Personalized Patient Care Research Articles

Abstract 2033: Assessment of human reference genomes on cancer somatic mutation detection in tumor-normal paired reference samples using whole genome short-read sequencing data

Abstract A typical cancer somatic mutation identification workflow involves using a standard human reference genome for aligning the sequencing reads and annotating the uncovered somatic variants. The completeness and the correctness of the reference genome, and the haplotype representations may all impact the sequencing read alignments and subsequent somatic variant identifications. However, the exact impacts of the underlying references being used on somatic mutation analysis has not been investigated. In this study, we selected 3 human reference genomes, including GRCh38, T2TCHM13, and a personalized genome (PG) that was derived from a normal cell line, and 12 tumor normal paired replicates of Illumina short read sequencing data for the HCC1395 breast cancer cell line and a matched normal cell line, and aim to illustrate and quantify the effects of the reference genomes on the accuracy of somatic SNV/SV mutation detection using various somatic variant callers. Our analysis shows that the use of a personalized haplotype-specific genome assembly, rather than an unrelated genome such as GRCh38 or T2TCHM13 as a reference, not only improves read alignments for short-read sequencing data but also ameliorates the detection accuracy of somatic SNVs and SVs. While most somatic mutation calls are identical or equivalent, we identify GRCh38 and T2TCHM13 specific somatic mutations that may need to be avoided for further pursuit of incorrect treatment options. We uncover novel somatic mutations only when personalized genome assembly is used as a reference, some of which overlap with genes involving with pathways related to cancer invasion and metastasis (e.g., CDH23, ST14 etc.). The predicted somatic SVs are found more precise. Such results may provide additional interventional target choices for patients, researchers or clinicians, and physicians to look into further for personalized patient care. Citation Format: Chunlin Xiao, Valerie Schneider. Assessment of human reference genomes on cancer somatic mutation detection in tumor-normal paired reference samples using whole genome short-read sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2033.

56 Using machine learning to predict 30-day readmission and reoperation following resection of supratentorial high-grade gliomas: A national analysis of 9,418 patients.

OBJECTIVES/GOALS: High-grade gliomas (HGG) are among the rarest, most aggressive tumors in neurosurgical practice. We aimed to identify the clinical predictors for 30-day readmission and reoperation following HGGs surgery using the NSQIP database and seek to create web-based applications predicting each outcome. METHODS/STUDY POPULATION: We conducted a retrospective, multicenter cohort analysis of patients who underwent resection of supratentorial HGG between January 1, 2016, and December 31, 2020, using the NSQIP database. Demographics and comorbidities were extracted. The primary outcomes were 30-day unplanned readmission and reoperation. A stratified 80:20 split of the available data was carried out. Supervised machine learning algorithms were trained to predict 30-day outcomes. RESULTS/ANTICIPATED RESULTS: A total of 9,418 patients were included in our cohort. The rate of unplanned readmission within 30 days of surgery was 14.9%.Weight, chronic steroid use, pre-operative BUN, and WBC count were associated with a higher risk of readmission. The rate of early unplanned reoperation was 5.47%. Increased weight, higher operative time, and a longer period between hospital admission and the operation were linked to increased risk of early reoperation. Our Random Forest algorithm showed the highest predictive performance for early readmission (AUC = 0.967), while the XG Boost algorithm showed the highest predictive performance for early reoperation (AUC = 0.985).Web-based tools for both outcomes were deployed: https://glioma-readmission.herokuapp.com/, https://glioma-reoperation.herokuapp.com/. DISCUSSION/SIGNIFICANCE: A high fraction of documented early unplanned readmission and reoperation were considered preventable and related to surgery. Machine learning allows better prediction of resected HGG’s prognosis based on findings from baseline methods leading to more personalized patient care.

