland Greenebaum Comprehensive Cancer Center University of Maryland School of Medicine University of Maryland Baltimore Baltimore MD USA Institute of Human Virology and Greeneba

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MFP-Unet: A novel deep learning based approach for left ventricle segmentation in echocardiography

arXiv

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arXiv 2019年

作者： Moradi, Shakiba Alizadehasl, Azin Dhooge, Jan Shiri, Isaac Oveisi, Niki Oveisi, Mehrdad Maleki, Majid Ghelich-Oghli, Mostafa Intelligent Imaging Technology Research Center Med Fanavarn Plus Co. 10th St. Shahid Babaee Blvd. Payam Special Economic Zone Karaj Department of Electrical Engineering Sharif University of Technology Tehran Iran Echocardiography and Cardiogenetic research centers Cardio-Oncology Department Rajaie Cardiovascular Medical & Research Center Tehran Department of Cardiovascular Sciences KU Leuven Leuven Belgium Department of Biomedical and Health Informatics Rajaie Cardiovascular Medical and Research Center Iran University of Medical Science Tehran Research Center for Molecular and Cellular Imaging Tehran University of Medical Sciences Tehran Iran School of Population and Public Health University of British Columbia BCV6T1Z4 Canada Department of Computer Science University of British Columbia VancouverBCV6T1Z4 Canada

Segmentation of the Left ventricle (LV) is a crucial step for quantitative measurements such as area, volume, and ejection fraction. However, the automatic LV segmentation in 2D echocardiographic images is a challenging task due to ill-defined borders, and operator dependence issues (insufficient reproducibility). U-net, which is a well-known architecture in medical image segmentation, addressed this problem through an encoder-decoder path. Despite outstanding overall performance, U-net ignores the contribution of all semantic strengths in the segmentation procedure. In the present study, we have proposed a novel architecture to tackle this drawback. Feature maps in all levels of the decoder path of U-net are concatenated, their depths are equalized, and up-sampled to a fixed dimension. This stack of feature maps would be the input of the semantic segmentation layer. The proposed network yielded state-of-the-art results when comparing with results from U-net, dilated U-net, and deeplabv3, using the same dataset. An average Dice Metric (DM) of 0.945, Hausdorff Distance (HD) of 1.62, Jaccard Coefficient (JC) of 0.97, and Mean Absolute Distance (MAD) of 1.32 are achieved. The correlation graph, bland-altman analysis, and box plot showed a great agreement between automatic and manually calculated volume, area, and length. Copyright © 2019, The Authors. All rights reserved.

关键词： Echocardiography

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A Review of Digital Surveillance Methods and Approaches to Combat Prescription Drug Abuse

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Current Addiction Reports 2017年第4期4卷 397-409页

作者： Kalyanam, Janani Mackey, Tim K. Department of Electrical and Computer Engineering University of California San Diego San Diego CA United States Global Health Policy Institute 6256 Greenwich Drive Mail Code: 0172X San Diego 92122 CA United States Department of Anesthesiology University of California San Diego School of Medicine San Diego CA United States Department of Medicine Division of Global Public Health University of California San Diego School of Medicine San Diego CA United States

Purpose of Review: The use of social media to conduct digital surveillance to address different health challenges is growing. This multidisciplinary review assesses the current state of methods and applied research used to conduct digital surveillance for prescription drug abuse. Recent Findings: Fifteen studies met our inclusion criteria from the databases reviewed (PubMed, IEEE Xplore, and ACM Digital Library). The articles were characterized based on their overarching goals and aims, data collection and dataset attributes, and analysis approaches. Overall, reviewed studies grouped into two overarching categories as either being method-focused (advancing novel methodologies using social media data), applied-focused (generating new information on prescription drug abuse behavior), or having both elements. The social media platform most predominantly used was Twitter, with wide variation in sample size and duration of data collection. Several data analysis strategies were employed, including machine learning, temporal analysis, rule-based approaches, and statistical analysis. Summary: Our review indicates that the field of prescription drug abuse digital surveillance is still maturing. Though many studies captured large volumes of data, the majority did not analyze data to characterize user behavior, a critical step needed in order to better explain the underlying risk environment for prescription drug abuse. Future studies need to better translate method-based approaches into applied research, use data generated from social media platforms other than Twitter, and take advantage of emerging data analysis strategies, including deep learning and multimodal approaches. © 2017, Springer International Publishing AG.

