Oncologic Diagnosis Research Articles

Uses of AI in Field of Radiology- What is State of Doctor & Pateints Communication in Different Disease for Diagnosis Purpose

Over the course of the past ten years, there has been a rising interest in the application of AI in radiology with the goal of improving diagnostic practises. Every stage of the imaging workflow might potentially be improved by AI, beginning with the ordering of diagnostic procedures and ending with the distribution of data. One of the disadvantages of utilising AI in radiology is that it can disrupt the doctor-patient contact that takes place during the diagnostic procedure. This research synthesis examines how patients and clinicians engage with AI in the process of diagnosing cancer, brain disorders, gastrointestinal tract, and bone-related diseases. [S]ome of the diseases that are studied include cancer, brain disorders, and gastrointestinal tract. Researchers began their investigation of several databases in 2021 and continued their work until 2023. Some of the databases that were examined include PubMed, Embase, Medline, Scopus, and PsycNet. The search terms "artificial intelligence" and "intelligence machine" as well as "communication," "radiology," and "oncology diagnosis" were utilised. It has been demonstrated that artificial intelligence can help medical professionals make more accurate diagnoses. Medical compliance can be enhanced with good training in doctor-patient diagnosis communication, and future research may assist boost patients' trust by informing them of the benefits of AI. Both of these things are important for the delivery of quality medical care.
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Differential Outcomes of VATS and Open Surgery in Lung Cancer Patients with Antecedent Oncological Diagnoses.

Primary lung cancer is a devastating disease with high morbidity and mortality rates. Patients with a previous oncological history may present with multiple comorbidities, unique clinical features, and unique outcomes after surgical intervention for primary lung cancer. This study aimed to compare the clinical features and outcomes of patients with a previous oncological history who underwent video-assisted thoracoscopic surgery (VATS) or open surgery (OS) for primary lung cancer. A retrospective analysis was conducted on 84 patients with a previous oncological history who underwent surgical intervention for primary lung cancer between January 2018 and January 2023. Among them, 55 patients underwent VATS, while 29 patients underwent OS. Demographic and clinical characteristics, perioperative variables, and postoperative outcomes of the two surgical groups were collected and compared. Most of the 84 patients were women (58.4%) with a high smoking prevalence (44.1%) and a median of 32.3 packs-year. The patients' histories were most predominant for gynecologic cancers (44.4%) and colorectal cancers (18.6%). The results showed that the VATS group had a significantly shorter median hospital stay than the OS group (6.0 days vs. 12.0 days, p-value < 0.001). Additionally, the VATS group had lower incidences of air leaks 24 h post-surgery (12.7% vs. 48.3%, p-value < 0.001) and intractable pain (3.6% vs. 17.2%, p-value = 0.031), as well as significantly lower operative times (270 min vs. 350 min, p-value = 0.046). However, there were no significant differences between the VATS and OS groups in overall survival (log-rank p-value = 0.447). Furthermore, although the 3-month survival was significantly higher in the VATS group (98.2% vs. 79.3%, p-value = 0.003), only one patient from the VATS group (1.8%) and two patients from the OS group (6.9%) were still alive five years after the intervention. In conclusion, VATS is a safe and effective surgical option for patients with a previous oncological history who require surgical intervention for primary lung cancer, with shorter operative times, shorter hospital stays, and lower rates of complications compared to those of OS patients, without compromising oncological outcomes. Nevertheless, both surgical options failed to improve the 5-year survival rate, probably due to the high prevalence of comorbidities and the burden of previous cancer in this population.

Critical Care Utilization in Children With Cancer: U.S. Pediatric Health Information System Database Cohort 2012-2021.

