Academic literature on the topic 'Youden index method'
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Journal articles on the topic "Youden index method"
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Larner, Andrew J. "Optimising the Cutoffs of Cognitive Screening Instruments in Pragmatic Diagnostic Accuracy Studies: Maximising Accuracy or the Youden Index?" Dementia and Geriatric Cognitive Disorders 39, no. 3-4 (2015): 167–75. http://dx.doi.org/10.1159/000369883.
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Background/Aims: The optimal method of establishing test cutoffs or cutpoints for cognitive screening instruments (CSIs) is uncertain. Of the available methods, two base cutoffs on either the maximal test accuracy or the maximal Youden index. The aim of this study was to compare the effects of using these alternative methods of establishing cutoffs. Methods: Datasets from three pragmatic diagnostic accuracy studies which examined the Mini-Mental State Examination (MMSE), the Addenbrooke's Cognitive Examination-Revised (ACE-R), the Montreal Cognitive Assessment (MoCA), and the Test Your Memory (TYM) test were analysed to calculate test sensitivity and specificity using cutoffs based on either maximal test accuracy or the maximal Youden index. Results: For ACE-R, MoCA, and TYM, optimal cutoffs for dementia diagnosis differed from those in index studies when defined using either the maximal accuracy or the maximal Youden index method. Optimal cutoffs were higher for MMSE, MoCA, and TYM when using the maximal Youden index method and consequently more sensitive. Conclusion: Revision of the cutoffs for CSIs established in index studies may be required to optimise performance in pragmatic diagnostic test accuracy studies which more closely resemble clinical practice.
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Thiele, Christian, and Gerrit Hirschfeld. "Confidence intervals and sample size planning for optimal cutpoints." PLOS ONE 18, no. 1 (January 3, 2023): e0279693. http://dx.doi.org/10.1371/journal.pone.0279693.
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Various methods are available to determine optimal cutpoints for diagnostic measures. Unfortunately, many authors fail to report the precision at which these optimal cutpoints are being estimated and use sample sizes that are not suitable to achieve an adequate precision. The aim of the present study is to evaluate methods to estimate the variance of cutpoint estimations based on published descriptive statistics (‘post-hoc’) and to discuss sample size planning for estimating cutpoints. We performed a simulation study using widely-used methods to optimize the Youden index (empirical, normal, and transformed normal method) and three methods to determine confidence intervals (the delta method, the parametric bootstrap, and the nonparametric bootstrap). We found that both the delta method and the parametric bootstrap are suitable for post-hoc calculation of confidence intervals, depending on the sample size, the distribution of marker values, and the correctness of model assumptions. On average, the parametric bootstrap in combination with normal-theory-based cutpoint estimation has the best coverage. The delta method performs very well for normally distributed data, except in small samples, and is computationally more efficient. Obviously, not every combination of distributions, cutpoint optimization methods, and optimized metrics can be simulated and a lot of the literature is concerned specifically with cutpoints and confidence intervals for the Youden index. This complicates sample size planning for studies that estimate optimal cutpoints. As a practical tool, we introduce a web-application that allows for running simulations of width and coverage of confidence intervals using the percentile bootstrap with various distributions and cutpoint optimization methods.
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Husaiyin, Sulaiya, Zhen Jiao, Kailibinuer Yimamu, Reyilanmu Maisaidi, Lili Han, and Mayinuer Niyazi. "ThinPrep cytology combined with HPV detection in the diagnosis of cervical lesions in 1622 patients." PLOS ONE 16, no. 12 (December 2, 2021): e0260915. http://dx.doi.org/10.1371/journal.pone.0260915.
