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196 citation(s) found for "Ibáñez, Mariam".

Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017
James, Spencer L , Castle, Chris D, Dingels, Zachary V, Fox, Jack T, Hamilton, Erin B, Sylte, Dillon O , Henry, Nathaniel J , LeGrand, Kate E , Abdelalim, Ahmed , Abdulkader, Rizwan Suliankatchi , Abedi, Aidin , Eshete, Akine , Abushouk, Abdelrahman Ibrahim , Adebayo, Oladimeji , Agudelo‐Botero, Marcela , Ahmad, Tauseef , Aichour, Miloud Taki Eddine, Alahdab, Fares , Alamene, Genet Melak, Alanezi, Fahad , Alebel, Animut , Alema, Niguse Meles , Ali, Beriwan Abdulqadir, Alikhani, Mahtab , Alipour, Vahid, Almasri, Nihad A. , Altirkawi, Khalid A , Amer, Yasser Sami , Amini, Saeed, Amit, Arianna Maever L. , Andrei, Cătălina Liliana , Ansari-Moghaddam, Alireza, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw , Arabloo, Jalal , Arefi, Zohreh , Aremu, Olatunde , Ariani, Filippo , Arora, Amit , Asghari, Babak , Awoke, Nefsu , Quintanilla, Beatriz Paulina Ayala , Ayano, Getinet , Ayanore, Martin Amogre , Azari, Samad , Azarian, Ghasem , Badawi, Alaa, Badiye, Ashish , Bagli, Eleni , Baig, Atif Amin , Bairwa, Mohan , Bakhtiari, Ahad , Banach, Maciej , Banerjee, Srikanta , Banik, Palash Chandra , Banstola, Amrit , Barker‐Collo, Suzanne , Bärnighausen, Till , Barrero, Lope H. , Barzegar, Akbar , Baye, Bayisa Abdissa , Bekuma, Tariku Tesfaye , Belete, Habte , Bennett, Derrick , Berhe, Kidanemaryam , Bhardwaj, Pankaj , Bhat, Anusha Ganapati , Bhattacharyya, Krittika , Bijani, Ali , Sayeed, Muhammad Shahdaat Bin , Borzì, Antonio Maria , Bražinová, Alexandra, Брико, Н. И. , Budhathoki, Shyam Sundar , Car, Josip , Cárdenas, Rosario , Carvalho, Félix , Castaldelli-Maia, João Maurício , Castañeda-Orjuela, Carlos A , Castelpietra, Giulio , Catalá-López, Ferrán , Cerin, Ester , Chandan, Joht Singh , Chanie, Wagaye Fentahun, Chattu, Soosanna Kumary , Chattu, Vijay Kumar , Chaudhary, Neha , Cho, Daniel , Chowdhury, Mohiuddin Ahsanul Kabir , Chu, Dinh‐Toi , Colquhoun, Samantha , Costa, Vera Marisa , Damiani, Giovanni , Dávila-Cervantes, Claudio Alberto , Demoz, Gebre Teklemariam , Demsie, Desalegn Getnet , Derakhshani, Afshin , Deribe, Kebede , Desai, Rupak , Nasab, Mostafa Dianati, Silva, Diana Dias da , Forooshani, Zahra Sadat Dibaji, Doyle, Kerrie , Driscoll, Tim , Dubljanin, Eleonora , Adema, Bereket Duko , Eagan, Arielle Wilder , Eftekhari, Aziz , Ehsani‐Chimeh, Elham , Elemineh, Demelash Abewa , El-Jaafary, Shaimaa I , El‐Khatib, Ziad , Ellingsen, Christian Lycke , Emamian, Mohammad Hassan , Endalew, Daniel Adane , Faris, Pawan , Faro, André , Farzadfar, Farshad , Fatahi, Yousef , Fekadu, Wubalem , Ferede, Tomas Y, Fereshtehnejad, Seyed‐Mohammad , Fernandes, Eduarda , Ferrara, Pietro , Feyissa, Garumma Tolu , Fischer, Florian , Foláyan, Morẹ́nikẹ́ Oluwátóyìn , Francis, Joel M , Fukumoto, Takeshi , Geberemariyam, Biniyam Sahiledengle, Gebre, Abadi Kahsu , Gebremedhin, Ketema Bizuwork , Gebremeskel, Gebreamlak Gebremedhn , Gebremichael, Berhe , Gedefaw, Getnet , Geta, Birhanu, Ghafourifard, Mansour , Ghamari, Farhad , Ghashghaee, Ahmad , Gholamian, Asadollah , Gill, Tiffany K, Goulart, Alessandra C. , Grada, Ayman , Gubari, Mohammed Ibrahim Mohialdeen , Guo, Yuming , Haagsma, Juanita A. , Hafezi‐Nejad, Nima , Hall, Brian J. , Hamadeh, Randah R , Hasan, Md. Mehedi , Hassen, Hamid Yimam , Havmoeller, Rasmus, Heydarpour, Fatemeh , Hı́jar, Martha , Ho, Hung Chak , Hoang, Chi Linh , Hole, Michael K., Hossain, Naznin , Hosseinzadeh, Mehdi , Hostiuc, Sorin , Ibitoye, Segun Emmanuel , Ilić, Irena , Ilić, Milena , Inbaraj, Leeberk Raja , Indriasih, Endang , Irvani, Seyed Sina Naghibi , Islam, Sheikh Mohammed Shariful , Islam, M. Mofizul , Ivers, Rebecca , Jacobsen, Kathryn H. , Jahani, Mohammad Ali, Jahanmehr, Nader , Jakovljević, Mihajlo , Jayaraman, Sudha , Jha, Ravi Prakash , John-Akinola, Yetunde O. , Joseph, Nitin , Joukar, Farahnaz, Jozwiak, Jacek Jerzy , Jürisson, Mikk , Kadel, Rajendra , Kahsay, Amaha , Kalankesh, Leila R , Kalhor, Rohollah , Kamil, Teshome Abegaz, Kapoor, Neeti , Karami, Manoochehr , Kasaeian, Amir , Kassaye, Hagazi Gebremedhin, Kavetskyy, Taras , Kebede, Hafte Kahsay , Keiyoro, Peter Njenga, Kelbore, Abraham Getachew , Kelkay, Bayew, Khader, Yousef , Khafaie, Morteza Abdullatif , Khalid, Nauman , Khalil, Ibrahim A, Khalilov, Rovshan , Khan, Ejaz Ahmad , Khan, Maseer , Khanna, Tripti, Shadmani, Fatemeh Khosravi , Khundkar, Roba , Kiirithio, Daniel N, Kim, Yun Jin , Kısa, Adnan , Kısa, Sezer , Komaki, Hamidreza , Kondlahalli, Shivakumar K M, Korshunov, Vladimir Andreevich , Kraemer, Moritz U. G. , Krishan, Kewal , Biçer, Burcu Küçük , Kugbey, Nuworza , Kumar, Vivek , Kumar, G Anil , Kumar, Manasi , Kumaresh, Girikumar, Kurmi, Om , Kuti, Oluwatosin, Lami, Faris , Lamichhane, Prabhat , Lang, Justin J. , Lasrado, Savita , Leasher, Janet L , Lee, Shaun Wen Huey , Lenjebo, Tsegaye Lolaso , Li, Shanshan , Linn, Shai , Liu, Xuefeng , Lunevičius, Raimundas , Lyons, Ronan A , Madadin, Mohammed , Razek, Muhammed Magdy Abd El, Mahotra, Narayan Bahadur , Majdán, Marek , Malagón-Rojas, Jeadran , Maled, Venkatesh , Manafi, Navid , Manafi, Amir , Manda, Ana-Laura, Mansour-Ghanaei, Fariborz, Mansouri, Borhan , March, Lyn , Mason‐Jones, Amanda J. , Masoumi, Seyedeh Zahra , Massenburg, Benjamin B. , Maulik, Pallab K , Meles, Gebrekiros Gebremichael , Melketsedik, Zeleke Aschalew , Memiah, Peter , Mendoza, Walter, Menezes, Ritesh G. , Mengesha, Melkamu Merid , Meretoja, Tuomo J , Meretoja, Atte , Merie, Hayimro Edemealem , Miazgowski, Bartosz , Miazgowski, Tomasz , Miller, Ted R. , Mini, GK , Мirrakhimov, Erkin М , Mirzaei-Alavijeh, Mehdi , Mithra, Prasanna , Moazen, Babak , Moghadaszadeh, Masoud, Mohammad, Yousef , Mohammad, Karzan Abdulmuhsin , Mezerji, Naser Mohammad Gholi, Mohammadian-Hafshejani, Abdollah , Mohammadoo-Khorasani, Milad, Mohammed, Shafiu , Mohammed, Jemal , Mohebi, Farnam , Molokhia, Mariam , Monasta, Lorenzo , Moodley, Yoshan , Moosazadeh, Mahmood , Moradi, Masoud , Moradi, Ghobad , Moradpour, Farhad , Morawska, Lídia , Velásquez, Ilais Moreno , Mossie, Tilahun Belete , Murthy, Srinivas , Musa, Kamarul Imran , Mustafa, Ghulam , Nabhan, Ashraf , Nagarajan, Ahamarshan Jayaraman , Naik, Gurudatta , Naimzada, Mukhammad David , Nangia, Vinay, Nascimento, Bruno Ramos , Naserbakht, Morteza , Ndwandwe, Duduzile , Negoi, Ionuţ , Ngunjiri, Josephine W, Nguyen, Cuong Tat , Nikbakhsh, Rajan , Ningrum, Dina Nur Anggraini , Nnaji, Chukwudi A , Nyasulu, Peter S. , Ogbo, Felix Akpojene , Oghenetega, Onome Bright , Okunga, Emmanuel , Olagunju, Andrew T , Olagunju, Tinuke O , Bali, Ahmed Omar , Onwujekwe, Obinna , Asante, Kwaku Oppong , Orpana, Heather , Otstavnov, Nikita , Otstavnov, Stanislav S , Mahesh, P A , Padubidri, Jagadish Rao , Pakhalé, Smita , Pakshir, Keyvan , Panda‐Jonas, Songhomitra, Park, Eun‐Kee , Patel, Sangram Kishor , Pathak, Ashish , Pati, Sanghamitra , Paulos, Kebreab , Pepito, Veincent Christian Filipino , Pham, Hai Quang , Pinheiro, Marina , Полибин, Р. В. , Polinder, Suzanne, Poustchi, Hossein, Prakash, Swayam , Pribadi, Dimas Ria Angga , Puri, Parul , Syed, Zahiruddin Quazi, Rabiee, Navid , Radfar, Amir , Rafay, Anwar, Rafiee, Ata , Rafiei, Alireza , Rahim, Fakher , Rahimi, Siavash , Rahimi‐Movaghar, Vafa , Rahman, Muhammad Aziz , Rajabpour-Sanati, Ali, Rajati, Fatemeh , Rakovac, Ivo , Ranganathan, Kavitha , Rao, Sowmya J, Rashedi, Vahid , Rastogi, Prateek , Rathi, Priya , Rawal, Lal , Rawassizadeh, Reza , Renjith, Vishnu , Renzaho, André M. N. , Resnikoff, Serge , Rezapour, Aziz, Rickard, Jennifer , Ríos-González, Carlos Miguel , Sabde, Yogesh , Saddik, Basema , Safari, Saeed , Safarpour, Hamid , Safdarian, Mahdi , Sajadi, S. Mohammad , Salamati, Payman, Salehi, Farkhonde , Zahabi, Saleh Salehi , Salem, Marwa Rashad , Salem, Hosni , Salman, Omar , Salz, Inbal, Samy, Abdallah M , Sanabria, Juan , Sànchez-Riera, Lídia , Santric-Milicevic, Milena M , Sarveazad, Arash , Sathian, Brijesh , Sawhney, Monika, Sawyer, Susan M. , Saxena, Sonia , Schwebel, David C. , Seedat, Soraya , Senthilkumaran, Subramanian , Seyedmousavi, Seyedmojtaba , Sha, Feng , Shaahmadi, Faramarz , Shaikh, Masood Ali , Shams-Beyranvand, Mehran , Shamsizadeh, Morteza , Sharif-Alhoseini, Mahdi , Sharifi, Hamid , Sheikh, Aziz , Shigematsu, Mika, Shin, Jae Il , Shiri, Rahman , Sigfúsdóttir, Inga Dóra, Singh, Pankaj Kumar , Sinha, Dhirendra Narain , Smarandache, Catalin-Gabriel , Soleymani, Bija, Soriano, Joan B. , Soyiri, Ireneous N , Stein, Dan J. , Sufiyan, Mu’awiyyah Babale , Suleria, Hafiz Ansar Rasul , Sykes, Bryan L. , Tabarés‐Seisdedos, Rafael , Tabb, Karen M. , Wogayehu, Biruk , Tamiru, Animut Tagele , Tarigan, Ingan