Patient-specific Outcomes Research Articles

What matters most to healthy older adults in treatment decision making: a discrete choice experiment

Abstract Introduction Shifting to a patient centered approach is crucial for a sustainable healthcare system. Understanding individuals’ priorities is essential for personalized care, especially in critical illness. Treatment decisions are often aimed at disease-specific outcomes such as life extension or survival, while patient-specific outcomes like maintaining independence may be equally vital. How healthy older adults prioritize treatment outcomes in case of a critical illness is currently unknown. Enhanced insight into their priorities can refine healthcare policy, for more personalized care. This study investigated outcomes (attributes) prioritized in hypothetical decision-making by healthy adults over 50 yr. Methods We conducted a Discrete Choice Experiment with individuals aged ≥50, comparing six pairs of hypothetical treatments with five attributes: life expectancy, independence, pain, memory complaints and societal costs. Attribute utility was analyzed using a conditional logit model, and latent class analyses were employed to explore preferences in groups. Results In 333 participants (mean age 70 +/- 7.7) all attributes emerged as impactful with independence being strongest (p < 0.05). Increased life expectancy had positive utility, but only for a two-year increase. Negative utility was found for all other attributes except mild pain and memory complaints. Latent class analyses identified two groups (22.4% and 77.6%). Group one valued life expectancy more (p .019 vs .940), whereas the second group valued independence (p .058 vs.<.001 and societal costs (p.053 vs. <.001) more. Conclusions In a hypothetical case of life-threatening disease, for people aged ≥ 50 life expectancy was not the sole relevant outcome for treatment decisions; pain, independence and societal costs are important and should be discussed in clinical decision making or healthcare policy. Key messages • Older adults find patient-specific outcomes relevant for decision making. • Societal costs are found relevant for decision making for treatment by older adults.

6844 Comparison of Lactated Ringers and Normal Saline in the Treatment of Diabetic Ketoacidosis

Abstract Disclosure: J.N. Johnson: None. A.T. Drincic: None. K. Nein: None. E. Buddenhagen: None. K. Samson: None. T. Langenhan: None. Background: Current guidelines recommend normal saline (NS) for fluid resuscitation in the management of patients presenting with diabetic ketoacidosis (DKA). However, previous prospective studies have demonstrated improvement in patient specific outcomes, including time to DKA resolution, when balanced crystalloid fluids are used. We hypothesized that the use of LR compared to NS for volume management in DKA will shorten time to DKA resolution, reduce time to DKA associated protocol insulin infusion discontinuation, and result in lower post-intravenous fluid resuscitation chloride values. Methods: We conducted a single institution, retrospective cohort study of patients admitted with the diagnosis of DKA following our institution’s transition from NS to lactated ringers (LR) as the default resuscitative and maintenance fluid in our DKA management protocol. Adult patients admitted with DKA before and after the protocol change were identified. The primary outcome was time from DKA clinical presentation until DKA resolution. The secondary outcome was time to discontinuation of DKA protocol continuous insulin infusion. Results: Of 246 patients meeting inclusion criteria, 119 were stratified to the NS group (pre-protocol change) and 127 to the LR group (post-protocol change). T-test analysis revealed decreased time to DKA resolution in the LR group (mean 17.1 hours; SD 11.02) relative to the NS group (mean 20.6 hours; SD 12.22; p = .02). Duration of DKA protocol continuous intravenous insulin was shorter in the LR group (mean 16.0 hours; SD 8.72) compared to the NS group (mean 21.4 hours; SD 12.50; p = 0.0001). Conclusions: In this retrospective cohort study, protocolized DKA intravenous fluid management with LR resulted in shorter time to resolution of DKA and reduced duration of DKA protocol continuous insulin infusion. Presentation: 6/2/2024

Developing an Individualized Patient Decision Aid for Chronic Coronary Disease Based on the ISCHEMIA Trial: A Mixed-Methods Study

