Risk Groups Research Articles

Public health and economic benefits of seasonal influenza vaccination in risk groups in France, Italy, Spain and the UK: state of play and perspectives

BackgroundSeasonal influenza epidemics have a substantial public health and economic burden, which can be alleviated through vaccination. The World Health Organization (WHO) recommends a 75% vaccination coverage rate (VCR) in: older adults (aged ≥ 65 years), individuals with chronic conditions, pregnant women, children aged 6–24 months and healthcare workers. However, no European country achieves this target in all risk groups. In this study, potential public health and economic benefits achieved by reaching 75% influenza VCR was estimated in risk groups across four European countries: France, Italy, Spain, and the UK.MethodsA static epidemiological model was used to estimate the averted public health and economic burden of increasing the 2021/2022 season VCR to 75%, using the efficacy data of standard-dose quadrivalent influenza vaccine. For each country and risk group, the most recent data on population size, VCR, pre-pandemic influenza epidemiology, direct medical costs and absenteeism were identified through a systematic literature review, supplemented by manual searching. Outcomes were: averted influenza cases, general practitioner (GP) visits, hospitalisations, case fatalities, number of days of work lost, direct medical costs and absenteeism-related costs.ResultsAs of the 2021/2022 season, the UK achieved the highest weighted VCR across risk groups (65%), followed by Spain (47%), France (44%) and Italy (44%). Based on modelling, the 2021/2022 VCR prevented an estimated 1.9 million influenza cases, avoiding 375,200 GP visits, 73,200 hospitalisations and 38,400 deaths. To achieve the WHO 75% VCR target, an additional 24 million at-risk individuals would need to be vaccinated, most of which being older adults and patients with chronic conditions. It was estimated that this could avoid a further 918,200 influenza cases, 332,000 GP visits, 16,300 hospitalisations and 6,300 deaths across the four countries, with older adults accounting for 52% of hospitalisations and 80% of deaths. An additional €84 million in direct medical costs and €79 million in absenteeism costs would be saved in total, with most economic benefits delivered in France.ConclusionsOlder adults represent most vaccine-preventable influenza cases and deaths, followed by individuals with chronic conditions. Health authorities should prioritise vaccinating these populations for maximum public health and economic benefits.

Impact of the COVID-19 pandemic on an Austrian population with or without pre-existing health issues

Background: The COVID-19 pandemic had significant effects on the well-being of individuals all over the world. The Austrian government decided to take various restrictions to contain the spread of the virus and thus protect the COVID-19 risk groups in particular. The aim of this study is to investigate how the COVID-19 risk groups perceive the pandemic and the restrictions to provide results for similar exceptional situations in the future. Methods: For this purpose, we developed a questionnaire consisting of eleven items concerning the influence of the COVID-19 pandemic and the restrictions on well-being and behavior. Participants of the ongoing epidemiological Paracelsus 10,000 study (P10), in Salzburg, Austria, were included. We analyzed data from 989 people and classified the participants into three sub-groups depending on their risk of suffering from a severe course of a COVID-19 infection and tested for effects of risk group, sex, and their interaction. For a better overview we decided to group the questions into four main topics, named “changes in behavior and environment”, “worries caused by the virus and the restrictions”, “mood and mental state” and “long-lasting effects.” Results: We found significant differences between the sub-groups in all main topics and a worsening in well-being across the entire sample. Especially anxiety, insecurity, nervousness, and sleep problems increased while satisfaction decreased. Conclusion: The COVID-19 pandemic and the restrictions have created a highly uncertain environment and the topic was omnipresent and therefore had effects on the well-being and behavior of the risk groups as well as on our entire cohort.

Identification of cuproptosis-related long non-coding RNA and construction of a novel prognostic signature for bladder cancer: An observational study.

Bladder Urothelial Carcinoma (BLCA), a prevalent and lethal cancer, lacks understanding regarding the roles and prognostic value of cuproptosis-related lncRNAs (CRLs), a novel form of cell death induced by copper. We collected RNA-seq data, clinical information, and prognostic data for 414 BLCA samples and 19 matched controls from The Cancer Genome Atlas. Using multivariate and univariate Cox regression analyses, we identified CRLs to create a prognostic signature. Patients were then divided into low- and high-risk groups based on their risk scores. We analyzed overall survival using the Kaplan-Meier method, evaluated stromal and immune scores, and explored functional differences between these risk groups with gene set enrichment analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were also conducted to understand the links between CRLs and BLCA development. We developed a prognostic signature using 4 independent CRLs: RC3H1-IT1, SPAG5-AS1, FAM13A-AS1, and GNG12-AS1. This signature independently predicted the prognosis of BLCA patients. High-risk patients had worse outcomes, with gene set enrichment analysis revealing enrichment in tumor- and immune-related pathways in the high-risk group. Notably, high-risk patients exhibited enhanced responses to immunotherapy and conventional chemotherapy drugs like sunitinib, paclitaxel, and gemcitabine. The independent prognostic signature variables RC3H1-IT1, SPAG5-AS1, FAM13A-AS1, and GNG12-AS1 predicted the prognoses of BLCA patients and provided a basis for the study of the mechanism of CRLs in BLCA development and progression, and the guidance of clinical treatments for patients with BLCA.

Oesophageal cell collection device and biomarker testing to identify high-risk Barrett's patients requiring endoscopic investigation.

Barrett's oesophagus surveillance places significant burden on endoscopy services yet is vital to detect early cancerous change. Oesophageal cell collection device (OCCD) testing was introduced across Scotland for Barrett's surveillance in response to the COVID-19 pandemic. This national pragmatic retrospective study presents the CytoSCOT programme results and evaluates whether OCCD testing is successfully identifying high-risk Barrett's patients requiring urgent endoscopy. All patients undergoing OCCD testing for Barrett's surveillance across 11 Scottish health boards over a 32-month period were identified. Patients who underwent endoscopy within 12 months of OCCD test were included. Individual patient records were interrogated to record clinical information and OCCD test result to categorize patients into risk groups. Endoscopic histopathology results were analysed according to risk group and segment length. Patients were deemed high risk if the OCCD test demonstrated atypia and/or p53 positivity. 4204 OCCD tests were performed in 3745 patients: 608 patients underwent endoscopy within 12 months and were included in this analysis. Patients with longer Barrett's segments were significantly more likely to have an abnormal OCCD test. 50/608 patients (8.2%) had high-grade dysplasia or cancer on endoscopic biopsies: this equates to 1.3% of the total group (50/3745). 46/50 patients (92.0%) were deemed high risk, triggering urgent endoscopy: this rose to 100% with insufficient tests removed. There were no cancers diagnosed within 12 months post-OCCD in the low-risk group. OCCD testing is an effective triage tool to identify high-risk patients with Barrett's oesophagus requiring further investigation with endoscopy within the real-world setting.

Impact of Anxiety, Depression, and Coping Strategies on Health-Related Quality of Life in Patients with Cystic Fibrosis.

