at least eight of these m z ranges and more preferably at all 12 of these ranges the significance and methods of discovery of these peaks is explained in the prior patent application publication u s 2007 0231921 it has been discovered that this set of peaks is not only useful for patient selection and monitoring of nsclc patients but also crc patients and hnscc cancer patients as well at step 316 the values obtained at step 314 are supplied to a classifier which in the illustrated embodiment is a k nearest neighbor knn classifier the classifier makes use of a training set of class labeled spectra from other patients the application of the knn classification algorithm to the values at 314 and the training set is explained in our patent application publication u s 2007 0231921 other classifiers can be used including a probabilistic knn classifier or other classifier at step 318 the classifier produces a label for the spectrum either u201c good u201d u201c poor u201d or u201c undefined u201d as mentioned above steps 304 318 are performed in parallel on three separate aliquots from a given patient sample at step 320 a check is made to determine whether all three aliquots produce the same class label if not an undefined result is returned as indicated at step 322 if all aliquots produce the same label.