bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantifying the clinical severity of immune-related cutaneous adverse events in clinical trial patients: A prospective study using 3D-total body photography.
Authors: Oh Yuna , Lacouture Mario E. , Paras Mehta , Kurtansky Nicholas , Kern Jeffrey , Leung Donald Y. M. , Noor Sarah J. , Rotemberg Veronica
Published: June 2021

e13548

Background: Accurate and comprehensive assessment of dermatologic adverse events (AEs) in clinical trials is challenging, given the heterogeneity of appearance and perception of these AEs. For dermatologic AEs, Common Terminology Criteria for Adverse Events (CTCAE) grading of clinical severity primarily relies on the clinician’s reporting of body surface area involved (BSA%) estimated by visual assessment combined with clinician’s interpretation of psychosocial impact, which can vary among raters. Although patient reported outcome (PRO-CTCAE) and QoL (SKINDEX-16) measures have been incorporated to improve accuracy and reliability of symptomatic AE evaluations, the subjective nature of dermatologic CTCAE grading remains. Clinical photography is routinely used to aid in visual comparison but cannot be incorporated to standardized measures due to inconsistencies in lighting, distance from the camera, and position. This prospective study aims to validate the accuracy and utility of affected BSA% using 3D-total body photography (TBP) and quantitative imaging analytics for standardized, objective assessment of immune-related cutaneous adverse events (ircAE) in clinical trials and/or prospective studies. Methods: Polarized and non-polarized TBPs (Canfield Vectra WB360) were acquired on two dermatology clinic visits 2-6 weeks apart (n = 8, to date). CTCAE, PRO-CTCAE, SKINDEX-16 were evaluated by one investigator for both visits. Image analysis including BSA% calculation was conducted using Vectra measurement software by an investigator blinded to clinical grades. Means and ranges for change in CTCAE, BSA%, and SKINDEX-16 were calculated. Results: To date, 29 patients with ircAE have been enrolled with 8 completing both visits. A greater improvement in affected BSA% (-1.9, -13.0, -20.1) and SKINDEX-16 (-8,-11.9,-19.5) were associated with a greater degree of clinical improvement measured by CTCAE (0 to -3). Widest range in the degree of change in BSA% (-24.4, -6.8) and SKINDEX-16 (-31,19) was observed in the group with intermediate change in CTCAE (-2 to -1, n = 5). Conclusions: Estimating affected BSA% via visual assessment is subject to human error and rely on memory or comparison with unstandardized photos to detect clinical improvement of dermatologic conditions. This poses a challenge particularly for cases with mild or moderate clinical improvement, demonstrated by the wide range in the degree of change for BSA% and SKINDEX-16. With consistent lighting, position, and objective measurements, 3D-TBP quantitative image analysis shows promise in reproducible, standardized monitoring and quantification of ircAE clinical severity. Furthermore, the quantitative nature of TBP measurement suggests its potential utility for correlation with underlying immunophenotyping correlative studies and clinical trials.
Global trends of COVID-19 research in cancer: A scientometric study.
Authors: Sharafeldin Noha , Quang Pham Hai , Hoang Nguyen Long , Thu Vu Giang , Huyen Trang , Thi Nguyen Tham , Xuan Tran Bach
Published: June 2021

