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1. SARS-CoV-2-Associated Multisystem Inflammatory Syndrome in Children (MIS-C): A Case Report from Iraq.

Author

Al-Simaani RBY, Al-Kzayer LFY, Ali KH, Al-Ani MH, and Nakazawa Y

Abstract

The novel coronavirus disease (COVID-19) continues to evolve. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-associated multisystem inflammatory syndrome in children (MIS-C) is a rare post-COVID-19 complication that affects children with critical outcomes. Few MIS-C reports were available from Arab-Asian ethnicities. We here describe a presentation mimicking a head injury overlapping the manifestations of MIS-C in a child from Iraq. A 10-year-old boy presented with blunt trauma in a shock-like status, and a head injury was suspected. Since he was febrile two days before the trauma, another pathology was assumed. Imaging and laboratory evaluations were performed, and after excluding gross neurosurgical etiology, he was initially treated as a toxic shock syndrome. Meanwhile, he was deteriorating with continuous fever, impaired consciousness, and seizure on the following day. Although not considered initially, close monitoring with a multidisciplinary approach and serial investigations revealed that the child met the criteria of MIS-C. SARS-CoV-2 IgG was shown to be high, while the RT-PCR of COVID-19 was negative. Once he received immunoglobulin and methylprednisolone, he improved dramatically. In conclusion, this report aimed to increase awareness about MIS-C among health workers and emphasized the need for a multidisciplinary team approach in Iraq due to the importance of timely treatment.

Published
2023
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2. The Global Retinoblastoma Outcome Study: a prospective, cluster-based analysis of 4064 patients from 149 countries

