Citations

Abstract Minimal residual disease (MRD) has been endorsed by the FDA Oncology Drugs Advisory Committee as an endpoint for accelerated approval in multiple myeloma based on individual patient data collected from randomized trials. However, emerging data from recent trials were not included. A novel artificial intelligence (AI)–assisted framework is proposed, which automates information identification and extraction, providing up-to-date analyses that confirm moderate trial-level and strong individual patient–level associations between MRD− rates at suspected complete response (MRD-CR) and survival endpoints in multiple myeloma. Specifically, this study utilized an AI-assisted framework that identifies relevant studies and filters critical information to analyze published data via 2 independent objectives. First, we examined the trial-level association using the coefficients of determination (R2) and its 95% confidence intervals (CI) based on published statistics of treatment effects on MRD and various endpoints. Next, we generated synthetic individual patient data with covariates through AI-curated tools to estimate the individual-level association. The AI tool searched for eligible randomized clinical trials (RCT). A total of 20 two-arm comparisons from 19 RCTs were analyzed. Trial-level analysis showed an R2 of 0.71 (95% CI, 0.52–0.89) pooling disease subpopulations. Furthermore, AI techniques were applied to create synthetic individual data, combining information extracted from Kaplan–Meier curves and subgroup analyses from published literatures. Using generated synthetic data, we estimated the individual-level correlation between MRD-CR rates and progression-free survival outcomes with a bivariate copula model and calculated a global odds ratio of 7.28 (95% CI, 5.60–8.95). Significance: (i) A novel AI-assisted framework is proposed, which automates information identification and extraction, providing rapid up-to-date analyses. (ii) Moderate trial-level and strong individual patient–level associations between MRD and various clinical endpoints in multiple myeloma are confirmed.

Abstract Background: Adhering to 2018 World Cancer Research Fund (WCRF)/American Institute for Cancer Research (AICR) Cancer Prevention Recommendations is reportedly associated with better survival among long-term colon cancer survivors (likely affected by immortal time bias). Thus, it is important to validate survival benefits by assessing adherence shortly after diagnosis, and further investigation is needed to examine its association with chemotherapy outcomes. Methods: Using an NCI-sponsored adjuvant chemotherapy trial conducted in patients with stage III colon cancer (CALGB/SWOG 80702; NCT01150045), we included 1,666 patients who returned valid Willett food frequency questionnaires (FFQ) at chemotherapy initiation and derived WCRF/AICR scores accordingly (higher score suggesting higher adherence). The primary outcome was disease-free survival (time from FFQ completion to recurrence or death), and secondary outcomes were reduced relative dose intensity (RDI; <85% suggesting worse completion) and severe toxicities (grade ≥3 for any chemotherapy-related toxicity). To estimate the associations of WCRF/AICR scores (quartiles) with survival and chemotherapy outcomes, we conducted multivariable Cox proportional hazards regression for disease-free survival and multivariable logistic regression for reduced RDI and severe toxicities. Results: Compared to those in the lowest quartile of the WCRF/AICR score, patients in the highest quartile had significantly better disease-free survival (hazard ratio: 0.75 [0.58, 0.98], Ptrend = 0.02) and lower risk of reduced RDI (odds ratio [OR]: 0.74 [0.54, 1.00], Ptrend = 0.03), but not for severe toxicities (OR: 1.24 [0.93, 1.67], Ptrend = 0.11). Conclusions: In patients with stage III colon cancer, higher adherence to WCRF/AICR recommendations was associated with better survival and chemotherapy completion, but not for severe toxicities. Funding: https://acknowledgments.alliancefound.org Citation Format: En Cheng, Chao Ma, Qian Shi, Anthony F. Shields, Peter T. Campbell, Ardaman P. Shergill, Katherine A. Guthrie, Felix Couture, Philip Kuebler, Pankaj Kumar, Benjamin Tan, Smitha S. Krishnamurthi, Kimmie Ng, Eileen M. O'Reilly, Justin C. Brown, Philip A. Philip, Jeffrey A. Meyerhardt. Associations of WCRF/AICR recommendations with survival and chemotherapy outcomes in colon cancer: CALGB/SWOG 80702 (Alliance) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5038.

This chapter provides a high-level overview of clinical informatics (CI) and artificial intelligence (AI) in healthcare. It covers foundational concepts such as electronic health records (EHRs) and data standards, current applications including Clinical Decision Support Systems (CDSS) and ambient scribing/documentation, and near-term directions for both clinicians and patients. The chapter also introduces how foundational CI systems and healthcare data are leveraged to develop AI solutions, ranging from traditional machine learning to large language models, while addressing key issues such as bias, generalizability, and regulatory considerations. Finally, the chapter examines a potential future in which decentralized AI models augment clinicians in their daily work, generate deeper clinical insights, and transform patient care through advanced predictive models and digital twins.

