CLASSIF1 Classification

Pretherapeutic Identification of High Risk AML Patients

< fig.3      fig.4: Reclassification of the Learning Set      > fig.5

- Displayed are the triple matrix patterns of ten sequential 5-year survivor and 5-year non survivor AML patients from the classification the in fig.2A.
- The disease classification masks fig.3 for the reference group of patients ( > 5-year, > 2 year survival) typically contains a sequence of (0) characters because the majority of the parameter values is located between the two percentile thresholds 10-90%, 15-85%, 20-80%, 25-75%, 30-70% of the value distributions. As an example, 80% of the values are (0) for the percentile pair 10-90%, 10% are below (-) the lower percentile and 10% above (+) the upper percentile.
- Unknown patients are classified according to the highest positional coincidence of their patient classification mask with any of the disease classification masks.
- The degree of coincidence between the patient mask and the best fitting disease mask is expressed by the disease coincidence factor. The coincidence factor is 1.00 for patients #100073 and #080055 with four triple matrix characters (0) and three characters (-) (arrows <= ) despite the fact that not all triple matrix characters are (0). The reason for this is that triple matrix characters in those parts of the reference value distribution curves which are not occupied by the triple matrix characters of the 5-year nonsurvivor disease mask count as positional coincidences for the 5-year survivor disease mask. With the 5-year nonsurvivor disease mask being: ++++++ the characters 0000000 and ------- belong to the 5-year survivor disease mask.
- Nineteen patients are correctly classified while the one patients #300040 is misclassified
- The patient disease masks labelled a) and b) are repetitive. The systematic analysis of disease masks may permit to define leukemia subgroups characterized by certain preferential molecular CD expression patterns.

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Last Update: Mar.31,2003