Ukur , Tefera, Yibekal Manaye , Tekle, Merhawi Gebremedhin , Tekulu, Gebretsadkan Hintsa , Kassie, Ayenew , Bedaso, Asres , Tlaye, Kenean Getaneh , Tohidinik, Hamid Reza , Topór-Mądry, Roman , Tripathy, Jaya Prasad , Tsai, Alexander C. , Car, Lorainne Tudor , Ullah, Saif , Ullah, Irfan , Umar, Maida, Unnikrishnan, Bhaskaran , Upadhyay, Era , Valdéz, Pascual , Violante, Francesco Saverio , Waheed, Yasir , Teklay, Girmay , Werdecker, Andrea , Wiangkham, Taweewat , Wolde, Haileab Fekadu , Woldeyes, Dawit Habte , Yadav, Rajaram , Yadollahpour, Ali , Yano, Yuichiro , Yaya, Sanni , Yazdi‐Feyzabadi, Vahid , Yisma, Engida , Yoon, Seok‐Jun , Youm, Yoosik , Younis, Mustafa Z , Yousefi, Zabihollah , Yu, Yong , Yusefzadeh, Hasan, Moghadam, Telma Zahirian , Zaman, Sojib Bin , Zamanian, Maryam , Zhang, Zhi-Jiang , Zhang, Yunquan , Zodpey, Sanjay , Dandona, Lalit , Dandona, Rakhi , Hay, Simon I , Mokdad, Ali H. , Reiner, Robert C. , Sartorius, Benn , Vos, Theo , Topór‐Mądry, Roman , Zahiruddin, Quazi Syed , Dianatinasab, Mostafa , Sanati, Ali Rajabpour , Baig, Atif Amin , Kumar, Vivek , Stein, Dan J , Castaldelli-Maia, João M , Farzadfar, Farshad , Shin, Jae I L , Islam, Sheikh Mohammed Shariful , Rahman, Muhammad Aziz , Belete, T , Liu, Zichen, Roberts, Nicholas L S , Abdoli, Amir , Abdollahpour, Ibrahim , Ahmed, Rushdiá , Ahmed, Muktar Beshir , Alghnam, Suliman Abdullah , Al‐Hajj, Samar , Ali, Saqib , Alinia, Cyrus , Aljunid, Syed Mohamed , Almasi‐Hashiani, Amir , Amini, Saeed, Antonio, Carl Abelardo T. , Arab-Zozani, Morteza , Asaad, Malke , Balachandran, Arun , Bayati, Mohsen , Bedi, Neeraj , Behzadifar, Masoud , Benjet, Corina L. , Benseñor, Isabela M. , Bibi, Sadia , Borges, Guilherme , Boufous, Soufiane , Chatziralli, Irini , Constantin, María Magdalena , Daryani, Ahmad , Demeke, Feleke Mekonnen , Demis, Asmamaw , Forooshani, Zahra Sadat Dibaji, Duko, Bereket , Zaki, Maysaa El Sayed , Adane, Daniel, Eskandarieh, Sharareh , Yeheyis, Tomas Y. , Filip, Irina , Foroutan, Masoud , Franklin, Richard C. , Gill, Tiffany K. , Grivna, Michal , Guimarães, Rafael Alves , Gupta, Gaurav Kumar , Haghparast‐Bidgoli, Hassan , Hamidi, Samer , Haro, Josep María , Hasanzadeh, Amir , Hassanipour, Soheil , Hassankhani, Hadi , Hayat, Khezar , Hendrie, Delia V. , Holla, Ramesh , Hu, Guoqing , Ilesanmi, Olayinka Stephen , Jalilian, Farzad , Jayatilleke, Achala Upendra , Jonas, Jost B , Jungari, Suresh Banayya , Kabir, Ali , Kanchan, Tanuj , Rade, Bayew Kelkay , Khalil, Ibrahim A, Khammarnia, Mohammad , Khazaie, Habibolah , Kim, Young‐Eun , Kim, Daniel , Shivakumar, KM , Koyanagi, Ai , Kumar, Nithin , Vecchia, Carlo La , Lansingh, Van Charles , Laryea, Dennis Odai , Latifi, Arman , Lauriola, Paolo , Levi, Miriam , Lopez, Alan D , Lotufo, Paulo A. , Majeed, Azeem , Malekzadeh, Reza , Malta, Déborah Carvalho , Manjunatha, Narayana , Mansour‐Ghanaei, Fariborz , Mansournia, Mohammad Alì , Maravilla, Joemer Calderon , Melese, Addisu Dagnaw , Aschalew, Zeleke , Mengesha, Meresa Berwo , Meštrović, Tomislav , Mirică, Andreea , Mohamadi, Efat , Darwesh, Aso Mohammad , Mohammadpourhodki, Reza , Moradi‐Lakeh, Maziar , Morisaki, Naho , Morrison, Shane D. , Muluneh, Atalay Goshu , Najafi, Farid , Nayak, Vinod C , Nguyen, Huong Lan Thi , Oh, In‐Hwan , Ota, Erika , Patton, George , Peden, Amy E. , Pereira, Jeevan , Phillips, Michael , Rabiee, Mohammad , Rawaf, Salman , Ribeiro, Ana Isabel , Ronfani, Luca , Roshandel, Gholamreza , Saad, Anas M. , Sabour, Siamak , Safari‐Faramani, Roya , Salamati, Payman, Sarker, Abdur Razzaque , Sayyah, Mehdi , Sepanlou, Sadaf Ghajarieh , Shahabi, Saeed , Siabani, Soraya , Singh, Jasvinder A. , Smith, Emma U.R. , Soheili, Amin , Soltanian, Ali Reza , Sorrie, Muluken Bekele , Stokes, Mark Andrew , Tadesse, Degena Bahrey , Tehrani‐Banihashemi, Arash , Tesfay, Berhe Etsay , Thapar, Rekha , Tran, Bach Xuan , Tran, Khanh Bao , Uthman, Olalekan Abdulrahman , Vasankari, Tommi Juhani , Venketasubramanian, Narayanaswamy , Vlassov, Vasily , Wondafrash, Dawit Zewdu , Wondmeneh, Temesgen Gebeyehu , Wondmieneh, Adam Belay , Wu, Aimin , YIP, PAUL S. F. , Yonemoto, Naohiro , Yu, Chuanhua , Zaidi, Zoubida , Zamani, Mohammad , Zandian, Hamed , Zarei, Ahmad , Zare, Fatemeh, Degenhardt, Louisa J , Dharmaratne, Samath Dhamminda , Olagunju, Andrew T , Baig, Atif Amin , Desai, Rupak , Alahdab, Fares , Rahim, Fakher

