bluuebunny/crossref_metadata_2025_split huggingface dataset:
Oncology consults in admitted cancer patients: The ways to reduce length of stay.
Authors: Baralo Bohdan , Hanif Muhammad , Krupadev Archen , Iqbal Sabah , Kagita Navyamani , Mustaqeem Ruqqiya , Patel Neel S , Panda Monisha , Choi Eugene Jinkyu , Thirumaran Rajesh 
Published: June 2021

e13516 Background: The cancer patients, while being admitted to the hospital often have an oncologist consult (OC) through the admission. The goal of the study is to assess, whether OC impact the length of stay (LOS) and to define the group of cancer patients in whom omitting the OC can decrease LOS. Methods: We reviewed 415 admissions of cancer patients from 1/1/2018 to 11/30/2020 to the both campuses of Mercy Catholic Medical Center. We included patients who are 18 years or older with confirmed malignancy. We excluded COVID positive, patients who died during admission, were transferred to tertiary care institutions, or were recommended hospice care, but decided to continue treatment despite poor prognosis. Patient with hematologic disorders were excluded as well. The LOS of stay in cancer patients with and without OC will be compared using two tailed unpaired t-test and Mann-Whitney test ( < 20 admissions in each group, or one of the groups had a largely skewed data). Sub-analysis will be done accounting for Charlson score, spread of the disease and reason of admission (cancer vs non-cancer related). Statistical software Prism 9 will be used for analysis. Results: 290 admissions were selected using inclusion and exclusion criteria. Throughout all admission 234 admission had OC and mean LOS was 4.86 day compare to 4.23 in 56 patients, who did not have OC. Patients with non-cancer related (non-CR) admissions who had Charlson score ≤6 and no OC had shorter LOS (13 admission with median LOS 3 days) compared to those who had OC (11 admissions with LOS 7days), p 0.0462. Also, patient with non-CR admission and localized cancer tend have shorter LOS when no OC involved (15 admission with median LOS 6 days) compare to OC (16 admissions with median LOS 2.5 days), p 0.0365. No other significant difference in LOS were observed (Table). Conclusions: The cancer patients admitted for the reasons not related to their primary malignancy and who have either localized disease or Charlson score < 6 have shorter length of stay when OC not done. The limitation of the current study is the small number of patients in analysis subgroups, as well as fact that patients who had OC may have more severe disease during admission, despite the fact that patient had same extend of disease and comorbidities. Study with larger number of admissions may be necessary to confirm findings of this study.[Table: see text]
The impact of COVID-19 pandemic on oncology workload: The experience of an Italian Reference Cancer Center.
Authors: Corvaja Carla , Targato Giada , Garattini Silvio Ken , Barazzutti Cristina , Bin Alessandra , Donato Raffaela , Mansutti Mauro , Riosa Chiara , Rizzato Simona , Troiero Graziella , Fasola Gianpiero 
Published: June 2021

e13520 Background: Since its outbreak in January 2020, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic dramatically affected health systems worldwide and a prompt realignment of clinical activities had to be thought. International Oncology guidelines recommended that routine oncology care continued to be delivered, ensuring triage procedures to prevent COVID-19 diffusion alongside treatments prioritization. Aim of this study was to assess the variation of activity volumes due to COVID-19 pandemic in the Oncology Department of the Academic Reference Cancer Center of Udine, Italy. Methods: We extracted activity volumes from the electronic “Data Warehouse” accountability system and compared activity in 2020 with historical activity in 2019. We then narrowed the analysis to the peak of COVID-19 pandemic, comparing data of a four-months period (February-May 2020 vs 2019). In accordance with the Italian Association of Medical Oncology guidelines, the activities analyzed included: new patients referrals, first consultations, new therapy assignments, treatment