Cargando…

Development and Validation of a Computed Tomography–Based Radiomics Signature to Predict Response to Neoadjuvant Chemotherapy for Locally Advanced Gastric Cancer

IMPORTANCE: Neoadjuvant therapies have been shown to decrease tumor burden, increase resection rate, and improve the outcomes among patients with locally advanced gastric cancer (GC). However, not all patients are equally responsive; therefore, differentiating potential respondents from nonresponden...

Descripción completa

Detalles Bibliográficos
Autores principales:	Wang, Wei, Peng, Ying, Feng, Xingyu, Zhao, Yan, Seeruttun, Sharvesh Raj, Zhang, Jun, Cheng, Zixuan, Li, Yong, Liu, Zaiyi, Zhou, Zhiwei
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	American Medical Association 2021
Materias:	Original Investigation
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377567/ https://www.ncbi.nlm.nih.gov/pubmed/34410397 http://dx.doi.org/10.1001/jamanetworkopen.2021.21143

Ejemplares similares

Computed tomography-based radiomics for prediction of neoadjuvant chemotherapy outcomes in locally advanced gastric cancer: A pilot study
por: Li, Zhenhui, et al.
Publicado: (2018)

Equibalancing immune‐related adverse events and anticancer activity of immune checkpoint inhibitors
por: Seeruttun, Sharvesh Raj
Publicado: (2019)

Re-engineering anti-CTLA-4 antibodies for enhancing cancer immunotherapy efficacy and safety
por: Seeruttun, Sharvesh Raj
Publicado: (2019)

The role of computed tomography features in assessing response to neoadjuvant chemotherapy in locally advanced gastric cancer
por: Wei, Chengzhi, et al.
Publicado: (2023)

A homogenized approach to classify advanced gastric cancer patients with limited and adequate number of pathologically examined lymph nodes
por: Seeruttun, Sharvesh Raj, et al.
Publicado: (2019)

Association of Adjuvant Chemotherapy With Overall Survival Among Patients With Locally Advanced Gastric Cancer After Neoadjuvant Chemotherapy
por: Lin, Jian-Xian, et al.
Publicado: (2022)

Radiomics signature of computed tomography imaging for prediction of survival and chemotherapeutic benefits in gastric cancer
por: Jiang, Yuming, et al.
Publicado: (2018)

Pretreatment Contrast-Enhanced Computed Tomography Radiomics for Prediction of Pathological Regression Following Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer: A Preliminary Multicenter Study
por: Xie, Kun, et al.
Publicado: (2022)

Proposal and validation of a modified staging system to improve the prognosis predictive performance of the 8th AJCC/UICC pTNM staging system for gastric adenocarcinoma: a multicenter study with external validation
por: Fang, Cheng, et al.
Publicado: (2018)

Assessment of Intratumoral and Peritumoral Computed Tomography Radiomics for Predicting Pathological Complete Response to Neoadjuvant Chemoradiation in Patients With Esophageal Squamous Cell Carcinoma
por: Hu, Yihuai, et al.
Publicado: (2020)

Radiomics Signature on Computed Tomography Imaging: Association With Lymph Node Metastasis in Patients With Gastric Cancer
por: Jiang, Yuming, et al.
Publicado: (2019)

Effectiveness and Safety of Apatinib Plus Chemotherapy as Neoadjuvant Treatment for Locally Advanced Gastric Cancer: A Nonrandomized Controlled Trial
por: Lin, Jian-Xian, et al.
Publicado: (2021)

Clinical significance and diagnostic value of serum CEA, CA19-9 and CA72-4 in patients with gastric cancer
por: Liang, Yao, et al.
Publicado: (2016)

Maximum Somatic Allele Frequency in Combination With Blood-Based Tumor Mutational Burden to Predict the Efficacy of Atezolizumab in Advanced Non-small Cell Lung Cancer: A Pooled Analysis of the Randomized POPLAR and OAK Studies
por: Chen, Yu-tong, et al.
Publicado: (2019)