Abstract Background Surrogate endpoints are increasingly used as the basis of cancer drug approvals. A strong association between treatment effects on the surrogate and true endpoint is essential for their validation as reliable endpoints. We assess the current evidence of trial-level surrogacy for colorectal cancer (CRC) endpoints through a novel framework. Methods We developed a framework to grade the quality of oncology surrogate endpoints in 7 domains of the surrogate relationship: data source quality (A-B); disease setting homogeneity (0-3); uniformness of surrogate and true endpoint definitions (0-3); number of trials evaluated (0-4); and individual- (0-2) and trial-level associations (0-8). We screened PubMed using keywords and medical subject headings terms for meta-analyses published before July 6, 2024, validating surrogate endpoint associations across CRC trials. Two reviewers blindly assessed each article before reaching a consensus score. The main outcomes were framework-derived evidence scores and reported trial-level associations (R2) with overall survival. Results A total of 18 articles were identified, containing 39 evaluations of 12 unique surrogate endpoints for overall survival. Evidence scores ranged from B6 to A23. Only disease-free survival consistently demonstrated high-quality evidence of trial-level surrogacy (≥A18, median R2 = 0.92). Progression-free survival and objective response rate were low-quality surrogates in metastatic CRC (progression-free survival: B6-A15, median R2 = 0.55; objective response rate: B6-A13, median R2 = 0.33). Other evaluated endpoints were demonstrated to be unreliable surrogates. Conclusion Disease-free survival shows high-quality surrogacy in stage II-III colon cancer. Endpoints identified in the metastatic setting demonstrate inconsistent surrogacy evidence. Reassessment and identification of new endpoints are warranted, particularly with immunotherapy.

Background: Healing of the tendon-bone interface (TBI) after rotator cuff injury is limited, often leading to scar-mediated repair. Decellularized tendon fibrocartilage–bone composite (dTFBC) and bone marrow mesenchymal stem cell sheets (BMSCS) improve repair in preclinical models, but full scaffold encapsulation with mechanical preconditioning remains unexplored. Purpose: To evaluate TBI regeneration using mechanically preconditioned, BMSCS-encapsulated dTFBC scaffolds in a rabbit model. Study Design: Controlled laboratory study. Methods: A total of 48 male New Zealand White rabbits were randomized into 4 groups (n = 12 each): (1) standard repair (control); (2) repair with dTFBC; (3) repair with dTFBC-BMSCS; and (4) repair with mechanically preconditioned dTFBC-BMSCS (mdTFBC-BMSCS). Healing at 12 weeks was assessed via gross observation, histomorphological and immunohistochemical analyses, and biomechanical testing. Results: The mdTFBC-BMSCS group demonstrated a higher ultimate failure load (mean, 203.9 ± 65.6 N) than both the control (118 ± 37.4 N; P = .003) and dTFBC groups (127 ± 44.1 N; P = .008), with no significant difference between the 2 BMSCS-treated groups. Histological analysis revealed enhanced fibrocartilage formation, improved collagen fiber organization, and reduced inflammation infiltration at the TBI in the mdTFBC-BMSCS group. Immunohistochemical analysis showed greater collagen type 2 alpha 1 chain-, interleukin 10-, and arginase 1-positive areas in the mdTFBC-BMSCS group than in the control and dTFBC groups. Conclusion: Mechanically preconditioned, fully BMSCS-encapsulated dTFBC scaffolds promoted TBI regeneration, with enhanced cellular integration, fibrocartilage formation, and favorable biomechanical performance. Clinical Relevance: This biomimetic scaffold strategy may enhance biological healing and reduce the risk of retear after rotator cuff repair.

Context: Traditional Chinese medicine (TCM) techniques, grounded in TCM theory, offer flexible and personalized therapeutic strategies. Increasing evidence indicates that gut microbiota dysbiosis is closely associated with the onset and progression of various diseases, highlighting a complex mutual relationship. Investigating the interaction between TCM techniques and gut microbiota may provide both a theoretical and practical foundation for clinical application. However, comprehensive systematic analyses remain limited. Objective: This study aimed to identify core themes and emerging trends in research on the interactions between TCM techniques and gut microbiota. In addition, it sought to explore underlying correlations using data mining approaches to provide insights supporting clinical applications and mechanistic studies. Materials and Methods: A systematic literature review was conducted using the Web of Science Core Collection and China National Knowledge Infrastructure for bibliometric analysis. Co-occurrence analysis was performed using CiteSpace software to identify research characteristics and development trends. Key data were extracted and visualized through an interactive network diagram generated with Cytoscape. Results: Current research predominantly focuses on acupoint application, moxibustion, and TCM enema, all of which exhibit significant effects in promoting beneficial microbiota and suppressing pathogenic strains. The regulatory impact of these TCM techniques on gut microbiota is closely associated with inflammatory response pathways and immunity. Conclusions: TCM techniques are extensively applied in disease management. Among them, moxibustion, acupoint application, TCM enema, and Tuina remain prominent and evolving areas of interest. Further empirical research is warranted to elucidate the biological mechanism underpinning these effects within the guidance of TCM pattern theory.

