bluuebunny/crossref_metadata_2025_split huggingface dataset:
Malignancy in patients with sickle cell disease: A single center experience.
Authors: Sharma Shivani , Walker Nakoma , Martinez Shidestini Chanta , Ramadas Poornima , Shi Runhua , Master Samip R. , Mansour Richard P. 
Published: June 2023

e22551 Background: The development of malignancy in patients with sickle cell disease has been documented in multiple case reports and case series. The incidence of malignancy in patients with sickle cell disease is unknown. Large national databases like the National Cancer Database, North American Association of Central Cancer Registries, and SEER do not collect data on the presence of sickle cell disease. This has made it difficult to calculate the incidence of malignancy in this patient population. In our study, we aim to calculate the prevalence of malignancy in sickle cell patients following our institution. Methods: After IRB approval, a retrospective analysis was conducted of adult sickle cell disease patients being followed at our Hematology outpatient clinic. We included patients aged > / = 18 years with sickle cell disease (HBSS, HBSC, HBS-beta thalassemia) as per hemoglobin electrophoresis, who were followed at the clinic from 1/1/2017 to 10/1/2022. We excluded prisoners. We did an extensive chart review to identify patients with a diagnosis of malignancy by pathology. Variables of age, sex, race, type of sickle cell disease, type of malignancy, age at the diagnosis of malignancy, and treatment were collected. Continuous descriptive data were summarized as means. Categorical data were summarized with a sample percentage. The prevalence of malignancy was calculated. SAS for windows 9.4 was used for analysis. Results: 438 patients with sickle cell disease were identified from 2017 to 2022. All the patients were African American. Their ages ranged from 16 to 84 with a mean of 35 years. Of these patients 53 % were females and 47 % were male. 62% had HBSS disease, 25 % had HBSC and 13% had HBS beta thalassemia genotype. 4 patients were diagnosed with malignancy. All 4 patients were female. The prevalence of malignancy was calculated as 0.91%. Conclusions: We found four patients with malignancy in the patient population with sickle cell disease at our hematology clinic. This data is based on limited sample size. The incidence of malignancy in sickle cell patients should be calculated in a larger population base. Further studies can be done to determine if a single type of sickle cell genotype increases the risk of malignancy. All the centers where sickle cell patients are followed should monitor the patients prospectively for the development of malignancy.[Table: see text]
Burnout in oncology nurses.
Authors: Sharma Priyanshi Rajesh , Sharma Rajesh 
Published: June 2023

e23000 Background: Burnout is a psychological condition that develops as a result of a sustained response to workplace interpersonal stressors. An overpowering sense of tiredness, feelings of cynicism and detachment from the job, and a sense of ineffectiveness & lack of accomplishment are the three primary dimensions of this response. Introduction: Specialties that is most impacted by burnout is oncology nursing. They work in environments with high patient: nurse ratios & demanding working conditions, which increases their load of emotional responsibility and increases the risk of burnout. The current research was done to determine the predictors of burnout in an Indian healthcare population due to the scarcity of Indian studies in this domain. Objective: The aim to this research is to investigate the level of burnout & fatigue in oncology nurses and how can we help them to recover from burnout. Outcomes are measured by Maslach Burnout Inventory test (MBI). Methods: In this study, total 300 nursing staff were included who are working in Oncology departments. The questionnaire comprised a total of 23 questions.The online surveys (Google form) were sent over 4-month period during April 2022 to June 2022 and nurses were met in person to interview and get the feedback submitted. The data were entered in the excel sheet and descriptive statistics were used to analyse the data using SPSS 20.0. The Mann-Whitney U test is used to compare differences between two independent groups. Logistic regression with stepwise selection was employed in multivariate analyses to find a group of demographic variables (age, gender) that were independently important in explaining the likelihood of burnout & fatigue in nurses. Results: In this study, 33.7% (101) male and 66.3% (199) of female nurses were included with highest number from the young age group 20-25 (51%, 153). The univariate analysis revealed that fatigue during daily routine shown significant association with gender and age classification, however positively dealing with anger, all the time energetic feelings, consideration themselves as happy person also shown statistical significance. It was found that the think of themselves during a busy time at work showed a significant association with gender classification in multivariate analysis. Similarly, dealing with anger was the most critical positive association with burnout variables in multivariate analysis. The overall multivariate test results on the basis of gender classification showed a significant difference for the burnout variables (p<0.01), while for age classification it was non-significant (p=0.87). Conclusions: The current study is a first step in understanding some of these mental health problems that Indian oncology nurses encounter and indicated prevalence of burnout consistent with age and gender criteria through standardizing measurement tools. It is helpful in raising awareness of the value of self-care and illnesses like burnout & fatigue among nursing professionals.
Incorporation of fellow-driven, interactive case-based discussions to improve fellowship education in a new fellowship program.
Authors: Sridhar Arthi , Ilyas Sama Imran , Rowe Julie H , Maithel Neha 
Published: June 2023

