bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bridging the gap: FDA diversity-related postmarketing requirements.
Authors: Kormanik Natasha L. , Carioti Theresa , Crai Kayla , Kanapuru Bindu , Richardson Nicholas C. , Gormley Nicole 
Published: June 2023

e13608 Background: Historically, pre-market clinical trials have lacked enrollment of racial and ethnic minority patients that represent the population intended to be treated with the approved drug in the US. The Food and Drug Administration (FDA) has several programs and initiatives designed to enhance diversity in oncology clinical trials, such as the Oncology Center of Excellence’s (OCE) Project Equity, FDA Guidance documents, and submission of Diversity Plans from industry. Under the code of federal regulations and/or statute, the FDA can issue post-marketing requirements (PMR) to fulfill accelerated approval requirements for confirmatory studies; for assessing safety signals; or for conducting dedicated studies in pediatric patients. FDA may also issue post-marketing commitments (PMC) to generate additional clinical evidence. PMRs and PMCs have been used to obtain additional information on under-represented populations. The objectives of this analysis were to identify oncology PMRs/PMCs issued with a specific focus on racial and ethnic minority populations and examine the trend over the 10-year period. Methods: We searched FDA’s publicly available database of PMR/PMCs, inclusive of drugs and biologic products, and internal agency databases for PMR/PMCs issued between 2012-2022. The PMR/PMC search was further narrowed down by keywords to capture all PMRs/PMCs relevant to races and ethnicity. The PMRs/PMCs were then manually reviewed for duplication and applicability to malignant indications. Results: In a 10-year period, 34 PMR/PMCs focused on race and ethnicity were issued across 461 oncology approvals (initial marketing approvals = 164, new indications = 297). Twenty-two were issued with the initial marketing approval and 12 with supplemental efficacy approvals. All PMR/PMCs were issued in the last 3 years (2019-2022). PMCs accounted for 55.9% (n = 19) and PMRs 44.1% (n = 15). Nine of the 15 PMRs requesting additional information on underrepresented populations were included with the accelerated approval PMRs. Six of the 34 PMR/PMCs were issued to obtain additional PK or dosing information in the underrepresented population. The most common PMR/PMC indications issued were lymphoma (n = 13, 38.2%), multiple myeloma (n = 8, 23.5%), and non-small cell lung cancer (n = 4, 11.8%). Although PMR/PMCs that mentioned a specific race were limited, African American/Black (n = 8) and Asian (n = 1) were occasionally identified. All studies identified in this analysis are ongoing except for one, for which the product was withdrawn. Conclusions: Our analysis highlights the trend and increased emphasis on race and ethnicity in post approval oncology studies. While progress has been made to promote studies that are representative of the US population through these PMRs/PMCs, diversity plans, and FDA guidance over the course of the past 10 years, more efforts are needed to better enhance diversity in clinical trials moving forward.
Comparative effectiveness trial of two supportive cancer care (SCC) delivery models at 24 clinics: An ongoing cluster randomized trial.
Authors: Medrano Hector S. , Wood Emily H. , Kapphahn Kris , Agarwal Madhuri , Perez Cynthia C. , Matthew Marika , Fuller Keely E. , Patel Manali I. 
Published: June 2023

