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5. Pembrolizumab versus placebo as post-nephrectomy adjuvant therapy for clear cell renal cell carcinoma (KEYNOTE-564): 30-month follow-up analysis of a multicentre, randomised, double-blind, placebo-controlled, phase 3 trial

Author

Tomczak, Piotr, Choueiri, Toni, Park, Se Hoon, Venugopal, Balaji, Ferguson, Thomas R., Hajek, Jaroslav, Lin, Tzu-Ping, Symeonides, Stefan N., Lee, Jae Lyun, Sawrycki, Piotr, Haas, Naomi B., Gurney, Howard P., Mahave, Mauricio, Sarwar, Naveed, Thiery-Vuillemin, Antoine, Gross-Goupil, Marine, Chevreau, Christine, Burke, John M., Doshi, Gurjyot, Melichar, Bohuslav, Topart, Delphine, Oudard, Stephane, Kopyltsov, Evgeniy, Hammers, Hans-Joerg, Quinn, David I., Alva, Ajjai, Menezes, Juliana de Janoski, Silva, Adriano Goncalves e, Winquist, Eric W., Hamzaj, Alketa, Procopio, Giuseppe, Karaszewska, Boguslawa, Nowakowska-Zajdel, Ewa M., Alekseev, Boris Y., Gafanov, Rustem A., Izmailov, Adel, Semenov, Andrey, Afanasyev, Sergey G., Lipatov, Oleg N., Powles, Thomas B., Srinivas, Sandy, McDermott, David, Kochuparambil, Samith T., Davis, Ian D., Peltola, Katriina, Sabbatini, Roberto, Chung, Jinsoo, Shkolnik, Michail I., Matveev, Vsevolod B., Gajate Borau, Pablo, McCune, Steven, Hutson, Thomas E., Dri, Alejandro, Sales, Silvio Correia, Yeung, Carrie, Alcala Castro, Carmen Marcela, Bostrom, Peter, Laguerre, Brigitte, Buttigliero, Consuelo, de Giorgi, Ugo, Fomin, Eugeniy A., Zakharia, Yousef, Hwang, Clara, Singer, Eric A., Yorio, Jeffrey T., Waterhouse, David, Kowalyszyn, Ruben Dario, Alfie, Margarita Sonia, Yanez Ruiz, Eduardo, Buchler, Tomas, Kankaanranta, Krista, Ferretti, Gianluigi, Kimura, Go, Nishimura, Kazuo, Masumori, Naoya, Tamada, Satoshi, Kato, Haruaki, Kitamura, Hiroshi, Danielewicz, Iwona, Wojcik-Tomaszewska, Joanna, Sala Gonzalez, Nuria, Chiu, Kun-Yuan, Atkins, Michael B., Heath, Elisabeth, Rojas-Uribe, Gustavo Adolfo, Gonzalez Fernandez, Manuel Enrique, Feyerabend, Susan, Pignata, Sandro, Numakura, Kazuyuki, Cybulska Stopa, Bozena, Zukov, Ruslan, Climent Duran, Miguel Angel, Maroto Rey, Pablo Jose, Montesa Pino, Alvaro, Chang, Chao-Hsiang, Vengalil, Salil, Waddell, Tom S., Cobb, Patrick W., Hauke, Ralph, Anderson, Daniel