More On Disease-Modifying

                                        See reference 6 and graphic credit for source.

 

My last post was not satisfactory after I read thorough it several times.  I decided to diagram the concepts of symptomatic and disease modifying with the suggested parameters and cite a few specific examples in the diagram.  An obvious problem with the definitions as used by Professor Ghaemi is that it involved a lot of inductive reasoning on the pathophysiology side of the equation. 

How can you say a medication is affecting underlying pathophysiology if it is unknown?  Much pathophysiology of complex disease is at the hypothetical rather than theoretical level. The hypotheses are restated over time, but there are no widely accepted theories. That has resulted in measurable proxies for pathophysiology being used like serum biomarkers for rheumatological disease and brain plaques for active disease and remissions in multiple sclerosis.  

The problem with that approach is highlighted with the recent controversy in the FDA approval of aducanumab ( an anti-beta~amyloid antibody) for Alzheimer’s Disease or mild cognitive impairment.  The biomarker of PET visualized beta~amyloid plaques were significantly improved in two clinical trials relative to placebo.  Both of these trials were terminated early when it became apparent, they would not reach primary efficacy endpoints. In this case, the drug did not reach clinical efficacy as a disease-modifying drug and it is effective against a biomarker that may not be a true marker of the pathophysiology of Alzheimer’s Disease.  Additionally, the drug was associated with amyloid-related imaging abnormalities (ARIA) at a significantly higher rate than placebo.  These lesions were thought to represent vasogenic edema and microhemorrhages and necessitate careful screening at baseline for preexisting vascular disease.

There are biases in the literature on where the term was used.  Disease-modifying seems to be associated primarily with rheumatological and some specific illnesses like multiple sclerosis.  In other areas it is mentioned primarily as an absence as in: “there are no disease-modifying drugs for this condition”.

 

What are the main points that I tried to incorporate into the diagram?

1.  Neither the disease-modifying or symptomatic interventions are 100% effective.  With any complex, polygenic illness there will be non-responders, partial responders, and optimal responders.  In many studies the optimal responders will meet study criteria for remission – but that also happens in clinical practice.  For example, it is common to assess people undergoing antidepressant treatment and find that from a subjective standpoint their depressive symptoms are gone and they feel like they are back at their baseline.  Of course, in randomized clinical trials there is an intent-to-treat analysis that counts study drops outs in the denominator no matter what the cause. In clinical practice that group would be provided with an alternate treatment.

2.  There can be overlap between disease-modifying and symptomatic treatment. There are a few examples in the graphic, but prednisone for rheumatoid arthritis is probably the best example.  It treats acute joint and systemic inflammation while preventing bone erosion early in the course of illness.  There are many drugs that are either symptomatic or disease-modifying.

3.  Many of the outcomes are not cleanly separable.  Symptom ratings and symptom defined remission can be associated with hospitalizations, disease markers, and composite outcomes. Measurable disease markers or biomarkers are certainly preferable, but as noted in the case of aducanumab there may be unexpected findings suggesting other important underlying pathophysiology.  In the case of complex diseases we are learning more and more that many genes and many gene networks are potentially involved.  In that case – a final common pathway or a parsimonious analysis should not be expected.  We appear to be at the very early stages of being able to analyze these complex interactions.

No matter how you parse it – the definitions considered above do not allow for a very clearly defined category of disease-modifying and symptomatic.  Does regulatory language from the US Food and Drug Administration (FDA) or the European Medicines Agency (EMA) help?  The standard for disease-modifying approvals apparently changed before 2019 (2).  Up until that time the standards were largely descriptive like delaying disability or slowing the progress of illness.  The authors note an uneven approach to the term disease-modifying with a tendency to use it in rheumatic diseases but less so in neurodegenerative diseases. They attribute that to disease-modifying being an inferential concept because “changes in the brain cannot be directly observed”.

This is an important concept because it applies to all of the hypothetical mechanisms of action of most drugs that exist.  In the previous post I pointed out that all of the disease modifying drugs for multiple sclerosis have no widely accepted theories about their mechanism of action.  The hypotheses may be listed but more commonly are listed as unknown or not fully understood.  The same is true for the disease-modifying drugs in psychiatry listed by Ghaemi in his recent paper (4).  Various signaling systems are cited, but the reality is there is no widely accepted mechanism of action and more importantly no mechanistic way to explain lithium nonresponse.  

The best way to approach disease-modifying drugs in general and more specifically in psychiatry is to discuss the hypothetical mechanisms of action and the implications of those mechanisms.  That is the focus of research and the basis for many purported biomarkers of disease in psychiatry but clearly in many other fields of medicine. With the advent of genomics we are also witnessing a necessary paradigm shift away from simple explanations.

 

George Dawson, MD, DFAPA

 

References:

1:  Rabinovici GD. Controversy and Progress in Alzheimer's Disease - FDA Approval of Aducanumab. N Engl J Med. 2021 Aug 26;385(9):771-774. doi: 10.1056/NEJMp2111320. Epub 2021 Jul 28. PMID: 34320284.

2:  Morant AV, Jagalski V, Vestergaard HT. Labeling of Disease-Modifying Therapies for Neurodegenerative Disorders. Front Med (Lausanne). 2019 Oct 17;6:223. doi: 10.3389/fmed.2019.00223. PMID: 31681780; PMCID: PMC6811601.

3:  Schubert, K.O., Thalamuthu, A., Amare, A.T. et al. Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients. Transl Psychiatry 11, 606 (2021). https://doi.org/10.1038/s41398-021-01702-2

4:  Ghaemi SN. Symptomatic versus disease-modifying effects of psychiatric drugs. Acta Psychiatr Scand. 2022 Jun 2. doi: 10.1111/acps.13459. Epub ahead of print. PMID: 35653111

5:  Alda M. Lithium in the treatment of bipolar disorder: pharmacology and pharmacogenetics. Mol Psychiatry. 2015 Jun;20(6):661-70. doi: 10.1038/mp.2015.4. Epub 2015 Feb 17. PMID: 25687772; PMCID: PMC5125816.

6:  Kerr F, Bjedov I and Sofola-Adesakin O (2018) Molecular Mechanisms of Lithium Action: Switching the Light on Multiple Targets for Dementia Using Animal Models. Front. Mol. Neurosci. 11:297. doi: 10.3389/fnmol.2018.00297

 

Graphic Credit:  Reference 6 and the following copyright and Open Access license:

Copyright © 2018 Kerr, Bjedov and Sofola-Adesakin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.