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18. Adverse Event Profiles of the Third-Generation Aromatase Inhibitors: Analysis of Spontaneous Reports Submitted to FAERS.

Author

Zhang, Yina, Zhao, Lingzhu, Liu, Yanning, Zhang, Jingkang, Zheng, Luyan, and Zheng, Min

Subjects
INTERSTITIAL lung diseases, AROMATASE inhibitors, DRUG toxicity, ANASTROZOLE, DATABASES, HORMONE receptor positive breast cancer
Abstract

The third-generation aromatase inhibitors (AIs), represented by letrozole, anastrozole, and exemestane, have been used as a standard first-line adjuvant therapy for postmenopausal breast cancer patients with positive hormone receptor. However, their safety in the real world has not been systematically analyzed. We used the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) to investigate adverse event (AE) profiles of the three AIs, covering the period from Q1 2004 to Q3 2023. The time-to-event onset profiles and cumulative incidence were analyzed by Weibull shape parameter test and Kaplan–Meier method, respectively. The disproportionality analysis was utilized to assess drug toxicity risk. Based on the FAERS database, 18,035, 8242, and 7011 reports listing letrozole, anastrozole, and exemestane as primary suspected drugs were extracted, respectively. AEs associated with anastrozole displayed the latest onset (p < 0.0001); meanwhile, WSP test showed that all three AIs had early failure-type profiles. At the preferred term level, we acquired 95, 59, and 42 significant signals associated with letrozole, anastrozole, and exemestane, which involved 18, 13, and 15 system organ classes, respectively. The three AIs all reported that their strongest AE signal was trigger finger. Neutropenia was the most frequent AE for letrozole, while the highest occurrences of anastrozole and exemestane were arthralgia. We also found that interstitial lung disease, a rare but serious AE, showed strong signal intensity in all three AIs. Additionally, letrozole was also associated with lots of other rare but serious AEs in hematologic, respiratory, and hepatic systems, which were not recorded in the instructions. Our analysis of safety warning signals of the third-generation AIs from the FAERS database provided reference for clinical safe and rational drug use. [ABSTRACT FROM AUTHOR]

Published
2024
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24. The Study of Cross Networks Alarm Correlation Based on Big Data Technology

Author

Man, Yi, Chen, Zhipeng, Chuan, Jianbin, Song, Mei, Liu, Ningning, Liu, Yanning, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Josef, Kittler, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Zu, Qiaohong, editor, and Hu, Bo, editor

Published
2016
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26. Nano‐calcipotriol as a potent anti‐hepatic fibrosis agent

Author

Zhang, Yina, primary, Wang, Liying, additional, Shao, Jiajia, additional, Liu, Yanning, additional, Lu, Yining, additional, Yang, Jing, additional, Xu, Siduo, additional, Zhang, Jingkang, additional, Li, Minwei, additional, Liu, Xiangrui, additional, and Zheng, Min, additional

Published
2023
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28. NEIM-11 DEUTERIUM METABOLIC IMAGING (DMI) DETECTS A LARGER WARBURG EFFECT IN HIGH-GRADE BRAIN TUMORS AND IN IDH WILD TYPE GLIOMAS

Author

Kim, Lauren, primary, De Feyter, Henk, additional, de Graaf, Robin, additional, Fulbright, Robert, additional, Liu, Yanning, additional, Rothman, Douglas, additional, Baehring, Joachim, additional, Blondin, Nicholas, additional, Kim, Peter, additional, Antonio, Omuro, additional, Chiang, Veronica, additional, Moliterno, Jennifer, additional, Omay, Sacit Bulent, additional, Piepmeier, Joseph, additional, and Corbin, Zachary, additional

Published
2023
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29. MT-6402, an engineered toxin body (ETB) targeting PD-L1: Interim efficacy and safety data.

Author

Barve, Minal A., primary, Van Tine, Brian Andrew, additional, Redman, Rebecca A., additional, Powell, Steven Francis, additional, Edenfield, William Jeffery, additional, Peguero, Julio Antonio, additional, Villaflor, Victoria Meucci, additional, Stein, Karen, additional, Moore, Chris, additional, Orlandella, Rachael, additional, Khanna, Swati, additional, Dekker, Joseph, additional, Ferrati, Silvia, additional, Charoenthongtrakul, Soratree, additional, Liu, Yanning, additional, Dabovic, Kristina, additional, and Spigel, David R., additional

Published
2023
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33. Lipid removal in deuterium metabolic imaging (DMI) using spatial prior knowledge.

