• Journal of Breast Disease
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• v.6 no.2
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• pp.52-59
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• 2018

Purpose: This study aimed to determine whether clinicopathological factors are potentially associated with successful breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NAC) and develop a nomogram for predicting successful BCS candidates, focusing on those who are diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative tumors during the pre-NAC period. Methods: The training cohort included 239 patients with an HR-positive, HER2-negative tumor (${\geq}3cm$), and all of these patients had received NAC. Patients were excluded if they met any of the following criteria: diffuse, suspicious, malignant microcalcification (extent >4 cm); multicentric or multifocal breast cancer; inflammatory breast cancer; distant metastases at the time of diagnosis; excisional biopsy prior to NAC; and bilateral breast cancer. Multivariate logistic regression analysis was conducted to evaluate the possible predictors of BCS eligibility after NAC, and the regression model was used to develop the predicting nomogram. This nomogram was built using the training cohort (n=239) and was later validated with an independent validation cohort (n=123). Results: Small tumor size (p<0.001) at initial diagnosis, long distance from the nipple (p=0.002), high body mass index (p=0.001), and weak positivity for progesterone receptor (p=0.037) were found to be four independent predictors of an increased probability of BCS after NAC; further, these variables were used as covariates in developing the nomogram. For the training and validation cohorts, the areas under the receiver operating characteristic curve were 0.833 and 0.786, respectively; these values demonstrate the potential predictive power of this nomogram. Conclusion: This study established a new nomogram to predict successful BCS in patients with HR-positive, HER2-negative breast cancer. Given that chemotherapy is an option with unreliable outcomes for this subtype, this nomogram may be used to select patients for NAC followed by successful BCS.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.3
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• pp.1481-1488
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• 2014

Background: To avoid performing axillary lymph node dissection (ALND) for non-sentinel lymph node (SLN)-negative patients with-SLN positive axilla, nomograms for predicting the status have been developed in many centers. We created a new nomogram predicting non-SLN metastasis in SLN-positive patients with invasive breast cancer and evaluated 14 existing breast cancer models in our patient group. Materials and Methods: Two hundred and thirty seven invasive breast cancer patients with SLN metastases who underwent ALND were included in the study. Based on independent predictive factors for non-SLN metastasis identified by logistic regression analysis, we developed a new nomogram. Receiver operating characteristics (ROC) curves for the models were created and the areas under the curves (AUC) were computed. Results: In a multivariate analysis, tumor size, presence of lymphovascular invasion, extranodal extension of SLN, large size of metastatic SLN, the number of negative SLNs, and multifocality were found to be independent predictive factors for non-SLN metastasis. The AUC was found to be 0.87, and calibration was good for the present Ondokuz Mayis nomogram. Among the 14 validated models, the MSKCC, Stanford, Turkish, MD Anderson, MOU (Masaryk), Ljubljana, and DEU models yielded excellent AUC values of > 0.80. Conclusions: We present a new model to predict the likelihood of non-SLN metastasis. Each clinic should determine and use the most suitable nomogram or should create their own nomograms for the prediction of non- SLN metastasis.

• Korean Journal of Radiology
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• v.25 no.10
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• pp.876-886
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• 2024

Objective: To develop a nomogram that integrates clinical-pathologic and imaging variables to predict ipsilateral breast tumor recurrence (IBTR) in women with ductal carcinoma in situ (DCIS) treated with breast-conserving surgery (BCS). Materials and Methods: This retrospective study included consecutive women with DCIS who underwent BCS at two hospitals. Patients who underwent BCS between 2003 and 2016 in one hospital and between 2005 and 2013 in another were classified into development and validation cohorts, respectively. Twelve clinical-pathologic variables (age, family history, initial presentation, nuclear grade, necrosis, margin width, number of excisions, DCIS size, estrogen receptor, progesterone receptor, radiation therapy, and endocrine therapy) and six mammography and ultrasound variables (breast density, detection modality, mammography and ultrasound patterns, morphology and distribution of calcifications) were analyzed. A nomogram for predicting 10-year IBTR probabilities was constructed using the variables associated with IBTR identified from the Cox proportional hazard regression analysis in the development cohort. The performance of the developed nomogram was evaluated in the external validation cohort using a calibration plot and 10-year area under the receiver operating characteristic curve (AUROC) and compared with the Memorial Sloan-Kettering Cancer Center (MSKCC) nomogram. Results: The development cohort included 702 women (median age [interquartile range], 50 [44-56] years), of whom 30 (4%) women experienced IBTR. The validation cohort included 182 women (48 [43-54] years), 18 (10%) of whom developed IBTR. A nomogram was constructed using three clinical-pathologic variables (age, margin, and use of adjuvant radiation therapy) and two mammographic variables (breast density and calcification morphology). The nomogram was appropriately calibrated and demonstrated a comparable 10-year AUROC to the MSKCC nomogram (0.73 vs. 0.66, P = 0.534) in the validation cohort. Conclusion: Our nomogram provided individualized risk estimates for women with DCIS treated with BCS, demonstrating a discriminative ability comparable to that of the MSKCC nomogram.