e13549

Background: The scientific literature experienced an unprecedented growth in archived pre-prints and peer-reviewed COVID-19 related publications with regional variations making the task of synthesizing the information burdensome. This study aims to characterize global patterns and domains of COVID-19 research in cancer. Methods: We used the NIH COVID-19 portfolio and Web of Science (WOS) curated databases to extract abstracts using standard search terms for COVID-19 and cancer between Nov 1 2019 and Dec 31 2020. A total of 21,325 publications matched the study search criteria (NIH: 18,029 records; WOS: 3512 records; 204 records overlapped). We performed a descriptive analysis to calculate country citations and intercountry collaboration networks. The Jaccard similarity index was utilized to identify the most frequently co-occurring terms. Latent Dirichlet Allocation (LDA) was used for classifying publications into corresponding research topics. Results: The most productive period was May 2020 with 3,181 published articles, mean citation rate per paper was highest in Jan 2020 (1,620.5) followed by Feb 2020 (236.7), highest mean use rate in the last 12 months was March 2020. Top productive countries are classified as High and Upper Middle-income countries, 17% of research contributed by USA, 12% by China PR, and 11.4% by Italy. Linkage between top 30 productive countries show USA, Italy, and England with the highest inter-country co-ordination. Analysis of keywords co-occurring at least 5 times resulted in 12 major clusters including: 1) cancer treatment and mortality; 2) inflammation and immunology; 3) chronic diseases and co-morbidities; and 4) mental health and social psychology. Ranked topics with the highest volume of publications include 1) effect of COVID-19 on treatment outcomes; 2) individual risk factors of COVID-19 severity and mortality, and 3) novel treatment options relevant to cancer patients [Table]. Growth of articles peaked between Mar and Apr 2020 with a steady decline across all topics in Sept 2020. Conclusions: Global cancer –related research productivity peaked following the declaration of the pandemic and first wave in Mar- Apr 2020. Systematic synthesis of a large volume of COVID-19 literature revealed the global research landscape highlighting focus on the study of outcomes in cancer patients.[Table: see text]
Python-based preprocessing for applying machine learning in breast cancer metastasis prediction.
Authors: Rostom Yousri A. , Abd-El-Moneim Salah-Eldin , Labib Nevine Makram , Gharib Samia , Shaker Marwa , Mahmoud Nayera
Published: June 2021

e13558

Background: Artificial intelligence (AI) and machine learning (ML) have outstanding contributions in oncology. One of the applications is the early detection of breast cancer. Recently, several ML and data mining techniques have been used for both detection and classification of breast cancer cases. It is found that about 25% of breast cancer cases have an aggressive cancer at diagnosis time, with metastatic spread. The absence or presence of metastatic spread largely determines the patient’s survival. Hence, early detection is very important for reducing cancer mortality rates Methods: This study aims at applying ML and data mining, using AI techniques, for exploring and preprocessing breast cancer dataset, before building the ML classification Model for breast cancer metastasis prediction. The model will be implemented for mass screening, to prioritize patients who are more likely to develop metastases. A dataset of breast cancer cases was provided by the Oncology and Nuclear Medicine Department, Faculty of Medicine, Alexandria University. It contains clinical records of 5236 patients, diagnosed with breast cancer. ML libraries in Python programming language was used to explore the dataset and determine ratio of missing data, define data types, redundant data, and specify class label and predictors that to be used for the classification model. Results: In this work, the results showed that missing data ratio in some columns exceeds 90%, there are redundant features to be eliminated, data type conversion and feature reduction should be applied to prepare the data. Conclusions: Based on the previous findings, it is recommended to use ML preprocessing python libraries to prepare the dataset before building ML classification model of breast cancer metastasis prediction.
Type of tissue biopsy and outcomes in diffuse large B-cell lymphoma (DLBCL).
Authors: Desai Sanjal , Mwangi Raphael , King Rebecca L. , Maurer Matthew J. , Cerhan James Robert , Feldman Andew L. , Habermann Thomas Matthew , Mou Eric , Farooq Umar , Thompson Carrie A. , Wang Yucai , Witzig Thomas E. , Nowakowski Grzegorz S.
Published: June 2021