Injury Prevention | April 24, 2020 | Volume: 26 | Issue: Suppl 2 | Pages: i96-i114

10.1136/injuryprev-2019-043494 | PMID 32332142 Get It

Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.
Clinicopathologic predictors of renal outcomes in light chain cast nephropathy: a multicenter retrospective study
Royal, Virginie , Leung, Nelson , Troyanov, Stéphan , Nasr, Samih H. , Écotière, Laure, LeBlanc, Richard , Adam, Benjamin , Angioi, Andrea , Alexander, Mariam P., Asunis, Anna Maria, Barreca, Antonella , Cohen, Camille , Drosou, Maria Eleni , Fatima, Huma , Gougeon, F. , Goujon, Jean‐Michel, Herrera, Guillermo A. , Knebelmann, Bertrand , Lepori, Nicola , Manso, Rita , Motwani, Shveta S. , Pani, Antonello , Rabant, Marion , Rennke, Helmut G. , Rocatello, Dario, Rosenblum, Frida , Sanders, Paul W. , Santos, Afonso , Soto, Karina , Sis, B. , Touchard, Guy, Venner, Christopher P. , Bridoux, Frank , Drosou, Maria E, Leung, Nelson , Bianco, Paola, Fenoglio, Roberta , Gougeon, François, Maletta, Francesca

Blood | March 11, 2020 | Volume: 135 | Issue: 21 | Pages: 1833-1846

10.1182/blood.2019003807 | PMID 32160635 Get It

Abstract Light chain cast nephropathy (LCCN) in multiple myeloma often leads to severe and poorly reversible acute kidney injury. Severe renal impairment influences the allocation of chemotherapy and its tolerability; it also affects patient survival. Whether renal biopsy findings add to the clinical assessment in predicting renal and patient outcomes in LCCN is uncertain. We retrospectively reviewed clinical presentation, chemotherapy regimens, hematologic response, and renal and patient outcomes in 178 patients with biopsy-proven LCCN from 10 centers in Europe and North America. A detailed pathology review, including assessment of the extent of cast formation, was performed to study correlations with initial presentation and outcomes. Patients presented with a mean estimated glomerular filtration rate (eGFR) of 13 ± 11 mL/min/1.73 m2, and 82% had stage 3 acute kidney injury. The mean number of casts was 3.2/mm2 in the cortex. Tubulointerstitial lesions were frequent: acute tubular injury (94%), tubulitis (82%), tubular rupture (62%), giant cell reaction (60%), and cortical and medullary inflammation (95% and 75%, respectively). Medullary inflammation, giant cell reaction, and the extent of cast formation correlated with eGFR value at LCCN diagnosis. During a median follow-up of 22 months, mean eGFR increased to 43 ± 30 mL/min/1.73 m2. Age, β2-microglobulin, best hematologic response, number of cortical casts per square millimeter, and degree of interstitial fibrosis/tubular atrophy (IFTA) were independently associated with a higher eGFR during follow-up. This eGFR value correlated with overall survival, independently of the hematologic response. This study shows that extent of cast formation and IFTA in LCCN predicts the quality of renal response, which, in turn, is associated with overall survival.
Treatment of fibrillary glomerulonephritis with rituximab: a 12-month pilot study
Erickson, Stephen B., Zand, Ladan , Nasr, Samih H. , Alexander, Mariam P., Drosou, Maria Eleni , Leung, Nelson , Fervenza, Fernando C.

Nephrology Dialysis Transplantation | March 11, 2020 | Volume: 36 | Issue: 1 | Pages: 104-110

10.1093/ndt/gfaa065 | PMID 32617582 Get It

Abstract Background Fibrillary glomerulonephritis (FGN) is a rare type of glomerulonephritis with poor prognosis, with no known effective therapies available for treatment. The objective of the study was to evaluate the efficacy and safety of rituximab in treatment of patients with FGN and to investigate the effect of rituximab on DNAJB9 levels. Methods This was a pilot prospective clinical trial in which patients with idiopathic FGN were treated with two courses of rituximab (1 g each) 2 weeks apart at the beginning and then again at 6 months. Primary outcome was defined as preservation of kidney function at 12 months with stable or increased creatinine clearance. Secondary outcome was defined as achieving complete remission (CR) defined as proteinuria <300 mg/24 h or partial remission (PR) with proteinuria <3 g/24 h and at least 50% reduction in the proteinuria. DNAJB9 levels were also measured in the serum at baseline, 6 and 12 months. Results The creatinine clearance did not change significantly during this time, from 47.7 mL/min/1.73 m2 at baseline to 43.7 mL/min/1.73 m2 during follow-up (P = 0.15). Proteinuria declined from 4.43 (1.6–5.53) g/24 h at baseline to 1.9 (0.46–5.26) g/24 h at 12 months but did not reach significance (P = 0.06). None of the patients reached CR, and 3 of the 11 achieved PR. There was no change in the DNAJB9 levels following treatment with rituximab. The most common adverse event was nasal congestion, fatigue and muscle cramps. Conclusions Treatment of patients with two courses of rituximab over a span of 6 months was associated with stabilization of renal function but did not result in a significant change in proteinuria and with no change in the DNAJB9 levels.
Development and Validation of a Next-Generation Sequencing Panel for Syndromic and Nonsyndromic Hearing Loss
Butz, Malinda L., McDonald, Amber , Lundquist, Patrick A. , Meyer, Mélanie, Harrington, Sean C., Kester, Sarah, Stein, Mariam I. , Mistry, Nipun A., Zuckerman, Eric Zimmerman , Schimmenti, Lisa A. , Hasadsri, Linda , Boczek, Nicole J. , Butz, Malinda, Harrington, Sean, Zimmerman Zuckerman, Eric, Schimmenti, Lisa, Schimmenti, Lisa A , Niu, Zhiyv