To determine changes in pediatric oncology hospitalizations requiring intensive care over the period 2012-2021. Retrospective study of hospital admission. Registry data from 36 children's hospitals in the U.S. Pediatric Health Information Systems database. Children 18 years or younger admitted to any of 36 hospitals with an oncology diagnosis. None. There were a total of 55,827 unique patients accounted for 281,221 pediatric oncology hospitalizations over the 10-year period, and 16.6% of hospitalizations included admission to the PICU. Hospitalizations and PICU admissions steadily increased over this decade. Between 2012 and 2016, 15.1% of oncology hospitalizations were admitted to the PICU compared with 18.0% from 2017 to 2021 (difference 2.9% [95% CI, 2.6-3.2%] p ≤ 0.0001). Support with invasive mechanical ventilation also increased over time with 3.7% during 2012-2016 compared with 4.1% from 2017 to 2021 (difference 0.4% [95% CI, 0.2-0.5%] p ≤ 0.0001). Similar results were seen with cardiorespiratory life support using extracorporeal membrane oxygenation (difference 0.05% [95% CI, 0.02-0.07%] p = 0.0002), multiple vasoactive agent use (difference 0.3% [95% CI, 0.2-0.4%] p < 0.0001), central line placement (difference 5.3% [95% CI, 5.1-5.6%], p < 0.001), and arterial line placement (difference 0.4% [95% CI, 0.3-0.4%], p < 0.001). Year-on-year case fatality rate was unchanged over time (1.3%), but admission to the PICU during the second 5 years, compared with the first 5 years, was associated with lower odds of mortality (difference 0.7% [95% CI, 0.3-1.1%]) (odds ratio 0.82 [95% CI, 0.75-0.90%] p < 0.001). The percentage of pediatric oncology hospitalizations resulting in PICU admission has increased over the past 10 years. Despite the increasing use of PICU admission and markers of acuity, and on comparing 2017-2021 with 2012-2016, there are lower odds of mortality.

S2097 Undifferentiated Carcinoma of the Pancreas With Osteoclast-Like Giant Cells: A Grave Oncologic Diagnosis

S2097 Undifferentiated Carcinoma of the Pancreas With Osteoclast-Like Giant Cells: A Grave Oncologic Diagnosis

Delay in Time to Oncologic Therapies for Patients with Positive COVID-19 Test

For several cancers, delays between diagnosis and initiation of treatment has important clinical implications, often affecting trial eligibility, treatment intention, and oncologic outcomes. The coronavirus disease-19 (COVID-19) pandemic placed an extraordinary strain on the United States healthcare system, and its effect on oncologic patterns of care has yet to be established. We hypothesize that patients who received a new cancer diagnosis and subsequently tested positive for COVID-19 had delayed oncologic treatment compared to those who did not test positive for COVID-19. The National Cancer Database (NCDB) was queried to identify patients who were diagnosed and treated for any of 10 common malignancies from 2019-2020. Included disease sites were head and neck, esophagus, rectum, anus, lung, breast, cervix, uterus, prostate, and primary brain. Those who tested positive for COVID-19 between time of diagnosis and first oncologic treatment (including surgery, radiation, or systemic therapy) were compared to those who did not test positive for COVID-19. COVID-19 positivity was assessed using a new variable in the NCDB, "SARSCOV2_POS," which captures whether patients received a positive COVID-19 test via reverse transcriptase-polymerase chain reaction testing in inpatient, outpatient, or emergency room settings in 2020. Duration in days from cancer diagnosis to time to first treatment (TTFT) was analyzed using two-sample t-tests, with significance level of p<0.05. A total of 1,503,127 patients were identified for analysis. Of these, 7,340 (0.5%) tested positive for COVID-19 between diagnosis and start of treatment. Initial treatment was most commonly surgery (55.3%), followed by systemic therapy (17.4%) and radiation (12.7%). Overall, median TTFT was 55 days [interquartile range (IQR) 31-91] for the COVID-19 group versus 34 days (IQR 15-56) for the non-COVID-19 group (p <0.01). Subgroup analysis of the 10 individual sites of disease revealed statistically significant delays in each, with greatest absolute difference in median TTFT in prostate (31.5 days; 95.5 versus 64.0) and greatest relative difference in brain (>700%, 28.5 versus 4.0). In the first year of the pandemic, patients who tested positive for COVID-19 between oncologic diagnosis and initial management experienced significant delays in initiation of cancer-directed therapy compared to those who did not test positive for COVID-19, with median increase in TTFT of 21 days. Additional follow-up is needed to evaluate the clinical impact of these delays, as well as change in patterns of care in later years of the pandemic.

