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1. Retinoblastoma with and without Extraocular Tumor Extension

Author

Swathi Kaliki, MD, Vijitha S. Vempuluru, MD, Ido Didi Fabian, MD, Elhassan Abdallah, MD, Shehu U. Abdullahi, MD, Rula A. Abdulqader, MD, Aminatu A. Abdulrahaman, MD, Sherif Abouelnaga, MD, Dupe S. Ademola-Popoola, FMCOph, FWACS, Adedayo Adio, FWACS, Mahmoud A. Afifi, MD, Armin R. Afshar, MD, Priyanka Aggarwal, MD, Ada E. Aghaji, FMCOph MSc, Alia Ahmad, MRCPCH UK, Marliyanti N.R. Akib, MD, Adeseye M. Akinsete, MBBS, Lamis Al Harby, MD, Saleh A. Al Mesfer, MD, Mouroge H. Al Ani, MD, Silvia Alarcón Portabella, MD, Safaa A.F. Al-Badri, MD, Ana Patricia A. Alcasabas, MD, Saad A. Al-Dahmash, MD, Amanda Alejos, MD, Ernesto Alemany-Rubio, MD, Amadou I. Alfa Bio, MD, Yvania Alfonso Carreras, MD, Christiane E. Al-Haddad, MD, Hamoud H.Y. Al-Hussaini, MD, MSc, Amany M. Ali, MD, Donjeta B. Alia, MD, Mazin F. Al-Jadiry, MD, Usama Al-Jumaly, MD, Hind M. Alkatan, MD, Charlotta All-Eriksson, MD, PhD, Ali A.R.M. Al-Mafrachi, FIBMS, Argentino A. Almeida, MD, Khalifa M. Alsawidi, MD, Athar A.S.M. Al-Shaheen, MD, Entissar H. Al-Shammary, MD, Doreen Amankwaa-Frempong, MBChB, Primawita O. Amiruddin, MD, Inggar Armytasari, MD, Nicholas J. Astbury, FRCS, FRCOphth, Hatice T. Atalay, MD, Eda Ataseven, MD, La-ongsri Atchaneeyasakul, MD, Rose Atsiaya, OCO, Rudolf Autrata, MD, PhD, Julia Balaguer, MD, PhD, Ruhengiz Balayeva, PhD, Honorio Barranco, MD, PhD, Paulina Bartoszek, MD, Katarina Bartuma, MD, PhD, Covadonga Bascaran, MD, MSc, Nikolaos E. Bechrakis, MD, Maja Beck Popovic, MD, Ainura S. Begimkulova, MD, Sarra Benmiloud, MD, Rokia C. Berete, MD, PhD, Jesse L. Berry, MD, Anirban Bhaduri, MD, Sunil Bhat, MBBS, MD, Arpita Bhattacharyya, MD, Eva M. Biewald, MD, Elaine Binkley, MD, Sharon Blum, MD, Nadia Bobrova, MD, H. Culver Boldt, MD, Maria Teresa B.C. Bonanomi, MD, PhD, Gabrielle C. Bouda, MD, Hédi Bouguila, MD, PhD, Rachel C. Brennan, MD, Bénédicte G. Brichard, MD, PhD, Jassada Buaboonnam, MD, Aléine Budiongo, MD, Matthew Burton, FRCOphth, Patricia Calderón-Sotelo, MD, Doris A. Calle Jara, MD, Jayne E. Camuglia, FRANZCO, Miriam R. Cano, MD, MSc, Michael Capra, FRCPI, Shani Caspi, MD, Nathalie Cassoux, MD, PhD, Guilherme Castela, MD, Luis Castillo, MD, Jaume Català-Mora, MD, PhD, Isabel Caviedes, MD, Arthika Chandramohan, MD, Guillermo L. Chantada, MD, PhD, Shabana Chaudhry, MD, Bhavna Chawla, MD, Wensi Chen, MD, Faraja S. Chiwanga, MSc, Tsengelmaa Chuluunbat, MD, PhD, Krzysztof Cieslik, MD, Antony Clark, FRANZCO, Ruellyn L. Cockcroft, MB ChB , M Med Paed, Codruta Comsa, MD, Maria G. Correa Llano, MD, Timothy W. Corson, PhD, Line Couitchere, MD, Kristin E. Cowan-Lyn, MD, MBBS, Monika Csóka, MD, PhD, Wantanee Dangboon, MD, Anirban Das, MD, Pranab Das, MD, Sima Das, MS, Jacquelyn M. Davanzo, BSN, BSPH, Alan Davidson, MBChB, MPhil, Sonia De Francesco, MD, Patrick De Potter, MD, PhD, Karina Q. Delgado, MD, PhD, Hakan Demirci, MD, Laurence Desjardins, MD, Rosdali Y. Diaz Coronado, MD, Helen Dimaras, PhD, Andrew J. Dodgshun, M Phil, Carla R. Donato Macedo, MD, Monica D. Dragomir, MD, PhD, Yi Du, MD, Magritha Du Bruyn, MD, Johannes P. Du Plessis, MMed (Paed), Gagan Dudeja, MBBS, MS, Katrin Eerme, MD, I Wayan Eka Sutyawan, MD, Asmaa El Kettani, MD, Amal M. Elbahi, MD, James E. Elder, MBBS, Alaa M. Elhaddad, MD, PhD, Moawia M.A. Elhassan, MD, Mahmoud M. Elzembely, MD, Connor Ericksen, MD, Vera A. Essuman, FWACS, Ted Grimbert A. Evina, MD, Ifeoma R. Ezegwui, FMCOph, FWACS, FAEH, Zehra Fadoo, MBBS, Adriana C. Fandiño, MD, Mohammad Faranoush, MD, Oluyemi Fasina, FWACS, Delia D.P.G. Fernández, MSc, Ana Fernández-Teijeiro, MD, PhD, Allen Foster, FRCOphth, Shahar Frenkel, MD, PhD, Ligia D. Fu, MD, Soad L. Fuentes-Alabi, MD, MPH, Juan L. Garcia, MSc, David García Aldana, MD, Henry N. Garcia Pacheco, MD, Jennifer A. Geel, MBChB, MMed, Fariba Ghassemi, MD, Ana