With the significant increase in the life expectancy of cystic fibrosis (CF) patients, many individuals now reach adulthood and develop specific coping strategies to maintain their physical and mental well-being. This study aims to evaluate coping styles and their relationship with mental health and Health-Related Quality of Life (H-RQoL) in adult CF patients. Thirty adult CF patients completed the Hospital Anxiety and Depression Scale to assess anxiety and depression, the Cystic Fibrosis Questionnaire-Revised to evaluate quality of life, and the Brief Coping Orientation to Problems Experienced questionnaire to assess coping strategies. Twelve individuals (40%) met the diagnostic criteria for being at risk of experiencing anxiety and/or depression. Anxiety risk group exhibited lower life quality scores in the domains of vitality, emotional functioning, and role limitations (P = .027, P = .001, and P = .001, respectively). Patients reporting depressive symptoms had lower scores in emotional functioning and role limitations domains of quality of life (P = .005 and P = .018, respectively). Multivariate analysis indicated that depression and anxiety scores were significant predictors of emotional quality of life. In terms of coping strategies, "acceptance" was the most commonly preferred, while "substance use" was the least preferred strategy among all participants. Patients at risk of anxiety and/or depression often chose "avoidance" as their coping strategy. Anxiety and depressive symptoms are prevalent and associated with poorer H-RQoL in adult CF patients. These patients preferred to employ giving up strategy when dealing with the disease. Therefore, it is essential to screen adult CF patients for mental health risks and to work on improving their coping strategies.

Improvement the Monitoring System for Post-Injection Infectious Complications

Relevance. The high intensity of the therapeutic and diagnostic process in medical organizations is accompanied by an increase in the manipulation load on patients and, accordingly, an increase in the risk of post-injection infectious complications. In the Russian Federation, in the structure of infections associated with medical care, post-injection complications in the last ten years before the pandemic of a new coronavirus infection occupied 7.0–11.0% [1]. The question of the impact on the prevalence of post-injection complications of medical care conditions that changed during the COVID-19 pandemic remains open for discussion and study. The purpose of this study is to give an epidemiological characterization of post–injection infectious complications in medical organizations, to determine their place in the structure of patient health losses in order to improve the monitoring system for infections associated with medical care. Materials and methods. The forms of statistical observation No. 1, 2 «Information on infectious and parasitic morbidity», No. 30 «Information on medical organizations» for the period 1994–2022, 101 forms of epidemiological investigation of cases of post-injection complications for the period 2015–2022 are analyzed. Epidemiological and statistical research methods were used in the work. Conclusions. During the study period, the prevalence of post-injection complications in outpatient polyclinic organizations of the Khanty–Mansiysk autonomous okrug – Ugra was 0.10 per 100 thousand visits and 3.85 per 100 thousand treated in hospital. The risk groups for post–injection complications were persons of older age groups, and the place of risk was procedural, vaccination rooms, and neurological departments. Abscesses prevailed in the structure of post-injection complications (85.4%), with the most frequent localization of post-injection complications in the gluteal region (47.7%). During laboratory examination of the material, gram-positive microorganisms were isolated from the focus of infection in 72.9% of cases, the largest proportion of which was Staphylococcus aureus (74.3%), including MRSA. In 80.5% of cases of post-injection complications, surgical intervention was required, including 77.8% in a hospital setting. The prerequisites for the occurrence of post-injection complications were excessive manipulation load, prescribing more than 5 drugs to patients and non-compliance with the instructions for injections in 4.8%. The complexity of monitoring post-injection complications is due to the lack of a standard definition of the case in most nosological forms, deliberate concealment of cases of infectious complications and imperfection of laboratory diagnostics.

Investigating the blood rheology in the first trimester pregnancies with high risk for preeclampsia.

Pregnancy is a dynamic process associated with changes in vascular and rheological resistance. Maternal maladaptation to these changes is the leading cause of pregnancy complications such as preeclampsia. This study aimed to assess the hemorheological alterations in pregnancies with a high risk for preeclampsia in the first trimester. Ninety-two pregnant women were allocated into the high preeclampsia risk group (37 cases) and control groups (55 cases). Plasma and whole blood viscosity and red blood cell morphodynamic properties, including deformability and aggregation were assessed by Brookfield viscometer and laser-assisted optical rotational cell analyzer (LORRCA) at 11-14 gestational weeks. Whole blood viscosity was significantly higher in the high-risk group at all shear rates. Plasma viscosity and hematologic factors showed no differences between the groups. Hematocrit levels positively correlated with high blood viscosity only in the high-risk group. There were no significant changes in the other deformability and aggregation parameters. Changes in the whole blood viscosity of pregnant women with high preeclampsia risk refer to impaired microcirculation beginning from the early weeks of gestation. We suggest that the whole blood viscosity is consistent with the preeclampsia risk assessment in the first trimester, and its measurement might be promising for identifying high-preeclampsia-risk pregnancies.

Enhancing pneumonia prognosis in the emergency department: a novel machine learning approach using complete blood count and differential leukocyte count combined with CURB-65 score

BackgroundPneumonia poses a major global health challenge, necessitating accurate severity assessment tools. However, conventional scoring systems such as CURB-65 have inherent limitations. Machine learning (ML) offers a promising approach for prediction. We previously introduced the Blood Culture Prediction Index (BCPI) model, leveraging solely on complete blood count (CBC) and differential leukocyte count (DC), demonstrating its effectiveness in predicting bacteremia. Nevertheless, its potential in assessing pneumonia remains unexplored. Therefore, this study aims to compare the effectiveness of BCPI and CURB-65 in assessing pneumonia severity in an emergency department (ED) setting and develop an integrated ML model to enhance efficiency.MethodsThis retrospective study was conducted at a 3400-bed tertiary medical center in Taiwan. Data from 9,352 patients with pneumonia in the ED between 2019 and 2021 were analyzed in this study. We utilized the BCPI model, which was trained on CBC/DC data, and computed CURB-65 scores for each patient to compare their prognosis prediction capabilities. Subsequently, we developed a novel Cox regression model to predict in-hospital mortality, integrating the BCPI model and CURB-65 scores, aiming to assess whether this integration enhances predictive performance.ResultsThe predictive performance of the BCPI model and CURB-65 score for the 30-day mortality rate in ED patients and the in-hospital mortality rate among admitted patients was comparable across all risk categories. However, the Cox regression model demonstrated an improved area under the ROC curve (AUC) of 0.713 than that of CURB-65 (0.668) for in-hospital mortality (p<0.001). In the lowest risk group (CURB-65=0), the Cox regression model outperformed CURB-65, with a significantly lower mortality rate (2.9% vs. 7.7%, p<0.001).ConclusionsThe BCPI model, constructed using CBC/DC data and ML techniques, performs comparably to the widely utilized CURB-65 in predicting outcomes for patients with pneumonia in the ED. Furthermore, by integrating the CURB-65 score and BCPI model into a Cox regression model, we demonstrated improved prediction capabilities, particularly for low-risk patients. Given its simple parameters and easy training process, the Cox regression model may be a more effective prediction tool for classifying patients with pneumonia in the emergency room.

