Citations

e18807 Background: CUP represents both a diagnostic and a management challenge. Despite improvements through sophisticated imaging modalities, specific and sensitive testing using immunohistochemistry, a concrete determination of the site of origin of the primary tumor can still be a diagnostic challenge Hereby, we described the genomic landscape of patients with CUP treated at our institution. Methods: Retrospective study of patients with CUP treated at Mayo Clinic Rochester MN from 2010 to 2021. Next generation sequencing (NGS) information was abstracted, and alterations were ranked into different levels of actionability following the Onco KB framework. All data were analyzed by the SPSS version 22.0 software (SPSS, Chicago, IL, United States). Results: From a total of 214 patients, we identified 67 (32%) patients in whom NGS was performed. Among patients with available NGS the median age was 64 years (range: 35-86) and 51% were female. the most prevalent histology included adenocarcinoma (39%), carcinoma NOS (31%), and neuroendocrine tumors (12%). NGS on tumor (t-NGS) was available in 56 (84 %) patients, circulating tumor NGS (b-NGS) was available in 12 (18%) patients, and only 1 patient had both testing available. Among the 56 patients with available t-NGS, MSI-high was detected in 9 patients, whereas among the 12 patients with available b-NGS, MSI-high was detected in 8 patients; yielding an MSI-high detection rate of 16% and 67% for t-NGS and b-NGS. In this cohort, there were a total of 474 genomic alterations detected from which 103 (22 %) were able to be ranked into one therapeutic level following the OncoKB framework. Genomic alterations were most observed among patients with carcinoma (n = 50, 48.53%) adenocarcinoma (n = 33, 32.03 %), squamous cell carcinoma (n = 3, 2.91 %) and neuroendocrine tumor (n = 2, 1.94%). Following the OncoKB framework, 39-level 1 genomic alterations were detected in a total of 14 genes. The most common level 1 genomic alterations comprised the BRCA2 (20.51%), NF1 ATM (17.95%) and HER2/NEU (ERBB2) (15.38%) genes. Therapeutic level 2 included 51 genomic alterations in 13 genes of which KRAS (17.65%), BRAF (15.69%), and BRCA2 (15.69%) were the most prevalent mutated genes. Additionally, level R comprised 13 genomic alterations in the following genes: KRAS (69.23) NRAS (23.08%) and PDGFRA (7.69%). Conclusions: CUP are malignancies rich in potentially actionable alterations, and NGS of tissue and blood samples can inform systemic therapy decisions. Alteration-specific targeted therapy may be an option for a substantial proportion of patients. NGS of tumor tissue or blood should be considered for all patients with CUP.

e18803 Background: CUPs are a heterogeneous group of metastatic cancers for which a standardized diagnostic work-up fails to identify the site of origin at the time of diagnosis. CUP accounts for 3%-5% of all cancer diagnoses worldwide, and the natural history of patient with CUP differs from that of patients (pts) with cancer with known primary tumor. Here we report and summarize the clinical features of patients with CUP treated at Mayo Clinic. Methods: Retrospective study of patients treated at Mayo Clinic Rochester MN from 2010 to 2021. Patient demographics, tumor-related variables, treatment-related variables, and clinical data were extracted. Descriptive statistics were used, and all data were analyzed by the SPSS version 22.0 software (SPSS, Chicago, IL, United States). Results: From a total of 214 pts, 207 pts were included, as primary tumor site was identified in 7 patients after initial evaluation. The pts in this study were predominantly white (87%) of female (50.2%) gender with a mean age of 63 (SD: 13) without history of smoking (51%) and either private or public insurance (82.6%). The predominant histology was adenocarcinoma (30%), followed by neuroendocrine neoplasms (27%), and carcinoma NOS (not otherwise specified) (25%). The most prevalent grade in this cohort was grade III with poorly differentiated tumor cells. All pts had diagnostic imaging and the most used imaging modalities included CT (81.2%), and PET-CT (43.5%). In our cohort, the 3 most common sites of metastases included lymph nodes (57.5%), liver (37.8%), lung (34.3%), and bone (23.7%); and in 64% of pts, there was a specific presentation pattern including liver-predominant (24.6%), lymph node-predominant (24.6%), bone-predominant (7.7%), and peritoneal carcinomatosis (7.7%). The majority of pts received systemic therapy (69%) as first line of therapy and the most frequent first line regimens included platinum-doublet (26.5%), gemcitabine-based regimen (20.7%), 5FU-based regimens (18%) and somatostatin analogs (16.7%); whereas salvage radiation and ablation were offered to 11% of pts and surgery to 17%. The median follow-up time was 22 months (IQR: 45) with a median survival time of 23 months and the 3-year cumulative survival rate was 30%. Conclusions: The heterogenous nature of CUPs and lack of specific immunohistochemical signature prevents primary tissue of origin diagnoses in CUP pts. Without the identification of a primary origin site, treatment is restricted to generic chemotherapy with limited benefit as demonstrated in this cohort.