V. Girón, MD, Marco A. Goenz, MD, Aaron S. Gold, OD, Hila Golberg, MD, Glen A. Gole, MD, FRANZCO, Nir Gomel, MD, Efren Gonzalez, MD, Graciela Gonzalez Perez, MD, Liudmira González-Rodríguez, MD, Malka Gorfine, PhD, Jaime Graells, MD, Pernille A. Gregersen, MD, Nathalia D.A.K. Grigorovski, MD, Koffi M. Guedenon, MD, D Sanjeeva Gunasekera, MD, Ahmet K. Gündüz, MD, Himika Gupta, MD, Sanjiv Gupta, MS, Vineeta Gupta, MD, Theodora Hadjistilianou, MD, Patrick Hamel, MD, Syed A. Hamid, FCPS, Norhafizah Hamzah, MSc, Eric D. Hansen, MD, J William Harbour, MD, M. Elizabeth Hartnett, MD, Murat Hasanreisoglu, MD, Sadiq Hassan, MD, FWACS, Shadab Hassan, FRCS, FCPS, Wojciech Hautz, MD, Huda A. Haydar, CHD, Stanislava Hederova, MD, Laila Hessissen, MD, Hoby Lalaina, MD, Suradej Hongeng, MD, Diriba F. Hordofa, MD, G. Baker Hubbard, MD, Marlies Hummlen, MD, Kristina Husakova, MD, Allawi N. Hussein Al-Janabi, MD, Affiong A. Ibanga, MB.BCh, FMCOph, Russo Ida, MD, Vesna R. Ilic, MD, Ziyavuddin Islamov, MD, Vivekaraj Jairaj, DNB, Teyyeb A. Janjua, MD, FCPS, FRCSEd, Irfan Jeeva, FRCOphth, Xunda Ji, MD, Dong Hyun Jo, MD, PhD, Michael M. Jones, MD, PhD, FRANZCO, Theophile B. Amani Kabesha, MD, PhD, Rolande L. Kabore, MD, Abubakar Kalinaki, MD, Pius Kamsang, MD, Mehmet Kantar, MD, Noa Kapelushnik, MD, Tamar Kardava, PhD, Rejin Kebudi, MD, Jonny Keomisy, MD, Tomas Kepak, MD, Petra Ketteler, MD, Zohora J. Khan, MD, Hussain A. Khaqan, MD, Vikas Khetan, FRCS, FACS, Alireza Khodabande, MD, Zaza Khotenashvili, MD, Jonathan W. Kim, MD, Jeong Hun Kim, MD, PhD, Hayyam Kiratli, MD, Tero T. Kivelä, MD, Artur Klett, MD, PhD, Irem Koç, MD, Jess Elio Kosh Komba Palet, MD, Dalia Krivaitiene, MD, PhD, Mariana Kruger, Mmed Paed, PhD, Kittisak Kulvichit, MD, Mayasari W. Kuntorini, MD, Alice Kyara, BA, Geoffrey C. Lam, FRANZCO, Scott A. Larson, MD, Slobodanka Latinović, MD, PhD, Kelly D. Laurenti, MD, Yotam Lavi, MD, PhD, Alenka Lavric Groznik, MD, Amy A. Leverant, MD, Cairui Li, MD, Kaijun Li, MD, Ben Limbu, MD, Chun-Hsiu Liu, MD, Quah Boon Long, FRCS (Ed), MMed ( Ophth), FAMS, Juan P. López, MD, Robert M. Lukamba, MD, Sandra Luna-Fineman, MD, Delfitri Lutfi, MD, Lesia Lysytsia, MD, Shiran Madgar, MD, George N. Magrath, MD, Amita Mahajan, MD, Puja Maitra, MD, Erika Maka, MD, Emil K. Makimbetov, MD, Azza M.Y. Maktabi, MD, Carlos Maldonado, MD, Ashwin Mallipatna, MD, Rebecca Manudhane, MD, Lyazat Manzhuova, MD, Nieves Martín Begue, MD, PhD, Sidra Masud, MBBS, Ibrahim O. Matende, MD, M. Med (Oph), Clarissa C.D.S. Mattosinho, MD, Marchelo Matua, BAPH, Ismail Mayet, MD, Freddy B. Mbumba, MD, MMed Paed, John D. McKenzie, MD, Azim Mehrvar, MD, Aemero A. Mengesha, MD, Vikas Menon, MD, Gary John V.D.D. Mercado, MD, Marilyn B. Mets, MD, Edoardo Midena, MD, PhD, Audra Miller, MD, Divyansh K.C. Mishra, DNB, Furahini G. Mndeme, MD, Ahmed A. Mohamedani, FRCPath, Mona T. Mohammad, MD, FRCS, Annette C. Moll, MD, PhD, Margarita M. Montero, MD, Claude Moreira, MD, PhD, Prithvi Mruthyunjaya, MD, MHS, Mchikirwa S. Msina, MMed Ophth, Gerald Msukwa, MMed Ophth, Sangeeta S. Mudaliar, DNB Pediatric, Hassan Muhammad, MD, Kangwa I. Muma, MMed Ophth, FCOphth, Francis L. Munier, MD, Timothy G. Murray, MD, MBA, Kareem O. Musa, FWACS, FMCOphth, FICO, Asma Mushtaq, MD, Anne A. Musika, MD, Hamzah Mustak, MD, Tajudeen Mustapha, MBBS, FWACS, Okwen M. Muyen, MD, Khumo H. Myezo, Msc, Gita Naidu, MMed Paed, PhD, Natasha Naidu, MBCHB, FCS Ophthalmol, Akshay Gopinathan Nair, MD, Sundaram Natarajan, FRCS, Larisa Naumenko, MD, PhD, Paule Aïda Ndoye Roth, MD PhD, Yetty M. Nency, MD, Vladimir Neroev, MD, PhD, Yvonne Ng, MBChB ( Auckland) , FRANZCO, Marina Nikitovic, MD, PhD, Elizabeth D. Nkanga, FMCOph, Henry E. Nkumbe, MD, Marcel N. Numbi, MD, Kalle Nummi, MD, Murtuza Nuruddin, FRCS, Mutale Nyaywa, MD, MMed Ophth, FCOphth, Chinsisi Nyirenda, MD, Ghislaine Obono-Obiang, MD, Scott C.N. Oliver, MD, Joaquin Ooporto, MD, Miriam