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The timely detection of precancerous lesions and early intervention can greatly reduce cervical cancer occurrence. The current study aimed to assess the diagnostic value and accuracy of different methods of cervical lesion screening. A total of 1622 females who visited the Outpatient Department of Xinjiang Uyghur Autonomous Region People’s Hospital between January and December 2018 were consecutively enrolled. All participants underwent separate high-risk human papilloma virus (HR-HPV) DNA detection, ThinPrep cytology testing (TCT) and colposcopic biopsy. Their medical records were retrospectively analyzed. While considering biopsy outcomes as the gold standard, the diagnostic values of TCT, HR-HPV testing, and TCT+HR-HPV testing for cervical cancer screening were compared. The sensitivity, specificity and Youden index of each method were calculated. Among the different methods, TCT+HR-HPV testing had the highest sensitivity (89.8%), followed by TCT (79.9%) and HR-HPV testing (49.2%). The combined method also had the highest Youden value, and its screening outcomes exhibited the highest consistency with those of biopsy. In addition, the combined method had the largest area under the receiver operating characteristic (ROC) curve, which was 0.673 (0.647, 0.699), compared with any other screening method. Compared with TCT or HR-HPV testing alone, TCT+HR-HPV testing serves as a better screening method for cervical cancer and precancerous lesions.
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Nyota, Passy Kimema, Dophie Tshibuela Beya, Placide Cyanga Ngandu, Aliocha Nkodila Natuhoyila, Blaise Sumbu Matondo Manzambi, Mamy Ngole Zita, Gustave Ilunga Ntita, et al. "Evaluation of the proteinuria - Creatininuria ratio for the diagnostic confirmation of preeclampsia in congolese pregnant women." Journal of Medical Research 7, no. 3 (June 10, 2021): 70–78. http://dx.doi.org/10.31254/jmr.2021.7303.
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Context: Preeclampsia is a multisystem endothelial disease characterized by hypertension of pregnancy and glomeruloendotheliosis resulting in significant proteinuria. These days, the weight determination of urinary proteins by 24-hour proteinuria (P24) remains the reference method for biologically confirming this condition. However, the completion of the exam appears to be very burdensome with a long waiting period for results. Hence the need to use a simple alternative method such as the proteinuria / creatininuria ratio (PCR). Aims: Improve the diagnosis and management of preeclampsia by using a simple, less restrictive but reliable diagnostic method. Methodology: The study compared the results obtained from P24 versus PCR in confirming the diagnosis of preeclampsia in 149 Congolese women in whom the disease was suspected thanks to the urine dipstick. The cut-off values used for the diagnosis of preeclampsia were, for P24, a proteinuria> 300 mg / 24 h and for PCR a value> 30 mg / mmol. Results: Of the 149 pregnant women in whom the diagnosis of preeclampsia was suspected using the urine dipstick, only 85.9% had a P24> 300 mg. This diagnostic confirmation rate was similar to that obtained with PCR (86.6%). A linear correlation was found between P24 and PCR in the quantification of proteinuria and in the diagnosis of preeclampsia (r² = 0.627, p <0.004). Comparing the pathological values diagnosed by the two methods, the agreement was 89.1% (kappa = 0.767). The PCR showed an excellent predictive performance of maternal-fetal complications at the optimal threshold of 30.8 mg / mmol corresponding to a sensitivity of 96.6% and a specificity of 95% (Youden index 0.866). This threshold was 323 mg / 24h corresponding to a sensitivity of 84% and a specificity of 61.9% (Youden index 0.459) for P24. Conclusion: PCR seems to be a good alternative to P24 in confirming the diagnosis of preeclampsia in the settings most affected by this pathology
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Curto Subirats, Juan José, Alba Fischer-Carles, and Anna Solé. "Automatic Detection of Sfe: A Step Forward." Atmosphere 13, no. 2 (January 26, 2022): 199. http://dx.doi.org/10.3390/atmos13020199.