e18802 Background: CUP is a rare cancer with an incidence of 7–12 cases per 100,000/year. CUP is defined as metastatic cancer with no identifiable primary tumor despite comprehensive evaluation. Despite its heterogeneous clinicopathological presentation, the treatment of CUP has primarily been with platinum-based combination chemotherapies but results are poor and survival is short. Here, we describe survival outcomes in real-world dataset of patients with CUP seen at a tertiary referral center. Methods: Retrospective study of patients treated at Mayo Clinic, Rochester MN, from 2010 to 2021. Survival probabilities were estimated with the Kaplan-Meier method. We used Cox proportional hazard regression with forward modeling to explore the association between each variable and death. Overall survival (OS) analysis was conducted in the entire cohort, and it was stratified by histological subtype. For the hypothesis test, we considered p < 0.05 to be statistically significant; all tests were two-sided. All data were analyzed by the SPSS version 22.0 software (SPSS, Chicago, IL, United States). Results: From a total of 214 patients, 198 patients were included in the survival analysis. The patients were predominantly white (87%), female (50.2%), with a mean age of 63 (SD: 13) without history of smoking (51%). The predominant histology was adenocarcinoma (30%), followed by neuroendocrine neoplasms (NEN) (27%), carcinoma NOS (25%), squamous cell carcinoma (SCC) (10%) and non-classifiable tumors (7%). The median follow-up time was 23 months, and medial OS was 23 months in the entire cohort. OS by histology was as follows: 51 months for NEN, 34 months for SCC, 18 months for carcinomas NOS and 11 months for adenocarcinomas (p < 0.001) (fig.1). Similar OS trends were observed when we restricted the analysis to poorly differentiated tumors. The 3- and 5-year cumulative survival by histology were as follows: 7% and 0% for adenocarcinoma, 25% and 8% for carcinoma NOS, 39% and 17% for SCC, and 56% and 22% for NEN. In Cox regression models we did not identify any prognostic factors among patients with adenocarcinoma. Conclusions: Patients with adenocarcinoma of unknown primary possess a considerable challenge and the OS is short. CUP of other histologies have higher OS. This study highlights the need of accurate tumor identification and better treatment, perhaps as a multiomics therapeutic approach.

Pain assessment is a complex task largely dependent on the patient’s self-report. Artificial intelligence (AI) has emerged as a promising tool for automating and objectifying pain assessment through the identification of pain-related facial expressions. However, the capabilities and potential of AI in clinical settings are still largely unknown to many medical professionals. In this literature review, we present a conceptual understanding of the application of AI to detect pain through facial expressions. We provide an overview of the current state of the art as well as the technical foundations of AI/ML techniques used in pain detection. We highlight the ethical challenges and the limitations associated with the use of AI in pain detection, such as the scarcity of databases, confounding factors, and medical conditions that affect the shape and mobility of the face. The review also highlights the potential impact of AI on pain assessment in clinical practice and lays the groundwork for further study in this area.

Pain is a complex and subjective experience, and traditional methods of pain assessment can be limited by factors such as self-report bias and observer variability. Voice is frequently used to evaluate pain, occasionally in conjunction with other behaviors such as facial gestures. Compared to facial emotions, there is less available evidence linking pain with voice. This literature review synthesizes the current state of research on the use of voice recognition and voice analysis for pain detection in adults, with a specific focus on the role of artificial intelligence (AI) and machine learning (ML) techniques. We describe the previous works on pain recognition using voice and highlight the different approaches to voice as a tool for pain detection, such as a human effect or biosignal. Overall, studies have shown that AI-based voice analysis can be an effective tool for pain detection in adult patients with various types of pain, including chronic and acute pain. We highlight the high accuracy of the ML-based approaches used in studies and their limitations in terms of generalizability due to factors such as the nature of the pain and patient population characteristics. However, there are still potential challenges, such as the need for large datasets and the risk of bias in training models, which warrant further research.

Unnecessary ED visits and transfers to hand clinics raise treatment costs and patient burden at trauma centers. In the present COVID-19 pandemic, needless transfers can increase patients’ risk of viral exposure. Therefore, this review analyzes different aspects of the remote diagnosis and triage of traumatic hand injuries. The most common file was photography, with the most common devices being cell phone cameras. Treatment, triage, diagnosis, cost, and time outcomes were assessed, showing concordance between teleconsultation and face-to-face patient evaluations. We conclude that photography and video consultations are feasible surrogates for ED visits in patients with traumatic hand injuries. These technologies should be leveraged to decrease treatment costs and potentially decrease the time to definitive treatment after initial evaluation.

