Mathematical Biomarkers Predict Prostate Cancer Outcomes in Adaptive Therapy
核心洞察
A study in JAMA Oncology identified mathematical biomarkers derived from PSA metrics that predict prostate cancer (搜索) outcomes, including time to progression and overall survival, with high certainty.
The adaptive therapy score strongly correlated with prolonged time to progression and was validated in a separate cohort of 13 patients receiving adaptive abiraterone acetate treatment.
Both adaptive therapy score and time to progression conferred prolonged overall survival, whereas standard PSA metrics showed no association with survival.
Most anti-cancer approaches, including chemotherapy, radiation, immunotherapies, targeted therapies, and bone marrow transplants, aim to eliminate cancer cells. However, these strategies do not always maximize cancer cell killing and can cause toxicity in healthy tissues throughout the body. In addition to toxic side effects, strategies that activate cancer-killing mechanisms can also upregulate factors that promote treatment resistance.
To prevent treatment resistance while still controlling tumor growth, some studies have explored modified protocols, such as reducing drug doses or adding intermittent breaks during treatment. These approaches aim to control tumors, not necessarily destroy them. Adaptive therapy—personalized treatment regimens that modify drug doses and schedules based on an individual patient's disease characteristics—has recently emerged from this research.
Adaptive therapy has shown promise for the treatment of prostate cancer (搜索). In this setting, intermittent breaks in drug delivery can control, but not minimize, prostate tumors. While effective in a subset of patients, oncologists have lacked a reliable way of identifying which patients will benefit from this treatment approach.
A new study in JAMA Oncology has addressed this unmet clinical need with new data that identify mathematical biomarkers to predict outcomes, including time to progression, mean daily dose, and overall survival, with a high degree of certainty.
Modeling Tumor Growth Kinetics
The researchers first used a previous study of 40 prostate cancer (搜索) patients to model an equation describing overall tumor growth and to understand the growth kinetics of drug-sensitive and drug-resistant cells in each patient. Patients in the study received intermittent androgen deprivation therapy. The researchers then derived mathematical biomarkers from standard prostate-specific antigen (搜索) (PSA) metrics measured in the first cycle of treatment.
Adaptive Therapy Score and Validation
Using mathematical modeling, the researchers developed an adaptive therapy score that strongly correlated to prolonged time to progression. Next, the researchers validated the model using data from a separate study including 13 prostate cancer (搜索) patients who received adaptive abiraterone acetate treatment. In this cohort, clinical time to progression also correlated with the adaptive therapy score.
Survival Outcomes
Notably, the researchers report that both adaptive therapy score and time to progression conferred prolonged overall survival. In contrast, standard PSA metrics had no association with overall survival.
The study concludes that mathematical biomarkers derived from PSA metrics predicted patient-specific outcomes, including survival. This readout performed better than PSA monitoring alone, suggesting that adaptive therapy scoring could help inform treatment decisions.