• Journal of Digestive Cancer Research
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• v.10 no.2
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• pp.99-106
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• 2022

Clinical research ultimately aimed to promptly diagnose and prevent diseases through precise biomarker development. Finding the optimal cut-off point of a regularly measured biomarker can help its interpretation and ultimately help in disease investigation and diagnosis, more specifically in determining the presence of diseases. Therefore, this study aimed to use the characteristics of outcome variables in clinical research to explain how to determine the optimal cutoff point. The outcome variables can be divided into dichotomous, ordinal, and survival types. The optimal cut-off point can be determined by finding points that maximize the Youden index, extended Youden index, and log-rank statistics. This study will enable clinical researchers to accurately determine the optimal cut-off points for regularly measured biomarkers, thereby enabling prompt disease diagnosis for effective treatment.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.4
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• pp.1651-1655
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• 2012

Background: Our aim was to investigate the efficacy of the Pap test in combination with the ThinPrep cytological test (TCT) in screening for cervical cancer in China. Design: From March 2006 to October 2008, 988 women with the mean age $46.4{\pm}10.5$ years (range, 23-80 years) were recruited to receive cervical cancer screening. Pap test results ${\geq}$ grade III and TCT findings ${\geq}$ ASCUS/AGUS were considered abnormal. Subjects with a Pap test result ${\geq}$ grade IIb received TCT. Colposcopy and biopsies were performed in all participants, and final diagnosis was based on pathological findings. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and Youden index for predicting CIN I or above were determined. Results: The sensitivity, specificity, PPV, NPV and Youden index of the Pap test were 43.1%, 97.2%, 70.0%, 91.9%, and 40.3%, respectively. The same values for TCT in predicting CIN were 80.0%, 63.2%, 16.0%, 97.3%, and 43.2%, respectively. The two tests in combination gave values for predicting CIN of 64.8%, 87.6%, 43.6%, 94.4%, and 53.5%, respectively. Combined testing exhibited the highest Youden index (53.4%). Conclusion: The Pap test with a reduced threshold in combination with the TCT has high sensitivity and high specificity in screening for cervical cancer.

• Gut and Liver
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• v.12 no.6
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• pp.655-663
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• 2018

Background/Aims: The association between metabolic syndrome and colorectal cancer (CRC) has been suggested as one of causes for the increasing incidence of CRC, particularly in younger age groups. The present study examined whether the current age threshold (50 years) for CRC screening in Korea requires modification when considering increased metabolic syndrome. Methods: We analyzed data from the National Health Insurance Corporation database, which covers ~97% of the population in Korea. CRC risk was evaluated with stratification based on age and the presence/absence of relevant metabolic syndrome components (diabetes, dyslipidemia, and hypertension). Results: A total of 51,612,316 subjects enrolled during 2014 to 2015 were analyzed. Among them, 19.3% had diabetes, hypertension, dyslipidemia, or some combination thereof. This population had a higher incidence of CRC than did those without these conditions, and this was more prominent in subjects <40 years of age. The optimal cutoff age for detecting CRC, based on the highest Youden index, was 45 years among individuals without diabetes, dyslipidemia, and hypertension. Individuals with at least one of these components of metabolic syndrome had the highest Youden index at 62 years old, but the value was only 0.2. Resetting the cutoff age from 50 years to 45 years achieved a 6% increase in sensitivity for CRC detection among the total population. Conclusions: Starting CRC screening earlier, namely, at 45 rather than at 50 years of age, may improve secondary prevention of CRC in Korea.

• Korean Journal of Community Nutrition
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• v.19 no.5
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• pp.490-498
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• 2014