Abstract PO5-15-11: A Novel Biosignature to Predict Radiation Therapy Response in Early-Stage Invasive Breast Cancer Treated with Breast-Conserving Surgery

Abstract Introduction: Radiation therapy (RT) is a standard component of treatment for most patients with early-stage, hormone receptor-positive, invasive breast cancer (BC) following breast-conserving surgery (BCS). RT recommendations are primarily based on clinicopathologic (CP) factors, such as tumor size, nodal status, and histological grade. While these factors provide prognostic information, their ability to accurately identify patients at a higher risk of ipsilateral breast recurrence (IBR) or those who will significantly benefit from RT is unclear. Therefore, incorporation of additional predictive markers beyond CP factors is warranted and there remains a need to refine the selection criteria for patients who will derive the greatest benefit from RT. In this study, we aimed to explore the role of immune and metabolic signaling axes as potential predictive markers for RT response in hormone receptor-positive breast cancer patients. Methods: A cohort of 939 women from Sweden were diagnosed with BC between 1987 and 2004. A subset of 471 patients was diagnosed with T1-T2N0M0 BC and underwent BCS with negative margins. Patients were treated with BCS plus/minus RT (median dose 50Gy) based upon physician preference. Biomarkers were assayed in formalin-fixed paraffin-embedded tissue micro arrays using multiplex immunofluorescence and multi-spectral imaging in a CLIA lab (Laguna Hills, CA). Immune and metabolic axes were defined employing biomarkers and used to classify patients into three risk groups: 1) Low Risk (lower baseline risk and no RT benefit), 2) Elevated Risk (higher baseline risk and significant RT benefit), and 3) Residual Risk (higher baseline risk and suboptimal RT benefit). Risk groups were analyzed for IBR rate using Kaplan-Meier and Cox proportional hazards analyses. Risk group prognosis and RT prediction was assessed for RT-risk group interaction in multivariable analysis, adjusting for CP factors. Results: Among the patients with complete biomarker data, 261 were hormone receptor-positive, and had a median follow-up of 140 months. Median age was 62 years (28-88 years), and median tumor size was 1.1 cm (0.1-4 cm). Some patients (21%) received endocrine therapy (ET), and most (76%) received RT, with 79% of patients who received ET also receiving RT. In the overall population, RT following BCS was associated with a reduction in HR for recurrence (HR=0.3, 95%CI [0.1, 0.5], p&amp;lt; 0.001). Patients classified as Low Risk (41%) did not have a significant benefit from RT (HR=0.9, 95%CI [0.1, 8.3], p=0.95) in multivariable analysis adjusted for CP factors. For patients who were classified as Elevated Risk (31%), multivariable analysis showed a higher IBR rate without RT (HR=5.7, 95%CI [1.3, 25.1], p&amp;lt; 0.021) relative to the Low Risk group who had a significant benefit from RT (HR=0.1, 95%CI [0.02, 0.2], p&amp;lt; 0.001). Patients classified into the Residual Risk group (28%) had no significant reduction from RT (HR=0.7, 95%CI [0.2, 2.0], p=0.61). However, in multivariable analysis adjusted for CP factors, patients treated with RT in the Residual Risk group had higher IBR rates (HR=3.7, 95%CI [1.6, 8.7], p=0.0026) compared to RT-treated patients in other risk groups. The biosignature was predictive for RT benefit in multivariable analysis adjusted for CP factors (p-interaction &amp;lt; 0.001). Conclusions:The biosignature used in this study demonstrated the potential to identify patients who may derive limited benefit from RT, allowing for tailored therapeutic approaches. These findings underscore the importance of individualized treatment decisions based on risk stratification. Further clinical validation and refinement of risk stratification strategies are warranted to optimize outcomes in hormone receptor-positive, BC patients undergoing BCS. Citation Format: Troy Bremer, Karuna Mittal, Chirag Shah, Frank Vicini, Steven Shivers, Charlotta Wadsten. A Novel Biosignature to Predict Radiation Therapy Response in Early-Stage Invasive Breast Cancer Treated with Breast-Conserving Surgery [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 PO5-15-11.

Abstract PO4-07-05: Clinical evaluation of image-based risk profiling in breast cancer histopathology and comparison to an established gene expression assay

Abstract Background: Among oestrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative early breast cancer, a significant proportion of patients are categorised as intermediate risk, based on classic clinico-pathological variables, thus providing limited information to guide adjuvant chemotherapy decisions. Prognostic risk profiling is an integrated part of modern breast cancer diagnostics to provide additional risk information for this patient group. Among the established prognostic assays based on gene expression, the Prosigna assay is widely used and provides an individual risk of recurrence (ROR) score and identifies intrinsic subtypes with associated survival outcomes. Pioneering artificial intelligence-based precision diagnostics, Stratipath Breast, is a deep learning-based image analysis tool that utilises digitised histopathological whole slide images to stratify intermediate risk patients in terms of risk of recurrence. Materials and methods: The study included 234 invasive breast tumours from patients with early ER-positive HER2-negative breast cancer, clinically assessed as intermediate risk tumours and eligible for chemotherapy. All tumours had therefore previously been analysed by the Prosigna assay in clinical routine at point of diagnosis between 2020 and 2022 at the Karolinska University Hospital and Södersjukhuset, Stockholm, Sweden. Clinicopathological data including Prosigna results (ROR score, risk group and intrinsic subtype) were extracted from medical records, along with the corresponding archived haematoxylin and eosin (HE)-stained formalin-fixed paraffin-embedded tissue slides. The HE slides were subsequently digitised and analysed by the Stratipath Breast tool. The agreement between the two tests for risk stratification was evaluated in this real-world breast cancer case series. Results: The Prosigna assay classified 76 (32.5%), 110 (47.0%) and 48 (20.5%) tumours as low, intermediate and high risk, respectively. The Stratipath Breast analysis identified 116 (49.6%) tumours as low risk and 118 (50.4%) as high risk. Among Prosigna intermediate risk tumours, 52 (47.3%) were stratified as low risk and 58 (52.7%) as high risk by Stratipath Breast. The overall agreement between the two tests for low risk and high risk groups was 71.0%, with a Cohen’s linear kappa of 0.42. Twelve of the 48 Prosigna high risk cases were classified as Stratipath low risk. ROR scores were higher in the Stratipath high risk group compared to the low risk group (p &amp;lt; 0.001), across all cases as well as in the Prosigna intermediate group. Among the 176 histological grade (NHG) 2 tumours, 97 (55.1%) and 79 (44.9%) were stratified as Stratipath low risk and high risk, respectively, whereas 66 (37.5%), 83 (47.2%) and 27 (15.3%) were stratified as Prosigna low, intermediate and high risk, respectively. The majority of NHG1 (10 of 12) and NHG3 (37 of 46) tumours were stratified as Stratipath low risk and high risk, respectively. For both risk profiling tests, NHG and Ki67 proliferation index differed between risk groups. Conclusions: In this study of clinically assessed intermediate risk ER-positive HER2-negative breast cancer, we observed a moderate agreement between Prosigna and Stratipath Breast for low risk and high risk groups. In addition, image-based risk profiling stratified more of the NHG2 tumours as high risk. Citation Format: Stephanie Robertson, Yinxi Wang, Wenwen Sun, Emelie Karlsson, Sandy Kang Lövgren, Mattias Rantalainen, Johan Hartman. Clinical evaluation of image-based risk profiling in breast cancer histopathology and comparison to an established gene expression assay [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 PO4-07-05.