M., Sarantopoulos, John, Gourdin, Theodore, Zhang, Tian, Jayram, Gautam, Fein, Luis Enrique, Harris, Carole, Beato, Patricia Medeiros Milhomem, Flores, Francisco, Estay, Angela, Rubiano, Juan Andres, Bedke, Jens, Hauser, Stefan, Neisius, Andreas, Busch, Jonas, Anai, Satoshi, Tsunemori, Hiroyuki, Sawka, Dariusz, Sikora-Kupis, Bozena, Arranz, Jose Angel, Delgado, Ignacio, Chen, Chung-Hsin, Gunderson, Elizabeth, Tykodi, Scott, Koletsky, Alan, Chen, Kevin, Agrawal, Manish, Kaen, Diego Lucas, Sade, Juan Pablo, Tatangelo, Marcelo Daniel, Parnis, Francis, Barbosa, Fernando Maciel, Faucher, Genevieve, Iqbal, Nayyer, Marceau, Daniele, Paradis, Jean-Benoit, Hanna, Nawar, Acevedo, Alejandro, Ibanez, Carolina, Villanueva, Luis, Galaz, Pedro Pablo, Durango, Isabel Cristina, Manneh, Ray, Kral, Zdenek, Holeckova, Petra, Hakkarainen, Heikki, Ronkainen, Hanna, Abadie-Lacourtoisie, Sophie, Tartas, Sophie, Goebell, Peter J., Grimm, Marc-Oliver, Hoefner, Thomas, Wirth, Manfred, Panic, Andrej, Schultze-Seemann, Wolfgang, Yokomizo, Akira, Mizuno, Ryuichi, Uemura, Hirotsugu, Eto, Masatoshi, Tsujihata, Masao, Matsukawa, Yoshihisa, Murakami, Yoji, Kim, Miso, Hamberg, Paul, Marczewska-Skrodzka, Malgorzata, Szczylik, Cezary, Humphreys, Alison C., Jiang, Peter, Kumar, Birendra, Lu, Gary, Desai, Arpita, Karam, Jose Antonio, Keogh, George, Fleming, Mark, Zarba, Juan Jose, Leiva, Viviana E., Mendez, Guillermo Ariel, Harris, Samuel J., Brown, Stephen J., Antonio Junior, Joao Neif, Costamilan, Rita de Cassia, Rocha, Roberto Odebrecht, Muniz, David, Brust, Leandro, Lalani, Aly-Khan, Graham, Jeffrey, Levesque, Michael, Orlandi, Francisco, Kotasek, Rostislav, Deville, Jean L., Borchiellini, Delphine, Merseburger, Axel, Rink, Michael, Roos, Frederik, McDermott, Ray, Oyama, Masafumi, Yamamoto, Yoshiaki, Tomita, Yoshihiko, Miura, Yuji, Ioritani, Naomasa, Westgeest, Hans, Kubiatowski, Tomasz, Bal, Wieslaw, Girones Sarrio, Regina, Rowe, Julie, Prow, Debra M., Senecal, Francis, Hashemi-Sadraei, Neda, Cole, Scott W., Kendall, Stephan D., Richards, Donald A., Schnadig, Ian D., Gupta, Mukul, Powles, Thomas, Ferguson, Thomas, Symeonides, Stefan N, Gurney, Howard, Chang, Yen-Hwa, Haas, Naomi B, Burgents, Joseph E, Xu, Lei, Imai, Kentaro, Quinn, David I, and Choueiri, Toni K