Author

Alia, DB, Tandili, A, Paiva, L, Wime, AD, Chantada, GL, Fandino, AC, Sgroi, M, Papyan, R, Tamamyan, G, Camuglia, JE, Gole, GA, Clark, A, Lam, GC, Elder, JE, McKenzie, JD, Staffieri, SE, Jones, MM, Manudhane, R, Sia, D, Ritter-Sovinz, P, Schwab, C, Balayeva, R, Khan, Z, Nuruddin, M, Roy, SR, Rashid, R, Sultana, S, Shakoor, SA, Naumenko, L, Zhilyaeva, K, Bartoszek, P, Brichard, BG, De Potter, P, Bio, AIA, Salas, B, Coleoni Suarez, ME, Mbumba, FB, Bonanomi, MTBC, Donato Macedo, CR, Grigorovski, NDAK, Mattosinho, CCDS, Teixeira, LF, Oscar, AH, Veleva-Krasteva, NV, Bouda, GC, Kabore, RL, Philbert, R, Evina, TGA, Nkumbe, HE, Kamsang, P, Muyen, OM, Dimaras, H, Mallipatna, A, Hamel, P, Superstein, R, Paton, KE, Strahlendorf, C, Palet, JEKK, Tyau-Tyau, H, Cavieres, I, Lopez, JP, Oporto, J, Ossandon, D, Chen, W, Xiang, D, Du, Y, Li, K, Ji, X, Tang, J, Li, C, Xu, B, Qian, J, Xue, K, Sun, X, Wang, Y-Z, Zhang, Y, Wu, S-Q, Xiao, Y, Yang, H, Ye, H, Polania, RA, Berete, RC, Couitchere, L, Peric, S, Alemany-Rubio, E, Gonzalez-Rodriguez, L, Autrata, R, Kepak, T, Pochop, P, Svojgr, K, Gregersen, PA, Urbak, SF, Montero, MM, Budiongo, A, Yanga, JM, Amani, TBK, Lukamba, RM, Numbi, MN, Calle Jara, DA, Villacis Chafla, EG, Sanchez, GL, Abouelnaga, S, Afifi, MA, Elhaddad, AM, Ali, AM, Elzembely, M, Said, AMA, Ziko, OAO, Fuentes-Alabi, SL, Goenz, MA, Eerme, K, Klett, A, Hordofa, DF, Mengesha, AA, Sherief, ST, Kivela, TT, Nummi, K, Cassoux, N, Desjardins, L, Obono-Obiang, G, Kardava, T, Khotenashvili, Z, Bechrakis, NE, Biewald, EM, Schlueter, S, Ketteler, P, Amankwaa-Frempong, D, Essuman, VA, Paintsil, V, Renner, LA, Alejos, A, Giron, A, Carreras, YA, Fu, LD, Maldonado, C, Wong, ES, Yam, JC, Csoka, M, Maka, E, Aggarwal, P, Gupta, V, Bhaduri, A, Bhattacharyya, A, Das, A, Chawla, B, Das, P, Das, S, Gupta, H, Gupta, S, Verma, N, Kaliki, S, Khetan, V, Maitra, P, Mahajan, A, Menon, V, Mishra, DKC, Palanivelu, MS, Ramanjulu, R, Mudaliar, SS, Nair, AG, Natarajan, S, Seth, R, Singh, U, Bhat, S, Dudeja, G, Tripathy, D, Akib, IMNR, Pagarra, H, Amiruddin, PO, Kuntorini, MW, Armytasari, I, Supriyadi, E, Sutyawan, IWE, Yuliawati, P, Lutfi, D, Soebagjo, HD, Rahman, A, Sitorus, RS, Victor, AA, Tehuteru, ES, Widiarti, W, Nency, YM, Faranoush, M, Mehrvar, A, Tashvighi, M, Sedaghat, A, Ghassemi, F, Khodabande, A, Abdulqader, RA, Al-Shaheen, AASM, Al Ani, MH, Haydar, H, Al-Badri, SAF, Al-Jadiry, MF, Sabhan, AH, Al-Jumaily, U, Al-Mafrachi, AARM, Al-Shammary, EH, Al-Janabi, ANH, Qadir, AO, Capra, M, Blum, S, Gomel, N, Fabian, ID, Goldberg, H, Kapelushnik, N, Madgar, S, Vishnevskia-Dai, V, Frenkel, S, Pe'er, J, Gorfine, M, Refaeli, D, Steinberg, DM, Lavy, Y, Toledano, H, Caspi, S, De Francesco, S, Hadjistilianou, T, Ida, R, Valente, P, Midena, E, Parrozzani, R, Cowan-Lyn, KE, Vaughan, LO, Suzuki, S, Mohammad, MT, Yousef, YA, Manzhuova, L, Atsiaya, R, Matende, IO, Begimkulova, AS, Makimbetov, EK, Keomisy, J, Sayalith, P, Valeina, S, Viksnins, M, Al-Haddad, CE, Saab, RH, Alsawidi, KM, Elbahi, AM, Krivaitiene, D, Tateshi, B, Randrianarisoa, HL, Raobela, L, Msukwa, G, Nyirenda, C, Hamzah, N, Teh, KH, Sylla, F, Traore, F, Cheikh, SS, Zein, E, Perez, GG, Sanchez Orozco, AJ, Ortega-Hernandez, M, Ramirez-Ortiz, MA, Chuluunbat, T, Abdallah, E, Benmiloud, S, El Kettani, A, Hessissen, L, Almeida, AA, Limbu, B, Rajkarnikar, P, Saiju, R, Moll, AC, Wijsard, MVH, Cockcroft, RL, Ng, Y, Dodgshun, AJ, Calderon-Sotelo, P, Abdullahi, SU, Hassan, S, Umar, AB, Abdulrahaman, AA, Wali, AH, Ademola-Popoola, DS, Adio, A, Aghaji, AE, Ezegwui, IR, Akinsete, A, Musa, KO, Fasina, O, Ibanga, A, Nkanga, ED, Mustapha, T, Ribadu, D, Hummelen, M, Ahmad, A, Mushtaq, A, Qayyum, S, Chaudhry, S, Fadoo, Z, Jeeva, I, Masud, S, Hamid, SA, Zia, N, Siddiqui, SN, Janjua, T, Yaqub, MA, Khaqan, HA, Quintero D, K, Yee, R, Jairaj, V, Cano, MR, Fernandez, DDPG, Diaz Coronado, RY, Zapata Lopez, AM, Garcia, JL, Ponce, J, Garcia Pacheco, HN, Pascual Morales, CR, Vasquez Anchaya, JK, Tarrillo Leiva, FF, Alcasabas, APA, Mercado, GJ, Cieslik, K, Hautz, W, Rogowska, A, Castela, G, Silva, S, Jo, DH, Kim, JH, Comsa, C, Dragomir, MD, Neroev, V, Saakyan, S, Polyakov, V, Ushakova, TL, Yarovaya, VA, Yarovoy, AA, Theophile, T, Al Mesfer, S, Maktabi, A, Al-Dahmash, SA, Alkatan, HM, Moreira, C, Roth, PAN, Ilic, VR, Nikitovic, M, Latinovic, S, Quah, B, Tan, D, Hederova, S, Husakova, K, Groznik, AL, Pompe, MT, Davidson, A, Du Bruyn, M, Du Plessis, J, Stones, DK, Geel, JA, Myezo, KH, Kruger, M, Mayet, I, Naidu, G, Naidu, N, Mustak, H, Reynders, D, Wetter, J, Alarcon Portabella, S, Martin-Begue, N, Wolley Dod, C, Balaguer, J, Barranco, H, Catala-Mora, J, Correa Llano, MG, Fernandez-Teijeiro, A, Garcia Aldana, D, Peralta Calvo, J, San Roman Pacheco, S, Gunasekera, DS, Elhassan, MMA, Mohamedani, AA, All-Eriksson, C, Bartuma, K, Popovic, MB, Munier, FL, Liu, C-H, Chiwanga, FS, Kyara, A, Mndeme, FG, Msina, MS, Scanlan, TA, Atchaneeyasakul, L-O, Buaboonnam, J, Dangboon, W, Singha, P, Hongeng, S, Kulvichit, K, Rojanaporn, D, Surukrattanaskul, S, Wangtiraumnuay, N, Wiwatwongwana, A, Wiwatwongwana, D, Wongwai, P, Sharma, MK, Guedenon, KM, Bouguila, H, Atalay, HT, Hasanreisoglu, M, Ataseven, E, Kantar, M, Gunduz, AK, Kebudi, R, Kiratli, H, Koc, I, Tuncer, S, Unal, E, Kalinaki, A, Matua, M, Waddell, K, Musika, AA, Ssali, G, Al Harby, L, Reddy, MA, Astbury, NJ, Bascaran, C, Bowman, R, Burton, MJ, Foster, A, Zondervan, M, Sagoo, MS, Bobrova, N, Sorochynska, T, Lysytsia, L, Castillo, L, Afshar, AR, Berry, JL, Kim, JW, Randhawa, JK, Binkley, E, Boldt, HC, Larson, SA, Brennan, RC, Chandramohan, A, Stacey, AW, Corson, TW, Plager, DA, Davanzo, JM, Singh, AD, Demirci, H, Ericksen, C, Magrath, GN, Gold, AS, Murray, TG, Gonzalez, E, Shah, AS, Hansen, ED, Hartnett, ME, Harbour, JW, Hubbard, GB, Uner, OE, Laurenti, KD, Mets, MB, Leverant, AA, Ramasubramanian, A, Luna-Fineman, S, Miller, A, Skalet, AH, Mruthyunjaya, P, Hassan, M, Oliver, SC, Shields, CL, Yaghy, A, Stahl, ED, Wilson, MW, Villegas, VM, Islamov, Z, Usmanov, RH, Graells, J, Romero, L, Pham, CTM, Trang, DL, Al-Hussaini, HH, Thawaba, ADM, Muma, KIM, Nyaywa, M, Alia, DB, Tandili, A, Paiva, L, Wime, AD, Chantada, GL, Fandino, AC, Sgroi, M, Papyan, R, Tamamyan, G, Camuglia, JE, Gole, GA, Clark, A, Lam, GC, Elder, JE, McKenzie, JD, Staffieri, SE, Jones, MM, Manudhane, R, Sia, D, Ritter-Sovinz, P, Schwab, C, Balayeva, R, Khan, Z, Nuruddin, M, Roy, SR, Rashid, R, Sultana, S, Shakoor, SA, Naumenko, L, Zhilyaeva, K, Bartoszek, P, Brichard, BG, De Potter, P, Bio, AIA, Salas, B, Coleoni Suarez, ME, Mbumba, FB, Bonanomi, MTBC, Donato Macedo, CR, Grigorovski, NDAK, Mattosinho, CCDS, Teixeira, LF, Oscar, AH, Veleva-Krasteva, NV, Bouda, GC, Kabore, RL, Philbert, R, Evina, TGA, Nkumbe, HE, Kamsang, P, Muyen, OM, Dimaras, H, Mallipatna, A, Hamel, P, Superstein, R, Paton, KE, Strahlendorf, C, Palet, JEKK, Tyau-Tyau, H, Cavieres, I, Lopez, JP, Oporto, J, Ossandon, D, Chen, W, Xiang, D, Du, Y, Li, K, Ji, X, Tang, J, Li, C, Xu, B, Qian, J, Xue, K, Sun, X, Wang, Y-Z, Zhang, Y, Wu, S-Q, Xiao, Y, Yang, H, Ye, H, Polania, RA, Berete, RC, Couitchere, L, Peric, S, Alemany-Rubio, E, Gonzalez-Rodriguez, L, Autrata, R, Kepak, T, Pochop, P, Svojgr, K, Gregersen, PA, Urbak, SF, Montero, MM, Budiongo, A, Yanga, JM, Amani, TBK, Lukamba, RM, Numbi, MN, Calle Jara, DA, Villacis Chafla, EG, Sanchez, GL, Abouelnaga, S, Afifi, MA, Elhaddad, AM, Ali, AM, Elzembely, M, Said, AMA, Ziko, OAO, Fuentes-Alabi, SL, Goenz, MA, Eerme, K, Klett, A, Hordofa, DF, Mengesha, AA, Sherief, ST, Kivela, TT, Nummi, K, Cassoux, N, Desjardins, L, Obono-Obiang, G, Kardava, T, Khotenashvili, Z, Bechrakis, NE, Biewald, EM, Schlueter, S, Ketteler, P, Amankwaa-Frempong, D, Essuman, VA, Paintsil, V, Renner, LA, Alejos, A, Giron, A, Carreras, YA, Fu, LD, Maldonado, C, Wong, ES, Yam, JC, Csoka, M, Maka, E, Aggarwal, P, Gupta, V, Bhaduri, A, Bhattacharyya, A, Das, A, Chawla, B, Das, P, Das, S, Gupta, H, Gupta, S, Verma, N, Kaliki, S, Khetan, V, Maitra, P, Mahajan, A, Menon, V, Mishra, DKC, Palanivelu, MS, Ramanjulu, R, Mudaliar, SS, Nair, AG, Natarajan, S, Seth, R, Singh, U, Bhat, S, Dudeja, G, Tripathy, D, Akib, IMNR, Pagarra, H, Amiruddin, PO, Kuntorini, MW, Armytasari, I, Supriyadi, E, Sutyawan, IWE, Yuliawati, P, Lutfi, D, Soebagjo, HD, Rahman, A, Sitorus, RS, Victor, AA, Tehuteru, ES, Widiarti, W, Nency, YM, Faranoush, M, Mehrvar, A, Tashvighi, M, Sedaghat, A, Ghassemi, F, Khodabande, A, Abdulqader, RA, Al-Shaheen, AASM, Al Ani, MH, Haydar, H, Al-Badri, SAF, Al-Jadiry, MF, Sabhan, AH, Al-Jumaily, U, Al-Mafrachi, AARM, Al-Shammary, EH, Al-Janabi, ANH, Qadir, AO, Capra, M, Blum, S, Gomel, N, Fabian, ID, Goldberg, H, Kapelushnik, N, Madgar, S, Vishnevskia-Dai, V, Frenkel, S, Pe'er, J, Gorfine, M, Refaeli, D, Steinberg, DM, Lavy, Y, Toledano, H, Caspi, S, De Francesco, S, Hadjistilianou, T, Ida, R, Valente, P, Midena, E, Parrozzani, R, Cowan-Lyn, KE, Vaughan, LO, Suzuki, S, Mohammad, MT, Yousef, YA, Manzhuova, L, Atsiaya, R, Matende, IO, Begimkulova, AS, Makimbetov, EK, Keomisy, J, Sayalith, P, Valeina, S, Viksnins, M, Al-Haddad, CE, Saab, RH, Alsawidi, KM, Elbahi, AM, Krivaitiene, D, Tateshi, B, Randrianarisoa, HL, Raobela, L, Msukwa, G, Nyirenda, C, Hamzah, N, Teh, KH, Sylla, F, Traore, F, Cheikh, SS, Zein, E, Perez, GG, Sanchez Orozco, AJ, Ortega-Hernandez, M, Ramirez-Ortiz, MA, Chuluunbat, T, Abdallah, E, Benmiloud, S, El Kettani, A, Hessissen, L, Almeida, AA, Limbu, B, Rajkarnikar, P, Saiju, R, Moll, AC, Wijsard, MVH, Cockcroft, RL, Ng, Y, Dodgshun, AJ, Calderon-Sotelo, P, Abdullahi, SU, Hassan, S, Umar, AB, Abdulrahaman, AA, Wali, AH, Ademola-Popoola, DS, Adio, A, Aghaji, AE, Ezegwui, IR, Akinsete, A, Musa, KO, Fasina, O, Ibanga, A, Nkanga, ED, Mustapha, T, Ribadu, D, Hummelen, M, Ahmad, A, Mushtaq, A, Qayyum, S, Chaudhry, S, Fadoo, Z, Jeeva, I, Masud, S, Hamid, SA, Zia, N, Siddiqui, SN, Janjua, T, Yaqub, MA, Khaqan, HA, Quintero D, K, Yee, R, Jairaj, V, Cano, MR, Fernandez, DDPG, Diaz Coronado, RY, Zapata Lopez, AM, Garcia, JL, Ponce, J, Garcia Pacheco, HN, Pascual Morales, CR, Vasquez Anchaya, JK, Tarrillo Leiva, FF, Alcasabas, APA, Mercado, GJ, Cieslik, K, Hautz, W, Rogowska, A, Castela, G, Silva, S, Jo, DH, Kim, JH, Comsa, C, Dragomir, MD, Neroev, V, Saakyan, S, Polyakov, V, Ushakova, TL, Yarovaya, VA, Yarovoy, AA, Theophile, T, Al Mesfer, S, Maktabi, A, Al-Dahmash, SA, Alkatan, HM, Moreira, C, Roth, PAN, Ilic, VR, Nikitovic, M, Latinovic, S, Quah, B, Tan, D, Hederova, S, Husakova, K, Groznik, AL, Pompe, MT, Davidson, A, Du Bruyn, M, Du Plessis, J, Stones, DK, Geel, JA, Myezo, KH, Kruger, M, Mayet, I, Naidu, G, Naidu, N, Mustak, H, Reynders, D, Wetter, J, Alarcon Portabella, S, Martin-Begue, N, Wolley Dod, C, Balaguer, J, Barranco, H, Catala-Mora, J, Correa Llano, MG, Fernandez-Teijeiro, A, Garcia Aldana, D, Peralta Calvo, J, San Roman Pacheco, S, Gunasekera, DS, Elhassan, MMA, Mohamedani, AA, All-Eriksson, C, Bartuma, K, Popovic, MB, Munier, FL, Liu, C-H, Chiwanga, FS, Kyara, A, Mndeme, FG, Msina, MS, Scanlan, TA, Atchaneeyasakul, L-O, Buaboonnam, J, Dangboon, W, Singha, P, Hongeng, S, Kulvichit, K, Rojanaporn, D, Surukrattanaskul, S, Wangtiraumnuay, N, Wiwatwongwana, A, Wiwatwongwana, D, Wongwai, P, Sharma, MK, Guedenon, KM, Bouguila, H, Atalay, HT, Hasanreisoglu, M, Ataseven, E, Kantar, M, Gunduz, AK, Kebudi, R, Kiratli, H, Koc, I, Tuncer, S, Unal, E, Kalinaki, A, Matua, M, Waddell, K, Musika, AA, Ssali, G, Al Harby, L, Reddy, MA, Astbury, NJ, Bascaran, C, Bowman, R, Burton, MJ, Foster, A, Zondervan, M, Sagoo, MS, Bobrova, N, Sorochynska, T, Lysytsia, L, Castillo, L, Afshar, AR, Berry, JL, Kim, JW, Randhawa, JK, Binkley, E, Boldt, HC, Larson, SA, Brennan, RC, Chandramohan, A, Stacey, AW, Corson, TW, Plager, DA, Davanzo, JM, Singh, AD, Demirci, H, Ericksen, C, Magrath, GN, Gold, AS, Murray, TG, Gonzalez, E, Shah, AS, Hansen, ED, Hartnett, ME, Harbour, JW, Hubbard, GB, Uner, OE, Laurenti, KD, Mets, MB, Leverant, AA, Ramasubramanian, A, Luna-Fineman, S, Miller, A, Skalet, AH, Mruthyunjaya, P, Hassan, M, Oliver, SC, Shields, CL, Yaghy, A, Stahl, ED, Wilson, MW, Villegas, VM, Islamov, Z, Usmanov, RH, Graells, J, Romero, L, Pham, CTM, Trang, DL, Al-Hussaini, HH, Thawaba, ADM, Muma, KIM, and Nyaywa, M

