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dc.contributor.authorİriağaç, Yakup
dc.contributor.authorÇavdar, Eyyüp
dc.contributor.authorKaraboyun, Kubilay
dc.contributor.authorTacar, Seher Yıldız
dc.contributor.authorTaskaynatan, H.
dc.contributor.authorAvcı, Okan
dc.contributor.authorSeber, Erdoğan Selcuk
dc.contributor.authorYolcu, A.
dc.contributor.authorGürdal, Sibel Özkan
dc.contributor.authorÖznur, M.
dc.contributor.authorSeber, E.S.
dc.date.accessioned2022-05-11T14:40:56Z
dc.date.available2022-05-11T14:40:56Z
dc.date.issued2021
dc.identifier.issn1107-0625
dc.identifier.urihttps://hdl.handle.net/20.500.11776/8982
dc.description.abstractPurpose: Estrogen receptor (ER) and progesterone receptor (PgR) levels as well as Ki-67 expression levels are independent predictive markers in patients with hormone receptor-positive breast cancer. In this study, we investigated the predictive significance of the formula of log (ER)*log (PgR)/Ki-67, which was created using 3 independent predictive markers, for the pathological complete response of the Hormone Receptor (HR)-positive/HER2-negative breast cancer patients receiving neoadjuvant chemotherapy (NACT). Methods: This retrospective study included 126 patients with HR-positive/HER2-negative breast cancer and axillary lymph node metastasis who received NACT. The log (ER)*log (PgR)/Ki-67 value was calculated from the pre-NACT pathological evaluation results in all patients. We determined the ideal predictive cut-off value, which separates patients into 2 groups according to pathological complete response (pCR) and pathological non-complete response (non-pCR), using Receiver Operating Characteristic (ROC) curve analysis. According to this cut-off point, patients were divided into 2 groups as cut-off ratio high and cut-off ratio low and were compared using logistic regression analysis along with clinicopathological features. Results: According to the predictive model, we estimated the ideal cut-off value that distinguishes patients as pCR and non-pCR to be 0.12 (p=0.015). According to this cut off value, %54.8 of the patients were categorized as cut-off value high and %46.2 were cut-off value low. The non-pCR rates of the groups were 91.3% and %71.9, respectively(p=0.004). A cutoff value of 0.12 provided the feature of being a predictive marker in the univariate analysis for distinguishing between pCR and non-pCR (OR=4.09 95% CI 1.48-11.33, p=0.007), and it preserved this feature in the multivariate analysis. (OR=3.27, 95% CI 1.12-9.56, p=0.030). Conclusion: The formula of log (ER)*log (PgR)/Ki-67 can be used as a simple and easy-to-use predictive marker for response to neoadjuvant therapy in patients with HR-positive/HER2-negative breast cancer receiving NACT. © 2021 Zerbinis Publications. All rights reserved.en_US
dc.language.isoengen_US
dc.publisherZerbinis Publicationsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBreast canceren_US
dc.subjectHormone positiveen_US
dc.subjectNeoadjuvant chemotherapyen_US
dc.subjectNew predictive markeren_US
dc.subjectPathologic complete responseen_US
dc.titleA new predictive marker for predicting response after neoadjuvant chemotherapy in hormone receptor positive/HER2-negative patients: a logarithmic modelen_US
dc.typearticleen_US
dc.relation.ispartofJournal of B.U.ON.en_US
dc.departmentFakülteler, Tıp Fakültesi, Dahili Tıp Bilimleri Bölümü, Radyasyon Onkolojisi Ana Bilim Dalıen_US
dc.identifier.volume26en_US
dc.identifier.issue6en_US
dc.identifier.startpage2274en_US
dc.identifier.endpage2281en_US
dc.institutionauthorİriağaç, Yakup
dc.institutionauthorÇavdar, Eyyüp
dc.institutionauthorKaraboyun, Kubilay
dc.institutionauthorAvcı, Okan
dc.institutionauthorSeber, Erdoğan Selcuk
dc.institutionauthorYolcu, A.
dc.institutionauthorGürdal, Sibel Özkan
dc.institutionauthorÖznur, M.
dc.institutionauthorŞeber, Erdoğan Selçuk
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.authorscopusid57226431644
dc.authorscopusid57226624079
dc.authorscopusid57431169800
dc.authorscopusid57222993248
dc.authorscopusid57193528797
dc.authorscopusid56082620300
dc.authorscopusid55376663700
dc.identifier.scopus2-s2.0-85123687967en_US


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