e13617 Background: Many patients with cancer receive care that is misaligned with their goals, values and preferences and have undertreated symptoms. Proactive integration of advance care planning and symptom management -- Supportive Cancer Care (SCC) -- through team-based and technology-based approaches can overcome these deficiencies. Yet, it is unknown which approach is more effective. Methods: This 24-clinic cluster-randomized trial (NCT05297734) will evaluate whether a team-based SCC delivery approach using community health workers more effectively improves health-related quality of life (HrQOL) than a technology-based approach utilizing the electronic health record. We are enrolling 2996 patients across 24 clinics (12 randomized into each group) in the United States including integrated community clinics, academic, Kaiser, VA, and safety-net centers. Eligible patients are: ≥ 21 years; newly diagnosed with cancer; English or Spanish speakers. Those unable to consent, enrolled in competing trials, or planning to move within 12 months are excluded. The primary outcome is change in HrQOL using the Functional Assessment of Cancer Therapy-General survey from baseline to 3-months post-enrollment. Secondary outcomes include changes in patient activation, satisfaction, and healthcare use (emergency department visits, hospitalizations, chemotherapy, radiation, surgery, palliative care, hospice use) from baseline to 3-, 6-, and 12-months post-enrollment. Results: Enrollment began June 2022. As of December 2022, 24 clinics obtained IRB approval and 11 of 24 clinics screened a total of 1075 patients and enrolled a total of 165 participants. The majority (n=146; 77%) are male; 89 (53.9%) reported less than college degree; 45 (27.3%) reported annual household income ≤ $49,999. Conclusions: This ongoing study will inform the most effective SCC delivery approach and strategies to improve SCC across a variety of clinical settings in the United States. Clinical trial information: NCT05297734 . [Table: see text]
Use of secondary subgroup analysis of clinical trials across solid malignancies.
Authors: Alzubi Marah , Odeh Nada Wael , A.l. Zyoud Muntaser , Hamadneh Yazan , Alrawabdeh Jawad , A.l. Hadidi Samer 
Published: June 2023

e13618 Background: The use of secondary (subgroup) analyses in medical literature is increasing. Findings from subgroup analyses may be misleading given they are observational in nature and do not resemble a randomized comparisons. Our study aimed to characterize the use of post hoc subgroup analysis in interventional clinical trials across solid malignancies. Methods: We searched OVID database for articles subgroup analyses from the year 2000 until Feb 15, 2022. Some of the used search terms were post-hoc, subgroup, secondary, cancer, tumor, breast, colorectal. 11641 articles were screened to include all secondary analyses of interventional solid tumor clinical trials. We excluded original trials, secondary analyses of cohort/observational studies. Results: Our final analysis included 1491 articles. Most studied malignancy was gastrointestinal cancers (22.6%), followed by genitourinary cancers (21%), and breast cancer (19%). The number of papers published per year increased steadily over the years with a peak in 2021 (16% of all articles). About 78% of articles reported receiving funding, with 40% reporting pharma-related funding. 29% of articles reported the usage of a medical writer. 55% of articles reported that authors had conflicts of interest (COI). Pharma-related funding was significantly associated with usage of a medical writer (p < 0.001). The mean percentage of authors with COI was 31.8 ± 0.95%. Articles that reported usage of a medical writer had a higher percentage of authors with COI (p < 0.0001). Women represented 32.7% and 25.9% of first and last authors, respectively. About 44% of both first and last authors resided in North America. Half of the articles explicitly indicated that they were secondary analyses in their titles. [Table]. Conclusions: Our study indicated that the use of secondary subgroup analysis in solid malignancies clinical trials is increasing. Half of the studies did not clarify the nature of them being secondary analyses in the title. Given their increased use, caution must be entertained when interpreting the results of secondary analysis. [Table: see text]
Using SMS technology to improve quality of life and symptom management in the breast cancer patient population: A feasibility study.
Authors: Fulton Tracy , Lettkeman Laura , Buchholz Thomas A. 
Published: June 2023

e13619 Background: Cancer patients experience a wide range of negative side effects/symptoms from chemotherapy and radiation including pain, dehydration, nausea/vomiting, and diarrhea/constipation. Symptoms are distressing and decrease the overall quality of life and increase unnecessary hospitalizations and emergency visits. Symptom management and quality of life may be improved by using Short Message System (SMS) texting in cardiac and diabetic patient populations. The technology may also decrease costs for unnecessary emergency department (ED) visits by breast cancer patients. The purpose of this study was to determine if an SMS texting service can improve quality of life by improving symptom management. A secondary purpose was to evaluate if texting decreases emergency visits by breast cancer patients. Methods: This IRB-approved, consented study implemented an SMS texting program for breast cancer patients. Participants received two texts per day during their chemotherapy treatment period (6 months), one text being informational regarding symptom management and the second was one of encouragement and inspiration. Participants were called bi-weekly to complete the Distress Thermometer for Patients (NCCN). ED visits and/or hospital admission rates for the sample were collected. An exit interview measured satisfaction with the program in quantitative measures and theme analysis for qualitative measures. Twenty patients participated in this study, with 13 included in the data analysis. Results: SMS texting provided a change in treatment for symptom management in 40% of patients. Overall satisfaction with the SMS program was at the 89th percentile. Almost all participants felt supported and cared for due to bi-weekly calls by the investigators. Only 10% of the participants visited the emergency department, which is lower than historical averages. Data concerning the distress thermometer proved to be non-informative. Conclusions: SMS texting is feasible and easily integrated into the care of breast cancer patients. Texting technology may provide engagement with the care team leading to changes and improvement in symptom management during chemotherapy treatment. Further study of texting technology providing interactive abilities for patient-reported outcomes is warranted.
Remote evaluation of NAVIFY Oncology Hub using clinical simulation.
Authors: Halligan Jack , Goh Ethan , Lo Ernest N. , Chabut Delphine , Prime Matthew Stewart , Ghafur Saira 
Published: June 2023