Background Demographic characteristics are known to influence the treatment and outcomes of patients with invasive melanoma. Whether these characteristics influence treatment costs is unknown. We aimed to analyze whether patient demographics and tumor characteristics influence treatment costs for patients with invasive cutaneous melanoma in Florida. Methods This was a cross-sectional study in which the Florida Inpatient and Outpatient Dataset of the Agency for Health Care Administration was analyzed for patients with a diagnosis of invasive melanoma between January 1, 2013 and December 31, 2018. Categorical variables were assessed using Pearson χ2 tests, and continuous variables were evaluated using Kruskal-Wallis tests. Logistic regression analysis was conducted to identify the association between patient demographics and total costs. All analyses were done using SAS 9.4 statistical software (SAS Institute, Inc). Results Multivariate analysis showed that sex (P < 0.001), hospital setting (P < 0.001), race/ethnicity (P < 0.01), patient region (P < 0.01), Elixhauser Comorbidity Index score (P < 0.001), presence of metastasis (P < 0.01), total number of procedures (P < 0.001), and length of stay (P < 0.001) were correlated with the cost of treatment of invasive cutaneous melanoma. After stratification, the association between cost and race/ethnicity disappeared for inpatients but remained for Black patients in the outpatient setting (P < 0.001). The association between cost and patient residence regions also differed when the cohort was stratified. Conclusions Strategies addressing disparities in treatment cost of invasive melanoma should differ, depending on the hospital setting where the patient is being treated.

Study Design Human bone marrow stem cells (hBMSCs) and human adipose-derived stem cells (hADSCs) have demonstrated the capability to regenerate bone once they have differentiated into osteoblasts. Objective This systematic review aimed to evaluate the in vitro osteogenic differentiation potential of these cells when seeded in a poly (lactic- co-glycolic) acid (PLGA) scaffold. Methods A literature search of 4 databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted in January 2021 for studies evaluating the osteogenic differentiation potential of hBMSCs and hADSCs seeded in a PLGA scaffold. Only in vitro models were included. Studies in languages other than English were excluded. Results A total of 257 studies were identified after the removal of duplicates. Seven articles fulfilled our inclusion and exclusion criteria. Four of these reviews used hADSCs and three used hBMSCs in the scaffold. Upregulation in osteogenic gene expression was seen in all the cells seeded in a 3-dimensional scaffold compared with 2-dimensional films. High angiogenic gene expression was found in hADSCs. Addition of inorganic material to the scaffold material affected cell performance. Conclusions Viability, proliferation, and differentiation of cells strongly depend on the environment where they grow. There are several factors that can enhance the differentiation capacity of stem cells. A PLGA scaffold proved to be a biocompatible material capable of boosting the osteogenic differentiation potential and mineralization capacity in hBMSCs and hADSCs.

In the US, at least one fall occurs in at least 28.7% of community-dwelling seniors 65 and older each year. Falls had medical costs of USD 51 billion in 2015 and are projected to reach USD 100 billion by 2030. This review aims to discuss the extent of smartphone (SP) usage in fall detection and prevention across a range of care settings. A computerized search was conducted on six electronic databases to investigate the use of remote sensing technology, wireless technology, and other related MeSH terms for detecting and preventing falls. After applying inclusion and exclusion criteria, 44 studies were included. Most of the studies targeted detecting falls, two focused on detecting and preventing falls, and one only looked at preventing falls. Accelerometers were employed in all the experiments for the detection and/or prevention of falls. The most frequent course of action following a fall event was an alarm to the guardian. Numerous studies investigated in this research used accelerometer data analysis, machine learning, and data from previous falls to devise a boundary and increase detection accuracy. SP was found to have potential as a fall detection system but is not widely implemented. Technology-based applications are being developed to protect at-risk individuals from falls, with the objective of providing more effective and efficient interventions than traditional means. Successful healthcare technology implementation requires cooperation between engineers, clinicians, and administrators.

In July 2020, Mayo Clinic introduced a hospital-at-home program, known as Advanced Care at Home (ACH) as an alternate option for clinically stable medical patients requiring hospital-level care. This retrospective cohort study evaluates the impact of the addition of a dedicated ACH patient acquisition Advanced Practice Provider (APP) on average length of stay (ALOS) and the number of patients admitted into the program between in Florida and Wisconsin between 6 July 2020 and 31 January 2022. Patient volumes and ALOS of 755 patients were analyzed between the two sites both before and after a dedicated acquisition APP was added to the Florida site on 1 June 2021. The addition of a dedicated acquisition APP did not affect the length of time a patient was in the emergency department or hospital ward prior to ACH transition (2.91 days [Florida] vs. 2.59 days [Wisconsin], p = 0.22), the transition time between initiation of the ACH consult to patient transfer home (0.85 days [Florida] vs. 1.16 days [Wisconsin], p = 0.28), or the total ALOS (6.63 days [Florida] vs. 6.34 days [Wisconsin], p = 0.47). The average number of patients acquired monthly was significantly increased in Florida (38.3 patients per month) compared with Wisconsin (21.6 patients per month) (p < 0.01). The addition of a dedicated patient acquisition APP resulted in significantly higher patient volumes but did not affect transition time or ALOS. Other hospital-at-home programs may consider the addition of an acquisition APP to maximize patient volumes.