The Journal of Applied Laboratory Medicine | February 3, 2020 | Volume: 5 | Issue: 3 | Pages: 467-479

10.1093/jalm/jfaa021 | PMID 32445360 Get It

Abstract Background Deafness and hearing loss are common conditions that can be seen independently or as part of a syndrome and are often mediated by genetic causes. We sought to develop and validate a hereditary hearing loss panel (HHLP) to detect single nucleotide variants (SNVs), insertions and deletions (indels), and copy number variants (CNVs) in 166 genes related to nonsyndromic and syndromic hearing loss. Methods We developed a custom-capture next-generation sequencing (NGS) reagent to detect all coding regions, ±10 flanking bp, for the 166 genes related to nonsyndromic and syndromic hearing loss. Our validation consisted of testing 52 samples to establish accuracy, reproducibility, and analytical sensitivity. In addition to NGS, supplementary methods, including multiplex ligation-dependent probe amplification, long-range PCR, and Sanger sequencing, were used to ensure coverage of regions that had high complexity or homology. Results We observed 100% positive and negative percentage agreement for detection of SNVs (n = 362), small indels (1–22 bp, n = 25), and CNVs (gains, n = 8; losses, n = 17). Finally, we showed that this assay was able to detect variants with a variant allele frequency ≥20% for SNVs and indels and ≥30% to 35% for CNVs. Conclusions We validated an HHLP that detects SNVs, indels, and CNVs in 166 genes related to syndromic and nonsyndromic hearing loss. The results of this assay can be utilized to confirm a diagnosis of hearing loss and related syndromic disorders associated with known causal genes.
Kidney Structural Features from Living Donors Predict Graft Failure in the Recipient
Issa, Naim , Lopez, Camden , Đenić, Aleksandar , Taler, Sandra J. , Larson, Joseph J. , Kremers, Walter K. , Ricaurte, Luisa , Merzkani, Massini , Alexander, Mariam P., Chakkera, Harini A. , Stegall, Mark D. , Augustine, Joshua J. , Alexander, Mariam Priya, Rule, Andrew D , Stegall, Mark D , Denic, Aleksandar , Lopez, Camden L , Chakkera, Harini A , Kremers, Walter K , Augustine, Joshua , Rule, Andrew D.

Journal of the American Society of Nephrology | January 23, 2020 | Volume: 31 | Issue: 2 | Pages: 415-423