prescriptions and therapy administrations, disease re-assessments, follow-up visits, tele-examinations, unplanned visits and ward discharges. Results: Overall, throughout COVID-19 pandemic a negligible reduction in the number of first consultations (-5%) and new patients referrals to our Oncology Department (-10%) was detected. Of note, a significant reduction in the number of unplanned oncologic visits was observed (-23%). The replacement of follow up visits with telephonic interviews with the interpretation of laboratory and radiologic examinations (tele-examinations) led to a substantial reduction in follow-up visits throughout 2020 (-25%). Conversely, treatment-related activities, including new therapy assignments (+1%), treatment prescriptions and therapy administrations (+2% and +3%, respectively), confirmed the increasing trend of the previous year. Interestingly, similar trends were observed in the four-months peak period with a substantially higher decrease in follow-up visits in 2020 vs 2019 (-51%), whereas treatment-related activities remained stable. Conclusions: In the context of COVID-19 pandemic, our Oncology Department maintained stable performances on critical oncology activities. Strict triage procedures, serial swabs for patients and healthcare professionals and strategic follow-up visits remodulation were crucial. Notwithstanding the significant decrease in cancer treatments observed in several published reports, our experience demonstrates that the reorganization of oncology departments during a global pandemic is feasible and it should be pursued to preserve patients’ safety without compromising the continuum of care.
Determining the cancer diagnostic interval using administrative data in a cohort of patients with pancreatic ductal adenocarcinoma (PDAC).
Authors: Paterson Bailey , Kong Shiying , Mahar Alyson , Webber Colleen , Lee-Ying Richard M. , Cheung Winson Y. , Groome Patti , Karim Safiya 
Published: June 2021

e13551 Background: PDAC is a leading cause of cancer death that is often diagnosed at an advanced stage. Population-based administrative data can be a valuable resource for studying the diagnostic interval, defined as the time from the first related healthcare encounter to cancer diagnosis. The objective of this study was to determine the diagnostic interval in a cohort of patients with PDAC using an empirical approach. Methods: This is a retrospective, cohort study of patients diagnosed with PDAC from 2007 – 2015 in Alberta, Canada. We used the Alberta Cancer Registry, physician billing claims, hospital discharge and emergency room visits to identify and categorize cancer-related healthcare encounters before diagnosis. We used statistical control charts to define the lookback period for each encounter category and used these lookback periods to identify the earliest encounter that represented the start of the diagnostic interval (index contact date). The end of the interval was the diagnosis date. Quantile regression was used to determine factors associated with the diagnostic interval. Results: We identified 3,142 patients with PDAC. Median age of diagnosis was 71 (IQR 61-80). We identified an index contact date and thus a diagnostic interval in 96.5% of patients. The median diagnostic interval length was 76 days (IQR 21-191; 90th percentile 276 days). A higher Elixhauser comorbidity score (+18.57 days/ 1 point increase, 95% CI 16.07-21.07, p<0.001) and stage 3 disease compared to stage 2 disease (+22.55 days, 95% CI 5.02-40.08, p=0.01) were associated with a longer diagnostic interval. Conclusions: In this cohort of patients with PDAC, there was a wide range in the diagnostic interval with 10% of patients having a diagnostic interval of approximately 9 months. Diagnostic interval research using administrative databases can understand variations in diagnosis times and can inform early detection efforts by identifying where and in whom delays may occur.
Improving consent forms for first-in-human trials through participant feedback.
Authors: Sibold Hannah Claire , Campbell Gavin Paul , Bourgeois John , Dixon Margie D. , Harvey R Donald , Pentz Rebecca D. 