MP35-15 PAIN CATASTROPHIZING IS ASSOCIATED WITH STENT-RELATED PAIN AFTER URETEROSCOPIC LASER LITHOTRIPSY

You have accessJournal of UrologyCME1 Apr 2023MP35-15 PAIN CATASTROPHIZING IS ASSOCIATED WITH STENT-RELATED PAIN AFTER URETEROSCOPIC LASER LITHOTRIPSY Alan J. Yaghoubian, Sarah Mozafarpour, Roman Shimonov, Raymond Khargi, Blair Gallante, Dara Lundon, Johnathan A. Khusid, William M. Atallah, and Mantu Gupta Alan J. YaghoubianAlan J. Yaghoubian More articles by this author , Sarah MozafarpourSarah Mozafarpour More articles by this author , Roman ShimonovRoman Shimonov More articles by this author , Raymond KhargiRaymond Khargi More articles by this author , Blair GallanteBlair Gallante More articles by this author , Dara LundonDara Lundon More articles by this author , Johnathan A. KhusidJohnathan A. Khusid More articles by this author , William M. AtallahWilliam M. Atallah More articles by this author , and Mantu GuptaMantu Gupta More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003269.15AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Ureteral stent-related pain varies in intensity for different patients. While stent-specific factors (e.g. stent position) may influence symptoms, patient-specific factors remain elusive. The pain catastrophizing scale (PCS) is a validated questionnaire quantifying the degree to which an individual may catastrophize painful stimuli. We aim to determine whether PCS score is associated with stent symptoms after ureteroscopic laser lithotripsy (URSLL). METHODS: This is an ongoing prospective study of patients undergoing URSLL. All patients completed the PCS prior to undergoing URSLL with stent placement and were labeled as catastrophizers (top third), non-catastrophizers (bottom third), or semi-catastrophizers (middle third). The ureteral stent symptom questionnaire (USSQ) was completed at 2 time points: post-op day (POD)#1 and POD#10. Prescriptions for phenazopyridine, ibuprofen, and oxybutynin were given. Outcomes included USSQ scores, total analgesic pills taken, pain-related office phone calls, and need for narcotic prescriptions. RESULTS: In sum 41 patients have been enrolled. Median USSQ pain scores on POD#10 were significantly higher among catastrophizers as compared to non-catastrophizers (24.5 vs. 14.0, p=0.036). There were no differences between all 3 groups in other USSQ domains. Catastrophizers took more tablets of phenazopyridine (11.0 vs. 5.5, p=0.027) and total prescribed tablets (26.5 vs. 15.5, p=0.023) compared to non-catastrophizers. Differences between number of pain-related calls between catastrophizers and non-catastrophizers approached significance (46.2% vs. 0%, p=0.057). Semi-catastrophizers had no significantly different outcomes from the other two groups. CONCLUSIONS: Pain catastrophizers have higher post-URSLL pain index scores, use more pain medications, and likely call the office more frequently. The PCS may ultimately become a practical tool to personalize patient care by identifying those at highest risk for severe stent pain. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e475 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Alan J. Yaghoubian More articles by this author Sarah Mozafarpour More articles by this author Roman Shimonov More articles by this author Raymond Khargi More articles by this author Blair Gallante More articles by this author Dara Lundon More articles by this author Johnathan A. Khusid More articles by this author William M. Atallah More articles by this author Mantu Gupta More articles by this author Expand All Advertisement PDF downloadLoading ...

The prognostic significance of Nectin-2 and Nectin-4 expression in glial tumors

Glial tumors are the most frequent neoplasms of the central nervous system in adults and despite recent advances in diagnosis and treatment of the disease, the prognosis of glioma is poor. Therefore, there is a great need to identify new prognostic factors and potential immunotherapeutic targets. Members of the Nectin family of proteins are gaining significant attention as possible diagnostic and immunotherapeutic targets in many solid tumors, but they have not been extensively investigated in glial tumors. The aim of the present study was to evaluate the expression of Nectin-2 and Nectin-4 in glial tumors of different grades, and to assess their prognostic value. The results showed heterogeneous expression of Nectin-2 and Nectin-4 in tumor cells and neuropil, with significantly higher Nectin-2 expression compared to Nectin-4, but without differences among tumor grades. In addition, the expression of Nectin-2 and Nectin-4 was associated with shorter survival times in patients with grade II/III gliomas. These results suggest that Nectin-2 and Nectin-4 expression may be used as an independent prognostic indicator for patients with II/III gliomas. This study contributes to the development of personalized care for patients with glioma and provides a basis for further research on nectin-based immunotherapy for brain tumors.

How positive deviants helped in fighting the early phase of COVID-19 pandemic? A qualitative study exploring the roles of frontline health workers in Nepal.

