C. Athena Aktipis 1, 2   Carlo C. Maley 3     Steven L. Neuberg 4

Despite the explanatory power of evolutionary theory in understanding disease and dysfunction, it has not yet become a common framework for thinking about medical problems in the laboratory or clinic.  This unfortunate delay is attributable to a variety of barriers.  Some are institutional and educational, such as the lack of evolutionary training in medical school.  Such barriers may be overcome by providing a clear set of training goals to foster a deep understanding of evolution in medical education, as suggested by Nesse et al (2010).  A second class of barriers are psychological and are likely critical to the integration of evolutionary thinking in medicine.  We suggest that several of these—the tendencies for doctors and patients to “essentialize” disease, to be risk averse, to possess a powerful disgust-elimination reaction, and to cognitively frame disease as an enemy to be vigorously and completely eradicated—limit the integration of evolutionary thinking into medical training and practice.  In the case of cancer, these psychological factors may contribute to inappropriate or dangerously aggressive treatment.

It is well known that psychological factors profoundly shape decision-making processes, including decision-making in medical contexts.  These influences are powerful across a variety of domains and have been shown to manifest in the most serious life or death decision-making contexts, including disease screening and diagnosis (as reviewed by Gigerenzer & Edwards, 2003) as well as treatment in the face of risk and uncertainty (Tversky & Kahneman, 1974; Kahneman & Tversky, 1979).  We propose that several psychological factors interfere with the integration and effective use of evolutionary thinking in medical research and clinical decision-making, potentially leading to inappropriately targeted or overly aggressive treatment that neglects the dynamic nature of the disease.

The difficulty of integrating evolutionary thinking into medicine is clearly seen in the case of cancer research and treatment. Cells in tumors evolve by natural selection through competition among mutant clones and the selective effects of cancer therapies (Merlo, Pepper, Reid, & Maley, 2006; Pepper, Findlay, Kassen, Spencer, & Maley, 2009). For over 30 years, the evolutionary theory of cancer has been accepted as the explanation for data on cancer progression, therapeutic resistance and recurrence (Nowell, 1976).  Yet, despite this acceptance, it has largely been ignored by cancer researchers and clinicians when designing research studies and treatments.  Psychological barriers may explain this problematic discrepancy.

People essentialize many categories of objects and living things, and the essentializing of disease—viewing diseases as unitary and static entities with particular natures—may interfere with evolutionary reasoning about disease and treatment.  In the case of cancer treatment, this conceptualization of cancer can lead to a neglect of its heterogeneous, dynamic and adaptive nature.  Cancer is not a unitary entity, but rather a collection of diverse cells with differential capacities for proliferation and survival.  These aspects of the disease are essential to understanding its responsiveness to treatment and the potential for selecting for therapeutic resistance.  Similar essentialist conceptualizations may interfere with effective evolutionary reasoning in infectious diseases because they also involve evolving populations.

Risk aversion and disgust psychology may also lead to barriers against implementing evolutionary approaches in medicine.  For example, cancer clinicians and patients may be overly eager to remove pre-malignant tissue because they are unwilling to tolerate the very low risk that malignancy will evolve from these “benign” tumors or pre-malignant conditions. When making decisions involving uncertainty, people are more willing to accept some errors than others.  Specifically, people are biased towards reducing the most serious of potential errors, and the costs of failing to eliminate a potentially deadly cancer is worse than the cost of removing a tumor that would turn out to be benign (see Nesse, 2005 on the ‘smoke detector’ principle and Haselton & Nettle, 2006 on error management).  This calculation may result from a framing that emphasizes the risks of developing cancer rather than a more objective evaluation of the tradeoffs that take into account the risks of intervention and the evolutionary nature of the disease.

Human disgust psychology may exacerbate this bias and contribute to overtreatment.  The emotion of disgust, with its associated eliminatory behaviors (e.g., retching, tongue protrusion), evolved to minimize exposure to dangerous pathogens (Oaten, Stevenson, & Case, 2009).  The perceived presence of an ostensibly unnatural thing living within one’s own body will engage this psychology, evoking a strong desire in both clinicians and patients to excise the parasitic and growing entity.