Published
2022
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8. The Sofu Seamount Submarine Volcano Present in the Source Area of the October 2023 Earthquakes and Tsunamis in Japan.

Author

Fujiwara, Toshiya, Imai, Kentaro, Obayashi, Masayuki, Yoshida, Kenta, Tada, Noriko, Obana, Koichiro, Fujie, Gou, Ono, Shigeaki, and Kodaira, Shuichi

Abstract

On 8 October 2023 (UTC), unique earthquakes occurred in the Izu‐Ogasawara Arc, Japan, in which the P‐ and S‐phases were barely visible and only the T‐phases were evident, followed by tsunamis that reached islands in the Izu‐Ogasawara Arc and a wide area of the Pacific coast of southwest Japan. Our estimated T‐phase source area coincides with the Sofu Seamount, which was previously unrecognized as an active submarine volcano. A bathymetric survey of the seamount conducted 1 month after the event revealed characteristics of the seamount with a caldera and a central cone. Compared to the bathymetry in 1987, the topography in the caldera had changed significantly such as a crater forming in the central cone. This seamount is likely to be an active volcano. The topographic changes on the caldera‐sized scale that occurred at the caldera can be explained as a source of the October tsunami. Plain Language Summary: On 8 October 2023 (UTC), earthquakes were followed by tsunamis in the Izu‐Ogasawara Arc of Japan that were higher than that estimated from the magnitude of the earthquake. The tsunamis were observed on islands in the Izu‐Ogasawara Arc and a wide area of the Pacific coast of southwest Japanese islands. Strong T‐phases that are underwater acoustic waves were observed accompanying that event. We estimated that the T‐phases originated from the area around the Sofu Seamount, which has not been recognized as an active submarine volcano until now. One month after the event, we conducted a bathymetric survey of the seamount and revealed the characteristics of a caldera and a central cone within the caldera. Compared to the bathymetric data obtained in 1987, the caldera and central cone topography have changed significantly, such as a crater forming in the central cone, indicating that this seamount is likely to have been an active submarine volcano. The topographic changes that occurred at the depth of the caldera (∼1,000 m) and its scale (diameter ∼5 km) can be associated with the source of the tsunami on 8 October 2023. Key Points: A bathymetric survey of the Sofu Seamount was conducted after the unique T‐phase dominant earthquakes and tsunamis on 8 October 2023Compared to data in 1987, the caldera and central cone topography have changed, indicating that this seamount is an active submarine volcanoThe observed seafloor displacement at the caldera scale may have contributed to the source of the tsunami on 8 October 2023 [ABSTRACT FROM AUTHOR]

Published
2024
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9. Tsunami hazard evaluation of river embankment structures incorporating their vulnerability to seismic strong motion.

Author

Imai, Kentaro, Nakai, Kentaro, Hirai, Takashi, Noda, Toshihiro, Arai, Nobuo, Iwama, Shunji, Iwase, Hiroyuki, and Baba, Toshitaka

Abstract

Development of coastal areas in Japan for various land uses since the 1960s has contributed to industrial upgrades and improved the efficiency of transportation networks. However, there are concerns about the vulnerability of developments on alluvial plains and reclaimed lands to geological events, like ground subsidence due to liquefaction during large earthquakes. Realistic assessment of earthquake and tsunami hazards and evaluation of possible countermeasures require accurate estimation of the amount of subsidence that can be expected from liquefaction at coastal and riverside sites supporting various structures. In this study, to evaluate the amount a river embankment structure might be expected to settle as a result of strong motion from an assumed Nankai Trough great earthquake, we conducted a numerical simulation using the soil–water coupled finite deformation analysis code GEOASIA. We then investigated the effect of the estimated embankment subsidence on tsunami inundation, which was simulated by using nonlinear shallow-water equations and a grid spacing as fine as 3.3 m. The influence of urban structures on the inundated area was taken into account by using a structure-embedded elevation model (SEM). The results showed that subsidence of river embankments and the collapse of parapet walls on top of them would increase both the depth and area of inundation caused by a tsunami triggered by a Nankai Trough scenario earthquake. Our findings underscore the importance of evaluating not only earthquake resistance but also vulnerability of coastal and riverside structures to strong motion in tsunami hazard analyses. Furthermore, the importance of tsunami inundation analysis using a SEM for predicting the behavior of tsunami flotsam in urban areas was demonstrated. [ABSTRACT FROM AUTHOR]

Published
2024
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11. ADJUVANT PEMBROLIZUMAB FOR RENAL CELL CARCINOMA (KEYNOTE-564): EXPLORATORY ANALYSIS ACROSS UCLA INTEGRATED STAGING SYSTEM RISK GROUPS AND DISEASE STAGE

