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Friday, 28.04.2017

Response (Martin M. Katz)

Martin M. Katz's response to Donald Klein's Answers

Don Klein cites a valid concern about “semantic slippage” when moving from one context to another with various statistical approaches. So he believes that despite the selection of the most mathematically based factor analysis technique, principal components, there is “ample grounds for disagreement” about the extent of interpretation involved. Although it can be true that “each loaded variable is a composite of correlated variables, each with…..an ambiguous label”, it is also true that with certain techniques, the labels or items involved can be unambiguous and straightforward in content.

In support of my earlier statement that interpretation was minimal with the principal components procedure, I was referring to such examples generated from observational and self-reported mood inventories as “depressed mood-motor retardation”. That title was for a component from our own work, that had in its high loading clusters such items as “looks sad”, “reports feeling down”, “blue”, “motor movements slowed down”, etc., where the additional variables in the component add reliability but no further conceptual complexity to the component.Nevertheless, the dimensions derived with principal components can get somewhat more complicated in concept so he has a basis for requiring more attention to the degree of interpretation involved in any example, even of this type.

He then questions in regard to the mixture issue, “Can dimensions be independent but nevertheless have interactions?” Toanswer this query, one has to step back and examine how the “dimension” is derived. It is originally composed of parts that are shown to be highly linked,with each part having a similar pattern of relationships with other variables that may be part of other dimensions. For example, despite forming the parts of the ”anxiety-agitation-somatization” dimension in our work, we note that each part has its own pattern of relationships with variables that make up the composition of other independent dimensions, e.g., anxiety, in itself, a component of psychopathology across most all mental disorders, is known from many studies to correlate significantly ( >0.50) with “depressed mood”and with “hostility” (>0.40), items representative of other dimensions. The opportunities for interaction of keyparts of different independent dimensions are, therefore, multiple. That is what we found in our studies and was elaborated on in the “Depression and Drugs” book.

The interactions in those studies were clear and led to the “opposed emotional states” hypothesis. We believe that the interactions of these states helped to explain,in great part, the psychological turmoil and general stress undergone by the patient. Note that there was no attempt with the principal components analysis to “produce results equivalent to a model of latent categories”.  The aim in that study was not to uncover new “diagnoses”, new subcategories of illness, but to identify and describe the dimensions of psychopathology that structure the “major depressive disorder”. 

Klein provides an interesting discussion of Chassen’s intensive research design. It reminds us that earlier, there were alternative approaches to the currently established model for clinical trials.  It is a much more satisfying approach to drug evaluation for the experienced investigator than the mechanical quality associated with the current established model, which relies less on the expert, more on the trained rater. This alternative approach was not taken up by many and is now rarely used because of the intense monitoring and the expertise required of the clinical investigators in the conduct of such studies.He also notes that we were still unable to predict response to any of the drug classes, i.e., which patients respond to which drugs. Despite its scientific advantages, the expense to conduct the intensive trial makes the current established model look more feasible and more modest in its overall costs. Others have advanced ideas to improve the current model.

The Depression book provides another alternative, also, applied in earlier trials.  The “componential” model of antidepressant clinical trials includes the use of the established trial’s Hamilton Depression Rating method for evaluating overall “efficacy”, but goes further to profile the specific clinical and psychological actions of the experimental drug. The latter step which requires little additional expense greatly expands the amount of information that can be retrieved from the study of a new treatment, and makes possible the uncovering of actions that although not applicable to the target disorder, may uncover drug actions that are applicable in the treatment of mental disorders, other than depression, e.g., anxiety or phobic disorders. The “intensive design” has a distinct place in the clinical evaluation of new drugs. It still, however, does not achieve what is even more essential when carrying out a major drug trial, that is, the uncovering and quantifying of the specific clinical and psychological actions of the new drug, something that none of the current approaches, including the established model endorsed by the FDA, make a serious attempt to accomplish.

 

Martin M. Katz

June 5, 2014