Ortega-Hernández, MD, Alexander Oscar, MD, Diego Ossandon, MD, Halimah Pagarra, MD, PhD, Vivian Paintsil, FWACP, Luisa Paiva, MD, Mahesh Shanmugam Palanivelu, FRCSED, Ruzanna Papyan, MD, Raffaele Parrozzani, MD, PhD, Claudia R. Pascual Morales, MD, Katherine E. Paton, MD, FRCSC, Jacob Pe'er, MD, Jesús Peralta Calvo, MD, Sanja Perić, MD, PhD, Chau T.M. Pham, MD, Remezo Philbert, MD, David A. Plager, MD, Pavel Pochop, MD, PhD, Rodrigo A. Polania, MD, Vladimir Polyakov, MD, Jimena Ponce, MD, Ali O. Qadir, MD, Seema Qayyum, FCPS, Jiang Qian, MD, Ardizal Rahman, MD, Purnima Rajkarnikar, MD, Rajesh Ramanjulu, MD, Aparna Ramasubramanian, MD, Marco A. Ramirez-Ortiz, MD, MPH, Jasmeen K. Randhawa, BA, Léa Raobela, MD, Riffat Rashid, MS, M. Ashwin Reddy, FRCOphth, Lorna A. Renner, FRCPCH (UK), David Reynders, MD, Dahiru Ribadu, FMCOph, Petra Ritter-Sovinz, MD, Anna Rogowska, MD, Duangnate Rojanaporn, MD, Livia Romero, MD, Soma R. Roy, DCO, Raya H. Saab, MD, Svetlana Saakyan, MD, PhD, Ahmed H. Sabhan, MD, Mandeep S. Sagoo, FRCS (Ed), Azza M.A. Said, MD, Rohit Saiju, MD, Beatriz Salas, MD, Sonsoles San Román Pacheco, MD, Gissela L. Sánchez, MD, Alma Janeth Sanchez Orozco, MD, Phayvanh Sayalith, MD, Trish A. Scanlan, MRCPI, MSc, Christoph Schwab, MD, Ahad Sedaghat, MD, Rachna Seth, DNB MNAMS, Mariana Sgroi, MD, Ankoor S. Shah, MD, PhD, Shawkat A. Shakoor, MS, Manoj K. Sharma, MD, Sadik T. Sherief, MD, Carol L. Shields, MD, David Sia, MB ChB, FRANZCO, Sorath Noorani Siddiqui, MD, Sidi Sidi cheikh, MD, PhD, Sónia Silva, MD, Arun D. Singh, MD, Usha Singh, MS, Penny Singha, MD, Rita S. Sitorus, MD, PhD, Alison H. Skalet, MD, PhD, Hendrian D. Soebagjo, MD, PhD, Tetyana Sorochynska, MD, PhD, Grace Ssali, MD, Andrew W. Stacey, MD, Sandra E. Staffieri, PhD, Erin D. Stahl, MD, David M. Steinberg, PhD, David K. Stones, MBChB, FCPaed, Caron Strahlendorf, MD, Maria Estela Coleoni Suarez, MD, Sadia Sultana, FCPS, Xiantao Sun, MD, Rosanne Superstein, MD, Eddy Supriyadi, MD, PhD, Supawan Surukrattanaskul, MD, Shigenobu Suzuki, MD, PhD, Karel Svojgr, MD, PhD, Fatoumata Sylla, MD, Gevorg Tamamyan, MD, PhD, Deborah Tan, MBBS, Alketa Tandili, MD, PhD, Jing Tang, MD, Fanny F. Tarrillo Leiva, MD, Maryam Tashvighi, MD, Bekim Tateshi, MD, PhD, Kok Hoi Teh, MD, Edi S. Tehuteru, MD, Luiz F. Teixeira, MD, Manca Tekavcic Pompe, MD, PhD, Abdullah Dahan M. Thawaba, MD, Tuyisabe Theophile, MSc, Helen Toledano, MBChB, Doan L. Trang, MD, Fousseyni Traoré, MD, Devjyoti Tripathy, MD, Samuray Tuncer, MD, Harba Tyau-Tyau, MD, Ali B. Umar, MD, FMCPath, Emel Unal, MD, Ogul E. Uner, BA, Steen F. Urbak, MD, PhD, Tatiana L. Ushakova, MD, Rustam H. Usmanov, MD, Sandra Valeina, MD, Paola Valente, MD, Milo van Hoefen Wijsard, MD, Jacqueline Karina Vasquez Anchaya, MD, Leon O. Vaughan, FRCS (Ed), Nevyana V. Veleva-Krasteva, MD, PhD, Nishant Verma, MD, Andi A. Victor, MD, PhD, Maris Viksnins, MD, Edwin G. Villacís Chafla, MD, Victor M. Villegas, MD, Victoria Vishnevskia-Dai, MD, Keith Waddell, DM, FRCP, FRCS, FRCOphth, Amina H. Wali, MD, FMCOph Nigeria, Yi-Zhuo Wang, MD, Nutsuchar Wangtiraumnuay, MD, FICO, Julie A. Wetter, MMed Rad Onc, FCRad Onc, Widiarti P. Riono, MD, Matthew W. Wilson, MD, Amelia D.C. Wime, MD, Atchareeya Wiwatwongwana, MD, Damrong Wiwatwongwana, MD, Charlotte Wolley Dod, MD, Emily S. Wong, FCOphth HK, FHKAM, Phanthipha Wongwai, MD, PhD, Si-qi Wu, MSc, Daoman Xiang, MD, PhD, Yishuang Xiao, MSc, Bing Xu, MD, Kang Xue, MD, Antonio Yaghy, MD, Jason C. Yam, FRCSEd, Huasheng Yang, MD, Jenny M. Yanga, MD, Muhammad A. Yaqub, MD, FCPS, FRCSEd, Vera A. Yarovaya, MD, Andrey A. Yarovoy, MD, PhD, Huijing Ye, MD, Roberto I. Yee, MD, Yacoub A. Yousef, MD, Putu Yuliawati, MD, Arturo M. López, MD, Ekhtelbenina Zein, MD, Yi Zhang, MD, PhD, Katsiaryna Zhilyaeva, MD, Nida Zia, MBBS, MCPS, Othman A.O. Ziko, MD, PhD, Marcia Zondervan, MBA, Sabrina Schlüter, MD, and Richard Bowman, FRCOphth