Abstract

BACKGROUND: Retinoblastoma is the most common intraocular cancer worldwide. There is some evidence to suggest that major differences exist in treatment outcomes for children with retinoblastoma from different regions, but these differences have not been assessed on a global scale. We aimed to report 3-year outcomes for children with retinoblastoma globally and to investigate factors associated with survival. METHODS: We did a prospective cluster-based analysis of treatment-naive patients with retinoblastoma who were diagnosed between Jan 1, 2017, and Dec 31, 2017, then treated and followed up for 3 years. Patients were recruited from 260 specialised treatment centres worldwide. Data were obtained from participating centres on primary and additional treatments, duration of follow-up, metastasis, eye globe salvage, and survival outcome. We analysed time to death and time to enucleation with Cox regression models. FINDINGS: The cohort included 4064 children from 149 countries. The median age at diagnosis was 23·2 months (IQR 11·0-36·5). Extraocular tumour spread (cT4 of the cTNMH classification) at diagnosis was reported in five (0·8%) of 636 children from high-income countries, 55 (5·4%) of 1027 children from upper-middle-income countries, 342 (19·7%) of 1738 children from lower-middle-income countries, and 196 (42·9%) of 457 children from low-income countries. Enucleation surgery was available for all children and intravenous chemotherapy was available for 4014 (98·8%) of 4064 children. The 3-year survival rate was 99·5% (95% CI 98·8-100·0) for children from high-income countries, 91·2% (89·5-93·0) for children from upper-middle-income countries, 80·3% (78·3-82·3) for children from lower-middle-income countries, and 57·3% (52·1-63·0) for children from low-income countries. On analysis, independent factors for worse survival were residence in low-income countries compared to high-income countries (hazard ratio 16·67; 95% CI 4·76-50·00), cT4 advanced tumour compared to