10.1681/asn.2019090964 | PMID 31974271 Get It

Significance Statement The quality of a kidney obtained from a living donor is often inferred from the donor’s age, risk factors, and kidney function. Little is known about the influence of a donated kidney’s structural features on the risk of death-censored graft failure in the recipient. In an analysis of 2293 kidney donor-recipient pairs, the authors identified subclinical nephrosclerosis, larger nephron size (but not nephron number), and smaller medullary volume as structural predictors of death-censored graft failure that were independent of both donor and recipient clinical characteristics. These findings provide important insights into the factors that define the “intrinsic quality” of the living kidney donor graft at the time of donation, and support use of intraoperative biopsies to identify donor kidneys that are at higher risk for failure. Background Nephrosclerosis, nephron size, and nephron number vary among kidneys transplanted from living donors. However, whether these structural features predict kidney transplant recipient outcomes is unclear. Methods Our study used computed tomography (CT) and implantation biopsy to investigate donated kidney features as predictors of death-censored graft failure at three transplant centers participating in the Aging Kidney Anatomy study. We used global glomerulosclerosis, interstitial fibrosis/tubular atrophy, artery luminal stenosis, and arteriolar hyalinosis to measure nephrosclerosis; mean glomerular volume, cortex volume per glomerulus, and mean cross-sectional tubular area to measure nephron size; and calculations from CT cortical volume and glomerular density on biopsy to assess nephron number. We also determined the death-censored risk of graft failure with each structural feature after adjusting for the predictive clinical characteristics of donor and recipient. Results The analysis involved 2293 donor-recipient pairs. Mean recipient follow-up was 6.3 years, during which 287 death-censored graft failures and 424 deaths occurred. Factors that predicted death-censored graft failure independent of both donor and recipient clinical characteristics included interstitial fibrosis/tubular atrophy, larger cortical nephron size (but not nephron number), and smaller medullary volume. In a subset with 12 biopsy section slides, arteriolar hyalinosis also predicted death-censored graft failure. Conclusions Subclinical nephrosclerosis, larger cortical nephron size, and smaller medullary volume in healthy donors modestly predict death-censored graft failure in the recipient, independent of donor or recipient clinical characteristics. These findings provide insights into a graft’s “intrinsic quality” at the time of donation, and further support the use of intraoperative biopsies to identify kidney grafts that are at higher risk for failure.
Burden of injury along the development spectrum: associations between the Socio-demographic Index and disability-adjusted life year estimates from the Global Burden of Disease Study 2017
Haagsma, Juanita A. , James, Spencer L , Castle, Chris D, Dingels, Zachary V, Fox, Jack T, Hamilton, Erin B, Lucchesi, Lydia R , Sylte, Dillon O , Adebayo, Oladimeji , Ahmadi, Alireza , Aichour, Miloud Taki Eddine, Alahdab, Fares , Al‐Raddadi, Rajaa , Alsharif, Ubai , Altirkawi, Khalid A , Anjomshoa, Mina, Appiah, Seth Christopher Yaw , Aremu, Olatunde , Arora, Amit , Assadi, Reza , Awasthi, Ashish , Quintanilla, Beatriz Paulina Ayala , Balalla, Shivanthi , Banstola, Amrit , Barker‐Collo, Suzanne , Bärnighausen, Till , Behzadifar, Meysam, Bennett, Derrick , Bhaumik, Soumyadeep , Bhutta, Zulfiqar A , Bijani, Ali , Borges, Guilherme , Borschmann, Rohan , Bose, Dipan, Bražinová, Alexandra, Campuzano, Julio César , Cárdenas, Rosario , Carvalho, Félix , Castañeda-Orjuela, Carlos A , Catalá-López, Ferrán , Choi, Jee-Young Jasmine , Christopher, Devasahayam Jesudas , Crowe, Christopher S. , Dalal, Koustuv , Leo, Diego De, Neve, Jan‐Walter De , Deribe, Kebede , Dessie, Getenet , deVeber, Gabrielle , Dharmaratne, Samath Dhamminda , Doan, Linh Phuong , Driscoll, Tim , El‐Khatib, Ziad , Ellingsen, Christian Lycke , Endries, Aman Yesuf , Faro, André , Fereshtehnejad, Seyed‐Mohammad , Fernandes, Eduarda , Fischer, Florian , Franklin, Richard C. , Fukumoto, Takeshi , Gezae, Kebede Embaye , Gill, Tiffany K, Goulart, Alessandra C. , Grada, Ayman , Guo, Yuming , Haghparast‐Bidgoli, Hassan , Haj‐Mirzaian, Arvin , Haj‐Mirzaian, Arya , Hamadeh, Randah R , Hassen, Hamid Yimam , Havmoeller, Rasmus, Henok, Andualem , Hı́jar, Martha, Hole, Michael K., Rad, Enayatollah Homaie , Hossain, Naznin , Hostiuc, Sorin , Igumbor, Ehimario , Irvani, Seyed Sina Naghibi , Islam, Sheikh Mohammed Shariful , Ivers, Rebecca , Jacobsen, Kathryn H. , Jahanmehr, Nader , Jakovljević, Mihajlo , Jha, Ravi Prakash , Shushtari, Zahra Jorjoran , Jozwiak, Jacek Jerzy , Jürisson, Mikk , Kalani, Rizwan, Kasaeian, Amir , Kelbore, Abraham Getachew , Kengne, André Pascal , Khader, Yousef , Khafaie, Morteza Abdullatif , Khalid, Nauman , Khan, Ejaz Ahmad , Kiadaliri, Ali , Kim, Yun Jin , Kısa, Adnan , Defo, Barthélémy Kuate , Biçer, Burcu Küçük , Kumar, Manasi , Lalloo, Ratilal , Lam, Hilton Y. , Lami, Faris , Leasher, Janet L , Li, Shanshan , Linn, Shai , Lunevičius, Raimundas , Machado, Flávia Ribeiro , Razek, Hassan Magdy Abd El , Razek, Muhammed Magdy Abd El, Mahotra, Narayan Bahadur , Majdán, Marek , Majeed, Azeem , Malekzadeh, Reza, Malik, Manzoor Ahmad , Manda, Ana-Laura, Massenburg, Benjamin B. , Maulik, Pallab K , Meheretu, Hailemariam Abiy Alemu , Mehndiratta, Man Mohan, Mendoza, Walter, Mengesha, Melkamu Merid , Meretoja, Tuomo J , Meretoja, Atte , Miazgowski, Tomasz , Miller, Ted R. , Mini, GK , Мirrakhimov, Erkin М , Moazen, Babak , Mezerji, Naser Mohammad Gholi, Mohammadibakhsh, Roghayeh , Mohammed, Shafiu , Molokhia, Mariam , Monasta, Lorenzo , Mondello, Stefania , Montero-Zamora, Pablo A. , Moodley, Yoshan , Moosazadeh, Mahmood , Moradi, Ghobad , Morawska, Lídia , Velásquez, Ilais Moreno , Moschos, Marilita M. , Mousavi, Seyyed Meysam , Murthy, Srinivas , Musa, Kamarul Imran , Naik, Gurudatta , Nangia, Vinay, Nascimento, Bruno Ramos , Ndwandwe, Duduzile , Negoi, Ionuţ , Nguyen, Son Hoang , Nguyen, Long Hoang , Ningrum, Dina Nur Anggraini , Nirayo, Yirga Legesse, Ofori‐Asenso, Richard , Ogbo, Felix Akpojene , Oladimeji, Olanrewaju , Olagunju, Andrew T , Olagunju, Tinuke O , Orpana, Heather , Otstavnov, Stanislav S , Mahesh, P A , Pakhalé, Smita , Park, Eun‐Kee , Pesudovs, Konrad , Polinder, Suzanne , Prakash, Swayam , Rafay, Anwar, Rafiei, Alireza , Rahimi, Siavash , Rahimi‐Movaghar, Vafa , Rahman, Muhammad Aziz , Kumar, Rajesh , Ramezanzadeh, Kiana, Rawaf, David Laith , Renzaho, André M. N. , Resnikoff, Serge , Roever, Leonardo , Sabde, Yogesh , Saddik, Basema , Salamati, Payman , Salimi, Yahya , Salz, Inbal, Samy, Abdallah M , Sanabria, Juan , Sànchez-Riera, Lídia , Santric-Milicevic, Milena M , Satpathy, Maheswar , Sawhney, Monika, Sawyer, Susan M. , Şaylan, Mete , Schwebel, David C. , Seedat, Soraya , Shaikh, Masood Ali, Shams-Beyranvand, Mehran , Shamsizadeh, Morteza , Sharif-Alhoseini, Mahdi , Sheikh, Aziz , Shigematsu, Mika, Shiri, Rahman , Shiue, Ivy , Silva, João Pedro , Sinha, Dhirendra Narain , Filho, Adauto Martins Soares , Soriano, Joan B. , Soshnikov, Sergey , Soyiri, Ireneous N , Starodubov, Vladimir I., Stein, Dan J. , Sufiyan, Mu’awiyyah Babale , Sunshine, Jacob E. , Sykes, Bryan L. , Tabarés‐Seisdedos, Rafael , Tabb, Karen M. , Tessema, Gizachew Assefa , Thakur, Jarnail Singh , Car, Lorainne Tudor , Uzochukwu, Benjamin, Valdéz, Pascual , Varavikova, Elena A. , Vasconcelos, Ana Maria Nogales , Violante, Francesco Saverio , Waheed, Yasir , Wang, Yuan‐Pang , Wijeratne, Tissa , Yadav, Priyanka , Yano, Yuichiro , Yenesew, Muluken Azage, Yisma, Engida , Younis, Mustafa Z , Zafar, Shamsa , Zaman, Sojib Bin , Zodpey, Sanjay , Hay, Simon I , Mokdad, Ali H. , Vos, Theo , Khubchandani, Jagdish , Padrón‐Monedero, Alicia , Wijeratne, T , Stein, Dan J , Islam, Sheikh Mohammed Shariful , Assadi, Reza , Rahman, Muhammad Aziz , Liu, Zichen, Roberts, Nicholas L S , Ahmed, Muktar Beshir , Alghnam, Suliman Abdullah , Aljunid, Syed Mohamed , Antonio, Carl Abelardo T. , Asayesh, Hamid , Bazargan‐Hejazi, Shahrzad , Bedi, Neeraj , Behzadifar, Masoud , Behzadifar, Meysam, Benjet, Corina L. , Benseñor, Isabela M. , Boufous, Soufiane , Carrero, Juan Jesús , Daryani, Ahmad , Daviţoiu, Dragoş Virgil , Degenhardt, Louisa J , Dolan, Kate A , Dubey, Manisha , Zaki, Maysaa El Sayed , Eskandarieh, Sharareh , Filip, Irina , Gill, Tiffany K. , Gupta, Rahul, Hamidi, Samer , Haro, Josep María , Hassankhani, Hadi , Hendrie, Delia V. , Hı́jar, Martha , Hu, Guoqing , Ilesanmi, Olayinka Stephen , Jayatilleke, Achala Upendra , Jonas, Jost B , Kabir, Ali , Kalani, Rizwan, Khoja, Abdullah T , Kim, Young‐Eun , Kim, Daniel , Koyanagi, Ai , Lansingh, Van Charles , Malta, Déborah Carvalho , Mansournia, Mohammad Alì , Melese, Addisu Dagnaw , Meštrović, Tomislav , Moradi‐Lakeh, Maziar , Morrison, Shane D. , Najafi, Farid , Nguyen, Trang Huyen , Nguyen, Huong Lan Thi , Oh, In‐Hwan , Olivares, Pedro Rufino , Patton, George , Phillips, Michael , Radfar, Amir , Rawaf, Salman , Rezaeian, Shahab , Ronfani, Luca , Roshandel, Gholamreza , Saxena, Sonia , Schneider, Ione Jayce Ceola , Sepanlou, Sadaf Ghajarieh , Shen, Jiabin , Singh, Jasvinder A. , Стародубов, В. И. , Stokes, Mark Andrew , Tehrani‐Banihashemi, Arash , Tran, Khanh Bao , Tran, Bach Xuan , Uthman, Olalekan Abdulrahman , Venketasubramanian, Narayanaswamy , Vlassov, Vasily , Winkler, Andrea Sylvia , Azage, Muluken , YIP, PAUL S. F. , Yonemoto, Naohiro , Yu, Chuanhua , Zaidi, Zoubida , Zamani, Mohammad , Zhao, Yong , Lopez, Alan D , Olagunju, Andrew T , Alahdab, Fares

