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Neoadjuvant pembrolizumab in combination with dabrafenib and trametinib (DTP) for BRAF V600E-mutated anaplastic thyroid cancer ( BRAF m-ATC): A multicenter phase 2 trial.
Zafereo, Mark , Busaidy, Naifa L. , Dadu, Ramona , Li, Xu , Geiger, J.L. , Kerrigan, Kathleen , Khan, Saad A. , Moore, Eric J. , Scharpf, Joseph , Wang, Jennifer Rui , Iyer, Priyanka , Waguespack, Steven G. , Maniakas, Anastasios , Banuchi, Victoria , Lai, Stephen Y. , Chinn, Steven Bennett , Ryder, Mabel , Worden, Francis P. , Williams, Michelle D. , Cabanillas, Maria E.

Journal of Clinical Oncology | May 28, 2025 | Volume: 43 | Issue: 16_suppl | Pages: 6008-6008

10.1200/jco.2025.43.16_suppl.6008 Get It

6008 Background: ATC patients present with advanced, often surgically unresectable disease with historically dismal prognosis. Median PFS and OS of DT without pembrolizumab were 6.7 and 13.5 months, respectively, in the ROAR trial. Neoadjuvant DTP achieved locoregional control without radical surgery in a retrospective series of BRAF m-ATC patients, providing rationale to evaluate efficacy and safety in a phase 2 prospective trial. Methods: In this single-arm multicenter phase 2 trial, patients with BRAF m-ATC stage IVB/IVC were enrolled in 5 US centers. Following a 3-6 week run-in with D (150 mg BID) and T (2 mg daily), P (200 mg Q3W) was added, with restaging every three (21-day) cycles. Post-operatively, patients continued P (or DTP) with radiotherapy or transitioned directly to adjuvant DTP (up to 26 cycles). Primary endpoints included R0/R1 resection rate (historically 5%) and overall survival (OS). Secondary endpoints included RECIST 1.1 response after DTP and progression-free survival (PFS). Results: Between 9/2021-1/2025, 42 patients were enrolled; 36 are included in the current analysis (3 not evaluable, 3 pending surgery) (Table). Patients received median 4 (range: 2-7) neoadjuvant DTP cycles, with 26 (72%) achieving radiographic PR/CR. 30 patients (83%) had surgery after neoadjuvant DTP, achieving R0/R1 resection in 29/30 (97%). Mean surgical morbidity score (0-4 scale, 4=unresectable) improved from 3.3 to 1.6 after DTP (p<0.01). Complete ATC pathologic response occurred in 20/30 patients (67%), while 10/30 (33%) had residual ATC in the surgical specimen. Postoperatively, 11/30 (37%) received adjuvant neck radiation, and 28/36 (78%) completed a median of 11 (range: 1-26) adjuvant DTP cycles. With median follow up 18 months, 15/36 (42%) patients died. Median OS was 20 months (95% CI: 12.6-NR); 1- and 2-year OS were 71% and 48%. Complete pathologic responders had better 2-year OS than those with residual ATC (69% vs. 22%, p=0.02). Median PFS was 13.9 months (95% CI, 7.5-NR); 1- and 2-year PFS were 57% and 36%. Grade 5 adverse events occurred in 8 patients (22%), including one possible (duodenal perforation), one probable (kidney injury with sepsis), and 6 unlikely/unrelated treatment-related deaths. Conclusions: Neoadjuvant DTP enables surgical resection in BRAF m-ATC compared with historical controls, and leads to improved PFS and OS. This approach should now be considered a standard of care for BRAF m-ATC. Clinical trial information: NCT04675710 . Total N=36 Age (y), median (range) 67 (46-86) Stage IVB/IVC, n (%) 15 (42%)/21 (58%) Best RECIST response neoadjuvant phase, n (%) CR 2 (6%) PR 24 (67%) SD 6 (17%) PD 4 (11%) Percent change target lesion diameter, mean (95% CI) -44% (-54%, -34%) Surgical morbidity score change, mean (95% CI) -1.7 (-2.1, -1.3)
Global, Regional, and National Burden of Nontraumatic Subarachnoid Hemorrhage
Collaborators, GBD 2021 Global Subarachnoid Hemorrhage Risk Factors, Rautalin, Ilari, Stark, Benjamin, Johnson, Catherine O., Kaprio, Jaakko , Korja, Miikka, Krishnamurthi, Rita , Nair, Balakrishnan , Vergouwen, Mervyn D. I. , Abdelkader, Atef , Abdullahi, Auwal , Abualruz, Hasan , Abukhadijah, Hana J , Adamu, Lawan Hassan, Adegboye, Oyelola A. , Adzigbli, Leticia Akua, Agyemang‐Duah, Williams , Ahinkorah, Bright Opoku, Ahmad, Aqeel , Ahmad, Danish , Ahmadzade, Amir Mahmoud , Akkaif, Mohammed Ahmed , Ali, Mohammed Usman, Alif, Sheikh Mohammad , Alimohamadi, Yousef, Alsabri, Mohammed , Altaf, Awais , Alvis‐Guzmán, Nelson , Alwafi, Hassan , Al‐Wardat, Mohammad , Alyahya, Mohammad S. , Amin, Tarek Tawfik , Amindarolzarbi, Alireza , Amusa, Ganiyu , Angappan, Dhanalakshmi , Anuoluwa, Boluwatife Stephen, Anwar, Saleha, Anyasodor, Anayochukwu Edward , Apostol, Geminn Louis Carace, Areda, Demelash, Artamonov, Anton A, Artanti, Kurnia Dwi , Ashemo, Mubarek Yesse , Athar, Mohammad , Aujayeb, Avinash , Awotidebe, Adedapo Wasiu , Azadnajafabad, Sina , Aziz, Shahkaar , Bagheri, Nasser , Taqanaki, Pegah Bahrami , Bahramian, Saeed , Bai, Ruhai , Baig, Atif Amin , Baltatu, Ovidiu Constantin , Bam, Kiran, Barker‐Collo, Suzanne , Bärnighausen, Till , Bastan, Mohammad‐Mahdi , Basu, Sanjay , Bell, Shelly L, Benseñor, Isabela M , Berhie, Alemshet Yirga , Bhagavathula, Akshaya Srikanth , Bhaskar, Sonu , Bhat, Ajay Nagesh, Bhat, Vivek , Birhan, Mekuriaw Mesfin , Borhany, Hamed, Breitner, Susanne , Bulamu, Norma B. , Butt, Zahid A , Cabral, Lucas Scotta , Santos, Florentino Luciano Caetano dos , Cámera, Luis Alberto , Capodici, Angelo , Chadwick, Joshua , Chakraborty, Promit Ananyo , Chanie, Gashaw Sisay , Chattu, Vijay Kumar , Chi, Gerald, Chichagi, Fatemeh , Columbus, Alyssa , Criqui, Michael H, Ohadi, Mohammad Amin Dabbagh , Dadras, Omid , Dalli, Lachlan L. , Debopadhaya, Shayom , Dervišević, Emina , Devanbu, Vinoth Gnana Chellaiyan, Dewan, Syed Masudur Rahman , Dhane, Amol S. , Chi, Thanh, Phuong, Thao Huynh, Dohare, Sushil , Докова, Клара , Dowou, Robert Kokou , Dsouza, Haneil Larson , Dutta, Siddhartha , Dziedzic, Arkadiusz , E’mar, Abdel Rahman, Edvardsson, David , Efendi, Ferry, Nahas, Nevine El , Elgendy, Islam Y. , Eltaha, Chadi, Emeto, Theophilus I. , Fakhradiyev, Ildar , Faris, Pawan , Fauk, Nelsensius Klau , Fazylov, Timur, Fekadu, Ginenus , Fetensa, Getahun, Fischer, Florian, Foschi, Matteo , Fridayani, Ni Kadek Yuni, Gaipov, Abduzhappar , Gajjar, Avi A. , Ganesan, Balasankar , Gebregergis, Miglas Welay, Gebremeskel, Teferi Gebru , Getie, Molla , Ghadirian, Fataneh , Ghasemzadeh, Afsaneh , Gholamalizadeh, Maryam , Gil, Artyom , Goleij, Pouya , Goulart, Alessandra C. , Goulart, Bárbara Niegia Garcia de , Guan, Shi‐Yang , Gupta, Sapna , Habibzadeh, Farrokh , Hadi, Najah R, Hankey, Graeme J. , Harlianto, Netanja I. , Hasani, Hamidreza, Hasnain, Md Saquib , Haubold, Johannes , Havmoeller, Rasmus, Hay, Simon I , Hbid, Youssef , Heidari, Golnaz , Hiraike, Yuta, Hoan, Nguyen Quoc , Hosseinzadeh, Mehdi , Hwang, Bing‐Fang , Ibitoye, Segun Emmanuel , Ikiroma, Adalia , Isola, Gaetano , Iwagami, Masao , Jacob, Louis, Jain, Akhil, Jakovljević, Mihajlo , Jatau, Abubakar Ibrahim , Jawaid, Talha, Jayapal, Sathish Kumar , Jonas, Jost B, Joseph, Nitin , Jürisson, Mikk , Kadashetti, Vidya, Kalani, Rizwan, Kamireddy, Arun , Kandel, Himal , Behnagh, Arman Karimi , Kashoo, Faizan , Kayode, Gbenga A , Kazemi, Foad , Khader, Yousef , Khaing, Inn Kynn , Khan, Fayaz Ahmad , Khan, Mohammad Jobair , Kashani, Hamid Reza Khayat , Khosla, Atulya Aman , Kim, Kwanghyun , Kim, Yun Jin , Korzh, Oleksii , Krishan, Kewal , Krishna, Varun, Krishnamoorthy, Vijay , Kuddus, Mohammed , Kulimbet, Mukhtar , Lahariya, Chandrakant, Lai, Daphne Teck Ching , Lai, Hanpeng , Laksono, Tri, Lallukka, Tea , Latifinaibin, Kaveh, Le, Nhi Huu Hanh, Le, Thao T. , Lee, Munjae , Lee, Yo Han , Lenzi, Jacopo , Leonardi, Matilde, Li, Ming‐Chieh , Li, Xiaopan , Lim, Stephen S , Lin, Jialing , Saute, Ricardo Lutzky , Malik, Ahmad Azam , Marateb, Hamid Reza , Maroufi, Seyed Farzad , Maugeri, Andrea , McPhail, Steven , Mehndiratta, Man Mohan, Mestrovic, Tomislav, Mettananda, Chamila Dinushi Kukulege , Miazgowski, Tomasz , Minervini, Giuseppe , Mithra, Prasanna , Mohamed, Abdalla Z. , Mohammad, Ameen Mosa , Mohammed, Shafiu , Moni, Mohammad Ali , Moradi, Yousef, Moraga, Paula , Morawska, Lídia , Munjal, Kavita , Murray, Christopher J L , Nagarajan, Ahamarshan Jayaraman , Naik, Ganesh R. , Najdaghi, Soroush , Davani, Delaram Narimani , DELETE-ME, Nawsherwan, Nazri-Panjaki, Athare , Negoi, Ruxandra Irina , Nematollahi, Soroush , Nguyen, Hau Thi Hien, Nguyen, Hau Thi Hien, Nguyen, Phat Tuan , Nguyễn, Văn Thành , Niazi, Robina Khan, Nikoobar, Ali , Sá, Antonio Tolentino Nogueira de , Nomura, Shuhei , Nzoputam, Chimezie Igwegbe , Oancea, Bogdan , Ojo-Akosile, Tolulope R, Oliveira, Gláucia Maria Moraes de , Olorukooba, Abdulhakeem Abayomi , Osuagwu, Uchechukwu Levi , Ouyahia, Amel, A, Mahesh Padukudru P, Panagiotakos, Demosthenes B. , Parikh, Romil R., Park, Seoyeon , Pedersini, Paolo , Peprah, Emmanuel , Perico, Norberto, Petermann-Rocha, Fanny Emily, Plotnikov, Evgenii , Полибин, Р. В. , Postma, Maarten J. , Prasad, Manya , Qian, Gangzhen , Rahmanian, Mohammad , Rajaa, Sathish , Rajput, Prashant , Ramadan, Mahmoud M. , Rane, Amey, Rashidi, Mohammad‐Mahdi , Razo, Christian , Reddy, Murali Mohan Rama Krishna, Remuzzi, Giuseppe, Rezaei, Negar , Rezaeian, Mohsen , Rocha, Hermano Alexandre Lima , Rodriguez, Jefferson Antonio Buendia, Roever, Leonardo , Romoli, Michele, Romozzi, Marina, Roy, Nitai , Saddik, Basema Ahmad, Sahoo, Pragyan Monalisa , Salaroli, Luciane Bresciani , Samuel, Vijaya Paul, Samy, Abdallah M , Santric-Milicevic, Milena M., Saravanan, Aswini, Schlaich, Markus P. , Sethi, Yashendra , Seylani, Allen, Shaaban, Ahmed Nabil , Shafie, Mahan , Shaikh, Summaiya Zareen , Shamsutdinova, Alfiya, Sharifan, Amin , Rad, Javad Sharifi, Sharma, Vishal, Shashamo, Bereket Beyene , Shetty, Premalatha K, Shigematsu, Mika, Shorofi, Seyed Afshin, Singh, Paramdeep , Singh, Puneetpal , Singh, Surjit , Sobia, Farrukh , Solanki, Shipra, Soraneh, Soroush , Spartalis, Michael, Srinivasamurthy, Suresh Kumar , Stanikzai, Muhammad Haroon , Sun, Zhong , Swain, Chandan Kumar , Damavandi, Payam Tabaee , Tabatabaeizadeh, Seyed-Amir, Tabche, Celine , Taiba, Jabeen , Tamuzi, Jacques Lukenze , Tan, Ker‐Kan , Teramoto, Masayuki , Thakur, Ramna, Thankappan, Kavumpurathu Raman , Thayakaran, Rasiah , Thirunavukkarasu, Sathish, Ticoalu, Jansje Henny Vera, Tiwari, Krishna Raj , Tonelli, Marcello , Topór-Mądry, Roman , Tovani-Palone, Marcos Roberto Roberto, Tran, Jasmine, Tran, Thang Huu , Duc, Nguyen Tran Minh , Truelsen, Thomas Clement, Unim, Brigid, Vahdati, Sanaz, Vaithinathan, Asokan Govindaraj , Eynde, Jef Van den , Vladimirov, Sergey Konstantinovitch , Waheed, Yasir, Wahood, Waseem , Walde, Mandaras Tariku, Wang, Yanzhong , Wickramasinghe, Nuwan Darshana , Wolfe, Charles D. A., Wubie, Yihun Miskir, Xiao, Hong , Xu, Xiaoyue , Yano, Yuichiro , Yarahmadi, Amir , Ye, Pengpeng, Yon, Dong Keon , Zanghì, Aurora , Zare, Iman, Zastrozhin, Michael, Zhang, Zhi-Jiang , Zhang, Zhiqiang , Zhang, Zhiqiang, Zhao, Hanqing , Zhou, Shang Cheng, Zhumagaliuly, Abzal , Zia, Hafsa, Roth, Gregory A., Topór‐Mądry, Roman , Oliveira, Arão Belitardo , Rahim, Fakher , Saddik, Basema , Waheed, Yasir , Liu, Xuefeng , Zhang, Yunquan , Ozair, Ahmad , Buendía, Jefferson Antonio , Korja, Miikka , Baig, Atif Amin , Shanawaz, Mohd , Elgendy, Islam Y , Hankey, Graeme J , Alif, Sheikh M , Rezaei, Negar , Bhagavathula, Akshaya Srikanth , Van den Eynde, Jef , Ozair, Ahmad , Collaborators, GBD 2021 Global Subarachnoid Hemorrhage Risk Factors, Rautalin, Ilari Matias , Volovici, Victor , Ranta, Annemarei , Rinkel, Gabriël J.E. , Abate, Yohannes Habtegiorgis, Abbastabar, Hedayat , Abd-Allah, Foad , Abdi, Parsa , Abdollahi, Arash , Abiodun, Olugbenga Olusola , Aboagye, Richard Gyan , Abouzid, Mohamed , Abtahi, Dariush , Abu‐Rumeileh, Samir , Abualhasan, Ahmed , Abu‐Zaid, Ahmed , Addo, Isaac Yeboah , Adedoyin, Rufus Adesoji , Adra, Saryia , Ahinkorah, Bright Opoku , Ahmed, Ali , Ahmed, Haroon , Ahmed, Syed Anees , Aji, Budi , Al‐Ajlouni, Yazan A. , Al‐Aly, Ziyad , ALBashtawy, Mohammed , Aljunid, Syed Mohamed , Alomari, Mahmoud A. , Alrawashdeh, Ahmad , Alsabri, Mohammed A., Salman, Rustam Al‐Shahi , Al‐Tammemi, Ala’a B. , Al‐Worafi, Yaser Mohammed , Aly, Hany Z. , Alzoubi, Karem Hasan , Amani, Reza, Anderlini, Deanna , Anil, Abhishek , Arabloo, Jalal , Ärnlöv, Johan , Arumugam, Ashokan , Aryan, Zahra , Jafarabadi, Mohammad Asghari , Ashraf, Tahira , Athari, Seyyed Shamsadin , Azzam, Ahmed Y , Babu, Giridhara R. , Bako, Abdulaziz Tijjani , Banach, Maciej , Bandyopadhyay, Soham , Banik, Biswajit , Bardhan, Mainak , Barqawi, Hiba Jawdat , Barua, Lingkan , Beyene, Kebede Abera , Bhat, Vivek, Bhatti, Gurjit Kaur , Bhatti, Jasvinder Singh , Bijani, Ali , Bikbov, Boris , Birhanu, Mulugeta Molla , Bitra, Veera Raghavulu , Boloor, Archith , Brenner, Hermann , Bugiardini, Raffaele , Călina, Daniela Cornelia , Campos, Luciana Aparecida , Campos‐Nonato, Ismael , Carvalho, Félix , Castañeda-Orjuela, Carlos A , Catapano, Alberico Luigi , Cegolon, Luca , Chakraborty, Chiranjib , Chakraborty, Sandip , Chandika, Rama Mohan , Chaudhary, Anis Ahmad , Chi, Gerald , Ching, Patrick R , Chopra, Hitesh , Choudhari, Sonali Gajanan , Chowdhury, E. , Chu, Dinh‐Toi , Chung, Sheng‐Chia , Silva, Alanna Gomes da , Dai, Xiaochen , Dalal, Koustuv , D’Amico, Emanuele , Dashti, Mohsen , Davletov, Kairat , Cruz-Góngora, Vanessa Vianey De la , Delgado‐Enciso, Iván , Devanbu, Vinoth Gnana Chellaiyan, Dibas, Mahmoud , Doheim, Mohamed Fahmy , Dongarwar, Deepa , D’Oria, Mario , Doshi, Ojas Prakashbhai , Doshi, Rajkumar , Efendi, Defi , Efendi, Ferry , Elhadi, Muhammed , Eltahir, Mohd. Elmagzoub , Fabin, Natalia , Fagbamigbe, Adeniyi Francis , Fahim, Ayesha , Fares, Jawad , Ferreira, Nuno Bravo , Gandhi, Aravind P. , Garg, Ravindra Kumar , Gebrehiwot, Mesfin , Ghadimi, Delaram J. , Ghahramani, Sulmaz , Ghazy, Ramy Mohamed , Ghozy, Sherief , Gilani, Jaleed Ahmed , Gnedovskaya, Elena V. , Hadei, Mostafa , Hamidi, Samer , Hanifi, Nasrin , Haro, Josep