Objectives: This study was conducted to propose the need of re-establishing the criteria of the body weight classification in the elderly. We compared the Asia-Pacific Region Criteria (APR-C) with Entropy Model Criteria (ENT-C) using Morbidity rate of chronic diseases which correlates significantly with Body Mass Index (BMI). Methods: Subjects were 886 elderly female participating in the 2007-2009 Korea National Health and Nutrition Examination Survey (KNHANES). We compared APR-C with those of ENT-C using Receiver Operating Characteristics (ROC) curve and logistic regression analysis. Results: In the case of the morbidity of hypertension, the results were as follows: Where it was in the T-off point of APR-C, sensitivity was 67.5%, specificity was 43.1%, and Youden's index was 10.6. While in the cut-off point of ENT-C, it was 56.7%, 56.6%, and 13.3 respectively. In the case of the morbidity of diabetes, the results were as follows: In the cut-off point of APR-C, Youden's index was 14.2. While in the cut-off point of ENT-C, it was 17.2 respectively. The Area Under the ROC Curve (AUC) of the subjects who had more than 2 diseases among hypertension, diabetes, and dyslipidemia was 0.615 (95% CI: 0.578-0.652). Compared to the normal group, the odds ratio of the hypertension group which will belong to the overweight or obesity was 1.79 (95% CI: 1.30-2.47) in the APR-C, and 2.04 (95% CI: 1.49-2.80) in the ENT-C (p < 0.001). Conclusions: We conclude that the optimal cut-off point of BMI to distinguish between normal weight and overweight was $24kg/m^2$ (ENT-C) rather than $23kg/m^2$ (APR-C).

• Communications for Statistical Applications and Methods
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• v.18 no.3
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• pp.343-355
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• 2011

For a data with the assumption of the mixture distribution, it is important to find an appropriate threshold and evaluate its performance. The relationship is found of well-known nine classification accuracy measures such as MVD, Youden's index, the closest-to-(0, 1) criterion, the amended closest-to-(0, 1) criterion, SSS, symmetry point, accuracy area, TA, TR. Then some conditions of these measures are categorized into seven groups. Under the normal mixture assumption, we calculate thresholds based on these measures and obtain the corresponding type I and II errors. We could explore that which classification measure has minimum type I and II errors for estimated mixture distribution to understand the strength and weakness of these classification measures.

• Nutrition Research and Practice
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• v.13 no.3
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• pp.247-255
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• 2019

BACKGROUND/OBJECTIVES: Accurate, early identification of acutely malnourished children has the potential to reduce related child morbidity and mortality. The current World Health Organisation (WHO) guidelines classify non-oedematous acute malnutrition among children under five using Mid-Upper Arm Circumference (MUAC) or Weight-for-Height Z-score (WHZ). However, there is ongoing debate regarding the use of current MUAC cut-offs. This study investigates the diagnostic performance of MUAC to identify children aged 6-24 months with global (GAM) or severe acute malnutrition (SAM). SUBJECTS/METHODS: Cross-sectional, secondary data from a community sample of children aged 6-24 months in Niger were used for this study. Children with complete weight, height and MUAC data and without clinical oedema were included. Using WHO guidelines for GAM (WHZ < -2, MUAC < 12.5 cm) and SAM (WHZ < -3, MUAC < 11.5 cm), the sensitivity (Se), specificity (Sp), predictive values, Youden Index and Receiver Operating Characteristic (ROC) curves were calculated for MUAC when compared with the WHZ reference criterion. RESULTS: Of 1161 children, 23.3% were diagnosed with GAM using WHZ, and 4.4% with SAM. Using current WHO cut-offs, the Se of MUAC to identify GAM was greater than for SAM (79 vs. 57%), yet the Sp was lower (84 vs. 97%). From inspection of the ROC curve and Youden Index, Se and Sp were maximised for MUAC < 12.5 cm to identify GAM (Se 79%, Sp 84%), and MUAC < 12.0 cm to identify SAM (Se 88%, Sp 81%). CONCLUSIONS: The current MUAC cut-off to identify GAM should continue to be used, but when screening for SAM, a higher cut-off could improve case identification. Community screening for SAM could use MUAC < 12.0 cm followed by appropriate treatment based on either MUAC < 11.5 cm or WHZ < -3, as in current practice. While the practicalities of implementation must be considered, the higher SAM MUAC cut-off would maximise early case-finding of high-risk acutely malnourished children.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.619-630
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• 2011

In order to estimate an appropriate threshold and evaluate its performance for the data mixed with two different distributions, nine kinds of well-known classification accuracy measures such as MVD, Youden's index, the closest-to- (0,1) criterion, the amended closest-to- (0,1) criterion, SSS, symmetry point, accuracy area, TA, TR are clustered into five categories on the basis of their characters. In credit evaluation study, it is assumed that the score random variable follows normal mixture distributions of the default and non-default states. For various normal mixtures, optimal cut-off points for classification measures belong to each category are obtained and type I and II error rates corresponding to these cut-off points are calculated. Then we explore the cases when these error rates are minimized. If normal mixtures might be estimated for these kinds of real data, we could make use of results of this study to select the best classification accuracy measure which has the minimum error rate.

