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Incorporating SULF1 polymorphisms in a pretreatment CT-based radiomic model for predicting platinum resistance in ovarian cancer treatment.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie - 1 Jan 2021

Yi Xiaoping, Liu Yingzi, Zhou Bolun, Xiang Wang, Deng Aojian, Fu Yan, Zhao Yuanzhe, Ouyang Qianying, Liu Yujie, Sun Zeen, Zhang Keqiang, Li Xi, Zeng Feiyue, Zhou Honghao, Chen Bihong T

Abstract excerpt

OBJECTIVE: Early detection of platinum resistance for ovarian cancer treatment remains challenging. This study aims to develop a machine learning model incorporating genomic data such as Single-Nucleotide Polymorphisms (SNPs) of Human Sulfatase 1 (SULF1) with a CT radiomic model based on pre-treatment CT images, to predict platinum resistance for ovarian cancer (OC) treatment. METHODS: A cohort of 102 patients...

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PMID: 33227705
DOI: 10.1016/j.biopha.2020.111013

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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