Pathologic response prediction to neoadjuvant chemotherapy utilizing pretreatment near-infrared imaging parameters and tumor pathologic criteria

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dc.contributor.authorZhu, Quing
dc.contributor.authorWang, Liqun
dc.contributor.authorTannenbaum, Susan
dc.contributor.authorRicci, Andrew
dc.contributor.authorDeFusco, Patricia
dc.contributor.authorHegde, Poornima
dc.date.accessioned2014-11-17T16:04:42Z
dc.date.available2014-11-17T16:04:42Z
dc.date.issued2014-10-28
dc.date.updated2014-11-17T16:04:43Z
dc.description.abstractAbstract Introduction The purpose of this study is to develop a prediction model utilizing tumor hemoglobin parameters measured by ultrasound-guided near-infrared optical tomography (US-NIR) in conjunction with standard pathologic tumor characteristics to predict pathologic response before neoadjuvant chemotherapy (NAC) is given. Methods Thirty-four patients’ data were retrospectively analyzed using a multiple logistic regression model to predict response. These patients were split into 30 groups of training (24 tumors) and testing (12 tumors) for cross validation. Tumor vascularity was assessed using US-NIR measurements of total hemoglobin (tHb), oxygenated (oxyHb) and deoxygenated hemoglobin (deoxyHb) concentrations acquired before treatment. Tumor pathologic variables of tumor type, Nottingham score, mitotic index, the estrogen and progesterone receptors and human epidermal growth factor receptor 2 acquired before NAC in biopsy specimens were also used in the prediction model. The patients’ pathologic response was graded based on the Miller-Payne system. The overall performance of the prediction models was evaluated using receiver operating characteristic (ROC) curves. The quantitative measures were sensitivity, specificity, positive and negative predictive values (PPV and NPV) and the area under the ROC curve (AUC). Results Utilizing tumor pathologic variables alone, average sensitivity of 56.8%, average specificity of 88.9%, average PPV of 84.8%, average NPV of 70.9% and average AUC of 84.0% were obtained from the testing data. Among the hemoglobin predictors with and without tumor pathological variables, the best predictor was tHb combined with tumor pathological variables, followed by oxyHb with pathological variables. When tHb was included with tumor pathological variables as an additional predictor, the corresponding measures improved to 79%, 94%, 90%, 86% and 92.4%, respectively. When oxyHb was included with tumor variables as an additional predictor, these measures improved to 77%, 85%, 83%, 83% and 90.6%, respectively. The addition of tHb or oxyHb significantly improved the prediction sensitivity, NPV and AUC compared with using tumor pathological variables alone. Conclusions These initial findings indicate that combining widely used tumor pathologic variables with hemoglobin parameters determined by US-NIR may provide a powerful tool for predicting patient pathologic response to NAC before the start of treatment. Trial registration ClincalTrials.gov ID: NCT00908609 (registered 22 May 2009)
dc.description.versionPeer Reviewed
dc.identifier.citationBreast Cancer Research. 2014 Oct 28;16(5):456
dc.identifier.doihttp://dx.doi.org/10.1186/s13058-014-0456-0
dc.identifier.urihttp://hdl.handle.net/1993/28568
dc.language.rfc3066en
dc.rightsopen accessen_US
dc.rights.holderQuing Zhu et al.; licensee BioMed Central Ltd.
dc.titlePathologic response prediction to neoadjuvant chemotherapy utilizing pretreatment near-infrared imaging parameters and tumor pathologic criteria
dc.typeJournal Article
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