Prehabilitation in Radiation Therapy: A Scoping Review

Radiation therapy (RT) is a central component of cancer treatment with survival and long-term quality-of-life benefits across a spectrum of oncologic diagnoses. However, for certain cancers, RT has been associated with high levels of fatigue, pain, weight loss, and changes in mental health both during and post-treatment. Prehabilitation aims to optimize health prior to anti-neoplastic therapy in order to reduce complications, increase adherence to treatment, expedite posttreatment recovery, and improve long-term outcomes. Though prehabilitation has been studied in those undergoing cancer-related surgery, literature on prehabilitation in individuals undergoing RT has not been comprehensively explored. Thus, this scoping review aims to summarize the existing literature focused on prehabilitation interventions for patients receiving RT. The PRISMA-ScR checklist for conducting scoping reviews was adopted to identify and evaluate studies investigating the efficacy of prehabilitation before and during RT for cancer over the past 21 years (10/2002-10/2022). A search of prehabilitation and RT was performed to identify studies investigating prehabilitation interventions in adult cancer patients before or during RT. A total of 31 articles met inclusion criteria, yielding 4,031 total participants. Nineteen (61%) studies were randomized controlled trials with sample sizes ranging from 26-221. The most commonly studied populations were patients with head and neck cancer, followed by rectal, breast, and lung cancer. A majority (87%) of studies evaluated one prehabilitation intervention (i.e., unimodal). Targeted exercises were the most common intervention, followed by general exercises and technology/apps. Adherence/feasibility was the most common primary outcome, representing 23% of studies. All studies collected data on sex, and six (19%) studies collected data on race and/or ethnicity. Prehabilitation interventions have been successfully implemented in samples of patients with cancer undergoing surgical treatment. Studies demonstrating the efficacy of prehabilitation in RT are evolving. Though our review identified many RCTs, they were frequently small trials with primary outcomes focused on feasibility, rather than functional status. Thus, there is a need for adequately powered, randomized controlled intervention trials to investigate the efficacy of prehabilitation in RT.

Detecting Tumor Infiltration in Diffuse Gliomas with Deep Learning

Glioblastoma tumor recurrences often occur in brain tissue areas harboring infiltrating tumor cells, resembling healthy tissue in brain imaging. Demarcating infiltrative regions for aggressive resections is critical for improving prognostic outcomes but is challenging in neurosurgery. Herein, a multilayer sigmoid‐activated convolutional neural network (MLS‐CNN) is developed for rapidly distinguishing glioma tumor infiltration in brain tissue histology. Unlike conventional multiclass classifiers, the MLS‐CNN employs sigmoidal activation to accommodate coexisting classes within patch images. 59 811 image patches (25 807 infiltrating edge, 15 178 normal brain, 18 826 cellular tumor) from 73 brain tissue samples are extracted to train the classifier. The model achieves an accuracy of 91.70% (sensitivity: 91.62%; specificity: 91.78%) and area under the curve (AUC) of 0.964 in distinguishing infiltrating edges, outperforming the current state‐of‐the‐art Vision Transformer (ViT) (accuracy: 89.45; AUC: 0.947). The MLS‐CNN is computationally efficient, generating predictions within 11.5 s in comparison to 81.4 s for ViT. The predictions strongly correlate with In Situ Hybridization expression intensities, validating the utility of the MLS‐CNN model in spatial genomics investigations in gliomas. The robust model can therefore serve as an automatic and accurate classifier to help pathologists identify infiltrative glioma for better diagnosis and patient outcomes in brain oncology.

Changes in the content of aminonitrogen and the activity of aminotransferases in saliva in lymphomas