e13569

Background: Progress in understanding the molecular biology of DLBCL has led to development of complex molecular classifications that rely on sequencing methods. These molecular clusters are defined by activation of distinct pathways and may aid in selecting targeted therapy. In the molecular era, tissue requirements in clinical trials have increased to ensure sufficient tissue for molecular testing, potentially resulting in bias for enrollment of patients with larger excisional biopsies (EB). We examined the impact of tissue biopsy method on outcomes of DLBCL in a prospective observational study. Methods: Consecutive adult patients with DLBCL within 9 months from their initial diagnosis were enrolled into the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). Demographics, clinical variables, type of tissue biopsy (EB vs. core needle biopsy (CNB)) for initial diagnosis and initial treatment were recorded at baseline. Pts were contacted every 6 months from the date of diagnosis for first 3 years and then annually thereafter. Study objectives were event free survival (EFS) and overall survival (OS) by tissue biopsy method. Results: A total of 1061 patients with newly diagnosed DLBCL, from 2002 to 2015, were included. The table lists baseline characteristics of the cohort. 593 (56%) pts underwent EB and 468 (44%) underwent CNB for initial diagnosis. A significantly higher proportion of patients receiving CNB had performance status >=2, advanced stage, high risk disease by international prognostic index (IPI), abnormal lactate dehydrogenase. Median time from diagnosis to treatment initiation (DTI) was significantly shorter in the CNB group (13 days) than EB group (19 days). 2-year EFS (60% vs 75%, HR 0.75 (0.6-0.9), p <0.01) was significantly lower in CNB than EB group. There was a trend towards lower OS (75% vs 80%, HR: 0.8 (0.6-0.95), p =0.049) in CNB than EB group. Conclusions: Patients undergoing CNB are more likely to have higher risk disease, shorter DTI and survival compared to those undergoing EB. A need for large amount of diagnostic tissue in biomarker driven clinical trials may result in disproportional exclusion of high risk DLBCL pts who have inferior outcomes after standard treatment and could potentially benefit from novel agents, resulting in overperformance of the control arm. The need for tissue must be carefully balanced against resulting selection bias.[Table: see text]
Conflicts of interest (COI) among the UpToDate oncology management authors.
Authors: Chengappa Madhuri , Desai Aakash , Go Ronald S. , Poonacha Thejaswi K.
Published: June 2021

e13573

Background: UpToDate is an evidence based clinical resource designed to provide current clinical information. It is a widely used clinical practice tool providing evidenced based recommendations for diagnosis, management, and therapy. The extent of COI among the UpToDate authors has not been well studied. Our study evaluated the extent of COI of UpToDate authors involved in medical management recommendations for the 10 most common cancers in United States. Methods: We examined the latest November 2020 version of the UpToDate clinical management recommendations for 10 most common cancers. Using disclosure lists, we catalogued COIs for participants in each work group. The categories included: Category I- Grant/Research/Clinical Trial Support; Category II- Consultant/Scientific Advisory Boards/Expert witness; Category III- Speakers Bureau; Category IV- Equity Ownership/Stock Options/Patent holder/Employment/Other Financial Interest; and Category V- Spouse/Domestic Partner/Dependent Potential Conflict. We cataloged the companies/institutions involved in each disclosure. An “episode” describes 1 instance of participation of an individual in 1 company in 1 category for each cancer section. Results: There was a total of 207 authors including section and deputy editors of oncology management section. All authors completed their COI disclosures (100%). 128 (62%) of a total of 207 individuals reported COIs. A total of 1343 episodes were disclosed. We found that each author had an average of 10.49 episodes overall. Authors involved in Category I, II, III, IV & V were 6.3%, 13.5%, 3.2%, 4.7% and 1.6% respectively. 29.36% authors were involved both in Category I and II. A total of 672 company affiliations were associated with COI disclosure. AstraZeneca (6.10%), Merck (4.31%) and Novartis (2.68%) were the companies most frequently reported. The guideline with the maximum episodes (223) was prostate cancer. Conclusions: COIs are prevalent among authors of UpToDate clinical management recommendations. More than ½ of the participants disclosed at least 1 COI, but there appears to be a substantial number of experienced experts without COIs. Further research studies are necessary to determine the impact of these COIs on clinical practice patterns and resource utilization. Distribution of COI and total episodes.[Table: see text]
Advanced tumor progression detection by leveraging EHR based convolutional neural network boosting approaches.
Authors: Wei Guanhao , Zhou Li , Lu Lynn L , Steen Robert G
Published: June 2021