e13622 Background: Clinical workflow is critical for the efficient and safe delivery of patient care. NAVIFY Oncology Hub is a clinical workflow solution that provides clinicians with a comprehensive view of a patient’s clinical journey and aims to enable effective and efficient care decisions in oncology care. This study explored the use of remote clinical simulation to assess the usability, efficiency, and cognitive burden associated with using NAVIFY Oncology Hub. Methods: Twenty seven (27) board-certified oncologists were recruited to participate in remote evaluation sessions conducted via teleconference. Participants were instructed to review and synthesize clinical information from 10 synthetic breast cancer cases using NAVIFY Oncology Hub (case order was randomized). After completing the exercise, participants answered a survey which included the system usability scale (SUS), Likert-scale questions designed for participants to self-report the efficiency of completing each task, and the NASA Task Load index (to assess cognitive burden). The survey and a short interview was also used to gather structured feedback on the solution, patient cases, and study methods. Results: NAVIFY Oncology Hub scored an “excellent” 82 on the system usability scale (SUS). Most participants (67%) indicated that they would be likely to use the solution in their clinical practice, with approximately half (48%) reporting they would recommend it to a colleague. The majority of participants (96%) said they were “a lot more efficient” or “somewhat more efficient” when using NAVIFY Oncology Hub to review patient information. The majority of participants (78%) felt it would be “significantly better” or “somewhat better” than their existing solution at facilitating patient discussion and coordinating care. On the NASA Task Load Index survey, the majority of participants (63%) required low or very low levels of mental demand, temporal demand, and effort to successfully complete tasks using NAVIFY Oncology Hub. The majority of participants (91%) felt the synthetic patient cases were either ‘very similar’ or ‘somewhat similar’ to cases seen in routine clinical practice, and that the tasks completed during the sessions were ‘very similar’ or ‘somewhat similar’ to their clinical practice. Conclusions: This novel clinical simulation study shows early evidence that NAVIFY Oncology Hub has high usability, potential to increase overall efficiency and reduce cognitive burden on oncologists compared to contemporary EHR systems. Clinical trial information: NCT05478135 .
Longitudinal MRI-based radiomic model to complement sentinel lymph node biopsy assessment after neoadjuvant chemotherapy in initially clinically node-positive breast cancer: A multicentre, diagnostic study.
Authors: Wang Kun , Zhu Teng , Huang Yuhong , Li Wei 
Published: June 2023