Background. The relevance of studying changes in the activity of metabolic enzymes in saliva in lymphomas lies in the non-invasive method of research, the search for new ways in the diagnosis of oncology to detect the disease in the early stages, as well as to obtain a complete picture of the course of the pathological process. The activity of certain biochemical enzymes is significantly higher in saliva than in blood serum. In addition, saliva is a less hazardous environment for laboratory testing than blood, which reduces the risk of infection for medical personnel. Objective. The aim of this work was to search for biochemical markers in saliva in Hodgkin’s and non-Hodgkin’s lymphomas, the value of which was statistically significantly different from the values of the same markers among healthy subjects included in the control group. Design and methods. In the case-control study, volunteers were divided into 2 groups: the main group, with a histologically confirmed diagnosis of Hodgkin’s lymphoma (53 people) or non-Hodgkin’s lymphoma (82 people) and the control group (135 people), apparently healthy individuals. Inclusion in groups occurred in parallel. All participants underwent a biochemical study of saliva to determine the content of amine nitrogen, the activity of enzymes (AlAT, AsAT, GGT, alkaline phosphatase). The patients of the main group were recruited on the basis of the Clinical Oncological Dispensary (Omsk, Russian Federation). Results. A significant increase in amino nitrogen (p &lt; 0,0084), ALT (p &lt; 0,0205), AST (p &lt; 0,0047), GGT (p&lt;0,0291) was found in the group of patients diagnosed with non-Hodgkin’s lymphoma, compared with subjects from the control group. Conclusion. A preliminary hypothesis was put forward that aminotransferases such as ALT, AST and GGT can be used not only as indicators of liver damage. A change in the activity of amine transferases with a simultaneous increase in the activity of amino nitrogen may reflect a pronounced redistribution of nitrogen in the body for the synthesis of new non-essential amino acids that are necessary for neoplastic cells as structural components for their growth and proliferation. This work also confirms that saliva is an informative diagnostic liquid that can be used in the routine practice of a clinician.

Increasing Provider Self-Efficacy to Manage Chronic Cancer Pain

BackgroundAims: Pain is a significant problem for those with a cancer diagnosis. Oncology providers often use opioid therapy to manage cancer-related pain. Accessing opioid therapy has grown increasingly difficult because of the opioid epidemic. The American Society of Clinical Oncology (ASCO) released guidelines to optimize pain management for patients with oncologic diagnoses. The goal of this quality improvement project was to create an educational session and evaluate self-efficacy in providers who manage chronic cancer pain. DesignThe Plan-Do-Study-Act was used as the framework for this quasi-experimental study with a pre/post education survey design. SettingsLevel 1 Trauma Center in Upstate, NY. Participants/SubjectsFamily Nurse Practitioners and Physicians Assistants in a local cancer institute. MethodsThere was a voice over PowerPoint educational intervention used to discuss key points of the guidelines, which included addressing aberrant behaviors, safe opioid prescribing, and interdisciplinary pain management. A convenience sample size of 18 advanced practice providers (APP) were recruited from a level 1-trauma center in Upstate, New York. Participants reviewed the educational intervention and completed a series of surveys to assess tool satisfaction and self-efficacy scores. ResultsData analysis revealed a significant increase in the mean self-efficacy scores on the post-education Jackson Opioid Therapy Self-Efficacy tool. The educational intervention was associated with improved perceptions of self-efficacy when managing chronic cancer pain. ConclusionsBased on the study's results, the guidelines released by ASCO should be reviewed and used to optimize pain management and self-efficacy in providers who work with oncologic patients. Furthermore, future research is recommended to evaluate the effect of evidence-based guidelines on patient outcomes and morbidity.

Mental Health Provision in PICU: An Analysis of Referrals to an Embedded Psychologist Over 20 Years at a Single Center.

The main aim of this study was to illustrate the type of mental health provision possible on PICU by describing the nature of referrals of child patients and their parents to an embedded psychologist over a 20-year period, adding to the literature on intervention and service development. Retrospective evaluation of anonymized departmental database. Twelve-bed PICU at a teaching hospital in a major urban center. Five hundred forty-five consecutive referrals for support for parent and/or child by PICU staff between 1998 and 2017. None. Referrals increased from seven of 288 (2.4%) in 1998 to 85 of 643 (13.2%) in 2017. The majority were for parent support initially (456/545, 84%). Mean ( sd ) number of contacts was 4.5 (10.2), range 1 to 143, and mode was 1. Patient gender and age typical of the total PICU population, but referrals were more common where children had an oncology or trauma diagnosis ( p < 0.001). Comparisons with other inpatient referrals at the same hospital revealed a higher proportion of requests were made for parent support on PICU (456/545 [84%] vs 789/1,997 [40%]; p < 0.001) and that nurses were more likely to initiate referrals on PICU than on the other wards (437/543 [80%] vs 1,190/1,993 [60%]; p < 0.001). In other respects, the two groups were similar in terms of number of sessions, waiting times, and attendance rates. Growing appreciation of the psychological impact of a child's admission to PICU has been associated with increasing referral to an embedded psychologist over a 20-year period, at this center. Clinical and service implications are outlined in the context of the latest research on the mitigation of post-intensive care syndrome in this population.

