Bhutani, Manoop S.

Abstract: Background Artificial intelligence (AI)-assisted colonoscopy reduces costs in colorectal cancer screening, but its incremental value relative to non-AI resect-and-discard (RD) strategies for diminutive polyps (≤ 5 mm) remain unclear. We aimed to compare the clinical, economic, and environmental outcomes of AI-assisted and non-AI RD strategies with standard of care (SoC). Methods In our Markov model simulating 6 million individuals aged ≥45 years undergoing screening colonoscopy, 4 strategies were evaluated: SoC, non-AI RD, CADe-assisted RD (CADe-RD), and CADe+CADx-assisted RD (CADe+CADx-RD). The primary outcome was total quality-adjusted life years (QALYs), with secondary outcomes including cost and carbon dioxide (CO₂) emissions. Results Non-AI RD achieved the lowest total cost ($36.6B) and carbon emissions (0.90 million kg CO₂), while yielding the highest QALYs (51.37 million), although differences in QALYs across strategies were small (<0.01%). CADe-RD and CADe+CADx-RD remained cost-saving relative to SoC ($36.9B and $37.4B vs $37.8B, respectively) but were associated with higher costs than non-AI RD. CADe modestly increased adenoma detection without improving QALYs, while the addition of CADx increased costs and emissions and resulted in slightly lower QALYs. Sensitivity analysis showed that CADe+CADx-RD matched or exceeded CADe-RD QALYs only within a limited region of high diagnostic performance. At currently reported CADx performance levels, CADe+CADx-RD yielded lower QALYs and higher costs than CADe-RD. CADe+CADx-RD achieved non-inferiority in QALYs relative to CADe-RD only within a limited region of high diagnostic performance. Conclusions In our non-deterministic model, non-AI RD provided the optimal balance of clinical benefit, cost savings, and lowest environmental impact.

Background: Pancreatitis significantly alters the microbial composition of the oral and intestinal compartments, causing dysbiosis that may contribute to disease mechanisms and potentially serve as a basis for diagnosis or treatment. Objective: To determine whether the oral or gut microbial signature can classify chronic pancreatitis (CP). Methods: Stool samples (n=707) were collected from participants in the Prospective Evaluation of Chronic Pancreatitis for Epidemiologic and Translational Studies (PROCEED). Samples were distributed among 200 healthy (HC), 310 CP, 49 acute pancreatitis (AP), and 148 recurrent acute pancreatitis (RAP). In addition, saliva samples were collected for a subset of participants (n=156). Whole genome sequencing was performed to assess microbiome composition. Machine learning algorithms were utilized to identify a signature with microbial features predictive of CP. Results: Gut alpha diversity was significantly decreased in AP, RAP, and CP compared with HC, with CP exhibiting the lowest diversity. In contrast, oral microbial diversity showed no significant variation across groups. Beta diversity analysis revealed distinct gut microbiome compositions between HC and pancreatitis subtypes, with CP showing the most pronounced differences. Random forest models using gut microbial species demonstrated robust predictive performance for CP using a minimum of 10 species (Area under the curve—AUC: 0.834; accuracy: 0.774). Despite similarities in gut microbiome composition across pancreatitis subtypes, a unique gut microbial signature for CP was identified highlighting the microbiome’s potential in CP diagnosis. Conclusion: Our study reveals a gut microbial signature predictive of CP using machine learning models in a large US multi-institutional cohort.

Importance Neoadjuvant therapy (NT) is an increasingly used treatment strategy for patients with localized pancreatic ductal adenocarcinoma (PDAC). Little research has been conducted on cancer care delivery during NT, and the standards for optimal delivery of NT have not been defined. Objective To develop consensus best practices for delivering NT to patients with localized PDAC. Design, Setting, and Participants This study used a modified Delphi approach consisting of 2 rounds of voting, and a series of virtual conferences (from October to December 2023) to reach expert consensus on candidate best practice statements generated from a systematic review of the literature and expert opinion. An interdisciplinary panel was formed including 47 North American experts from surgical, medical, and radiation oncology, radiology, pathology, gastroenterology, integrative oncology, anesthesia, pharmacy, nursing, cancer care delivery research, and nutrition as well as patient and caregiver stakeholders. Main Outcome and Measures Statements that reached 75% agreement or greater were included in final consensus statements. Results Of the 47 participating panel members, 27 (57.64%) were male, and the mean (SD) age was 47.6 (8.2) years. Physicians reported completing training a mean (SD) 14.6 (8.6) years prior and seeing a mean (SD) 110.6 (38.4) patients with PDAC annually; 35 (77.7%) were in academic practice. Final consensus was reached on 82 best practices for delivering NT. Of these, 38 statements focused on pre-NT practices, including diagnosis and staging (n = 15), evaluation and optimization (n = 20), and decision-making (n = 3); 29 statements defined best practices during NT, including initiation (n = 3), delivery of therapy (n = 8), restaging practices (n = 12), and management of complications during NT (n = 6); and 15 best practices were identified to guide treatment post-NT, focusing on surgery (n = 7), pathology (n = 4), and follow-up (n = 3). Conclusions Using a modified Delphi consensus technique, best practice guidelines were developed focusing on the optimal standards for delivering NT to patients with localized PDAC. Given the prognostic importance of completing multimodality therapy, efforts to standardize and optimize the delivery of NT represent an immediate opportunity to decrease care variation and improve outcomes for patients with PDAC. Future research should focus on validating and implementing best practice standards into clinical practice.