Published
2022

3. Global Retinoblastoma Presentation and Analysis by National Income Level

Author

Fabian, ID, Abdallah, E, Abdullahi, SU, Abdulqader, RA, Boubacar, SA, Ademola-Popoola, DS, Adio, A, Afshar, AR, Aggarwal, P, Aghaji, AE, Ahmad, A, Akib, MNR, Al Harby, L, Al Ani, MH, Alakbarova, A, Portabella, SA, Al-Badri, SAF, Alcasabas, APA, Al-Dahmash, SA, Alejos, A, Alemany-Rubio, E, Bio, AIA, Carreras, YA, Al-Haddad, C, Al-Hussaini, HHY, Ali, AM, Alia, DB, Al-Jadiry, MF, Al-Jumaly, U, Alkatan, HM, All-Eriksson, C, Al-Mafrachi, AARM, Almeida, AA, Alsawidi, KM, Al-Shaheen, AASM, Al-Shammary, EH, Amiruddin, PO, Antonino, R, Astbury, NJ, Atalay, HT, Atchaneeyasakul, L-O, Atsiaya, R, Attaseth, T, Aung, TH, Ayala, S, Baizakova, B, Balaguer, J, Balayeva, R, Balwierz, W, Barranco, H, Bascaran, C, Popovic, MB, Benavides, R, Benmiloud, S, Guebessi, NB, Berete, RC, Berry, JL, Bhaduri, A, Bhat, S, Biddulph, SJ, Biewald, EM, Bobrova, N, Boehme, M, Boldt, HC, Bonanomi, MTBC, Bornfeld, N, Bouda, GC, Bouguila, H, Boumedane, A, Brennan, RC, Brichard, BG, Buaboonnam, J, Calderon-Sotelo, P, Calle Jara, DA, Camuglia, JE, Cano, MR, Capra, M, Cassoux, N, Castela, G, Castillo, L, Catala-Mora, J, Chantada, GL, Chaudhry, S, Chaugule, SS, Chauhan, A, Chawla, B, Chernodrinska, VS, Chiwanga, FS, Chuluunbat, T, Cieslik, K, Cockcroft, RL, Comsa, C, Correa, ZM, Correa Llano, MG, Corson, TW, Cowan-Lyn, KE, Csoka, M, Cui, X, Da Gama, I, Dangboon, W, Das, A, Das, S, Davanzo, JM, Davidson, A, De Potter, P, Delgado, KQ, Demirci, H, Desjardins, L, Diaz Coronado, RY, Dimaras, H, Dodgshun, AJ, Donaldson, C, Donato Macedo, CR, Dragomir, MD, Du, Y, Du Bruyn, M, Edison, KS, Sutyawan, IWE, El Kettani, A, Elbahi, AM, Elder, JE, Elgalaly, D, Elhaddad, AM, Elhassan, MMA, Elzembely, MM, Essuman, VA, Evina, TGA, Fadoo, Z, Fandino, AC, Faranoush, M, Fasina, O, Fernandez, DDPG, Fernandez-Teijeiro, A, Foster, A, Frenkel, S, Fu, LD, Fuentes-Alabi, SL, Gallie, BL, Gandiwa, M, Garcia, JL, Garcia Aldana, D, Gassant, PY, Geel, JA, Ghassemi, F, Giron, A, Gizachew, Z, Goenz, MA, Gold, AS, Goldberg-Lavid, M, Gole, GA, Gomel, N, Gonzalez, E, Gonzalez Perez, G, Gonzalez-Rodriguez, L, Garcia Pacheco, HN, Graells, J, Green, L, Gregersen, PA, Grigorovski, NDAK, Guedenon, KM, Gunasekera, DS, Gunduz, AK, Gupta, H, Gupta, S, Hadjistilianou, T, Hamel, P, Hamid, SA, Hamzah, N, Hansen, ED, Harbour, JW, Hartnett, ME, Hasanreisoglu, M, Hassan, S, Hederova, S, Hernandez, J, Carcamo Hernandez, LM, Hessissen, L, Hordofa, DF, Huang, LC, Hubbard, GB, Hummlen, M, Husakova, K, Al-Janabi, ANH, Ida, R, Ilic, VR, Jairaj, V, Jeeva, I, Jenkinson, H, Ji, X, Jo, DH, Johnson, KP, Johnson, WJ, Jones, MM, Kabesha, TBA, Kabore, RL, Kaliki, S, Kalinaki, A, Kantar, M, Kao, L-Y, Kardava, T, Kebudi, R, Kepak, T, Keren-Froim, N, Khan, ZJ, Khaqan, HA, Khauv, P, Kheir, WJ, Khetan, V, Khodabande, A, Khotenashvili, Z, Kim, JW, Kim, JH, Kiratli, H, Kivela, TT, Klett, A, Palet, JEKK, Krivaitiene, D, Kruger, M, Kulvichit, K, Kuntorini, MW, Kyara, A, Lachmann, ES, Lam, CPS, Lam, GC, Larson, SA, Latinovic, S, Laurenti, KD, Le, BHA, Lecuona, K, Leverant, AA, Li, C, Limbu, B, Quah, BL, Lopez, JP, Lukamba, RM, Lumbroso, L, Luna-Fineman, S, Lutfi, D, Lysytsia, L, Magrath, GN, Mahajan, A, Majeed, AR, Maka, E, Makan, M, Makimbetov, EK, Manda, C, Martin Begue, N, Mason, L, Mason, JO, Matende, IO, Materin, M, Mattosinho, CCDS, Matua, M, Mayet, I, Mbumba, FB, McKenzie, JD, Medina-Sanson, A, Mehrvar, A, Mengesha, AA, Menon, V, Mercado, GJVD, Mets, MB, Midena, E, Mishra, DKC, Mndeme, FG, Mohamedani, AA, Mohammad, MT, Moll, AC, Montero, MM, Morales, RA, Moreira, C, Mruthyunjaya, P, Msina, MS, Msukwa, G, Mudaliar, SS, Muma, K, Munier, FL, Murgoi, G, Murray, TG, Musa, KO, Mushtaq, A, Mustak, H, Muyen, OM, Naidu, G, Nair, AG, Naumenko, L, Roth, PAN, Nency, YM, Neroev, V, Ngo, H, Nieves, RM, Nikitovic, M, Nkanga, ED, Nkumbe, H, Nuruddin, M, Nyaywa, M, Obono-Obiang, G, Oguego, NC, Olechowski, A, Oliver, SCN, Osei-Bonsu, P, Ossandon, D, Paez-Escamilla, MA, Pagarra, H, Painter, SL, Paintsil, V, Paiva, L, Pal, BP, Palanivelu, MS, Papyan, R, Parrozzani, R, Parulekar, M, Morales, CRP, Paton, KE, Pawinska-Wasikowska, K, Pe'er, J, Pena, A, Peric, S, Pham, CTM, Philbert, R, Plager, DA, Pochop, P, Polania, RA, Polyakov, VG, Pompe, MT, Pons, JJ, Prat, D, Prom, V, Purwanto, I, Qadir, AO, Qayyum, S, Qian, J, Rahman, A, Rahman, S, Rahmat, J, Rajkarnikar, P, Ramanjulu, R, Ramasubramanian, A, Ramirez-Ortiz, MA, Raobela, L, Rashid, R, Reddy, MA, Reich, E, Renner, LA, Reynders, D, Ribadu, D, Riheia, MM, Ritter-Sovinz, P, Rojanaporn, D, Romero, L, Roy, SR, Saab, RH, Saakyan, S, Sabhan, AH, Sagoo, MS, Said, AMA, Saiju, R, Salas, B, San Roman Pacheco, S, Sanchez, GL, Sayalith, P, Scanlan, TA, Schefler, AC, Schoeman, J, Sedaghat, A, Seregard, S, Seth, R, Shah, AS, Shakoor, SA, Sharma, MK, Sherief, ST, Shetye, NG, Shields, CL, Siddiqui, SN, Cheikh, SS, Silva, S, Singh, AD, Singh, N, Singh, U, Singha, P, Sitorus, RS, Skalet, AH, Soebagjo, HD, Sorochynska, T, Ssali, G, Stacey, AW, Staffieri, SE, Stahl, ED, Stathopoulos, C, Kranjc, BS, Stones, DK, Strahlendorf, C, Suarez, MEC, Sultana, S, Sun, X, Sundy, M, Superstein, R, Supriyadi, E, Surukrattanaskul, S, Suzuki, S, Svojgr, K, Sylla, F, Tamamyan, G, Tan, D, Tandili, A, Tarrillo Leiva, FF, Tashvighi, M, Tateshi, B, Tehuteru, ES, Teixeira, LF, Teh, KH, Theophile, T, Toledano, H, Trang, DL, Traore, F, Trichaiyaporn, S, Tuncer, S, Tyau-Tyau, H, Umar, AB, Unal, E, Uner, OE, Urbak, SF, Ushakova, TL, Usmanov, RH, Valeina, S, Wijsard, MVH, Varadisai, A, Vasquez, L, Vaughan, LO, Veleva-Krasteva, NV, Verma, N, Victor, AA, Viksnins, M, Villacos Chafla, EG, Vishnevskia-Dai, V, Vora, T, Wachtel, AE, Wackernagel, W, Waddell, K, Wade, PD, Wali, AH, Wang, Y-Z, Weiss, A, Wilson, MW, Wime, ADC, Wiwatwongwana, A, Wiwatwongwana, D, Dod, CW, Wongwai, P, Xiang, D, Xiao, Y, Yam, JC, Yang, H, Yanga, JM, Yaqub, MA, Yarovaya, VA, Yarovoy, AA, Ye, H, Yousef, YA, Yuliawati, P, Zapata Lopez, AM, Zein, E, Zhang, C, Zhang, Y, Zhao, J, Zheng, X, Zhilyaeva, K, Zia, N, Ziko, OAO, Zondervan, M, Bowman, R, Fabian, ID, Abdallah, E, Abdullahi, SU, Abdulqader, RA, Boubacar, SA, Ademola-Popoola, DS, Adio, A, Afshar, AR, Aggarwal, P, Aghaji, AE, Ahmad, A, Akib, MNR, Al Harby, L, Al Ani, MH, Alakbarova, A, Portabella, SA, Al-Badri, SAF, Alcasabas, APA, Al-Dahmash, SA, Alejos, A, Alemany-Rubio, E, Bio, AIA, Carreras, YA, Al-Haddad, C, Al-Hussaini, HHY, Ali, AM, Alia, DB, Al-Jadiry, MF, Al-Jumaly, U, Alkatan, HM, All-Eriksson, C, Al-Mafrachi, AARM, Almeida, AA, Alsawidi, KM, Al-Shaheen, AASM, Al-Shammary, EH, Amiruddin, PO, Antonino, R, Astbury, NJ, Atalay, HT, Atchaneeyasakul, L-O, Atsiaya, R, Attaseth, T, Aung, TH, Ayala, S, Baizakova, B, Balaguer, J, Balayeva, R, Balwierz, W, Barranco, H, Bascaran, C, Popovic, MB, Benavides, R, Benmiloud, S, Guebessi, NB, Berete, RC, Berry, JL, Bhaduri, A, Bhat, S, Biddulph, SJ, Biewald, EM, Bobrova, N, Boehme, M, Boldt, HC, Bonanomi, MTBC, Bornfeld, N, Bouda, GC, Bouguila, H, Boumedane, A, Brennan, RC, Brichard, BG, Buaboonnam, J, Calderon-Sotelo, P, Calle Jara, DA, Camuglia, JE, Cano, MR, Capra, M, Cassoux, N, Castela, G, Castillo, L, Catala-Mora, J, Chantada, GL, Chaudhry, S, Chaugule, SS, Chauhan, A, Chawla, B, Chernodrinska, VS, Chiwanga, FS, Chuluunbat, T, Cieslik, K, Cockcroft, RL, Comsa, C, Correa, ZM, Correa Llano, MG, Corson, TW, Cowan-Lyn, KE, Csoka, M, Cui, X, Da Gama, I, Dangboon, W, Das, A, Das, S, Davanzo, JM, Davidson, A, De Potter, P, Delgado, KQ, Demirci, H, Desjardins, L, Diaz Coronado, RY, Dimaras, H, Dodgshun, AJ, Donaldson, C, Donato Macedo, CR, Dragomir, MD, Du, Y, Du Bruyn, M, Edison, KS, Sutyawan, IWE, El Kettani, A, Elbahi, AM, Elder, JE, Elgalaly, D, Elhaddad, AM, Elhassan, MMA, Elzembely, MM, Essuman, VA, Evina, TGA, Fadoo, Z, Fandino, AC, Faranoush, M, Fasina, O, Fernandez, DDPG, Fernandez-Teijeiro, A, Foster, A, Frenkel, S, Fu, LD, Fuentes-Alabi, SL, Gallie, BL, Gandiwa, M, Garcia, JL, Garcia Aldana, D, Gassant, PY, Geel, JA, Ghassemi, F, Giron, A, Gizachew, Z, Goenz, MA, Gold, AS, Goldberg-Lavid, M, Gole, GA, Gomel, N, Gonzalez, E, Gonzalez Perez, G, Gonzalez-Rodriguez, L, Garcia Pacheco, HN, Graells, J, Green, L, Gregersen, PA, Grigorovski, NDAK, Guedenon, KM, Gunasekera, DS, Gunduz, AK, Gupta, H, Gupta, S, Hadjistilianou, T, Hamel, P, Hamid, SA, Hamzah, N, Hansen, ED, Harbour, JW, Hartnett, ME, Hasanreisoglu, M, Hassan, S, Hederova, S, Hernandez, J, Carcamo Hernandez, LM, Hessissen, L, Hordofa, DF, Huang, LC, Hubbard, GB, Hummlen, M, Husakova, K, Al-Janabi, ANH, Ida, R, Ilic, VR, Jairaj, V, Jeeva, I, Jenkinson, H, Ji, X, Jo, DH, Johnson, KP, Johnson, WJ, Jones, MM, Kabesha, TBA, Kabore, RL, Kaliki, S, Kalinaki, A, Kantar, M, Kao, L-Y, Kardava, T, Kebudi, R, Kepak, T, Keren-Froim, N, Khan, ZJ, Khaqan, HA, Khauv, P, Kheir, WJ, Khetan, V, Khodabande, A, Khotenashvili, Z, Kim, JW, Kim, JH, Kiratli, H, Kivela, TT, Klett, A, Palet, JEKK, Krivaitiene, D, Kruger, M, Kulvichit, K, Kuntorini, MW, Kyara, A, Lachmann, ES, Lam, CPS, Lam, GC, Larson, SA, Latinovic, S, Laurenti, KD, Le, BHA, Lecuona, K, Leverant, AA, Li, C, Limbu, B, Quah, BL, Lopez, JP, Lukamba, RM, Lumbroso, L, Luna-Fineman, S, Lutfi, D, Lysytsia, L, Magrath, GN, Mahajan, A, Majeed, AR, Maka, E, Makan, M, Makimbetov, EK, Manda, C, Martin Begue, N, Mason, L, Mason, JO, Matende, IO, Materin, M, Mattosinho, CCDS, Matua, M, Mayet, I, Mbumba, FB, McKenzie, JD, Medina-Sanson, A, Mehrvar, A, Mengesha, AA, Menon, V, Mercado, GJVD, Mets, MB, Midena, E, Mishra, DKC, Mndeme, FG, Mohamedani, AA, Mohammad, MT, Moll, AC, Montero, MM, Morales, RA, Moreira, C, Mruthyunjaya, P, Msina, MS, Msukwa, G, Mudaliar, SS, Muma, K, Munier, FL, Murgoi, G, Murray, TG, Musa, KO, Mushtaq, A, Mustak, H, Muyen, OM, Naidu, G, Nair, AG, Naumenko, L, Roth, PAN, Nency, YM, Neroev, V, Ngo, H, Nieves, RM, Nikitovic, M, Nkanga, ED, Nkumbe, H, Nuruddin, M, Nyaywa, M, Obono-Obiang, G, Oguego, NC, Olechowski, A, Oliver, SCN, Osei-Bonsu, P, Ossandon, D, Paez-Escamilla, MA, Pagarra, H, Painter, SL, Paintsil, V, Paiva, L, Pal, BP, Palanivelu, MS, Papyan, R, Parrozzani, R, Parulekar, M, Morales, CRP, Paton, KE, Pawinska-Wasikowska, K, Pe'er, J, Pena, A, Peric, S, Pham, CTM, Philbert, R, Plager, DA, Pochop, P, Polania, RA, Polyakov, VG, Pompe, MT, Pons, JJ, Prat, D, Prom, V, Purwanto, I, Qadir, AO, Qayyum, S, Qian, J, Rahman, A, Rahman, S, Rahmat, J, Rajkarnikar, P, Ramanjulu, R, Ramasubramanian, A, Ramirez-Ortiz, MA, Raobela, L, Rashid, R, Reddy, MA, Reich, E, Renner, LA, Reynders, D, Ribadu, D, Riheia, MM, Ritter-Sovinz, P, Rojanaporn, D, Romero, L, Roy, SR, Saab, RH, Saakyan, S, Sabhan, AH, Sagoo, MS, Said, AMA, Saiju, R, Salas, B, San Roman Pacheco, S, Sanchez, GL, Sayalith, P, Scanlan, TA, Schefler, AC, Schoeman, J, Sedaghat, A, Seregard, S, Seth, R, Shah, AS, Shakoor, SA, Sharma, MK, Sherief, ST, Shetye, NG, Shields, CL, Siddiqui, SN, Cheikh, SS, Silva, S, Singh, AD, Singh, N, Singh, U, Singha, P, Sitorus, RS, Skalet, AH, Soebagjo, HD, Sorochynska, T, Ssali, G, Stacey, AW, Staffieri, SE, Stahl, ED, Stathopoulos, C, Kranjc, BS, Stones, DK, Strahlendorf, C, Suarez, MEC, Sultana, S, Sun, X, Sundy, M, Superstein, R, Supriyadi, E, Surukrattanaskul, S, Suzuki, S, Svojgr, K, Sylla, F, Tamamyan, G, Tan, D, Tandili, A, Tarrillo Leiva, FF, Tashvighi, M, Tateshi, B, Tehuteru, ES, Teixeira, LF, Teh, KH, Theophile, T, Toledano, H, Trang, DL, Traore, F, Trichaiyaporn, S, Tuncer, S, Tyau-Tyau, H, Umar, AB, Unal, E, Uner, OE, Urbak, SF, Ushakova, TL, Usmanov, RH, Valeina, S, Wijsard, MVH, Varadisai, A, Vasquez, L, Vaughan, LO, Veleva-Krasteva, NV, Verma, N, Victor, AA, Viksnins, M, Villacos Chafla, EG, Vishnevskia-Dai, V, Vora, T, Wachtel, AE, Wackernagel, W, Waddell, K, Wade, PD, Wali, AH, Wang, Y-Z, Weiss, A, Wilson, MW, Wime, ADC, Wiwatwongwana, A, Wiwatwongwana, D, Dod, CW, Wongwai, P, Xiang, D, Xiao, Y, Yam, JC, Yang, H, Yanga, JM, Yaqub, MA, Yarovaya, VA, Yarovoy, AA, Ye, H, Yousef, YA, Yuliawati, P, Zapata Lopez, AM, Zein, E, Zhang, C, Zhang, Y, Zhao, J, Zheng, X, Zhilyaeva, K, Zia, N, Ziko, OAO, Zondervan, M, and Bowman, R

