Optimizing exercise training to improve post-treatment health and reduce risk of comorbid chronic disease/and recurrence is imperative for long term treatment and survivorship in the cancer continuum. However, much like those studies testing the benefits of exercise for healthy persons, the clinical guidelines for cancer patients closely adhere to the exercise guidelines of World Health Organization (2019) and American College of Sports Medicine (American College of Sports Medicine, 2018) (Piercy et al., 2018; Powell et al., 2019). Overall, the recommendations are similar for both healthy and clinical populations with little or no consideration of for physical function, physiological or psychological health or disease state.

Exercise oncology studies using prescriptions based on the national exercise guidelines have often shown physiological, psychological and physical function non-responses, leading authors to conclude a given intervention is not effective and/or not strong enough evidence to base future exercise recommendations on. (Campbell et al., 2019). This is not surprising, as using a reductionist approach to exercise prescription produces singular results. These results should be viewed with caution, as a non-response in one variable does not mean the individual is not benefiting in other outcomes (see Figure 1). Exercise outcomes in exercise oncology should thus be centered around the current health status of individuals and health-related goals should be considered as a spectrum, rather than one or two outcomes. Additionally, it has been hypothesized that an individual’s response to a given exercise stimulus may vary due to the direct effects of cancer treatments on physiological systems, the symptoms and side effects of cancer treatment, and demographic differences. (Schmitz et al., 2010; Sweegers et al., 2018). Most importantly, an individual’s ability to tolerate exercise may vary from day to day during and after active treatment. (Schmitz et al., 2010). Therefore, rather than broadly prescribing the same exercise protocol across patients, technology advances and our understanding of underlying mechanisms should be used to focus on clinical outcomes that are critical to improving health. Technology can also provide several important metrics to increase a professional’s ability to understand the context of responses and allow objective assessment of the exercise prescription within a daily readiness approach.

The principles of training derived from Exercise Physiology have remained largely impervious to the transdisciplinary and holistic insights emanating from complex systems approaches (Balagué et al., 2020; Pol et al., 2020). Often exercise physiologists rely on cardiovascular, respiratory, metabolic or neuromuscular endpoints that are based on the fragmentation of fitness in dimensions and sub-dimensions derived from reductionism (Balagué et al., 2020). This concept is most readily viewed in the view of V0² max as a linear process that is trainable. Using this reasoning, every person who trained hard enough would be running the Boston marathon. This is of course not the case, as interactions change in time, both quantitatively and qualitatively. There is not a clear dose response relationship to VO (Chang et al., 2019) max among components. This is also evident in the limitations of current guidelines of exercise prescription in health and disease when reviewed on the basis of NPE. Research is also lacking to provide an understanding of exercising individuals as networked embedded systems and a clear absence of knowledge regarding the effects of exercise on the interactions among physiological systems.

Despite the adoption of a relatively homogeneous prescription approach, aerobic and strength training have been, for the most part, associated with benefits across a diverse range of populations (Bishop et al., 1999; Reid et al., 2010; Voisin et al., 2015; Flannery et al., 2019; Klil-Drori et al., 2020; Maestroni et al., 2020). On this evidence, it is assumed that a standardized, largely homogeneous exercise prescription that adopts a conventional approach is safe, efficacious, and therefore sufficient. Even though most studies present favorable results, systematic reviews and meta-analysis on exercise prescription point to the lack of high-quality studies showing the sustainability of standardized programs (Sørensen et al., 2006) and the need for personalizing the current recommendations (Zimmer et al., 2018). Current research is predominantly based on comparisons of group data means and evaluating quantitative changes of isolated variables in lab conditions. Such practices are clearly limiting the application of a precision exercise medicine approach (Balagué et al., 2020).