Subjects
External beam radiotherapy, Extraocular extension, Multimodal treatment, Retinoblastoma, Tumor, Ophthalmology, RE1-994
Abstract

Purpose: To study the treatment and outcomes of children with retinoblastoma (RB) with extraocular tumor extension (RB-EOE) and compare them with RB without extraocular tumor extension (RB-w/o-EOE). Design: Multicenter intercontinental collaborative prospective study from 2017 to 2020. RB-EOE cases included those with overt orbital tumor extension in treatment-naive patients. Cases with microscopic orbital extension detected postenucleation were excluded from the study. Participants: A total of 319 children with RB-EOE and 3116 children with RB-w/o-EOE. Intervention: Chemotherapy, enucleation, exenteration, radiotherapy. Main Outcome Measures: Systemic metastasis and death. Results: Of the 3435 RB patients included in this study, 309 (9%) were from low-income countries (LIC), 1448 (42%) from lower-middle income, 1012 (29%) from upper-middle income, and 666 (19%) patients from high-income countries. There was an inverse relationship between the percentage of RB-EOE and national income level, with 96 (31%) patients from LIC, 197 (6%) lower-middle income, 20 (2%) upper-middle income, and 6 (1%) patients from high-income countries (P = 0.0001). The outcomes were statistically significant for RB-EOE compared with RB-w/o-EOE: systemic metastasis (32% vs. 4% respectively; P = 0.0001) and metastasis-related death (63% vs. 6% respectively; P = 0.0001). Multimodal treatment was the most common form of treatment (n = 177; 54%) for RB-EOE, with most cases undergoing a combination of intravenous chemotherapy and enucleation (n = 97; 30%). Adjuvant external beam radiotherapy (EBRT) after surgery (enucleation/orbital exenteration) was given in only 68 (21%) cases. Kaplan–Meier analysis for systemic metastasis and metastasis-related death in RB-EOE was 28% and 57% at 1 year, 29% and 60% at 2 years, and 29% and 61% at 3 years, respectively. Cox regression analysis revealed that the risk of death from RB-EOE was greater in patients aged >4 years than

