[Application of digital pathology tools. An unusual case of non-Hodgkin lymphoma].

Currently, lymphoma diagnosis is based on a combination of morphology, immunophenotyping, and molecular testing. Using the example of an unusual case of malignant non-Hodgkin lymphoma, we show that improved visualization using digital pathology contributes to the convergence of these complementary diagnostic modalities. A 45-year-old woman presented with skin rash and cervical lymphadenopathy.

[Syndrome combinations as meta-syndromes in configuration frequency analysis].

The paper defines metasyndromes as syndrome combinations. Within the framework of Configural Frequency Analysis the authors propose using a single test for identifying patterns of syndromes rather than applying simultaneous tests for identifying singular syndromes. The authors describe and illustrate the method using the "classical data" that describe symptom patterns under LSD (Lienert, 1971).

[2 sample configuration frequency analysis: solitary and complementary discriminant types of treatment and control groups].

The paper entitled "Two-sample CFA: Solitary and complementary discriminant types of treatment- and control groups" suggests to modify 2-sample and c-sample CFA as follows: While singular patterns of attributes define solitary types, complementary pairs of patterns define complementary types which may be interpreted as poles of a type-defining factor in factor analysis. The new version of 2-sample CFA is illustrated in 2 examples from clinical psychology with patterns of scales and symptoms.

[The configuration frequency analysis. Victor's singular types and syndromes].

A new concept on configural frequency analysis (CFA) is presented under the title: CFA, Victor's singular types and syndromes. The new concept is suitable and highly effective if one and only one type, a singular type, is present within a population of subjects or patients. It is based on the nullhypothesis of quasi-independence which assumes that a type-population with coincident variables is superimposed to a residual population with independent variables.

[Configuration cluster analysis as an alternative to configuration frequency analysis].

The paper discusses configural cluster analysis (CCA) as an alternative to configural frequency analysis (CFA). CFA defines types as deviations from the assumption of no interactions among the variables. CCA defines clusters as deviations from the stronger assumption of a total lack of effects, in the contingency table.