Discriminant analysis on small cell lung cancer and non-small cell lung cancer by means of NSE and CYFRA-21.1

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Abstract
A correct diagnosis of small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) is essential both for prognostic and therapeutic reasons. We used discriminant analysis as a method to optimize the discriminant power of serum tumour marker levels for differentiation between SCLC and NSCLC. A panel of serum markers, including neurone specific enolase (NSE), cytokeratin fragment antigen 21.1 (CYFRA-21.1), tissue polypeptide antigen (TPA) and carcinoembryonic antigen (CEA) was obtained in 50 consecutive NSCLC and 17 SCLC. Data were analysed by the BMDP statistical program after logarithmic transformation of marker levels. The variables selected were NSE and CYFRA-21.1. Considered together, they were able to give a 97% rate of correct classification. The formula generated (canonic variable, CV) was validated on a group of seven SCLC and 22 NSCLC patients. Only two errors occurred. We therefore conclude that the canonic variable tested, based on NSE and CYFRA-21.1, provides a good discrimination between the two types of lung cancer. The method is rapid, relatively inexpensive, and based on simple serum tests.

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