How Time, Living Situation, and Stress Related to Technology Influence User Acceptance and Usability of a Socialization Service for Older Adults and Their Formal and Informal Caregivers: Six-Month Pilot Study.

Background: Considering the growing population of older adults, addressing the influence of loneliness among this demographic group has become imperative, especially due to the link between social isolation and deterioration of mental and physical well-being. Technology has the potential to be used to create innovative solutions to increase socialization and potentially promote healthy aging. Objective: This 6-month study examined the usability and acceptability of a technology-based socialization service and explored how stress and living situation affect older adults' and their ecosystem's perceptions of technology, investigating cross-sectional and longitudinal differences among and across user groups. Methods: Participants were recruited in Tuscany and Apulia (Italy) through a network of social cooperatives and a research hospital, respectively. A total of 20 older adults were provided with the same technology installed on a tablet and on a smart television. The technology has three functionalities: video calling, playing games, and sharing news. Additionally, 20 informal caregivers (IC) and 13 formal caregivers (FC) connected to the older adults were included in the study. After both initial training in the use of the system (T0) and 6 months of using the system (T6), questionnaires on usability, acceptability, and technostress were filled in by older adults, IC, and FC. Nonparametric or parametric tests were conducted to investigate group differences at both time points and changes over time. Additional analyses on older adults were done to assess whether differences in usability and acceptability were related to living situation (ie, alone or with someone). Furthermore, correlation analyses were performed between usability, acceptability, and stress toward technology at T0 and T6. Results: At both T0 and T6, older adults had lower usability scores than IC and FC and higher anxiety than IC. Over time, there was a significant decrease in older adults' attitudes toward technology score, depicting a negative attitude over time (T0 median 4.2, IQR 0.5; T6 median 3.7, IQR 0.8; Cohen d=0.7), while there was no change for IC and FC. At T0, those living alone had lower acceptability than those living with someone but this difference disappeared at T6. People or participants living with someone had a decline in anxiety, attitudes toward technology, enjoyment, and perceived usefulness. Stress toward technology affected usability and acceptability in the older adult group entering the study (ρ=-.85) but this was not observed after 6 months. In the IC group, stress affected trust at T0 (ρ=-.23) but not at T6. Conclusions: At the start of the study, older adults judged the system to be less usable and more stressful than did the caregivers. Indeed, at first, technostress was correlated with usability and acceptability; however, with repeated use, technostress did not influence the perception of technology. Overall, getting accustomed to technology decreased anxiety and stress toward technology.

Metronomic chemotherapy and breast cancer: a critical evaluation of its role in the new landscape of therapeutics.

INTRODUCTION: Breast cancer (BC) remains a prevalent and challenging malignancy among women, with significant advancements in treatment strategies over the past decades. Traditional chemotherapy has been progressively supplemented by newer modalities, including Antibody-Drug Conjugates (ADCs), Immunotherapy (IO), and Targeted Therapies (TT). Despite these advancements, there remains a critical need for strategies that maintain efficacy while minimizing toxicity. AREAS COVERED: This review delves into metronomic chemotherapy (MC), a novel approach involving the frequent administration of low-dose chemotherapy without prolonged breaks. We explore MC's impact across various breast cancer subtypes, such as Estrogen Receptor-Positive (ER+), HER2-Positive, and Triple-Negative Breast Cancer (TNBC). The literature reviewed highlights MC's mechanisms, including its anti-angiogenic, immunomodulatory, and antiproliferative effects, and its potential to improve treatment tolerability and address drug resistance. EXPERT OPINION: MC represents a promising adjunct to existing therapies, particularly in advanced or resistant cases. Its unique dosing schedule could offer sustained antitumor activity with reduced toxicity, making it a viable option for long-term management. However, further research is warranted to establish optimal dosing regimens, identify predictive biomarkers, and delineate its role within combination treatment strategies. Clarifying these aspects could refine MC's application, potentially reshaping treatment paradigms and enhancing patient outcomes in breast cancer management.

Artificial intelligence: A new tool in the pathologist's armamentarium for the diagnosis of IBD.

