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Cai JW, Li MY, Wang WH, Shi HQ, Yang YH, Chen JJ. Blastic plasmacytoid dendritic cell neoplasm in Jinhua, China: Two case reports. World J Clin Cases 2024; 12:5263-5270. [DOI: 10.12998/wjcc.v12.i22.5263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 05/31/2024] [Accepted: 06/20/2024] [Indexed: 06/30/2024] Open
Abstract
BACKGROUND Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and clinically aggressive hematologic malignancy originating from the precursors of plasmacytoid dendritic cells. BPDCN often involves the skin, lymph nodes, and bone marrow, with rapid clinical progression and a poor prognosis. The BPDCN diagnosis is mainly based on the immunophenotype.
CASE SUMMARY In this paper, we retrospectively analyzed 2 cases of BPDCN. Both patients were elderly males. The lesions manifested as skin masses. Morphological manifestations included diffuse and dense tumor cell infiltration of the dermis and subcutaneous tissues. Immunohistochemistry staining showed that cluster of differentiation CD4, CD56, CD43, and CD123 were positive.
CONCLUSION In this paper, we retrospectively analyzed 2 cases of BPDCN. Both patients were elderly males. The lesions manifested as skin masses. Morphological manifestations included diffuse and dense tumor cell infiltration of the dermis and subcutaneous tissues. Immunohistochemistry staining showed that cluster of differentiation CD4, CD56, CD43, and CD123 were positive.
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Affiliation(s)
- Jia-Wei Cai
- Department of Pathology, Jinhua Hospital, Jinhua 321000, Zhejiang Province, China
| | - Meng-Yao Li
- Department of Pathology, Shaoxing People’s Hospital, Shaoxing 312000, Zhejiang Province, China
| | - Wei-Hao Wang
- Department of Urology, Shaoxing People's Hospital, Shaoxing 312000, Zhejiang Province, China
| | - Hong-Qi Shi
- Department of Pathology, Jinhua Hospital, Jinhua 321000, Zhejiang Province, China
| | - Yi-Hui Yang
- Department of Pathology, Jinhua Hospital, Jinhua 321000, Zhejiang Province, China
| | - Jia-Jun Chen
- Department of Urology, Shaoxing People's Hospital, Shaoxing 312000, Zhejiang Province, China
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Daneshjou R, Vodrahalli K, Novoa RA, Jenkins M, Liang W, Rotemberg V, Ko J, Swetter SM, Bailey EE, Gevaert O, Mukherjee P, Phung M, Yekrang K, Fong B, Sahasrabudhe R, Allerup JAC, Okata-Karigane U, Zou J, Chiou AS. Disparities in dermatology AI performance on a diverse, curated clinical image set. SCIENCE ADVANCES 2022; 8:eabq6147. [PMID: 35960806 PMCID: PMC9374341 DOI: 10.1126/sciadv.abq6147] [Citation(s) in RCA: 84] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/30/2022] [Indexed: 06/10/2023]
Abstract
An estimated 3 billion people lack access to dermatological care globally. Artificial intelligence (AI) may aid in triaging skin diseases and identifying malignancies. However, most AI models have not been assessed on images of diverse skin tones or uncommon diseases. Thus, we created the Diverse Dermatology Images (DDI) dataset-the first publicly available, expertly curated, and pathologically confirmed image dataset with diverse skin tones. We show that state-of-the-art dermatology AI models exhibit substantial limitations on the DDI dataset, particularly on dark skin tones and uncommon diseases. We find that dermatologists, who often label AI datasets, also perform worse on images of dark skin tones and uncommon diseases. Fine-tuning AI models on the DDI images closes the performance gap between light and dark skin tones. These findings identify important weaknesses and biases in dermatology AI that should be addressed for reliable application to diverse patients and diseases.
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Affiliation(s)
- Roxana Daneshjou
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Kailas Vodrahalli
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Roberto A. Novoa
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
| | - Melissa Jenkins
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Weixin Liang
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Veronica Rotemberg
- Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Justin Ko
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Susan M. Swetter
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Elizabeth E. Bailey
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Olivier Gevaert
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Pritam Mukherjee
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Michelle Phung
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Kiana Yekrang
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Bradley Fong
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Rachna Sahasrabudhe
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | - Johan A. C. Allerup
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
| | | | - James Zou
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Chan-Zuckerberg Biohub, San Francisco, CA, USA
| | - Albert S. Chiou
- Department of Dermatology, Stanford School of Medicine, Redwood City, CA, USA
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Beziat G, Ysebaert L. Tagraxofusp for the Treatment of Blastic Plasmacytoid Dendritic Cell Neoplasm (BPDCN): A Brief Report on Emerging Data. Onco Targets Ther 2020; 13:5199-5205. [PMID: 32606740 PMCID: PMC7293389 DOI: 10.2147/ott.s228342] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 05/27/2020] [Indexed: 12/18/2022] Open
Abstract
Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare myeloid malignancy, for which conventional chemotherapy has poor outcomes. CD123, the α-subunit of interleukin (IL)-3 receptor, is constantly overexpressed at the surface of tumoral cells. Tagraxofusp (or SL-401) is a recombinant cytotoxin which consists of human interleukin-3 fused to a truncated diphtheria toxin. It is currently the only novel therapy with a prospective evaluation of efficacy and safety in the treatment of BPDCN and is also the only one to achieve FDA approval. In this short review, the results of tagraxofusp are summarized and perspectives of its use in BPDCN and in other malignancies are discussed. The safety profile is also summarized, since capillary leak syndrome is the main toxic effect of the drug, along with more common toxicities including an increase in transaminases and thrombocytopenia.
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Affiliation(s)
- Guillaume Beziat
- Hematology Department, University Hospitals of Toulouse, IUC Toulouse-Oncopole, Toulouse, France
| | - Loïc Ysebaert
- Hematology Department, University Hospitals of Toulouse, IUC Toulouse-Oncopole, Toulouse, France.,University Toulouse-3 Paul Sabatier, Toulouse, France
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