Centre-independent detection of non-small cell lung cancer (NSCLC) by means of classification with receiver operating characteristic (ROC)-based data transformation

• Verfasst von: Bitterlich, Norman [VerfasserIn]
• Verfasst von: Muley, Thomas [VerfasserIn]
• Verfasst von: Schneider, Joachim [VerfasserIn]
• Titel: Centre-independent detection of non-small cell lung cancer (NSCLC) by means of classification with receiver operating characteristic (ROC)-based data transformation
• Verf.angabe: Norman Bitterlich, Thomas Muley and Joachim Schneider
• E-Jahr: 2010
• Jahr: March 15, 2010
• Umfang: 5 S.
• Fussnoten: Gesehen am 09.02.2023
• Titel Quelle: Enthalten in: Anticancer research
• Ort Quelle: Attiki, 2004
• Jahr Quelle: 2010
• Band/Heft Quelle: 30(2010), 5, Seite 1661-1665
• ISSN Quelle: 1791-7530
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Adult
• Sach-SW: Aged
• Sach-SW: Biomarkers, Tumor
• Sach-SW: Carcinoembryonic Antigen
• Sach-SW: Carcinoma, Non-Small-Cell Lung
• Sach-SW: Cohort Studies
• Sach-SW: Female
• Sach-SW: Humans
• Sach-SW: Keratin-19
• Sach-SW: Lung Neoplasms
• Sach-SW: Male
• Sach-SW: Middle Aged
• Sach-SW: Models, Statistical
• Sach-SW: ROC Curve
• Sach-SW: Sensitivity and Specificity
• K10plus-PPN: 1833834488

Abstract

The diagnosis of non-small cell lung cancer (NSCLC) by using tumour markers needs to be improved and standardised in order to compare marker profiles from different centres. A centre-independent tool based on receiver operating characteristics (ROC) curves instead of cut-off-based approaches for NSCLC diagnosis was established. Carcinoembryonic antigen (CEA) and cytokeratin-19 fragments (CYFRA 21-1) were measured in 326 NSCLC patients and 160 patients with benign lung diseases (Heidelberg, HD) and compared to 158 NSCLC patients and 128 controls from an occupational medicine high-risk cohort (Giessen, GI). The cohorts differed in tumour-stages, marker cut-offs and therefore in sensitivity for NSCLC detection. Sensitivity for CYFRA 21-1 (most sensitive marker) was 65% GI, 35% HD, for CEA: 43% GI and 35% HD. Marker-combination increased sensitivity to 53% HD resp. 73% GI, accompanied by decreasing specificity. A transfer of the cut-off-based classification methods from HD to GI and vice versa led to false classifications. Sensitivity and specificity do not change using classification methods on transformed data such as the described decision guarantee. CEA/CYFRA-combination allows a classification method transferable despite structural differences of the cohorts. Only 0.8% of the datasets showed discordance in classification. The diagnosis of NSCLC based on ROC curves eliminate centre-specific differences. Classification methods lead to an improvement in NSCLC diagnosis.