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PEER-TO-PEER CLINICAL CONVERSATIONS |
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Prognostic Power of the Multi-Modal Artificial Intelligence Biomarker in the CHAARTED Trial Subset
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Mark Markowski, MD, PhD
Zach Klaassen speaks with Mark Markowski about the advancements in AI, particularly the ArteraAI Prostate Test, and its implications for prostate cancer treatment. Dr. Markowski explains how ArteraAI has evolved from predicting treatment responses in localized prostate cancer to potentially guiding treatment decisions in metastatic hormone-sensitive prostate cancer.
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Best Practices for Successfully Implementing Triplet Therapy in mHSPC
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Christopher Pieczonka, MD
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| Christopher Pieczonka discusses the management of metastatic hormone-sensitive prostate cancer with a focus on triplet therapy. Dr. Pieczonka emphasizes that ADT is no longer the standard of care as monotherapy for metastatic prostate cancer, citing the ARASENS study's results, which demonstrate the overall survival benefit of adding docetaxel and Nubeqa to ADT.
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| The EvoPAR-Prostate 01 Trial: Novel PARP Inhibitor Saruparib in mHSPC |
| Neeraj Agarwal, MD, FASCO |
| Zach Klaassen discusses the EvoPAR-Prostate 01 trial with Neeraj Agarwal. The trial examines a new PARP inhibitor combined with ARPI in metastatic hormone-sensitive prostate cancer, both in biomarker-positive and -negative populations. |
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| Novel Targets and Treatment Developments in Metastatic Hormone-Sensitive Prostate Cancer
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| Zachary Klaassen, MD, MSc and Rashid Sayyid, MD, MSc
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| There is still an unmet need to reach these patients with new treatment options and find new novel targets. Ultimately, the answer to guiding personalization of therapy in mHSPC likely lies in tumor biology and biomarkers for directing treatment. Zach Klaassen and Rashid Sayyid highlight new novel targets and address recent treatment development and prognostication approaches that may improve outcomes among mHSPC.
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| Prognostic Validation of a Digital Pathology-Based Multi-Modal Artificial Intelligence Biomarker in Patients with Metastatic Hormone-Sensitive Prostate Cancer from the CHAARTED Trial (ECOG-ACRIN EA3805) |
| Mark Markowski, MD, Ph.D. |
| Mark Markowski presented the validation of a digital pathology-based multi-modal AI (MMAI) biomarker in metastatic hormone-sensitive prostate cancer (mHSPC) patients from the CHAARTED trial. The ArteraAI MMAI biomarker effectively predicted overall survival, demonstrating significant prognostic value independent of treatment, metastatic burden, and status at diagnosis, with higher MMAI scores correlating with lower survival rates. |
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| Introduction to mHSPC – What Are Relevant Prognostic/Predictive Factors for the Management of Patients?
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| Matthew Smith, MD, Ph.D. |
| Matthew Smith discusses key prognostic and predictive factors for managing metastatic hormone-sensitive prostate cancer. Prognostic biomarkers like disease presentation, anatomic metastases patterns, and disease volume significantly influence overall survival. Additionally, specific gene alterations and high Decipher scores correlate with poorer outcomes.
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| Future Changes in the Setting of mHSPC |
| Gerhardt Attard, MD, Ph.D. |
| Gerhardt Attard discusses future changes in managing metastatic hormone-sensitive prostate cancer (mHSPC), emphasizing treatment advancements and biomarker integration. Key phase 3 trials are ongoing, but there's unanimous agreement that immune checkpoint inhibitors have no role in unselected M1 prostate cancer starting ADT. |
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| External Validation of a Digital Pathology-Based Multimodal Artificial Intelligence (MMAI)-Derived Model in High-Risk M0/M1 Prostate Cancer Starting ADT in the Docetaxel or Abiraterone Phase 3 STAMPEDE Trials |
| Charles Parker, Ph.D. |
| Charles Parker presented the external validation of the ArteraAI multimodal artificial intelligence (MMAI) model in high-risk M0/M1 prostate cancer from the STAMPEDE trials. The study validated that ArteraAI, which incorporates digitized histopathology, Gleason score, T-stage, age, and pre-ADT PSA, strongly predicted prostate cancer-specific mortality (PCSM) and other survival metrics. |
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| State-of-the-Art Lecture: How to Personalize Treatment in mHSPC? More than Just Counting Metastases |
| Karim Fizazi, MD, Ph.D. |
| Karim Fizazi, at the 2024 EAU annual meeting, highlighted the need to personalize mHSPC treatment beyond just counting metastases. He discussed the importance of considering factors like disease burden, timing of metastases, and biomarker-based approaches to optimize treatment strategies. Future directions include utilizing metabolic modulators and integrating biomarkers for more tailored therapies. |
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| PIONEER: Development of a Predictive Model for Death Amongst Patients with mHSPC Treated with One of the Approved Treatment Plans Based on Characteristics Present at Admission Using Big Data |
| Rossella Nicoletti, MD |
| Rossella Nicoletti presented preliminary results from the PIONEER project, which developed a predictive model for mortality among mHSPC patients using real-world data. Key factors influencing mortality included age, cancer variant, and metastasis type, with the model achieving 74.3% accuracy in predicting death within the first year after diagnosis. While promising, further validation is needed to confirm these findings. |
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