Abstract PO1-14-05: A comparison of chemotherapy recommendations by NPI, Predict, and Oncotype DX testing in UK women with early node positive breast cancer

Abstract Introduction: Gene expression testing is expensive and, unless it changes the chemotherapy (CT) decision, unnecessary. Both Nottingham Prognostic Index (NPI) and Predict Breast Cancer (Predict) are free to use and based on clinico-pathological data. Each gives a guide to the prognosis. Many clinical teams in the UK have used these indices to guide treatment and more recently to help decide who should have access to gene expression testing. NPI scores of ≤2.4 have a cancer-specific ten-year survival of 96%, and &amp;gt;2.4 to ≤3.4, &amp;gt;3.4 to ≤5.4 and &amp;gt;5.4 have survivals of 93%, 78% and 44% respectively. UK oncologists use it as a guide in recommending adjuvant treatment. CT is not recommended for patients with NPI ≤3.4, is discussed as on option for NPI &amp;gt;3.4 to ≤5.4 and is recommended for NPI &amp;gt;5.4. Similarly, Predict can be used to guide CT decisions as follows: &amp;lt; 3% benefit, CT not recommended; 3-5% CT discussed as a possible option; &amp;gt;5% CT recommended. The OncotypeDX® Breast Recurrence Score® test has been assessed recently in the RxPONDER trial which concluded that postmenopausal women with a Recurrence Score (RS) result &amp;lt; 26 showed no benefit from the addition of CT. This study compares the clinical utility of three indices (NPI, Predict, and RS result) by assessing the distribution of NPI and Predict across RS result, evaluates changes in CT recommendations based on risk group, and by estimating the likelihood of CT recommendation. Methods: We recently conducted a prospective UK decision impact, decision conflict and economic analysis of Oncotype DX® test in early node positive, hormone receptor positive and HER2 negative breast cancer involving 664 women. Using these data, we calculated the NPI and the Predict score. Descriptive statistics, logistic regression and McNemar’s tests were used to assess the associations between NPI, Predict, RS result and change in CT decisions for all patients (n=664) and in the cohort of post-menopausal patients recruited after RxPONDER reported (n=176). Results: Table 1 shows similar stratification for all three indices within the low-risk groups, but not for the high-risk groups. Similar results were observed in the post-menopausal, post-RxPONDER cohort. The results of the CT decision change in the post-menopausal, post-RxPONDER patients by NPI and Predict demonstrate the utility of RS results across all NPI and Predict risk groups (Table 2). There was a stronger association between RS result (26-100 vs 0-25) and CT recommendation (OR152.8, 95% CI 53.9-433.2, p&amp;lt; 0.001) as compared to the association between either NPI or Predict (OR 8.7, 95% CI 3.8-19.8, p&amp;lt; 0.001 and OR 7.2, 95% CI 2.8-18.3, p=0.003 respectively), suggesting that UK Oncologists are predominantly using RS to guide their CT decisions. Conclusions: Either basing CT decisions or selecting which patients should undergo OncotypeDX testing by pre-screening with either NPI or Predict risks misclassifing many patients who either need potentially lifesaving CT or who can safely avoid chemotherapy altogether. Table 1. Predict and NPI risk groups by RS result for all patients and for the post-menopausal, post-RxPONDER cohort. Table 2. CT recommendation pre-and post-assay by risk group for post-menopausal, post-RxPONDER patients. Citation Format: Simon Holt, Paige Innis, Priyadharshini Sai-Giridhar, Satish Seerapu. A comparison of chemotherapy recommendations by NPI, Predict, and Oncotype DX testing in UK women with early node positive breast cancer [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 PO1-14-05.

Interactions between physical exercise, associative memory, and genetic risk for Alzheimer's disease.

The ε4 allele of the APOE gene heightens the risk of late onset Alzheimer's disease. ε4 carriers, may exhibit cognitive and neural changes early on. Given the known memory-enhancing effects of physical exercise, particularly through hippocampal plasticity via endocannabinoid signaling, here we aimed to test whether a single session of physical exercise may benefit memory and underlying neurophysiological processes in young ε3 carriers (ε3/ε4 heterozygotes, risk group) compared with a matched control group (homozygotes for ε3). Participants underwent fMRI while learning picture sequences, followed by cycling or rest before a memory test. Blood samples measured endocannabinoid levels. At the behavioral level, the risk group exhibited poorer associative memory performance, regardless of the exercising condition. At the brain level, the risk group showed increased medial temporal lobe activity during memory retrieval irrespective of exercise (suggesting neural compensatory effects even at baseline), whereas, in the control group, such increase was only detectable after physical exercise. Critically, an exercise-related endocannabinoid increase correlated with task-related hippocampal activation in the control group only. In conclusion, healthy young individuals carrying the ε4 allele may present suboptimal associative memory performance (when compared with homozygote ε3 carriers), together with reduced plasticity (and functional over-compensation) within medial temporal structures.

Construction of oxidative phosphorylation-related prognostic risk score model in uveal melanoma

BackgroundUveal melanoma (UVM) is a malignant intraocular tumor in adults. Targeting genes related to oxidative phosphorylation (OXPHOS) may play a role in anti-tumor therapy. However, the clinical significance of oxidative phosphorylation in UVM is unclear.MethodThe 134 OXPHOS-related genes were obtained from the KEGG pathway, the TCGA UVM dataset contained 80 samples, served as the training set, while GSE22138 and GSE39717 was used as the validation set. LASSO regression was carried out to identify OXPHOS-related prognostic genes. The coefficients obtained from Cox multivariate regression analysis were used to calculate a risk score, which facilitated the construction of a prognostic model. Kaplan-Meier survival analysis, logrank test and ROC curve using the time “timeROC” package were conducted. The immune cell frequency in low- and high-risk group was analyzed through Cibersort tool. The specific genomic alterations were analyzed by “maftools” R package. The differential expressed genes between low- or high-risk group were analyzed and performed Gene Ontology (GO) and GSEA. Finally, we verified the function of CYC1 in UVM by gene silencing in vitro.ResultsA total of 9 OXPHOS-related prognostic genes were identified, including NDUFB1, NDUFB8, ATP12A, NDUFA3, CYC1, COX6B1, ATP6V1G2, ATP4B and NDUFB4. The UVM prognostic risk model was constructed based on the 9 OXPHOS-related prognostic genes. The prognosis of patients in the high-risk group was poorer than low-risk group. Besides, the ROC curve demonstrated that the area under the curve of the model for predicting the 1 to 5-year survival rate of UVM patients were all more than 0.88. External validation in GSE22138 and GSE39717 dataset revealed that these 9 genes could also be utilized to evaluate and predict the overall survival of patients with UVM. The risk score levels related to immune cell frequency and specific genomic alterations. The DEGs between the low- and high- risk group were enriched in tumor OXPHOS and immune related pathway. In vitro experiments, CYC1 silencing significantly inhibited UVM cell proliferation and invasion, induced cell apoptosis.ConclusionIn sum, a prognostic risk score model based on oxidative phosphorylation-related genes in UVM was developed to enhance understanding of the disease. This prognostic risk score model may help to find potential therapeutic targets for UVM patients. CYC1 acts as an oncogene role in UVM.