Published
2025
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2. Hospital load and increased COVID-19 related mortality in Israel

Author

Hagai Rossman, Tomer Meir, Jonathan Somer, Smadar Shilo, Rom Gutman, Asaf Ben Arie, Eran Segal, Uri Shalit, and Malka Gorfine

Subjects
Science
Abstract

COVID-19 has caused many healthcare systems to become overwhelmed, potentially impacting patient care. Here, the authors show that COVID-19-related in-hospital mortality rates in Israel increased in periods of moderate or high hospital load, independent of patient characteristics.

Published
2021
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3. General Semiparametric Shared Frailty Model: Estimation and Simulation with frailtySurv

Author

John V. Monaco, Malka Gorfine, and Li Hsu

Subjects
shared frailty model, survival analysis, clustered data, frailtysurv, Statistics, HA1-4737
Abstract

The R package frailtySurv for simulating and fitting semi-parametric shared frailty models is introduced. Package frailtySurv implements semi-parametric consistent estimators for a variety of frailty distributions, including gamma, log-normal, inverse Gaussian and power variance function, and provides consistent estimators of the standard errors of the parameters' estimators. The parameters' estimators are asymptotically normally distributed, and therefore statistical inference based on the results of this package, such as hypothesis testing and confidence intervals, can be performed using the normal distribution. Extensive simulations demonstrate the flexibility and correct implementation of the estimator. Two case studies performed with publicly available datasets demonstrate applicability of the package. In the Diabetic Retinopathy Study, the onset of blindness is clustered by patient, and in a large hard drive failure dataset, failure times are thought to be clustered by the hard drive manufacturer and model.

Published
2018
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4. Heritability Estimation using a Regularized Regression Approach (HERRA): Applicable to continuous, dichotomous or age-at-onset outcome.

Author

Malka Gorfine, Sonja I Berndt, Jenny Chang-Claude, Michael Hoffmeister, Loic Le Marchand, John Potter, Martha L Slattery, Nir Keret, Ulrike Peters, and Li Hsu

Subjects
Medicine, Science
Abstract

The popular Genome-wide Complex Trait Analysis (GCTA) software uses the random-effects models for estimating the narrow-sense heritability based on GWAS data of unrelated individuals without knowing and identifying the causal loci. Many methods have since extended this approach to various situations. However, since the proportion of causal loci among the variants is typically very small and GCTA uses all variants to calculate the similarities among individuals, the estimation of heritability may be unstable, resulting in a large variance of the estimates. Moreover, if the causal SNPs are not genotyped, GCTA sometimes greatly underestimates the true heritability. We present a novel narrow-sense heritability estimator, named HERRA, using well-developed ultra-high dimensional machine-learning methods, applicable to continuous or dichotomous outcomes, as other existing methods. Additionally, HERRA is applicable to time-to-event or age-at-onset outcome, which, to our knowledge, no existing method can handle. Compared to GCTA and LDAK for continuous and binary outcomes, HERRA often has a smaller variance, and when causal SNPs are not genotyped, HERRA has a much smaller empirical bias. We applied GCTA, LDAK and HERRA to a large colorectal cancer dataset using dichotomous outcome (4,312 cases, 4,356 controls, genotyped using Illumina 300K), the respective heritability estimates of GCTA, LDAK and HERRA are 0.068 (SE = 0.017), 0.072 (SE = 0.021) and 0.110 (SE = 5.19 x 10-3). HERRA yields over 50% increase in heritability estimate compared to GCTA or LDAK.

Published
2017
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5. A novel host-proteome signature for distinguishing between acute bacterial and viral infections.

Author

Kfir Oved, Asi Cohen, Olga Boico, Roy Navon, Tom Friedman, Liat Etshtein, Or Kriger, Ellen Bamberger, Yura Fonar, Renata Yacobov, Ron Wolchinsky, Galit Denkberg, Yaniv Dotan, Amit Hochberg, Yoram Reiter, Moti Grupper, Isaac Srugo, Paul Feigin, Malka Gorfine, Irina Chistyakov, Ron Dagan, Adi Klein, Israel Potasman, and Eran Eden

Subjects
Medicine, Science
Abstract

Bacterial and viral infections are often clinically indistinguishable, leading to inappropriate patient management and antibiotic misuse. Bacterial-induced host proteins such as procalcitonin, C-reactive protein (CRP), and Interleukin-6, are routinely used to support diagnosis of infection. However, their performance is negatively affected by inter-patient variability, including time from symptom onset, clinical syndrome, and pathogens. Our aim was to identify novel viral-induced host proteins that can complement bacterial-induced proteins to increase diagnostic accuracy. Initially, we conducted a bioinformatic screen to identify putative circulating host immune response proteins. The resulting 600 candidates were then quantitatively screened for diagnostic potential using blood samples from 1002 prospectively recruited patients with suspected acute infectious disease and controls with no apparent infection. For each patient, three independent physicians assigned a diagnosis based on comprehensive clinical and laboratory investigation including PCR for 21 pathogens yielding 319 bacterial, 334 viral, 112 control and 98 indeterminate diagnoses; 139 patients were excluded based on predetermined criteria. The best performing host-protein was TNF-related apoptosis-inducing ligand (TRAIL) (area under the curve [AUC] of 0.89; 95% confidence interval [CI], 0.86 to 0.91), which was consistently up-regulated in viral infected patients. We further developed a multi-protein signature using logistic-regression on half of the patients and validated it on the remaining half. The signature with the highest precision included both viral- and bacterial-induced proteins: TRAIL, Interferon gamma-induced protein-10, and CRP (AUC of 0.94; 95% CI, 0.92 to 0.96). The signature was superior to any of the individual proteins (P