Positive deviance is an approach wherein learnings from persons who fare better than their peers under similar circumstances are used to enable behavioral and social change. Such behaviors and solutions are likely affordable, acceptable, sustainable, and fit into the socio-cultural milieu. Despite the wide use of positive deviance in many public health programs and research, it has yet to be used to study frontline workers in the context of COVID-19. Therefore, this study aimed to explore the positive deviance traits among frontline health workers during the early days of the COVID-19 pandemic in Nepal. This qualitative study followed a grounded theory approach. The data was collected through in-depth interviews among the 17 identified participants representing different cadres of the health workforce, types of health facilities, and regions across Nepal purposively. The findings are structured around four major themes: challenges, finding solutions and innovations, positive lessons, and motivations. The personal challenges included fear and anxiety about the uncertainties. The professional challenges included stigma, infection control, and changing work style with the use of personal protective equipment. Despite the challenges, they managed available resources and innovated low-cost, technological, and practice-based solutions. They were able to reflect upon the positive lessons learned, such as self-sustainability, teamwork, and policy direction and research, and self-reflection of personal growth and patient care. The intrinsic motivation included their inherent value system, and the extrinsic motivation included appreciation and acknowledgment, family and social support, psychosocial support from peers, and support from higher authorities. This study provides insights into how the positive deviance approach can help identify the solution amid the most challenging circumstances, such as the COVID-19 pandemic in low-resource settings. However, more extensive studies are warranted to explore deeper into positive deviance and its long-term effects in bringing positive outcomes during the pandemic.

Abstract P1-08-04: Therapeutic Advances in Metastatic Triple-Negative Breast Cancer: Identifying and Reducing Clinician Knowledge Gaps

Abstract Background: Characterization of the aggressive biology of triple-negative breast cancer (TNBC), defined by its lack of estrogen receptor, progesterone receptor, and human epidermal growth factor 2 (HER2) expression, has led to the development of more effective treatments for patients, but research indicates that clinicians face challenges in maintaining a working knowledge of evolving data. This study was conducted to determine what learning gaps exist in the area of therapeutic advances in TNBC and to investigate whether an online, case-based continuing medical education (CME)/nursing continuing professional development (NCPD)–approved activity could address gaps in clinicians’ knowledge regarding the personalized care of patients with metastatic TNBC. Methods: The CME/NCPD-approved live webinar series titled Metastatic Triple-Negative Breast Cancer: Applying Treatment Advances to Personalized Care was presented by Sara A. Hurvitz, MD, FACP, on July 13 and July 15, 2021, and was made accessible as a CME/NCPD-approved enduring webinar archive starting on July 23, 2021. Learners participated in a 1-hour activity that highlighted emerging therapeutic targets in TNBC, with an emphasis on current challenges and new opportunities in the management of metastatic disease. Learners completed a repeated-pairs pre- and post-activity assessment consisting of case-based questions that gauged their ability to apply emerging data to clinical decision making. Baseline knowledge gaps and subsequent learning gains were calculated based on percentages of learners obtaining correct responses on the pre- and post-activity assessments. Significance was assessed using a chi-squared test. In addition, learners reported self-perceived gains in confidence and competence using 5-point Likert scale questions. Results: As of June 28, 2022, 811 clinicians had completed the activity for credit; 62 learners participated in the live webinar, while 749 participated in the online enduring activity. Baseline assessment data revealed gaps in knowledge regarding emerging actionable targets and management of treatment-related adverse events (Table 1). Learners participating in the enduring activity scored an average of 43% on pretest topics; after completing the activity, the posttest average rose to 92%. The activity resulted in significant gains in knowledge and competence related to these topics, with P < 0.0001 for all learning gains. Upon completion of the activity, 86% of learners self-reported that knowledge acquired from this activity would be utilized to improve the outcomes of their patients, and 86% of learners self-reported that based on the information learned during the activity, they felt more confident in treating patients with metastatic TNBC. Conclusions: These data indicate that a substantial knowledge gap exists regarding the latest developments in the treatment of metastatic TNBC. They also demonstrate that online, case-based CME/NCPD-approved activities can result in statistically significant improvements in clinicians’ knowledge of therapeutic advances and management of treatment-related adverse events for patients with metastatic TNBC. Acknowledgements: This activity was supported by an independent educational grant from Merck. Table 1. Baseline Knowledge Gaps and Post-Activity Learning Gains. Citation Format: Elizabeth J. Heller, Keira Smith, Sarah L. Williams. Therapeutic Advances in Metastatic Triple-Negative Breast Cancer: Identifying and Reducing Clinician Knowledge Gaps [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P1-08-04.