e13581

Background: Medical research in the areas of immunotherapies and targeted therapies has been drawing heavy attention and investment as the number of approved therapies continue to rise. Advanced findings on cancer treatment based on rich healthcare records help doctors to understand patient’s characteristics. The more accurate one can make a mathematical model predicting the likelihood of disease appearance, progression or treatment initiation, the better a proactive and effective targeting solution can be provided. Methods: Create positive/negative labels for patients who start to receive treatment or not within a time-sensitive window. Based on EHR records as Procedures, Prescription, and Diagnosis (PPD), patient’s feature interrelationship can be determined by a conditional probability matrix. Map PPD data to a well-designed patient-image profiles based a modified genetic algorithm to optimize and measure closeness. A Convolutional Neural Networks (CNN) model is then used to extract characteristics from patients’ feature image and learn the local patterns. Training the CNN model together with other upgraded AIML models is used to enhance overall prediction precision. Results: 144 different aggregated PPD features for patients with Chronic Lymphocytic Leukemia (CLL) were selected from the databases. Overall, the number of positive patients, who received treatment due to disease progression, is around 3% among 60K cases in each cohort, which is an extremely unbalanced dataset that is a challenge task for model training. In practice, we care about the model precision at k, which is the percentage of truly identified patients with k highest prediction scores. Comparing to common machine models like Random Forest, XGBoost and CatBoost, our proposed CNN model boosts the ensemble of baseline model performance in terms of average prediction precision at 1000 from 14.9% to 17.1%, which is about 15% relative percentage increase. Using this approach, many more truly identified patients could potentially receive targeted treatment on time. Patients’ top features and key feature interactions can also be identified as important references. Conclusions: The novel CNN boosting algorithm considers both aggregated PPD feature pairs using the graphical structure, significantly improves prediction model performance, and increases the model interpretability. In summary, the proposed model can help identify more potential patient candidates and determine precise treatment options.
Leveraging machine learning technology to efficiently identify and match patients for precision oncology clinical trials.
Authors: Sachse Laura , Dasari Smriti , Ackermann Marc , Patnaude Emily , OLeary Stephanie , Al-Olimat Hussein , Grigorenko Alexander , Stewart Andrew , Ward AnnaJane , Darmofal Annie , Ballakur Sowmya , Bennett William , Franzen Amy , Blau Sibel , Chandra Abhinav Binod , Nikolinakos Petros , Orsini James Michael , Peguero Julio Antonio , Blackwell Kimberly L. , Cooney Matthew M.
Published: June 2021

e13588

Background: Pre-screening for clinical trials is becoming more challenging as inclusion/exclusion criteria becomes increasingly complex. Oncology precision medicine provides an exciting opportunity to simplify this process and quickly match patients with trials by leveraging machine learning technology. The Tempus TIME Trial site network matches patients to relevant, open, and recruiting clinical trials, personalized to each patient’s clinical and molecular biology. Methods: Tempus screens patients at sites within the TIME Trial Network to find high-fidelity matches to clinical trials. The patient records include documentation submitted alongside NGS orders as well as electronic medical records (EMR) ingested through EMR Integrations. While Tempus-sequenced patients were automatically matched to trials using a Tempus-built matching application, EMR records were run through a natural language processing (NLP) data abstraction model to identify patients with an actionable gene of interest. Structured data were analyzed to filter to patients that lack a deceased date and have an encounter date within a predefined time period. Tempus abstractors manually validated the resulting unstructured records to ensure each patient was matched to a TIME Trial at a site capable of running the trial. For all high-level patient matches, a Tempus Clinical Navigator manually evaluated other clinical criteria to confirm trial matches and communicated with the site about trial options. Results: Patient matching was accelerated by implementing NLP gene and report detection (which isolated 17% of records) and manual screening. As a result, Tempus facilitated screening of over 190,000 patients efficiently using proprietary NLP technology to match 332 patients to 21 unique interventional clinical trials since program launch. Tempus continues to optimize its NLP models to increase high-fidelity trial matching at scale. Conclusions: The TIME Trial Network is an evolving, dynamic program that efficiently matches patients with clinical trial sites using both EMR and Tempus sequencing data. Here, we show how machine learning technology can be utilized to efficiently identify and recruit patients to clinical trials, thereby personalizing trial enrollment for each patient.[Table: see text]
Postmarketing requirements for drugs approved by the Food and Drug Administration for the treatment of solid tumor cancers, 2010-2019.
Authors: Jeune-Smith Yolaine , Zettler Marjorie E. , Fortier Stephanie , Rupard Skyler , Gajra Ajeet , Feinberg Bruce A.
Published: June 2021