PURPOSE Detection of molecular residual disease using circulating tumor DNA (ctDNA) may enable postoperative risk stratification and guide adjuvant therapy. We evaluated the prognostic value of a tissue-free, epigenomic ctDNA assay in patients with stage III colon cancer (CC) enrolled in a phase III adjuvant chemotherapy trial. METHODS Plasma samples were collected after surgery and before adjuvant infusional fluorouracil, leucovorin, and oxaliplatin alone or combined with cetuximab. ctDNA was analyzed using a tissue-free assay; in ctDNA-positive patients, tumor fraction (TF) was quantified and genotyping was performed with a 739-gene panel. Associations with disease-free survival (DFS), time to recurrence (TTR), and overall survival (OS) were assessed using multivariable Cox models adjusted for covariates. RESULTS Among 2,260 evaluable patients, 461 (20.4%) were ctDNA-positive with significantly higher detection in advanced T-/N-stage, high-grade, obstruction/perforation, and BRAF V600E tumors. At a median follow-up of 6.1 years, ctDNA positivity was independently associated with shorter TTR (hazard ratio [HR], 5.96 [95% CI, 5.11 to 6.96]), DFS (HR, 5.03 [95% CI, 4.36 to 5.81]), and OS (HR, 4.45 [95% CI, 3.76 to 5.27]; all P < .0001). The 5-year DFS was 27.7% (95% CI, 23.8 to 32.2) v 77.1% (95% CI, 75.1 to 79.1) in ctDNA-positive versus ctDNA-negative patients, and adverse prognostic impact was greater in lower T/N stage, low-risk, and dMMR subsets (interaction P = .0012-.041). Among ctDNA-positive patients, TF was nearly double in those who recurred or died ( P = .0002) and stratified patients for TTR, DFS, and OS (all adjusted P < .002). Genotyping identified mutations in FLT1 (OR, 8.99) and PREX2 (OR, 7.73) genes that were most strongly associated with recurrence ( P < .03). CONCLUSION Evaluation of ctDNA in resected stage III CC using a tissue-free assay provided robust and independent prognostic value. Higher ctDNA burden, dMMR, and specific mutations defined poor prognostic groups among ctDNA-positive patients.

64 Background: The incidence of eoCRC (diagnosed at age <50) is increasing. We have previously shown higher rates of severe anxiety and depression in this group compared to adults diagnosed at age ≥50 (average-onset CRC, aoCRC). We assessed the impact of ePROM collection coupled with a CC-based supportive care intervention on symptom burden in patients with eoCRC. Methods: The Enhanced, EHR-facilitated Cancer Symptom Control (E2C2) trial was a cluster-randomized, pragmatic trial conducted at Mayo Clinic Rochester and within the Mayo Clinic Health System (in Minnesota and Wisconsin) between 2019 and 2023. Enrolled patients serially reported the severity of six SPPADE symptoms (Sleep deficit, Pain, Physical function impairment, Anxiety, Depression, and Energy deficit/fatigue) on 11-point numerical rating scales. Symptom scores were interpreted as none to mild (0-3), moderate (4-6), or severe (7-10). Those with moderate symptoms were offered symptom management education and self-management materials, while those with severe symptoms were offered the option to work with a symptom care manager. In this post hoc analysis we examined the effects of the intervention on change in symptom scores among those with eoCRC, and using the Kaplan-Meier method, the median time to improvement to a mild/moderate level in those with a severe symptom, comparing eoCRC with aoCRC. Results: Among 4,422 patients with CRC, 887 had eoCRC. Forty-six percent of patients were female ( p =0.61), and a greater proportion of eoCRC patients were of a non-white race (11.6% vs 4.7%), lived in an urban setting (65.6% vs 50.5%), had a Bachelor’s degree or higher (36.8% vs 24.4%), were employed (78.5% vs 36.7%), on a non-government insurance plan (83.4% vs 35.3%), single (19.7% vs 11.2%) or married (74.2% vs 67.9%), and had metastatic disease (54.8% vs 46.1%, p <0.0001 for all). Compared to a pre-intervention baseline, the mean change in symptom scores for eoCRC patients following the intervention demonstrated improvements in anxiety (-0.238), depression (-0.134), and fatigue (-0.146, p <0.05 for all). Time to symptom improvement from severe to mild/moderate was longer for anxiety and depression in eoCRC patients compared to aoCRC patients (Table 1). Conclusions: Collection of ePROMs coupled with a CC-based intervention led to improvements in anxiety, depression, and fatigue among eoCRC patients, although time to symptom improvement was longer among eoCRC patients compared to aoCRC patients. Time to improvement of severe symptom (months), median (95% CI). eoCRC aoCRC p -value Sleep 4.2 (3.1-5.8) 3.8 (2.7-5.4) 0.4 Pain 4.1 (3.0-7.5) 3.2 (2.3-5.0) 0.5 Physical function impairment 3.1 (1.9-6.3) 2.8 (2.2-4.2) 0.5 Anxiety 4.3 (3.4-9.1) 2.6 (2.0-3.5) 0.009 Depression 4.3 (2.6-7.5) 2.6 (2.1-3.5) 0.04 Fatigue 4.3 (3.7-9.5) 3.4 (2.7-4.2) 0.06

