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Diagnostic Value of Combinatorial Markers in Colorectal Carcinoma

Voronova V., Glybochko P. V.[1], Svistunov A. A.[1], Fomin V. V.[1], Kopylov P., Tzarkov P., Egorov A., Gitel E., Ragimov A., Boroda A., Poddubskaya E., Sekacheva M.[2]
FRONTIERS IN ONCOLOGY
Vol. 10 , Num. 832
Опубликовано: 22 2020
Тип ресурса: Article

DOI:10.3389/fonc.2020.00832

Документ://resource.rucml.ru/feml/protected/0000000005E/0000000005E.epub

Издатель: Frontiers Media S.A., Lausanne
Аннотация:
Objectives: Blood-based tests have been shown to be an effective strategy for colorectal cancer (CRC) detection in screening programs. This study was aimed to test the performance of 20 blood markers including tumor antigens, inflammatory markers, and apolipoproteins as well as their combinations.
Methods: In total 203 healthy volunteers and 102 patients with CRC were enrolled into the study. Differences between healthy and cancer subjects were evaluated using Wilcoxon rank-sum test. Several multivariate classification algorithms were employed using information about different combinations of biomarkers altered in CRC patients as well as age and gender of the subjects; random sub-sampling cross-validation was done to overcome overfitting problem. Diagnostic performance of single biomarkers and multivariate classification models was evaluated by receiver operating characteristic (ROC) analysis.
Results: Of 20 biomarkers, 16 were significantly different between the groups (p-value <= 0.001); ApoA1, ApoA2 and ApoA4 levels were decreased, whereas levels of tumor antigens (e.g. carcinoembriogenic antigen) and inflammatory markers (e.g., C-reactive protein) were increased in CRC patients vs. healthy subjects. Combinatorial markers including information about all 16 significant analytes, age and gender of patients, demonstrated better performance over single biomarkers with average accuracy on test datasets >= 95[%] and area under ROC curve (AUROC) >= 98[%].
Conclusions: Combinatorial approach was shown to be a valid strategy to improve performance of blood-based CRC diagnostics. Further evaluation of the proposed models in screening programs will be performed to gain a better understanding of their diagnostic value.
Ключевые слова:
diagnostics; machine learning; biomarkers; colorectal cancer; carcinoembryonic antigen; apolipoproteins
CANCER; MODEL; DNA; SENSITIVITY; VALIDATION; BIOMARKERS; SOCIETY; TESTS
Рубрики Mesh:
Colorectal Neoplasms
Carcinoembryonic Antigen
Apolipoproteins D
Biomarkers
[1]Sechenov University.Rectorate
[2]Sechenov University.Clinical center.Institute of personalized medicine
Язык текста: Английский
ISSN: 2234-943X
Voronova V.
Glybochko P. V. Petr Vitalyevich urologist 1964- Sechenov University.Rectorate
Svistunov A. A. Andrey Alekseevich pharmacist Sechenov University.Rectorate
Fomin V. V. Victor Victorovich therapist Sechenov University.Rectorate
Kopylov P.
Tzarkov P.
Egorov A.
Gitel E.
Ragimov A.
Boroda A.
Poddubskaya E.
Sekacheva M. Sechenov University.Clinical center.Institute of personalized medicine
Воронова В. Вероника
Глыбочко П.В. Петр Витальевич уролог 1964- Сеченовский университет.Ректорат
Свистунов А. А. Андрей Алексеевич фармацевт Сеченовский университет.Ректорат
Фомин В. В. Виктор Викторович терапевт Сеченовский университет.Ректорат
Копылов Ф. Филипп
Жарков П. Пётр
Егоров А. Алексей
Гител Е. Евгений
Рагимов А. Алигейдар
Борода А. Александр
Поддубская Е. Елена
Секачева М. И. Марина Игоревна 1976- Сеченовский университет.Клинический центр.Институт персонализированной медицины
Diagnostic Value of Combinatorial Markers in Colorectal Carcinoma
Text visual unmediated
FRONTIERS IN ONCOLOGY
Lausanne Frontiers Media S.A. 2011-
Vol. 10 Num. 832
22 MAY 2020
Article
diagnostics machine learning biomarkers colorectal cancer carcinoembryonic antigen apolipoproteins
CANCER MODEL DNA SENSITIVITY VALIDATION BIOMARKERS SOCIETY TESTS
Colorectal Neoplasms C04.588.274.476.411.307 C06.301.371.411.307 C06.405.249.411.307 C06.405.469.158.356 C06.405.469.491.307 C06.405.469.860.180
Carcinoembryonic Antigen D12.776.395.550.200.210 D12.776.543.550.200.210 D23.050.285.329 D23.050.301.350.210 D23.101.140.300
Apolipoproteins D D10.532.091.450 D12.776.070.400.450 D12.776.521.120.450
Колоректальные новообразования C04.588.274.476.411.307 C06.301.371.411.307 C06.405.249.411.307 C06.405.469.158.356 C06.405.469.491.307 C06.405.469.860.180
Раково-эмбриональный антиген D12.776.395.550.200.210 D12.776.543.550.200.210 D23.050.285.329 D23.050.301.350.210 D23.101.140.300
Аполипопротеины d D10.532.091.450 D12.776.070.400.450 D12.776.521.120.450
Biomarkers D23.101
Биомаркеры D23.101
Objectives: Blood-based tests have been shown to be an effective strategy for colorectal cancer (CRC) detection in screening programs. This study was aimed to test the performance of 20 blood markers including tumor antigens, inflammatory markers, and apolipoproteins as well as their combinations.
Methods: In total 203 healthy volunteers and 102 patients with CRC were enrolled into the study. Differences between healthy and cancer subjects were evaluated using Wilcoxon rank-sum test. Several multivariate classification algorithms were employed using information about different combinations of biomarkers altered in CRC patients as well as age and gender of the subjects; random sub-sampling cross-validation was done to overcome overfitting problem. Diagnostic performance of single biomarkers and multivariate classification models was evaluated by receiver operating characteristic (ROC) analysis.
Results: Of 20 biomarkers, 16 were significantly different between the groups (p-value <= 0.001); ApoA1, ApoA2 and ApoA4 levels were decreased, whereas levels of tumor antigens (e.g. carcinoembriogenic antigen) and inflammatory markers (e.g., C-reactive protein) were increased in CRC patients vs. healthy subjects. Combinatorial markers including information about all 16 significant analytes, age and gender of patients, demonstrated better performance over single biomarkers with average accuracy on test datasets >= 95[%] and area under ROC curve (AUROC) >= 98[%].
Conclusions: Combinatorial approach was shown to be a valid strategy to improve performance of blood-based CRC diagnostics. Further evaluation of the proposed models in screening programs will be performed to gain a better understanding of their diagnostic value.
Унифицированный идентификатор ресурса для цитирования: //repo.rucml.ru/articles/0000000005/