Modifying Adaptive Therapy to Enhance Competitive Suppression
Abstract
:Simple Summary
Abstract
1. Introduction
2. Results
2.1. A Primer on Adaptive Therapy
2.2. The Role of Tumor Size and Resistance Frequency in Adaptive Therapy
- Current design: Maximum tumor size is determined by a patient’s initial baseline burden. Different patients will have different initial burdens when they present for treatment. Despite this, the current adaptive therapy regimen always implements the “ rule” from the patient’s “initial baseline burden”. This limits the maximum size of the tumor and so lowers the amount of competitive suppression.Design modification: Can the patient’s tumor burden be safely increased? If yes, then the initiation of adaptive therapy should be delayed until this new larger “acceptable baseline burden” is reached. Withholding treatment until the tumor has grown to a larger size should increase the amount of competition and enhance the performance of adaptive therapy. Whether it is acceptable to allow the tumor to grow before initiating treatment will depend on the specific details of the patient and the cancer, as well as the size of the initial baseline burden. In general, making this decision will require balancing the possible benefits (e.g., prolonged time to progression, reduced drug use) with the possible risks (e.g., increased metastasis, greater morbidity). The relationship between tumor size and these other factors is not straightforward [32,33,34,35,36]. In the original trial, however, the initial baseline PSAs ranged from 2.42 to 109.4 ng/mL, suggesting that there is a wide range of acceptable PSA levels [13]. Although an acceptable PSA level will be different for different patients, this wide range points to the possibility that the baselines of certain patients could be safely increased.
- Current design: The “ rule” reduces the average tumor size. In the current design, treatment begins whenever the tumor reaches the baseline burden and stops whenever it falls below 50 percent of the baseline burden. These successive reductions in tumor burden reduce the average size of the population that is generating competition.Design modification: What should trigger treatment? Since larger populations generate more competition, we suggest “inverting” what triggers treatment starts and stops. Treatment should start whenever the tumor burden exceeds the baseline level by a measurable amount (e.g., larger than the baseline burden), and treatment should stop whenever the burden returns to the baseline. Figure 2 shows how this modification shifts the timing of treatment (shaded blocks in Panel b are shifted relative to shaded blocks in Panel a). This should increase the average size of the population and enhance competition.
- Current design: Patients with a high resistance frequency cannot benefit from adaptive therapy. If a patient’s initial resistance frequency is high, they will not be able to achieve a reduction in PSA during the first cycle of adaptive therapy. For these patients, treatment resembles the standard of care, and they are unable to benefit from adaptive therapy. The above suggested modifications of (i) increasing the baseline (whenever acceptable) and (ii) treating only when the burden exceeds this baseline help to ameliorate this shortcoming. With these modifications, only patients who begin with almost completely resistant tumors will be unable to complete multiple rounds of adaptive therapy.Design modification: Is the patient’s initial resistance frequency likely to be low? Although the previous modifications should allow patients with high resistance frequencies to benefit from adaptive therapy, special consideration should also be given to patients with very low resistance frequencies. Patients with low initial resistance frequencies may do better with the standard of care than with adaptive therapy (Box 2). For this reason, an effort should be made to identify and exclude patients with very low resistance frequencies. This may be difficult to do, but an evaluation of patient treatment history could help.
3. Discussion
4. Materials and Methods
4.1. Mathematical Model
4.2. Parameter Values and Simulation Details
4.3. The Role of Resistance Frequency: Additional Considerations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
ALL | Acute lymphoblastic leukemia |
mCRPC | metastatic castrate-resistant prostate cancer |
PSA | Prostate-specific antigen |
GnRH | Gonadotropin-releasing hormone |
ADT | Androgen deprivation therapy |
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Clinical Trial Identifier | Cancer Type | Therapeutic |
---|---|---|
NCT02415621 | prostate cancer | abiraterone |
(metastatic castrate resistant) | ||
NCT03511196 | prostate cancer | GnRH agonist and/or |
(stage IV castration sensitive) | abiraterone plus prednisone | |
NCT03543969 | melanoma | vemurafenib and cobimetinib |
(advanced BRAF mutant) | ||
NCT03630120 | thyroid cancer | tyrosine kinase inhibitor |
(advanced progressive 131I-refractory | ||
differentiated or medullary) |
Patient 1 | 1 | 0.8 | 0.7 | 0.6 | 1 | 0.9 | 0.4 | 0.5 | 1 |
Patient 2 | 1 | 0.8 | 0.6 | 0.5 | 1 | 0.9 | 0.4 | 0.7 | 1 |
Patient 3 | 1 | 0.9 | 0.7 | 0.5 | 1 | 0.8 | 0.4 | 0.6 | 1 |
Patient 1 | |||
Patient 2 | |||
Patient 3 |
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Hansen, E.; Read, A.F. Modifying Adaptive Therapy to Enhance Competitive Suppression. Cancers 2020, 12, 3556. https://doi.org/10.3390/cancers12123556
Hansen E, Read AF. Modifying Adaptive Therapy to Enhance Competitive Suppression. Cancers. 2020; 12(12):3556. https://doi.org/10.3390/cancers12123556
Chicago/Turabian StyleHansen, Elsa, and Andrew F. Read. 2020. "Modifying Adaptive Therapy to Enhance Competitive Suppression" Cancers 12, no. 12: 3556. https://doi.org/10.3390/cancers12123556
APA StyleHansen, E., & Read, A. F. (2020). Modifying Adaptive Therapy to Enhance Competitive Suppression. Cancers, 12(12), 3556. https://doi.org/10.3390/cancers12123556