Andre Esteva

Supplementary Table S2 from Validation of a Digital Pathology–Based Multimodal Artificial Intelligence Biomarker in a Prospective, Real-World Prostate Cancer Cohort Treated with Prostatectomy

Anders S Bjartell, Agnieszka Krzyzanowska, Vinnie Y.T. Liu, Meghan K. Tierney et autres

Univariable analyses of multimodal artificial intelligence (MMAI) score for biochemical recurrence (BCR) and adverse pathology (AP) at radical prostatectomy within NCCN Subgroup.

Supplementary Table S3 from Validation of a Digital Pathology–Based Multimodal Artificial Intelligence Biomarker in a Prospective, Real-World Prostate Cancer Cohort Treated with Prostatectomy

Anders S Bjartell, Agnieszka Krzyzanowska, Vinnie Y.T. Liu, Meghan K. Tierney et autres

Comparison of multimodal artificial intelligence (MMAI) score to individual clinical variables, NCCN risk groups, and CAPRA score.

Integration of AI-based risk-stratified therapy to optimize outcomes in localized prostate cancer.

Purvish Trivedi, Ryan Putney, Riley Smith, Esther N. Katende et autres

e17131 Background: Androgen deprivation therapy (ADT) is the backbone of systemic treatment for prostate cancer (PCa). However, ADT is also associated with increased cardiovascular disease (CVD) risk. This is particularly evident among members of the underserved population who have the highest incidence …

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Image-only and multimodal AI digital pathology biomarkers to demonstrate risk stratification across standard prostate cancer management strategies.

Xinglei Shen, Rana R. McKay, Yi Ren, Xiaoxuan Yang et autres

5023 Background: Reliable risk stratification across standard treatment pathways is essential for the clinical adoption of precision medicine biomarkers in localized prostate cancer. We previously developed and validated a multimodal artificial intelligence (MMAI) model that integrates digitized hematoxylin and eosin (H&E) prostate …

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External validation of a digital pathology-based multimodal artificial intelligence (MMAI)-derived prognostic biomarker in the randomised phase III CHHiP trial.

Sarah Stewart, Elizabeth S. Limb, Holly Tovey, Yi Ren et autres

308 Background: Risk stratification in localised prostate cancer (PCa) based on clinicopathological parameters is inadequate, leading to under- and over-treatment. We used CHHiP trial data to externally validate a previously-developed MMAI prognostic model with potential for cost-effective improved treatment personalisation. Methods: H&E …

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An artificial intelligence–digital pathology algorithm to predict outcomes in a cohort of men diagnosed with prostate cancer within a low resource setting.

Samantha Webking, Purvish Trivedi, Ryan M. Putney, Esther N. Katende et autres

399 Background: In the era of precision oncology, personalized prognostic biomarkers have demonstrated superior prostate cancer (PCa) risk stratification, but their deployment in low- and middle-income countries (LMICs) is limited by resource and infrastructure constraints. Although digital pathology-based multimodal artificial intelligence (MMAI) …

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Development and Validation of a Multimodal Artificial Intelligence–derived Digital Pathology–based Biomarker Predicting Metastasis Among Patients with Biochemical Recurrence After Radical Prostatectomy in NRG/RTOG Trials

Todd Matthew Morgan, Yi Ren, Siyi Tang, Wouter Zwerink et autres

BACKGROUND AND OBJECTIVE: Biochemical recurrence (BCR) after radical prostatectomy (RP) is a heterogeneous disease state in prostate cancer with multiple treatment options. Improved risk stratification could enable more personalized decision-making. We developed and validated a digital pathology-based multimodal artificial intelligence (MMAI) model …

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Multimodal Artificial Intelligence Model From Baseline Histopathology Adds Prognostic Information for Distant Recurrence Assessment in Hormone Receptor–Positive/Human Epidermal Growth Factor Receptor 2–Negative Early Breast Cancer

Daniel Kates-Harbeck, Hans Heinrich Kreipe, Oleg Gluz, Matthias Christgen et autres

PURPOSE: Prognostic assessment in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) early breast cancer (EBC) remains challenging, given relatively low rates of disease progression. Modern artificial intelligence (AI)-based techniques have provided advanced prognostic tools in cancer. PATIENTS AND METHODS: The …

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External validation of a digital pathology-based multimodal artificial intelligence-derived prognostic model in patients with advanced prostate cancer starting long-term androgen deprivation therapy: a post-hoc ancillary biomarker study of four phase 3 randomised controlled trials of the STAMPEDE platform protocol

Charles T.A. Parker, Larissa Sena Teixeira Mendes, Vinnie Y.T. Liu, Emily Grist et autres

BACKGROUND: Effective prognostication improves selection of patients with prostate cancer for treatment combinations. We aimed to evaluate whether a previously developed multimodal artificial intelligence (MMAI) algorithm was prognostic in very advanced prostate cancer using data from four phase 3 trials of the …

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Supplementary Figure S1 from Validation of a Digital Pathology–Based Multimodal Artificial Intelligence Biomarker in a Prospective, Real-World Prostate Cancer Cohort Treated with Prostatectomy

Anders S Bjartell, Agnieszka Krzyzanowska, Vinnie Y.T. Liu, Meghan K. Tierney et autres

Multimodal artificial intelligence (MMAI) biomarker score distribution by A) NCCN and B) CAPRA risk groups.

Data from Validation of a Digital Pathology–Based Multimodal Artificial Intelligence Biomarker in a Prospective, Real-World Prostate Cancer Cohort Treated with Prostatectomy

Anders S Bjartell, Agnieszka Krzyzanowska, Vinnie Y.T. Liu, Meghan K. Tierney et autres

AbstractPurpose: A multimodal artificial intelligence (MMAI) biomarker was developed using clinical trial data from North American men with localized prostate cancer treated with definitive radiation, using biopsy digital pathology images and key clinical information (age, PSA, and T-stage) to generate prognostic scores. …

Supplementary Table S1 from Validation of a Digital Pathology–Based Multimodal Artificial Intelligence Biomarker in a Prospective, Real-World Prostate Cancer Cohort Treated with Prostatectomy

Anders S Bjartell, Agnieszka Krzyzanowska, Vinnie Y.T. Liu, Meghan K. Tierney et autres

Demographic and clinical characteristics of the UPCA referral cohort.