e13623 Background: The high false-negative rate (FNR) of sentinel lymph node biopsy (SLNB) alone results in unnecessary axillary lymph node dissection (ALND) in initially clinically node-positive (cN+) breast cancer after neoadjuvant chemotherapy (NAC). This study aimed to reduce the FNR by establishing a longitudinal MRI radiomics-assisted SLNB model compared with SLNB alone. Methods: We established and tested a machine learning algorithm (RMLM) based on pre-NAC, post-NAC and longitudinal MRI radiomics features to detect axillary complete response (ypN0) to neoadjuvant chemotherapy in cN+ breast cancer. In total, 234 eligible patients who underwent SLNB and ALND were retrospectively recruited in the primary cohort (PC), 723 patients were in external validation cohorts (EVC) 1-3, and 81 patients from two multicentre prospective clinical trials (ClinicalTrials.gov, NCT03154749, NCT04858529) were enrolled in the prospective validation cohort (PVC). The U test and least absolute shrinkage and selection operator with tenfold cross-validation were used to select the most significant features. The specificity and FNR of RMLM-assisted SLNB were compared with those of SLNB alone. Results: In the primary (n=234 patients), external validation (n=723) and prospective validation sets (n=81), RMLM achieved excellent performance in detecting metastatic axillary lymph nodes (AUC=0.938 in the primary cohort, 0.842-0.913 in the external cohorts, 0.865 in the prospective validation cohort). RMLM-assisted SLNB achieved an FNR of 4.96% in PC, 5.83-8.08% in EVC1-3, and 9.09% in the prospective validation cohort. The removal of more than two SLNs combined with RMLM could further reduce the FNR to 2.78% in PC, 3.28-7.27% in EVC1-3, and 6.67% in the prospective validation cohort. Conclusions: RMLM combined with SLNB provides a potential tool to evaluate residual nodal disease after NAC and reduce unnecessary ALND.
Integrating technology to support data management abstraction of adverse events (AE) and concomitant medications (ConMed) from the electronic health record (EHR) to sponsor electronic data capture (EDC) systems using design thinking (DT) methodology.
Authors: Yuravlivker Leemor , Buckley Michael T. , Bouvier Nancy , Jeevarathnam Sundar , Lazan Steve , Panchal Renata , McKellop Mairi , Lengfellner Joseph M. , Terzulli Stephanie Lucia , Sabbatini Paul 
Published: June 2023

e13624 Background: Manual abstraction of data from a site’s EHR to pharmaceutical sponsor’s EDC system is labor intensive and inefficient. To reduce the time and effort of this process for data managers (DM), a web-based application, Clinical Trials Data Hub (CTDH), was developed using Design Thinking methods. It extracts and consolidates AE and ConMed data from the EHR and displays it in a user friendly, automated, and consolidated view for easy entry into EDC forms. Methods: Following DT methodology to develop CTDH, we interviewed 12 DMs to identify data entry bottlenecks, and ideated solutions for what is now CTDH. To evaluate CTDH’s value, we built a functioning prototype using Splunk and conducted pilot A/B testing with 6 DMs for 2 use cases (Case I: basic easy to find ConMed linked to the AE, and Case 2: complex, where the ConMed linked to the AE was buried in a 33-page document) using their current workflow (A) versus CTDH (B) where a 5-minute training of CTDH occurred prior to testing. We hypothesized that CTDH would outperform current workflows across 3 primary outcomes: 1) correct data identification, 2) time to identify data, and 3) using a modified Single Ease Question (SEQ) rating scale to assess how difficult users found the task. This study was conducted in Jan-Aug 2022 at a large single-center cancer hospital. Results: DMs spend ~20 hours/week on data entry; the majority of which is spent searching the EHR for which ConMeds are associated with an AE. A/B testing results are noted in Table I (see below). Use case 2 showed that DMs using CTDH reduced the time to find one ConMed linked to an AE by 148%, saving ~5 minutes in one task. 5 of 6 participants preferred CTDH to existing clinical systems. Conclusions: Our findings suggest that CTDH allows DMs to 1) identify AE and ConMed data required for EDCs more quickly than in current workflow, 2) identify data more accurately to be entered in sponsor EDCs, and 3) perceive the task of identifying this data to be easier. CTDH reduces the time DMs spend searching clinical systems and documents and has the potential to save meaningful time per patient per study. CTHD will launch into production in May 2023. Digital tool product development using DT methodology has the potential to improve operational efficiency and the clinical staff user experience. This is particularly important in an industry that has struggled with burnout, cost containment, and high turnover. [Table: see text]
Continuous temperature monitoring: A systematic review of literature findings.
Authors: Phillips Ruth Anne , Bradley Sarah K. , Jani Janvi 
Published: June 2023

