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dc.contributor.authorLan, C
dc.contributor.authorLi, J
dc.contributor.authorHuang, X
dc.contributor.authorHeindl, A
dc.contributor.authorWang, Y
dc.contributor.authorYan, S
dc.contributor.authorYuan, Y
dc.date.accessioned2020-06-11T12:18:02Z
dc.date.issued2019-02-18
dc.identifier.citationBMC cancer, 2019, 19 (1), pp. 159 - ?
dc.identifier.issn1471-2407
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/3720
dc.identifier.eissn1471-2407
dc.identifier.doi10.1186/s12885-019-5343-8
dc.description.abstractBackground Identifying high-risk patients for platinum resistance is critical for improving clinical management of ovarian cancer. We aimed to use automated image analysis of hematoxylin & eosin (H&E) stained sections to identify the association between microenvironmental composition and platinum-resistant recurrent ovarian cancer.Methods Ninety-one patients with ovarian cancer containing the data of automated image analysis for H&E histological sections were initially reviewed.Results Seventy-one patients with recurrent disease were finally identified. Among 30 patients with high stromal cell ratio, 60% of the patients had platinum-resistant recurrence, which was significantly higher than the rate in patients with low stromal cell ratio (9.80%, P <  0.001). Multivariate logistic regression analysis revealed elevated CA125 level after 3 cycles of chemotherapy (P <  0.001) and high stromal cell ratio (P = 0.002) were the negative predictors of platinum-resistant relapse. The area under the curve (AUC) of receiver operating characteristic (ROC) curves of the models for predicting platinum-resistant recurrence with stromal cell ratio, normalization of CA125 level, and the combination of two parameters were 0.78, 0.79, and 0.89 respectively.Conclusions Our results demonstrated stromal cell ratio based on automated image analysis may be a potential predictor for ovarian cancer patients at high risk of platinum-resistant recurrence, and it could improve the predictive value of model when combined with normalization of CA125 level after 3 cycles of chemotherapy.
dc.formatElectronic
dc.format.extent159 - ?
dc.languageeng
dc.language.isoeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectStromal Cells
dc.subjectHumans
dc.subjectOvarian Neoplasms
dc.subjectNeoplasm Recurrence, Local
dc.subjectPlatinum
dc.subjectMembrane Proteins
dc.subjectCA-125 Antigen
dc.subjectDrug Therapy
dc.subjectLogistic Models
dc.subjectOdds Ratio
dc.subjectChi-Square Distribution
dc.subjectDrug Resistance, Neoplasm
dc.subjectImage Processing, Computer-Assisted
dc.subjectAged
dc.subjectFemale
dc.subjectTumor Microenvironment
dc.subjectBiomarkers, Tumor
dc.titleStromal cell ratio based on automated image analysis as a predictor for platinum-resistant recurrent ovarian cancer.
dc.typeJournal Article
dcterms.dateAccepted2019-02-01
rioxxterms.versionofrecord10.1186/s12885-019-5343-8
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2019-02-18
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfBMC cancer
pubs.issue1
pubs.notesNot known
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Computational Pathology & Integrated Genomics
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Computational Pathology & Integrated Genomics
pubs.publication-statusPublished
pubs.volume19
pubs.embargo.termsNot known
icr.researchteamComputational Pathology & Integrated Genomicsen_US
dc.contributor.icrauthorYuan, Yinyinen


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