e23001 Background: Evidence-based education is crucial for meeting the evolving needs of learners in the oncology workforce. In this new virtual era, engagement of trainees in educational presentations has become increasingly difficult and reaping the benefits of a conventional didactic learning environment is challenging. Case-based learning is a relatively newer modality that is being used more commonly in teaching programs. In this study, we aimed to incorporate a novel, interactive case-based learning paradigm to improve fundamental knowledge and engagement among oncology trainees. Methods: We conducted six case conferences over 6 months. The case conferences were designed to encourage open discussion of real-life oncology cases. A faculty expert and specific topics were assigned to the presenters: colon, breast, gastric, hepatocellular (HCC), prostate, and non-small cell lung (NSCLC) cancer. Guidelines on the preparation of the case presentation were provided with 5 main pillars: specific staging/workup, first-line management with a landmark trial, second-line management, case-specific challenges, and mechanism of action and monitoring parameters for discussed drugs. Fellows completed a pre- and post-conference survey that assessed their perceived comfort level with the topic, quality of the presentation (post-conference) utilizing the 1–5 Likert scale (5 being extremely satisfied/comfortable), and test questions. Results: Nearly all of the 6 fellows responded to all surveys. The table shows the mean scores given by fellows on the surveys using the Likert scale and the percentage of test questions answered correctly. Overall, the fellows felt that the case conferences were a worthwhile experience. When comparing pre- and post-conference questions, the percentage of test questions correct overall improved for 5 of 6 conferences. Conclusions: The results of our study could have implications for the curriculum planning of hematology/oncology fellowships. [Table: see text]
The power of writing: Impact of writing for health professionals working with oncology patients.
Authors: Chagas Sabrina , Coradazzi Ana , Caponero Ricardo 
Published: June 2023

e23002 Background: Healthcare professionals are subject to stressful events, especially in areas such as oncology or palliative care. Writing is a valuable tool for dealing with stress, increasing empathy and job satisfaction. Narratives have therapeutic potential and can provide useful information for diagnosis and individualized strategies. Expressive Writing and Narrative Medicine have been studied in this field, resulting in physical and psychological benefits to health professionals, and can be a medical-educational tool. The practice of writing can promote healthier relationships between patients, professionals, and oneself. However, little is known about the perception that health professionals have about writing as a habit. These data can help to develop strategies for stimulating practice in universities, contributing to better professionals mental health. Methods: An online questionnaire was disseminated through social networks of the authors and professional associations inviting health professionals who deal with cancer patients and have the habit of writing to answer the questions, voluntarily and anonymously. The questionnaire was composed by 13 multiple choice questions and 1 free choice question, divided into 3 categories: 3 related to personal and professional data, 5 to the habit of writing and 5 to the impact that the habit of writing has on their lives. The data were analyzed descriptively, based on the results provided by the platform itself. Results: 177 responses to the form were obtained. Most participants were over 40 years old (53.9%). Eighty-seven participants were physicians (49.4%), 41 psychologists (23.3%), and 27.3% worked in other health fields. The majority (32.1%) declared they write sporadically when they feel the need. Only 17.8% wrote daily. Thirty-two percent write mainly short texts (blogs or social networks); 16.9% write mainly narratives. Most participants have been writing for more than ten years (63.2%). Using writing as a tool for self-knowledge was the main reason to start writing for 19.8%, and improving the ability to understand what is happening to other people for 18.7%. The themes of the texts were personal experiences (21.1%), personal feelings (19.4%), technical issues (14.8%), the process of getting sick (6.2%), or other topics (28.5%). Most reported that writing provides them with serenity (24.4%), comfort (23.8%), pride (19.3%), relief (13.6%), or other. Participants reported that the impact of writing on their lives is essential (32%), very positive (30.9%), or positive (33.7%), and the majority (48.8%) reported that the impact is both immediate and long-term. Conclusions: The personal perception about the impact of writing is extremely positive among healthcare professionals, suggesting that the practice should be stimulated during professional training and considered as a useful tool for the promotion of mental health.
Trends in application and match outcomes for hematology and oncology fellowship: An analysis of charting outcomes from 2008 to 2022.
Authors: Ojo Ademola Samuel , Ali Ahmed 
Published: June 2023