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Solar flare effects (Sfe) are magnetic variations caused by solar flare events. They only show up in the illuminated hemisphere. Their detection is a difficult task because they do not have a definite pattern and, additionally, they must be separated from other magnetic perturbations. However, we attempted to automatize these detections by using two different strategies. The first strategy takes advantage of one of the Sfe characteristics, as they usually have a rapid rise, followed by a smooth decay, which typically produces a crochet-like shape in the magnetograms. Thus, we created several morphological models for each magnetic component. Then, we identified a definite Sfe time interval by setting the conditions for various parameters, such as the correlations of the measured data with the models, or the model similarities among the different components. In the second stage of this strategy, we observed clusters of time intervals. Each of these clusters were attributed to a timespan of event possibility. We found the statistical optimal value of the correlation parameters by using the ROC curve method and Youden index. The second strategy was based on some of the properties of Sfe ionospheric electric currents, such as their spherical symmetry around the vortex. Here, the algorithm calculated the derivative of the data in order to avoid contamination of the daily variation Sq, and, by means of trigonometric formulas, computed the magnetic radial component relative to the Sfe current vortex (the focus). It then created an Sfe index with this data. A prior assumption of the focus position in a preceding work is no longer needed since we made a wide patrol of the space area to find it. Through a progressive thresholding process, we found its statistical optimal value (0.4 nT min−1) again by using the ROC curve method and Youden index. For both of the strategies, we have made a large calculation of Sfe detection (for the period of 2000–2020), which included 33 Sfe. Finally, we combined the results of both methods—which in fact are complementary—and obtained a unified list that gave a higher hit ratio than those that were obtained separately. This unified method gave promising results towards the possibility of Sfe automatic detection.
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Sun, Xue, Runrun Ren, Xiaoqian Yu, Fang Peng, and Xia Gao. "Application of Color Doppler Ultrasound Combined with Magnetic Resonance Imaging in Placenta Accreta." Scanning 2022 (July 13, 2022): 1–7. http://dx.doi.org/10.1155/2022/1050029.
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In order to improve the diagnostic value of color Doppler ultrasonography in placenta accreta and make the diagnosis more accurate, a method to detect placenta accreta by combining color Doppler ultrasonography and magnetic resonance is proposed. The patients with placenta accreta were selected for color Doppler ultrasonography and MRI examination. Kappa test was used to analyze the consistency between the results of ultrasound and MRI examination alone and combined diagnosis and pathological examination results, and the receiver operating characteristic (ROC) was drawn. Price compliance, sensitivity, specificity, good estimate rate, negative bid success rate, and Youden index were chosen as the basis for measuring the value of our tests. The results showed that the Kappa combined test rate was 0.609, the equivalent efficiency was 80.90%, and the correlation was good; ROC curve analysis showed that the sensitivity and specificity of articular placenta accreta were 91.75% and 89.26%. The sensitivity, uniqueness, good estimate, negative predictive value, and Youden index of color Doppler ultrasound combined with magnetic resonance imaging>magnetic resonance imaging>color Doppler ultrasound in our laboratory were compared, and the difference was significant ( P < 0.05 ). The experimental results show that color Doppler ultrasound and MRI are effective in the diagnosis of placenta accreta, and each has advantages and disadvantages. Therefore, it has been improved in the diagnosis of placenta accreta, is helpful for the diagnosis of placenta accreta, and is suitable for popularization and use.
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Chiang, Charng-Yen, Chien-Fu Lin, Peng-Huei Liu, Fu-Cheng Chen, I.-Min Chiu, and Fu-Jen Cheng. "Clinical Validation of the Shock Index, Modified Shock Index, Delta Shock Index, and Shock Index-C for Emergency Department ST-Segment Elevation Myocardial Infarction." Journal of Clinical Medicine 11, no. 19 (October 1, 2022): 5839. http://dx.doi.org/10.3390/jcm11195839.