María , Hasan, Faizul , Tabatabaei, Mahgol Sadat Hassan Zadeh , Heidari, Mohammad , Hemmati, Mehdi , Holla, Ramesh , Hostiuc, Sorin , Huang, Junjie , Huynh, Hong-Han , Ikeda, Nayu , Ilaghi, Mehran , Ilesanmi, Olayinka Stephen , Ilić, Irena , Ilić, Milena , Islam, Md. Rabiul , Ismail, Nahlah Elkudssiah , Iso, Hiroyasu , Jafarzadeh, Abdollah , Jairoun, Ammar Abdulrahman , Kalani, Rizwan, Kamal, Vineet Kumar , Kanchan, Tanuj , Karami, Jafar , Karaye, Ibraheem M. , Karimi, Yeganeh , Kesse‐Guyot, Emmanuelle , Khan, Fayaz, Khatatbeh, Haitham , Khatatbeh, Moawiah Mohammad , Kheirallah, Khalid Ahmed , Khidri, Feriha Fatima , Khormali, Moein , Kısa, Adnan , Kısa, Sezer , Kivimäki, Mika , Kolahi, Ali‐Asghar , Kompani, Farzad , Kostev, Karel , Kothari, Nikhil , Kunutsor, Setor K. , Kurniasari, Maria Dyah , Kusuma, Dian Palupi , Kytö, Ville , Vecchia, Carlo La , Lahariya, Chandrakant , Latief, Kamaluddin , Lee, Seung Won , Lee, Wei‐Chen , Leonardi, Matilde, Liu, Xuefeng , Lohner, Valerie , Lorenzovici, László , Lotufo, Paulo A. , Lucchetti, Giancarlo , Lusk, Jay B. , Amin, Hawraz Ibrahim M. , Malhotra, Armaan Kush , Malhotra, Kashish , Malta, Déborah Carvalho , Mansournia, Mohammad Alì , Mantovani, LG , Manu, Emmanuel, Marino, Mirko , Martínez, Ramón , Martini, Santi , Martorell, Miquel , Marzo, Roy Rillera , Mathangasinghe, Yasith , Mathews, Elezebeth , Mehmood, Asim , Mehrabani-Zeinabad, Kamran , Menezes, Ritesh G. , Meo, Sultan A , Meretoja, Atte , Meštrović, Tomislav , Sá, Ana Carolina Micheletti Gomide Nogueira de , Minh, Le Huu Nhat , Mirică, Andreea , Мirrakhimov, Erkin М , Mirza‐Aghazadeh‐Attari, Mohammad , Mishra, Ajay Kumar , Mohamed, Ahmed Ismail , Mohammadi, Soheil , Mohammadian-Hafshejani, Abdollah , Mokdad, Ali H. , Molinaro, Sabrina , Momani, Shaher , Ghalibaf, AmirAli Moodi , Moradi, Maryam , Msherghi, Ahmed A.A. , Ansari, Noureddin Nakhostin , Nargus, Shumaila , Natto, Zuhair S. , Nauman, Javaid , DELETE-ME, Nawsherwan, Nayak, Vinod C , Newton, Charles R. , Nigatu, Yeshambel T. , Noubiap, Jean Jacques , Nugen, Fred , Oduro, Michael Safo , Okati‐Aliabad, Hassan , Okeke, Sylvester Reuben , Okekunle, Akinkunmi Paul , Olagunju, Andrew T , Olaiya, Muideen Tunbosun , Olufadewa, Isaac Iyinoluwa , Ornello, Raffaele , Ortiz‐Prado, Esteban , Ouyahia, Amel , Owolabi, Mayowa , Padrón‐Monedero, Alicia , Padubidri, Jagadish Rao , Panos, Leonidas D , Pantazopoulos, Ioannis N. , Parikh, Romil R., Patel, Jay , Patel, Urvish , Patoulias, Dimitrios , Pereira, Gavin F , Perianayagam, Arokiasamy , Perna, Simone , Petermann‐Rocha, Fanny , Philip, Anil K. , Пирадов, М. А. , Pradhan, Jalandhar , Puvvula, Jagadeesh , Qasim, Nameer Hashim , Raggi, Alberto , Rahimi‐Movaghar, Vafa , Rahman, Muhammad Aziz , Rahmani, Amir Masoud , Sanati, Ali Rajabpour , Ramasamy, Shakthi Kumaran , Ramazanu, Sheena , Rathish, Devarajan , Rawaf, Salman , Redwan, Elrashdy M , Remuzzi, Giuseppe , Romoli, Michele, Romozzi, Marina , Ross, Allen Guy , Rout, Himanshu Sekhar , Roy, Priyanka , Saad, Aly M A , Saadatian, Zahra , Sabour, Siamak , Sacco, Simona , Sadeghi, Erfan , Saeed, Usman, Sharif‐Askari, Fatemeh Saheb , Sahebkar, Amirhossein , Sajib, Md Refat Uz Zaman , Saleh, Mohamed A. , Samodra, Yoseph Leonardo , MİLİCEVİC, Milena Santric, Saravanan, Aswini , Sarkar, Tanmay, Sarode, Sachin Chakradhar , Sartorius, Benn , Satpathy, Maheswar , Schneider, Ione Jayce Ceola , Schuermans, Art , Selvaraj, Siddharthan , Senthilkumaran, Subramanian , Sepanlou, Sadaf Ghajarieh , Shahwan, Moyad Jamal , Shamim, Muhammad Aaqib , Shamsi, Anas , Shannawaz, Mohammed , Rad, Javad Sharifi, Sharma, Vishal , Shittu, Aminu , Shiue, Ivy , Shlobin, Nathan A. , Siddig, Emmanuel Edwar , Spartalis, Michael , Stanaway, Jeffrey D , Starodubova, Antonina Vladimirovna , Szarpak, Łukasz , Tabatabaeizadeh, Seyed‐Amir , Tabatabaeizadeh, Seyed-Amir, Talaat, Iman Mamdouh , Temsah, Mohamad‐Hani , Thakur, Ramna , Thirunavukkarasu, Sathish, Tiwari, Krishna, Truyen, Thien Tan Tri Tai , Tsai, Daniel Hsiang‐Te , Ullah, Atta , Unnikrishnan, Bhaskaran , Unsworth, Carolyn Anne, Usman, Jibrin Sammani , Valizadeh, Rohollah , Varghese, Joe , Vasankari, Tommi Juhani , Venketasubramanian, Narayanaswamy , Vervoort, Dominique , Villafañe, Jorge Hugo , Vinayak, Manish , Wafa, Hatem A , Walde, Mandaras Tariku, Willeit, Peter , Wolfe, Charles D.A. , Wolfe, Charles D. A., Yamagishi, Kazumasa , Yaribeygi, Habib , Yaya, Sanni , Ye, Pengpeng, Yonemoto, Naohiro , Yu, Chuanhua , Zastrozhin, Michael, Zhang, Chen , Zhang, Zhiqiang, Zielińska, Magdalena , Zyoud, Samer H. , Roth, Gregory A. , Feigin, Valery L. , Kulimbet, Mukhtar , Rahim, Fakher