e13597

Background: In recent years, efforts to improve the efficiency and speed of drug development and approval have driven a surge of Food and Drug Administration (FDA) approvals for cancer drugs. For many cancer therapies, the serious or life-threatening nature of the condition and unmet medical need confers eligibility for expedited programs. Many cancers are also rare diseases, and the increasing use of precision medicine principles to define cancer types further contributes to smaller trial sizes. With limited clinical evidence at the time of approval, cancer drugs may be subject to a greater burden of postmarketing requirements (PMRs). We analyzed PMRs for solid tumor therapies approved by the FDA over the past decade. Methods: The FDA’s novel drug approvals (2010-2019) were reviewed to identify drugs receiving primary approval for solid tumor indications. Approval letters were accessed via the Drugs@FDA database and analyzed for PMRs required under accelerated approval (AA), the Pediatric Research Equity Act (PREA) and the FDA Amendments Act of 2007 Section 505(o) (505(o)). Data are presented using descriptive statistics. Results: A total of 60 drugs received primary approval from the FDA for solid tumor indications between 2010 and 2019 (20 [33.3%] received AA, 33 [55.0%] received orphan designation, and 45 [75.0%] received Fast Track or Breakthrough Therapy designation). The proportion of drugs receiving AA doubled between the period 2010-2014 and 2015-2019 (Table). Of the 60 drugs approved, 52 (86.7%) received a total of 180 PMRs. All 20 drugs approved under AA received PMRs, with a total of 25 PMRs issued under AA. Data from new clinical trials were required for 22 (88.0%) of the 25 PMRs. No PMRs were issued under PREA. Additional safety data required under 505(o) comprised the largest proportion of PMRs; 155 total PMRs (86.1% of all PMRs) were issued for 45 (75.0%) of the drug approvals. Pharmacokinetic or other clinical safety data were required for 96 (61.9%) of the 155 PMRs. Conclusions: More than three-quarters of the cancer drugs approved for the treatment of solid tumors in the past 10 years were issued PMRs, with the majority requiring new safety data. The results of this study indicate that PMRs represent a critical mechanism by which FDA collects safety and efficacy for solid tumor therapies, and underscore the importance of PMR fulfillment. Post-marketing requirements (PMRs) for solid tumor drugs approved 2010-2019.[Table: see text]
Effect of digital technologies on mammographic screening in the Republic of Kazakhstan.
Authors: Saktaganov Murat , Kaidarova Dilyara , Zhylkaidarova Alma , Suleimenova Danara
Published: June 2021

