Is it time to abandon mutation-centric metastasis as the dominant paradigm? Does ‘seed and soil’ do more harm than good?
By Denis G. Rancourt , PhD
Abstract
Part-I: I critically review the context of cancer research, where it has been advanced that most published research findings are false, that medicine itself is the third leading cause of death in the Western world, and that experienced stress arising from an individual’s position in society’s dominance hierarchy is the primary determinant of individual health.
Part-II: I critically review the randomized trials for treatments and screening, especially for breast cancer. It has been advanced that screening does more harm than good, and that treatment protocols have little effect on net population mortality from cancer. There is no robust demonstration that the treatment protocols for the common cancers do more good than harm to individual patients.
Part-III: I critically review the mutation-centric metastasis dominant paradigm of cancer, and various efforts to somewhat or definitively challenge the dominant paradigm, with an eye to answering the question “What is cancer?”
Final section: I propose a conceptual model of cancer, which incorporates the leading criticisms of the dominant paradigm, and which is testable. In my model, cancer is an age-dependent and tissue-specific stress-induced breakdown of tissue-shape homeostasis. My model is aided by a graphical picture depicting age-specific and tissue-specific curves of steady-state nodule size (DT) versus experienced stress level (S). A given curve has a critical stress (SC) beyond which there is runaway tumour growth due to tissue-response feedback. Here, “metastasis” is the simple consequence of the individual’s tissue susceptibility to loss of shape homeostasis having gone supercritical for a cluster of tissue-specific DT v. S curves. The model provides treatment strategies on three branches: Psychological, tissue-surface-shape homeostasis, and tumour growth feedback attenuation.
Introduction
This paper was presented in the uOttawa Cinema Academica series at the University of Ottawa on November 21, 2015. A video of the presentation is on YouTube (
PART-ONE,
PART-TWO). It will be “peer reviewed” if peers and others review it.
I am not a medical doctor. I am an interdisciplinary scientist with a PhD in physics. I have published over 100 articles in scientific journals, in a broad array of disciplines.
My starting outlook in researching cancer is best represented by these three non-journal-article publications:
• “A Theory of Chronic Pain: A social and evolutionary theory of human disease and chronic pain” (2011)
• “Self-Image-Incongruence Theory of Individual Health” (2014), and references therein
• Chapter: “Human Biology id Such that People Make and Inhabit Dominance Hierarchies”, in my 2013 book
The paper is organized in three main parts, followed by my proposal for a unifying model of cancer.
PART-I: Context of Cancer Research
Approximately 30% of us who are fortunate enough to live in the Western countries will be diagnosed to have died of cancer. Breast cancer is the main life-threatening disease affecting women, when tumours are present on several organs.
Prior to starting this review to find out what establishment science actually knows about cancer, it is important to admit the possibility that medicine is largely a pack of lies, the usual kinds of lies that provide the mental environment substrate that is created and maintained by any professional group that claims high status in society. In that sense, medicine should be viewed as no different than law, or even basic science itself.
Some prominent critics have made this observation from within the medical establishment, in different ways. For example, the “Gold Effect” was described by Professor T. Gold in 1979 and is the phenomenon in which a scientific (often medical) idea is developed to the status of an accepted position within a professional body or association by the social process itself of scientific conferences, committees, and consensus building, despite not being supported by conclusive evidence.
The Gold Effect was reviewed by Drs. Petr Skrabanek and James McCormick in their book Follies and Fallacies in Medicine, and it is used to analyze errors in public health policy and practice, such as the widespread use of cholesterol screening in the prevention of cardiovascular disease.
Most published research findings are false
From a different perspective, renowned medical researcher John P.A. Ioannidis applied Bayesian statistical modelling to prove that it is likely that “most published research findings are false”. I know something about Bayesian inference theory. I found Dr. Ioannidis’ argument to be entirely rigorous. Other Bayesian practitioners were critical of the work, but Ioannidis ably put them in their place.
Ioannidis showed that published medical claims of net benefits of a treatment (such as a regiment of one or more drugs) or of policy implementation (such as cancer screening or vaccination), based on statistical evaluation of large randomized trials, are most often false. In his words:
“Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias.”
He also points out what is essentially an alternative statement of the Gold Effect:
“… when more teams are involved in a scientific field in chase of statistical significance … The hotter a scientific field (with more scientific teams involved), the less likely the research findings are to be true.”
And he clearly describes main sources of researcher bias:
“Prejudice may not necessarily have financial roots. Scientists in a given field may be prejudiced purely because of their belief in a scientific theory or commitment to their own findings. Many otherwise seemingly independent, university-based studies may be conducted for no other reason than to give physicians and researchers qualifications for promotion or tenure. Such nonfinancial conflicts may also lead to distorted reported results and interpretations. Prestigious investigators may suppress via the peer review process the appearance and dissemination of findings that refute their findings, thus condemning their field to perpetuate false dogma. Empirical evidence on expert opinion shows that it is extremely unreliable.”
In his most recent critical overview, Ioannidis is merciless in his assessment of the medical research enterprise, even questioning whether fundamental lab-bench science is of any use in advancing medicine for patient benefit. In his words:
“… a novel model is needed in funding research to avoid the creation of narrow, isolated specialties that only self-perpetuate … For example, human genetics research has received tremendous funding. This money has not been wasted because other activities and high-tech industry have emerged to support the needs of the genetics community. However, few lives have been saved because of accumulated human genetics knowledge to date, and future prospects (eg, extensions to personalized and precision medicine) also are not promising. Similarly, intellectual fascination in neuroscience for many decades has led to few new practical applications …”