This combination of human tendencies toward essentialism, risk aversion, and disgust reactions to contact with potential pathogens may contribute to the simplified framing of disease as an enemy that must be immediately eliminated, thereby eliciting the very powerful psychology of inter-group warfare and conflict (Shaller & Neuberg, 2008).  This could lead to problematically aggressive approaches to cancer treatment, because the rate of the evolution of resistance is proportional to the fitness difference between sensitive and resistant cells.  In certain circumstances it may be more viable to live with cancer, treating with less aggressive approaches that acknowledge its evolutionary nature (e.g., applying chemotherapy only when a tumor is growing) (Gatenby, Brown, & Vincent, 2009).  It may even be possible to design treatments that specifically target the most aggressive cancer cells and boost the fitness of more benign cells in order to shift the balance towards slower progression of cancer (Maley, Reid, & Forrest, 2004).  This evolutionary perspective suggests that there may be an alternative to fighting cancer and other diseases to the death; instead, it may be possible to live with them as chronic but controlled diseases.

Our analysis is based on a reasoned application of empirically supported features of human psychology.  To date, however, there have been no rigorous studies of these psychological processes or others as they specifically apply to the adoption of evolutionary thinking in medicine.  Because many diseases have evolutionary components, including but not limited to cancer and infectious disease, effective treatment will ultimately depend on understanding and addressing the evolutionary dynamics of diseases. This, in turn, will depend on overcoming the psychological barriers to the adoption of evolutionary concepts and strategies in medicine. The study of those barriers and the evaluation of methods for overcoming them could have a dramatic impact on suffering and mortality due to cancer and other diseases.

1- Department of Ecology and Evolutionary Biology, University of Arizona

2- Department of Psychology, University of Pennsylvania

3- Molecular and Cellular Oncogenesis Program, Systems Biology Division, Wistar Institute

4- Department of Psychology, Arizona State University


Gatenby, R. A., Brown, J., & Vincent, T. (2009). Lessons from applied ecology: cancer control using an evolutionary double bind. Cancer Research, 69(19), 7499-7502. doi: 10.1158/0008-5472.CAN-09-1354.

Gigerenzer, G., & Edwards, A. (2003). Simple tools for understanding risks: from innumeracy to insight. BMJ,327(7417), 741-744. doi: 10.1136/bmj.327.7417.741.

Haselton, M. G., & Nettle, D. (2006). The Paranoid Optimist: An Integrative Evolutionary Model of Cognitive Biases.Personality and Social Psychology Review, 10(1), 47-66. doi: 10.1207/s15327957pspr1001_3.

Kahneman, D., & Tversky, A. (1979). Prospect theory: an analysis of decision under risk. In D. Kahneman & A. Tversky (Eds.), Choices, Values and Frames (pp. 17-43). Cambridge: Cambridge University Press.

Maley, C. C., Reid, B. J., & Forrest, S. (2004). Cancer prevention strategies that address the evolutionary dynamics of neoplastic cells: simulating benign cell boosters and selection for chemosensitivity. Cancer Epidemiology, Biomarkers & Prevention: A Publication of the American Association for Cancer Research, Cosponsored by the American Society of Preventive Oncology, 13(8), 1375-1384.

Merlo, L. F., Pepper, J. W., Reid, B. J., & Maley, C. C. (2006). Cancer as an evolutionary and ecological process. Nature reviews Cancer, 6(12), 924-935.

Nesse, R. M. (2005). Natural selection and the regulation of defenses: A signal detection analysis of the smoke detector principle. Evolution and Human Behavior, 26(1), 88-105. doi: 10.1016/j.evolhumbehav.2004.08.002.

Nesse, R. M., Bergstrom, C. T., Ellison, P. T., Flier, J. S., Gluckman, P., Govindaraju, D. R., et al. (2010). Making evolutionary biology a basic science for medicine. Proceedings of the National Academy of Sciences, 107(suppl 1), 1800-1807. doi: 10.1073/pnas.0906224106.

Nowell, P. (1976). The clonal evolution of tumor cell populations. Science (New York, NY), 194(4260), 23-28.

Oaten, M., Stevenson, R. J., & Case, T. I. (2009). Disgust as a disease-avoidance mechanism. Psychological Bulletin,135(2), 303-321. doi: 10.1037/a0014823.

Pepper, J., Findlay, S., Kassen, R., Spencer, S., & Maley, C. (2009). Cancer research meets evolutionary biology.Evolutionary Applications, 2(1), 62-70. doi: 10.1111/j.1752-4571.2008.00063.x.

Shaller, M., & Neuberg, S. (2008). Intergroup prejudices and intergroup conflicts. In In C. Crawford and D. L. Krebs (Eds.), Foundations of evolutionary psychology (pp. 401-414). Mahwah, NJ: Erlbaum.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: heuristics and biases. Science, 185, 1124-1130.

This work was supported in part by the Landon AACR Innovator Award for Cancer Prevention, Research Scholar Grant #117209-RSG-09-163-01-CNE from the American Cancer Society and NIH grants F32 CA144331, R03 CA137811, P01 CA91955, P30 CA010815,and R01 CA140657.