Published: June 2021

e13563 Background: Risks and benefits of investigational agents that have not been tested in humans are, at best, incompletely characterized in nonclinical investigations. Despite the growing emphasis to include patient voices in clinical trial design, no published research has explored patient preferences on how best to convey the information that the agent has not been tested in humans. This study established that First in Human (FIH) consent forms present this information in different locations and queried participants for their input on the preferable FIH consent form structure. Methods: Consent forms for FIH oncology trials open to accrual at Winship Cancer Institute in 2019-2020 were analyzed for (1) the location of the mention that the study drug has not been used in humans before (FIH information), (2) the location of animal and other nonclinical data, and (3) placement of the risks section. Patients offered enrollment in a FIH trial were eligible for this study. Participants were interviewed during a clinic visit after consent was obtained. An ethics researcher asked questions about the participant’s opinions on the wording and placement of the FIH, nonclinical, and risk information in the specific trial consent form. All interviews were audio-recorded and double coded by two independent coders. The location of FIH and nonclinical data in the consent forms was compared to the patient’s suggested location for this information. Results: Saturation of themes was reached after interviewing 17 (17/19, 89% accrual) participants who were enrolled in 9 different FIH trials. Twenty FIH consents were qualitatively analyzed. Preferred placement compared to actual consent placement is listed in the table. 82% (14/17) of participants thought that nonclinical data on risks and efficacy was important to mention. 95% (19/20) of consents listed nonclinical data and most participants thought the placement in the consent was appropriate but 18% (3/17) of participants wanted the information earlier in the consent. No consent forms that were analyzed had the risks section before the study schedule; however, 47% (8/17) of participants wanted to move the risks sections before the study schedule. Conclusions: There is considerable variation in the layout of FIH consent forms that does not align with patient preferences. Standardization of FIH consent forms to better reflect patient input is essential in order to promote understandability of these important yet sometimes misunderstood clinical trials and to ensure ethical informed consent.[Table: see text]
The Neat-HER virtual registry: Updated results on HER2+ breast cancer patients receiving neratinib as extended adjuvant therapy.
Authors: Vidal Gregory A. , Tripathy Debu , Hill Nina , Lalla Deepa , Hanson Gillian , Drozd Daniel R. , Xu Feng , Rugo Hope S. 
Published: June 2021

e13565 Background: Data from traditional registries are usually limited to patients treated at study sites. Virtual registries can enroll a broader real-world population. Neat-HER is a U.S.-based virtual registry pilot through PicnicHealth that is enrolling patients with HER2+ breast cancer receiving neratinib as extended adjuvant therapy. Methods: Neat-HER evaluates the feasibility of enrolling patients and answering research questions using a novel electronic platform. Eligibility includes receipt of neratinib in the extended adjuvant setting, signed informed consent for medical record retrieval/data abstraction and age > 18 years. Patients who do not complete enrollment procedures, are participating in a clinical trial or have metastatic disease are excluded. Patients are recruited through multiple mechanisms including private social media groups, treating clinicians and patients enrolled in the Puma Texting Program. Patient health records for breast cancer-related treatment are collected from time of diagnosis to 1-year post-enrollment in the registry. Research questions focus on patient and tumor characteristics, receipt of therapy (e.g. radiotherapy, adjuvant therapy), neratinib duration, and diarrhea prophylaxis. Results: 33 patients with HER2+ early-stage breast cancer who received neratinib as extended adjuvant therapy have been enrolled in this registry study since December 2018. Median age was 50 years, with 79% of patients self-identifying as white. 82% of patients had hormone receptor-positive (ER/PR) disease and 73% of patients had node-positive disease. Prior HER2-targeted adjuvant therapy regimens were as follows: trastuzumab with paclitaxel (9%); trastuzumab/pertuzumab in combination with a taxane(s) (91%). 17 patients (52%) completed 12 months of neratinib treatment; 4 patients (12%) discontinued treatment early; 10 patients (30%) were still ongoing at the time of data cutoff. 31 patients (94%) had diarrhea prophylaxis discussed prior to the start of neratinib treatment. Conclusions: Neat-HER provides useful information on patient/tumor characteristics and treatment patterns in a real-world cohort receiving extended adjuvant neratinib and patient recruitment is ongoing. Updated results show that this pilot virtual registry continues to be a feasible and efficient modality to collect important data on descriptive characteristics and treatment patterns for a patient population derived from real-world practice settings. Validation of this method is needed and could be used in other tumor types.