Published
2015
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6. Function of cancer associated genes revealed by modern univariate and multivariate association tests.

Author

Malka Gorfine, Boaz Goldstein, Alla Fishman, Ruth Heller, Yair Heller, and Ayelet T Lamm

Subjects
Medicine, Science
Abstract

Copy number variation (CNV) plays a role in pathogenesis of many human diseases, especially cancer. Several whole genome CNV association studies have been performed for the purpose of identifying cancer associated CNVs. Here we undertook a novel approach to whole genome CNV analysis, with the goal being identification of associations between CNV of different genes (CNV-CNV) across 60 human cancer cell lines. We hypothesize that these associations point to the roles of the associated genes in cancer, and can be indicators of their position in gene networks of cancer-driving processes. Recent studies show that gene associations are often non-linear and non-monotone. In order to obtain a more complete picture of all CNV associations, we performed omnibus univariate analysis by utilizing dCov, MIC, and HHG association tests, which are capable of detecting any type of association, including non-monotone relationships. For comparison we used Spearman and Pearson association tests, which detect only linear or monotone relationships. Application of dCov, MIC and HHG tests resulted in identification of twice as many associations compared to those found by Spearman and Pearson alone. Interestingly, most of the new associations were detected by the HHG test. Next, we utilized dCov's and HHG's ability to perform multivariate analysis. We tested for association between genes of unknown function and known cancer-related pathways. Our results indicate that multivariate analysis is much more effective than univariate analysis for the purpose of ascribing biological roles to genes of unknown function. We conclude that a combination of multivariate and univariate omnibus association tests can reveal significant information about gene networks of disease-driving processes. These methods can be applied to any large gene or pathway dataset, allowing more comprehensive analysis of biological processes.

Published
2015
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7. Hospital load and increased COVID-19 related mortality in Israel

Author

Asaf Ben Arie, Smadar Shilo, Hagai Rossman, Jonathan Somer, Rom Gutman, Tomer Meir, Eran Segal, Malka Gorfine, and Uri Shalit

Subjects
Adult, Male, 2019-20 coronavirus outbreak, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Epidemiology, Science, General Physics and Astronomy, 030204 cardiovascular system & hematology, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, 0302 clinical medicine, Patient Load, medicine, Computational models, Humans, 030212 general & internal medicine, Hospital Mortality, Israel, Epidemics, Aged, Aged, 80 and over, Multidisciplinary, business.industry, SARS-CoV-2, Mortality rate, COVID-19, General Chemistry, Middle Aged, Hospitals, Hospitalization, Patient population, Standard error, Viral infection, Emergency medicine, Christian ministry, Female, business, Monte Carlo Method, Healthcare system
Abstract

The spread of Coronavirus disease 19 (COVID-19) has led to many healthcare systems being overwhelmed by the rapid emergence of new cases. Here, we study the ramifications of hospital load due to COVID-19 morbidity on in-hospital mortality of patients with COVID-19 by analyzing records of all 22,636 COVID-19 patients hospitalized in Israel from mid-July 2020 to mid-January 2021. We show that even under moderately heavy patient load (>500 countrywide hospitalized severely-ill patients; the Israeli Ministry of Health defined 800 severely-ill patients as the maximum capacity allowing adequate treatment), in-hospital mortality rate of patients with COVID-19 significantly increased compared to periods of lower patient load (250–500 severely-ill patients): 14-day mortality rates were 22.1% (Standard Error 3.1%) higher (mid-September to mid-October) and 27.2% (Standard Error 3.3%) higher (mid-December to mid-January). We further show this higher mortality rate cannot be attributed to changes in the patient population during periods of heavier load., COVID-19 has caused many healthcare systems to become overwhelmed, potentially impacting patient care. Here, the authors show that COVID-19-related in-hospital mortality rates in Israel increased in periods of moderate or high hospital load, independent of patient characteristics.

Published
2021

8. Revisiting the Cumulative Incidence Function With Competing Risks Data

Author

David M Zucker and Malka Gorfine

Subjects
Statistics and Probability, Methodology (stat.ME), FOS: Computer and information sciences, 62N02, Statistics, Probability and Uncertainty, Statistics - Methodology
Abstract

We consider estimation of the cumulative incidence function (CIF) in the competing risks Cox model. We study three methods. Methods 1 and 2 are existing methods while Method 3 is a newly-proposed method. Method 3 is constructed so that the sum of the CIF's across all event types at the last observed event time is guaranteed, assuming no ties, to be equal to 1. The performance of the methods is examined in a simulation study, and the methods are illustrated on a data example from the field of computer code comprehension. The newly-proposed Method 3 exhibits performance comparable to that of Methods 1 and 2 in terms of bias, variance, and confidence interval coverage rates. Thus, with our newly-proposed estimator, the advantage of having the end-of-study total CIF equal to 1 is achieved with no price to be paid in terms of performance.