Abstract PO1-14-11: Different molecular processes are associated with recurrence in the clinical high- genomic low risk (cH/gL) and clinical low- genomic high risk (cL/gH) groups of the MINDACT clinical trial

Abstract Background: Despite the growing understanding of estrogen receptor positive/HER2-negative (ER+/HER2-) breast cancer (BC) biology, many unknowns remain regarding the mechanisms of disease recurrence. While several multigene prognostic signatures have shown clinical utility in identifying those patients at high or low genomic risk of recurrence, they can present with some limitations. In this retrospective analysis of the MINDACT trial, we interrogated the available transcriptomic data to understand which biological characteristics of the tumor are associated with recurrence in patients from the clinical high- genomic low risk (cH/gL) and clinical low- genomic high risk (cL/gH) groups (where the clinical and genomic risk were defined by a modified version of Adjuvant Online! and the 70-gene signature, respectively). Methods: These analyses focused on the subset of patients with ER+/HER2- tumors of no special type (NST) who received endocrine therapy (which comprised the majority of this NST ER+/HER2- sub-cohort) and for which central pathology and gene expression data were available (n= 1245). Scores of gene expression modules associated with key biological processes in breast cancer defined in a collection of previous publications were computed from the gene expression matrix using the formula described in Desmedt et al. (Clin. Cancer Res. 2008). Gene Set Variation Analysis method (R package ‘GSVA’ – version 1.40.1) was used to derive the enrichment scores of fifty hallmark gene sets available in the ‘H’ collection of the MSigDB database (version 7.5.1). Survival analyses were performed for disease-free survival (DFS) and distant recurrence-free survival (DRFS). Univariable and multivariable regression models, implemented by Cox regression and Fine-Gray subdistribution hazard regression methods, were performed to evaluate the association of enrichment of hallmarks and gene modules with DFS and DRFS, respectively (covariates =age, nodal status, KI67, tumor size, chemotherapy, radiotherapy). Results: DFS event occurred in 150/913 (16.4%) and 51/332 (15.4%) NST ER+/HER2- patients in the cH/gL and cL/gH groups, respectively. DRFS event occurred in 70/913 (7.7%) and 21/332 (6.3%) NST ER+/HER2- patients in the cH/gL and cL/gH groups, respectively. In the cH/gL group, we observed an association of hallmarks related to cell cycle and downregulation of gene modules related to lymphocyte-centric immune activities with worse prognosis (Table). For the cL/gH, we did not observe an association between hallmarks related to cell cycle and worse prognosis but an enrichment of hallmarks related to PI3K/AKT/mTOR signaling as well as several metabolic hallmarks related to insulin activities (Table). Of interest, in this group of patients, higher scores of the HER2-associated gene expression signature were also associated with worse prognosis. Across the two groups effects were more pronounced for DRFS than DFS. Conclusion: Different molecular processes are associated with progression in these two distinct groups of patients. The association of hallmarks related to cell cycle with survival in the cH/gL group supports the observation that adjuvant chemotherapy could benefit a subset of these patients. In the cL/gH group, the association of signatures associated with PI3K pathway and HER2 can have potential clinical relevance given their current targetability in the metastatic setting. This retrospective study is funded by the Breast Cancer Research Foundation. Table. Representative hallmarks and gene expression modules independently associated with prognosis in NST ER+/HER2- patients in the cH/gL group and in the cL/gH group #p-values reported were not corrected for multiple testing Citation Format: Christine Desmedt, Ha-Linh Nguyen, François Richard, Marion Maetens, Coralie Poncet, Laura De Meulemeester, Kim Aalders, Mauro Delorenzi, Suzette Delaloge, Jean-Yves Pierga, Etienne Brain, Suzan Vrijaldenhoven, Peter A Neijenhuis, Emiel Rutgers, Florentine Hilbers, Laura Van ’t Veer, Giuseppe Viale, Christos Sotiriou, Martine Piccart, Fatima Cardoso. Different molecular processes are associated with recurrence in the clinical high- genomic low risk (cH/gL) and clinical low- genomic high risk (cL/gH) groups of the MINDACT clinical 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 PO1-14-11.

Abstract PO1-28-03: Impact of the Oncotype DX® test over time and association with clinicopathological characteristics of Peruvian patients with early breast cancer: Experience in the last 15 years