Author

Zhang, Tian, primary, Choueiri, Toni K., additional, Tomczak, Piotr, additional, Park, Se Hoon, additional, Venugopal, Balaji, additional, Ferguson, Tom, additional, Symeonides, Stefan N., additional, Hajek, Jaroslav, additional, Chang, Yen-Hwa, additional, Lee, Jae-Lyun, additional, Sarwar, Naveed, additional, Thiery-Vuillemin, Antoine, additional, Gross-Goupil, Marine, additional, Mahave, Mauricio, additional, Haas, Naomi B., additional, Sawrycki, Piotr, additional, Xu, Lei, additional, Imai, Kentaro, additional, Poehlein, Christian, additional, and Powles, Thomas, additional

Published
2024
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12. Pembrolizumab alone or combined with chemotherapy versus chemotherapy as first-line therapy for advanced urothelial carcinoma (KEYNOTE-361): a randomised, open-label, phase 3 trial

Author

Cascallar, Diana Vera, Varela, Mirta, Lazzaro, Mauricio Fernandez, Kaen, Diego Lucas, Gatica, Gabriela, Flores, David Hugo, Falco, Agustin, Molina, Matias, Van Aelst, Filip, Vulsteke, Christof, Sautois, Brieuc, Machiels, Jean-Pascal, Schallier, Denis, Brust, Leandro, Rapatoni, Liane, Azevedo, Sergio J, Marinho, Gisele, Soares, Joao Paulo Holanda, Dzik, Carlos, Almeida Silva, Jamile, Fay, Andre Poisl, Gingerich, Joel, Fradet, Yves, Ferrario, Cristiano, Potvin, Kylea, Vanhuyse, Marie, Abdelsalam, Mahmoud, Cheng, Susanna, Caglevic, Christian, Reyes, Felipe, Leal, Jose Luis, Francisco, Francisco, Ibanez, Carolina, Joly, Florence, Laguerre, Brigitte, Ladoire, Sylvain, Flechon, Aude, Topart, Delphine, Huillard, Olivier, Oudard, Stéphane, Gross-Goupil, Marine, Culine, Stephane, Loriot, Yohann, Gravis, Gwenaelle, Reichardt, Peter, Retz, Margitta, Herden, Jan, Pfister, David, Ohlman, Carsten, Stoeckle, Michael, Wirth, Manfred, Lorch, Anja, Niegisch, Guenter, Goebell, Peter J, Boegemann, Martin, Merseburger, Axel, Gakis, Georgios, Bedke, Jens, Neisius, Andreas, Thomas, Christian, Hoefner, Thomas, Telekes, Andras, Kosa, Judit Erzsebet, Revesz, Janos, Bodoky, Gyorgy, Csoszi, Tibor, Csejtei, Andras, Geczi, Lajos, Ruzsa, Agnes, Kolonics, Zsuzsanna, Erfan, Jozsef, McDermott, Ray, Bambury, Richard, Sella, Avishay, Frank, Stephen Jay, Kejzman, Daniel, Goldman, Olesya, Rosenbaum, Eli, Peer, Avivit, Berger, Raanan, Rouvinov, Keren, Sarid, David, Fukasawa, Satoshi, Arai, Gaku, Yamaguchi, Akito, Yokomizo, Akira, Takayama, Tatsuya, Kinoshita, Hidefumi, Kikuchi, Eiji, Mizuno, Ryuichi, Fujii, Yasuhisa, Sassa, Naoto, Matsukawa, Yoshihisa, Fujimoto, Kiyohide, Matsubara, Nobuaki, Tanikawa, Toshiki, Tomita, Yoshihiko, Nishimura, Kazuo, Tsujihata, Masao, Oyama, Masafumi, Masumori, Naoya, Kanayama, Hiroomi, Takano, Toshimi, Miura, Yuji, Miyazaki, Jun, Joraku, Akira, Kimura, Tomokazu, Yamamoto, Yoshiaki, Kobayashi, Kazuki, De