e23004 Background: The rapidly evolving advances in the field of oncology make it attractive to many internal medicine residents and graduates who must secure a position through the hematology and oncology fellowship match to get a chance to complete training in oncology. We aim to evaluate the trends in the application, competitiveness, and match rates of the hematology and oncology fellowship match based on the category of applicants. Methods: This is a retrospective cohort study of applicants who applied for the hematology and oncology fellowship from 2008 to 2022 based on the match data released by the National Residency Match Program (NRMP). The number of applicants, type of applicants, number of positions, and match outcomes was evaluated. Applicant types were classified into US-allopathic graduates and non-US-allopathic graduates. Chi-square tests were used to compare the match outcomes and the applicant types. Results: A total of 11,357 applicants participated in the hematology and oncology fellowship match during the study period. The number of applicants increased from 724 in 2008 to 894 in 2022 (a 23% increase), while the number of positions increased from 424 to 663 (a 36% increase). The average match rate was 68.5% during the study period, rising from 57.5% in 2008 to 73.5% in 2022. US allopathic graduates have a higher match rate when compared to non-US allopathic graduates (83.8% vs 56.2%; p < 0.00001). Although this disparity is maintained over time, it progressively narrowed (77.2% vs 42.5% in 2008 compared to 85.4% vs 63.3% in 2022). Fifty-three percent of applicants matched in their top 3 programs (36.5% in 1st, 11.2% in 2nd, and 7.3% in 3rd). The percentage of applicants matched in their top 3 programs increased from 53.4% in 2009 to 57.4% in 2022 (range: 50-62%). Conclusions: The hematology and oncology fellowship match is highly competitive with outcomes more favorable to US-allopathic graduates than non-US allopathic graduates. Most successful applicants matched in one of their top three programs. [Table: see text]
From abstract to publication: Factors predictive of publication success in the field of breast and gynecological malignancy.
Authors: Kapoor Ankita , Roy Arya Mariam , Aggarwal Sanjana , Gill Simrat , Attwood Kristopher , George Anthony , Ahlawat Yagya , Gandhi Asha , Patel Riya Jayesh , Kapoor Harshit , Jizzini Mazen , Sarma Maithreyi , Gandhi Shipra 
Published: June 2023

e23007 Background: Cancer research has rapidly evolved over the last few decades which has led to an improvement in patient care and outcomes. Dissemination of this research presented at meetings is essential to inform clinical practice. However, there continues to be a delay in the publication of data even after successful presentation of research as abstracts. In our study, we aim to determine abstract characteristics associated with successful peer-reviewed publication after presentation at the American Society of Clinical Oncology (ASCO) annual meeting for Breast and Gynecological malignancies. Methods: All oral abstracts (OA) & poster abstracts (PA) presented in the Breast & Gynecologic cancers categories from 2017/2018 ASCO annual meetings were included in the retrospective study. Manuscript publication was confirmed by searching PubMed using a data cut-off of December 2022. Publication characteristics like number of authors, time to publication (in months (mo)), study size, nature of results, impact factor, gender, H-index, citation of first author (FA) & last author (LA), NIH funding of LA were collected. Univariate logistic regression modeling was used to measure the association between publication status and select predictors. Results: 40/50 (80%) OA & 246/527 (46.6%) PA were published in PubMed indexed journals. Mean time to publication for OA was 17.41 mo & for PA was 19.52 mo. Mean IF for published OA was 28 & PA was 9.98. Of presented abstracts, 30/50 (60%) OA & 313/527 (59.39%) PA had positive results. Of the ones published, 23/40 (57.5%) of OA (p=0.72) & 190/246 (77.2%) of PA (p<0.001) had positive findings. 250/527 (49.14%) PA & 17/50 (33.3%) of OA were presented by females. Of the published OA, 15/40 (37.5%) had female FA & 10/40 (25%) female LA. For published PA, FA females were 118/246 (47.9%) while LA females were 86/246 (34.9%). For published PA, median H-index for FA was 33 & LA was 68. 16/40 (40%) LA of published OA & 62/246 (25%) of published PA had NIH funding. Conclusions: Our study reveals that poster abstracts with positive findings are more likely to be published, implying publication bias in research. In addition, there is also higher likelihood of publication if last author is NIH funded. Our study highlights the need to address these factors to maximize the chances of publication of impactful research. [Table: see text]
The impact of large oncology meetings (#ASCO, #AACR, #ASH) and health equity hashtags (#DEI+) on social media engagement.
Authors: Dizon Don S. , Florez Narjust , Subbiah Vivek , Weeks Lachelle Dawn , Dezzani Luca , Juneja Renu , Smith John , Edobor Wanda 
Published: June 2023

