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Dergiler / Black Sea Journal of Health Science / 2022 / Cilt: 5 Sayı: 3

Time-Dependent Receiver Operating Characteristic Analysis and Applications in the Field of Medicine

Ceren Efe Sayın(KAHRAMANMARAŞ SÜTÇÜ İMAM ÜNİVERSİTESİ, TIP FAKÜLTESİ)0000-0001-9506-9219
İlker Unal(ÇUKUROVA ÜNİVERSİTESİ, TIP FAKÜLTESİ)0000-0002-9485-3295
Sayfa
411–416
Yayın Tarihi
2022-09-01
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Results of this study show that time-dependent ROC analysis performs more accurately when there is a time dependency between the biomarker and the event of interest; therefore, it is recommended.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:When there is a time-dependency between the biomarker and the event of interest (death, disease, relapse etc.), classical receiver operating characteristic (ROC) analysis may not be able to estimate the true performance of the biomarker.
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Temel Bulgular & Veri:In this study, the aim is to demonstrate applications of this modified ROC method on medical datasets and find out if it should be preferred over classical ROC for time-dependent situations.
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Sonuç & Katkı:Results of this study show that time-dependent ROC analysis performs more accurately when there is a time dependency between the biomarker and the event of interest; therefore, it is recommended.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Time-dependent ROC · Diagnostic tests · Biomarker

Abstract

When there is a time-dependency between the biomarker and the event of interest (death, disease, relapse etc.), classical receiver operating characteristic (ROC) analysis may not be able to estimate the true performance of the biomarker. For such cases, time-dependent ROC, an extended version of the standard ROC, is developed. In this study, the aim is to demonstrate applications of this modified ROC method on medical datasets and find out if it should be preferred over classical ROC for time-dependent situations. Comparison between classical ROC and Kaplan-Meier (KM) estimator, which is one of the two time-dependent ROC estimators, has been made using datasets in this study. Nearest Neighbor Estimator (NNE), the alternative of KM estimator, is also applied on all datasets. Then the findings of these two approaches are compared. It is concluded that time-dependent ROC method is superior to the standard ROC analysis. In general, the closer to the event time, the higher performance is observed. Especially, biomarkers measured at last 12 or 6 months before the event are determined to be better at classification than the earlier measurements. Though in all applications KM and NNE yielded very similar results, the latter is considered to be more appropriate to evaluate the performance of a biomarker when a time dependent data is also censored. Results of this study show that time-dependent ROC analysis performs more accurately when there is a time dependency between the biomarker and the event of interest; therefore, it is recommended.

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Bu Makaleye Atıf Yap

Sayın, C. E., Unal, İ. (2022). Time-Dependent Receiver Operating Characteristic Analysis and Applications in the Field of Medicine. Black Sea Journal of Health Science, Cilt: 5 Sayı: 3, 411–416. https://doi.org/10.19127/bshealthscience.1107599

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