Author

de Graaf, Robin A., Liu, Yanning, Corbin, Zachary A., and De Feyter, Henk M.

Subjects
*DEUTERIUM, *PRIOR learning, *LIPIDS, *BRAIN tumors, *BRAIN mapping
Abstract

Deuterium metabolic imaging (DMI) is a novel method to generate spatial maps depicting dynamic metabolism of deuterated substrates, such as [6,6 ′ - 2H2 ]-glucose, and their metabolic products, like 2H -lactate. While DMI acquisition methods are simple and robust, DMI processing still requires expert user interaction, e.g., in the removal of extracranial natural abundance 2H lipid signals that interfere with metabolism-linked 2H -lactate formation. Here we pursue the use of MRI-based spatial prior knowledge on brain and non-brain/skull locations to provide robust and objective lipid removal. Magnetic field heterogeneity was accounted for using DMI-derived surrogate B0 and B1 maps, as well as through subdivision of the skull region into smaller compartments. Adequate lipid removal with an average suppression of 90.5 ± 11.4 % is achieved on human brain in vivo without perturbation of the metabolic profile in brain voxels, thereby allowing for the generation of distinct and reliable metabolic maps for patients with brain tumors. [ABSTRACT FROM AUTHOR]

Published
2024
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38. Abstract OT2-11-01: A phase 1 study of the novel immunotoxin MT-5111 in patients with HER2+ tumors: interim results

Author

Okera, Meena, primary, Van Tine, Brian A., additional, Hubbard, Joleen M., additional, Barve, Minal, additional, Hamilton, Erika, additional, Mita, Monica M., additional, Valdes-Albini, Frances, additional, Ahn, Daniel, additional, Mamuye, Admasu, additional, Pelham, Joshua, additional, Yuet, Amy, additional, Yurewicz, Diana, additional, Liu, Yanning, additional, Sandri, Andres Machado, additional, Edenfield, William J., additional, Morikawa, Aki, additional, Gradishar, William, additional, Kumar, Rajiv, additional, and Wainberg, Zev A., additional

Published
2023
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44. Lipid Removal in Deuterium Metabolic Imaging (DMI) using Spatial Prior Knowledge.

Author

Graaf, Robin A. de, Liu, Yanning, Corbin, Zachary A., and Feyter, Henk M. De

Subjects
*DEUTERIUM, *PRIOR learning, *LIPIDS, *BRAIN tumors, *BRAIN mapping
Abstract

Deuterium Metabolic Imaging (DMI) is a novel method to generate spatial maps depicting dynamic metabolism of deuterated substrates, such as [6,6'-2H2]-glucose, and their metabolic products, like 2H-lactate. While DMI acquisition methods are simple and robust, DMI processing still requires expert user interaction, for example in the removal of extracranial natural abundance 2H lipid signals that interfere with metabolism-linked 2H-lactate formation. Here we pursue the use of MRI-based spatial prior knowledge on brain and non-brain/skull locations to provide robust and objective lipid removal. Magnetic field heterogeneity was accounted for using DMI-derived surrogate B0 and B1 maps, as well as through subdivision of the skull region into smaller compartments. Adequate lipid removal with an average suppression of 90.5 ± 11.4 % is achieved on human brain in vivo without perturbation of the metabolic profile in brain voxels, thereby allowing the generation of distinct and reliable metabolic maps on patients with brain tumors. [ABSTRACT FROM AUTHOR]

Published
2023
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48. NIMG-105. DEUTERIUM METABOLIC IMAGING (DMI) DETECTS A LARGER WARBURG EFFECT IN HIGH-GRADE BRAIN TUMORS AND IN IDH WILD TYPE GLIOMAS

Author

Kim, Lauren, primary, De Feyter, Henk, additional, de Graaf, Robin, additional, Fulbright, Robert, additional, Liu, Yanning, additional, Rothman, Douglas, additional, Baehring, Joachim, additional, Blondin, Nicholas, additional, Kim, Peter, additional, Omuro, Antonio, additional, Chiang, Veronica, additional, Moliterno, Jennifer, additional, Omay, Sacit Bulent, additional, Piepmeier, Joseph, additional, and Corbin, Zachary, additional

Published
2022
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