Citations

Abstract This literature‐based systematic review and associated guidelines provide evidence‐based paradigms for the management of locoregionally recurrent rectal cancer (LRRC). This multispecialty committee included gastrointestinal radiation and medical oncology, gastroenterology, radiology, and colorectal surgery. As is the standard, the previously described American Radium Society Appropriate Use Criteria methodology for this project was followed rigorously, with the Population, Intervention, Comparator, Outcome, Timing, and Study Design framework and Preferred Reporting Items for Systematic Reviews and Meta‐Analyses methodology to assess the evidence. RAND/University of California Los Angeles consensus methodology (modified Delphi) was used to rate the appropriateness of treatment options. Published between January 1, 2013, and July 16, 2025, 116 peer‐reviewed trials provided the evidence: 10 were well‐designed randomized phase 2/3 trials, 29 were moderately well designed trials that accounted for most common biases (matched cohort and phase 2), 76 trials had design limitations (retrospective), and one was a meta‐analysis. Clinical cases were created as examples to illustrate current acceptable management of LRRC. Treatment and prognosis are influenced by prior therapy and the site(s) and extent of LRRC. The ability to achieve a margin‐negative surgical resection is the ultimate determinant of survival and local control. Preoperative systemic therapy, radiation therapy, or a combination of the two can facilitate tumor downsizing and improve the likelihood of a margin‐negative resection. An individualized multidisciplinary approach is required to ensure the best outcome. Although this review does not suggest a major alteration of current practice, it provides reassuring evidence of the importance of combined‐modality therapy.

Purpose of review A substantial proportion of esophageal adenocarcinoma (EAC) and high-grade dysplasia (HGD) cases in Barrett's esophagus (BE) are diagnosed after a dysplasia-negative endoscopy before the next recommended surveillance interval. These are classified as postendoscopy esophageal carcinoma (PEEC) or postendoscopy esophageal neoplasia (PEEN) and represent critical failures of BE surveillance. This review summarizes current definitions, epidemiology, potential etiologies, and evolving strategies to reduce PEEC/PEEN and improve the quality of BE surveillance. Recent findings High-quality endoscopic examination using high-definition white-light endoscopy (HD-WLE) and virtual chromoendoscopy (CE), adherence to the Seattle biopsy protocol, adequate inspection time, and training in the recognition of visible lesions harboring prevalent dysplasia/EAC, are critical in reducing PEEC/PEEN. Initial data on the use of adjunctive tools (wide-area transepithelial sampling) and molecular biomarkers (p53, DNA methylation panels, and Tissue Systems Pathology tests) demonstrate promising results for detecting prevalent dysplasia and for reducing PEEC and PEEN. BE surveillance quality metrics, such as cancer and neoplasia detection rates, have been shown to be inversely associated with PEEN. Summary PEEC and PEEN reflect critical gaps in the effectiveness of BE surveillance. Improving the quality of endoscopic surveillance is essential, including meticulous mucosal inspection, appropriate use of advanced imaging techniques, and adherence to systematic biopsy protocols, to minimize missed neoplasia.

Background: There is growing support for high-efficacy disease-modifying therapy (DMT) in multiple sclerosis (MS), but escalation (ESC) approaches remain common. Objective: To describe decision-making in a pragmatic trial of early high-efficacy treatment (EHT) versus ESC. Methods: DELIVER-MS is a multi-center, pragmatic, randomized controlled trial (RCT) with a parallel observational study (OBS), which enrolled treatment-naïve people with RRMS in 31 UK/US sites. Primary outcome was as follows: 36-month brain volume loss according to initial treatment approach (EHT vs. ESC). Stepwise multivariable logistic regression was used to predict participation in RCT versus OBS and choice of EHT versus ESC within the OBS cohort. Results: In total, 816 people with MS were enrolled. Participants declined randomization due to preference for a particular DMT (85%), efficacy concerns (20%), and safety concerns (9%). RCT versus OBS participation was associated with lower relapse rate ( p = 0.043) and greater brain parenchymal fraction ( p = 0.002). Among 374 in the OBS cohort, 125 (33%) chose ESC and 249 (67%) chose EHT. People commencing EHT had higher education attainment ( p < 0.001) and relapse rate ( p = 0.025). Conclusion: Baseline DELIVER-MS data demonstrate that participants with milder disease are more likely to participate in RCT. The choice of EHT versus ESC was associated with demographic factors and disease activity. Clinical trial registration: NCT03535298