e13601

Background: Since 2011 breast cancer (BC) has been the most common cancer in the Republic of Kazakhstan (RK) with the incidence of 43 per 100,000, and the third most common cause for cancer deaths with 9.4 deaths per 100,000 in 2019. Nationwide population-based screening program was implemented in the RK in 2008 inviting women aged 50–60 years every 2 years, with the subsequent expansion of the target group age to 40-70 years in 2018. The majority of screening mammography units was screen-film units at a time of program’s initiation. Gradual conversion to digital mammography (DM) has begun in 2014. This paper examines the impact of digital technologies on BC screening results on the example of the largest city in the RK - Almaty. Methods: We analyzed BC screening indicators such as incidence, mortality, proportion of early stage cancers, cancer detection rate. In order to assess the influence of transition to DM we divided the studied period to two stages: stage A (2008-2013)- when screen-film mammography (SFM) was widely used, and stage B (2014-2019)- when DM became prevalent in screening. Results: 598,058 women underwent BC screening from 2008 to 2019 in Almaty, 969 cancers were detected. At a time of program introduction in 2008 all 10 units used for screening were SFM units. The number of SFM units steadily increased from 10 in 2008 to 19 in 2014 and to 30 in 2019. Proportion of DM units concomitantly grew from 0% in 2008 to 47% in 2014 and to 83% in 2019. During the stage A 282 BC cases were detected (cancer detection rate 1 per 100,000 investigations). During the period B 687 BC cases were identified (cancer detection rate 2 per 100,000 investigations). Proportion of early stage cancers (0-I stage) rose from 26.7% in stage A to 41.0% in stage B. Widespread implementation of screening in 2008 led to a steady increase in BC incidence from 51 per 100,000 in 2008 to 63 per 100,000 in 2014. A noticeable decline in BC incidence has been evident since 2015 following 7 years of BC screening with incidence rate as low as 47.2 per 100,000 in 2019. Proportion of early stage BC among all newly diagnosed cases increased from 73.6% in 2008 to 86.6% in 2019. The average proportion of early stage BC was 77.5% for period A compared to 85,9% for stage B. Mortality rate was also affected by screening- it dropped by 38% from 20.6 per 100,000 in 2008 to 12.8 per 100,000 in 2019. Conclusions: BC state in Almaty reflects the general situation with BC in the whole country. Mammographic screening positively affected both BC incidence and mortality in Almaty. Increased utilization of digital technologies in screening resulted in rise in the proportion of early (0-I) stage BC by 21.4% and in the proportion of I-II stage BC by 13%. We suggest that, based on these results, further digitalization of mammographic screening should be strongly advised and digital to screen-film units ratio should be one of the main indicators for BC screening quality audit.
Key features to ensure sustainability of a tele-oncology program at a national cancer center.
Authors: Rariy Chevon , Truesdale Lynn , Greenman Jennifer , Schink Julian C.
Published: June 2021