Delayed‐type hypersensitivity gastrointestinal symptoms induced by food oral immunotherapy and efficiently treated by dupilumab: A case report

Delayed‐type hypersensitivity gastrointestinal symptoms induced by food oral immunotherapy and efficiently treated by dupilumab: A case report

Clinical Nurse Specialist and Clinical Nurse Leader Collaboration During the COVID-19 Pandemic.

The aim of this study was to describe an innovative strategy to maintain healthcare worker safety and optimal patient outcomes that was implemented by a healthcare system in the Southeastern United States during the COVID-19 pandemic. During the surges of the COVID-19 pandemic, healthcare systems have struggled with healthcare worker burnout, high staff turnover rates, and redeployment of staff to unfamiliar areas and the uncertainty regarding COVID-19 personal protection and patient care. Clinical nurse specialist/clinical nurse leader teams were created to help ensure healthcare worker safety and optimize patient care outcomes. Healthcare worker safety and desired patient outcomes were maintained. Throughput was expedited for emergency department patients, and there was timely implementation of therapeutic modalities for critically ill patients. Clinical nurse specialist/clinical nurse leader team collaboratively cross-trained staff to ensure their safety and delivery of quality patient care. The team was pivotal in helping safeguard staff from harm while optimizing patient outcomes. Lessons learned will help us in future disasters as well as our daily operations.

Coping styles and quality of life in oral cancer patients undergoing radical resection and free flap reconstruction

ObjectiveOral cancer is associated with functional impairment and changes in appearance due to disease progression and/or treatment. It therefore places a heavy psychological burden on patients. Coping styles of patients with cancer may affect their quality of life (QOL). However, there is limited research assessing this association. We aimed to clarify the relationship between coping styles and QOL in patients with oral cancer to underpin personalized patient care. MethodsPatients who underwent surgery with reconstruction for oral cancer between February 2017 and June 2021 were included in this study. Coping styles were assessed preoperatively using the Mental Adjustment to Cancer (MAC) scale. Mental and physical QOL was assessed preoperatively and at 3, 6 and 9 months postoperatively, using the Short Form-8 (SF-8) health survey. ResultsTwenty-seven patients completed the MAC and SF-8. The median (interquartile range) scores of MAC subscales summary positive adjustment (SPA) and summary negative adjustment were 48.0 (44.0–55.0) and 34.0 (29.0–38.0) points, respectively. The mental component summary (MCS) scores of the SF-8 at the preoperative assessment and 3, 6 and 9 months postoperatively were 47.2 (43.5–50.6), 45.2 (41.2–51.3), 48.4 (43.7–52.0) and 47.7 (43.2–51.0) points, respectively; the physical component summary scores were 47.2 (42.4–51.0), 41.9 (38.4–47.7), 44.8 (41.4–49.9) and 47.0 (42.9–50.0) points, respectively. A positive correlation was noted between the SPA and MCS preoperatively, and 3 and 9 months postoperatively. ConclusionsCoping style may have predictive value for oral cancer patients with low mental QOL.

Biomarker testing in colorectal cancer.

Christopher Lieu, co-director of gastrointestinal medical oncology and the associate director for clinical research at the University of Colorado Cancer Center (Aurora, CO, USA) discusses the importance of biomarker testing in metastatic colorectal cancer to inform personalized patient care.

Risk of acute myocardial infarction, stroke, and venous thromboembolism among patients with anti-neutrophil cytoplasmic antibody-associated vasculitis in South Korea: A nationwide population-based study.