Inflammatory bowel diseases (IBD) are classified into two entities, namely Crohn's disease (CD) and ulcerative colitis (UC), which differ in disease trajectories, genetics, epidemiological, clinical, endoscopic, and histopathological aspects. As no single golden standard modality for diagnosing IBD exists, the differential diagnosis among UC, CD, and non-IBD involves a multidisciplinary approach, considering professional groups that include gastroenterologists, endoscopists, radiologists, and pathologists. In this context, histological examination of endoscopic or surgical specimens plays a fundamental role. Nevertheless, in differentiating IBD from non-IBD colitis, the histopathological evaluation of the morphological lesions is limited by sampling and subjective human judgment, leading to potential diagnostic discrepancies. To overcome these limitations, artificial intelligence (AI) techniques are emerging to enable automated analysis of medical images with advantages in accuracy, precision, and speed of investigation, increasing interest in the histological analysis of gastrointestinal inflammation. This review aims to provide an overview of the most recent knowledge and advances in AI methods, summarizing its applications in the histopathological analysis of endoscopic biopsies from IBD patients, and discussing its strengths and limitations in daily clinical practice.

Synergizing Immunotherapy and Antibody-Drug Conjugates: New Horizons in Breast Cancer Therapy.

The advent of immunotherapy and antibody-drug conjugates (ADCs) have revolutionized breast cancer treatment, offering new hope to patients. However, challenges, such as resistance and limited efficacy in certain cases, remain. Recently, the combination of these therapies has emerged as a promising approach to address these challenges. ADCs play a crucial role by delivering cytotoxic agents directly to breast cancer cells, minimizing damage to healthy tissue and enhancing the tumor-killing effect. Concurrently, immunotherapies harness the body's immune system to recognize and eliminate cancer cells. This integration offers potential to overcome resistance mechanisms and significantly improve therapeutic outcomes. This review explores the rationale behind combining immunotherapies with ADCs, recent advances in this field, and the potential implications for breast cancer treatment.

Therapeutic inhibition of isocitrate dehydrogenase mutations in glioma and cholangiocarcinoma: new insights and promises-a narrative review.

BACKGROUND AND OBJECTIVE: The identification of mutation hot spots in the isocitrate dehydrogenase (IDH) genes is one of the most important cancer genome-wide sequencing discoveries with relevant impact in the treatment of some orphan tumors. These genes were mostly found mutated in lower-grade gliomas (LGGs), acute myeloid leukaemia (AML), myelodysplastic syndromes (MDS) and myeloproliferative neoplasms (MPNs) and in cholangiocarcinoma. This aberrant genomic condition represents a therapeutic target of great interest in cancer research, especially in AML, given the limitations of currently approved therapies in this field. In this review, we investigate the role of IDH mutation and the mutant IDH (mIDH)- targeted therapies for cholangiocarcinoma and glioma. METHODS: Here, we provide an overview of the IDH mutation role and discuss its role in tumorigenesis and progression of some solid cancers, in which the therapeutic strategy can be completely changed thanks to these brand-new therapeutic options. KEY CONTENT AND FINDINGS: The encouraging early clinical data demonstrated to be a proof of concept for investigational mIDH1/2 inhibitors in tumors with a paucity of therapeutic possibilities. CONCLUSIONS: Moreover, we list the most important randomised clinical trials still active with their preliminary results.

Inflammatory bowel disease genomics, transcriptomics, proteomics and metagenomics meet artificial intelligence.

Various extrinsic and intrinsic factors such as drug exposures, antibiotic treatments, smoking, lifestyle, genetics, immune responses, and the gut microbiome characterize ulcerative colitis and Crohn's disease, collectively called inflammatory bowel disease (IBD). All these factors contribute to the complexity and heterogeneity of the disease etiology and pathogenesis leading to major challenges for the scientific community in improving management, medical treatments, genetic risk, and exposome impact. Understanding the interaction(s) among these factors and their effects on the immune system in IBD patients has prompted advances in multi-omics research, the development of new tools as part of system biology, and more recently, artificial intelligence (AI) approaches. These innovative approaches, supported by the availability of big data and large volumes of digital medical datasets, hold promise in better understanding the natural histories, predictors of disease development, severity, complications and treatment outcomes in complex diseases, providing decision support to doctors, and promising to bring us closer to the realization of the "precision medicine" paradigm. This review aims to provide an overview of current IBD omics based on both individual (genomics, transcriptomics, proteomics, metagenomics) and multi-omics levels, highlighting how AI can facilitate the integration of heterogeneous data to summarize our current understanding of the disease and to identify current gaps in knowledge to inform upcoming research in this field.

