=============================================================== == == == ----------- ALS Interest Group ----------- == == ALS Digest (#117, 15 August 1994) == == == == ------ Amyotrophic Lateral Sclerosis (ALS) == == ------ Motor Neurone Disease (MND) == == ------ Lou Gehrig's disease == == ----- == == This e-mail list has been set up to serve the world-wide == == ALS community. That is, ALS patients, ALS researchers, == == ALS support/discussion groups, ALS clinics, etc. Others == == are welcome (and invited) to join. Currently there are == == 300+ subscribers. == == == == To subscribe, to unsubscribe, to contribute notes, == == etc. to ALS Digest, please send e-mail to: == == bro@huey.met.fsu.edu (Bob Broedel) == == Sorry, but this is *not* a LISTSERV setup. == == == == Bob Broedel; P.O. Box 20049; Tallahassee, FL 32316 USA == =============================================================== CONTENTS OF THIS ISSUE: 1 .. an article about ALS from THE CUTTING EDGE >From : CraigR3@aol.com X-Mailer: America Online Mailer Sender : "CraigR3" Date : Mon, 15 Aug 94 14:44:13 EDT Subject : ALS article Bro, Here it is; please keep the larger point text intact to make sure it all stays together. And, thanks again! Please feel free to keep in touch regarding anything related to health care and methodology - Epidemiology. Craig The Cutting Edge - Investments in Biotechnology excerpt from issue no. 8 4/27/94 cThe Cutting Edge Internet Address: Cedge@aol.com / AOL: Cedge Telephone: (805) 482-2098 Editor note: As most people are well aware by this time, Regeneron (REGN) did stop their CNTF trial and it is quite possible that Synergen (SYGN) may experience difficulties as well. This is not known at this point in time. The problems in the biotech industry continue as conflict in Washington produces uncertainty over the future of health care and failures continue to pour out from the clinical trial front. SYGN and Cortech (CRTQ) recently added fuel to the fire announcing disappointing results with their blinded trials in sepsis patients. These trials were very high risk, as are the ALS trials, but they follow failures by other development stage biotechs such as Magainin (MAGN), Ribi Immunochem (RIBI), SYGN and others. Development stage biotechs are still reporting "there are no problems" but we have heard first hand of financing problems with some and venture programs being scaled back or cut. This was announced today as well in a Dow Jones newswire discussing problems in the biotech industry - many of which stem from threats of price controls. This is probably a very opportune time for readers to become acquainted with their local Congressman or Senator if they are concerned about private industry venture research. Amyotrophic Lateral Sclerosis ALS: The Approval Process Throughout the centuries that followed the teachings of early rationalists (scientific knowledge is derived through reason and intuition) and empiricists (scientific knowledge is derived from what is seen), the scientific community has struggled to craft research methods that best define causal inference. By causal inference we refer to the confidence we have in the ability to define the role of an event, condition or compound in the occurrence of a health outcome - using principles that seek to best minimize the arguments raised by philosophers of science. By treatment effect we refer to the measurement of effect in terms of a factor's influence on the frequency or risk of a health outcome. Our current FDA feels that the necessary implementation of these principles is the randomized, placebo controlled, blinded clinical trial testing a prospectively defined outcome. The clinical trial is an experiment, conducted under controlled circumstances, which allows scientists to manipulate the intervention group (those who receive the drug) for comparison to a control group (those who typically get a placebo) to determine prospectively defined treatment effect. It is typically thought to be the "gold standard" for determining causality and treatment effect. Much of the structure we see in today's FDA is the result of changes implemented in the administration in 1966. These changes did produce better scientific and ethical standards for health care policy, but many things have changed since that time. Biotechnology now explores the treatment of many different diseases - some previously untreatable or not even in existence in 1966. Many of the current standards of biostatistics and epidemiology have also greatly advanced and solidified during that period, but little has been changed in our FDA to reflect an evolving statistical world. It is easy to see how the clinical trial, the purist of statistical methodology, raises serious questions of bio-ethics. In asserting control of the clinical trial, the researchers need a comparison to define a therapeutic's treatment effect - typically a placebo. If the treatment effect is sufficient by this comparison and the trial was properly controlled, the drug in question should fare well at the FDA panel meeting that convenes to recommend or deny the drug's approval. But the use of a placebo condemns hundreds of thousands of individuals with a disease, or disorder, to suffer or die for these drugs to be approved to be marketed in the United States. In the case of terminal illnesses, many people are outraged that the same system that was designed to protect and promote human health often plays the randomized role of hangman