Objective: To discern recurrence risk stratification and investigate its influence on postoperative surveillance in patients with esophageal adenocarcinoma (EAC) after neoadjuvant chemoradiotherapy (CRT). Background: Reports documenting recurrence risk stratification in EAC after neoadjuvant CRT are scarce. Methods: Between 1998 and 2014, 601 patients with EAC who underwent neoadjuvant CRT followed by esophagectomy were included for analysis. The pattern, site, timing, and frequency of the first recurrence and potential prognostic factors for developing recurrences were analyzed. This cohort was used as the training set to propose a recurrence risk stratification system, and the stratification was further validated in another cohort of 172 patients. Results: A total of 150 patients (25.0%) achieved pathologic complete response (pCR) after neoadjuvant CRT and the rest were defined as the non-pCR group (n = 451) in the training cohort. After a median follow-up of 63.6 months, the pCR group demonstrated a significantly lower locoregional (4.7% vs 19.1%) and distant recurrence rate (22.0% vs.44.6%) than the non-pCR group (P < 0.001). Based on independent prognostic factors, patients were stratified into 4 recurrence risk categories: pCR with clinical stage I/II, pCR with clinical stage III, non-pCR with pN0, and non-pCR with pN+, with corresponding 5-year recurrence-free survival rates of 88.7%, 65.8%, 55.3%, and 33.0%, respectively (P < 0.001). The risk stratification was reproducible in the validation cohort. Conclusions: We proposed a recurrence risk stratification system for EAC patients based on pathologic response and pretreatment clinical stage. Risk-based postoperative surveillance strategies could be developed for different risk categories.

Abstract Esophageal adenocarcinoma (EAC) is thought to arise from the metaplastic condition known as Barrett's esophagus (BE), which is caused by chronic inflammation due to gastroesophageal reflux disease. Since the molecular mechanisms underlying the pathogenesis of EAC are unknown, understanding EAC development mechanisms and their regulation is crucial for the treatment of EAC. Comparative genomic studies of evolutionarily similar and dissimilar species have been suggested as a means of studying the evolutionary biology in the species. Thus, we performed a cross-species comparison of gene expression patterns in human and rat tissues, uncovering the evolutionarily conserved gene expression patterns during EAC progression across both species. Using a non-carcinogenic rat model that progresses from normal esophagus to BE to EAC, we were able to identify the biological mechanisms of EAC development. We analyzed gene expression data from rat specimens (15 NE, 18 BE, and 30 EAC) as well as from human tissues (28NE, 72BE, and 75EAC). Using the presence of orthologous genes in both microarray platforms and various statistical tests, we uncovered a number of genes whose expression patterns were well conserved during progression from NE to BE in humans and rats. The expression of 869 genes was commonly altered when NE progressed to BE in both humans and rats (P&lt;0.005). One of the most significantly conserved signaling pathways during the progression from NE to BE was IL-6-mediated E2F transcription factor1 (E2F1). The increased E2F1 induced activation of CCNA2, CCNB2, CCND1, CCNE 1 and 2, CDC 2 and 6, CASP3, CASP6, CASP8, CASP9, and Rad 51, which are important genes for the regulation of cell cycle, apoptosis, and DNA repair. These up-regulated genes may consequently cause abnormal cell cycle regulation and induce dysplasia and metaplasia of normal esophagus tissue during NE to BE progression. During BE to EAC progression in both species, 541 gene expressions were altered (P&lt;0.005). An increased TGF-β/RAS/SPI1 signaling pathway significantly increased the expression of SPARC and SPP1 during progression from BE to EAC. Increased SPP1 and SPARC activated MMP9, CCL2, CCL4, COL1A1, COL3A1, and SNAL1, which mostly function in invasion, cell adhesion, and migration. Intriguingly, SPP1 and SPARC already had been discovered in our previous study (Kim et al.,) as markers of poor prognosis for EAC patients, strongly indicating that SPP1 and SPARC are also genetic determinants for progression to EAC. In conclusion, systems-level characterization of gene expression data from humans and a rodent model shows evolutionarily conserved genes and pathways during EAC progression, and these genes and pathways could become reliable biomarkers for early detection, or therapeutic targets for the treatment of EAC patients. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2005.

Abstract To better understand the molecular mechanisms behind esophageal adenocarcinoma (EAC) tumorigenesis, we used high-density single nucleotide polymorphism arrays to profile chromosomal aberrations at each of the four sequential progression stages, Barrett's metaplasia (BM), low-grade dysplasia (LGD), high-grade dysplasia (HGD), and EAC, in 101 patients. We observed a significant trend toward increasing loss of chromosomes with higher progression stage. For BM, LGD, HGD, and EAC, respectively, the average numbers of chromosome arms with loss per sample were 0.30, 3.21, 7.70, and 11.90 (P for trend = 4.82 × 10−7), and the mean percentages of single nucleotide polymorphisms with allele loss were 0.1%, 1.8%, 6.6%, and 17.2% (P for trend = 2.64 × 10−6). In LGD, loss of 3p14.2 (68.4%) and 16q23.1 (47.4%) was limited to narrow regions within the FHIT (3p14.2) and WWOX (16q23.1) genes, whereas loss of 9p21 (68.4%) occurred in larger regions. A significant increase in the loss of other chromosomal regions was seen in HGD and EAC. Loss of 17p (47.6%) was one of the most frequent events in EAC. Many recurrent small regions of chromosomal loss disrupted single genes, including FHIT, WWOX, RUNX1, KIF26B, MGC48628, PDE4D, C20orf133, GMDS, DMD, and PARK2, most of which are common fragile site regions in the human genome. However, RUNX1 at 21q22 seemed to be a potential tumor suppressor gene in EAC. Amplifications were less frequent than losses and mostly occurred in EAC. 8q24 (containing Myc) and 8p23.1 (containing CTSB) were the two most frequently amplified regions. In addition, a significant trend toward increasing amplification was associated with higher progression stage. Cancer Prev Res; 3(9); 1176–86. ©2010 AACR.