Abstract Introduction: Gene expression assays provide prognostic and therapy-predictive information that complements management of early breast cancer patients. Oncotype DX® had showed prognostic and prediction of adjuvant chemotherapy benefit. The present study evaluates the impact of Oncotype DX® on therapeutic decision-making for 15 years and explores the association of clinicopathological characteristics with the Recurrence Score (RS) in Peruvian patients with early breast cancer. Material and methods: A retrospective multicenter analysis of 759 breast cancer patients treated in three oncological centers in Lima-Peru (Instituto Nacional de Enfermedades Neoplásicas, Oncosalud and Ricardo Palma) between 2007 and 2022 was conducted. Risk groups were classified according to Oncotype DX® result and menopausal status. For premenopausal women ≤ 50 years: low (RS=0-20), intermediate (RS=21-25) and high-risk (RS=26-100). A descriptive analysis was evaluated to observe the trend and profile of the patients who used the Oncotype test in 5 time periods (2007-2009, 2010-2013, 2014-2016, 2017-2019, 2020-2022). Subsequently, chi-square, t-test, analysis of variance and Poisson linear regression tests were applied to compare clinicopathological features with RS. Finally, univariate and multivariate analyses were performed using Cox logistic regression to identify the probability of association with the high-risk group. Results: 642 patients were included, 78.5% were postmenopausal, and 64.2% had clinical stage (CS) I. Overall, 63.4% had no recommendation for chemotherapy and only 5.6% had recurrence. 74.8% were classified as low-risk according to the Oncotype DX® result. Postmenopausal patients had negative lymph nodes (95.4%), the majority had undergone conservative surgery (71.8%) and had a low rate of breast reconstruction (11.9%). An increase in the use of Oncotype DX® was observed over time, especially in premenopausal patients (from 4.5% in 2007 to 36.9% in 2022). A significant association was found between luminal B subtype (p &amp;lt; 0.0001), histological grade 3 (p &amp;lt; 0.0001) and T3 vs. T1/2 (p=0.025). In univariate analysis, luminal B subtype (vs. luminal A, OR=5.56, 95% CI, 2.80-12.3, p&amp;lt; 0.001), T3 (vs. T1/2, OR=2.84, 95% CI, 0.13-30.0, p=0.006), histological grade 3 (vs. 1/2, OR=13.1, 95% CI, 5.35-39.6, p&amp;lt; 0.001) and histology (other vs. ductal/lobulillar/mucinous, OR=2.94, 95% CI, 0.57-13.5, p=0.003) provided a higher probability of obtaining a high-risk RS result. Similar results were found in multivariate analysis. Conclusion: The use of the Oncotype DX® had a significant impact on therapeutic decision-making in Peruvian patients with early breast cancer, with an increase of use in the last 15 years. A high-risk RS was associated with luminal B subtype, histological grade 3 and T3 tumor size, which could facilitate risk stratification and provide valuable information for the need of adjuvant chemotherapy. Keywords: Early breast cancer, Oncotype DX®, clinicopathological characteristics, Recurrence Score (RS), Peru Oncotype PERU Table Citation Format: Steffi Katheryne Gonzalez Bocanegra, Guillermo valencia Mesías, Yomali Aroa Ferreyra Chombo, Karoll Tatiana Meza Garcia, Mariano Lopez-Pereyra, Jorge Torres Maldonado, Edgar Fermín Yan Quiroz, Zaida Morante Cruz, Jose Cotrina-Concha, Henry Gómez, Gabriela Calderon Valencia, Mauricio León Rivera. Impact of the Oncotype DX® test over time and association with clinicopathological characteristics of Peruvian patients with early breast cancer: Experience in the last 15 years [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 PO1-28-03.

Abstract GS03-06: Genomic and transcriptomic profiling of primary tumors from patients with HR+, HER2-, node-positive, high-risk early breast cancer in the monarchE trial

Abstract Background Two years of adjuvant abemaciclib combined with endocrine therapy (ET) resulted in significant and clinically meaningful improvement in invasive disease-free survival (IDFS) and distant relapse-free survival (DRFS) in patients (pts) with HR+, HER2-, node-positive, high-risk early breast cancer in the monarchE trial (NCT03155997). Abemaciclib benefit was sustained beyond the completion of treatment (tx) with deepening magnitude of absolute benefit in IDFS and DRFS at 5 years. Here, we evaluate comprehensive molecular profiling of archived primary tumor tissue and association with clinical outcomes. Methods For biomarker analysis, a proportionally stratified random sampling case-cohort design was utilized to include all patients who experienced an IDFS event at a pre-specified interim analysis with a median follow up of 54 months. A cohort of 895 pts (189 with IDFS event) in the abemaciclib + ET arm was matched 1:1 with 903 pts (270 with IDFS event) in the ET arm. Baseline primary tumor samples underwent exome-capture RNA sequencing (RNAseq; n=1324, 23% intent-to-treat (ITT) population) and paired tumor-normal (germline blood samples) whole-exome sequencing (WES; n=1234, 22% ITT population). Expression-based intrinsic subtypes (i.e., luminal A (LumA), luminal B (LumB), HER2-enriched (HER2E), basal- and normal-like) were characterized using the Absolute Intrinsic Molecular Subtyping model. The 21-gene expression signature score (Oncotype DX test) was inferred from RNAseq; samples were categorized into lower (0-25) and high (26-100) risk groups. To investigate associations of biomarkers with abemaciclib benefit, WES genomic events including oncogenic and hotspot mutations by OncoKB, and copy number events, of incidence &amp;gt;9% were pre-selected. Results The biomarker subset of monarchE was reflective of the ITT population. A total of 1190 tumors (abemaciclib+ET n= 605; ET alone n=585) yielded adequate RNAseq results. Intrinsic subtype distribution was consistent across tx arms (Table A). Low tumor purity limited assessment of the normal-like subtype. The 4-year IDFS benefit of abemaciclib was consistent across all subtypes. LumA cancers had the lowest risk of recurrence while HER2E and basal-like subtypes had the highest. Inferred 21-gene expression signature score showed similar benefits from abemaciclib in both lower and high-risk groups (Table B). A total of 1173 tumors yielded adequate WES results (abemaciclib+ET n=580; ET alone n=593). Consistent abemaciclib benefit was observed across the most frequently altered genes (Table C). In exploratory analysis, lower benefit from abemaciclib was seen in the subset of focal-high level MYC amplified tumors (n=176, HR 1.30, 95% CI, 0.77, 2.20) compared to MYC non-amplified tumors (n=997, HR 0.62, 95% CI, 0.47, 0.80, nominal interaction p=0.014). The treatment benefit of abemaciclib was observed across all subpopulations of altered genes based on gene expression data. Conclusions Adjuvant abemaciclib+ET maintained IDFS benefit compared to ET alone across all molecular subtypes as measured by RNAseq. Benefit was consistent across most altered genes assessed by WES, except for the subset of tumors with MYC amplification. Additional research is necessary to confirm these findings. Table. Citation Format: Nicholas Turner, Jorge Reis-Filho, Matthew Goetz, Christine Desmedt, Sarat Chandarlapaty, Hironobu Sasano, Carlos Arteaga, Sherene Loi, Stephanie Graff, Deli Liu, Vanessa Rodrik-Outmezguine, Anthony Sireci, Cynthia Sandoval Rubenstein, Helen Won, Lacey M. Litchfield, Maria Munoz, Stephen Johnston. Genomic and transcriptomic profiling of primary tumors from patients with HR+, HER2-, node-positive, high-risk early breast cancer in the monarchE 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 GS03-06.

Abstract PO2-01-14: Development of Artificial Intelligence-based Machine Learning Models for Predicting Survival In Hormone-Receptor-Positive/HER2-Negative Early Breast Cancer undergoing Neoadjuvant Chemotherapy