Use of single-arm trials to support malignant hematology and oncology drug and biologic approvals: A 20-year FDA experience.
Authors: Agrawal Sundeep , Arora Shaily , Vallejo Jonathon Joseph , Gwise Thomas , Chuk Meredith Kathleen , Amiri-Kordestani Laleh , Pazdur Richard , Kluetz Paul Gustav , Beaver Julia A. 
Published: June 2021

e13572 Background: Improved understanding of the underlying biology of cancer has led to a paradigm shift in cancer drug development and has paved the way for many products to receive accelerated or regular approval based on non-randomized/single arm trials (SATs). Given the high unmet medical need of cancer patients, challenges with lengthy and confounded survival endpoints, and difficulty enrolling rare biomarker-defined subsets of disease, SATs have been used to evaluate a variety of cancer therapies. Unlike time to event endpoints, the objective and clinically relevant endpoint of response rate (RR) and duration of response is interpretable in SATs, as spontaneous tumor shrinkage is not expected. Methods: A search of FDA databases identified all drugs and biologics approved for malignant hematology and oncology indications from January 1, 2001, to December 31, 2020 based on SATs. Data sources included approval letters, U.S. prescribing information, and clinical review documents. The definition of response varied by setting and time period (e.g. RECIST, WHO, IWG, etc.). Results: Between January 1, 2001 and December 31, 2020, FDA granted 153 new indications based on SATs, including 102 accelerated approvals (AAs) and 51 regular approvals (RAs). Overall, 69 approvals (45%) were for new molecular entities and 84 (55%) were expanded indications. Response rate was the most common endpoint used in the trial providing substantial evidence of efficacy to support approval [120/153, (78%)]. The durability of response was also considered to support evidence of clinical benefit. Of the 102 AAs, 38 (37%) have fulfilled their post-marketing requirement (PMR) to verify clinical benefit, 59 (58%) are pending verification of benefit, and 5 (5%) have been withdrawn from the market. Of note, 88% (52/59) of AAs pending verification of benefit occurred in the last 5 years alone (22 AAs in 2020, 8 in 2019, 8 in 2018, 12 in 2017, and 2 in 2016). Between 2001-2020, 58 (38%) new indications were granted for kinase inhibitors, 34 (22%) for immune checkpoint inhibitors (CPIs), and 61 (40%) for drugs with other mechanisms of action including but not limited to antibody-drug conjugates, cytotoxic drugs, and non-CPI monoclonal antibodies. Conclusions: In the last two decades, SATs have been effectively used to study anti-cancer therapies in well-defined patient populations using durable RR as an objective and interpretable clinical endpoint. Although randomized clinical trials remain the gold standard in clinical research, SATs have allowed for rapid advancements in oncology drug development and will continue to serve an important role in bringing new therapies to patients with unmet need.
Expedited development and review pathways for novel oncology drugs.
