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

• The Korean Journal of Applied Statistics
• /
• v.33 no.5
• /
• pp.555-567
• /
• 2020

Hypertension has a steadily increasing incidence rate as well as represents a risk factors for secondary diseases such as cardiovascular disease. Therefore, it is important to predict the incidence rate of the disease. In this study, we constructed nomograms that can predict the incidence rate of hypertension. We use data from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. The complex sampling data required the use of a Rao-Scott chi-squared test to identify 10 risk factors for hypertension. Smoking and exercise variables were not statistically significant in the Logistic regression; therefore, eight effects were selected as risk factors for hypertension. Logistic and Bayesian nomograms constructed from the selected risk factors were proposed and compared. The constructed nomograms were then verified using a receiver operating characteristics curve and calibration plot.

• Clinical and Experimental Reproductive Medicine
• /
• v.43 no.2
• /
• pp.112-118
• /
• 2016

Objective: Ovarian reserve tests are commonly used to predict ovarian response in infertile patients undergoing ovarian stimulation. Although serum markers such as basal follicle-stimulating hormone (FSH) or random $anti-M{\ddot{u}}llerian$ hormone (AMH) level and ultrasonographic markers (antral follicle count, AFC) are good predictors, no single test has proven to be the best predictor. In this study, we developed appropriate equations and novel nomograms to predict the number of oocytes that will be retrieved using patients' age, serum levels of basal FSH and AMH, and AFC. Methods: We analyzed a database containing clinical and laboratory information of 141 stimulated in vitro fertilization (IVF) cycles performed at a university-based hospital between September 2009 and December 2013. We used generalized linear models for prediction of the number of oocytes. Results: Age, basal serum FSH level, serum AMH level, and AFC were significantly related to the number of oocytes retrieved according to the univariate and multivariate analyses. The equations that predicted the number of oocytes retrieved (log scale) were as follows: model (1) $3.21-0.036{\times}(age)+0.089{\times}(AMH)$, model (2) $3.422-0.03{\times}(age)-0.049{\times}(FSH)+0.08{\times}(AMH)$, model (3) $2.32-0.017{\times}(age)+0.039{\times}(AMH)+0.03{\times}(AFC)$, model (4) $2.584-0.015{\times}(age)-0.035{\times}(FSH)+0.038{\times}(AMH)+0.026{\times}(AFC)$. model 4 showed the best performance. On the basis of these variables, we developed nomograms to predict the number of oocytes that can be retrieved. Conclusion: Our nomograms helped predict the number of oocytes retrieved in stimulated IVF cycles.

• The Korean Journal of Applied Statistics
• /
• v.31 no.3
• /
• pp.329-342
• /
• 2018

Nomogram is a statistical tool that visualizes the risk factors of the disease and then helps to understand the untrained people. This study used risk factors of chronic obstructive pulmonary disease (COPD) and compared with logistic regression model and naïve Bayesian classifier model. Data were analyzed using the Korean National Health and Nutrition Examination Survey 6th (2013-2015). First, we used 6 risk factors about COPD. We constructed nomogram using logistic regression model and naïve Bayesian classifier model. We also compared the nomograms constructed using the two methods to find out which method is more appropriate. The receiver operating characteristic curve and the calibration plot were used to verify each nomograms.

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

• Journal of Gastric Cancer
• /
• v.17 no.3
• /
• pp.204-211
• /
• 2017

Purpose: Recently, a nomogram predicting overall survival after gastric resection was developed and externally validated in Korea and Japan. However, this gastric cancer nomogram is derived from large-volume centers, and the applicability of the nomogram in smaller centers must be proven. The purpose of this study is to externally validate the gastric cancer nomogram using a dataset from a medium-volume center in Korea. Materials and Methods: We retrospectively analyzed 610 patients who underwent radical gastrectomy for gastric cancer from August 1, 2005 to December 31, 2011. Age, sex, number of metastatic lymph nodes (LNs), number of examined LNs, depth of invasion, and location of the tumor were investigated as variables for validation of the nomogram. Both discrimination and calibration of the nomogram were evaluated. Results: The discrimination was evaluated using Harrell's C-index. The Harrell's C-index was 0.83 and the discrimination of the gastric cancer nomogram was appropriate. Regarding calibration, the 95% confidence interval of predicted survival appeared to be on the ideal reference line except in the poorest survival group. However, we observed a tendency for actual survival to be constantly higher than predicted survival in this cohort. Conclusions: Although the discrimination power was good, actual survival was slightly higher than that predicted by the nomogram. This phenomenon might be explained by elongated life span in the recent patient cohort due to advances in adjuvant chemotherapy and improved nutritional status. Future gastric cancer nomograms should consider elongated life span with the passage of time.

