Monday, 27.03.2017

Martin M. Katz: Clinical Trials of Antidepressants
How Changing the Mode Can Uncover New, More Effective Molecules

Comments by Malcolm Lader


Martin Katz is a psychologist with a distinguished record in psychopharmacological research. In this book of exemplary succinctness, he concentrates on the FDA requirements for efficacy trials for antidepressants. He is particularly critical of the wasteful nature of these trials and the limited conclusions that can be drawn. The Hamilton Depression Scale is a particular bête noire (Hamilton, 1960). My comments are primarily designed to stimulate controversy and initiate a discussion. Thankfully, as a European I do not have to comply with the rigid, almost ossified, FDA regulations. I have those of the EMA instead!

I shall consider some general points first. What is the purpose of an efficacy trial of this sort? It is basically a legal procedure to establish efficacy according to pre-set, usually legislative criteria. The outcome variable may be specified as, for example, a proportional drop in the Hamilton Depression Scale Score. But this is an artificial outcome. The practising clinician actually relies on a probabilistic analysis of the chance of obtaining a useful therapeutic response in her/his patients as compared with other treatments, both pharmacological and non-pharmacological. In clinical practice this therapeutic response is a pragmatic outcome such as discharge from hospital or outpatient clinic (e.g., Keller, 2003). Furthermore, in conjunction with the efficacy, it is essential that the risks of the treatment are carefully evaluated so that a proper risk-benefit ratio can be estimated (Friedman and Leon, 2007). Such profiles usually need much larger numbers than for an efficacy trial particularly if the profile of adverse effects contains some rare but severe, even life-threatening, reactions. Post-marketing surveillance may be needed to fulfil that role. In addition, the clinician will have calibrated this risk-benefit ratio against the severity of the condition that he is treating, accepting greater risks for a more severe indication. He may conclude that the risks outweigh the benefits in all but the most severe of the the patients who seek help. Also a differential response in some patients needs careful evaluation so that a particularly responsive sub-type can be identified.

Severity is an important dimension that regulatory authorities may overlook or delegate to cost-effective assessments. As a general rule it is easiest to establish efficacy in the most severely ill patients such as those with a Hamilton Score in the 30s or a MADRS of at least 30 or even 35 (Montgomery and Asberg, 1979; Thase, 2011). Too often because of the exigencies of being able to recruit patients at an adequate rate, quite mildly ill patients are included and those may not show an adequate response.

One factor which is overlooked in this book is that most cases of unipolar depression have a self-limiting time span (Spijker et al., 2002). Natural remission is the rule rather than the exception. This raises practical problems - if the trial goes on for too long, say over 12 weeks, natural remission in the placebo group will obfuscate the improvement in the drug-treated patients. The theoretical way to control for this is to have a non-treatment group but this raises major practical and ethical problems.

Katz inveighs against the wasteful nature of the trials carried out under FDA auspices. I entirely agree with the waste of expensive resources but also question whether trials with such limited results can be truly ethical. Patients are being exposed to untried treatment procedures for a limited and over-focussed return.

One glaring example of this waste of patients and resources concerns the offset of action of putative antidepressants. A pharmaceutical company has a responsibility, scientific and moral, not to introduce any new medication to the market until it has been shown that the medication can be discontinued at the end of treatment with impunity or with only minor perturbations. The placebo-controlled trial provides an appropriate framework in which to establish whether cessation of treatment is uneventful, attended by a few symptoms, or by a recognisable and troublesome withdrawal reaction (Wilson and Lader, 2015).

Another neglected topic is compliance which can vitiate the usefulness of an efficacious compound (Demyttenaere   and Haddad, 2000).