Authors: Vadola Lisa Ambrosini , Winter-Vann Ann , Knoll Miriam , Whitsell Robin 
Published: June 2021

e13578 Background: Following approval of the Food and Drug Administration (FDA) Safety and Innovation Act in 2012, the FDA launched a 3-year plan to promote innovation, increase stakeholder involvement, secure the drug supply chain, and fund these endeavors by collecting user fees. The FDA created its fourth expedited pathway, Breakthrough Therapy Designation (BTD) to focus on the development and approval of therapies to treat serious and life-threatening conditions that lack adequate therapies. Our 2017 study (ASCO abstract #e18270) identified a trend of increased use of these approaches with oncology drugs, particularly the BTD, which was a nascent pathway at the time. We aimed to reexamine FDA pathway and approval trends in oncology interventions. Methods: We analyzed publicly available data on novel drug approvals by the FDA’s Center for Drug Evaluation and Research (CDER) from 2012-2020 and the 4 expedited pathways (BTD, Accelerated Approval, Fast Track Designation [FTD], and Priority Review). Results: Between 2012 and 2020, CDER approved 380 new chemical entities, including 101 oncology drugs. Due to data limitations, 3 novel oncology biologics (approved by the Center for Biologics Evaluation and Research) and 4 diagnostics were excluded from the analyses. Oncology drugs comprised a mean 27% (range 14-34%) of all approvals from 2012-2020, including 25% from 2012–2016 and 28% from 2017-2020. Of all approved oncology drugs from 2012-2020, 94% (range 82-100%) utilized at least one expedited pathway. Oncology approvals were more likely than non-oncology approvals to have used one or more expedited pathways. Use of these pathways for oncology approvals increased from 2012-2016 to 2017-2020: ≥2 (65% vs 78%) and ≥3 (35% vs 50%) pathways. BTD usage for oncology drugs increased from 35% in 2012-2016 to 57% in 2017-2020, though for 2012-2016, the time interval between awarding the (new) designation and the remainder of development activities must be considered. Presumably because BTD grants additional benefits over FTD, generally the use of FTD for oncology drugs has declined over time. The use of Priority Review and Accelerated Approval has remained the same. Despite the pandemic, for oncology and non-oncology drugs alike, approvals using pathways remained consistent between 2019 and 2020. Conclusions: Efficient FDA review plays an important role in oncology drug development. Since its inception in 2012, BTD has been adopted and expeditiously used, comprising more than half of all novel oncology drug approvals from 2017-2020. Our data show a gradual increase in approvals of drugs granted BTD, which, given the duration of drug development, likely reflects the time between the acceptance of the BTD request and remainder of the pre-submission development activities. As BTD was expressly developed to increase stakeholder interaction and prioritize innovation, the speed-to-adoption and use of this pathway among oncology interventions is promising.
MLkit: A machine-learning-powered automatic workflow for classification of cancer samples.
Authors: Li Qingyuan , He Ji 
Published: June 2021

e13583 Background: In the era of data explosion, precision classification of cancer samples based on multi-dimensional medical data provides more insights into disease mechanism and useful hints on clinical treatment associated with tissue of origin, recurrence tendency and prognostic of chemotherapy or immunotherapy. We developed an automatic workflow MLkit to select features from large-scale multi-dimensional medical data and conduct classification through various machine learning techniques. Methods: MLkit is an automatic and one-stop workflow for classification of cancer samples with four modules: preprocessing (missing data remove or imputation and feature standardization), feature selection (unsupervised multi-statistics and supervised multiple machine estimators with recursive feature elimination and cross-validation), modeling (hyper-parameter, performance evaluation and probability calibration) and prediction. Most of current machine learning algorithms were implemented in this workflow, including linear model (logistic regression, ridge regression and stochastic gradient descent), ensemble model (gradient boosting, random forest, xgboost, catboost, lightgmb and stacking), support vector kernel (linear and non-linear), naive Bayes, k-nearest neighbors and multi-layer perceptron neural network. To evaluate the performance of this workflow, we utilized it to fit a model used for prediction of tissue of origin based on 450K DNA methylation data of 2,210 samples from lung, kidney and breast cancer patients collected in TCGA. Results: MLkit performed well in the prediction of tissue of origin for independent validation sets of cancer patients with stable feature selection, automatic hyper-parameters and efficient probability calibration, in which the model achieved AUCs ranged from 0.85 to 0.96. In addition, we also utilized this workflow on extensive real world data and most of results showed superior accuracy and stable performance. Conclusions: MLkit facilitates automated and one-stop classification of cancer samples using machine learning algorithms. It can be operated with simple command line, making it accessible to a broad range of users. The well performance of this workflow based on multi-dimensional medical data can help to improve the discovery of tumor biomarker and optimize clinical follow-up and therapeutic treatment for cancer patients.