A comprehensive analysis comparing the eighth AJCC gastric cancer pathological classification to the seventh, sixth, and fifth editions
por: Seeruttun, Sharvesh Raj, et al.
Publicado: (2017)

A New Strategy Using ALDH(high)-CD8+T Cells to Inhibit Tumorigenesis
por: Luo, Huiyan, et al.
Publicado: (2014)

Standardizing the classification of gastric cancer patients with limited and adequate number of retrieved lymph nodes: an externally validated approach using real-world data
por: Wang, Wei, et al.
Publicado: (2022)

Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy
por: Xu, Qinmei, et al.
Publicado: (2021)

Functions of the AP-2α gene in activating apoptosis and inhibiting proliferation of gastric cancer cells both in vitro and in vivo
por: Zeng, Changqing, et al.
Publicado: (2017)

CT-based radiomics scores predict response to neoadjuvant chemotherapy and survival in patients with gastric cancer
por: Sun, Kai-Yu, et al.
Publicado: (2020)

Non-invasively predicting response to neoadjuvant chemotherapy in gastric cancer via deep learning radiomics
por: Fang, Mengjie, et al.
Publicado: (2022)

Identification of molecular biomarkers for the diagnosis of gastric cancer and lymph-node metastasis
por: Seeruttun, Sharvesh Raj, et al.
Publicado: (2019)

Prevalence of hypertension and prehypertension in Nepal: a systematic review and meta-analysis
por: Huang, Yun, et al.
Publicado: (2019)

Recurrence risk stratification based on Epstein–Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study
por: Mao, Minjie, et al.
Publicado: (2022)

Neoadjuvant Chemotherapy in Asian Patients With Locally Advanced Gastric Cancer
por: Tong, Xie, et al.
Publicado: (2023)

Prediction of Residual Axillary Nodal Metastasis Following Neoadjuvant Chemotherapy for Breast Cancer: Radiomics Analysis Based on Chest Computed Tomography
por: Lee, Hyo-jae, et al.
Publicado: (2023)

Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer
por: Roy, Sudipta, et al.
Publicado: (2021)

The Correlation Between Computed Tomography Volumetry and Prognosis of Advanced Gastric Cancer Treated with Neoadjuvant Chemotherapy
por: Chen, Chao, et al.
Publicado: (2020)

Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer
por: Li, Zheng-Yan, et al.
Publicado: (2020)

Identification and Validation of Plasma Metabolomic Signatures in Precancerous Gastric Lesions That Progress to Cancer
por: Huang, Sha, et al.
Publicado: (2021)

Computed tomography-based radiomic to predict resectability in locally advanced pancreatic cancer treated with chemotherapy and radiotherapy
por: Rossi, Gabriella, et al.
Publicado: (2022)

Association of Tumor-Associated Collagen Signature With Prognosis and Adjuvant Chemotherapy Benefits in Patients With Gastric Cancer
por: Chen, Dexin, et al.
Publicado: (2021)

Pre-Treatment Computed Tomography Radiomics for Predicting the Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Retrospective Study
por: Mao, Yitao, et al.
Publicado: (2022)

Correction to: Co‑clinical FDG‑PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple‑negative breast cancer
por: Roy, Sudipta, et al.
Publicado: (2021)

Neoadjuvant chemotherapy in locally advanced gastric adenocarcinoma: our experience in the elderly
por: Bugiantella, W, et al.
Publicado: (2009)

A Retrospective Study of Neoadjuvant Chemotherapy for Locally Advanced Gastric Cancer
por: Wang, Yajing, et al.
Publicado: (2020)

A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer
por: McAnena, Peter, et al.
Publicado: (2022)

Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre study
por: Sun, Caixia, et al.
Publicado: (2019)

The Usefulness of Pretreatment MR-Based Radiomics on Early Response of Neoadjuvant Chemotherapy in Patients With Locally Advanced Nasopharyngeal Carcinoma
por: Yongfeng, Piao, et al.
Publicado: (2021)

Using Radiomics and Machine Learning Applied to MRI to Predict Response to Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer
por: Chiappa, Valentina, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_d1p60sd7712m6igoov7lh6vv6e