 Katz implies that the FDA-type trial could fulfil 2 main goals. It can establish efficacy for registration purposes and it could be used for more widely useful scientific purposes. I believe that he is right that opportunities are lost but essentially he is asking for scientific studies into antidepressants to be carried out in a controlled context, a laudable aim. Unfortunately, this cannot be achieved in the controlled trials before efficacy is actually established. Otherwise, if the candidate antidepressant proves inefficacious, much time, effort, and ethical credibility will be lost trying to elucidate the other aspects of the psychopharmacology such as biochemical changes. Caution is needed not to substitute one source of waste with another. I am also less enthusiastic than Katz in accepting correlations between antidepressant effects and biochemical changes. The relationships probably hold for norepinephrine (and I think dopamine) and motor activity, and between serotonin and anxiety, but I am less convinced that the biochemical correlates of depression itself are firmly established. To suggest that they could form the basis of a new model and thereby act as surrogate markers for clinical depression is surely an over-simplification. Correlations appear stronger with adverse effects than wanted effects (e.g., Gelder et al, 2009).

I would also urge evaluation of correlates of insomnia which is not only a common concomitant of depression but a notable harbinger (Benca and Peterson, 2008).

Katz adduces a small study from his own group to bolster his support of the different model of depression. I am concerned that he uses a circular argument when he states that his sample were “soundly diagnosed” as depressed. This merely means that the investigators came to some consensus on empirically derived criteria à la current DSM. He also falls back on the weak argument that it is “common knowledge” that a high level of anxiety accompanies depression and retardation. This is too facile. The approach needed in this argument is a return to first principles by carrying out a large study on a population sample with no preconceived assumptions about psychopathological categories. But I do think that the categorical approach merely serves to establish reimbursement criteria for health insurance agencies.

Katz takes particular issue with the Hamilton Depression Scale. It is a poor creature, indeed, with insensitive items. I once gently chided Max Hamilton – one did confront him trenchantly – about the Scale. He generously admitted that it had been drawn up hastily from text-book descriptions and had not been adequately tested for reliability and validity. Max regarded his Anxiety Scale as superior, and so do I.  In fact, the MADRS generally seems superior to the Hamilton for rating changes in depression severity (Carmody et al, 2006).

In conclusion, I heartily support Katz’s criticisms and his plea for a new approach that maximises the biological factors.  But I do not think that this constitutes a new model. Certainly more can be achieved and Katz points the way. But I am not fully convinced that we know enough as yet for the alternative model to prove successful in the search for new medications. We are still caught in the Laocoönian coils of serendipity in the history of antidepressant discovery.

Benca R, and Peterson MJ. Insomnia and depression. Sleep Medicine 2008;

 9; Suppl 1:  S3–S9.

Carmody T, Rush AJ, Bernstein I, Warden D, Brannan S, Burnham B, Woo A, Trivedi  M. The Montgomery Äsberg and the Hamilton Ratings of depression.

A comparison of measures. European Neuropsychopharmacology 2006; 16: 601–611.


Demyttenaere  K. and  Haddad  PCompliance with antidepressant therapy and antidepressant discontinuation symptoms. Acta Psychiatrica Scandinavica 2000; 101, Suppl. S403: 50–56.


Friedman RA and Leon AC. Expanding the Black Box — Depression, Antidepressants, and the Risk of Suicide. New England Journal of Medicine 2007; 356: 2343-2346


Gelder MG, Andreasen NC, Lopéz-Ibor JJ, Geddes JR. New Oxford Textbook of Psychiatry 2009, Oxford, University Press. , pp.1190-2.

Hamilton M. A rating scale for depression. Journal of Neurology, Neurosurgery and Psychiatry 1960; 23: 56-62.


Keller MB. Past, present, and future directions for defining optimal treatment outcome in depression; Remission and beyond.  JAMA. 2003; 289: 3152-3160.


Montgomery SA and Asberg. A new depression scale designed to be sensitive to change. British Journal of Psychiatry 1979; 134: 382-389.


Spijker J, de Graaf R, van Bijl R,  Beekman ATF, et al. Duration of major depressive episodes in the general population: results from The Netherlands Mental Health Survey and Incidence Study (NEMESIS). British Journal of Psychiatry 2002; 181:  08-213.


Thase ME, Larsen KG, and Kennedy SH. Assessing the ‘true’ effect of active antidepressant therapy v. placebo in major depressive disorder: use of a mixture model. British Journal of Psychiatry 2011; 199: 501–507.


Wilson E. and Lader M. A review of the management of antidepressant discontinuation symptoms. Therapeutic Advances in Psychopharmacology 2015; 5:357-368.



Malcolm Lader

June 23, 2016