• Clinical and Experimental Reproductive Medicine
• /
• v.48 no.2
• /
• pp.163-173
• /
• 2021

Objective: This study aimed to characterize a validated model for predicting oocyte retrieval in controlled ovarian stimulation (COS) and to construct model-based nomograms for assistance in clinical decision-making regarding the gonadotropin protocol and dose. Methods: This observational, retrospective, cohort study included 636 women with primary unexplained infertility and a normal menstrual cycle who were attempting assisted reproductive therapy for the first time. The enrolled women were split into an index group (n=497) for model building and a validation group (n=139). The primary outcome was absolute oocyte count. The dose-response relationship was tested using modified Poisson, negative binomial, hybrid Poisson-E_max, and linear models. The validation group was similarly analyzed, and its results were compared to that of the index group. Results: The Poisson model with the log-link function demonstrated superior predictive performance and precision (Akaike information criterion, 2,704; λ=8.27; relative standard error (λ)=2.02%). The covariate analysis included women's age (p<0.001), antral follicle count (p<0.001), basal follicle-stimulating hormone level (p<0.001), gonadotropin dose (p=0.042), and protocol type (p=0.002 and p<0.001 for short and antagonist protocols, respectively). The estimates from 500 bootstrap samples were close to those of the original model. The validation group showed model assessment metrics comparable to the index model. Based on the fitted model, a static nomogram was built to improve visualization. In addition, a dynamic electronic tool was created for convenience of use. Conclusion: Based on our validated model, nomograms were constructed to help clinicians individualize the stimulation protocol and gonadotropin doses in COS cycles.

• Korean Journal of Radiology
• /
• v.24 no.7
• /
• pp.668-680
• /
• 2023

Objective: To compare multiparametric magnetic resonance imaging (MRI) features of intraductal carcinoma of the prostate (IDC-P) with those of prostatic acinar adenocarcinoma (PAC) and develop prediction models to distinguish IDC-P from PAC and IDC-P with a high proportion (IDC ≥ 10%, hpIDC-P) from IDC-P with a low proportion (IDC < 10%, lpIDC-P) and PAC. Materials and Methods: One hundred and six patients with hpIDC-P, 105 with lpIDC-P and 168 with PAC, who underwent pretreatment multiparametric MRI between January 2015 and December 2020 were included in this study. Imaging parameters, including invasiveness and metastasis, were evaluated and compared between the PAC and IDC-P groups as well as between the hpIDC-P and lpIDC-P subgroups. Nomograms for distinguishing IDC-P from PAC, and hpIDC-P from lpIDC-P and PAC, were made using multivariable logistic regression analysis. The discrimination performance of the models was assessed using the receiver operating characteristic area under the curve (ROC-AUC) in the sample, where the models were derived from without an independent validation sample. Results: The tumor diameter was larger and invasive and metastatic features were more common in the IDC-P than in the PAC group (P < 0.001). The distribution of extraprostatic extension (EPE) and pelvic lymphadenopathy was even greater, and the apparent diffusion coefficient (ADC) ratio was lower in the hpIDC-P than in the lpIDC-P group (P < 0.05). The ROC-AUCs of the stepwise models based solely on imaging features for distinguishing IDC-P from PAC and hpIDC-P from lpIDC-P and PAC were 0.797 (95% confidence interval, 0.750-0.843) and 0.777 (0.727-0.827), respectively. Conclusion: IDC-P was more likely to be larger, more invasive, and more metastatic, with obviously restricted diffusion. EPE, pelvic lymphadenopathy, and a lower ADC ratio were more likely to occur in hpIDC-P, and were also the most useful variables in both nomograms for predicting IDC-P and hpIDC-P.

• Communications for Statistical Applications and Methods
• /
• v.23 no.4
• /
• pp.343-353
• /
• 2016

In doubly-censored data, an originating event time and a terminating event time are interval-censored. In certain analyses of such data, a researcher might be interested in the elapsed time between the originating and terminating events as well as regression modeling with risk factors. Therefore, in this study, we introduce a model evaluation method to measure the predictive ability of a model based on negative predictive values. We use a semiparametric estimate of the predictive accuracy to provide a simple and flexible method for model evaluation of doubly-censored survival outcomes. Additionally, we used simulation studies and tested data from a prostate cancer trial to illustrate the practical advantages of our approach. We believe that this method could be widely used to build prediction models or nomograms.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.11a
• /
• pp.938-942
• /
• 1996

Despite the increasing demand for improved product design, a limited number of works have been reported in the field of sheet metal forming. In the present study, introducing the Taguchi method, an optimal and robust combination of parameters is found and a data base management system and nomograms are utilized for knowledge acquisition. The developed system is applied to a deep drawing process, Through the present study, it is shown that the developed system is useful for the design and the formability estimation of sheet metal forming processes.