To investigate the incidence and risk of cerebro-cardiovascular comorbidities (stroke, acute myocardial infarction, venous thromboembolism, and pulmonary embolism) in anti-neutrophil cytoplasmic antibody-associated vasculitis using nationwide Korean population-based medical claims data. We identified 1905 patients with newly diagnosed anti-neutrophil cytoplasmic antibody-associated vasculitis during 2009-2019. Incidence rates and hazard ratios with 95% confidence intervals were calculated to estimate the risk of cerebro-cardiovascular comorbidities in these patients and compared to age- and sex-matched controls (1:10) using the Cox proportional hazards model. Most patients had microscopic polyangiitis (42.5%), followed by granulomatosis with polyangiitis (29.1%) and eosinophilic granulomatosis with polyangiitis (28.4%). The annual incidence rate of anti-neutrophil cytoplasmic antibody-associated vasculitis in 2019 was 0.55 per 100,000 person-years. Cerebro-cardiovascular comorbidities occurred in 12.6%. Stroke was most common (64.6%), followed by venous thromboembolism (34.6%), pulmonary embolism (18.3%), and acute myocardial infarction (5.4%). Korean patients with anti-neutrophil cytoplasmic antibody-associated vasculitis were at a significantly (2.3 times) higher overall risk for cerebro-cardiovascular comorbidities than the general population (adjusted hazard ratios, 4.5, 3.1, and 2.0 times higher for pulmonary embolism, venous thromboembolism, and stroke, respectively). These findings were similar for patients with each subtype of anti-neutrophil cytoplasmic antibody-associated vasculitis. This is the first nationwide population-based study to demonstrate a significant risk of cerebro-cardiovascular comorbidities as complications of anti-neutrophil cytoplasmic antibody-associated vasculitis in Korean patients. Knowing these risks may enable personalized patient care and improve overall survival.

Radiomics in Lung Metastases: A Systematic Review.

Due to the rich vascularization and lymphatic drainage of the pulmonary tissue, lung metastases (LM) are not uncommon in patients with cancer. Radiomics is an active research field aimed at the extraction of quantitative data from diagnostic images, which can serve as useful imaging biomarkers for a more effective, personalized patient care. Our purpose is to illustrate the current applications, strengths and weaknesses of radiomics for lesion characterization, treatment planning and prognostic assessment in patients with LM, based on a systematic review of the literature.

Conditional autoencoder pre-training and optimization algorithms for personalized care of hemophiliac patients.

This paper presents the use of deep conditional autoencoder to predict the effect of treatments for patients suffering from hemophiliac disorders. Conditional autoencoder is a semi-supervised model that learns an abstract representation of the data and provides conditional reconstruction capabilities. Such models are suited to problems with limited and/or partially observable data, common situation for data in medicine. Deep conditional autoencoders allow the representation of highly non-linear functions which makes them promising candidates. However, the optimization of parameters and hyperparameters is particularly complex. For parameter optimization, the classical approach of random initialization of weight matrices works well in the case of simple architectures, but is not feasible for deep architectures. For hyperparameter optimization of deep architectures, the classical cross-validation method is costly. In this article, we propose solutions using a conditional pre-training algorithm and incremental optimization strategies. Such solutions reduce the variance of the estimation process and enhances convergence of the learning algorithm. Our proposal is applied for personalized care of hemophiliac patients. Results show better performances than generative adversarial networks (baseline) and highlight the benefits of your contribution to predict the effect of treatments for patients.

Health-related quality of life after curative treatment for muscle-invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) is an aggressive disease for which the gold-standard treatment is radical cystectomy (RC) in combination with cisplatin-based neoadjuvant chemotherapy. Bladder-sparing strategies such as trimodal therapy (TMT) have also emerged to improve health-related quality of life (HRQoL) of patients. However, an improved understanding of the effect of all these treatment modalities on HRQoL is essential to provide personalized patient care. Different combinations of generic, cancer-specific and bladder cancer-specific questionnaires can be used as instruments for HRQoL evaluation in patients with MIBC before and after curative treatments, which can largely affect multiple domains of HRQoL including general health as well as physical, functional, social and emotional well-being. However, diagnosis of MIBC per se is also likely to affect HRQoL, and the perspective of cure after RC or TMT could induce a return to baseline HRQoL values for most of these domains. A considerable amount of data on HRQoL after RC is available, but conflicting results have been reported regarding the effect of urinary diversion (ileal conduit or orthotopic neobladder) and surgical approach (open or robotic surgery) on patient quality of life. Data on HRQoL after TMT are scarce, and additional comparative studies including patients receiving RC (especially using ileal orthotopic neobladder) are needed.

Increase of Circulating Endothelial Progenitor Cells and Released Angiogenic Factors in Children with Moyamoya Arteriopathy.