Abstract Background: Immune checkpoint inhibitors (ICIs) have improved survival in non-small-cell lung cancer (NSCLC), yet only a subset of patients benefits, and biomarkers like PD-L1 remain limited. Here, we introduce a deep learning-based pathomics framework that utilizes routine H&E-stained slides to predict therapeutic response and survival outcomes in ICI-treated metastatic NSCLC. Methods: The study included 797 ICI-treated NSCLC patients from MD Anderson, with external validation in 280 patients from Mayo Clinic, Gustave Roussy, and the Phase III ICI-naïve LUSC Lung-MAP S1400I trial receiving nivolumab with or without ipilimumab. Path-IO (Pathology-Driven Immunotherapy Optimization) comprised of four major steps: (1) pathologist-verified tissue classifier segmented WSIs into eight compartments—Background, Bronchi, Immune, Lung, Necrosis, Stroma, Tumor, and Vessel—and was validated on TCGA and CPTAC dataset; (2) a survival prediction module generating patient-level risk scores in the MD Anderson cohort and validated across external datasets; (3) integration of Path-IO risk scores with radiomics and clinical features to improve prognostic accuracy; and (4) biological interpretability analyses correlating Path-IO risk immune contexture from multiplex immunofluorescence and transcriptomic signatures from NanoString profiling. Results: Path-IO effectively stratified patients into high and low-risk groups with significant survival differences. In the MD Anderson cohort, it achieved HR = 2.11 (p &lt; 0.001) and HR = 2.51 (p &lt; 0.001) for OS in the discovery and validation sets, and HR = 2.34 (p &lt; 0.001) and HR = 1.87 (p &lt; 0.001) for PFS, respectively. In the multicenter Phase III Lung-MAP S1400I trial, Path-IO achieved HR = 1.78 (p = 0.016) for OS and HR = 2.76 (p = 0.006) for PFS. In external validation, it predicted outcomes in the Gustave Roussy (OS = 1.97, p = 0.003; PFS = 1.51, p = 0.046) and Mayo Clinic (OS = 2.46, p = 0.007; PFS = 2.45, p = 0.027) cohorts. Path-IO outperformed PD-L1 and remained an independent predictor in multivariate analysis (p &lt; 0.001). It enabled data-driven frontline selection between anti-PD-1 monotherapy and chemo-immunotherapy, offering guidance toward more personalized treatment decisions. Integration with radiomics and clinical features further improved predictive accuracy (OS 0.63→0.75; PFS C-index 0.58→0.70), while high Path-IO risk scores correlated with immune-cold phenotypes identified by multiplex immunofluorescence and NanoString transcriptomics. Conclusions: Path-IO demonstrates that deep learning models rooted in histopathologic architecture can generate interpretable and biologically informed survival predictions in NSCLC treated with ICIs. By integrating pathology, radiology, and clinical data, Path-IO provides complementary predictive value beyond established biomarkers such as PD-L1. Citation Format: Rukhmini Bandyopadhyay, Linghzi Hong, Mihaela Aldea, Shenduo Li, Lodovica Zullo, Frank R. Rojas, Maliazurina B. Saad, Maricel C. Marin, Muhammad Waqas, Jiexin Zhang, Eman Showkatian, Claudio A. Arrechedera, Xiaoyu Han, Yuliya Kitsel, Sherif Ismail, Muhammad Aminu, Bo Zhu, Carol C. Wu, Brett W. Carter, Joe Y Chang, Zhongxing Liao, Maria R. Ghigna, Davide Soldato, Hai T. Tran, Xiuning Le, Tina Cascone, Bingnan Zhang, Haniel A. Araujo, Mehmet Altan, Simon Heeke, David Jaffray, Don L. Gibbons, Ara Vaporciyan, J Jack Lee, Neda Kalhor, Cara Haymaker, Ignacio Wistuba, John V. Heymach, Yanyan Lou, Natalie Vokes, Luisa M. Solis Soto, Jianjun Zhang, Jia Wu. Path-IO: A deep learning pathomics framework for personalized immunotherapy selection and outcome prediction in metastatic non-small cell lung cancer [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 4003.

Abstract Background Postoperative spinal implant infections (PSIIs) are a serious complication of instrumented spinal fusion. Although debridement with implant retention is standard for early infection, the optimal duration of antimicrobial therapy remains uncertain. Methods We conducted a multicenter retrospective cohort study across 10 US academic centers, including adults with early PSII (≤90 days after fusion surgery) from 2017 to 2021. We excluded patients who experienced treatment failure within 6 weeks of debridement. The primary outcome was treatment failure. Antibiotic therapy effect was analyzed as a time-varying exposure using adjusted Cox proportional hazards models. Secondary analyses included 12-week landmark and clone-censor-weighted models to compare durations ≤ 12 weeks versus &gt;12 weeks. Results A total of 116 patients out of 499 (23.2%) experienced treatment failure during a median follow-up of 3.2 years. Among patients who remain failure-free 6 weeks from debridement, being on antibiotics was not associated with treatment failure (adjusted hazard ratio [aHR] 0.71; 95% CI .48–1.07; P = .10). In a 12-week landmark analysis limited to 359 patients who were not on indefinite suppressive antibiotic therapy, treatment durations &gt; 12 weeks did not significantly reduce the risk of failure (aHR 1.01; 95% CI .62–1.64; P = .99). Results were consistent in the clone-censor-weight sensitivity analysis (aHR 0.85; 95% CI .62–1.16; P = .30). Conclusions Prolonged antibiotic therapy was not associated with improved outcomes in early PSII managed with debridement and implant retention. These results support shorter, individualized antibiotic courses in patients with adequate surgical source control.

Despite advances in imaging, instrumentation, surgical techniques, and postoperative care, outcomes for certain peripheral nerve procedures remain consistently disappointing. In this article, we describe five surgical scenarios--adult pan-brachial plexus injuries, peroneal nerve injury after knee dislocation, sciatic nerve injury after total hip arthroplasty, radiation-induced brachial plexopathy, and lower trunk injury after cardiac surgery--that, in our experience and review of the literature, frequently lead to limited and consistently poor functional recovery after nerve surgery. These challenging cases reflect not only technical and anatomical complexity but the profound biological limitations of nerve regeneration in specific contexts. By critically analyzing these five procedures, we aim to promote more realistic patient counseling, support timely and individualized decision-making, and foster a more nuanced understanding of when and what type of surgical intervention may or may not be beneficial.