BACKGROUND: Pursuing initial invasive or conservative management of chronic coronary disease (CCD) is a preference-sensitive decision that should include shared decision-making. Communicating the benefits of either approach is challenging, as individual patients rarely achieve the population-averaged outcomes reported in clinical trials. Our objective was to develop a patient decision aid (PDA) with patient-specific estimates of outcomes for initial invasive versus conservative management of CCD, based on the ISCHEMIA trial (International Study of Comparative Health Effectiveness With Medical and Invasive Approaches). METHODS: This was a multiphase mixed-methods study using focus groups of outpatients with CCD, caregivers, clinicians, and researchers. Focus groups were held in Kansas City, MO and New York City, NY between September 2021 and June 2022. Patients with CCD were included if they had a positive stress test within 1 year. Phase 1 focused on patient priorities for outcomes to guide treatment decisions. Phase 2 involved PDA development and refinement. Phase 3 involved further refinement and member checking. Key themes involving shared decision-making and treatment preferences were elicited from focus groups using a deductive approach to develop a PDA representing the outcomes most important to patients. RESULTS: Of 46 patient and caregiver participants, the mean age was 63.5 years, 53% were female, 61% were White, 24% were Black, and 9% were Hispanic. When deciding between treatments, participants valued shared decision-making but generally deferred decisions to clinicians. The outcomes most important to participants were survival and quality of life, followed by physical functioning and symptoms. To represent these outcomes, participants favored simple visualizations, such as a speedometer or health meter. When deciding between treatment options, participants preferred to use the PDA collaboratively with a clinician instead of as a stand-alone tool. CONCLUSIONS: Our novel, patient-centered approach to developing a PDA for CCD with patient-specific outcomes has the potential to rapidly translate clinical trial results to individual patients and support shared decision-making.

Computational haemodynamics for pulmonary valve replacement by means of a reduced fluid-structure interaction model.

Pulmonary valve replacement (PVR) consists of substituting a patient's original valve with a prosthetic one, primarily addressing pulmonary valve insufficiency, which is crucially relevant in Tetralogy of Fallot repairment. While extensive clinical and computational literature on aortic and mitral valve replacements is available, PVR's post-procedural haemodynamics in the pulmonary artery and the impact of prosthetic valve dynamics remain significantly understudied. Addressing this gap, we introduce a reduced Fluid-Structure Interaction (rFSI) model, applied for the first time to the pulmonary valve. This model couples a three-dimensional computational representation of pulmonary artery haemodynamics with a one-degree-of-freedom model to account for valve structural mechanics. Through this approach, we analyse patient-specific haemodynamics pre and post PVR. Patient-specific geometries, reconstructed from CT scans, are virtually equipped with a template valve geometry. Boundary conditions for the model are established using a lumped-parameter model, fine-tuned based on clinical patient data. Our model accurately reproduces patient-specific haemodynamic changes across different scenarios: pre-PVR, six months post-PVR, and a follow-up condition after a decade. It effectively demonstrates the impact of valve implantation on sustaining the diastolic pressure gradient across the valve. The numerical results indicate that our valve model is able to reproduce overall physiological and/or pathological conditions, as preliminary assessed on two different patients. This promising approach provides insights into post-PVR haemodynamics and prosthetic valve effects, shedding light on potential implications for patient-specific outcomes.

Chronic Venous Insufficiency Evaluation and Medical Management.

This review will focus on comprehensive evaluation of chronic venous insufficiency (CVI), nuances in diagnostic testing and advances in medical therapies to provide improvement in patient specific outcomes. Chronic venous insufficiency of the lower extremities represents an often underrecognized source of morbidity. Comprehensive evaluation focuses on personal and family history of deep vein thrombosis and varicose veins. Diagnostic testing is initially with a thorough duplex ultrasound, but advanced imaging with CT scan and MRV may be indicated in selected patients who might benefit from more invasive intervention. Compression therapy, wraps and garments, remains the mainstay of conservative therapy for patients with CVI. In addition, there is renewed interest in lifestyle and nutritional supplements, most commonly micronized purified flavanoid fraction (MPFF), in relieving symptoms and preventing morbidity. A holistic approach to patients with CVI provides the best opportunity for enduring improvement in quality of life.