JAMA Neurology | May 23, 2025 | Volume: 82 | Issue: 8 | Pages: 765

10.1001/jamaneurol.2025.1522 | PMID 40406922 Get It

Importance Nontraumatic subarachnoid hemorrhage (SAH) represents the third most common stroke type with unique etiologies, risk factors, diagnostics, and treatments. Nevertheless, epidemiological studies often cluster SAH with other stroke types leaving its distinct burden estimates obscure. Objective To estimate the worldwide burden of SAH. Design, Setting, and Participants Based on the repeated cross-sectional Global Burden of Disease (GBD) 2021 study, the global burden of SAH in 1990 to 2021 was estimated. Moreover, the SAH burden was compared with other diseases, and its associations with 14 individual risk factors were investigated with available data in the GBD 2021 study. The GBD study included the burden estimates of nontraumatic SAH among all ages in 204 countries and territories between 1990 and 2021. Exposures SAH and 14 modifiable risk factors. Main Outcomes and Measures Absolute numbers and age-standardized rates with 95% uncertainty intervals (UIs) of SAH incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) as well as risk factor–specific population attributable fractions (PAFs). Results In 2021, the global age-standardized SAH incidence was 8.3 (95% UI, 7.3-9.5), prevalence was 92.2 (95% UI, 84.1-100.6), mortality was 4.2 (95% UI, 3.7-4.8), and DALY rate was 125.2 (95% UI, 110.5-142.6) per 100 000 people. The highest burden estimates were found in Latin America, the Caribbean, Oceania, and high-income Asia Pacific. Although the absolute number of SAH cases increased, especially in regions with a low sociodemographic index, all age-standardized burden rates decreased between 1990 and 2021: the incidence by 28.8% (95% UI, 25.7%-31.6%), prevalence by 16.1% (95% UI, 14.8%-17.7%), mortality by 56.1% (95% UI, 40.7%-64.3%), and DALY rate by 54.6% (95% UI, 42.8%-61.9%). Of 300 diseases, SAH ranked as the 36th most common cause of death and 59th most common cause of DALY in the world. Of all worldwide SAH-related DALYs, 71.6% (95% UI, 63.8%-78.6%) were associated with the 14 modeled risk factors of which high systolic blood pressure (population attributable fraction [PAF] = 51.6%; 95% UI, 38.0%-62.6%) and smoking (PAF = 14.4%; 95% UI, 12.4%-16.5%) had the highest attribution. Conclusions and Relevance Although the global age-standardized burden rates of SAH more than halved over the last 3 decades, SAH remained one of the most common cardiovascular and neurological causes of death and disabilities in the world, with increasing absolute case numbers. These findings suggest evidence for the potential health benefits of proactive public health planning and resource allocation toward the prevention of SAH.
Consensus Statement on Robotic Nipple Sparing Mastectomy Expert Panel
Ryu, Jai Min , Mok, Chi Wei , Toesca, Antonio , Lai, Hung‐Wen , Kuo, Wen‐Ling , Cheng, Fiona Tsui-Fen , Song, Seung Yong , Johnson, Jeffrey , Shin, Hyukjai , Park, Hyung Seok , Johnson, Jeffrey E , Cheng, Fiona Tsui-Fen