关键词： Digital surveillance Infoveillance Non-medical use of prescription drugs Prescription drug abuse Social media Twitter

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A Critical Analysis on the Thin Crystalline Silicon PV Module of the Lightweight PV System

A Critical Analysis on the Thin Crystalline Silicon PV Modul...

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2017 IEEE 44th Photovoltaic Specialist Conference (PVSC)

作者： Meixi Chen Abhishek Iyer Cheng-Hao Shih Lado Kurdgelashvili Robert Opila Department of Material Science and Engineering University of Delaware Newark Delaware USA Department of Electrical and Computer Engineering University of Delaware Newark Delaware USA Department of Energy and Environmental Policy University of Delaware Newark Delaware USA

This work provides an analysis of the thin crystalline silicon PV module for a Lightweight PV (LPV) system. We first examine the advantages of the LPV system and then discuss the technical and economic challenges of the thin crystalline silicon PV module in assisting LPV system development for future market penetration. A critical analysis is conducted on the efficiency and yield challenge, and the system weight and costs reduction of thin crystalline silicon PV for the future development of the LPV system. It has shown that the key in speeding up thin silicon LPV market diffusion lies in developing cost-effective passivation and light trapping methods, as well as high-yield thin silicon fabrication technologies.

关键词： Silicon Passivation Fabrication Light trapping Photovoltaic systems

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COVID-19 causes record decline in global CO2 emissions

arXiv

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arXiv 2020年

作者： Liu, Zhu Ciais, Philippe Deng, Zhu Lei, Ruixue Davis, Steven J. Feng, Sha Zheng, Bo Cui, Duo Dou, Xinyu He, Pan Zhu, Biqing Lu, Chenxi Ke, Piyu Sun, Taochun Wang, Yuan Yue, Xu Wang, Yilong Lei, Yadong Zhou, Hao Cai, Zhaonan Wu, Yuhui Guo, Runtao Han, Tingxuan Xue, Jinjun Boucher, Olivier Boucher, Eulalie Chevallier, Frederic Wei, Yimin Zhong, Haiwang Kang, Chongqing Zhang, Ning Chen, Bin Xi, Fengming Marie, François Zhang, Qiang Guan, Dabo Gong, Peng Kammen, Daniel M. He, Kebin Schellnhuber, Hans Joachim Department of EarthSystem Science Tsinghua University Beijing100084 China Laboratoire des Sciences du Climate et de l'Environnement LSCE Orme de Merisiers Gif-sur-Yvette91191 France Department of Meteorology andAtmospheric Science The Pennsylvania State University University ParkPA16802 United States Department of Earth System Science University of California Irvine 3232 Croul Hall IrvineCA92697-3100 United States Division of Geological and Planetary Sciences California Institute of Technology PasadenaCA United States Jet Propulsion Laboratory California Institute of Technology PasadenaCA United States Nanjing210044 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China School of Environment Tsinghua University Beijing100084 China School of Mat hemat ical School T singhua University Beijing100084 China Department of Mathematical Sciences Tsinghua University Beijing100084 China Center of Hubei Cooperative Innovation for Emissions Trading System Wuhan China Faculty of Management and Economics Kunming University of Science and Technology 13 Kunming China Economic Research Centre of Nagoya University Furo-cho Chikusa-ku Nagoya Japan Institute Pierre-Simon Laplace Sorbonne Université CNRS Paris France Center for Energy and Environmental Policy Research Beijing Institute of Technology Beijing China Department of Electrical Engineering Tsinghua University Beijing100084 China Jinan University Guangzhou China Beijing Normal University Beijing China Institute of Applied Ecology Chinese Academy of Sciences Shenyang China Energy and Resources Group Goldman School of Pub