The Role of HL7 FHIR in the European Project GATEKEEPER.

The European Project GATEKEEPER aims to develop a platform and marketplace to ensure a healthier independent life for the aging population. In this platform the role of HL7 FHIR is to provide a shared logical data model to collect data in heterogeneous living, which can be used by AI Service and the Gatekeeper HL7 FHIR Implementation Guide was created for this purpose. Independent pilots used this IG and illustrate the impact of the approach, benefit, value, and scalability.

The Role of Coherent Robot Behavior and Embodiment in Emotion Perception and Recognition During Human-Robot Interaction: Experimental Study.

BACKGROUND: Social robots are becoming increasingly important as companions in our daily lives. Consequently, humans expect to interact with them using the same mental models applied to human-human interactions, including the use of cospeech gestures. Research efforts have been devoted to understanding users' needs and developing robot's behavioral models that can perceive the user state and properly plan a reaction. Despite the efforts made, some challenges regarding the effect of robot embodiment and behavior in the perception of emotions remain open. OBJECTIVE: The aim of this study is dual. First, it aims to assess the role of the robot's cospeech gestures and embodiment in the user's perceived emotions in terms of valence (stimulus pleasantness), arousal (intensity of evoked emotion), and dominance (degree of control exerted by the stimulus). Second, it aims to evaluate the robot's accuracy in identifying positive, negative, and neutral emotions displayed by interacting humans using 3 supervised machine learning algorithms: support vector machine, random forest, and K-nearest neighbor. METHODS: Pepper robot was used to elicit the 3 emotions in humans using a set of 60 images retrieved from a standardized database. In particular, 2 experimental conditions for emotion elicitation were performed with Pepper robot: with a static behavior or with a robot that expresses coherent (COH) cospeech behavior. Furthermore, to evaluate the role of the robot embodiment, the third elicitation was performed by asking the participant to interact with a PC, where a graphical interface showed the same images. Each participant was requested to undergo only 1 of the 3 experimental conditions. RESULTS: A total of 60 participants were recruited for this study, 20 for each experimental condition for a total of 3600 interactions. The results showed significant differences (P<.05) in valence, arousal, and dominance when stimulated with the Pepper robot behaving COH with respect to the PC condition, thus underlying the importance of the robot's nonverbal communication and embodiment. A higher valence score was obtained for the elicitation of the robot (COH and robot with static behavior) with respect to the PC. For emotion recognition, the K-nearest neighbor classifiers achieved the best accuracy results. In particular, the COH modality achieved the highest level of accuracy (0.97) when compared with the static behavior and PC elicitations (0.88 and 0.94, respectively). CONCLUSIONS: The results suggest that the use of multimodal communication channels, such as cospeech and visual channels, as in the COH modality, may improve the recognition accuracy of the user's emotional state and can reinforce the perceived emotion. Future studies should investigate the effect of age, culture, and cognitive profile on the emotion perception and recognition going beyond the limitation of this work.

Stay cognitively and socially active with me: a six-month study of a socialization service.

50% of older adults over 60 years old are experiencing social isolation. Assistive technology can provide solutions that promote the connection with their families and other stakeholders. In this context, this paper presents a pilot study of a socialization service with 3 functions tested by 10 older adults and 10 informal caregivers. After a short training, participants were requested to use the system in their daily life for six months. At the beginning (T0) and at the end (T6) of the trial, qualitative structured questionnaires were addressed to investigate training, usability, acceptance (i.e. trust, anxiety, facilitating condition, enjoyment, and attitude), and user experience. Collected results underline good training, good usability of the system (SUS>68), and user experience for both groups. Furthermore, the values associated with acceptance domains are higher than 3.5 for intention to use and trust, at the end of the tests. We can observe a decreasing trend in stress associated with technology use. Informal caregivers have a higher evaluation of the system novelty with respect to older adults. Overall, qualitative feedback collected remarked the good impression of this service among the study's participants. Finally, this study represents a promising starting point for better investigating technology-based services that can improve the quality of life of older people living alone providing them with tools that can decrease their social isolation.Clinical Relevance- The results suggest the potential use of this type of service for promoting socialization among older adults thus reducing their loneliness.