Abstract

IMPORTANCE: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale. OBJECTIVES: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis. DESIGN, SETTING, AND PARTICIPANTS: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017. MAIN OUTCOMES AND MEASURES: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis. RESULTS: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis

Published
2020

4. Impact of the coronavirus disease 2019 (COVID-19) pandemic on pediatric oncology care in the Middle East, North Africa, and West Asia region: A report from the Pediatric Oncology East and Mediterranean (POEM) group.

Author

Saab R, Obeid A, Gachi F, Boudiaf H, Sargsyan L, Al-Saad K, Javakhadze T, Mehrvar A, Abbas SS, Abed Al-Agele YS, Al-Haddad S, Al Ani MH, Al-Sweedan S, Al Kofide A, Jastaniah W, Khalifa N, Bechara E, Baassiri M, Noun P, El-Houdzi J, Khattab M, Sagar Sharma K, Wali Y, Mushtaq N, Batool A, Faizan M, Raza MR, Najajreh M, Mohammed Abdallah MA, Sousan G, Ghanem KM, Kocak U, Kutluk T, Demir HA, Hodeish H, Muwakkit S, Belgaumi A, Al-Rawas AH, and Jeha S

Subjects
Africa, Northern epidemiology, Asia, Western epidemiology, Child, Cross-Sectional Studies, Delivery of Health Care, Health Personnel organization & administration, Health Personnel statistics & numerical data, Hospitals statistics & numerical data, Humans, Middle East epidemiology, Surveys and Questionnaires, COVID-19 epidemiology, Neoplasms therapy
Abstract

Background: Childhood cancer is a highly curable disease when timely diagnosis and appropriate therapy are provided. A negative impact of the coronavirus disease 2019 (COVID-19) pandemic on access to care for children with cancer is likely but has not been evaluated., Methods: A 34-item survey focusing on barriers to pediatric oncology management during the COVID-19 pandemic was distributed to heads of pediatric oncology units within the Pediatric Oncology East and Mediterranean (POEM) collaborative group, from the Middle East, North Africa, and West Asia. Responses were collected on April 11 through 22, 2020. Corresponding rates of proven COVID-19 cases and deaths were retrieved from the World Health Organization database., Results: In total, 34 centers from 19 countries participated. Almost all centers applied guidelines to optimize resource utilization and safety, including delaying off-treatment visits, rotating and reducing staff, and implementing social distancing, hand hygiene measures, and personal protective equipment use. Essential treatments, including chemotherapy, surgery, and radiation therapy, were delayed in 29% to 44% of centers, and 24% of centers restricted acceptance of new patients. Clinical care delivery was reported as negatively affected in 28% of centers. Greater than 70% of centers reported shortages in blood products, and 47% to 62% reported interruptions in surgery and radiation as well as medication shortages. However, bed availability was affected in <30% of centers, reflecting the low rates of COVID-19 hospitalizations in the corresponding countries at the time of the survey., Conclusions: Mechanisms to approach childhood cancer treatment delivery during crises need to be re-evaluated, because treatment interruptions and delays are expected to affect patient outcomes in this otherwise largely curable disease., (© 2020 American Cancer Society.)

Published
2020
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5. Global Retinoblastoma Presentation and Analysis by National Income Level.