The considerable cessation of human activities during the COVID-19 pandemic has affected global energy use and CO2 emissions. Here we show the unprecedented decrease in global fossil CO2 emissions from January to April 2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-σ uncertainty) when compared with the period last year. In addition other emerging estimates of COVID impacts based on monthly energy supply1 or estimated parameters2, this study contributes to another step that constructed the near-real-time daily CO2 emission inventories based on activity from power generation (for 29 countries), industry (for 73 countries), road transportation (for 406 cities), aviation and maritime transportation and commercial and residential sectors emissions (for206 countries). The estimates distinguished the decline of CO2 due to COVID-19 from the daily, weekly and seasonal variations as well as the holiday events. The COVID-related decreases in CO2 emissions in road transportation (340.4 Mt CO2, -15.5%), power (292.5 Mt CO2, -6.4% compared to 2019), industry (136.2 Mt CO2, -4.4%), aviation (92.8 Mt CO2, -28.9%), residential (43.4 Mt CO2, - 2.7%), and international shipping (35.9Mt CO2, -15%). Regionally, decreases in China were the largest and earliest (234.5 Mt CO2,-6.9%), followed by Europe (EU-27 & UK) (138.3 Mt CO2, -12.0%) and the U.S. (162.4 Mt CO2, -9.5%). The declines of CO2 are consistent with regional nitrogen oxides concentrations observed by satellites and ground-based networks, but the calculated signal of emissions decreases (about 1Gt CO2) will have little impacts (less than 0.13ppm by April 30, 2020) on the overserved global CO2 concertation. However, with observed fast CO2 recovery in China and partial re-opening globally, our findings suggest the longer-term effects on CO2 emissions are unknown and should be carefully monitored using multiple measures. Copyright © 2020, The Authors. All rights reserved.

关键词： Carbon dioxide

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穿山甲可能不是新型冠状病毒的中间宿主

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中国预防兽医学报 2020年第12期42卷 1311-1311页

作者： LIU PING JIANG JING-ZHE WANXIU-FENG Guangdong Key Laboratory of Animal Conservation and Resource Utilization Guangdong Public Laboratory of Wild Animal Conservation and Utilization Guangdong Institute of Applied Biological Resources Guangdong Academy of Science Guangzhou Guangdong Province China. Key Laboratory of South China Sea Fishery Resources Exploitation & Utilization Ministry of Agriculture South China Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Guangzhou Guangdong Province China. Department of Molecular Microbiology and Immunology School of Medicine University of Missouri Columbia Missouri United States of America. Department of Electrical Engineering & Computer Science College of Engineering University of Missouri Columbia Missouri United States of America. MU Center for Research on Influenza Systems Biology (CRISB) University of Missouri Columbia Missouri United States of America. Bond Life Sciences Center University of Missouri Columbia Missouri United States of America. MU Institute for Data Science and Informatics University of Missouri Columbia Missouri United States of America. Guangdong Provincial Key Laboratory of Silviculture Protection and Utilization Guangdong Academy of Forestry Guangzhou Guangdong Province China. Institute of Animal Health Guangdong Academy of Agricultural Sciences Guangzhou Guangdong Province China. Guangdong Provincial Wildlife Rescue Center Guangzhou Guangdong Province China.

当前,新型冠状病毒肺炎(COVID-19)疫情仍在全球范围内肆虐,新冠肺炎的防控工作依然是重中之重。研究表明新型冠状病毒与中菊头蝠携带的Bat-CoV-RaTG13冠状病毒全基因组核苷酸一致性高达96%,推测该病毒可能起源于蝙蝠,再由中间野生动物... 详细信息

当前,新型冠状病毒肺炎(COVID-19)疫情仍在全球范围内肆虐,新冠肺炎的防控工作依然是重中之重。研究表明新型冠状病毒与中菊头蝠携带的Bat-CoV-RaTG13冠状病毒全基因组核苷酸一致性高达96%,推测该病毒可能起源于蝙蝠,再由中间野生动物宿主进一步传播,但目前中间宿主仍然未知。

关键词：中间宿主防控工作动物宿主穿山甲冠状病毒全球范围全基因组肺炎

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Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic (vol 11, 5172, 2020)