Reirradiation with radiosurgery or stereotactic fractionated radiotherapy in association with regorafenib in recurrent glioblastoma.

PURPOSE: No standard treatment has yet been established for recurrent glioblastoma (GBM). In this context, the aim of the current study was to evaluate safety and efficacy of reirradiation (re-RT) by radiosurgery or fractionated stereotactic radiotherapy (SRS/FSRT) in association with regorafenib. METHODS: Patients with a histological or radiological diagnosis of recurrent GBM who received re-RT by SRS/FSRT and regorafenib as second-line systemic therapy were included in the analysis. RESULTS: From January 2020 to December 2022, 21 patients were evaluated. The median time between primary/adjuvant RT and disease recurrence was 8 months (range 5-20). Median re-RT dose was 24 Gy (range 18-36 Gy) for a median number of 5 fractions (range 1-6). Median regorafenib treatment duration was 12 weeks (range 3-26). Re-RT was administered before starting regorafenib or in the week off regorafenib during the course of chemotherapy. The median and the 6­month overall survival (OS) from recurrence were 8.4 months (95% confidence interval [CI] 6.9-12.7 months) and 75% (95% CI 50.9-89.1%), respectively. The median progression-free survival (PFS) from recurrence was 6 months (95% CI 3.7-8.5 months). The most frequent side effects were asthenia that occurred in 10 patients (8 cases of grade 2 and 2 cases of grade 3), and hand-foot skin reaction (2 patients grade 3, 3 patients grade 2). Adverse events led to permanent regorafenib discontinuation in 2 cases, while in 5/21 cases (23.8%), a dose reduction was administered. One patient experienced dehiscence of the surgical wound after reintervention and during regorafenib treatment, while another patient reported intestinal perforation that required hospitalization. CONCLUSION: For recurrent GBM, re-RT with SRT/FSRT plus regorafenib is a safe treatment. Prospective trials are necessary.

Design and Adoption of a FHIR IG to Support a Telemonitoring Environment in Gatekeeper Project.

Telemedicine can provide benefits in patient affected by chronic diseases or elderly citizens as part of standard routine care supported by digital health. The GATEKEEPER (GK) Project was financed to create a vendor independent platform to be adopted in medical practice and to demonstrate its effect, benefit value, and scalability in 8 connected medical use cases with some independent pilots. This paper, after a description of the GK platform architecture, is focused on the creation of a FHIR (Fast Healthcare Interoperability Resource) IG (Implementation Guide) and its adoption in specific use cases. The final aim is to combine conventional data, collected in the hospital, with unconventional data, coming from wearable devices, to exploit artificial intelligence (AI) models designed to evaluate the effectiveness of a new parsimonious risk prediction model for Type 2 diabetes (T2D).

Assessing Feasibility of Cognitive Impairment Testing Using Social Robotic Technology Augmented with Affective Computing and Emotional State Detection Systems.

Social robots represent a valid opportunity to manage the diagnosis, treatment, care, and support of older people with dementia. The aim of this study is to validate the Mini-Mental State Examination (MMSE) test administered by the Pepper robot equipped with systems to detect psychophysical and emotional states in older patients. Our main result is that the Pepper robot is capable of administering the MMSE and that cognitive status is not a determinant in the effective use of a social robot. People with mild cognitive impairment appreciate the robot, as it interacts with them. Acceptability does not relate strictly to the user experience, but the willingness to interact with the robot is an important variable for engagement. We demonstrate the feasibility of a novel approach that, in the future, could lead to more natural human-machine interaction when delivering cognitive tests with the aid of a social robot and a Computational Psychophysiology Module (CPM).

Evaluating the Use of a Robot in a Hematological Intensive Care Unit: A Pilot Study.