Analysis of hepatic lentiviral vector transduction; implications for preclinical studies and clinical gene therapy protocols.

Lentiviral vector-transduced T-cells were approved by the FDA as gene therapy anti-cancer medications. Little is known about the host genetic variation effects on the safety and efficacy of the lentiviral vector gene delivery system. To narrow this knowledge-gap, we characterized hepatic gene delivery by lentiviral vectors across the Collaborative Cross (CC) mouse genetic reference population. For 24 weeks, we periodically measured hepatic luciferase expression from lentiviral vectors in 41 CC mouse strains. Hepatic and splenic vector copy numbers were determined. We report that CC mouse strains showed highly diverse outcomes following lentiviral gene delivery. For the first time, moderate correlation between mouse strain-specific sleeping patterns and transduction efficiency was observed. We associated two quantitative trait loci (QTLs) with intra-strain variations in transduction phenotypes, which mechanistically relates to the phenomenon of metastable epialleles. An additional QTL was associated with the kinetics of hepatic transgene expression. Genes comprised in the above QTLs are potential targets to personalize gene therapy protocols. Importantly, we identified two mouse strains that open new directions in characterizing continuous viral vector silencing and HIV latency. Our findings suggest that wide-range patient-specific outcomes of viral vector-based gene therapy should be expected. Thus, novel escalating dose-based clinical protocols should be considered.

Metabolic and Oxidative Stress Management Heterogeneity in a Panel of Breast Cancer Cell Lines.

Metabolic alterations are recognized as one of the hallmarks of cancer. Among these, alterations in mitochondrial function have been associated with an enhanced production of Reactive Oxygen Species (ROS), which activate ROS-regulated cancer cell signaling pathways. Breast cancer is the main cancer-related cause of death for women globally. It is a heterogeneous disease with subtypes characterized by specific molecular features and patient outcomes. With the purpose of identifying differences in energy metabolism and the oxidative stress management system in non-tumorigenic, estrogen receptor positive (ER+) and triple negative (TN) breast cancer cells, we evaluated ROS production, protein enzyme levels and activities and profiled energy metabolism. We found differences in energetic metabolism and ROS management systems between non-tumorigenic and cancer cells and between ER+ and TN breast cancer cells. Our results indicate a dependence on glycolysis despite different glycolytic ATP levels in all cancer cell lines tested. In addition, our data show that high levels of ROS in TN cells are a result of limited antioxidant capacity in the NADPH producing and GSH systems, mitochondrial dysfunction and non-mitochondrial ROS production, making them more sensitive to GSH synthesis inhibitors. Our data suggest that metabolic and antioxidant profiling of breast cancer will provide important targets for metabolic inhibitors or antioxidant treatments for breast cancer therapy.

Advancing stroke patient care: a network meta-analysis of dysphagia screening efficacy and personalization.

The increasing incidence of stroke globally has led to dysphagia becoming one of the most common complications in stroke patients, with significant impacts on patient outcomes. Accurate early screening for dysphagia is crucial to avoid complications and improve patient quality of life. Included studies involved stroke-diagnosed patients assessed for dysphagia using bedside screening tools. Data was sourced from Embase, PubMed, Web of Science, Scopus, and CINAHL, including publications up to 10 December 2023. The study employed both fixed-effect and random-effects models to analyze sensitivity, specificity, positive predictive value (PPV), and Negative Predictive Value (NPV), each with 95% confidence intervals. The random-effects model was particularly utilized due to observed heterogeneity in study data. From 6,979 records, 21 studies met the inclusion criteria, involving 3,314 participants from 10 countries. The analysis included six assessment tools: GUSS, MASA, V-VST, BSST, WST, and DNTA, compared against gold-standard methods VFSS and FEES. GUSS, MASA, and V-VST showed the highest reliability, with sensitivity and specificity rates of 92% and 85% for GUSS, 89% and 83% for MASA, respectively. Heterogeneity among studies was minimal, and publication bias was low, enhancing the credibility of the findings. Our network meta-analysis underscores the effectiveness of GUSS, MASA, and V-VST in dysphagia screening for stroke patients, with high sensitivity and specificity making them suitable for diverse clinical settings. BSST and WST, with lower diagnostic accuracy, require more selective use. Future research should integrate patient-specific outcomes and standardize methodologies to enhance dysphagia screening tools, ultimately improving patient care and reducing complications. https://www.crd.york.ac.uk/PROSPERO/#recordDetails.