引用

NATURE COMMUNICATIONS 2020年第1期11卷 1-12页

作者： Liu, Zhu Ciais, Philippe Deng, Zhu Lei, Ruixue Davis, Steven J. Feng, Sha Zheng, Bo Cui, Duo Dou, Xinyu Zhu, Biqing Guo, Rui Ke, Piyu Sun, Taochun Lu, Chenxi He, Pan Wang, Yuan Yue, Xu Wang, Yilong Lei, Yadong Zhou, Hao Cai, Zhaonan Wu, Yuhui Guo, Runtao Han, Tingxuan Xue, Jinjun Boucher, Olivier Boucher, Eulalie Chevallier, Frederic Tanaka, Katsumasa Wei, Yiming Zhong, Haiwang Kang, Chongqing Zhang, Ning Chen, Bin Xi, Fengming Liu, Miaomiao Breon, Francois-Marie Lu, Yonglong Zhang, Qiang Guan, Dabo Gong, Peng Kammen, Daniel M. He, Kebin Schellnhuber, Hans Joachim Department of Earth System Science Tsinghua University Beijing China Laboratoire des Sciences du Climat et de l’Environnement LSCE CEA CNRS UVSQ Centre d’Etudes Orme de Merisiers Gif-sur-Yvette France Department of Meteorology and Atmospheric Science The Pennsylvania State University University Park USA Department of Earth System Science University of California Irvine Irvine USA Division of Geological and Planetary Sciences California Institute of Technology Pasadena USA Jet Propulsion Laboratory California Institute of Technology Pasadena USA Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology Nanjing China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China School of Environment Tsinghua University Beijing China School of Mathematical School Tsinghua University Beijing China Department of Mathematical Sciences Tsinghua University Beijing China Center of Hubei Cooperative Innovation for Emissions Trading System Wuhan China Faculty of Management and Economics Kunming University of Science and Technology Kunming China Economic Research Centre of Nagoya University Furo-cho Chikusa-ku Nagoya Japan Institut Pierre-Simon Laplace Sorbonne Université / CNRS Paris France Université Paris Dauphine Place du Maréchal de Lattre de Tassigny Paris France Center for Global Environmental Research National Institute for Environmental Studies Tsukuba Japan Center for Energy and Environmental Policy

A Correction to this paper has been published: https://***/10.1038/s41467-020-20254-5

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Byte by bite: Use of a mobile Bite Counter and weekly behavioral challenges to promote weight loss

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Smart Health 2017年 3-4卷 20-26页

作者： Turner-McGrievy, Gabrielle M. Boutté, Alycia Crimarco, Anthony Wilcox, Sara Hutto, Brent E. Hoover, Adam Muth, Eric R. Department of Health Promotion Education and Behavior Arnold School of Public Health University of South Carolina 915 Greene Street Room 529 Columbia 29208 SC United States Department of Exercise Science Director Prevention Research Center Arnold School of Public Health University of South Carolina Columbia SC United States Prevention Research Center Arnold School of Public Health University of South Carolina Columbia SC United States Holcombe Department of Electrical and Computer Engineering Clemson University Clemson SC United States Department of Psychology Clemson University Clemson SC United States

The goal of this study was to examine the usability and feasibility of the mobile Bite Counter (a watch-like device that detects when a user consumes food or beverage) and the impact of weekly behavioral challenges on diet and physical activity outcomes. Overweight (mean BMI 31.1±4.9 kg/m²) adults (n=12) were recruited to participate in a four-week study to test both the usability and feasibility of using the device as part of a behavioral weight loss intervention. Participants were instructed to self-monitor number of bites/day using the Bite Counter, attend weekly group sessions, and listen to weekly podcasts. Participants were given weekly challenges: use a daily bite limit goal (wk1), turn off Bite Counter when fruits/vegetables are consumed (wk2), self-monitor kilocalories vs. bites (wk3), and receive a 10 bites/day bonus for every 30 min of exercise (wk4). Participants lost a mean of −1.2±1.3 kg. Only the wk3 challenge produced significant differences in kcal change (wk3 1302±120 kcal/day vs. baseline 2042±302 kcal/d, P<0.05). Bite Counter use was significantly correlated with weight loss (r= −0.58, P<0.05). Future studies should examine the use of the Bite Counter and impact of behavioral challenges over a longer period of time in a controlled study. © 2017 Elsevier Inc.