The aim of the SYRIACA project was to test the capability of a social robot to perform specific tasks in healthcare settings, reducing infection risks for patients and caregivers. The robot was piloted in an Intensive Hematological Unit, where the patients' and healthcare operators' acceptability of the robot was evaluated. The robot's functions, including logistics, surveillance, entertainment, and remote visits, were well accepted. Patients expressed interest in having multiple interactions with the robot, which testifies to its engaging potential and that it provides useful services. During remote visits, the robot reduced perceived stress among patients, alleviating feelings of isolation. The successful implementation of the robot suggests its potential to enhance safety and well-being in healthcare settings.

A New Risk Prediction Model for Venous Thromboembolism and Death in Ambulatory Lung Cancer Patients.

(1) Background: Venous thromboembolism (VTE) is a frequent complication in ambulatory lung cancer patients during chemotherapy and is associated with increased mortality. (2) Methods: We analyzed 568 newly diagnosed metastatic lung cancer patients prospectively enrolled in the HYPERCAN study. Blood samples collected before chemotherapy were tested for thrombin generation (TG) and a panel of hemostatic biomarkers. The Khorana risk score (KRS), new-Vienna CATS, PROTECHT, and CONKO risk assessment models (RAMs) were applied. (3) Results: Within 6 months, the cumulative incidences of VTE and mortality were 12% and 29%, respectively. Patients with VTE showed significantly increased levels of D-dimer, FVIII, prothrombin fragment 1 + 2, and TG. D-dimer and ECOG performance status were identified as independent risk factors for VTE and mortality by multivariable analysis and utilized to generate a risk score that provided a cumulative incidence of VTE of 6% vs. 25%, death of 19% vs. 55%, and in the low- vs. high-risk group, respectively (p < 0.001). While all published RAMs significantly stratified patients for risk of death, only the CATS and CONKO were able to stratify patients for VTE. (4) Conclusions: A new prediction model was generated to stratify lung cancer patients for VTE and mortality risk, where other published RAMs failed.

The Treatment Landscape of Elderly Patients with Hormone Receptor-Positive Her2 Negative Advanced Breast Cancer: Current Perspectives and Future Directions.

Breast cancer (BC) in elderly women is an increasing health issue due to demographic changes. BC tends to present later and may receive less than standard treatment options. More often, BC in elderly patients is endocrine-positive (HR+). The treatment of elderly patients with metastatic BC (mBC) represents a therapeutic challenge. In recent years, the treatment landscape of patients that are HR+/Her2-negative has changed due to the introduction in clinical practice of new targeted drugs, which have improved patient outcomes. Elderly patients are a small percentage of all patients enrolled in clinical trials and, to date, there are no standardized guidelines that define the best treatment option for this patient population. This can lead to undertreatment or overtreatment, impacting patient morbidity and mortality. Geriatric Assessment tools to tailor the treatment in elderly patients are underused because they are long and difficult to apply in a busy routine clinical practice. For all these reasons, there is an urgent need to produce data about the best treatment for elderly patients with HR+ mBC. Herein, we report data from randomized clinical trials and real-world evidence on the therapeutic options for HR+ Her2-negative mBC elderly patients and explore future treatment directions.

Experience from the Development of HL7 FHIR IG for Gatekeeper Project.

The GATEKEEPER (GK) Project was financed by the European Commission to develop a platform and marketplace to share and match ideas, technologies, user needs and processes to ensure a healthier independent life for the aging population connecting all the actors involved in the care circle. In this paper, the GK platform architecture is presented focusing on the role of HL7 FHIR to provide a shared logical data model to be explored in heterogeneous daily living environments. GK pilots are used to illustrate the impact of the approach, benefit value, and scalability, suggesting ways to further accelerate progress.

Immunotherapy in Prostate Cancer: State of Art and New Therapeutic Perspectives.

