SHOWALTER, TIMOTHY

Background: The rapid adoption of digital pathology and artificial intelligence (AI) in oncology creates multiple opportunities for precision diagnostics but also creates an urgent need for evidence-based standards to ensure safe and effective implementation. Goal: This article, developed by the Digital Pathology Association, presents recommendations for digital pathology as well as the validation and clinical utility of AI-enabled digital pathology tools in clinical practice. This guidance addresses analytical and clinical validation, algorithm reliability, and criteria for establishing clinical utility attributed to test use. Key recommendations emphasize separate validation of scanning processes and AI algorithms, concordance studies to support interscanner generalizability, rigorous assessment of accuracy and reliability in real-world settings, and clear description of algorithmic use limitations. These recommendations further provide frameworks for when AI may replace or augment existing diagnostic approaches, such as biomarker scoring, cancer diagnosis, and prognostic risk assessment. Conclusions: By considering payer, regulatory, and clinical perspectives, the recommendations promote transparency, trust, and reproducibility in digital pathology while encouraging value-based care delivery. We support responsible innovation in computational pathology, ensuring that AI applications achieve not only technical performance goals but also deliver measurable clinical benefit to patients.

LBA5012 Background: There is a critical evidence gap on the relative benefits and harms of proton therapy (PT) compared with photon-based intensity-modulated radiation therapy (IMRT) in prostate cancer. Herein we report early results from COMPPARE, a non-randomized comparative study of outcomes with PT and IMRT in prostate cancer. Methods: Between 2018-2022, 2524 patients from 51 facilities (28 PT and 23 IMRT) enrolled in COMPPARE, including 1501 treated with PT and 1023 treated with IMRT, and were followed prospectively. Treatment naïve patients with localized prostate cancer except those with very high-risk disease were eligible. Treatment was pragmatic with daily standard fractionation (1.8-2.1 Gy) and moderate hypofractionation (2.4-3.1 Gy) permitted. Use of rectal spacers and androgen deprivation were at physician discretion. Patient-reported quality of life data and treatment team-reported toxicity and disease control outcomes were collected at baseline and pre-specified time intervals via VisionTreeOptimalCare; treatment planning and delivery data were collected via the Advanced Treatment Consortium. We analyzed 1404 PT patients and 939 IMRT patients. We report the early primary endpoint of the study, a comparison of patient reported bowel urgency and bowel frequency at 2-years using the EPIC tool, and the secondary endpoints of 2-year CTCAE v5 ≥ grade 2 gastrointestinal toxicity outcomes and 3-year freedom from biochemical progression (FFBP) results reported by the study teams. Results: Study sample size was targeted at 1,500 PT patients and 1,000 IMRT patients, and median follow-up time was 4.0 years. The primary endpoint and secondary toxicity 2-year endpoints focused on the alternative hypothesis of PT superiority. All results include inverse probability of treatment weighting. Using generalized linear mixed effects models, we found there to be no significant difference in EPIC bowel urgency scores (p = 0.324) or bowel frequency scores (p = 0.514) between PT and IMRT cohorts over time up to the 2-year endpoint. For grade 2 gastrointestinal toxicity, the 2-year cumulative incidence was 5.2% for PT and 5.6% for IMRT. Gray’s Test for competing risks showed a hazard ratio (HR) of 0.91 [95% confidence interval (CI): 0.65-1.28, p = 0.6] for PT versus IMRT. The exploratory non-inferiority endpoint of 3-year FFBP was 98.0% for PT and 97.9% for IMRT, and Gray’s Test showed a HR of 0.95 (95% CI: 0.52-1.71, p = 0.90). Conclusions: Analysis of early results of COMPPARE show no significant differences between PT and IMRT in patient reported bowel frequency and urgency, grade ≥2 gastrointestinal toxicity, or FFBP. Assessment of long-term disease control, late toxicity and secondary malignancy will require longer follow-up. Clinical trial information: NCT03561220 .

Retrieval-augmented generation (RAG) is rapidly emerging as a transformative paradigm for large language models (LLMs), especially in high-stakes domains like oncology that demand precision, factual grounding, and up-to-date knowledge. By pairing LLMs with external knowledge repositories, RAG systems explicitly ground model outputs in relevant retrieved documents, helping to reduce hallucinations and ensure responses reflect current evidence. In oncology, where clinical knowledge evolves continually with new research and drug approvals, RAG offers a way to integrate the latest data (e.g., trial results, guidelines, genomic databases) into decision-making. This review synthesizes the technical foundations of RAG, including its architecture and key components, and examines current applications in oncology such as clinical decision support, patient education, radiology reporting, pathology analysis, and genomics-driven precision medicine. We highlight recent studies that demonstrate RAG’s potential—for instance, improving treatment recommendations by incorporating genetic profiles and literature, and enhancing diagnostic accuracy by integrating guidelines. We also discuss emerging developments like multimodal RAG (combining text with imaging or other data), ensemble model approaches, and new explainability tools that trace model outputs to sources. Finally, we critically analyze the limitations and challenges of deploying RAG in healthcare, including computational costs, retrieval errors, noise or conflicts in retrieved information, and ethical and regulatory considerations. While RAG-based systems show promise in augmenting oncologists’ expertise with timely knowledge, careful implementation, high-quality curation of knowledge bases, and human oversight will be crucial for safe and effective adoption in clinical practice.