for the sake of statistical purity. Throughout our history of medical and scientific inquiry, philosophical disagreements regarding causal inference have created different branches of research methodology - most harboring the benefit of causal inference when properly applied. It would not be a tremendous leap of faith to question whether all branches of scientific discipline are applied to best assess therapeutic treatment effect in light of bio-ethical concerns. The same plurality of discussion regarding causal inference that led to new research methods could be aptly applied to our approval process. We feel that the topic of ALS illustrates a focal point for the discussion of this issue because of the nature of the disease. With a preventable, but terminal, illness we have several levels of intervention whereas health care policy can impact the severity or outcome of the disease. AIDS is a classic example as it is a highly preventable disease. With ALS, researchers are forced to intervene at the last stage possible - where someone probably has the disorder. The problems that REGN and SYGN experienced at this stage of intervention highlight inequities that are created by our current approval process requirements. SYGN's Phase II/III trial was delayed because of the side effects they experienced while in Phase I trials. But the nature of the approval process forced them to keep recently diagnosed patients on hold. So this delay not only let diagnosed ALS patients deteriorate, but it also put them behind REGN in the race to begin large scale Phase II/III trials to test CNTF in these patients. Is this fair to allow terminally ill patients to degenerate when there are potential treatments available - especially if each day could mean death or, in this case, the loss of potentially unrecoverable neurons? In this case, a better question is - would we be better off if we used a coalescence of statistical disciplines to best assess treatment effect in selected terminal and severe illnesses? In REGN's case, the actual mandatory requirement for statistical significance relative to placebo comparison resulted in problems late in their large scale trial. They have yet to hear from the FDA regarding their Phase III CNTF trial and they do not know if they will perform another Phase III trial if they are not allowed to modify the trial. We feel the concept of dropping the use of a placebo in all clinical trials involving terminally ill patients is premature at this point - as it is very beneficial in reducing bias - but other avenues of complementary methodology should be explored for our medical future. The fields of epidemiology and biostatistics, when properly applied, could be of great value in addressing the measurement of therapeutic effect while maintaining a higher standard of medical ethics. Already we've seen numerous cases where epidemiology was applied to measure effects not easily obtained in clinical trials. We have long since felt that the FDA was in need of approval protocol changes - treatment effect is a relative term and we don't feel it has been incorporated properly into all FDA decisions regarding drug approvals. Measurement of effect, for example, does not presume that a placebo is the only measure of comparison. Causality, for example, is a comparative measurement. Kenneth Rothman argues in his book Modern Epidemiology, that an unconventional example of this would be that cigarette smoking could be a preventive to lung cancer. His argument - if the comparison of effect is the measurement of smoking one pack of cigarettes a day for 10 years compared with the fact that someone will be smoking two packs a day in that same period, then it is quite possible that smoking one pack a day is a preventive behavior in this case. This argument makes sense because the alternative is worse. If the alternative to treatment is death, then we need to address the usefulness of a particular treatment based upon the fact that death is a probable outcome if we do nothing. The FDA is often unwilling to accept this based on their belief that it could provide "false hope." In many terminal and severe diseases, this is not a relevant issue. If we use ALS as an example - ALS patients could be followed and monitored in current trials and this data could be applied later when patients leave their respective trials. As more treatments are explored and the database expands, we will have greater means to direct future research. There is always the potential for bias in an observation design study but in no way does it mean it is a rule. Certain statistical disciplines have achieved levels of causal inference that are useful in clinical medicine. This is in the absence of some of the restraints that cause bio-ethical concerns. Randomization, blinding and placebo are used in clinical trials to reduce bias. But the notion that trials are bias free simply by design is not true. As the information age progresses, patients in blinded trials will be sharing information with each other, and possibly the world, from inside their trials. We saw this recently in REGN's case as both REGN and SYGN trial patients are reporting their effects and side effects on a national support board. If those without side effects and positive effect assume they are on a placebo, can we be convinced they will not try other medications? There is a chance for differential bias even in a clinical trial. How will the FDA take this into consideration