• 제목/요약/키워드: nomograms

검색결과 27건 처리시간 0.022초

Validation of Three Breast Cancer Nomograms and a New Formula for Predicting Non-sentinel Lymph Node Status

  • Derici, Serhan;Sevinc, Ali;Harmancioglu, Omer;Saydam, Serdar;Kocdor, Mehmet;Aksoy, Suleyman;Egeli, Tufan;Canda, Tulay;Ellidokuz, Hulya;Derici, Solen
    • Asian Pacific Journal of Cancer Prevention
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    • 제13권12호
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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.

고혈압 예측을 위한 노모그램 구축 및 비교 (Comparison of nomograms designed to predict hypertension with a complex sample)

  • 김민호;신민석;이제영
    • 응용통계연구
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    • 제33권5호
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    • pp.555-567
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    • 2020
  • 고혈압은 발병률이 꾸준히 증가하고 있을 뿐 아니라, 심혈관 질환과 같은 2차 질병의 주된 위험 요인이 되었다. 게다가 고혈압은 뇌졸중, 혈관성 치매와 같은 다른 합병증을 유발하는 질병이다. 따라서 고혈압 발병률을 예측하는 것은 중요한 일이다. 본 연구에서, 고혈압 발병률을 예측할 수 있는 노모그램을 구축하였다. 데이터는 2013년부터 2016년까지의 국민건강영양조사로부터 얻어졌다. 복합 표본의 특성을 고려하여 Rao-Scott chi-squared test를 통해 고혈압에 영향을 미치는 10가지 요인을 규명하였다. 하지만 로지스틱 회귀분석 시, 흡연 상태와, 운동 유무는 유의하지 않았다. 따라서 8개의 주 효과를 고혈압의 위험요인으로 최종 선별하였다. 그리고 최종 선별된 위험 요인들로 로지스틱 노모그램과 베이지안 노모그램을 제시 및 비교하였다. 마지막으로 ROC curve 그래프와 calibration plot을 통해 노모그램을 검증하였다.

Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation

  • Moon, Kyoung Yong;Kim, Hoon;Lee, Joong Yeup;Lee, Jung Ryeol;Jee, Byung Chul;Suh, Chang Suk;Kim, Ki Chul;Lee, Won Don;Lim, Jin Ho;Kim, Seok Hyun
    • Clinical and Experimental Reproductive Medicine
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    • 제43권2호
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    • pp.112-118
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    • 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.

만성 폐쇄성 폐질환을 이용한 노모그램 구축과 비교 (Comparison of nomogram construction methods using chronic obstructive pulmonary disease)

  • 서주현;이제영
    • 응용통계연구
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    • 제31권3호
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    • pp.329-342
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    • 2018
  • 노모그램은 질병의 위험 요인과 예측 확률을 쉽게 이해할 수 있도록 시각적으로 표현하는 통계적 도구이다. 본 논문은 만성 폐쇄성 폐질환(chronic obstructive pulmonary disease)의 위험 요인을 이용하여 로지스틱 회귀모형과 순수 베이지안 분류기 모형의 노모그램을 구축하고 이를 비교하였다. 분석 데이터는 국민건강영양조사 6기(2013-2015)를 이용하여 진행하였다. 총 6개의 위험 요인을 이용하였다. 그리고 로지스틱 회귀모형, 순수 베이지안 분류기 모형과 각각의 구축 방법을 이용하여 만성 폐쇄성 폐질환의 노모그램을 제시하였다. 또한, 구축된 두 노모그램을 비교하여 유용성을 살펴보았다. 마지막으로 ROC curve와 Calibration plot을 통하여 각 노모그램을 검증하였다.

A Breast Cancer Nomogram for Prediction of Non-Sentinel Node Metastasis - Validation of Fourteen Existing Models

  • Koca, Bulent;Kuru, Bekir;Ozen, Necati;Yoruker, Savas;Bek, Yuksel
    • Asian Pacific Journal of Cancer Prevention
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    • 제15권3호
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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.

External Validation of a Gastric Cancer Nomogram Derived from a Large-volume Center Using Dataset from a Medium-volume Center

  • Kim, Pyeong Su;Lee, Kyung-Muk;Han, Dong-Seok;Yoo, Moon-Won;Han, Hye Seung;Yang, Han-Kwang;Bang, Ho Yoon
    • Journal of Gastric Cancer
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    • 제17권3호
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    • pp.204-211
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    • 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.

Novel nomogram-based integrated gonadotropin therapy individualization in in vitro fertilization/intracytoplasmic sperm injection: A modeling approach

  • Ebid, Abdel Hameed IM;Motaleb, Sara M Abdel;Mostafa, Mahmoud I;Soliman, Mahmoud MA
    • Clinical and Experimental Reproductive Medicine
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    • 제48권2호
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    • pp.163-173
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    • 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-Emax, 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.

Nomogram Models for Distinguishing Intraductal Carcinoma of the Prostate From Prostatic Acinar Adenocarcinoma Based on Multiparametric Magnetic Resonance Imaging

  • Ling Yang;Xue-Ming Li;Meng-Ni Zhang;Jin Yao;Bin Song
    • Korean Journal of Radiology
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    • 제24권7호
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    • pp.668-680
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    • 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.

A semiparametric method to measure predictive accuracy of covariates for doubly censored survival outcomes

  • Han, Seungbong;Lee, JungBok
    • Communications for Statistical Applications and Methods
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    • 제23권4호
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    • pp.343-353
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    • 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.

다구찌방법을 이용한 디프드로잉 공정의 가공성평가에 대한 연구 (A Study on the Formability Estimation of Deep Drawing Process by using Taguchi Method)

  • 이병찬;강연식;양동열;문재호
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1996년도 추계학술대회 논문집
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    • pp.938-942
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    • 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.

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