Abstract Background. In hormone-receptor positive (HoR)/HER2 negative early breast cancer (BC) multiple efforts have been made to predict disease recurrence and survival. Machine learning techniques have been used but few studies have looked into their applicability in predicting survival on the basis of clinico-pathological characteristics. The aim of this study was to evaluate a random survival forest model to predict the prognosis of this specific BC subtype. Methods. In this multicenter, retrospective study, patients who fulfilled the following inclusion criteria were included: (1) diagnosis of pathologically confirmed HoR-positive/HER2-negative invasive BC; (2) early or locally advanced, stage I-II-III (3) patients receiving neoadjuvant anthracycline and/or taxane-based chemotherapy, concurrently or sequentially; (4) patients undergoing surgery for primary BC. Survival endpoints were disease-free survival (DFS) and overall survival (OS). A random survival forest algorithm was used to develop the predictive model. Ten-fold cross-validation was performed. The C-index and the continuous rank probability score (CRPS) were used to evaluate the discrimination of the predictive model, and a ROC curve was used to evaluate model precision. A cut point analysis based on maximally selected rank statistics was conducted to evaluate the best cut-off in the out-of-bag (OOB) mortality that could maximize DFS and OS prediction. Variable importance was assessed using Breiman-Cutler permutation importance. Results. Overall, 572 patients with HoR-positive/HER2-negative early BC were included. At univariate analysis age, T stage, N stage, grading, ER, PR and Ki67 were found to be significantly associated with DFS and ER, PgR, HER2, pCR ypT and ypN retained statistical significance at multivariate analysis. ER, pCR, pathological T and N stage were found to be significantly associated with OS at univariate and multivariate analysis. The following variables were included in the final model: menopausal status, age, histology, grade, clinical T/N, ER/PgR, Ki67 and HER2, pathological complete response (pCR), ypT and ypN. For DFS, the cross-validated C-index was 0.68 (95% CI 0.63-0.73) and the OOB CRPS was 0.15, with a OOB performance error of 0.31. The AUC calculated at 60 months was 0.91 (95% CI 0.88-0.94). Out-of bag RSF-based risk scores for individual patients were calculated and an optimal cut-off of 22.58 was identified. The HR between high risk and low risk group was 3.08 (95% CI 2.16-4.39, p&amp;lt; 0.001). For OS, the cross-validated C-index was 0.66 (95% CI 0.60-0.71) and the OOB CRPS was 0.17, with a OOB performance error of 0.35. The AUC calculated at 60 months 0.91 (95% CI 0.88-0.95). An optimal cut-off of 21.54 was identified and the HR between low risk and high risk group was 2.50 (95% CI 1.73-3.61, p&amp;lt; 0.001). For DFS, the most important variables were cN (9.00), ypN (7.35), ER (7.21), ypT (5.38), PgR (4.11), pCR (4.01) and age (2.82) while for OS the most important variables were cN (7.88), ER (5.37), PgR (3.61), age (3.37), pCR (2.80), ypT (2.64) and ypN (2.60). Discussion. We analyzed the performance of RSF in the prediction of DFS and OS based on the contribution of clinico-pathological features commonly available at the baseline of the NCT and post-surgery. By selecting patients with HoR-positive HER2-negative disease, we were able to show which clinico-pathological features within a ML model have greater predictive importance. The model could be integrated with image-based tumor and radiology features to improve its predictive accuracy. This retrospective multicenter study suggests that the combination of easily accessible clinico-pathological features within a ML model may reliably predict DFS and OS in the context of HoR-positive/HER2-negative BCs. Citation Format: Luca Mastrantoni, Giovanna Garufi, Noemi Maliziola, Elena Di Monte, Giorgia Arcuri, Valentina Frescura, Angelachiara Rotondi, Giulia Giordano, Luisa Carbognin, Alessandra Fabi, Ida Paris, Gianluca Franceschini, Armando Orlandi, Antonella Palazzo, Giovanni Scambia, Giampaolo Tortora, Emilio Bria. Development of Artificial Intelligence-based Machine Learning Models for Predicting Survival In Hormone-Receptor-Positive/HER2-Negative Early Breast Cancer undergoing Neoadjuvant Chemotherapy [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 PO2-01-14.

Abstract PO4-11-01: Validation of a CARG-BC-based score for the prediction of therapy-induced toxicities in patients with metastatic breast cancer

Abstract Introduction Prediction of treatment-induced toxicities is important in order to tailor and adjust oncologic therapies. As limited tools exist to predict the risk of therapy-induced toxicities in patients with metastatic cancer, we aimed to develop and to validate a score for the prediction of therapy-induced toxicities in patients with metastatic breast cancer treated with chemotherapy and immunotherapy. The score was based on the Cancer and Aging Research Group-Breast Cancer early-stage breast cancer score for prediction of chemotherapy-induced toxicities. Methods All patients treated for metastatic breast cancer with chemotherapy and immunotherapy at the Department of Gynecology, Obstetrics and Reproductive Medicine at Saarland University Hospital between 01/2014 and 05/2022 were included in this retrospective study. Patient characteristics and therapy-relevant oncological parameters were recorded, as well as therapy-induced toxicities (recorded according to CTC), hospitalization rates, toxicity-related dose reductions and therapy discontinuations. In the first cohort (development cohort), a new score for the prediction of therapy-induced toxicities was developed using ROC analysis and multivariate analysis based on the CARG-BC score. In the second cohort (validation cohort), this was validated using Pearson’s correlation coefficient. Results Data from 32 patients were analyzed for the development cohort, and inclusion of 102 patients contributed to the validation cohort. The newly developed score consists of seven independent factors for the prediction of toxicities ≥ CTC III° and includes the parameters “presence of visceral metastases” (yes/no), “received previous lines of therapy” (yes/no), “limited mobility/able to walk less than one kilometer” (yes/no), “a fall in the last six months” (yes/no), “social interactions” (yes/no), “pretherapeutic change of transaminases” (yes/no) and “pretherapeutic change of hemoglobin” (hemoglobin &amp;lt;/&amp;gt; 10 g/dl). Based on the results, three risk groups were defined (low (0-2), medium (3-5) and high (6-15) risk). 28% of patients were in the low-risk group, 37% in the intermediate-risk group and 34% in the high-risk group. Overall, 49% of the patients had toxicities ≥ CTC III°. Distributed across the subgroups, these occurred in 14% in the low-risk group, 34% in the intermediate-risk group and in 52% in the high-risk group (p ≤ 0.01). Risk score results showed a correlation with treatment discontinuation and hospitalization rate (p ≤ 0.01), but not with dose reduction (p = 0.77). Conclusion The available data show a correlation between the risk score results and the occurrence of systemic therapy-induced toxicities in patients with metastatic breast cancer. The results can be used to further identify risk populations and to systematically apply preventive and supportive measures in order to approve quality of life in patients with metastatic breast cancer. Citation Format: Julia SM Zimmermann, Aylin Aygün, Askin Kaya, Marc P Radosa, Christoph G Radosa, Erich F Solomayer, Julia C Radosa. Validation of a CARG-BC-based score for the prediction of therapy-induced toxicities in patients with metastatic breast cancer [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 PO4-11-01.