Current ACSM exercise guidelines are one-size fits all recommendations, which assume ideal or prototypic health and fitness state in which individualization is based on the objective evaluation of the patient’s baseline physiological status (Schmitz et al., 2010). Utilizing an approach that focuses on daily external factors to prescribe daily exercise, would allow for diversity to define fitness (Pol et al., 2020). Non-linear periodization offers an ideal framework in cancer populations due to the heterogeneity across cancers (i.e., medical history, various demographics, treatment type and duration, symptoms, comorbid chronic disease and demographics). This heterogeneity can have profound effects on daily motivation, readiness and also capacity for physical activity. (Sasso et al., 2015). Cancer treatment is associated with a myriad of physiological and psychological side effects, many of which create fluctuations in anxiety, depressive symptoms, fatigue, health related quality of life and physical function, all of which can change daily during the cancer continuum. (Craft et al., 2012; Jones and Alfano, 2013; Bower, 2014; Cvetković and Nenadović, 2016; Miller et al., 2016). Additionally, treatment can have side effects such as loss of muscle mass and increase in fat mass. (Kumar et al., 1997; Fearon et al., 2011; Elliott et al., 2017; Baracos and Arribas, 2018). Wildly disparate symptoms and side effects all support the premise that individualization that is contextually sensitive and meaningful is better to target multiple timeframes and an individual’s subjective and objective daily responses and should be considered as a prescriptive element of exercise prescription and subsequent daily training.

Non-linear periodization follows a network physiology of exercise approach, as it is a malleable method of autoregulation that considers assessment of an individual’s daily readiness is flexible nonlinear periodization. (Fleck, 2011). Flexible nonlinear periodization was developed by Fleck and Kraemer and uses the nonlinear training model framework, but changes training based on the daily readiness of a trainee to perform a specific training zone (Fleck, 2011). Daily training decisions are based upon several pieces of information that can include sleep, fatigue, physical function, and mood. In general, when performance or perceptions of ability to perform are higher, individuals pick more challenging sessions and on days perceptions are lower, individuals pick less challenging sessions. Therefore, the goal of flexible linear periodization is to alter the distribution of training to better align with an individual’s daily preparedness. Because training zones are not necessarily performed in a certain order due to self-selection.

Exercise prescription should thus focus on a Person-Centered Approach based in complex adaptive systems. Recent definitions of health reflect a dynamic interplay between the external environment and internal physiology (Speck et al. 2010; Sturmberg, 2018). Health can change in response to somatic conditions, social connectedness and emotional feelings (Sturmberg, 2018). Within this paradigm, the question becomes is this person in a stable or unstable health state and how can this stability be regained or maintained? This approach is centered in the emergent nature of a person and how objective and subjective variables inherently underly a person’s health and/or illness status.

The focus on disease management fails to see the other factors impacting health and impacting exercise outcomes (socio-economic factors) and thus the aim of prescription becomes a decrease in variability and improvements in quality of life. A daily exercise session needs to consider a patient’s health status beyond disease state and consider daily mood, nutrition, previous night’s sleep, illness (cold, cough, etc.), stress levels and the in the moment environment. These factors all individually contribute to how each exercise session will affect the physiological systems as a whole. Thus, a person-centered perspective that considers daily external variables and internal physiology (Figure 1) would combine both objective and subjective management and allow for a non-linear approach to prescription. This approach adapts the suggestions others have identified, that would allow for adapted, varied and sufficiently challenging individual exercise prescription.

Given the multitude of different responses that changing one of the four steps of exercise prescription (Figure 2) can elicit in both physiological and psychosocial adaptations, it appears the full therapeutic potential of exercise may be being masked by a lack of optimization and individualization in oncology settings. Optimization and individualization are widely employed in exercise science and the practice involves purposefully adjusting training to center around measurements of both training and non-training related stressors (sleep quality and quantity, nutrition, mood, illness, fatigue). The concept of autoregulation is one that describes an emergent process that can be used to systematically individualize exercise training (Haley et al., 2019). Autoregulation is based on an individual’s performance and perceptions of their ability to perform. Historically, autoregulation is applied in one of three ways, to adjust intra-training loads, as a weekly progression or more recently to select a daily set and repetition schemes prior to exercise based on current mood, sleep or fatigue levels. Current research has demonstrated that autoregulation of training may be superior to training strategies that employ predetermined loading strategies for such training goals as strength and increased lean body mass and is believed to be a framework that can enhance other physiological and psychological outcomes (Mann et al., 2010; Fleck, 2011; Colquhoun et al., 2017; Sturmberg, 2018; Greig et al., 2020). A method of autoregulation, non-linear periodization has recently been proposed for aerobic exercise in cancer populations (Sasso et al., 2015). Such an approach could also be useful in prescribing resistance exercise, as a nonlinear approach could prevent overtraining and plateaus in a population with multiple symptoms requiring highly context specific individualization (Schwartz, 2000; Mcnamara and Stearne, 2010; Klijn et al., 2013; Duijts et al., 2014). Nonlinear periodization is implemented by utilizing daily and weekly alterations in volume and intensity (Bower et al., 2000). Exercise programs are periodized by properly combining and monitoring the four key training principles of specificity, overload, variation and progression. Additionally, periodization of training is accomplished by implementing planned changes to any of the acute training variables to bring about continued and optimal fitness gains. Based on these factors, the prescription of exercise becomes a dynamic process. Optimized prescription must be based on the measurement of a patient’s performance or perceived ability to perform and be responsive to the changing levels of adaptation and functional capacities to be systematically individualized (Roy, 2009; Jim et al., 2011; Klemp et al., 2016).