Nurse Well-Being and Patient-Specific Outcomes: A Scoping Review.

The health and well-being of the nursing workforce has received recent attention due to nurse attrition and the critical nurse shortages projected across the country. A nurse's well-being may impact patient outcomes. The purpose of this scoping review was to assess the association between nurse well-being factors and specific patient outcomes. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) PRISMA Scoping Review protocol and 2020 reporting guidelines were utilized in this review. Staffing, environment, physical health, and mental health of nurses were correlated to specific adverse patient outcomes among the 97 articles included in the final review. The majority of the articles reported significant findings. Patient outcomes were reviewed as discrete events in the articles examined. With mixed results found on key patient outcomes, future research requires more in-depth investigation into the role nurse well-being has on patient outcomes.

Video-Based Performance Analysis in Pituitary Surgery—Part 1: Surgical Outcomes

Endoscopic pituitary adenoma surgery has a steep learning curve, with varying surgical techniques and outcomes across centers. In other surgeries, superior performance is linked with superior surgical outcomes. This study aimed to explore the prediction of patient-specific outcomes using surgical video analysis in pituitary surgery. Endoscopic pituitary adenoma surgery videos from a single center were annotated by experts for operative workflow (3 surgical phases and 15 surgical steps) and operative skill (using modified Objective Structured Assessment of Technical Skills [mOSATS]). Quantitative workflow metrics were calculated, including phase duration and step transitions. Poisson or logistic regression was used to assess the association of workflow metrics and mOSATS with common inpatient surgical outcomes. 100 videos from 100 patients were included. Nasal phase mean duration was 24minutes and mean mOSATS was 21.2/30. Mean duration was 34minutes and mean mOSATS was 20.9/30 for the sellar phase, and 11minutes and 21.7/30, respectively, for the closure phase. The most common adverse outcomes were new anterior pituitary hormone deficiency (n= 26), dysnatremia (n= 24), and cerebrospinal fluid leak (n= 5). Higher mOSATS for all 3 phases and shorter operation duration were associated with decreased length of stay (P= 0.003 &P < 0.001). Superior closure phase mOSATS were associated with reduced postoperative cerebrospinal fluid leak (P < 0.001), and superior sellar phase mOSATS were associated with reduced postoperative visual deterioration (P= 0.041). Superior surgical skill and shorter surgical time were associated with superior surgical outcomes, at a generic and phase-specific level. Such video-based analysis has promise for integration into data-driven training and service improvement initiatives.

A machine learning approach to predict in vivo skin growth

Since their invention, tissue expanders, which are designed to trigger additional skin growth, have revolutionised many reconstructive surgeries. Currently, however, the sole quantitative method to assess skin growth requires skin excision. Thus, in the context of patient outcomes, a machine learning method which uses non-invasive measurements to predict in vivo skin growth and other skin properties, holds significant value. In this study, the finite element method was used to simulate a typical skin expansion protocol and to perform various simulated wave propagation experiments during the first few days of expansion on 1,000 individual virtual subjects. An artificial neural network trained on this dataset was shown to be capable of predicting the future skin growth at 7 days (avg. R2=0.9353\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R^2 = 0.9353$$\\end{document}) as well as the subject-specific shear modulus (R2=0.9801\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R^2 = 0.9801$$\\end{document}), growth rate (R2=0.8649\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R^2 = 0.8649$$\\end{document}), and natural pre-stretch (R2=0.9783\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R^2 = 0.9783$$\\end{document}) with a very high degree of accuracy. The method presented here has implications for the real-time prediction of patient-specific skin expansion outcomes and could facilitate the development of patient-specific protocols.