Incidence and Predictors for Oncologic Etiologies in Chinese Children with Pituitary Stalk Thickening.

With the increasing use of magnetic resonance imaging (MRI) in the evaluation of children with endocrine disorders, pituitary stalk thickening (PST) poses a clinical conundrum due to the potential for underlying neoplasms and challenges in obtaining a tissue biopsy. The existing literature suggests Langerhans cell histiocytosis (LCH) to be the commonest (16%) oncologic cause for PST, followed by germ cell tumors (GCTs, 13%) (CCLG 2021). As the cancer epidemiology varies according to ethnicity, we present herein the incidence and predictors for oncologic etiologies in Hong Kong Chinese children with PST. Based on a territory-wide electronic database, we reviewed patients aged < 19 years who presented to three referral centers with endocrinopathies between 2010 and 2022. Records for patients who underwent at least one MRI brain/pituitary were examined (n = 1670): those with PST (stalk thickness ≥ 3 mm) were included, while patients with pre-existing cancer, other CNS and extra-CNS disease foci that were diagnostic of the underlying condition were excluded. Twenty-eight patients (M:F = 10:18) were identified. The median age at diagnosis of PST was 10.9 years (range: 3.8-16.5), with central diabetes insipidus (CDI) and growth hormone deficiency (GHD) being the most frequent presenting endocrine disorders. At a median follow-up of 4.8 years, oncologic diagnoses were made in 14 patients (50%), including 13 GCTs (46%; germinoma = 11, non-germinoma = 2) and one LCH (4%). Among patients with GCTs, 10 were diagnosed based on histology, two by abnormal tumor markers and one by a combination of histology and tumor markers. Three patients with germinoma were initially misdiagnosed as hypophysitis/LCH. The cumulative incidence of oncologic diagnoses was significantly higher in boys and patients with PST at presentation ≥6.5 mm, CDI or ≥2 pituitary hormone deficiencies at presentation and evolving hypopituitarism (all p < 0.05 by log-rank). A higher rate of GCTs was observed in Chinese children with endocrinopathy and isolated PST. The predictors identified in this study may guide healthcare providers in Asia in clinical decision making. Serial measurement of tumor markers is essential in management.

The role and relevance of nutritional diagnosis in pediatric oncology

In the Russian Federation the incidence of cancer remains high. Depending on the nosology of the tumor, the probability of malnutrition during primary hospitalization may be 10-50%, and during treatment it may reach 100%. Undernutrition and obesity are independent factors of poor prognosis, reducing the overall effectiveness of treatment. At the same time, the diagnosis of nutritional status (NS) in pediatric oncology is not clearly regulated, which, in the presence of a large number of factors affecting the functioning of the digestive, nervous, endocrine and other systems, creates prerequisites for untimely recognition of nutritional disorders and, accordingly, inadequate nutritional support. Taking into account the mentioned tendencies above it is of great value to establish the foundations for recommendations on the assessment of NS and for making nutritional diagnosis in pediatric oncology. In order to highlight and resolve this challenge the interpretation of clinical aspects, advantages and disadvantages of existing screening scales for NS assessing, anthropometric indicators, methods for body composition evaluation, eating disorders classification according to the World Health Organization, the International Classification of Diseases 10 revision and specialized medical associations was carried out. Based on modern convictions regarding the pathogenesis of protein-energy malnutrition and cachexia, side effects and complications of antitumor treatment, available tools for assessing NS, their systematization, a unified nutritional diagnosis structure was formed. It includes: NS screening, nutritional history, anthropometry dynamics, evaluation of the gastrointestinal tract state and the presence of metabolic disorders, alimentation level, determination of nutritional risk factors. NS is a complex indicator and its reflection can be a nutritional diagnosis, which will potentially allow determining the current NS state, predicting the risks of malnutrition developing, implementing rational nutritional support, and thus improving the effectiveness of cancer treatment.