Author

Fabian ID, Abdallah E, Abdullahi SU, Abdulqader RA, Adamou Boubacar S, Ademola-Popoola DS, Adio A, Afshar AR, Aggarwal P, Aghaji AE, Ahmad A, Akib MNR, Al Harby L, Al Ani MH, Alakbarova A, Portabella SA, Al-Badri SAF, Alcasabas APA, Al-Dahmash SA, Alejos A, Alemany-Rubio E, Alfa Bio AI, Alfonso Carreras Y, Al-Haddad C, Al-Hussaini HHY, Ali AM, Alia DB, Al-Jadiry MF, Al-Jumaily U, Alkatan HM, All-Eriksson C, Al-Mafrachi AARM, Almeida AA, Alsawidi KM, Al-Shaheen AASM, Al-Shammary EH, Amiruddin PO, Antonino R, Astbury NJ, Atalay HT, Atchaneeyasakul LO, Atsiaya R, Attaseth T, Aung TH, Ayala S, Baizakova B, Balaguer J, Balayeva R, Balwierz W, Barranco H, Bascaran C, Beck Popovic M, Benavides R, Benmiloud S, Bennani Guebessi N, Berete RC, Berry JL, Bhaduri A, Bhat S, Biddulph SJ, Biewald EM, Bobrova N, Boehme M, Boldt HC, Bonanomi MTBC, Bornfeld N, Bouda GC, Bouguila H, Boumedane A, Brennan RC, Brichard BG, Buaboonnam J, Calderón-Sotelo P, Calle Jara DA, Camuglia JE, Cano MR, Capra M, Cassoux N, Castela G, Castillo L, Català-Mora J, Chantada GL, Chaudhry S, Chaugule SS, Chauhan A, Chawla B, Chernodrinska VS, Chiwanga FS, Chuluunbat T, Cieslik K, Cockcroft RL, Comsa C, Correa ZM, Correa Llano MG, Corson TW, Cowan-Lyn KE, Csóka M, Cui X, Da Gama IV, Dangboon W, Das A, Das S, Davanzo JM, Davidson A, De Potter P, Delgado KQ, Demirci H, Desjardins L, Diaz Coronado RY, Dimaras H, Dodgshun AJ, Donaldson C, Donato Macedo CR, Dragomir MD, Du Y, Du Bruyn M, Edison KS, Eka Sutyawan IW, El Kettani A, Elbahi AM, Elder JE, Elgalaly D, Elhaddad AM, Elhassan MMA, Elzembely MM, Essuman VA, Evina TGA, Fadoo Z, Fandiño AC, Faranoush M, Fasina O, Fernández DDPG, Fernández-Teijeiro A, Foster A, Frenkel S, Fu LD, Fuentes-Alabi SL, Gallie BL, Gandiwa M, Garcia JL, García Aldana D, Gassant PY, Geel JA, Ghassemi F, Girón AV, Gizachew Z, Goenz MA, Gold AS, Goldberg-Lavid M, Gole GA, Gomel N, Gonzalez E, Gonzalez Perez G, González-Rodríguez L, Garcia Pacheco HN, Graells J, Green L, Gregersen PA, Grigorovski NDAK, Guedenon KM, Gunasekera DS, Gündüz AK, Gupta H, Gupta S, Hadjistilianou T, Hamel P, Hamid SA, Hamzah N, Hansen ED, Harbour JW, Hartnett ME, Hasanreisoglu M, Hassan S, Hassan S, Hederova S, Hernandez J, Hernandez LMC, Hessissen L, Hordofa DF, Huang LC, Hubbard GB, Hummlen M, Husakova K, Hussein Al-Janabi AN, Ida R, Ilic VR, Jairaj V, Jeeva I, Jenkinson H, Ji X, Jo DH, Johnson KP, Johnson WJ, Jones MM, Kabesha TBA, Kabore RL, Kaliki S, Kalinaki A, Kantar M, Kao LY, Kardava T, Kebudi R, Kepak T, Keren-Froim N, Khan ZJ, Khaqan HA, Khauv P, Kheir WJ, Khetan V, Khodabande A, Khotenashvili Z, Kim JW, Kim JH, Kiratli H, Kivelä TT, Klett A, Komba Palet JEK, Krivaitiene D, Kruger M, Kulvichit K, Kuntorini MW, Kyara A, Lachmann ES, Lam CPS, Lam GC, Larson SA, Latinovic S, Laurenti KD, Le BHA, Lecuona K, Leverant AA, Li C, Limbu B, Long QB, López JP, Lukamba RM, Lumbroso L, Luna-Fineman S, Lutfi D, Lysytsia L, Magrath GN, Mahajan A, Majeed AR, Maka E, Makan M, Makimbetov EK, Manda C, Martín Begue N, Mason L, Mason JO 3rd, Matende IO, Materin M, Mattosinho CCDS, Matua M, Mayet I, Mbumba FB, McKenzie JD, Medina-Sanson A, Mehrvar A, Mengesha AA, Menon V, Mercado GJVD, Mets MB, Midena E, Mishra DKC, Mndeme FG, Mohamedani AA, Mohammad MT, Moll AC, Montero MM, Morales RA, Moreira C, Mruthyunjaya P, Msina MS, Msukwa G, Mudaliar SS, Muma KI, Munier FL, Murgoi G, Murray TG, Musa KO, Mushtaq A, Mustak H, Muyen OM, Naidu G, Nair AG, Naumenko L, Ndoye Roth PA, Nency YM, Neroev V, Ngo H, Nieves RM, Nikitovic M, Nkanga ED, Nkumbe H, Nuruddin M, Nyaywa M, Obono-Obiang G, Oguego NC, Olechowski A, Oliver SCN, Osei-Bonsu P, Ossandon D, Paez-Escamilla MA, Pagarra H, Painter SL, Paintsil V, Paiva L, Pal BP, Palanivelu MS, Papyan R, Parrozzani R, Parulekar M, Pascual Morales CR, Paton KE, Pawinska-Wasikowska K, Pe'er J, Peña A, Peric S, Pham CTM, Philbert R, Plager DA, Pochop P, Polania RA, Polyakov VG, Pompe MT, Pons JJ, Prat D, Prom V, Purwanto I, Qadir AO, Qayyum S, Qian J, Rahman A, Rahman S, Rahmat J, Rajkarnikar P, Ramanjulu R, Ramasubramanian A, Ramirez-Ortiz MA, Raobela L, Rashid R, Reddy MA, Reich E, Renner LA, Reynders D, Ribadu D, Riheia MM, Ritter-Sovinz P, Rojanaporn D, Romero L, Roy SR, Saab RH, Saakyan S, Sabhan AH, Sagoo MS, Said AMA, Saiju R, Salas B, San Román Pacheco S, Sánchez GL, Sayalith P, Scanlan TA, Schefler AC, Schoeman J, Sedaghat A, Seregard S, Seth R, Shah AS, Shakoor SA, Sharma MK, Sherief ST, Shetye NG, Shields CL, Siddiqui SN, Sidi Cheikh S, Silva S, Singh AD, Singh N, Singh U, Singha P, Sitorus RS, Skalet AH, Soebagjo HD, Sorochynska T, Ssali G, Stacey AW, Staffieri SE, Stahl ED, Stathopoulos C, Stirn Kranjc B, Stones DK, Strahlendorf C, Suarez MEC, Sultana S, Sun X, Sundy M, Superstein R, Supriyadi E, Surukrattanaskul S, Suzuki S, Svojgr K, Sylla F, Tamamyan G, Tan D, Tandili A, Tarrillo Leiva FF, Tashvighi M, Tateshi B, Tehuteru ES, Teixeira LF, Teh KH, Theophile T, Toledano H, Trang DL, Traoré F, Trichaiyaporn S, Tuncer S, Tyau-Tyau H, Umar AB, Unal E, Uner OE, Urbak SF, Ushakova TL, Usmanov RH, Valeina S, van Hoefen Wijsard M, Varadisai A, Vasquez L, Vaughan LO, Veleva-Krasteva NV, Verma N, Victor AA, Viksnins M, Villacís Chafla EG, Vishnevskia-Dai V, Vora T, Wachtel AE, Wackernagel W, Waddell K, Wade PD, Wali AH, Wang YZ, Weiss A, Wilson MW, Wime ADC, Wiwatwongwana A, Wiwatwongwana D, Wolley Dod C, Wongwai P, Xiang D, Xiao Y, Yam JC, Yang H, Yanga JM, Yaqub MA, Yarovaya VA, Yarovoy AA, Ye H, Yousef YA, Yuliawati P, Zapata López AM, Zein E, Zhang C, Zhang Y, Zhao J, Zheng X, Zhilyaeva K, Zia N, Ziko OAO, Zondervan M, and Bowman R

Subjects
Child, Preschool, Female, Humans, Infant, Male, Retinoblastoma economics, Retinoblastoma epidemiology
Abstract

Importance: Early diagnosis of retinoblastoma, the most common intraocular cancer, can save both a child's life and vision. However, anecdotal evidence suggests that many children across the world are diagnosed late. To our knowledge, the clinical presentation of retinoblastoma has never been assessed on a global scale., Objectives: To report the retinoblastoma stage at diagnosis in patients across the world during a single year, to investigate associations between clinical variables and national income level, and to investigate risk factors for advanced disease at diagnosis., Design, Setting, and Participants: A total of 278 retinoblastoma treatment centers were recruited from June 2017 through December 2018 to participate in a cross-sectional analysis of treatment-naive patients with retinoblastoma who were diagnosed in 2017., Main Outcomes and Measures: Age at presentation, proportion of familial history of retinoblastoma, and tumor stage and metastasis., Results: The cohort included 4351 new patients from 153 countries; the median age at diagnosis was 30.5 (interquartile range, 18.3-45.9) months, and 1976 patients (45.4%) were female. Most patients (n = 3685 [84.7%]) were from low- and middle-income countries (LMICs). Globally, the most common indication for referral was leukocoria (n = 2638 [62.8%]), followed by strabismus (n = 429 [10.2%]) and proptosis (n = 309 [7.4%]). Patients from high-income countries (HICs) were diagnosed at a median age of 14.1 months, with 656 of 666 (98.5%) patients having intraocular retinoblastoma and 2 (0.3%) having metastasis. Patients from low-income countries were diagnosed at a median age of 30.5 months, with 256 of 521 (49.1%) having extraocular retinoblastoma and 94 of 498 (18.9%) having metastasis. Lower national income level was associated with older presentation age, higher proportion of locally advanced disease and distant metastasis, and smaller proportion of familial history of retinoblastoma. Advanced disease at diagnosis was more common in LMICs even after adjusting for age (odds ratio for low-income countries vs upper-middle-income countries and HICs, 17.92 [95% CI, 12.94-24.80], and for lower-middle-income countries vs upper-middle-income countries and HICs, 5.74 [95% CI, 4.30-7.68])., Conclusions and Relevance: This study is estimated to have included more than half of all new retinoblastoma cases worldwide in 2017. Children from LMICs, where the main global retinoblastoma burden lies, presented at an older age with more advanced disease and demonstrated a smaller proportion of familial history of retinoblastoma, likely because many do not reach a childbearing age. Given that retinoblastoma is curable, these data are concerning and mandate intervention at national and international levels. Further studies are needed to investigate factors, other than age at presentation, that may be associated with advanced disease in LMICs.