Wit, Ronald, Aarts, Maureen, Gerritsen, Winald, Los, Maartje, Beerepoot, Laurens, Izmailov, Adel, Gorelov, Sergey Igorevich, Alekseev, Boris Yakovlevich, Semenov, Andrey, Kostorov, Vladimir Anatolyevich, Alekseev, Sergey M, Zyryanov, Alexander, Oschepkov, Vasiliy Nikolaevich, Shidin, Vladimir Aleksandrovich, Vladimirov, Vladimir Ivanovich, Gafanov, Rustem Airatovich, Karlov, Petr Alexandrovich, Anderson, David Brian, Shepherd, Lucinda, Cohen, Graham Lawrence, Rapoport, Bernardo Louis, Ruff, Paul, Lee, Nari, Bae, Woo Kyun, Lee, Hyo Jin, Herranz, Urbano Anido, Rodriguez-Vida, Alejo, Morales Barrera, Rafael, Grande, Enrique, Alonso Gordoa, Teresa, Guma Padro, Josep, Gauna, Daniel Castellano, Arranz, Jose Angel, Munoz Langa, Jose, Sarrio, Regina Girones, Montesa Pino, Alvaro, Juan Fita, Maria Jose, Su, Yu-Li, Lin, Yung-Chang, Su, Wen-Pin, Shen, Ying-Chun, Chang, Yen-Hwa, Huang, Yi-Hsiu, Sriuranpong, Virote, Chansriwong, Phichai, Srimuninnimit, Vichien, Danchaivijitr, Pongwut, Abali, Huseyin, Yavuz, Sinan, Ozyilkan, Ozgur, Sendur, Mehmet Ali Nahit, Ekenel, Meltem, Ozguroglu, Mustafa, Arslan, Cagatay, Gunduz, Seyda, Ozdogan, Mustafa, Birtle, Alison, Powles, Thomas, Huddart, Robert, de Santis, Maria, Zarkar, Anjali, Evans, Linda, Hussain, Syed, DiSimone, Christopher, Muina, Antonio F, Schlegel, Peter, Jhangiani, Haresh S, Harrison, Michael, Slater, Dennis E, Wright, David, Percent, Ivor J, Lin, Jianqing, Hwang, Clara, Mamtani, Ronac, Gupta, Sumati, Bajaj, Madhuri, Galamaga, Robert, Eklund, John, Wallace, James, Shtivelband, Mikhail, Suh, Jason Jung-Gon, Burhani, Nafisa, Eadens, Matthew, Gunturu, Krishna, Burgess, Earle, Wong, John, Chaudhry, Arvind, Van Veldhuizen, Peter, Graff, Stephanie, Thomas, Christian A, Schnadig, Ian D, Carneiro, Benedito, Hussain, Maha, Morgans, Alicia, Fitzharris, John T, Oliff, Ira A, Vuky, Jacqueline, Hauke, Ralph, Baron, Ari, Joshi, Monika, Bolemon, Britt H, Jiang, Peter, Mega, Anthony E, Markus, Maurice, Pfanzelter, Nicklas, Lawler, William Eyre, Cobb, Patrick Wayne, Courtright, Jay G, Jain, Sharad, Doshi, Gurjyot, Gunuganti, Vijay K, Sartor, Oliver Alton, Cole, Scott W, Babiker, Hani, Uchio, Edward M, Drakaki, Alexandra, Mannuel, Heather D, Alva, Ajjai, Guancial, Elizabeth, Fung, Chunkit, Charles, Anthony, Amato, Robert J, Arriaga, Yull, Bowman, Isaac, Ades, Steven, Dreicer, Robert, Yu, Evan, Quinn, David I, Fleming, Mark, Csőszi, Tibor, Özgüroğlu, Mustafa, Géczi, Lajos, Cheng, Susanna Y-S, Oudard, Stephane, Fléchon, Aude, Yu, Evan Y, Nam, Kijoeng, Imai, Kentaro, and Homet Moreno, Blanca

Published
2021
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14. Authentic fault models and dispersive tsunami simulations for outer-rise normal earthquakes in the southern Kuril Trench.

