Body composition as a predictor of toxicity after treatment with eribulin for advanced soft tissue sarcoma View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-11-21

AUTHORS

Hiroshi Kobayashi, Tomotake Okuma, Hiroyuki Oka, Koichi Okajima, Yuki Ishibashi, Liuzhe Zhang, Toshihide Hirai, Takahiro Ohki, Yusuke Tsuda, Masachika Ikegami, Ryoko Sawada, Yusuke Shinoda, Toru Akiyama, Hirotaka Kawano, Takahiro Goto, Sakae Tanaka

ABSTRACT

BackgroundDespite the clinical benefits of eribulin on overall survival of advanced soft tissue sarcoma (STS) patients, treatment-related toxicity reduces their QOL. Body composition metrics (BCMs) are associated with poor outcome and drug toxicities in several cancers. This study investigated whether BCMs could predict drug toxicity occurrence in advanced STS patients treated with eribulin.MethodsThis study included 23 advanced STS patients treated with eribulin between March 2016 and April 2018. BCMs were evaluated using a CT scan obtained within 1 month before or after treatment initiation. The relationship of BCMs and other clinical factors was evaluated and CART analysis used to develop classification models for risk groups of drug toxicity.ResultsSixteen patients (69.6%) experienced any grade 3/4 toxicity. Eleven patients (47.8%) developed G4 hematologic toxicity, which was significantly higher in those with low skeletal muscle gauge (SMG) (P = 0.02) and low pretreatment neutrophil count (P = 0.0002). Six patients (26.1%) had grade 3/4 non-hematologic toxicity, and was higher in those with low SMG (P = 0.004), and low serum albumin level (P = 0.02). Five patients with high BMI (P = 0.03) experienced febrile neutropenia (FN) and low pretreatment neutrophil count (P = 0.02). CART analysis classified three risk groups, and area under the receiver operating characteristic curve (AUROCC) was 0.92, 0.88, 0.92 in G4 hematologic AE, G3/4 non-hematologic AE, FN, respectively.ConclusionsSMG is a significant predictive factor of eribulin drug toxicity in advanced STS patients. Risk classification of drug toxicity through combining predictive factors, could improve the therapeutic strategy used in chemotherapy. More... »

PAGES

437-444

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10147-018-1370-8

DOI

http://dx.doi.org/10.1007/s10147-018-1370-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110098690

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30465138


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