Injury Prevention | January 9, 2020 | Volume: 26 | Issue: Suppl 2 | Pages: i12-i26

10.1136/injuryprev-2019-043296 | PMID 31915273 Get It

Background The epidemiological transition of non-communicable diseases replacing infectious diseases as the main contributors to disease burden has been well documented in global health literature. Less focus, however, has been given to the relationship between sociodemographic changes and injury. The aim of this study was to examine the association between disability-adjusted life years (DALYs) from injury for 195 countries and territories at different levels along the development spectrum between 1990 and 2017 based on the Global Burden of Disease (GBD) 2017 estimates. Methods Injury mortality was estimated using the GBD mortality database, corrections for garbage coding and CODEm—the cause of death ensemble modelling tool. Morbidity estimation was based on surveys and inpatient and outpatient data sets for 30 cause-of-injury with 47 nature-of-injury categories each. The Socio-demographic Index (SDI) is a composite indicator that includes lagged income per capita, average educational attainment over age 15 years and total fertility rate. Results For many causes of injury, age-standardised DALY rates declined with increasing SDI, although road injury, interpersonal violence and self-harm did not follow this pattern. Particularly for self-harm opposing patterns were observed in regions with similar SDI levels. For road injuries, this effect was less pronounced. Conclusions The overall global pattern is that of declining injury burden with increasing SDI. However, not all injuries follow this pattern, which suggests multiple underlying mechanisms influencing injury DALYs. There is a need for a detailed understanding of these patterns to help to inform national and global efforts to address injury-related health outcomes across the development spectrum.
The association of microhematuria with mesangial hypercellularity, endocapillary hypercellularity, crescent score and renal outcomes in immunoglobulin A nephropathy
Bobart, Shane A. , Alexander, Mariam P., Shawwa, Khaled , Vaughan, Lisa E. , Ghamrawi, Ranine , Sethi, Sanjeev , Cornell, Lynn D. , Glassock, Richard J. , Zand, Ladan , Cornell, Lynn, Cornell, Lynn , Fervenza, Fernando C.