Moyamoya arteriopathy (MMA) is a rare cerebrovascular disorder that causes recurrent ischemic and hemorrhagic strokes, leading young patients to severe neurological deficits. The pathogenesis of MMA is still unknown. The disease onset in a wide number of pediatric cases raises the question of the role of genetic factors in the disease's pathogenesis. In these patients, MMA's clinical course, or progression, is largely unclear. By performing a comprehensive molecular and cellular profile in the plasma and CSF, respectively, of MMA pediatric patients, our study is aimed at assessing the levels of circulating endothelial progenitor cells (cEPC) and the release of selected proteins at an early disease stage to clarify MMA pathogenesis and progression. We employed cytofluorimetric methods and immunoassays in pediatric MMA patients and matched control subjects by age and sex. We detected increased levels of cEPC in peripheral blood and an upregulation of angiogenic markers in CSF (i.e., angiopoietin-2 and VEGF-A). This finding is probably associated with deregulated angiogenesis, as stated by the moderate severity of collateral vessel network development (Suzuki III-IV). The absence of significant modulation of neurofilament light in CSF led us to rule out the presence of substantial neuronal injury in MMA children. Despite the limited cohort of pediatric patients, we found some peculiar cellular and molecular characteristics in their blood and CSF samples. Our findings may be confirmed by wider and perspective studies to identify predictive or prognostic circulating biomarkers and potential therapeutic targets for personalized care of MMA pediatric patients.

Assessing the Acceptability of Home Blood Monitoring for Patients With Cancer Who Are Receiving Systemic Anticancer Therapy From a Patient, Caregiver, and Clinician Perspective: Focus Group and Interview Study.

Regular blood testing is an integral part of systemic anticancer therapy delivery. Blood tests are required before every administration of treatment to ensure that a patient is sufficiently well to receive it. Blood testing is burdensome for patients as they require either an extra visit within 48 hours of planned administration of treatment or a significantly long visit if performed on the day of treatment. The additional time for appointments can have a significant impact on the quality of life of someone who is living with cancer. In the United Kingdom, the COVID-19 pandemic created unprecedented disruption to the delivery of cancer care. Face-to-face hospital visits were reduced, resulting in the need to develop more innovative ways of working to minimize treatment interruptions. This led to significant uptake of digital technologies, with new models of care rapidly deployed across the UK health service to meet these challenges. This study aimed to explore the acceptability of a point-of-care home blood monitoring device for people with cancer who are receiving systemic anticancer therapy, which is being developed in response to the increased need for remote care for patients with cancer. Qualitative focus groups and semistructured interviews were conducted with patients (23/47, 49%), caregivers (6/47, 13%), and health care professionals (18/47, 38%) over a 19-month time frame from May 2019 to December 2020. Data were analyzed using framework analysis guided by the Unified Theory of Acceptance and Use of Technology model. Analysis identified 4 overarching themes: performance expectancy, effort expectancy, social influence, and facilitating conditions. This study found that patients with cancer, their caregivers, and health care professionals had positive perceptions about home blood monitoring. Although they are often considered synonymously, self-testing and self-management are not mutually exclusive, and this study illustrated some disparity in opinions regarding patient self-management. Home blood monitoring has the potential to provide patients with cancer with a convenient option for blood monitoring. It would minimize hospital attendances, decrease late treatment deferrals, and provide prompt recognition of cancer treatment toxicities, thus enhancing the existing nurse-led protocols and clinical pathways. Home blood monitoring would create a long-term sustainable transformation for the delivery of cancer care, using digital health to act as a facilitator to address a pertinent issue regarding improving the efficiency of hospital resources and increasing the delivery of personalized patient care. Further studies are needed to determine how and where home blood monitoring would fit within clinical pathways, in a way that is robust and equitable.

Metaverse for Healthcare: A Survey on Potential Applications, Challenges and Future Directions

The rapid progress in digitalization and automation have led to an accelerated growth in healthcare, generating novel models that are creating new channels for rendering treatment at reduced cost. The Metaverse is an emerging technology in the digital space which has huge potential in healthcare, enabling realistic experiences to the patients as well as the medical practitioners. The Metaverse is a confluence of multiple enabling technologies such as artificial intelligence, virtual reality, augmented reality, internet of medical devices, robotics, quantum computing, etc. through which new directions for providing quality healthcare treatment and services can be explored. The amalgamation of these technologies ensures immersive, intimate and personalized patient care. It also provides adaptive intelligent solutions that eliminates the barriers between healthcare providers and receivers. This article provides a comprehensive review of the Metaverse for healthcare, emphasizing on the state of the art, the enabling technologies to adopt the Metaverse for healthcare, the potential applications, and the related projects. The issues in the adaptation of the Metaverse for healthcare applications are also identified and the plausible solutions are highlighted as part of future research directions.