Author

Baba, Toshitaka, No, Tetsuo, Obana, Koichiro, Imai, Kentaro, Chikasada, Naotaka, Tanioka, Yuichiro, and Kodaira, Shuichi

Subjects
EARTHQUAKE zones, EULER equations, HYDROGRAPHIC surveying, EARTHQUAKES, TRENCHES, TSUNAMIS
Abstract

The southern Kuril Trench is one of the most seismically active regions in the world. In this study, marine surveys and observations were performed to construct fault models for possible outer-rise earthquakes. Seismic and seafloor bathymetric surveys indicated that the dip angle of the outer-rise fault was approximately 50°–80°, with a strike that was slightly oblique to the axis of the Kuril Trench. The maximum fault length was estimated to be ~ 260 km. Based on these findings, we proposed 17 fault models, with moment magnitudes ranging from 7.2 to 8.4. To numerically simulate tsunami, we solved two-dimensional dispersive wave and three-dimensional Euler equations using the outer-rise fault models. The results of both simulations yielded identical predictions for tsunami with short-wavelength components, resulting in significant dispersive deformations in the open ocean. We also found that tsunami generated by outer-rise earthquakes were affected by refraction and diffraction because of the source location beyond the trench axis. These findings can improve future predictions of tsunami hazards. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Real‐world study on the characteristics, post‐nephrectomy journey, and outcomes of patients with early‐stage renal cell carcinoma based on risk groups.

Author

Karam, Jose A., Bhattacharya, Rituparna, Ogbomo, Adesuwa, Gautam, Santosh, Yu, Rebekah, Sundaram, Murali, Imai, Kentaro, Chhabra, Jatin, and Haas, Naomi B.

Subjects
RENAL cell carcinoma, NEPHRECTOMY, OVERALL survival, PROGRESSION-free survival, SURVIVAL rate
Abstract

Objectives: To examine real‐world characteristics, journey, and outcomes among patients with locoregional, nonmetastatic renal cell carcinoma (RCC). Methods: A retrospective analysis of medical records from the ConcertAI Oncology Dataset was performed on adults in the United States with newly diagnosed nonmetastatic RCC between January 2012–December 2017 who received surgical treatment, and were followed until August 2021. Patients were stratified based on the risk of recurrence after nephrectomy. Recurrence rate and survival outcomes were assessed. Results: The cohort (n = 439) had a median age of 64 years, 66.1% were male, and 76.5% had clear‐cell histology. The median follow‐up time from nephrectomy was 39.3 months overall, 41.0 months for intermediate‐high‐risk patients (n = 377; 85.9%) and 24.1 months for high‐risk patients (n = 62; 14.1%). For intermediate‐high‐ and high‐risk patients, respectively, 68.4% and 56.5% had ≥1 medical oncologist visit after nephrectomy. Of 260 patients with documentation of postoperative imaging assessments, 72% were ordered by medical oncologists, and the median time from initial nephrectomy to the first scan was 110 days (intermediate‐high‐risk) and 51 days (high‐risk). Provider‐documented recurrence occurred in 223 (50.8%) patients, of whom 41.7% had ≥1 medical oncologist visit before the recurrence. Three‐year disease‐free survival (DFS), and overall survival rates were 49.4% and 80.8% (all patients): 27.7% and 64.7% (high‐risk); and 52.9% and 83.3% (intermediate‐high‐risk). Conclusions: Our study reports low DFS after nephrectomy for patients with intermediate‐high‐ and high‐risk RCC. Subsequent approval and use of new and newly approved adjuvant therapeutic options could potentially delay or prevent recurrence. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Coformulation of pembrolizumab and vibostolimab in patients (pts) with docetaxel-pretreated metastatic castration-resistant prostate cancer (mCRPC): KEYNOTE-365 cohort G.