关键词： Dietary self-monitoring Mobile health Mobile technology Personal health device Weight loss

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Resilient Wide-Area Damping Control for Interarea Oscillation Considering Communication Failure

Resilient Wide-Area Damping Control for Interarea Oscillatio...

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IEEE Power and Energy Society General Meeting

作者： Yu Shen Wei Yao Jinyu Wen Haibo He Cheng Luo State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science & Technology Department of Electrical Computer and Biomedical Engineering University of Rhode Island Northern Indiana Public Service Company (NIPSCO)

ISBN: (纸本)9781538622131;9781538622124

The wide-area damping controller, which uses the wide-area signal transmitted by communication network as the input signal, is an effective measure to suppress interarea oscillations. However, communication failure may occur when communication device fault, disaster or even attack occur. It would lead to the loss of wide-area signal and may disable the wide-area damping controller (WADC). To address this problem, this paper proposes a resilient WADC by employing both a wide-area signal and a local signal as the input signals to combine the observability and reliability of input signals. Moreover, a goal representation heuristic dynamic programming (GrHDP) algorithm is employed to design the resilient WADC of voltage source converter high voltage direct current (VSC-HVDC) transmission system for interarea oscillation. The proposed resilient GrHDP-WADC has the ability of online learning and strong adaptivity to handle the communication failure. Meanwhile, it does not need the exact model of the power system. Case study is undertaken based on a 10-machine 39-bus system with one VSC-HVDC transmission line. Simulation results show that the proposed resilient GrHDP-WADC can maintain a good control performance under communication failure.

关键词： Oscillators Power transmission lines Damping Power conversion Mathematical model Neural networks

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Conditional Survival Analysis of Patients With Locally Advanced Laryngeal Cancer: Construction of a Dynamic Risk Model and Clinical Nomogram

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SCIENTIFIC REPORTS 2017年第1期7卷 1-10页

作者： Sheu, Tommy Vock, David M. Mohamed, Abdallah S. R. Gross, Neil Mulcahy, Collin Zafereo, Mark Gunn, G. Brandon Garden, Adam S. Sevak, Parag Phan, Jack Lewin, Jan S. Frank, Steven J. Beadle, Beth M. Morrison, William H. Lai, Stephen Y. Hutcheson, Katherine Marai, G. Elisabeta Canahuate, Guadalupe M. Kies, Merrill El-Naggar, Adel Weber, Randal S. Rosenthal, David I. Fuller, Clifton D. Department of Radiation Oncology The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Clinical Oncology and Nuclear Medicine University of Alexandria Alexandria Egypt Division of Biostatistics University of Minnesota School of Public Health Minneapolis Minnesota USA Department of Head and Neck Surgery The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Radiation Oncology Henry Ford Hospital Detroit MI USA Department of Computer Science University of Illinois at Chicago Chicago Illinois USA Department of Electrical & Computer Engineering University of Iowa Iowa City IA USA Department of Medical Oncology The University of Texas MD Anderson Cancer Center Houston Texas USA Department of Pathology The University of Texas MD Anderson Cancer Center Houston Texas USA

Conditional survival (CS), the survival beyond a pre-defined time interval, can identify periods of higher mortality risk for patients with locally advanced laryngeal cancer who face treatment-related toxicity and comorbidities related to alcohol and smoking in the survivorship setting. Using Weibull regression modeling, we analyzed retrospectively abstracted data from 638 records of patients who received radiation to identify prognostic factors for overall survival (OS) and recurrence free survival (RFS) for the first 3 years of survival and for OS conditional upon 3 years of survival. The CS was iteratively calculated, stratifying on variables that were statistically significant on multivariate regression. Predictive nomograms were generated. The median total follow up time was 175 months. The 3-and 6-year actuarial overall survival (OS) was 68% (95% confidence interval [CI] 65-72%) and 49% (CI 45-53%). The 3-year conditional overall survival (COS) at 3 years was 72% (CI 65-74%). Black patients had worse COS over time. Nodal disease was significantly associated with recurrence, but after 3 years, the 3-year conditional RFS converged for all nodal groups. In conclusion, the CS analysis in this patient cohort identified subgroups and time intervals that may represent opportunities for intervention.

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