Computational framework for the generation of one-dimensional vascular models accounting for uncertainty in networks extracted from medical images.

One-dimensional (1D) cardiovascular models offer a non-invasive method to answer medical questions, including predictions of wave-reflection, shear stress, functional flow reserve, vascular resistance and compliance. This model type can predict patient-specific outcomes by solving 1D fluid dynamics equations in geometric networks extracted from medical images. However, the inherent uncertainty in in vivo imaging introduces variability in network size and vessel dimensions, affecting haemodynamic predictions. Understanding the influence of variation in image-derived properties is essential to assess the fidelity of model predictions. Numerous programs exist to render three-dimensional surfaces and construct vessel centrelines. Still, there is no exact way to generate vascular trees from the centrelines while accounting for uncertainty in data. This study introduces an innovative framework employing statistical change point analysis to generate labelled trees that encode vessel dimensions and their associated uncertainty from medical images. To test this framework, we explore the impact of uncertainty in 1D haemodynamic predictions in a systemic and pulmonary arterial network. Simulations explore haemodynamic variations resulting from changes in vessel dimensions and segmentation; the latter is achieved by analysing multiple segmentations of the same images. Results demonstrate the importance of accurately defining vessel radii and lengths when generating high-fidelity patient-specific haemodynamics models. KEY POINTS: This study introduces novel algorithms for generating labelled directed trees from medical images, focusing on accurate junction node placement and radius extraction using change points to provide haemodynamic predictions with uncertainty within expected measurement error. Geometric features, such as vessel dimension (length and radius) and network size, significantly impact pressure and flow predictions in both pulmonary and aortic arterial networks. Standardizing networks to a consistent number of vessels is crucial for meaningful comparisons and decreases haemodynamic uncertainty. Change points are valuable to understanding structural transitions in vascular data, providing an automated and efficient way to detect shifts in vessel characteristics and ensure reliable extraction of representative vessel radii.

Impact of wheat sensitization on wheeze and T2 phenotypes in general population of children

BackgroundThe association between sensitization to specific aeroallergens and outcomes in patients with asthma is well-researched; however, the association between childhood-onset wheeze/asthma and sensitization to various aeroallergens and food allergens in the general pediatric population remains poorly understood. ObjectiveThe association between sensitization to common aeroallergens and food allergens with wheeze and type 2 (T2) inflammation in the general pediatric population was investigated. MethodsSpecific IgEs against nine aeroallergens and four food allergens were measured in the prospective Hokkaido birth cohort of 428 school-age children (approximately 10 years of age). Wheeze and other allergic symptoms were assessed using the International Study of Asthma and Allergies in Childhood questionnaire. Blood eosinophil count and fractional exhaled nitric oxide level were assessed as T2 biomarkers. The Isle of Wight (IOW) birth cohort in UK was used for replication analysis (n=1032). ResultsThe prevalence of sensitization to at least one aeroallergen and food allergen was 70.5% and 22.3%, respectively. A significant association between wheeze and sensitization to aeroallergens such as ragweed, Japanese cedar, mugwort, and pet dander, were found. However, the association between wheeze and wheat sensitization was highly significant (Hokkaido birth cohort, odds ratio [OR]: 4.67; 95% confidence interval [CI]: 1.98–11.01; IOW birth cohort, OR: 4.01, 95% CI: 1.78–9.07). Sensitization to most aeroallergens, though not any food allergens, was associated with the T2high phenotype. ConclusionSensitization to wheat may be an important risk factor for wheeze/asthma development, especially the pathogenesis of T2-non/low asthma, independent of aeroallergens, in the general pediatric population.