e13625 Background: Recent studies have determined continuous temperature monitoring (CTM) identifies fever up to 12 hours earlier than intermittent temperature monitoring in patients with neutropenic fever. In 2010, Van Vliet showed CTM enabled the early administration of antibiotics. Verma and colleagues (2021) reported that self-monitored temperature taking was frequently inaccurate. Nessle et al. (2022) observed 2 instances of fever, associated with bloodstream infections, detected by CTM 5 hours and 12 hours earlier than oral temperature. CTM records 8,640 data points in 24 hours versus the current standard of care (SOC), which typically measures up to 6 data points in 24 hours. The increased frequency of data collection presents a comprehensive picture of the patient’s status which enables earlier detection in trends or patterns of fever. As a result, earlier medical evaluation and prompt administration of antibiotics has led to improved patient care and outcomes. Methods: A literature review was executed to determine the validity of evidence available related to CTM utilization in both oncology and other high-risk therapeutic areas. Levels of evidence were assigned based on the design, methodology, validity, and applicability of the studies. Journal impact scores were added to support findings and implementation into real-world practices. A table was created to organize the data, including level of evidence, journal impact score, and study results. Results: This review of the literature included 17 documents related to CTM. Levels of evidence for CTM include 4 documents with Level 1 and 5 documents with Level 2 evidence. The journal impact scores found 6 of the 17 documents to be above 5. Overall, the study results showed a positive correlation between the use of CTM and earlier fever detection. Conclusions: CTM use has grown in recent years; however, there is still a need for randomized controlled trials to observe health economic, and clinical outcomes. CTM allows for earlier detection of fever, improving patient outcomes over SOC in high-risk patients. CTM should be considered a clinical decision tool to enhance current vital sign monitoring, thereby improving neutropenic patient care.
A deep learning system to predict origins for cancers of unknown primary using cytological images from hydrothorax and ascites.
Authors: Tian Fei , Sun Lin , Wei Na , Liu Wei , Li Xiangchun , Chen Gong 
Published: June 2023

e13628 Background: Cancer of unknown primary (CUP) origin is still a mystery in the field of tumor diagnosis, which is difficult to be diagnosed by conventional imaging methods. The aim of this study is to develop a deep learning based method to assist pathologists in determining the origin of malignant hydrothorax and ascites using cytological images. Methods: By curating cytology images of hydrothorax and ascites from 42682 cases at three hospitals, we developed a deep-learning-based method -Tumor Origin diffeRentiation for Cytological Histology (TORCH)- for diagnosis of malignancy and prediction of tumor origin. We examined its performance on three individual test sets (n=12799). We compared TORCH with a panel of four pathologists on 496 cases that were randomly selected from test sets. Area under the receiver operating characteristic curve (AUROC) was used as the primary classification metric. Metrics including accuracy, sensitivity, specificity, precision and negative predictive value were used to measure the efficacy of TORCH versus pathologists. A score system was used to evaluate and compare the performance between our AI model and pathologist experts. Attention heatmap was used to interpret model prediction results. Results: TORCH model reached an overall micro-average one versus rest auroc of 0.957(95% CI: 0.955-0.959). On the three test sets, TORCH achieved an AUROC of 0.964 (95% CI 0.957-0.972), 0.947 (0.940-0.953), and 0.988 (0.985-0.993) in the diagnosis of cancer and 0.947 (0.942-0.952), 0.957 (0.953-0.960) and 0.972 (0.968-0.976) in localization of tumor origin, respectively. For primary tumor origin prediction, TORCH achieved an overall top-1 accuracy of 79.2% and top-3 accuracy of 98.5%. On three test sets, the top-1 accuracy was 75.7%, 79.4%, and 85.0% respectively. Compared with pathologists, TORCH demonstrated a better prediction efficacy (1.665 ± 0.677 vs. 1.265 ± 0.555; P <0.001). The mean diagnostic score of junior pathologists assisted with TORCH was also remarkably higher than the previous one (1.326 ± 0.728 vs. 1.101 ± 0.824; P <0.001). The comprehensive accuracy of attention heatmaps capturing main area of isolated tumor cells was 87.3% (95% CI: 81.9-92.8%). Conclusions: TORCH model was able to provide relatively accurate diagnosis of malignancy and prediction of tumor cell origin in hydrothorax and ascites. It can be used as an effective ancillary method to aid clinicians in allocating personalized therapy and improving patients’ prognosis.