if these companies learn, after the trials are finished, that a number of potentially effective drugs were tried? If we use all of the data possible in terminal and severe illnesses, it seems possible that probationary approvals could be issued for certain experimental drugs or treatment protocols if they pass a probationary FDA panel. In this way, the patients get the drug at an earlier stage, the biotech company is allowed to funnel income into more clinical trials and research studies, and final decisions regarding the use of the drug can be made when the summation of evidence is produced. It is easy to see how past failures, such as sepsis treatments, could provide more ethical research inquires into the treatment of some diseases. Because so many people have died of sepsis, and the data have been compiled into a large database named APACHE III, we already know what a sepsis victim's near term risk of death is without subjecting him to a placebo. If the standardization of experimental data is good, comparisons could then be made of risk of survival from a particular treatment, and dose of treatment, compared with their risk of death at a selected point in time. This is relevant in other - non-life threatening - diseases as well. In Celtrix's (CTRX) Phase II macular degeneration trial, 2/3 of the patients will be getting a placebo. This study is testing BetaKine in the treatment of exudative or "wet" age related macular degeneration - using three treatment groups. Patients are randomly assigned to a BetaKine plus surgery group, surgery plus placebo group or placebo alone group. Imagine the anguish of a patient told that they are in third group. They've just been told by their ophthalmologist that they will most probably go blind, and there is some encouraging data from a new therapeutic, but that they are in the placebo alone group - there is no hiding it from them. It is surprising that historical controls were not allowed by the FDA in this situation. It is simply an indication of a larger problem. ALS: The Future The biotech research into ALS is a shining example of medical free market capitalism and the success of the Orphan Drug Act. While we await the conclusion of three large scale Phase III trials to treat ALS, newer drugs are moving into Phase I/II trials in search of a cure. Private research into ALS illustrates a system that works, but most probably needs protocol changes to best represent our collective research skills, and our sense of compassion. We must become increasingly aware that if we continue to ratchet up the risk of research, while not protecting the reward, we will see negative changes in the biotech industry. Additionally, an integration of research principles today could help usurp the eventual fragmentation caused by political pressure. The well organized, and powerful, AIDS activist groups did sway the FDA into the acceptance of parallel design, or FASTRACK, trials to not only test experimental therapeutics but avoid traditional clinical trial requirements. The problem is that, in an absence of an organized experimental drug program in complement with our current system, we run the risk of losing precious data which may help greater numbers of patients in a shorter period of time. The treatment protocols would then be separated into rigid - and potentially unethical - research requirements or unstructured exemptions for groups that lobby stronger than anyone else. In time, it seems appropriate that insurance company providers have input with regard to experimental research as it is often they who see the greatest benefit, or detriment, to their bottom line. In light of what we have learned from ALS research, we encourage the Congress and the FDA to discuss new possibilities for treatment protocols. With a focused discussion, at a national level, it seems possible that we can blend the disciplines of research methodology to best complement each other for specific diseases. This would not mean that it is simply the severity of a disease that alters the research methods used, but that the quality of the research - the confidence we have in its causality - and the ethical concerns in question, assist us in moving away from rigid conformity to adapt individually to specific disorders. We feel this would not only raise the standard of medical ethics in our country, but also improve the breadth of private research, allow for concurrent research in multiple indications, lower the cost of biotech therapeutics and shorten the time frame that delays effective therapeutics from the public. At this stage of health care reform, we feel it is a fitting topic for discussion. Contents based on information from sources believed to be reliable but accuracy and completeness cannot be guaranteed. Nothing in this publication should be construed as an offer or the solicitation of an offer to buy or sell any security. Previous results cannot be guaranteed nor should they be expected. The editors or publisher may, at any point in time, make purchases or sales of securities mentioned in this publication. This newsletter is designed for sophisticated investors who are well aware of the risk involved in securities investments. These terms apply to all communications sent from personal electronic mailboxes - Prodigy, BFFW97A, and America Online - CraigR3 and Cedge. The Cutting Edge is edited by: Craig N. Robinson MPH - Epidemiology And John Fitisoff Published by Cutting Edgex == end of als 117 ==