Author

Fong, Peter C.C., Kwiatkowski, Mariusz, Mosca, Alessandra, Perez Valderrama, Begona, Huang, Yi-Hsiu, Zedan, Ahmed H., Kuc, Kamil, Wiechno, Pawel, Laguerre, Brigitte, Gonzalez-Billalabeitia, Enrique, Osipov, Mikhail, Sener Dede, Didem, Goh, Jeffrey, Daugaard, Gedske, Zhu, Pengfei, Imai, Kentaro, liu, yingjie, and Arranz Arija, Jose Angel

Published
2024
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28. Pembrolizumab (pembro) plus lenvatinib (lenva) in patients (pts) with docetaxel-pretreated, metastatic castration-resistant prostate cancer (mCRPC): KEYNOTE-365 cohort E.

Author

Augustin, Marinela, Laguerre, Brigitte, Baldini, Capucine, Zedan, Ahmed H., Gonzalez-Billalabeitia, Enrique, Fong, Peter C.C., Zukov, Ruslan, Hammerer, Peter, Prentice, Mark, Shore, Neal D., Necchi, Andrea, Todenhöfer, Tilman, Kessler, Elizabeth R., Köse, Fatih, Gurney, Howard, Perez Valderrama, Begona, Zhu, Pengfei, Imai, Kentaro, liu, yingjie, and McDermott, Raymond S.

Published
2024
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39. Long non-coding RNA lnc-CHAF1B-3 promotes renal interstitial fibrosis by regulating EMT-related genes in renal proximal tubular cells

Author

Imai, Kentaro, primary, Ishimoto, Takuji, additional, Doke, Tomohito, additional, Tsuboi, Toshiki, additional, Watanabe, Yu, additional, Katsushima, Keisuke, additional, Suzuki, Miho, additional, Oishi, Hideto, additional, Furuhashi, Kazuhiro, additional, Ito, Yasuhiko, additional, Kondo, Yutaka, additional, and Maruyama, Shoichi, additional

Published
2023
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41. Adjuvant pembrolizumab (pembro) for renal cell carcinoma (RCC) across UCLA Integrated Staging System (UISS) risk groups and disease stage: Subgroup analyses from the KEYNOTE-564 study.

Author

Choueiri, Toni K., primary, Tomczak, Piotr, additional, Park, Se Hoon, additional, Venugopal, Balaji, additional, Ferguson, Tom, additional, Symeonides, Stefan N., additional, Hajek, Jaroslav, additional, Chang, Yen-Hwa, additional, Lee, Jae-Lyun, additional, Sarwar, Naveed, additional, Thiery-Vuillemin, Antoine, additional, Gross-Goupil, Marine, additional, Mahave, Mauricio, additional, Haas, Naomi B., additional, Sawrycki, Piotr, additional, Zhang, Tian, additional, Xu, Lei, additional, Imai, Kentaro, additional, Poehlein, Christian Heinrich, additional, and Powles, Thomas, additional

Published
2023
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46. Evaluation of a Natural Language Processing Model to Identify and Characterize Patients in the United States With High-Risk Non–Muscle-Invasive Bladder Cancer.

Author

Narayan, Vikram M., Siolas, Despina, Meadows, Eric S., Turzhitsky, Vladimir, Sillah, Arthur, Imai, Kentaro, McMurry, Andrew J., and Li, Haojie

Subjects
NON-muscle invasive bladder cancer, NATURAL language processing, MEDICAL terminology, CANCER diagnosis, ELECTRONIC health records, DEEP learning
Abstract