A review on deep learning applications in highly multiplexed tissue imaging data analysis.

Since its introduction into the field of oncology, deep learning (DL) has impacted clinical discoveries and biomarker predictions. DL-driven discoveries and predictions in oncology are based on a variety of biological data such as genomics, proteomics, and imaging data. DL-based computational frameworks can predict genetic variant effects on gene expression, as well as protein structures based on amino acid sequences. Furthermore, DL algorithms can capture valuable mechanistic biological information from several spatial "omics" technologies, such as spatial transcriptomics and spatial proteomics. Here, we review the impact that the combination of artificial intelligence (AI) with spatial omics technologies has had on oncology, focusing on DL and its applications in biomedical image analysis, encompassing cell segmentation, cell phenotype identification, cancer prognostication, and therapy prediction. We highlight the advantages of using highly multiplexed images (spatial proteomics data) compared to single-stained, conventional histopathological ("simple") images, as the former can provide deep mechanistic insights that cannot be obtained by the latter, even with the aid of explainable AI. Furthermore, we provide the reader with the advantages/disadvantages of DL-based pipelines used in preprocessing highly multiplexed images (cell segmentation, cell type annotation). Therefore, this review also guides the reader to choose the DL-based pipeline that best fits their data. In conclusion, DL continues to be established as an essential tool in discovering novel biological mechanisms when combined with technologies such as highly multiplexed tissue imaging data. In balance with conventional medical data, its role in clinical routine will become more important, supporting diagnosis and prognosis in oncology, enhancing clinical decision-making, and improving the quality of care for patients. Since its introduction into the field of oncology, deep learning (DL) has impacted clinical discoveries and biomarker predictions. DL-driven discoveries and predictions in oncology are based on a variety of biological data such as genomics, proteomics, and imaging data. DL-based computational frameworks can predict genetic variant effects on gene expression, as well as protein structures based on amino acid sequences. Furthermore, DL algorithms can capture valuable mechanistic biological information from several spatial "omics" technologies, such as spatial transcriptomics and spatial proteomics. Here, we review the impact that the combination of artificial intelligence (AI) with spatial omics technologies has had on oncology, focusing on DL and its applications in biomedical image analysis, encompassing cell segmentation, cell phenotype identification, cancer prognostication, and therapy prediction. We highlight the advantages of using highly multiplexed images (spatial proteomics data) compared to single-stained, conventional histopathological ("simple") images, as the former can provide deep mechanistic insights that cannot be obtained by the latter, even with the aid of explainable AI. Furthermore, we provide the reader with the advantages/disadvantages of the DL-based pipelines used in preprocessing the highly multiplexed images (cell segmentation, cell type annotation). Therefore, this review also guides the reader to choose the DL-based pipeline that best fits their data. In conclusion, DL continues to be established as an essential tool in discovering novel biological mechanisms when combined with technologies such as highly multiplexed tissue imaging data. In balance with conventional medical data, its role in clinical routine will become more important, supporting diagnosis and prognosis in oncology, enhancing clinical decision-making, and improving the quality of care for patients.

A Qualitative Analysis of the Experiences of Young Patients and Caregivers Confronting Pediatric and Adolescent Oncology Diagnosis.

Epidemiological studies show that new cases of young oncology patients are increasing by 400,000 every year. Psychological literature has shown that receiving an oncological diagnosis can cause significant psychological stress and discomfort. However, the experiences of young patients and their caregivers as they confront this challenge are not yet fully understood. This paper adopts a qualitative methodological approach to explore how young patients with an oncological diagnosis and their parents make sense of the experiential challenges they face. Thus, the research realized 18 semi-structured interviews, 11 of which were with pediatric and adolescent oncology patients, and 7 of which were with 6 mothers and 1 father. The qualitative thematic analysis revealed that the oncological diagnosis triggers different emotions taking the scene in the attempt to cope with the threats of meaning that the diagnosis poses. However, such intense experience promotes transformative feelings in parents and young patients, leading to important personal growth. Lastly, this article discusses the need to improve palliative psychological care competences in pediatric oncology. By providing comprehensive psychological care to young oncology patients and their families, healthcare providers can mitigate the psychological stress and pain associated with the diagnosis and treatment of cancer.