German Translation and Linguistic Validation of the LIMB‑Q: A Patient-reported Outcome Measure for Lower Extremity Trauma.

Lower extremity trauma can have a significant impact on a patient's quality of life. The LIMB-Q is a recently developed and validated patient-reported outcome measure that assesses patient-specific outcomes and experience of health care. The aim of this study was to translate and linguistically validate the LIMB-Q from English to German. The translation was performed by combining World Health Organization and Professional Society for Health Economics and Outcomes Research guidelines. The process consisted of forward translations, a backward translation, expert panel meetings, cognitive debriefing interviews with patients, and several rounds of discussion and reconciliation with the creators of LIMB-Q. The goal was to obtain a culturally and conceptually accurate translation of LIMB-Q into German for use in Switzerland. From the two forward translations, there was one primary discrepancy between the two translators that was discussed to determine the most conceptually accurate translation. From the backward translations, there were 63 items that required discussion and re-translation. Nine patients participated in the cognitive debriefing interviews, which led to three items being modified. The translation process led to a linguistically validated and conceptually equivalent German version of the LIMB-Q. The German (Switzerland) version of LIMB-Q is now available. This will offer a valuable tool for lower extremity trauma research and clinical care in German-speaking populations.

Insights into Personalized Care Strategies for Wilms Tumor: A Narrative Literature Review.

Wilms tumor (WT), or nephroblastoma, is the predominant renal malignancy in the pediatric population. This narrative review explores the evolution of personalized care strategies for WT, synthesizing critical developments in molecular diagnostics and treatment approaches to enhance patient-specific outcomes. We surveyed recent literature from the last five years, focusing on high-impact research across major databases such as PubMed, Scopus, and Web of Science. Diagnostic advancements, including liquid biopsies and diffusion-weighted MRI, have improved early detection precision. The prognostic significance of genetic markers, particularly WT1 mutations and miRNA profiles, is discussed. Novel predictive tools integrating genetic and clinical data to anticipate disease trajectory and therapy response are explored. Progressive treatment strategies, particularly immunotherapy and targeted agents such as HIF-2α inhibitors and GD2-targeted immunotherapy, are highlighted for their role in personalized treatment protocols, especially for refractory or recurrent WT. This review underscores the necessity for personalized management supported by genetic insights, with improved survival rates for localized disease exceeding 90%. However, knowledge gaps persist in therapies for high-risk patients and strategies to reduce long-term treatment-related morbidity. In conclusion, this narrative review highlights the need for ongoing research, particularly on the long-term outcomes of emerging therapies and integrating multi-omic data to inform clinical decision-making, paving the way for more individualized treatment pathways.

Translating training to medical practice in trauma care, a literature review.

Trauma, a global health challenge, remains a significant cause of mortality despite advances in trauma management. The establishment of trauma teams has revolutionized care in trauma resuscitation. The training of these teams is designed to promote self-trust and empower trainees in trauma care, enhance performance, and improve patient outcomes. Various training curricula have been developed, utilizing a plethora of teaching methods such as lectures, simulations, debriefings, skill workshops, and demonstrations. However, a universally accepted gold standard curriculum in trauma training is yet to be defined, and there is no standard method for delivering education in injury care teaching. In this review, we have examined relevant literature data on standard teaching programs, the educational delivery methods used, and their impact on adult trauma patients' outcomes and trained team-related outcomes. While most studies indicate improved trained team performance, they consistently show no improvement in patient-specific outcomes such as mortality, morbidity, and length of stay. However, data hints at optimal educational delivery and the role that technology may play in the future of trauma training development.

DenseNet model incorporating hybrid attention mechanisms and clinical features for pancreatic cystic tumor classification.