• Radiation Oncology Journal
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• v.36 no.2
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• pp.139-146
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• 2018

Purpose: IBTR! 2.0 nomogram is web-based nomogram that predicts ipsilateral breast tumor recurrence (IBTR). We aimed to validate the IBTR! 2.0 using an external data set. Materials and Methods: The cohort consisted of 2,206 patients, who received breast conserving surgery and radiation therapy from 1992 to 2012 at our institution, where wide surgical excision is been routinely performed. Discrimination and calibration were used for assessing model performance. Patients with predicted 10-year IBTR risk based on an IBTR! 2.0 nomogram score of <3%, 3%-5%, 5%-10%, and >10% were assigned to groups 1, 2, 3, and 4, respectively. We also plotted calibration values to observe the actual IBTR rate against the nomogram-derived 10-year IBTR probabilities. Results: The median follow-up period was 73 months (range, 6 to 277 months). The area under the receiver operating characteristic curve was 0.607, showing poor accordance between the estimated and observed recurrence rate. Calibration plot confirmed that the IBTR! 2.0 nomogram predicted the 10-year IBTR risk higher than the observed IBTR rates in all groups. High discrepancies between nomogram IBTR predictions and observed IBTR rates were observed in overall risk groups. Compared with the original development dataset, our patients had fewer high grade tumors, less margin positivity, and less lymphovascular invasion, and more use of modern systemic therapies. Conclusions: IBTR! 2.0 nomogram seems to have the moderate discriminative ability with a tendency to over-estimating risk rate. Continued efforts are needed to ensure external applicability of published nomograms by validating the program using an external patient population.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.12
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• pp.6181-6185
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• 2012

Background: The aim of the study was to evaluate the available breast nomograms (MSKCC, Stanford, Tenon) to predict non-sentinel lymph node metastasis (NSLNM) and to determine variables for NSLNM in SLN positive breast cancer patients in our population. Materials and Methods: We retrospectively reviewed 170 patients who underwent completion axillary lymph node dissection between Jul 2008 and Aug 2010 in our hospital. We validated three nomograms (MSKCC, Stanford, Tenon). The likelihood of having positive NSLNM based on various factors was evaluated by use of univariate analysis. Stepwise multivariate analysis was applied to estimate a predictive model for NSLNM. Four factors were found to contribute significantly to the logistic regression model, allowing design of a new formula to predict non-sentinel lymph node metastasis. The AUCs of the ROCs were used to describe the performance of the diagnostic value of MSKCC, Stanford, Tenon nomograms and our new nomogram. Results: After stepwise multiple logistic regression analysis, multifocality, proportion of positive SLN to total SLN, LVI, SLN extracapsular extention were found to be statistically significant. AUC results were MSKCC: 0.713/Tenon: 0.671/Stanford: 0.534/DEU: 0.814. Conclusions: The MSKCC nomogram proved to be a good discriminator of NSLN metastasis in SLN positive BC patients for our population. Stanford and Tenon nomograms were not as predictive of NSLN metastasis. Our newly created formula was the best prediction tool for discriminate of NSLN metastasis in SLN positive BC patients for our population. We recommend that nomograms be validated before use in specific populations, and more than one validated nomogram may be used together while consulting patients.