e23008 Background: Social media has revolutionized scientific communication to extend engagement beyond peer-reviewed publications and traditional media channels. Hashtags (#) promote awareness of key topics and enable tracking of social media engagement (Katz et al. JAMA Oncol. 2016;2(3):392-4). We evaluated the utilization of Diversity, Equity, and Inclusion (#DEI) hashtags around large oncology meetings to describe the trends of DEI-focused social media conversations. Methods: Using Symplur Signals healthcare analytics on Twitter data, 5 dashboards with # datasets (#ASCO 18-22, #AACR 18-22, #ASH 18-22, #ASHDEI) were analyzed over 2018–2022. Data were then refined by content word filters (most used DEI hashtags: #cancerdisparities, #healthdisparities, #healthequity). Utilizing proprietary natural language processing combined with artificial intelligence, the Netbase Quid platform used a Boolean algorithm to collect ASCO DEI social media data (Twitter and others) to identify discussion themes between January 2021 – January 2023. Results: Use of the ASCO hashtag resulted in high and relatively stable social media activity from 2018-2022 (Table). In contrast, a major decline in both the DEI and DEI+ASCO hashtags occurred in 2022 after the peak in 2021 (Table). The peak use of DEI hashtags coincided with sentinel events in the US, including the deaths of George Floyd and Breonna Taylor and subsequent public protests. However, DEI conversations made up only 2% of ASCO’s social media conversations and accounted for far less for American Society of Hematology (ASH) and American Association for Cancer Research (AACR) (Table). Although smaller in number, AACR hashtags (#AACR, +DEI hashtags) were stable in 2021-22 compared with ASCO and ASH, coinciding with a dedicated conference focus on DEI topics during the AACR meeting. Conclusions: In general, oncology-associated Twitter activity appeared to be less frequent, possibly due to inconsistent use of DEI hashtags. To generate consistent and searchable DEI social media activity—and to communicate the outcomes of DEI initiatives—the oncology community should develop a lexicon of DEI hashtags. [Table: see text]
Distinguishing enchondroma from low-grade chondrosarcoma using a multi-stage deep learning model for patient radiographs and histopathology.
Authors: Nye Logan , Ghaednia Hamid , Schwab Joseph H. 
Published: June 2023

e23500 Background: Enchondroma and low-grade (grade 1) chondrosarcoma are cartilaginous tumors of the peripheral bone. Enchondroma is benign, requiring only routine clinical monitoring. Chondrosarcoma is malignant, demanding prompt and aggressive treatment to prevent metastasis. Despite drastically different treatment protocols, these tumors are histologically and radiographically similar, making them difficult to tell apart. Even specialized treatment, years of experience, and access to both imaging modalities, pathologists and radiologists have reported low reliability in distinguishing between these two tumors. Better diagnostic and grading strategies are needed for these lesions. In this study, we propose a two-stage computer vision framework for distinguishing enchondroma from low-grade chondrosarcoma using deep learning. Methods: Our team compiled a ground truth dataset of radiographic and histological images from the annotated records of Dr. Henry Jaffe, a pioneering authority in musculoskeletal pathology. From his records, 55 cases of low-grade chondrosarcoma and 19 cases of enchondroma containing both radiology and histology imaging were identified and included. Radiographs and histology samples corresponding to the same individual were paired together to create 290 paired images of enchondroma and 318 paired images of low-grade chondrosarcoma (pair = 1 histology + 1 radiograph). These image pairings were randomly split into training (~80%) or validation (~20%) groups, excepting minimal reallocations to prevent leakage between training and validation data. All images were preprocessed and augmented for improved model training. Image pairings (one histology image, one radiograph) corresponding to the same patient case were passed through separate VGG16 models pre-trained on ImageNet weights. These models produced two feature vectors as outputs, which were concatenated and subsequently passed through a second-stage binary classification network to predict tumor identity. Results: After 17 epochs, the model recorded training loss and accuracy of 0.6723 and 0.7583, and validation loss and accuracy of 0.7362 and 0.7373, respectively – an improvement upon diagnostic accuracies reported in previous studies. Conclusions: We have created a two-stage deep learning model that predicts whether patient radiographs and histology show enchondroma or low-grade chondrosarcoma. The trained model’s validation accuracy of 73.7% improves upon past reported methods. This suggests that computer vision methods that utilize multiple imaging modalities might augment physicians' capability to discriminate between these two tumor types.