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Background: ST-segment elevation myocardial infarction (STEMI) is a leading cause of death worldwide. A shock index (SI), modified SI (MSI), delta-SI, and shock index-C (SIC) are known predictors of STEMI. This retrospective cohort study was designed to compare the predictive value of the SI, MSI, delta-SI, and SIC with thrombolysis in myocardial infarction (TIMI) risk scales. Method: Patients > 20 years old with STEMI who underwent percutaneous coronary intervention (PCI) were included. Receiver operating characteristic (ROC) curve analysis with the Youden index was performed to calculate the optimal cutoff values for these predictors. Results: Overall, 1552 adult STEMI cases were analyzed. The thresholds for the emergency department (ED) SI, MSI, SIC, and TIMI risk scales for in-hospital mortality were 0.75, 0.97, 21.00, and 5.5, respectively. Accordingly, ED SIC had better predictive power than the ED SI and ED MSI. The predictive power was relatively higher than TIMI risk scales, but the difference did not achieve statistical significance. After adjusting for confounding factors, the ED SI > 0.75, MSI > 0.97, SIC > 21.0, and TIMI risk scales > 5.5 were statistically and significantly associated with in-hospital mortality of STEMI. Compared with the ED SI and MSI, SIC (>21.0) had better sensitivity (67.2%, 95% CI, 58.6–75.9%), specificity (83.5%, 95% CI, 81.6–85.4%), PPV (24.8%, 95% CI, 20.2–29.6%), and NPV (96.9%, 95% CI, 96.0–97.9%) for in-hospital mortality of STEMI. Conclusions: SIC had better discrimination ability than the SI, MSI, and delta-SI. Compared with the TIMI risk scales, the ACU value of SIC was still higher. Therefore, SIC might be a convenient and rapid tool for predicting the outcome of STEMI.
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Lim, Jayeon, SoYoun Bang, Jiyeon Kim, Cheolyong Park, JunSang Cho, and SungHwan Kim. "Integrative Deep Learning for Identifying Differentially Expressed (DE) Biomarkers." Computational and Mathematical Methods in Medicine 2019 (November 2, 2019): 1–10. http://dx.doi.org/10.1155/2019/8418760.
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As a large amount of genetic data are accumulated, an effective analytical method and a significant interpretation are required. Recently, various methods of machine learning have emerged to process genetic data. In addition, machine learning analysis tools using statistical models have been proposed. In this study, we propose adding an integrated layer to the deep learning structure, which would enable the effective analysis of genetic data and the discovery of significant biomarkers of diseases. We conducted a simulation study in order to compare the proposed method with metalogistic regression and meta-SVM methods. The objective function with lasso penalty is used for parameter estimation, and the Youden J index is used for model comparison. The simulation results indicate that the proposed method is more robust for the variance of the data than metalogistic regression and meta-SVM methods. We also conducted real data (breast cancer data (TCGA)) analysis. Based on the results of gene set enrichment analysis, we obtained that TCGA multiple omics data involve significantly enriched pathways which contain information related to breast cancer. Therefore, it is expected that the proposed method will be helpful to discover biomarkers.
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Poon, Michael T. C., Shivank Keni, Vineeth Vimalan, Chak Ip, Colin Smith, Sara Erridge, Christopher Weir, and Paul Brennan. "Extent of MGMT Promoter Methylation Modifies the Effect of Temozolomide on Overall Survival in Patients with Glioblastoma: A Regional Cohort Study." Neuro-Oncology 24, Supplement_4 (October 1, 2022): iv16—iv17. http://dx.doi.org/10.1093/neuonc/noac200.073.
