Digital histopathology-based multimodal artificial intelligence scores predict risk of progression in a randomized phase III trial in patients with nonmetastatic castration-resistant prostate cancer.
Bibliographic record
Abstract
5035 Background: The addition of apalutamide (APA) to androgen deprivation therapy (ADT) improved metastasis-free survival (MFS) and second progression-free survival (PFS2) among patients (pts) with nonmetastatic castration-resistant prostate cancer (nmCRPC) [1]. We applied a previously-reported digital histopathology-based multimodal AI (MMAI) algorithm developed based on 5 phase III randomized trials, validated, and accepted to NCCN guidelines for localized prostate cancer, to evaluate whether MMAI could define risk of progression among nmCRPC pts treated with APA or placebo in the SPARTAN trial. Methods: Pts enrolled in the SPARTAN trial with available H&E-stained biopsy slides from their primary diagnosis were included. H&E slides were digitized. Baseline clinical parameters to generate MMAI scores were Gleason score, age, T stage, and PSA. MMAI scores for distant metastasis (DM) were generated, ranging from 0 to 1. Pts were further categorized into MMAI non-high-risk and high-risk groups using a previously established score cutoff. Kaplan Meier estimates were calculated for PFS2 and MFS; comparisons were performed using log-rank test and Cox proportional-hazards regression for treatment arms and MMAI risk groups. Two-way ANOVA was used to evaluate the interaction between treatment arms and risk groups. Results: The study included 471 pts with 1051 biopsy pathology slides: 311 pts treated with APA, and 156 with placebo. 55 pts were excluded due to missing treatment (n=4) or clinical data (n=49) and inadequate H&E images (n=2), resulting in 273 evaluable APA-treated and 147 placebo-treated pts. 63% of pts were MMAI high risk and 37% MMAI non-high risk. MMAI high risk pts demonstrated significant improvement in MFS with APA (HR 0.19 (95% CI: 0.12-0.29, p<0.005)), but not in PFS2 (HR 0.76 (95% CI: 0.45-1.28, p=0.30)). There was a significant interaction between MMAI risk group and treatment for MFS (p=0.02). Among the placebo-treated cohort, MMAI high risk status was associated with shorter MFS (HR 2.98 (95% CI: 1.72-5.18, p<0.005)) and PFS2 (HR 1.83 (95% CI: 1.09-3.09, p=0.02)). For APA-treated pts, MMAI risk group was not associated with MFS and PFS2. Conclusions: These findings suggest that MMAI may provide prognostic risk stratification for nmCRPC pts and that MMAI high-risk pts may benefit most from treatment with APA. The current results represent the first evaluation of this MMAI classifier in the nmCRPC setting. Prospective validation is warranted. [1] Smith MR, Saad F, Chowdhury S, et al.; SPARTAN Investigators. Apalutamide treatment and metastasis-free survival in prostate cancer. N Engl J Med. 2018;378(15):1408-1418. Clinical trial information: NCT01946204 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".