The aim of this study is to develop a deep learning model capable of discriminating between pancreatic plasma cystic neoplasms (SCN) and mucinous cystic neoplasms (MCN) by leveraging patient-specific clinical features and imaging outcomes. The intent is to offer valuable diagnostic support to clinicians in their clinical decision-making processes. The construction of the deep learning model involved utilizing a dataset comprising abdominal magnetic resonance T2-weighted images obtained from patients diagnosed with pancreatic cystic tumors at Changhai Hospital. The dataset comprised 207 patients with SCN and 93 patients with MCN, encompassing a total of 1761 images. The foundational architecture employed was DenseNet-161, augmented with a hybrid attention mechanism module. This integration aimed to enhance the network's attentiveness toward channel and spatial features, thereby amplifying its performance. Additionally, clinical features were incorporated prior to the fully connected layer of the network to actively contribute to subsequent decision-making processes, thereby significantly augmenting the model's classification accuracy. The final patient classification outcomes were derived using a joint voting methodology, and the model underwent comprehensive evaluation. Using the five-fold cross validation, the accuracy of the classification model in this paper was 92.44%, with an AUC value of 0.971, a precision rate of 0.956, a recall rate of 0.919, a specificity of 0.933, and an F1-score of 0.936. This study demonstrates that the DenseNet model, which incorporates hybrid attention mechanisms and clinical features, is effective for distinguishing between SCN and MCN, and has potential application for the diagnosis of pancreatic cystic tumors in clinical practice.

Abstract PO5-15-12: Spatial immune correlates of response to eribulin and pembrolizumab in metastatic triple negative breast cancer (mTNBC) on the ENHANCE1 trial

Abstract Background: PD-L1 is the only approved biomarker for pembrolizumab in metastatic breast cancer for response to combination chemo-immunotherapy. As it is not predictive of response in all cases, additional biomarkers are needed. Previously we have demonstrated that stromal tumor infiltrating lymphocytes (sTILs) are associated with response to therapy in patients treated with front-line combination chemoimmunotherapy on the ENHANCE-1 study with eribulin and pembrolizumab. However, sTILs was not predictive of response in patients treated with prior lines of chemotherapy in the metastatic setting. We used multiplexed immunofluorescence on whole slide images to characterize associations between specific immune populations and outcomes in patients treated prospectively on the ENHANCE-1 study. Methods: ENHANCE-1 was a single arm phase Ib/II trial which evaluated the efficacy and safety of eribulin and pembrolizumab in 167 patients (pts) with mTNBC who had received 0-2 prior lines of therapy (66 pts in the first line setting [stratum 1] and 101 pts with 1-2 prior lines of therapy [stratum 2]). 138 patient samples were evaluable for our study: 58 samples from stratum 1 and 80 samples from stratum 2. Objective response rate (ORR) was defined as percentage of pts with either complete response (CR) or partial response (PR) by RECIST 1.1. The ORR was 25.8% in stratum 1 and 22.5% in stratum 2 for the 138 patients analyzed. We utilized whole tissue sections and quantitative multiplexed immunofluorescence (qmIF) stained with: CD4, FoxP3, CD8, CD56 and pancytokeratin to characterize T-cells, NK cells and tumor cells. Halo (Indica labs) was used to segment and threshold cells for positive markers as well as to identify tumor and stromal tissue areas. Results: We found that the ratio of CD8+ to CD4+FoxP3+ T-cells were associated with response, irrespective of stratum (p=0.005). As biopsies were not required immediately prior to enrollment on ENHANCE-1, we also evaluated samples based on prior number of treatments since biopsy to enrollment. We found that only 58/138 patient samples evaluated were obtained without intervening treatment: 35 out of 58 from stratum 1 and 12 out of 80 from stratum 2. When samples were evaluated by stratum and the timing of tissue acquisition we found the ratio of CD8+ to CD4+FoxP3+ T-cells was more significantly associated with response (&amp;lt; 0.001) in patients whose sample were collected prior to enrollment, regardless of patient stratum. The ratio was not predictive in samples taken prior to treatments before enrollment. In addition, we found stromal and intratumoral CD8+ T-cell density is associated with response (p=0.02 and p=0.03 respectively) across both stratum. We did not find any significant changes assessed by qmIF in patient samples which had intervening treatment between sample collection and enrollment onto ENHANCE-1 trial. Conclusion: In this population of patients with mTNBC treated prospectively with eribulin and pembrolizumab, we find that a higher ratio of CD8+ to CD4+FoxP3+ T-cells and stromal and intratumoral CD8+ T-cell density is associated with response in patients with biopsy samples obtained prior to enrollment without intervening treatments after sample collection. The tumor microenvironment on patient samples obtained before one or more lines of therapy prior to enrollment on study are not predictive of response to treatment. Further characterization of the TME via quantitative immunofluorescence is ongoing. This study was funded by Eisai Citation Format: Matthew Kearney, Hua Guo, Rami Vanguri, Qi Wang, Eileen Connolly. Spatial immune correlates of response to eribulin and pembrolizumab in metastatic triple negative breast cancer (mTNBC) on the ENHANCE1 trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-15-12.