Journal of Breast Cancer | May 19, 2025 | Volume: 28 | Issue: 3 | Pages: 180

10.4048/jbc.2025.0030 | PMID 40432351 Get It

Reply: Considerations on the use of LPCN 1148 in cirrhotic patients with sarcopenia
Bruno, Benjamin, Weavil, Joshua C. , Ogle, Jonathan , Chidambaram, Nachiappan, DelConte, Anthony , Patel, Mahesh, Carey, Elizabeth J. , Lai, Jennifer C. , Bruno, Benjamin J , Lai, Jennifer , Sanyal, Arun J.

Hepatology | April 8, 2025 | Volume: 82 | Issue: 1 | Pages: E9-E10

10.1097/hep.0000000000001348 | PMID 40198269 Get It

Response to Letter to the Editor From Zhang et al: “Cabozantinib Plus Ipilimumab/Nivolumab in Patients with Previously Treated Advanced Differentiated Thyroid Cancer”
Konda, Bhavana , Sherman, Eric J. , Ryder, Mabel , Agulnik, Mark , Handley, Demond , Moses, Catherine, Jacob, Rajani, Streicher, Howard , Shah, Manisha H. , Streicher, Howard , Ryder, Mabel , Massarelli, Erminia , Nieva, Jorgé , Muzaffar, Jameel, Morris, John C, Ho, Alan L. , Wei, Lai , Moses, Catherine, Jacob, Rajani, Wright, John, Carson, William E.

The Journal of Clinical Endocrinology & Metabolism | April 4, 2025 | Volume: 110 | Issue: 7 | Pages: e2425-e2426

10.1210/clinem/dgaf221 | PMID 40184489 Get It

ALADDIN: A Machine Learning Approach to Enhance the Prediction of Significant Fibrosis or Higher in Metabolic Dysfunction-Associated Steatotic Liver Disease
Alkhouri, Naim , Yip, Terry Cheuk‐Fung , Takawy, Marina , Adams, Leon A. , Jafri, Syed‐Mohammed , Zhong, Bihui , Chen, Vincent , Dunn, Nicholas , Nadeem, Rida, Wang, Zhengyi, Duseja, Ajay , Almahanna, Yousef , Omeish, Haya , Ye, Junzhao , Harrison, Stephen A. , Cristiu, Jessica , Robert, Sage, Bajunayd, Amani, Shao, Congxiang , Kubina, Matthew , Cheuk-Fung Yip, Terry , Castera, Laurent , Takawy, Marina , Verma, Nipun , Jafri, Syed-Mohammed , Chen, V L , Singal, Ashwani K , Díaz, Luis A , Dunn, Nicholas , Wong, Vincent Wai-Sun , Abdelmalek, Manal F. , Wang, Zhengyi , Duseja, Ajay , Almahanna, Yousef , Ye, Junzhao , Cristiu, Jessica , Arrese, Marco , Lai-Hung Wong, Grace , Kubina, Matthew , Dunn, Winston , Verma, Nipun , Arab, Juan Pablo , Zhong, Bihui , Dubourg, Julie , Singal, Ashwani K. , Díaz, Luis Antonio , Wong, Vincent Wai‐Sun , Omeish, Haya A. , Harrison, Stephen A. , Arrese, Marco , Wong, Grace Lai‐Hung , Dunn, Winston

American Journal of Gastroenterology | March 30, 2025 | Volume: 121 | Issue: 2 | Pages: 362-374