Abstract PO3-02-04: Comparison of OncotypeDX Recurrence Scores (RS) and MammaPrint (MP) scores, and chemotherapy indications in early-stage Estrogen Receptor positive/HER2 negative (ER-/HER2-) breast cancer

Abstract Background: Both RS and MP are endorsed by ASCO and NCCN practice guidelines to estimate prognosis of early-stage ER+/HER2- breast cancers and results guide adjuvant chemotherapy treatment recommendations. Earlier studies reported around 30% discordance in risk assignments by different genomic assays, but these comparisons were complicated by the 3-way (low, intermediate, high) versus 2-way (low, high) risk assignment by RS and MP respectively. More recently, RS thresholds were re-evaluated in the context of the TAILORx and RxPONDER randomized clinical trials and RS &amp;gt;25 is now considered indication for adjuvant chemotherapy. MP results are now also reported as continuous scores similar to RS, and MP high risk patients can be subdivided into MP1 (high) and MP2 (ultra-high) risk groups. The goal of this analysis was to assess correlation between RS and MP scores as continuous variables and examine concordance in chemotherapy eligibility and risk category assignments. Methods: 168 patients treated at the West Cancer Center and Research Institute had patients with both MP and RS results available for the same patient generated by Agendia as a research activity and Exact Sciences in the context of routine care. Molecular class was assigned by the MammaPrint Blueprint assay. Results and clinical information were retrieved from the medical records. Median age was 64 years (range 25-92), 77% were postmenopausal, 59% White, 37% Black and 4% other. 78% had histologic grade 1 or 2 cancers, 53%, 38%, and 8% were stage I, II, and III, respectively. 84% were invasive ductal carcinoma, 13% invasive lobular carcinoma, the rest mixed or other rare histologies. Patients were considered high-risk and chemotherapy eligible if the RS was &amp;gt;25 or the MP score was &amp;lt; 0 (i.e. any negative value), MP high-risk patients were further categorized into MP1 (MP score between 0 to -0.5699) and MP2 (MPs score -0.57 or less). Correlation between scores were assessed using Pearson correlation. Results: There was statistically significant correlation between RS and MP scores with a Pearson correlation coefficient of -0.61, (p&amp;lt; 0.0001). 51 (30%) cancers were MP low-risk (Luminal A), and 122 (73%) were RS low risk (RS≤25). Among the MP low-risk cancers, 47 (92%) had concordant low risk assignment by RS. Based on RS, 46 (27%) patients were high-risk chemotherapy eligible and 42 of these (91%) were concordantly classified as MP high-risk. MP high-risk cancers included 115 Luminal B and 1 Basal-like cancers, and 64% of these (n=74) had low-risk status by RS. When the MP high category was subdivided into MP 1 (n=105) and MP2 (n=11) subgroups, (35/105) 33% and (7/11) 64% of cases were RS &amp;gt;25, respectively. Black patients had a statistically higher mean index MP score of -0.191 compared to -0.082 for White patients (p=0.02). No statistical difference was noted by race for RS. Conclusions: There was strong concordance (92%) between low-risk MP and low-risk RS. Similar concordance was not identified when comparing chemotherapy eligible high-risk MP (MP1 and MP2) to high-risk ( &amp;gt;25) recurrence scores. Only 36% of chemotherapy eligible MP patients (MP1 and MP2) would be chemotherapy eligible by RS. Higher concordance (58%) for chemotherapy eligibility was seen when limited to the ultra-high (MP2) scores. By contrast most (92%) of chemotherapy eligible patients by RS (&amp;gt;25) were considered high risk by MP (MP1 or MP2). Table1. RS and MP risk categories Citation Format: Rishika Singh, William Barlow, Nupur Singh, James Elliott, Richard Fine, Michael Berry, Erin Cobain, Lajos Pusztai, Gregory Vidal. Comparison of OncotypeDX Recurrence Scores (RS) and MammaPrint (MP) scores, and chemotherapy indications in early-stage Estrogen Receptor positive/HER2 negative (ER-/HER2-) breast cancer [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 PO3-02-04.

Abstract PO5-07-01: A novel clinical risk score that can accurately predict the survival of young breast cancer patients: A UAE-based cohort study

Abstract Introduction: Breast cancer (BC) in women below the age of 40 accounts for approximately 7% of all BC cases. According to studies, BC in younger women is more likely to have negative tumor characteristics and outcomes compared to older women. The rate of early-onset breast cancer in the United Arab Emirates (UAE) is higher than in the Western population (24%, previously reported). Young breast cancer patients in the UAE have worse adverse features, including a higher grade, a larger tumor size, and lymph node involvement, as we reported previously. Therefore, combining several clinical indicators to predict recurrence risk in our unique, heterogeneous young breast cancer group is needed. Aim:The aim of this study is to develop a statistical machine learning model that can predict survival and the risk of recurrence in a young breast cancer population seen and treated in a large-volume tertiary cancer center in the United Arab Emirates (Tawam Hospital). Methods: Early-onset breast cancer patients from a retrospective observational cohort study were included in this study (N = 904). A broad range of clinical data was collected. A multivariate ridge Cox regression model was performed using age, histology, molecular type (ER,PR,HER-2 status), T-stage, N-Stage, M-stage, grade, and BMI, and the interaction term age*BMI at the time of diagnosis. The primary outcome was time-to-death. A novel breast cancer risk score (BCRS) was developed as the linear predictor of the fitted-ridge Cox regression model. Breast cancer patients were categorized into low, medium, and high risk using the 33th and 66th centiles of the novel BCRS. A univariate Cox regression model was performed with a categorized BCRS as a predictor of time-to-death. Hazard ratios (HR) with a 95% confidence interval (95% CI) were estimated. Kaplan-Meier (KM) curves were plotted and compared using the log-rank test. Time-dependent sensitivity and specificity were computed at five- and ten-year follow-ups, respectively. Statistical analyses were performed in R version 4.2.3. Results: The median age was 36 years (IQR: 32–38), and 64% were Arabic. Fifteen percent had an event with a median duration of follow-up of 15.4 years (95% CI: 13.6–17.1). The estimated HR of the categorized novel BCRS in a univariate Cox regression model was 1.968 (95% CI: 1.075- 3.601) and 8.040 (95% CI: 4.695–13.769) for the intermediate and high-risk groups as compared to the low-risk group, respectively. KM curves show a clear separation in terms of survival between the three risk groups, p&amp;lt; 0.0001 (Figure 1). A cutoff value of -1.733 gives a sensitivity of 93.8 and 90.6 with corresponding specificities of 31.42 and 31.31 at five- and ten-year follow-up, respectively. Conclusion: This is the first study in the region that uses clinical data that combines several clinical characteristics and aims to design a statistical machine learning model to predict the risk of death from breast cancer. Our novel model can be used in daily clinical practice to identify high risk breast cancer patients and aid clinical decision-making in patients with breast cancer. However, further validation studies are needed. Figure 1:KM curves of breast-cancer survival for patients with low-risk (BCRS in [-2.32, -1.63], black curve), intermediate-risk (BCRS in [-1.64, -1.25], red curve), and high-risk BCRS in [-1.26, 1.41], green curve). Citation Format: Aydah Al-Awadhi, Mohammed Hourani, Mawada Hussein, Fatima Alkindi, Lina Wahba, Abla AlAgha, Alaa Shoqeir, Mouza AlShebli, Atlal Abusanad, Amar Ahmad. A novel clinical risk score that can accurately predict the survival of young breast cancer patients: A UAE-based cohort study [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 PO5-07-01.