The role of preoperative immune cell metrics in renal cell carcinoma with a tumor thrombus.

The objective of this study was to stratify preoperative immune cell counts by cancer specific outcomes in patients with renal cell carcinoma (RCC) and a tumor thrombus after radical nephrectomy with tumor thrombectomy. Patients with a diagnosis of RCC with tumor thrombus that underwent radical nephrectomy with thrombectomy across an international consortium of seven institutions were included. Patients who were metastatic at diagnosis and those who received preoperative medical treatment were also included. Retrospective chart review was performed to collect demographic information, past medical history, preoperative lab work, surgical pathology, and follow up data. Neutrophil counts, lymphocyte counts, monocyte counts, neutrophil to lymphocyte ratios (NLR), lymphocyte to monocyte ratios (LMR), and neutrophil to monocyte ratios (NMR) were compared against cancer-specific outcomes using independent samples t-test, Pearson's bivariate correlation, and analysis of variance. One hundred forty-four patients were included in the study, including nine patients who were metastatic at the time of surgery. Absolute lymphocyte count preoperatively was greater in patients who died from RCC compared to those who did not (2 vs 1.4; p < 0.001). Patients with tumor pathology showing perirenal fat invasion had a greater neutrophil count compared to those who did not (7.5 vs 5.5; p = 0.010). Patients with metastatic RCC had a lower LMR compared to those without metastases after surgery (2.5 vs 3.2; p = 0.041). Tumor size, both preoperatively and on gross specimen, had an interaction with multiple immune cell metrics (p < 0.05). Preoperative immune metrics have clinical utility in predicting cancer-specific outcomes for patients with RCC and a tumor thrombus. Additional study is needed to determine the added value of preoperative serum immune cell data to established prognostic risk calculators for this patient population.

Advances in preclinical assessment of therapeutic targets for bladder cancer precision medicine.

Bladder cancer incidence is on the rise, and until recently, there has been little to no change in treatment regimens over the last 40 years. Hence, it is imperative to work on strategies and approaches to untangle the complexity of intra- and inter-tumour heterogeneity of bladder cancer with the aim of improving patient-specific care and treatment outcomes. The focus of this review is therefore to highlight novel targets, advances, and therapy approaches for bladder cancer patients. The success of combining an antibody-drug conjugate (ADC) with immunotherapy has been recently hailed as a game changer in treating bladder cancer patients. Hence, interest in other ADCs as a treatment option is also rife. Furthermore, strategies to overcome chemoresistance to standard therapy have been described recently. In addition, other studies showed that targeting genomic alterations (e.g. mutations in FGFR3 , DNA damage repair genes and loss of the Y chromosome) could also be helpful as prognostic and treatment stratification biomarkers. The use of single-cell RNA sequencing approaches has allowed better characterisation of the tumour microenvironment and subsequent identification of novel targets. Functional precision medicine could be another avenue to improve and guide personalized treatment options. Several novel preclinical targets and treatment options have been described recently. The validation of these advances will lead to the development and implementation of robust personalized treatment regimens for bladder cancer patients.