Citations

AbstractBackgroundGastroparesis (GP) is characterized by delayed gastric emptying in the absence of mechanical obstruction.ObjectiveGenetic predisposition may play a role; however, investigation at the genome‐wide level has not been performed.MethodsWe carried out a genome‐wide association study (GWAS) meta‐analysis on (i) 478 GP patients from the National Institute of Diabetes and Digestive and Kidney Diseases Gastroparesis Clinical Research Consortium (GpCRC) compared to 9931 population‐based controls from the University of Michigan Health and Retirement Study; and (ii) 402 GP cases compared to 48,340 non‐gastroparesis controls from the Michigan Genomics Initiative. Associations for 5,811,784 high‐quality SNPs were tested on a total of 880 GP patients and 58,271 controls, using logistic mixed models adjusted for age, sex, and principal components. Gene mapping was obtained based on genomic position and expression quantitative trait loci, and a gene‐set network enrichment analysis was performed. Genetic associations with clinical data were tested in GpCRC patients. Protein expression of selected candidate genes was determined in full thickness gastric biopsies from GpCRC patients and controls.ResultsWhile no SNP associations were detected at strict significance (p ≤ 5 × 10−8), nine independent genomic loci were associated at suggestive significance (p ≤ 1 × 10−5), with the strongest signal (rs9273363, odds ratio = 1.4, p = 1 × 10−7) mapped to the human leukocyte antigen region. Computational annotation of suggestive risk loci identified 14 protein‐coding candidate genes. Gene‐set network enrichment analysis revealed pathways potentially involved in immune and motor dysregulation (pFDR ≤ 0.05). The GP risk allele rs6984536A (Peroxidasin‐Like; PXDNL) was associated with increased abdominal pain severity scores (Beta = 0.13, p = 0.03). Gastric muscularis expression of PXDNL also positively correlated with abdominal pain in GP patients (r = 0.8, p = 0.02). Dickkopf WNT Signaling Pathway Inhibitor 1 showed decreased expression in diabetic GP patients (p = 0.005 vs. controls).ConclusionWe report preliminary GWAS findings for GP, which highlight candidate genes and pathways related to immune and sensory‐motor dysregulation. Larger studies are needed to validate and expand these findings in independent datasets.

Abstract BACKGROUND Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features with Visually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. Gliomas with CDKN2A mutations are known to have worse prognosis but imaging features of these gliomas are unknown. Our goal is to identify CDKN2A specific qualitative imaging biomarkers in glioblastomas using a new informatics workflow that enables rapid analysis of qualitative imaging features withVisually AcceSAble Rembrandtr Images (VASARI) for large datasets in PACS. MATERIAL AND METHODS Sixty nine patients undergoing GBM resection with CDKN2A status determined by whole-exome sequencing were included. GBMs on magnetic resonance images were automatically 3D segmented using deep learning algorithmsincorporated within PACS. VASARI features were assessed using FHIR forms integrated within PACS. RESULTS GBMs without CDKN2A alterations were significantly larger (64% vs. 30%, p=0.007) compared to tumors with homozygous deletion (HOMDEL) and heterozygous loss (HETLOSS). Lesions larger than 8 cm were four times more likely to have no CDKN2A alteration (OR: 4.3; 95% CI:1.5-12.1; p<0.001). The pial invasion was predictive of HOMDEL (OR: 8.1, 95% CI: 1.8-53.2; p<0.012) as tumors with pial invasion were eight times more likely to be HOMDEL, even after adjusting for deep white matter and subependymal invasion. CONCLUSION We developed a novel integrated PACS informatics platform for the assessment of GBM molecular subtypes and show that tumors with HOMDEL are more likely to have radiographic evidence of pial invasion and less likely to have deep white matter invasion or subependymal invasion. These imaging features may allow noninvasive identification of CDKN2A allele status.

Abstract Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector‐based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well‐described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

AbstractThe clinical significance of the tumor‐immune interaction in breast cancer is now established, and tumor‐infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple‐negative (estrogen receptor, progesterone receptor, and HER2‐negative) breast cancer and HER2‐positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state‐of‐the‐art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false‐positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in‐depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple‐negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Physician categorizations of electronic health record (EHR) data (e.g., depression) into sensitive data categories (e.g., Mental Health) and their perspectives on the adequacy of the categories to classify medical record data were assessed. One thousand data items from patient EHR were classified by 20 physicians (10 psychiatrists paired with ten non-psychiatrist physicians) into data categories via a survey. Cluster-adjusted chi square tests and mixed models were used for analysis. 10 items were selected per each physician pair (100 items in total) for discussion during 20 follow-up interviews. Interviews were thematically analyzed. Survey item categorization yielded 500 (50.0%) agreements, 175 (17.5%) disagreements, 325 (32.5%) partial agreements. Categorization disagreements were associated with physician specialty and implied patient history. Non-psychiatrists selected significantly ( p = .016) more data categories than psychiatrists when classifying data items. The endorsement of Mental Health and Substance Use categories were significantly ( p = .001) related for both provider types. During thematic analysis, Encounter Diagnosis (100%), Problems (95%), Health Concerns (90%), and Medications (85%) were discussed the most when deciding the sensitivity of medical information. Most (90.0%) interview participants suggested adding additional data categories. Study findings may guide the evolution of digital patient-controlled granular data sharing technology and processes.

Background:The coronavirus disease 2019 (COVID-19) pandemic provoked rapid changes in clinical practice to accommodate mandated restrictions within healthcare delivery. This study reviewed patient-reported experiences and clinical outcomes after implementation of a same-day discharge protocol after mastectomy with immediate alloplastic breast reconstruction compared with our historical overnight stay protocol.Methods:This is a retrospective single-institution study of consecutive patients who underwent mastectomy and immediate alloplastic reconstruction between July 2019 and November 2020. A postoperative survey was completed by patients to evaluate satisfaction with perioperative communications, recovery, and their overall experience.Results:A total of 302 patients (100% women) underwent mastectomy and immediate alloplastic reconstruction (174 pre-COVID-19, 128 during COVID-19). During COVID-19, 71% of patients were scheduled for a same-day discharge, among which 89% were successfully discharged the same day. Compared with pre-COVID-19, there were no differences in type of surgery, operative times, pain scores, 30-day readmission, or unplanned visits (allP> 0.05) during the COVID-19 pandemic. Compared with pre-COVID-19, patients during the pandemic reported comparable satisfaction with their care experience and postoperative recovery (56% survey response rate). Patient satisfaction was also similar between those discharged the same day (n = 81) versus the next day (n = 47) during COVID-19.Conclusions:Same-day discharge is feasible, safe, and can provide similar patient-reported satisfaction and outcomes compared with traditional overnight stay. These data highlight the ability to deliver adaptable, high-quality breast cancer care, within the constraints of a global pandemic.

In 2023, the NCCN Guidelines for Hepatobiliary Cancers were divided into 2 separate guidelines: Hepatocellular Carcinoma and Biliary Tract Cancers. The NCCN Guidelines for Biliary Tract Cancers provide recommendations for the evaluation and comprehensive care of patients with gallbladder cancer, intrahepatic cholangiocarcinoma, and extrahepatic cholangiocarcinoma. The multidisciplinary panel of experts meets at least on an annual basis to review requests from internal and external entities as well as to evaluate new data on current and emerging therapies. These Guidelines Insights focus on some of the recent updates to the NCCN Guidelines for Biliary Tract Cancers as well as the newly published section on principles of molecular testing.