Using the Cell-Cycle Risk Score to Predict the Benefit of Androgen-Deprivation Therapy Added to Radiation Therapy in Patients with Newly Diagnosed Prostate Cancer

Urology Medicine Oncology
Prostate Cancer Cell-Cycle Risk Score Radiation Therapy Androgen-Deprivation Therapy 10-Year Metastasis Risk Individualized Genomic Testing

Using Cell Cycle Risk Score to Predict the Benefit of Radiotherapy Combined with ADT in Newly Diagnosed Prostate Cancer Patients

Background

Prostate cancer is one of the most common cancers among men globally. In terms of treatment, localized prostate cancer is often treated primarily with radiotherapy (RT). However, the efficacy of RT alone is often suboptimal, especially for intermediate and high-risk patients. Expert guidelines recommend combining androgen deprivation therapy (ADT) with radiotherapy in certain cases to enhance therapeutic outcomes. However, ADT often comes with side effects such as hot flashes, fatigue, sexual dysfunction, bone loss, cognitive changes, and cardiovascular risks, which may impact the patient’s quality of life in the long term. Therefore, how to balance the risks and benefits of ADT and propose personalized treatment plans has become a critical concern for both clinicians and patients.

Advances in genomics have opened new possibilities for personalized treatment. This paper describes a mathematical model that can predict the 10-year metastasis risk from combined ADT and RT treatment based on individual clinical cell cycle risk (CCR) scores. This provides essential guidance for prostate cancer patients and doctors when considering treatment intensification.

Study Source

This research was conducted by Jonathan D. Tward (MD, PhD) and his team, with key participants including Lauren Lenz (MS), Alexander Gutin (PhD), Wyatt Clegg (MS), Chelsea R. Kasten (PhD), Robert Finch (MS, CGC), Todd Cohen (MD), Jeff Michalski (MD), and Amar U. Kishan (MD). The study was accepted on March 21, 2024, and published on May 15, 2024, in the “JCO Precision Oncology” journal (DOI: https://doi.org/10.1200/po.23.00722).

Study Process

Data Sets

This study used data from two cohorts of male prostate cancer patients: 1. RT Alone Treatment Cohort: Including 467 patients from two previously published retrospective cohort studies. 2. Clinical Cohort: Including 56,485 patients who underwent Prolaris testing between January 1, 2020, and October 31, 2022.

Subjects and Process

In the RT Alone Treatment Cohort, the CCP scores and other clinical data of the subjects were recorded and summarized. The Prolaris test was used for RNA extraction and gene expression detection to calculate the cell cycle progression (CCP) score. By integrating CCP scores and the UCSF Prostate Cancer Risk Score, a CCR score was obtained.

Statistical Methods

Using a causal Cox proportional hazards model, the 10-year metastasis risk was predicted for RT alone treatment. Subsequently, based on randomized trial rules, the relative benefit of adding ADT was estimated. Additionally, confidence intervals were generated through simulation methods, and ARR (Absolute Risk Reduction) values and NNT (Number Needed to Treat) were calculated.

Main Results

The study showed that for prostate cancer patients, those with higher CCR scores obtained a more significant absolute risk reduction from ADT combined with RT. For example, when the CCR is 3.690, the absolute risk reduction from adding ADT can reach 17.1%, with an NNT of only 6, meaning that treating 6 patients can prevent 1 metastasis within 10 years. Conversely, the benefit significantly decreases for patients with lower CCR scores. For example, with a CCR below 2.112, the average ARR of adding ADT is only 0.86%, while the NNT is as high as 116.

Conclusion and Significance

The CCR score can provide precise metastasis risk predictions for prostate cancer patients, guiding whether treatment intensification is needed. This personalized prediction was further validated, showing that for patients with CCR scores above a certain threshold (e.g., 2.112), adding ADT significantly reduced the 10-year metastasis risk. This method not only helps clinicians and patients make more informed treatment decisions but also filters out treatment recommendations based solely on group data rather than individual risk in shared decision-making.

Study Highlights

  • Personalized Risk Assessment: This paper is the first to use a mathematical model to combine CCR scores with the relative benefit of ADT treatment, predicting the 10-year metastasis risk individually.
  • Threshold Verification: The study validated the threshold of the CCR score, showing that when this value is exceeded, ADT combined with RT significantly reduces the metastasis risk.
  • Data Support: Detailed analysis using large-scale retrospective clinical datasets ensures the reliability and generalizability of the results.

Limitations and Future Research Directions

The primary limitation of the study is that risk estimates come from retrospective datasets. Decisions, particularly for high-risk patients, should be made cautiously. Additionally, the model assumes a constant relationship between the CCR score and ADT response, which can be externally validated and optimized with more independent datasets in the future.

Summary

Using CCR scores for personalized risk assessment provides clear treatment guidance for prostate cancer patients, helping them balance risks and benefits in treatment choices, thereby improving clinical decision-making precision and effectiveness. This study not only offers a new perspective on the application of personalized medicine in prostate cancer treatment but also demonstrates the great potential of genomics in clinical practice.