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Abstract AIMS MGMT methylation in glioblastoma predicts response to temozolomide but dichotomizing methylation status may mask the true prognostic value of quantitative MGMT methylation. This study evaluated whether extent of MGMT methylation interacts with the effect of temozolomide on overall survival. METHOD We included consecutive glioblastoma patients aged ≥16 years diagnosed (April 2012–May 2020) at a neuro-oncology center. All patients had quantitative MGMT methylation measured using pyrosequencing. Those with MGMT methylated tumors were stratified into high and low methylation groups based on a cut-off using Youden index on 2-year survival. Our accelerated failure time survival models included extent of MGMT methylation, age, postoperative Karnofsky performance score, extent of resection, temozolomide regimen, and radiotherapy. RESULTS There were 414 patients. Optimal cut-off point using Youden index was 25.9% MGMT methylation. The number of patients in the unmethylated, low and high methylation groups was 223 (53.9%), 81 (19.6%), and 110 (26.6%), respectively. In the adjusted model, high (hazard ratio [HR] 0.60, 95% confidence intervals [CI] 0.46– 0.79, P=0.005) and low (HR 0.67, 95% CI 0.50–0.89, P<0.001) methylation groups had better survival compared to unmethylated group. There was no evidence for interaction between MGMT methylation and completed temozolomide regimen (interaction term for low methylation P=0.097; high methylation P=0.071). This suggests no strong effect of MGMT status on survival in patients completing temozolomide regimen. In patients not completing the temozolomide regimen, higher MGMT methylation predicted better survival (interaction terms P<0.001). CONCLUSION Quantitative MGMT methylation may provide additional prognostic value. This is important when assessing clinical and research therapies.
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Szmyd, Bartosz, Małgorzata Biedrzycka, Filip Franciszek Karuga, Magdalena Rogut, Iwona Strzelecka, and Maria Respondek-Liberska. "Interventricular Septal Thickness as a Diagnostic Marker of Fetal Macrosomia." Journal of Clinical Medicine 10, no. 5 (March 1, 2021): 949. http://dx.doi.org/10.3390/jcm10050949.
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Serious complications in both mother and newborn arising as a result of fetal macrosomia indicate the need for early diagnosis and prevention. Unfortunately, current predictors, such as fetal biometry, fundal height, and amniotic fluid index, appear to be insufficient. Therefore, we decided to assess the predictive potential of interventricular septal thickness (IVST), as measured at ≥33 weeks of gestation. Two hundred and ninety-nine patients met the inclusion criteria: complete medical history including all necessary measurements—namely, IVST obtained by M-mode echocardiography, fetal biometry, and birth weight. The Statistica 13.1 PL software was used to generate the receiver operating curve. The optimal cut-off point (IVST of 4.7 mm) was selected using the Youden index method. The analysis of fetal biometry abnormalities resulted in 46.6% of macrosomia cases being correctly predicted; however, IVST analysis detected 71.4% of cases. IVST at ≥4.7 mm appears to have a higher sensitivity and negative predictive value (NPV) than routine ultrasound.
Dissertations / Theses on the topic "Youden index method"
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ROTA, MATTEO. "Cut-pont finding methods for continuous biomarkers." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/40114.
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My PhD dissertation deals with statistical methods for cut-point finding for continuous biomarkers. Categorization is often needed for clinical decision making when dealing with diagnostic (or prognostic) biomarkers and a dichotomous or censored failure time outcome. This allows the definition of two or more prognostic risk groups, or also patient’s stratifications for inclusion in randomized clinical trials (RCTs).
We investigate the following cut-point finding methods: minimum P-value, Youden index, concordance probability and point closest to-(0,1) corner in the ROC plane. We compare them by assuming both Normal and Gamma biomarker distributions, showing whether they lead to the identification of the same true cut-point and further investigating their performance by simulation. Within the framework of censored survival data, we will consider here new estimation approaches of the optimal cut-point, which use a conditional weighting method to estimate the true positive and false positive fractions. Motivating examples on real datasets are discussed within the dissertation for both the dichotomous and censored failure time outcome.
In all simulation scenarios, the point closest-to-(0,1) corner in the ROC plane and concordance probability approaches outperformed the other methods. Both these methods showed good performance in the estimation of the optimal cut-point of a biomarker. However, to improve results communicability, the Youden index or the concordance probability associated to the estimated cut-point could be reported to summarize the associated classification accuracy. The use of the minimum P-value approach for cut-point finding is not recommended because its objective function is computed under the null hypothesis of absence of association between the true disease status and X. This is in contrast with the presence of some discrimination potential of the biomarker X that leads to the dichotomization issue.