Published
2020
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6. Extraction Planning in Orthodontics.

Author

Al-Ani MH and Mageet AO

Subjects
Esthetics, Dental, Humans, Malocclusion surgery, Oral Hygiene, Time Factors, Tooth, Supernumerary surgery, Treatment Outcome, Orthodontics methods, Patient Care Planning, Practice Guidelines as Topic, Tooth Extraction methods
Abstract

Introduction: Planning extraction of teeth for orthodontic treatment is one of the challenging factors for successful functional and esthetic orthodontic results and for the long-term stability., Aim: The aim of this study is to document possible extraction guidelines for planning of orthodontic treatment for space deficiency cases related to excess tooth material., Results: The guidelines are written as patterns to facilitate the decision of extraction of teeth for class I, class II division 1, class II division 2, and class III malocclusions, for crowding, overjet reduction, or correcting the buccal segment relationship. The decision for extraction of teeth for orthodontic treatment is enforced by the oral hygiene, carious teeth, periodontal involvement, impacted teeth, supernumeraries, hypodontia, or for orthognathic purposes. Also, planning the decision for accurate extraction pattern is the main factor in the success of the orthodontic treatment and for the long-term stability of the results., Conclusion: Orthodontic tooth extraction should always be planned with consideration of the width and length of the face, the oral hygiene, carious activity, periodontal involvement, malformed crowns, length and health of the root of the teeth, prognosis of impacted teeth, supernumeraries, and hypodontia., Clinical Significance: Accurate diagnosis and treatment planning following orthodontic extraction guidelines lead to a long-term stability of the corrected results.

Published
2018

8. Analysis of class I and II aberrations in Iraqi childhood acute myeloid leukemia using filter paper cards.

Author

Al-Kzayer LF, Uyen le TN, Al-Jadiry MF, Al-Hadad SA, Al-Badri SA, Ghali HH, Ameen NA, Liu T, Matsuda K, Abdulkadhim JM, Al-Shujairi TA, Matti ZI, Hasan JG, Al-Abdullah HM, Al-Ani MH, Saber PA, Khalil HM, Inoshita T, Kamata M, Koike K, and Sakashita K

Subjects
Adolescent, Alleles, Blood Specimen Collection instrumentation, Blood Specimen Collection methods, Bone Marrow pathology, Child, Child, Preschool, DNA, Neoplasm genetics, Female, Humans, Infant, Iraq, Leukemia, Myeloid, Acute blood, Leukemia, Myeloid, Acute pathology, Leukemia, Myeloid, Acute therapy, Leukemia, Myelomonocytic, Acute blood, Leukemia, Myelomonocytic, Acute genetics, Leukemia, Myelomonocytic, Acute pathology, Leukemia, Myelomonocytic, Acute therapy, Male, Nucleophosmin, Oncogene Proteins, Fusion genetics, Oncogenes, Paper, Prognosis, Reverse Transcriptase Polymerase Chain Reaction, Specimen Handling instrumentation, Translocation, Genetic, Treatment Outcome, Chromosome Aberrations, Leukemia, Myeloid, Acute genetics, Mutation, Sequence Analysis, DNA, Specimen Handling methods
Abstract

The lack of molecular diagnosis in the field of cancer in Iraq has motivated us to perform a genetic analysis of pediatric acute myelogenous leukemia (AML), including class I and II aberrations. Peripheral blood or bone marrow cells were collected from 134 AML children aged ≤15 years. Flinders Technology Associates (FTA) filter paper cards were used to transfer dried blood samples from five Iraqi hospitals to Japan. DNA sequencing was performed to identify class I mutations. Nested RT-PCR was used to detect class II aberrations, except that MLL rearrangement was detected according to long distance inverse-PCR. NPM1 and FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD) mutations were analyzed by GeneScan using DNA template. Among 134 Iraqi pediatric AML samples, the most prevalent FAB subtype was M2 (33.6 %) followed by M3 (17.9 %). Class I mutations: 20 (14.9 %), 8 (6.0 %), and 8 (6.0 %) patients had FLT3-ITD, FLT3-TKD, and KIT mutations, respectively. Class II mutations: 24 (17.9 %), 19 (14.2 %), and 9 (6.7 %) children had PML-RARA, RUNX1-RUNX1T1, and CBFB-MYH11 transcripts, respectively. MLL rearrangements were detected in 25 (18.7 %) patients. NPM1 mutation was detected in seven (5.2 %) cases. Collectively, approximately 30 % of AML children were proved to carry favorable prognostic genetic abnormalities, whereas approximately 10 % had high FLT3-ITD allelic burden and needed a special treatment plan including allogeneic hematopoietic stem cell transplantation. Acute promyelocytic leukemia (APL) was frequent among Iraqi pediatric AML. It is likely that molecular diagnosis using FTA cards in underdeveloped countries could guide doctors towards an appropriate treatment strategy.

Published
2014
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9. Genetic evaluation of childhood acute lymphoblastic leukemia in Iraq using FTA cards.

Author

Al-Kzayer LF, Sakashita K, Matsuda K, Al-Hadad SA, Al-Jadiry MF, Abed WM, Abdulkadhim JM, Al-Shujairi TA, Hasan JG, Al-Abdullah HM, Al-Ani MH, Saber PA, Inoshita T, Kamata M, and Koike K

Subjects
Child, Child, Preschool, Core Binding Factor Alpha 2 Subunit analysis, Female, Fusion Proteins, bcr-abl analysis, Homeodomain Proteins analysis, Humans, Infant, Iraq, Male, Myeloid-Lymphoid Leukemia Protein analysis, Oncogene Proteins, Fusion analysis, Precursor Cell Lymphoblastic Leukemia-Lymphoma diagnosis, RNA, Messenger, Translocation, Genetic, Precursor Cell Lymphoblastic Leukemia-Lymphoma genetics
Abstract

Background: Genetic examination of childhood leukemia has not been available in Iraq. We here report the frequency of TEL-AML1, E2A-PBX1, MLL-AF4, and BCR-ABL chimeric transcripts in 264 Iraqi children newly diagnosed with acute lymphoblastic leukemia (ALL), using FTA cards impregnated with bone marrow aspirate or whole blood., Patients and Methods: The diagnosis of ALL was made according to standard French-American-British morphologic criteria. Based on the results of storage temperature and duration, most of the FTA samples were preserved at 4°C for up to 6 weeks in five Iraqi hospitals and then transferred to Japan for molecular analysis. Nested reverse transcription-polymerase chain reaction was adopted for the analysis., Results: TEL-AML1 chimeric transcript product was found in 32 (12.1%) of 264 ALL patients. Eleven (4.2%) patients, 4 (1.5%) patients, and 11 (4.2%) patients had E2A-PBX1 mRNA, MLL-AF4 mRNA, and BCR-ABL mRNA, respectively. One patient had both TEL-AML1 and E2A-PBX1 fusion genes. The incidence of TEL-AML1 in Iraqi ALL children appears to be similar to or slightly higher than those of Jordan (12%) and Kuwait (7%). The prevalence and clinical findings of ALL patients with either E2A-PBX1 or BCR-ABL were comparable to the data reported elsewhere., Conclusion: International collaboration via FTA cards may be helpful to improve diagnosis and management of patients with hematological malignancies in low-income and underdeveloped countries., (Copyright © 2012 Wiley Periodicals, Inc.)

Published
2012
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11. An artificial neural network approach for rational decision-making in borderline orthodontic cases: A preliminary analytical observational in silico study.

Author

Kapoor, Shanya, Shyagali, Tarulatha R, Kuraria, Amit, Gupta, Abhishek, Tiwari, Anil, and Goyal, Payal

Subjects
MACHINE learning, EXPERT systems, ARTIFICIAL intelligence, SUPERVISED learning, DECISION making
Abstract

Artificial intelligence (AI) technology has transformed the way healthcare functions in the present scenario. In orthodontics, expert systems and machine learning have aided clinicians in making complex, multifactorial decisions. One such scenario is an extraction decision in a borderline case. The present in silico study was planned with the intention of building an AI model for extraction decisions in borderline orthodontic cases. An observational analytical study. Department of Orthodontics, Hitkarini Dental College and Hospital, Madhya Pradesh Medical University, Jabalpur, India. An artificial neural network (ANN) model for extraction or non-extraction decisions in borderline orthodontic cases was constructed based on a supervised learning algorithm using the Python (version 3.9) Sci-Kit Learn library and feed-forward backpropagation method. Based on 40 borderline orthodontic cases, 20 experienced clinicians were asked to recommend extraction or non-extraction treatment. The decision of the orthodontist and the diagnostic records, including the selected extraoral and intra-oral features, model analysis and cephalometric analysis parameters, constituted the training dataset of AI. The built-in model was then tested using a testing dataset of 20 borderline cases. After running the model on the testing dataset, the accuracy, F1 score, precision and recall were calculated. The present AI model showed an accuracy of 97.97% for extraction and non-extraction decision-making. The receiver operating curve (ROC) and cumulative accuracy profile showed a near-perfect model with precision, recall and F1 values of 0.80, 0.84 and 0.82 for non-extraction decisions and 0.90, 0.87 and 0.88 for extraction decisions. As the present study was preliminary in nature, the dataset included was too small and population-specific. The present AI model gave accurate results in decision-making capabilities related to extraction and non-extraction treatment modalities in borderline orthodontic cases of the present population. [ABSTRACT FROM AUTHOR]

Published
2023
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12. Evaluation of different machine learning algorithms for extraction decision in orthodontic treatment.

