DISCRIMINANT-ANALYSIS ON SMALL-CELL LUNG-CANCER AND NONSMALL CELL LUNG-CANCER BY MEANS OF NSE AND CYFRA-21.1

A correct diagnosis of small cell lung cancer (SCLC) and non-small cel l lung cancer (NSCLC) is essential both for prognostic and therapeutic reasons, We used discriminant analysis as a method to optimize the di scriminant power of serum tumour marker levels for differentiation bet ween SCLC and NSCLC. A panel of serum markers, including neurone speci fic enolase (NSE), cytokeratin fragment antigen 21.1 (CYFRA-21.1), tis sue polypeptide antigen (TPA) and carcinoembryonic antigen (CEA) was o btained in 50 consecutive NSCLC and 17 SCLC, Data were analysed by the BMDP statistical program after logarithmic transformation of marker l evels. The variables selected were NSE and CYFRA-21.1. Considered toge ther, 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 therefo re conclude that the canonic variable tested, based on NSE and CYFRA-2 1.1, provides a good discrimination between the two types of lung canc er. The method is rapid, relatively inexpensive, and based on simple s erum tests.