Over 50 years of exercise research has informed practice in athletic and general populations, however these findings have rarely been used in clinical trials and populations (Campbell et al., 2019) Athletic performance has been informed by this practice which has been able to adjust and improve precision and personalization of dosing, scheduling and minimization of injury through rapid advances in exercise science (Jones and Alfano, 2013; Sasso et al., 2015). Given that the current non-specific exercise prescription in exercise oncology research and the resulting lack of individualization this current consensus guidelines it utilizes, it is important to understand how refined prescription and individualization can optimize outcomes in cancer populations trials. This could move current t exercise oncology research beyond assessments on based on quantitative benchmarks, which result in conclusions drawn from isolated variables and functions. These benchmarks provide little information about the coordinated activity of physiological systems and are not sufficiently responsive to daily training effects. This exercise prescription is based on the tenets of reductionism, which are centered around a three-step process. A needs analysis, the acute program variables (in Resistance Exercise) or the FITT principle (in Aerobic Exercise) and an application of the key training principles (specificity, overload, variation and progression. It is believed that application of these key training principles are what will produce the desired outcomes (ie strength, hypertrophy, muscular endurance, power, producing change in biomarkers, decreased depression, decreased anxiety, increased quality of life and physical function) (Wolin et al., 2012). However, given the multitude of different responses that changing one of the three steps of exercise prescription can elicit in both physiological and psychosocial adaptations, it appears the full therapeutic potential of exercise may be being masked by a lack of optimization and patient centered individualization in oncology settings.

A person-Centered Exercise Prescription offers an ideal framework in cancer populations due to the heterogeneity across cancers (i.e., medical history, various demographics, treatment type and duration, symptoms, comorbid chronic disease and demographics). This heterogeneity can have profound effects on daily motivation, readiness and also capacity for physical activity (Sasso et al., 2015). Cancer treatment is associated with a myriad of physiological and psychological side effects, many of which create fluctuations in anxiety, depressive symptoms, fatigue, health related quality of life and physical function, all of which can change daily during the cancer continuum (Craft et al., 2012; Jones and Alfano, 2013; Bower, 2014; Cvetković and Nenadović, 2016; Miller et al., 2016). Additionally, treatment can have side effects such as loss of muscle mass and increase in fat mass (Kumar et al., 1997; Fearon et al., 2011; Elliott et al., 2017; Baracos and Arribas, 2018). Wildly disparate symptoms and side effects all support the premise that individualization is better to target multiple timeframes and an individual’s subjective and objective daily responses and should be considered as a prescriptive element of exercise training.

Therefore, exercise prescription in the cancer continuum should be centered around a four-step process. This four-step process is a combination of understanding how acute exercise sessions combine to affect chronic change (Figure 2).

1) Completion of a Person-Centered Needs Analysis

This Person-Centered approach to autoregulation is based in flexible nonlinear periodization and considers an individual’s daily readiness to prescribe acute exercise. This approach uses the nonlinear training model framework but changes daily training based on the daily readiness of a trainee to perform in a specific training zone (Fleck, 2011). Daily training decisions are based upon several pieces of information that can include sleep, fatigue, physical function, and mood. In general, when performance or perceptions of ability to perform are higher, individuals pick more challenging sessions and on days perceptions are lower, individuals pick less challenging sessions and activities. The ultimate goal of such a prescription is to alter the distribution of training to better align with an individual’s daily preparedness. and allow the person to be the co-creator of their daily training session. Because training zones are not necessarily performed in a certain order due to daily fluctuations, intensity or volume does not follow a consistently increasing or decreasing pattern. This distinction is very important because it will allow clinical populations to focus on four key elements:

-more efficient recovery patterns (ie stress to recovery ratio)