Editorial introductions.

Editorial introductions.

Evaluation of potential cost savings through chemotherapy and biotherapy dose-rounding at a pediatric institution.

Rapidly increasing costs of medication acquisition can pose a challenge for health-system pharmacy budgets. The impact of dose-rounding in a pediatric oncology population has not previously been well documented and a retrospective review was undertaken to quantify the potential cost benefits. A retrospective chart review of patients with an oncologic diagnosis was performed for cytotoxic agents, asparaginase products, and biotherapy administered between January 1, 2014, and December 31, 2017. In the analysis, orders that could be rounded down to the nearest vial size by 5 or 10% were included. Medication pricing information was based on wholesale acquisition cost (WAC) and was provided by the Department of Pharmacy. Cost savings per medication were determined by multiplying the WAC of the medication by the number of vials saved. Over a 4-year span, 347 patients were evaluated and 552 out of a possible 3110 orders (17.7%) met criteria for a theoretical cost savings of approximately $1,126,000 (∼$3200 per patient). Rounding down doses by up to 5% resulted in a potential savings of about $529,000. When rounding was extended to 5-10% of the originally ordered dose, an additional $597,000 of approximate cost savings could have been realized. The medications with the largest impact on cost savings were rituximab, pegaspargase, and erwinia asparaginase. For pediatric oncology patients, there exists a unique potential cost savings opportunity if doses are rounded down within 5 or 10% of the originally ordered weight-based or body surface area-calculated dose.

Sleep health behaviors in pediatric patients with newly diagnosed cancer

ObjectiveDisrupted sleep and fatigue are common symptoms in children with cancer, but little is known about this population's sleep health behaviors and how they may impact nighttime sleep. We aimed to describe the sleep health behaviors of children with newly diagnosed cancer and to determine if they changed over the next 8 weeks. MethodsOur sample included 169 children with cancer (86 males) who were aged 2–18 years (mean [SD] = 8.14 [4.4] y), with parent proxy report for 140 children (71 male) aged 2–12 years (mean [SD] = 6.67 [3.2] y) and self-report for 78 children (39 male) aged 8–18 years (mean [SD] = 12.0 [2.9] y). Parents and patients completed sleep hygiene questionnaires within 30 days of oncology diagnosis (T1); follow-up questionnaires were collected 8 weeks later (T2). Descriptive analyses characterized the sample by sociodemographic characteristics, cancer diagnosis, treatments received, and prescribed medications. ResultsAge-related differences were found in sleep health behaviors, with adolescents reporting better overall sleep health behaviors than younger children at both time points. No differences in sleep health behaviors were found at T1 related to diagnosis, treatment, or medications. Some differences in sleep health behaviors were found at T2 related to gender, diagnosis, treatment, and medications. Sleep health behaviors and sleep problems remained relatively stable over 8 weeks. Fatigue was significantly associated with more pre-bedtime worries, insomnia, and lower rates of daytime sleepiness. ConclusionsThese findings offer novel descriptive characteristics of sleep health behaviors in a pediatric oncology sample and show relatively stable yet somewhat poor sleep health behaviors across 8 weeks. Better understanding of sleep health behaviors as modifiable factors will help inform targeted interventions.

Genetic Algorithms as a Tool for Assisting Medical Diagnosis in Oncology and Radiology

Data on medical diagnoses might be complex and challenging to interpret with conventional statistical techniques. Metaheuristic algorithms, like genetic algorithms, have been created recently to offer almost ideal solutions to challenging medical issues. Natural selection is mimicked by genetic algorithms, which are nature- inspired methods for finding the best answers to challenging issues. Although genetic algorithms are widely employed in other industries, their potential in medicine is yet largely unexplored. This article examines possible medical applications for genetic algorithms and provides a synopsis of the related research.

