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TBH score: a new model to predict and prevent severe liver damage after chemotherapy for cancer patients

Authors Zhang M, Bao Y, Chen W, Wei M, Pang H, Ren YF, Mei J, Ye S, Fu S, Peng ZW

Received 31 December 2018

Accepted for publication 8 May 2019

Published 11 July 2019 Volume 2019:11 Pages 6443—6456

DOI https://doi.org/10.2147/CMAR.S199967

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Amy Norman

Peer reviewer comments 3

Editor who approved publication: Dr Chien-Feng Li


Mengping Zhang,1,* Yong Bao,2,* Wei Chen,3,* Mengchao Wei,4 Hui Pang,5 Yu Feng Ren,2 Jie Mei,6 Sheng Ye,1 Shunjun Fu,7 Zhen Wei Peng1,6

1Department of Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; 2Department of Radiation Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; 3Department of Pancreatobiliary Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; 4Department of Liver Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; 5Department of Medical Records Management, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; 6Clinical Trials Unit, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; 7Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China

*These authors contributed equally to this work

Purpose: To explore a quantitative predictive model for the risk of chemotherapy-induced severe liver damage (CISLD).
Materials and methods: In total, 3870 consecutive cancer patients initially treated with chemotherapy were retrospectively collected and randomly assigned to a training (n=2580) or internal validation (n=1290) set in a 2:1 ratio to construct and validate the model. Additional external validation was performed using another data set (n=413). A total of 486 patients were prospectively enrolled to assess the clinical significance of the model. CISLD was defined as grade ≥3 hepatotoxicity.
Results: CISLD was found in 255 (9.9%), 128 (9.9%) and 36 (8.7%) patients in the training, internal and external validation sets, respectively. Serum triglyceride, body mass index and history of hypertension formed the basis of the score model. Patients could be stratified into low, intermediate and high-risk groups with <10%, 10–30% and >30% CISLD occurrence, respectively. This model displayed a concordance index (C-index) of 0.834 and was validated in both the internal (C-index, 0.830) and external (C-index, 0.817) sets. The incidence of CISLD was significantly reduced in those who received preventive hepatoprotective drugs compared to those who did not among patients assessed as the intermediate risk group (8.9% vs 17.5%, p=0.042) and the high risk group (15.6% vs 55.8%, p=0.043).
Conclusions: The new score model can be used to accurately predict the risk of CISLD in cancer patients undergoing chemotherapy. Clinically, this can be translated into a reference tool for oncologists in the clinical decision-making process before chemotherapy to provide appropriate prevention and interventions for patients with a high risk of CISLD.

Keywords: chemotherapy, liver damage, predictive model

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