The investigated cut-point finding methods are based on measures, i.e. sensitivity and specificity, defined conditionally on the outcome. My PhD dissertation opens the question on whether these methods could be applied starting from predictive values, that typically represent the most useful information for clinical decisions on treatments. However, while sensitivity and specificity are invariant to disease prevalence, predictive values vary across populations with different disease prevalence. This is an important drawback of the use of predictive values for cut-point finding.
More in general, great care should be taken when establishing a biomarker cut-point for clinical use. Methods for categorizing new biomarkers are often essential in clinical decision-making even if categorization of a continuous biomarker is gained at a considerable loss of power and information. In the future, new methods involving the study of the functional form between the biomarker and the outcome through regression techniques such as fractional polynomials or spline functions should be considered to alternatively define cut-points for clinical use. Moreover, in spite of the aforementioned drawback related to the use of predictive values, we also think that additional new methods for cut-point finding should be developed starting from predictive values.
Conference papers on the topic "Youden index method"
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William, Darren Eduardo, Mitra Andini Sigilipoe, and Widya Christine Manus. "Comparison of Mini-Mental State Examination and Clock Drawing Test with Orientation-Memory-Concentration Test in the Elderly with Cognitive Function Impairment in Jetis Sub-District, Yogyakarta." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.05.17.
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ABSTRACT Background: Dementia is a collective term for several diseases that affect memory, other cognitive abilities, and behavior. These diseases can seriously interfere with people’s ability of daily living. This is not a normal phenomenon of aging. With the increasing prevalence of dementia in the elderly, the importance of dementia as a comorbidity of hypertension is increasing. However, several questions regarding the link between hypertension and dementia remain unresolved. This study aimed to determine Orientation-Memory-Concentration-Test (OMCT) can be used to assess cognitive function in the elderly as an early step in the early detection of dementia. Subjects and Method: This was a comparative study using a case-control design. The study was conducted in Jetis Sub-District, Yogyakarta from September 2019 to June 2020. A total sample of 110 of elderly was divided into two groups 42 elderly (case), and 68 elderly (control) selected by consecutive sampling using the Mini-Mental State Examination (MMSE), Clock-Drawing Test (CDT) and Orientation-Memory-Concentration Test (OMCT). The dependent variables were the sensitivity and specificity level of the OMCT instrument while the scores of the MMSE. The independent variable was CDT instruments. The collected data will then be processed by diagnostic analysis followed by analysis of ROC and Youden’s index to determine the optimal cut off. Respondents are categorized as having impaired cognitive function if the MMSE (cut off ≤ 24) or CDT (cut off <18) shows a positive result. Results: 110 elderlies were involved. A total of 42 elderlies were included in the case population, and 68 elderlies were included in the control population. In the total OMCT population (cut off> 11) it has a sensitivity (29%) and specificity (97%) to the combination of MMSE and CDT. In populations with hypertension OMCT (cut off> 2.5) has sensitivity (68%) with specificity (46%). In a population without hypertension OMCT (cut off> 7) has a sensitivity (55%) and specificity (90%) to the combination of MMSE and CDT. Conclusion: OMCT can be used as a screening tool for cognitive dysfunction in older people with hypertension because of its short duration, ease of use, and can be used in patients with visual impairments. Keywords: Dementia, cognitive dysfunction, OMCT, 6-CIT. Correspondence: Darren Eduardo William. School of medicine Universitas Kristen Duta Wacana, Yogyakarta. Jl. Dr. Wahidin Sudirohusodo 5-25 Yogyakarta 55224, Indonesia. Email: Darreneduardowilliam@gmail.com. Mobile: 0813-4136-9999 DOI: https://doi.org/10.26911/the7thicph.05.17