Abstract 34: Evaluation of Potential Risk for Developing Treatment-Associated Late Effects Among Childhood Cancer Survivors in Northern Tanzania

Abstract Purpose: Global advancement in pediatric cancer treatment has significantly increased survival rates for children with cancer. Childhood cancer survivors (CCS) now represent a growing population at risk of potentially debilitating late effects of their treatment. This study evaluates the potential risk for long-term complications related to cancer therapy among childhood cancer survivors who completed treatment in Tanzania at Bugando Medical Centre (BMC), and compares the relative risk assessment of childhood cancer survivors at BMC as compared to the published British Childhood Cancer Survivor Study (BCCSS) cohort. Methods: Files of all patients age &amp;lt;18 yo with an oncologic diagnosis who received and completed their treatment at BMC from 2016 to 2020 were retrospectively reviewed. Extracted data included patient demographics, primary disease diagnosis and site, treatment received, and cumulative treatment doses. BCCSS risk assessment was assigned and predicted long-term follow-up surveillance needs were extrapolated from published Children’s Oncology Group Long-Term Follow-Up Guidelines. Results: 190 patients were initially identified, with 17 excluded due to missing treatment information. Among the remaining 173 patients, the mean age was 7yo, 47% were female (n=82), and the most common diagnoses were Wilms tumour (30%, n=52) and Burkitt’s Lymphoma (26%, n=45). 98% received chemotherapy (n=170), 42% (n=73) underwent tumour resection, and 8% (n=18) received radiation. Distribution of BCCSS late effect risk assessment included 6% low risk (n=10), 80% moderate risk (n=139) and 14% (n=24) high risk. This was a higher rate of moderate/severe risk (94%) compared to the published UK BCCSS cohort (84%). Based on treatment received, the late effects with highest potential risk were cardiomyopathy (57% of patients, n=98), bladder and urinary tract toxicity (50%, n=87), and ototoxicity (22%, n=38). Conclusion: Childhood cancer survivors at BMC have a higher risk of late effects as compared to published survivor cohorts in high-income countries. There is a need to develop and improve long-term follow-up care for survivors by enhancing patient and provider education to promote early detection of late effects. Based on risk assessment, survivorship programs in Tanzania should at a minimum include the capacity to perform echocardiograms, urinalysis, renal ultrasound, audiological evaluation, fundoscopic and neurological exams, and renal function test. Citation Format: Goodluck Nchasi, Gaudence Ajuaye, David Noyd, Hannah Spiegl, Erica Sanga, Heronima Joas, Kristin Schroeder. Evaluation of Potential Risk for Developing Treatment-Associated Late Effects Among Childhood Cancer Survivors in Northern Tanzania [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 34.

Aligning Germline Cancer Predisposition With Tumor-Based Next-Generation Sequencing for Modern Oncology Diagnosis, Interception, and Therapeutic Development.

In the era of precision medicine, genomic interrogation for identification of both germline and somatic genetic alterations has become increasingly important. While such germline testing was usually undertaken via a phenotype-driven single-gene approach, with the advent of next-generation sequencing (NGS) technologies, the widespread utilization of multigene panels, often agnostic of cancer phenotype, has become a commonplace in many different cancer types. At the same time, somatic tumor testing in oncology performed for the purpose of guiding therapeutic decisions for targeted therapies has also rapidly expanded, recently starting to incorporate not just patients with recurrent or metastatic cancer but even patients with early-stage disease. An integrated approach may be the best approach for the optimal management of patients with different cancers. The lack of complete congruence between germline and somatic NGS tests does not minimize the power or importance of either, but highlights the need to understand their limitations so as not to overlook an important finding or omission. NGS tests built to more uniformly and comprehensively evaluate both the germline and tumor simultaneously are urgently required and are in development. In this article, we discuss approaches to somatic and germline analyses in patients with cancer and the knowledge gained from integration of tumor-normal sequencing. We also detail strategies for the incorporation of genomic analysis into oncology care delivery models and the important emergence of poly(ADP-ribose) polymerase and other DNA Damage Response inhibitors in the clinic for patients with cancer with germline and somatic BRCA1 and BRCA2 mutations.