Nephrology Dialysis Transplantation | November 20, 2019 | Volume: 36 | Issue: 5 | Pages: 840-847

10.1093/ndt/gfz267 | PMID 31859353 Get It

Abstract Background Microhematuria is common in immunoglobulin A nephropathy (IgAN). However, current prognostication is based on proteinuria and mesangial hypercellularity, endocapillary hypercellularity, segmental sclerosis, tubulointerstitial fibrosis and crescent (MEST-C) scores. Methods In this retrospective study, we evaluated whether MEST-C score components are associated with the presence of microhematuria at biopsy and whether the degree of microhematuria during follow-up is associated with change in estimated glomerular filtration rate (eGFR), after adjusting for clinical and histological parameters. We identified 125 patients with biopsy-proven IgAN and MEST-C scoring who were not on immunosuppressive therapy at biopsy. Microhematuria was defined as ≥3 red blood cells (RBCs)/high-power field (hpf). Results Of the 125 patients, 97 had microhematuria at baseline and were more likely to have M1, E1 and C ≥ 1 lesions (P < 0.05 for all) compared with patients without microhematuria. Of the 125 patients, 72 had follow-up data available. An increase in the degree of microhematuria was significantly associated with an eGFR decline of −0.81 mL/min/1.73 m2 [95% confidence interval (CI) −1.44 to −0.19, P = 0.01], after adjusting for follow-up time, proteinuria and T score. Severe microhematuria (≥21 RBCs/hpf) was associated with an even larger decline in eGFR (−3.99 mL/min/1.73 m2; 95% CI −6.9411 to −1.0552, P = 0.008), after similar adjustments. Conclusion Degree of microhematuria during follow-up is an independent predictor of eGFR decline after adjusting for clinical and histological parameters. Therefore, monitoring the degree of microhematuria as well as proteinuria is important when evaluating patients with IgAN. Additional studies using improvement in microhematuria as a primary surrogate outcome are needed.
Deep Learning–Based Histopathologic Assessment of Kidney Tissue
Hermsen, Meyke , Bel, Thomas de , Boer, Marjolijn den, Steenbergen, Eric J., Florquin, Sandrine , Roelofs, Joris J. T. H. , Stegall, Mark D. , Alexander, Mariam P., Smeets, Bart , Laak, Jeroen van der , Stegall, Mark D , Kers, Jesper , Smith, Byron H. , Hilbrands, Luuk B.

Journal of the American Society of Nephrology | September 5, 2019 | Volume: 30 | Issue: 10 | Pages: 1968-1979

10.1681/asn.2019020144 | PMID 31488607 Get It

Significance Statement Histopathologic assessment of kidney tissue currently relies on manual scoring or traditional image-processing techniques to quantify and classify tissue features, time-consuming approaches that have limited reproducibility. The authors present an alternative approach, featuring a convolutional neural network for multiclass segmentation of kidney tissue in sections stained by periodic acid–Schiff. Their findings demonstrate applicability of convolutional neural networks for tissue from multiple centers, for biopsies and nephrectomy samples, and for the analysis of both healthy and pathologic tissues. In addition, they validated the network’s results with components from the Banff classification system. Their convolutional neural network may have utility for quantitative studies involving kidney histopathology across centers and potential for application in routine diagnostics. Background The development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized kidney tissue sections stained with periodic acid–Schiff (PAS). Methods We trained the network using multiclass annotations from 40 whole-slide images of stained kidney transplant biopsies and applied it to four independent data sets. We assessed multiclass segmentation performance by calculating Dice coefficients for ten tissue classes on ten transplant biopsies from the Radboud University Medical Center in Nijmegen, The Netherlands, and on ten transplant biopsies from an external center for validation. We also fully segmented 15 nephrectomy samples and calculated the network’s glomerular detection rates and compared network-based measures with visually scored histologic components (Banff classification) in 82 kidney transplant biopsies. Results The weighted mean Dice coefficients of all classes were 0.80 and 0.84 in ten kidney transplant biopsies from the Radboud center and the external center, respectively. The best segmented class was “glomeruli” in both data sets (Dice coefficients, 0.95 and 0.94, respectively), followed by “tubuli combined” and “interstitium.” The network detected 92.7% of all glomeruli in nephrectomy samples, with 10.4% false positives. In whole transplant biopsies, the mean intraclass correlation coefficient for glomerular counting performed by pathologists versus the network was 0.94. We found significant correlations between visually scored histologic components and network-based measures. Conclusions This study presents the first convolutional neural network for multiclass segmentation of PAS-stained nephrectomy samples and transplant biopsies. Our network may have utility for quantitative studies involving kidney histopathology across centers and provide opportunities for deep learning applications in routine diagnostics.
Myoglobinuria in Autopsy Pathology: Relevant and Potentially Unrecognized
Blessing, Melissa M. , Reichard, R. Ross , Maleszewski, Joseph J. , Alexander, Mariam P.

Academic Forensic Pathology | June 26, 2019 | Volume: 4 | Issue: 2 | Pages: 226-234

10.23907/2014.035 Get It

Background Myoglobin-related renal injury (MRRI) is a significant cause of acute renal injury and may result in death. Common etiologies in forensic pathology include trauma and drug abuse. This study sought to determine the prevalence and causes of MRRI at autopsy and discuss diagnostic challenges. Methods The institutional autopsy archives were queried for cases in which a myoglobin (MG) immunohistochemical stain was performed or MRRI was diagnosed or considered. The clinicopathological characteristics of this population were described. Results Of 9996 cases over a period of 19.5 years, 17 cases (0.2%) fulfilled the criteria. Patient age ranged from 15 to 74 years; 11 were men. The MG stain was performed in 13 cases. In 11 (65%) cases, MRRI was diagnosed with or without immunohistochemistry. The clinical backgrounds were varied; sepsis and liver injury predominated. Time between original insult and death ranged from seven hours to four months. Patterns of MRRI included cast formation or fine brush border staining in the proximal tubules. Discussion MRRI is infrequently considered in the autopsy setting. Many causes of MRRI identified in this series involved circumstances placing the death into medical examiner jurisdiction; the MG stain contributed to understanding the mechanism of death. Acute tubular injury with cast formation was observed in the majority of cases. Conclusion MRRI is common in a select group of autopsies but may be underappreciated. The MG stain is a useful and inexpensive tool to aid in the diagnosis of MRRI in autopsy pathology.
Use of homologous recombination deficiency (HRD) score to enrich for niraparib sensitive high grade ovarian tumors.
Wilcoxen, Keith, Becker, Marc A., Neff, Christopher, Abkevich, Victor, Jones, Joshua T., Hou, Xiaonan , Wang, Yan , Hartman, Anne‐Renee , AlHilli, Mariam , Gutin, Alexander , Agarwal, Shefali , Timms, Kirsten M. , Neff, Chris, Haluska, Paul

Journal of Clinical Oncology | March 7, 2019 | Volume: 33 | Issue: 15_suppl | Pages: 5532-5532

10.1200/jco.2015.33.15_suppl.5532 Get It