Published
2022

9. Nonparametric Adjustment for Measurement Error in Time-to-Event Data: Application to Risk Prediction Models

Author

Hormuzd A. Katki, Malka Gorfine, Argyrios Ziogas, Danielle Braun, and Giovanni Parmigiani

Subjects
Statistics and Probability, Mean squared error, Calibration (statistics), Mismeasured Covariates, Statistics & Probability, Context (language use), Bioengineering, 01 natural sciences, Article, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Statistics, Breast Cancer, Econometrics, 0101 mathematics, Family History, Mathematics, Event (probability theory), Cancer, Demography, Observational error, Carrier Status Prediction, Prevention, Nonparametric statistics, Estimator, Smoothed Kaplan-Meier Estimator, Survival Analysis, 030220 oncology & carcinogenesis, Monte Carlo integration, Statistics, Probability and Uncertainty
Abstract

Mismeasured time-to-event data used as a predictor in risk prediction models will lead to inaccurate predictions. This arises in the context of self-reported family history, a time-to-event predictor often measured with error, used in Mendelian risk prediction models. Using validation data, we propose a method to adjust for this type of error. We estimate the measurement error process using a nonparametric smoothed Kaplan–Meier estimator, and use Monte Carlo integration to implement the adjustment. We apply our method to simulated data in the context of both Mendelian and multivariate survival prediction models. Simulations are evaluated using measures of mean squared error of prediction (MSEP), area under the response operating characteristics curve (ROC-AUC), and the ratio of observed to expected number of events. These results show that our method mitigates the effects of measurement error mainly by improving calibration and total accuracy. We illustrate our method in the context of Mendelian risk prediction models focusing on misreporting of breast cancer, fitting the measurement error model on data from the University of California at Irvine, and applying our method to counselees from the Cancer Genetics Network. We show that our method improves overall calibration, especially in low risk deciles. Supplementary materials for this article are available online.

Published
2017

10. Social adjustment and self-esteem in remitted patients with unipolar and bipolar affective disorder: A case-control study

Author

Yemima Osher, Baruch Shapira, Bernard Lerer, Yevgenia Gelfin, Joseph Zislin, Malka Gorfine, Daniel Souery, and Julien Mendlewicz

Subjects
Adult, Male, medicine.medical_specialty, Bipolar Disorder, lcsh:RC435-571, Matched-Pair Analysis, media_common.quotation_subject, Sex Factors, lcsh:Psychiatry, medicine, Humans, Personality, Bipolar disorder, Family history, Psychiatry, Depression (differential diagnoses), media_common, Analysis of Variance, Depressive Disorder, Remission Induction, Case-control study, Self-esteem, Middle Aged, medicine.disease, Self Concept, Psychiatry and Mental health, Clinical Psychology, Socioeconomic Factors, Case-Control Studies, Antidepressant, Female, Analysis of variance, Psychology, Social Adjustment
Abstract

To evaluate social adjustment and self-esteem in patients with unipolar (UP) and bipolar (BP) affective disorder and to examine demographic and clinical correlates of these variables, outpatients with UP and BP disorder in remission for at least 12 months were consecutively recruited and individually matched to control subjects with no personal or family history of psychiatric illness (UP-control matched pairs, n = 23; BP-control matched pairs, n = 27). Subjects completed the Rosenberg Self-Esteem scale (SES) and the self-report version of the Social Adjustment Scale (SAS). UP patients reported significantly worse overall social adjustment than their matched controls (P = .009), specifically in the area of social and leisure activities (P = .0003) and poorer self-esteem (P = .02). When separated by gender, only the female UP group manifested significant findings on the SAS. BP patients reported poorer self-esteem than their controls (P = .04), but were not significantly different on the SAS. Although the patients were not clinically depressed, a worse social adjustment was significantly associated with a higher score on the Hamilton Depression Scale (HAM-D) in both groups. In the UP group, this association was absent when the analysis was limited to patients receiving antidepressant pharmacotherapy. The findings indicate that (1) UP patients, particularly women, experience substantial difficulties in social adjustment, primarily in social and leisure activities, even during stable clinical remission, and (2) in both UP and BP patients, adjustment problems are related to depressive symptoms even though these are minimal in severity.