NANOTECHNOLOGY IN U.S. MEDICAL DIAGNOSTICS: A COMPREHENSIVE REVIEW

This comprehensive review evaluates the advancements, potential, and ethical implications of nanotechnology in medical diagnostics within the U.S. healthcare system. The primary objective was to assess how nano-tools are revolutionizing early disease detection and management. The methodology involved a systematic review of peer-reviewed literature, focusing on studies published between 2000 and 2023. Data sources included academic databases such as PubMed, Scopus, and Web of Science, supplemented by secondary sources like journals and conference proceedings. The study emphasized the historical development of nanotechnology in diagnostics, current innovations, and future prospects in the field. Key findings reveal significant advancements in nano-diagnostic tools, highlighting their increased sensitivity and specificity in early disease detection. Innovations such as nano-enabled imaging and targeted drug delivery systems have shown potential in personalizing patient care. However, the study also identified challenges, including ethical concerns related to patient privacy, data security, and the need for comprehensive regulatory frameworks. The review concludes that while nanotechnology in diagnostics offers transformative potential, it also presents unique challenges. Recommendations for industry leaders and policymakers include fostering innovation within ethical and safety boundaries, investing in research, and establishing clear regulatory guidelines. Future research directions emphasize long-term efficacy and safety studies, cost-effective manufacturing processes, and exploring new applications in disease management. This study underscores the pivotal role of nanotechnology in shaping the future of healthcare diagnostics.

Review on Advent of Artificial Intelligence in Electrocardiogram for the Detection of Extra-Cardiac and Cardiovascular Disease

Artificial intelligence (AI) is that encompasses machine learning (ML) combined with human intelligence had begun to reform medical practices into a new dimension. Advancements and developments of AI molds improved diagnostics in the field of cardiology. Electrocardiogram (ECG) is a simple and cost-effective tool to identify cardiac disorder and which is its reason for being into practice till date. Increasing the population of ECG big data annually requires automatic analysis and immediate interpretation for improved diagnosis. Modern AI techniques like deep learning (DL)-based convolutional neural networks (CNNs) provide an improved way of cardiac disease management and diagnosis. This review throws a light over application of AI in ECG analysis and its necessity. Rich sets of clinical ECG data curated carefully as private and public access developed for various cardiac and extra-cardiac diseases management. Rather than human ECG interpretation, AI can move modern medicine toward more personalized patient care. The intention of this review article is to assess clinical and research possibilities, gaps, and jeopardies involved in cardiac anomalies detection using ECG measurement.

An Adaptive Privacy Preserving Framework for Distributed Association Rule Mining in Healthcare Databases

It is crucial, while using healthcare data, to assess the advantages of data privacy against the possible drawbacks. Data from several sources must be combined for use in many data mining applications. The medical practitioner may use the results of association rule mining performed on this aggregated data to better personalize patient care and implement preventive measures. Historically, numerous heuristics (e.g., greedy search) and metaheuristics-based techniques (e.g., evolutionary algorithm) have been created for the positive association rule in privacy preserving data mining (PPDM). When it comes to connecting seemingly unrelated diseases and drugs, negative association rules may be more informative than their positive counterparts. It is well-known that during negative association rules mining, a large number of uninteresting rules are formed, making this a difficult problem to tackle. In this research, we offer an adaptive method for negative association rule mining in vertically partitioned healthcare datasets that respects users’ privacy. The applied approach dynamically determines the transactions to be interrupted for information hiding, as opposed to predefining them. This study introduces a novel method for addressing the problem of negative association rules in healthcare data mining, one that is based on the Tabu-genetic optimization paradigm. Tabu search is advantageous since it removes a huge number of unnecessary rules and item sets. Experiments using benchmark healthcare datasets prove that the discussed scheme outperforms state-of-the-art solutions in terms of decreasing side effects and data distortions, as measured by the indicator of hiding failure.