10.14309/ajg.0000000000003432 | PMID 40146016 Get It

INTRODUCTION: The recent US Food and Drug Administration approval of resmetirom for treating metabolic dysfunction-associated steatohepatitis in patients necessitates patient selection for significant fibrosis or higher (≥F2). No existing vibration-controlled transient elastography (VCTE) algorithm targets ≥F2. METHODS: The mAchine Learning ADvanceD fibrosis and rIsk metabolic dysfunction-associated steatohepatitis Novel predictor (ALADDIN) study addressed this gap by introducing a machine-learning-based web calculator that estimates the likelihood of significant fibrosis using routine laboratory parameters with and without VCTE. Our study included a training set of 827 patients, a testing set of 504 patients with biopsy-confirmed metabolic dysfunction-associated steatotic liver disease from 6 centers, and an external validation set of 1,299 patients from 9 centers. Five algorithms were compared using area under the curve (AUC) in the test set: ElasticNet, random forest, gradient boosting machines, XGBoost, and neural networks. The top 3 (random forest, gradient boosting machines, and XGBoost) formed an ensemble model. RESULTS: In the external validation set, the ALADDIN-F2-VCTE model, using routine laboratory parameters with VCTE (AUC 0.791, 95% confidence interval [CI]: 0.764–0.819), outperformed VCTE alone (0.745, 95% CI 0.717–0.772, P < 0.0001), FibroScan-aspartate aminotransferase (0.710, 0.679–0.748, P < 0.0001), and Agile-3 model (0.740, 0.710–0.770, P < 0.0001) regarding the AUC, decision curve analysis, and calibration. The ALADDIN-F2-Lab model, using routine laboratory parameters without VCTE, achieved an AUC of 0.706 (95% CI: 0.668–0.749) and outperformed Fibrosis-4, steatosis-associated fibrosis estimator, and LiverRisk scores. DISCUSSION: Along with the steatosis-associated fibrosis estimator model developed to target significant fibrosis or higher, ALADDIN-F2-VCTE (https://aihepatology.shinyapps.io/ALADDIN1) uniquely supports a refined noninvasive approach to patient selection for resmetirom without the need for liver biopsy. In addition, ALADDIN-F2-Lab (https://aihepatology.shinyapps.io/ALADDIN2) offers an effective alternative when VCTE is unavailable.
Outcome of Goniotomy Over 120, 240 and 360 Degrees in Juvenile Open Angle Glaucoma: A Multicenter Study
Wang, Zhixuan , Fan, Hanying, Ge, Qingshu, Dang, Guangfu , Yang, Xiao , Xie, Lin , Zhu, Xiaoming , Yang, Yangfan , Wang, Yuhong , Liu, Jinkun , Zhang, Hongyang , Feng, Yuhan, Qi, Yongjun , Ye, Xiangxiang, Lai, Mingying , Lin, Peijie , Wang, Pusheng, Han, Shumei, Xu, Jiangang , Tao, Liming, Liu, Heting , Nie, Xin , Liao, Mengfei, Zou, Kai , Song, Yunhe , Lin, Fengbin , Xiaokaiti, Dilimulati, Liu, Xiaoyi , Fang, Zige , Jin, Ling, Chen, Yu , Han, Ying , Zeng, Liuzhi , Tham, Clement C, Yang, Zefeng , Ye, Xiangxiang, Lin, Peijie , Wang, Pusheng, Han, Shumei, Nie, Xin, Zou, Kai, Jiang, Yi , Zhou, Fengqi , Tham, Clement Chee Yung , Pan, Xiaojing , Weinreb, Robert Neal , Zhang, Xiulan

Journal of Glaucoma | March 19, 2025 | Volume: 34 | Issue: 6 | Pages: 433-439

10.1097/ijg.0000000000002569 | PMID 40105411 Get It

Précis: 240-degree and 360-degree goniotomy (GT) demonstrated similar efficacy in intraocular pressure (IOP) reduction, both outperforming 120-degree GT in patients with juvenile open angle glaucoma (JOAG) at postoperative 6-month follow-up. Objective: To compare the surgical efficacy and safety of 120-degree, 240-degree, and 360-degree GT for patients with JOAG. Patients and Methods: This multicenter retrospective study included 102 eyes of 102 patients with JOAG, who underwent GT with a follow-up of at least 6 months. Patients were categorized into 3 groups: (1) 120-degree GT, (2) 240-degree GT, and (3) 360-degree GT. IOP, glaucoma medications, and complications were recorded at baseline and the final visit. Complete success and qualified success were defined as a postoperative IOP ≤21 mm Hg without and with medications, respectively. Results: Mean age of the participants was 24.4 ± 7.9 years. After a mean follow-up of 8.1 ± 2.7 months, complete success rates were similar between the 240-degree GT (45.2%) and the 360-degree GT (63.2%; P = 0.135), and both were superior to 120-degree GT (18.2%; P < 0.05). Qualified success rates among patients in the 120-degree, 240-degree, and 360-degree GT groups were 93.9%, 96.8%, and 100%, respectively, and showed no statistically significant difference (P = 0.292). 360-degree GT required fewer medications than 240-degree GT and 120-degree GT (P < 0.05), with no significant difference in medications between 120-degree GT and 240-degree GT (P > 0.05). Hyphema was the most common postoperative complication, with a significantly higher incidence in the 360-degree GT (68.4%) compared with the 240-degree GT (41.9%) and 120-degree GT (33.3%; P < 0.05). Conclusions: 240-degree and 360-degree GT showed similar efficacy in IOP reduction and were superior to 120-degree GT. More extensive GT may provide better outcomes in JOAG.
Establishing a Threshold of Impairment to Define Preoperative Coronal Malalignment in Adult Spinal Deformity Patients
Hassan, Fthimnir M. , Lai, Christopher , Ha, Alex , Buchannan, Ian, Lee, Nathan J., Sardar, Zeeshan M. , Lehman, Ronald A. , Lenke, Lawrence G. , Hassan, Fthimnir M , Zuckerman, Scott L. , Shen, Yong , Kerolus, Mena G. , Cerpa, Meghan K. , Lee, Nathan J.

Clinical Spine Surgery | March 13, 2025 | Volume: 38 | Issue: 10 | Pages: E541-E548