Prostate cancer (PC) is the most common type of tumor in men. In the early stage of the disease, it is sensitive to androgen deprivation therapy. In patients with metastatic castration-sensitive prostate cancer (mHSPC), chemotherapy and second-generation androgen receptor therapy have led to increased survival. However, despite advances in the management of mHSPC, castration resistance is unavoidable and many patients develop metastatic castration-resistant disease (mCRPC). In the past few decades, immunotherapy has dramatically changed the oncology landscape and has increased the survival rate of many types of cancer. However, immunotherapy in prostate cancer has not yet given the revolutionary results it has in other types of tumors. Research into new treatments is very important for patients with mCRPC because of its poor prognosis. In this review, we focus on the reasons for the apparent intrinsic resistance of prostate cancer to immunotherapy, the possibilities for overcoming this resistance, and the clinical evidence and new therapeutic perspectives regarding immunotherapy in prostate cancer with a look toward the future.

GATEKEEPER's Strategy for the Multinational Large-Scale Piloting of an eHealth Platform: Tutorial on How to Identify Relevant Settings and Use Cases.

BACKGROUND: The World Health Organization's strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. OBJECTIVE: We aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. METHODS: The selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. RESULTS: Seven European countries were selected, covering Europe's geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence-based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. CONCLUSIONS: This paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space.

Advances in pharmacotherapies that target the cell cycle for treatment of breast cancer: where are we at today?

INTRODUCTION: Advances in pharmacotherapies that target cell cycle in breast cancer have transformed the therapeutic armamentarium of breast oncology leading to the approval of CDK4/6 inhibitors plus endocrine therapy as the upfront treatment in the HR+/HER2- metastatic setting. The current challenge is to evaluate the efficacy of these drugs in the early setting. The current challenge is to evaluate the efficacy of these drugs in the early setting. Research is also making progress for other breast cancer subtypes (triple negative and HER 2+ breast cancer). AREAS COVERED: The aim of this review is to summarize the recent therapeutic updates regarding the efficacy of CDK4/6 inhibitors in the metastatic and early setting for the treatment of HR+/HER2- breast cancer. The review also presents data regarding the clinical role of CDK4/6 inhibitors in HER2+, triple negative breast cancer, and on therapeutic sequences in resistant tumors. A comprehensive search for the literature was conducted using MEDLINE, ASCO, ESMO, and SABCS databases. EXPERT OPINION: The therapeutic paradigm of breast cancer involving CDK4/6 inhibitors presents some still open discussion points. Further evidence regarding the best treatment strategy in HR+ HER2- metastatic breast cancer and the efficacy of CDK 4/6is in the early stage will be necessary in the next future. Predictive biomarkers of response or resistance need to be validated.

Utility of the Khorana and the new-Vienna CATS prediction scores in cancer patients of the HYPERCAN cohort.

BACKGROUND: Risk assessment models (RAMs) are relevant approaches to identify cancer outpatients at high risk of venous thromboembolism (VTE). Among the proposed RAMs, the Khorana (KRS) and the new-Vienna CATS risk scores have been externally validated in ambulatory patients with cancer. OBJECTIVES: To test KRS and new-Vienna CATS scores in 6-month VTE prediction and mortality in a large prospective cohort of metastatic cancer outpatients during chemotherapy. PATIENTS/METHODS: Newly diagnosed patients with metastatic non-small cell lung, colorectal, gastric, or breast cancers were analyzed (n = 1286). The cumulative incidence of objectively confirmed VTE was estimated with death as a competing risk and multivariate Fine and Gray regression. RESULTS: Within 6 months, 120 VTE events (9.7%) occurred. The KRS and the new-Vienna CATS scores showed comparable c-stat. Stratification by KRS provided VTE cumulative incidences of 6.2%, 11.4%, and 11.5% in the low-, intermediate-, and high-risk categories, respectively (p = ns), and of 8.5% vs. 11.8% (p = ns) in the low- vs. high-risk group by the single 2-point cut-off value stratification. Using a pre-defined 60-point cut-off by the new-Vienna CATS score, 6.6% and 12.2% cumulative incidences were obtained in the low- and high-risk groups, respectively (p < 0.001). Furthermore, having a KRS ≥2 = or a new-Vienna CATS score >60 points was also an independent risk factor for mortality. CONCLUSION: In our cohort, the 2 RAMs showed a comparable discriminating potential; however, after the application of cut-off values, the new-Vienna CATS score provided statistically significant stratification for VTE. Both RAMs proved to be effective in identifying patients at increased risk of mortality.