Author

Köktürk B, Pamukçu H, and Gözüaçık Ö

Abstract

Introduction: The extraction decision significantly affects the treatment process and outcome. Therefore, it is crucial to make this decision with a more objective and standardized method. The objectives of this study were (1) to identify the best-performing model among seven machine learning (ML) models, which will standardize the extraction decision and serve as a guide for inexperienced clinicians, and (2) to determine the important variables for the extraction decision., Methods: This study included 1000 patients who received orthodontic treatment with or without extraction (500 extraction and 500 non-extraction). The success criteria of the study were the decisions made by the four experienced orthodontists. Seven ML models were trained using 36 variables; including demographic information, cephalometric and model measurements. First, the extraction decision was performed, and then the extraction type was identified. Accuracy and area under the curve (AUC) of the receiver operating characteristics (ROC) curve were used to measure the success of ML models., Results: The Stacking Classifier model, which consists of Gradient Boosted Trees, Support Vector Machine, and Random Forest models, showed the highest performance in extraction decision with 91.2% AUC. The most important features determining extraction decision were maxillary and mandibular arch length discrepancy, Wits Appraisal, and ANS-Me length. Likewise, the Stacking Classifier showed the highest performance with 76.3% accuracy in extraction type decisions. The most important variables for the extraction type decision were mandibular arch length discrepancy, Class I molar relationship, cephalometric overbite, Wits Appraisal, and L1-NB distance., Conclusion: The Stacking Classifier model exhibited the best performance for the extraction decision. While ML models showed a high performance in extraction decision, they could not able to achieve the same level of performance in extraction type decision., (© 2024 The Author(s). Orthodontics & Craniofacial Research published by John Wiley & Sons Ltd.)

Published
2024
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13. Growth regulators promote soybean productivity: a review.

Author

Amoanimaa-Dede, Hanna, Chuntao Su, Yeboah, Akwasi, Hang Zhou, Dianfeng Zheng, and Hongbo Zhu

Subjects
PLANT regulators, GROWTH regulators, ABIOTIC stress, PLANT proteins, SOYBEAN
Abstract

Soybean [Glycine max (L.) Merrill] is a predominant edible plant and a major supply of plant protein worldwide. Global demand for soybean keeps increasing as its seeds provide essential proteins, oil, and nutraceuticals. In a quest to meet heightened demands for soybean, it has become essential to introduce agro-technical methods that promote adaptability to complex environments, improve soybean resistance to abiotic stress, and increase productivity. Plant growth regulators are mainly exploited to achieve this due to their crucial roles in plant growth and development. Increasing research suggests the influence of plant growth regulators on soybean growth and development, yield, quality, and abiotic stress responses. In an attempt to expatiate on the topic, current knowledge, and possible applications of plant growth regulators that improve growth and yield have been reviewed and discussed. Notably, the application of plant growth regulators in their appropriate concentrations at suitable growth periods relieves abiotic stress thereby increasing the yield and yield components of soybean. Moreover, the regulation effects of different growth regulators on the morphology, physiology, and yield quality of soybean are discoursed in detail. [ABSTRACT FROM AUTHOR]

Published
2022
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15. Frequency of Orthodontic Extractions and Malocclusion-Related Factors in a University Setting During a 25-Year Period.

Author

Tahmasbi, Soodeh, Behzadi, Zahra Rezaei, Shabestari, Samira Basir, Namdari, Mahshid, Elah, Vahid-Dastjerdi, and Hamedi, Roya

Subjects
DENTAL extraction, DENTAL arch, CORRECTIVE orthodontics, DENTAL schools, AGE groups
Abstract

Objectives The decision regarding orthodontic tooth extraction or dental arch expansion is an important yet challenging topic in orthodontic treatment planning. However, studies in this respect are limited In Iran. This study aimed to assess the frequency of orthodontic tooth extractions and the role of malocclusion-related factors that affect the frequency of orthodontic extractions in a university setting during 25 years. Methods This descriptive retrospective study evaluated 1,222 records of patients who underwent fixed orthodontic treatment in Shahid Beheshti Dental School from 1994 to 2018. The frequency of tooth extraction, type of malocclusion, and age and gender of patients were analyzed by the Chi-square test. The correlation of quantitative and qualitative variables related to occlusion (overjet, overbite, space discrepancy, cross-bite, A point–nasion–B point angle, mandibular plane angle, canine relationship, molar relationship, and the Curve of Spee) with orthodontic extraction was analyzed by the binary logistic regression. All statistical analyses were performed by SPSS version 21. Results The frequency of orthodontic extraction decreased from 1994 (74.5%) to 2018 (41.6%). The highest frequency of orthodontic extraction (60%) occurred in class II division I malocclusion cases. Frequency of orthodontic extraction in the age group of 12-20 years was significantly higher than in other age groups (P=0.003). The odds of orthodontic extraction increased by an increase in overjet (P=0.036) and in class II malocclusion cases (P=0.05), and decreased by an increase in overbite (P=0.020). Conclusion Tendency to orthodontic extraction has decreased in contemporary orthodontics in Shahid Beheshti Dental School. In addition to the degree of dental crowding, the decision regarding orthodontic extraction also depended on overjet, overbite, and type of malocclusion. [ABSTRACT FROM AUTHOR]

Published
2021
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16. Anaemia Among Children Who Attended the Children's Teaching Hospital in Karbala, Iraq.

Author

Albaroodi, Khansaa

Subjects
CHILDREN'S hospitals, ANEMIA, HOSPITAL laboratories, GROWTH of children, REFERENCE values
Abstract

Introduction: The World Health Organization (WHO) reported a moderate incidence of anaemia among pregnant and nonpregnant women and among children younger than 59 months in 2011. Purpose: The aim of this study was to investigate anaemia among children younger than 14 years submitted to haematological exams at the Children's Teaching Hospital in Karbala, Iraq. Patients and Methods: This was a cross-sectional study carried out in the Children's Teaching Hospital Laboratory Department in Karbala, Iraq, from 1 July 2019 until 1 September 2019. Results: The prevalence of anaemia among children aged 0– 14 years in Karbala was 9.9%. There was no significant relationship between the type of anaemia diagnosed and age or sex. However, there was a significantly positive relationship between the type of anaemia diagnosed and each ferritin level, mean corpuscular volume, and mean corpuscular haemoglobin (p< 0.0001). The study participant skull diameter and length in relation to sex were compared to the WHO reference values for child growth standards, and the study values were less than the normal range for children below 5 years of age. Conclusion: A high prevalence of anaemia among children was reported with its apparent consequence on their health. This study highlights the prevalence of anaemia among children up to 14 years of age in Karbala, and future research is encouraged. [ABSTRACT FROM AUTHOR]

Published
2021
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17. Analysis of KRAS and NRAS Gene Mutations in Arab Asian Children With Acute Leukemia: High Frequency of RAS Mutations in Acute Lymphoblastic Leukemia.

Author

Al‐Kzayer, Lika'a Fasih Y., Sakashita, Kazuo, Al‐Jadiry, Mazin Faisal, Al‐Hadad, Salma Abbas, Ghali, Hasanein Habeeb, Uyen, Le T.N., Liu, Tingting, Matsuda, Kazuyuki, Abdulkadhim, Jaafar M.H., Al‐Shujairi, Tariq Abadi, Matti, Zead Ismael I.K., Sughayer, Maher A., Rihani, Rawad, Madanat, Faris F., Inoshita, Toshi, Kamata, Minoru, Koike, Kenichi, Al-Kzayer, Lika'a Fasih Y, Al-Jadiry, Mazin Faisal, and Al-Hadad, Salma Abbas

Published
2015
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18. Back pain: An unusual manifestation of acute lymphoblastic leukemia -- A case report and review of literature.

Author

Latha, Magatha Sneha, Thirugnanasambandam, Ram Prakash, Venkatraman, Padmasani, and Scott, Julius Xavier

Subjects
BACKACHE, PAIN, OSTEOPENIA, LEUKEMIA, PATIENTS
Abstract

Acute lymphoblastic leukemia (ALL) presented with bone pain and leukopenia is a well-recognized complex. Bone and joint pain are seen as presenting symptoms in 25% of patients with acute leukemia, but generalized osteopenia and vertebral complications are less common. Back pain due to vertebral changes as an early feature has been infrequently reported. We report a case of a 9-year-old female child who presented with back pain for 3 weeks. Blood counts and peripheral smear were normal. X-ray of the spine showed wedge-shaped deformity in L3-L5 vertebrae. Magnetic resonance imaging of the spine confirmed the lytic lesions of L3-L5 vertebrae. Infective etiological evaluation was normal. Bone marrow aspiration revealed pre-B-cell lymphoblastic leukemia. She was started on ALL protocol and pain subsided within a week, and remodeling of the bony lesions could be seen 2 months later. This case highlights that spinal involvement may be a presenting feature despite normal peripheral blood counts. [ABSTRACT FROM AUTHOR]

Published
2017
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