• Nutrition Research and Practice
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• v.14 no.1
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• pp.20-24
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• 2020

BACKGROUND/OBJECTIVES: Malnutrition has multiple impacts on surgical success, postoperative complications, duration of hospital stay, and costs, particularly for cancer patients. There are various nutrition risk screening tools available for clinical use. Herein, we aim to determine the most appropriate nutritional risk screening system for esophageal cancer (EC) patients in China. SUBJECTS/METHODS: In total, 138 EC patients were enrolled in this study and evaluated by experienced nurses using three different nutritional screening tools, the Nutrition Risk Screening 2002 tool (NRS2002), the Patient-generated Subjective Globe Assessment (PG-SGA), and the Nutrition Risk Index (NRI).We compared sensitivity, specificity, positive and negative likelihood ratios, and Youden index generated by each of the three screening tools. Finally, cut-off points for all three tools were re-defined to optimize and validate the best nutritional risk screening tool for assessing EC patients. RESULTS: Our data suggested that all three screening tools were 100% sensitive for EC patients, while the specificities were 44.4%, 2.96%, and 59.26% for NRS 2002, PG-SGA, and NRI, respectively. NRI had a higher positive likelihood ratio as well as a higher area under the receiver operating characteristic curve compared to those of NRS 2002 and PG-SGA; although, all three tools had null negative likelihood ratios. After adjusting the cut-off points, the specificity and accuracy for all tools were significantly improved, however, the NRI remained the most appropriate nutritional risk screening system for EC patients. CONCLUSIONS: The NRI is the most suitable (highest sensitivity and accuracy) nutritional risk screening tool for EC patients. The performance of the NRI can be significantly improved if the cut-off point is modified according to the results obtained using MedCalc software.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1489-1496
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• 2013

Consider the ROC surface which is a generalization of the ROC curve for three-class diagnostic problems. In this work, we propose ve criteria for the three-class ROC surface by extending the Youden index, the sum of sensitivity and specificity, the maximum vertical distance, the amended closest-to-(0,1) and the true rate. It may be concluded that these five criteria can be expressed as a function of two Kolmogorov-Smirnov statistics. A paired optimal thresholds could be obtained simultaneously from the ROC surface. It is found that the paired optimal thresholds selected from the ROC surface are equivalent to the two optimal thresholds found from the two ROC curves.

• The Journal of Internal Korean Medicine
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• v.35 no.4
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• pp.483-497
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• 2014

Objectives: The aims of study were developing cut-off value of Yin-deficiency questionnaire (YDQ) for diagnosis of Yin-deficiency (YD) and compare diagnostic ability between YDQ and Yin-deficiency scale score (YDS) in xerostomia patients. Methods: We recruited 58 xerostomia patients. They were diagnosed YD or non-YD by 3 Korean medicine doctors (KMD). We assessed YD using YDQ and YDS. We evaluated xerostomia using VAS, Dry Mouth Symptom Questionnaire (DMSQ), Salivary Flow Rate (SFR), oral moisture on buccal mucosa and tongue surface (OMB and OMT). We surveyed tongue coatings using Winkel Tongue Coating Index (WTCI). Results: We diagnosed 23 patients YD and 35 patients non-YD. There were no significant differences of age, sex and body mass index between the YD and non-YD groups. Using receiver operating characteristic curve analysis, the optimal cut-off value of YDQ was defined as 304. Sensitivity, specificity and Youden index of YDQ were 86.96%, 71.43% and 1.5839 respectively. Using Cohen's coefficient of agreement, we found that degree of agreement between KMD and YDQ diagnosis was moderate (${\kappa}$=0.524, p<0.001). Using Pearson's correlation analysis, we found concurrent validity of YDQ and YDS were significant correlated. Using area under curve value, we found diagnostic ability between YDQ and YDS were not significantly different (p=0.505), but there were more strong correlations between DMSQ-symptoms and YDQ (r=0.731, p<0.001) than correlations between DMSQ-symptoms and YDS (r=0.418, p<0.01). Conclusions: The cut-off value of YDQ can diagnose YD in xerostomia and diagnostic ability of YDQ in xerostomia is better than YDS.