622 Background: Colorectal small and large cell neuroendocrine carcinoma (SCNEC and LCNEC) comprise <1% of colorectal cancers and have poor prognosis. Detailed survival information is limited due to rarity. We analyzed survival outcomes using Survival, Epidemiology, and End Result (SEER) database (2000-2022) and compared with NETs and adenocarcinoma (AC). Methods: All patients with SCNEC, LCNEC, NETs or AC with colorectal primaries were extracted. AJCC stage was calculated with 8 th ed. TNM classification. Kaplan-Meier estimator, log-rank test, and Cox regression (including AJCC stage, surgery, radiation, and chemotherapy variables) were used to analyze survival outcomes. Results: Comparing colon and rectal primaries, the only significant mOS difference was in stage IV SCNEC (2 vs 7 months, p<0.0001). Comparing LCNEC and SCNEC, the only significant mOS difference was in stage IV colon SCNEC and LCNEC (2 vs 5 months, p<0.0001). Stage III and IV colorectal SCNEC and LCNEC had significantly shorter mOS than stage III and IV AC and NETs. In multivariate Cox regressions, surgery and chemotherapy were associated with significantly improved survival for both SCNEC and LCNEC at both primaries (p<0.001), while radiation was never significant. Conclusions: Most colorectal SCNEC and LCNEC patients present with stage IV disease. Stage IV colon SCNEC had significantly shorter mOS than both stage IV colon LCNEC and stage IV rectal SCNEC. Further research should explore early diagnosis and effective therapies for this rare, aggressive malignancy. Median overall survival (months) Colon SCNEC (n/mOS) Colon LCNEC (n/mOS) Colon NETs (n/mOS) Colon AC (n/mOS) SCNEC vs NETs in colon: P-value LCNEC vs NETs in colon: P-value SCNEC vs AC in colon: P-value LCNEC vs AC in colon: P-value SCNEC vs LCNEC in colon: P-value Rectal SCNEC (n/mOS) Rectal LCNEC (n/mOS) Rectal NETs (n/mOS) Rectal AC (n/mOS) SCNEC vs NETs in rectum: P-value LCNEC vs NETs in rectum: P-value SCNEC vs AC in rectum P-value LCNEC vs AC in rectum SCNEC vs LCNEC in rectum: P-value Colon SCNEC vs rectal SCNEC P-value Colon LCNEC vs rectal LCNEC: P-value Stage I 19/32 17/122 4496/NA 114,213/144 <0.0001 <0.0001 <0.0001 0.34 0.25 27/23 10/28 5185/NA 54,702/160 <0.0001 <0.0001 <0.0001 0.00047 0.88 0.99 0.24 Stage II 17/38 30/49 259/NA 121,757/106 0.0015 <0.0001 0.4 0.0068 0.65 17/16 3/NA 33/NA 38,417/106 <0.0001 0.57 <0.0001 0.87 0.3 0.065 0.55 Stage III 40/14 107/13 582/184 104,793/82 <0.0001 <0.0001 <0.0001 <0.0001 0.48 50/19 37/17 103/102 46,687/107 <0.0001 <0.0001 <0.0001 <0.0001 0.45 0.48 0.47 Stage IV 245/2 217/5 393/49 83,542/13 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 260/7 57/6 158/36 36,652/17 <0.0001 <0.0001 <0.0001 <0.0001 0.25 <0.0001 0.95