10.1097/bsd.0000000000001792 | PMID 40079475 Get It

Study Design: Single-center retrospective analysis. Objective: To establish an empirically derived threshold to define both coronal and sagittal malalignment (CM & SM) based on preoperative patient-reported outcomes (PROs). Summary of Background Data: Currently, no radiographic alignment threshold defines preoperative CM in adult spinal deformity (ASD) patients based on disability. In a cohort of ASD patients undergoing corrective surgery, we sought to establish a threshold to define both CM and SM based on PRO and assess the clinical impact of CM and combined with SM. Methods: ASD patients with ≥6 level fusions were included. CVA and SVA were measured. PROs included preoperative ODI and SRS-22r scores. CVA and SVA thresholds were derived to accurately differentiate patients with ODI >40 and SRS-pain+function <5. Patients were then separated into 4 groups: (1) neutral alignment (NA); (2) CM; (3) SM; and (4) combined coronal and sagittal malalignment (CCSM). Results: Totally, 368 patients were included. Thresholds to distinguish patients with ODI ≥40 and SRS-pain/function <5 were: (1) CVA=3.96 cm (ODI) and 3.17 cm (SRS); (2) SVA=4.97 cm (ODI) and 7.52 cm (SRS). The lower numbers were chosen to define each threshold: CVA=3 cm and SVA=5 cm. Alignment breakdown was: NA=179 (48.6%), CM=66 (17.9%), SM=65 (17.7%), and CCSM=58 (15.8%). Both SM=( P =0.006) and CCSM ( P <0.001) patients had significantly worse ODI scores than NA patients, and CCSM patients were significantly worse than SM alone ( P =0.010). On the basis of preoperative total SRS-22r scores, only CCSM ( P =0.003) patients were significantly worse than the NA group. CVA significantly correlated with 4/7 (57.1%) preoperative PROs (ODI/SRS-total/function/image), while SVA correlated with 5/7 (71.4%) preoperative PROs (ODI/SRS-total/function/image/pain). A linear relationship was seen between increasing CVA and worsening ODI (β=0.92, 95% CI: 0.37–1.48, P =0.001). A significant and slightly stronger relationship was seen between increasing SVA and worsening ODI (β=1.28, 95% CI: 1.00–1.56, P <0.001). Conclusions: CM and SM thresholds that accurately distinguished ASD patients with severe pain and disability preoperatively were 3 cm for CVA and 5 cm for SVA, respectively. Preoperative CM was significantly associated with worse ODI, SRS-22r total/function/image scores. CCSM led to more disability than SM alone.
Semaglutide and Nonarteritic Anterior Ischemic Optic Neuropathy
Cai, Cindy X. , Hribar, Michelle R. , Swaminathan, Swarup S. , Flowers, Alexis , Brown, Eric N. , Chen, John J. , Chen, Aiyin , Wang, Sophia Y. , Ehrlich, Joshua R. , Armbrust, Karen R. , Alshammari, Thamir , Swerdel, Joel N. , Suchard, Marc A. , Falconer, Thomas , DuVall, Scott L. , Viernes, Benjamin , O’Brien, William J. , Martin, Benjamin , Westlund, Erik , Mathioudakis, Nestoras , Fan, Ruochong, Stocking, Jacqueline C. , Takkouche, Sahar , Humes, Izabelle, McCoy, David , Adibuzzaman, Mohammad, Areaux, Raymond G. , Rojas‐Carabali, William , Brash, James T., Lee, David A. , Mawn, Louise A. , Agrawal, Rupesh, Morgan‐Cooper, Hannah, Desai, Priya , Ryan, Patrick , Barkmeier, Andrew, Chen, John J , Mathioudakis, Nestoras N , Stocking, Jacqueline C , Lee, Cecilia S , Baxter, Sally L. , Goetz, Kerry , Toy, Brian C. , Xu, Benjamin Yixing , Leng, Theodore , Barkmeier, Andrew J. , Boland, Michael V. , Dorr, David A , Boyce, Danielle M. , Schuemie, Martijn J. , Bu, Fan , Sena, Anthony G. , Hripcsak, George , Nishimura, Akihiko, Nagy, Paul G. , Matheny, Michael E. , Zhang, Linying , Martin, Benjamin, Fan, Ruochong, Wilcox, Adam B , Lai, Albert M. , Lee, Lok Hin , Xie, Yangyiran , Weiskopf, Nicole G. , Desai, Priya

JAMA Ophthalmology | February 20, 2025 | Volume: 143 | Issue: 4 | Pages: 304

10.1001/jamaophthalmol.2024.6555 | PMID 39976940 Get It

Importance Semaglutide, a glucagonlike peptide-1 receptor agonist (GLP-1RA), has recently been implicated in cases of nonarteritic anterior ischemic optic neuropathy (NAION), raising safety concerns in the treatment of type 2 diabetes (T2D). Objective To investigate the potential association between semaglutide and NAION in the Observational Health Data Sciences and Informatics (OHDSI) network. Design, Setting, and Participants This was a retrospective study across 14 databases (6 administrative claims and 8 electronic health records). Included were adults with T2D taking semaglutide, other GLP-1RA (dulaglutide, exenatide), or non–GLP-1RA medications (empagliflozin, sitagliptin, glipizide) from December 1, 2017, to December 31, 2023. The incidence proportion and rate of NAION were calculated. Association between semaglutide and NAION was assessed using 2 approaches: an active-comparator cohort design comparing new users of semaglutide with those taking other GLP-1RAs and non–GLP-1RA drugs, and a self-controlled case-series (SCCS) analysis to compare individuals’ risks during exposure and nonexposure periods for each drug. The cohort design used propensity score–adjusted Cox proportional hazards models to estimate hazard ratios (HRs). The SCCS used conditional Poisson regression models to estimate incidence rate ratios (IRRs). Network-wide HR and IRR estimates were generated using a random-effects meta-analysis model. Exposures GLP-1RA and non–GLP-1RAs. Main Outcomes and Measures NAION under 2 alternative definitions based on diagnosis codes: one more inclusive and sensitive, the other more restrictive and specific. Results The study included 37.1 million individuals with T2D, including 810 390 new semaglutide users. Of the 43 620 new users of semaglutide in the Optum’s deidentified Clinformatics Data Mart Database, 24 473 (56%) were aged 50 to 69 years, and 26 699 (61%) were female. The incidence rate of NAION was 14.5 per 100 000 person-years among semaglutide users. The HR for NAION among new users of semaglutide was not different compared with that of the non–GLP-1RAs using the sensitive NAION definition—empagliflozin (HR, 1.44; 95% CI, 0.78-2.68; P = .12), sitagliptin (HR, 1.30; 95% CI, 0.56-3.01; P = .27), and glipizide (HR, 1.23; 95% CI, 0.66-2.28; P = .25). The risk was higher only compared with patients taking empagliflozin (HR, 2.27; 95% CI, 1.16-4.46; P = .02) using the specific definition. SCCS analysis of semaglutide exposure showed an increased risk of NAION (meta-analysis IRR, 1.32; 95% CI, 1.14-1.54; P &amp;lt; .001). Conclusions and Relevance Results of this study suggest a modest increase in the risk of NAION among individuals with T2D associated with semaglutide use, smaller than that previously reported, and warranting further investigation into the clinical implications of this association.