Published
1999

11. Missing Genetic Information in Case-Control Family Data with General Semi-Parametric Shared Frailty Model

Author

Anna Graber-Naidich, Malka Gorfine, Kathleen E. Malone, and Li Hsu

Subjects
Hazard (logic), Adult, Genotype, Computer science, Ubiquitin-Protein Ligases, Population, Breast Neoplasms, Article, Statistics, Econometrics, Humans, Computer Simulation, Family, Baseline (configuration management), education, BRCA2 Protein, education.field_of_study, Iterative and incremental development, Models, Statistical, Models, Genetic, Applied Mathematics, Estimator, General Medicine, Function (mathematics), Middle Aged, Semiparametric model, Case-Control Studies, Female, Likelihood function
Abstract

Case-control family data are now widely used to examine the role of gene-environment interactions in the etiology of complex diseases. In these types of studies, exposure levels are obtained retrospectively and, frequently, information on most risk factors of interest is available on the probands but not on their relatives. In this work we consider correlated failure time data arising from population-based case-control family studies with missing genotypes of relatives. We present a new method for estimating the age-dependent marginalized hazard function. The proposed technique has two major advantages: (1) it is based on the pseudo full likelihood function rather than a pseudo composite likelihood function, which usually suffers from substantial efficiency loss; (2) the cumulative baseline hazard function is estimated using a two-stage estimator instead of an iterative process. We assess the performance of the proposed methodology with simulation studies, and illustrate its utility on a real data example.

Published
2010

12. Prospective survival analysis with a general semiparametric shared frailty model - a pseudo full likelihood approach

Author

David M. Zucker, Li Hsu, and Malka Gorfine

Subjects
Statistics and Probability, Pseudolikelihood, Applied Mathematics, General Mathematics, Estimator, Mathematics - Statistics Theory, Variance (accounting), Statistics Theory (math.ST), Agricultural and Biological Sciences (miscellaneous), Standard error, Simple (abstract algebra), Expectation–maximization algorithm, Linear regression, Statistics, Consistent estimator, 62N99, FOS: Mathematics, Statistics, Probability and Uncertainty, General Agricultural and Biological Sciences, Mathematics
Abstract

In this work we provide a simple estimation procedure for a general frailty model for analysis of prospective correlated failure times. Rigorous large-sample theory for the proposed estimators of both the regression coefficient vector and the dependence parameter is given, including consistent variance estimators. In a simulation study under the widely used gamma frailty model, our proposed approach was found to have essentially the same efficiency as the EM-based estimator considered by other authors, with negligible difference between the standard errors of the two estimators. The proposed approach, however, provides a framework capable of handling general frailty distributions with finite moments and yields an explicit consistent variance estimator., 35 pages

Published
2005

14. Survivor Function Estimators Under Group Sequential Monitoring Based on the Logrank Statistic.

Author

Malka Gorfine

Abstract

In this paper we investigate a group sequential analysis of censored survival data with staggered entry, in which the trial is monitored using the logrank test while comparisons of treatment and control Kaplan-Meier curves at various time points are performed at the end of the trial. We concentrate on two-sample tests under local alternatives. We describe the relationship of the asymptotic bias of Kaplan-Meier curves between the two groups. We show that even if the asymptotic bias of the Kaplan-Meier curve is negligible relative to the true survival, this is not the case for the difference between the curves of the two arms of the trial. A corrected estimator for the difference between the survival curves is presented and by simulations we show that the corrected estimator reduced the bias dramatically and has a smaller variance. The methods of estimation are applied to the Beta-Blocker Heart Attack Trial (1982), a well-known group sequential trial. [ABSTRACT FROM AUTHOR]

Published
2003

15. Holocaust Experience and Mortality Patterns: 4-Decade Follow-up in a Population-Based Cohort

Author

Ora Paltiel, Yechiel Friedlander, Orly Manor, Ronit Calderon-Margalit, Hagit Hochner, Malka Gorfine, David S. Siscovick, and Iaroslav Youssim

Subjects
Epidemiology, Population, Coronary Disease, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Statistical significance, Neoplasms, Medicine, Humans, 030212 general & internal medicine, Registries, Survivors, Israel, Mortality, Sex Distribution, education, Survival analysis, education.field_of_study, business.industry, Proportional hazards model, Holocaust, Mortality rate, Hazard ratio, Age Factors, Original Contribution, Confidence interval, 3. Good health, Europe, Socioeconomic Factors, 030220 oncology & carcinogenesis, Erratum, business, Demography, Cohort study
Abstract

Research on mortality associated with exposure to the Holocaust is relevant for a better understanding of the effects of genocides on survivors. To our knowledge, previous studies have not investigated the long-term cause-specific mortality of Holocaust survivors. We compared mortality rates among Israelis born in European countries controlled by the Nazis during World War II with those among Israelis of European descent who did not have this exposure. Records of 22,671 people (45% women; 5,042 survivors) from the population-based Jerusalem Perinatal Study (1964–1976) were linked to the Israeli Population Registry, which was updated through 2016. Cox models were used for analysis, with 2-sided tests of statistical significance. Risk of all-cause mortality was higher among exposed women (hazard ratio (HR) = 1.15, 95% confidence interval (CI): 1.05, 1.27) than in unexposed women. No association was found between Holocaust exposure and male all-cause mortality. In both sexes, survivors had higher cancer-specific mortality (HR = 1.17 (95% CI: 1.01, 1.35) in women and HR = 1.14 (95% CI: 1.01, 1.28) in men). Exposed men also had excess mortality due to coronary heart disease (HR = 1.39, 95% CI: 1.09, 1.77) and lower mortality from other known causes combined (HR = 0.86, 95% CI: 0.75, 0.99). In summary, experiencing the Holocaust was associated with excess all-cause and cancer-specific mortality in women and cancer- and coronary heart disease–specific mortality in men.

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