PURPOSE: Treatment of non–muscle-invasive bladder cancer (NMIBC) is guided by risk stratification using clinical and pathologic criteria. This study aimed to develop a natural language processing (NLP) model for identifying patients with high-risk NMIBC retrospectively from unstructured electronic medical records (EMRs) and to apply the model to describe patient and tumor characteristics. METHODS: We used three independent EMR-derived data sets including adult patients with a bladder cancer diagnosis in 2011-2020 for NLP model development and training (n = 140), validation (n = 697), and application for the retrospective cohort analysis (n = 4,402). Deep learning methods were used to train NLP recognition of medical chart terminology to identify seven high-risk NMIBC criteria; model performance was assessed using the F1 score, weighted across features. An algorithm was then used to classify each patient as high-risk NMIBC (yes/no). Manually reviewed records served as the gold standard. RESULTS: The F1 scores after model training were >0.7 for all but one uncommon feature (prostatic urethral involvement). The highest area under the receiver operating curves (AUC) was observed for Ta (0.897) and T1 (0.897); the lowest AUC was for carcinoma in situ (CIS; 0.617). For high-risk NMIBC classification, positive predictive value was 79.4%, negative predictive value was 93.2%, and false-positive rate was 8.9%. Sensitivity and specificity were 83.7% and 91.1%, respectively. Of 748 patients manually confirmed as having high-risk NMIBC, 196 (26%) had CIS (of whom 19% also had T1 and 23% also had Ta disease); 552 tumors (74%) had no associated CIS. CONCLUSION: The NLP model, combined with a rule-based algorithm, identified high-risk NMIBC with good performance and will enable future work to study real-world treatment patterns and clinical outcomes for high-risk NMIBC. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Cost-Effectiveness Analysis of Pembrolizumab as an Adjuvant Treatment of Renal Cell Carcinoma Post-nephrectomy in the United States.

Author

Yizhen Lai, Bensimon, Arielle G., Gao, Emily, Bhattacharya, Rituparna, Ruifeng Xu, Chevure, Jestinah, Imai, Kentaro, and Haas, Naomi B.

Subjects
PEMBROLIZUMAB, RENAL cell carcinoma, RENAL cancer treatment, NEPHRECTOMY
Abstract

A Markov-based cost-effectiveness model was developed to project long-term effectiveness and costs among patients who undergo nephrectomy for renal cell carcinoma and receive either adjuvant pembrolizumab, adjuvant sunitinib, or routine surveillance alone (no adjuvant treatment). Over a lifetime horizon, pembrolizumab was estimated to prolong quality-adjusted life expectancy and be cost-effective relative to both comparator treatment strategies. Introduction: Pembrolizumab was recently approved as an adjuvant treatment of renal cell carcinoma (RCC), based on prolonged disease-free survival compared to placebo in the phase III KEYNOTE-564 trial. The objective of this study was to evaluate the cost-effectiveness of pembrolizumab as monotherapy in the adjuvant treatment of RCC post-nephrectomy, from a US health sector perspective. Patients and Methods: A Markov model with 4 health states (disease-free, locoregional recurrence, distant metastases, and death) was developed to compare the cost and effectiveness of pembrolizumab versus routine surveillance or sunitinib. Transition probabilities were estimated using patient-level KEYNOTE-564 data (cutoff: June 14, 2021), a retrospective study, and published literature. Costs of adjuvant and subsequent treatments, adverse events, disease management, and terminal care were estimated in 2022 US$. Utilities were based on EQ-5D-5L data collected in KEYNOTE-564. Outcomes included costs, life-years (LYs), and quality-adjusted LYs (QALYs). Robustness was assessed through one-way and probabilistic sensitivity analyses. Results: Total cost per patient was $549,353 for pembrolizumab, $505,094 for routine surveillance, and $602,065 for sunitinib. Over a lifetime, pembrolizumab provided gains of 0.96 QALYs (1.00 LYs) compared to routine surveillance, yielding an incremental cost-effectiveness ratio of $46,327/QALY. Pembrolizumab dominated sunitinib with 0.89 QALYs (0.91 LYs) gained while saving costs. At a $150,000/QALY threshold, pembrolizumab was cost-effective versus both routine surveillance and sunitinib in 84.2% of probabilistic simulations. Conclusion: Pembrolizumab is projected to be cost-effective as an adjuvant RCC treatment versus routine surveillance or sunitinib based on a typical willingness-to-pay threshold. [ABSTRACT FROM AUTHOR]

Published
2023
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