e13613

Background: Prior to COVID-19, there were few telehealth services offered in the oncology specialty area. During the pandemic, we at a national cancer center rapidly scaled our oncology telehealth program to meet the needs of our patients. At the peak of the pandemic, telehealth initially served as a risk-mitigation strategy providing continued care to our patients while socially distancing, yet additionally, we have embedded necessary processes in place to create a sustained a telehealth oncology program that encompasses a hybrid model including face to face visits augmented with telehealth visits, where appropriate. Here we describe the key telehealth program features that have enabled a national cancer center to evolve into a hybrid model of oncology care across its five geographically distinct hospitals. Methods: Transitioning into a sustainable hybrid telehealth model of care involves a foundation of clinical leadership and partnerships among multiple departments. The telehealth oncology program leaders collaborate with the operations, technology, finance, clinical care teams, and governance council to implement telehealth growth initiatives and nimbly troubleshoot and ameliorate issues. A concierge service provides telehealth readiness checks to ensure timely resolution of issues. Workflows are followed to standardize processes. Telehealth use-cases ensure patients who need on-site services keep their in-person appointments, allowing telehealth visits for symptom management to enhance patient outcomes. A provider education session includes training on telehealth technology and “webside manner” training to ensure we preserve the personal touch with our patients in each telehealth encounter. Program data is regularly collected and reviewed to track the program’s success and opportunities for improvement. Results: After the initial peak of telehealth visits driven by the COVID pandemic, we continue to see a sustained 10-fold increase in service volume versus Jan/Feb 2020. There were 25,328 total telehealth visits from Mar. 2020-Jan. 2021, 75 clinical trial visits between July-Dec. 2020, and 848 readiness check escalations from Nov. 2020-Dec. 2021. Service lines expanded from 2 to 33, including growing rural health partnerships and a home chemotherapy infusion model. Use-cases expanded to bridge to on-site care, rapid initial visits, preop/postop checks, symptom management, and surveillance. Press Ganey patient satisfaction rates are as high as 92% and 90% of providers reported overall satisfaction with the telehealth consultations. Conclusions: Our key program features have enabled the growth and success of our enterprise tele-oncology program. One of the most promising indicators of success is the positive provider and patient satisfaction rates. Telehealth provides an effective means to provide a bridge to onsite cancer care even for our complex oncology patients.
Telehealth to increase access to transplant survivorship care for allogeneic stem cell transplant recipients regardless of distance to transplant center or neighborhood income.
Authors: Ahmed Nausheen , Fitzmaurice Sarah , Morey Cherie , Torres Tania , Beckman Darla , Ganguly Siddhartha , Bansal Rajat , Rodriguez Liza , Abdelhakim Haitham , Singh Anurag K , Abhyankar Sunil H. , Shune Leyla , Kribs Robert , Devine Clint , Hanses Jennifer , Mushtaq Muhammad Umair , McGuirk Joseph
Published: June 2021

e13615

Background: Transplant Survivorship Clinic at our institution serves to improve outcomes and overall health of allogeneic transplant survivors. The COVID19 pandemic allowed for growth of telemedicine in our program. We examine the patterns of use of telehealth and hypothesize that the use of telemedicine allowed continued access to care compared to the era prior to availability. We compared our transplant survivorship clinic data from July- December 2020, when telehealth was well established and compared to July-December 2019. Methods: All patients seen by the survivorship team for end of treatment visits, graft versus host disease assessments and survivorship visits annually between July-December 2019 and July-December 2020 were included. Their zip codes were used to get direct distance to survivorship clinic, average drive time, driving distance and average household income as in zip-codes.com database. Results: Total number of office visits in July-Dec 2019 was 163 visits (0% via telehealth) and in July-Dec 2020 was 228 (66.2% via telehealth). All encounters (telehealth and office visits) were lower in July and August 2020 compared to July and August 2019 but higher in months of September -December 2020 compared to 2019. Comparing all encounters during 7/2019-12/2019 to 7/2020-12/2020, there was no statistically significant difference in median age (58yr vs 60 yr), gender (males: 58% vs 59%), race (non-white: 11% vs 8.7%), median years from transplant (4yr vs 3 yrs), median income of patient neighborhood ($63,735 vs $60,465) and average drive time to center from zip code (40 min vs 51min). Comparison of patients who chose telehealth vs. office visit is summarized in table. While there was no statistically significant difference in age when comparing all encounters in 2019 and 2020, those who chose telehealth were younger (55yrs vs 60yrs, p=0.003). Conclusions: There were higher patient encounters in the 2020 period compared to 2019. Most of these 2020 encounters were via were telehealth, demonstrating the role of telehealth in increasing access. Younger patients appeared to choose telehealth, but telehealth served patients up to the age of 77 yrs. Utilization of telehealth appeared to be irrespective of demographics such as gender, neighborhood income and driving distance to the center. Comparison of telehealth vs office visit for July-December 2019 and 2020.[Table: see text]
Virtual health in cancer care: Results from a semi-structured interview-survey of oncology health care providers.
Authors: Le Dan , Brain Amanda , Shenkier Tamara Nina , Ingledew Paris-Ann
Published: June 2021

e13618

Background: The COVID-19 pandemic has compelled an increased use of virtual care delivery models in oncology. This study sought to examine the views of oncology health care providers (HCP) in British Columbia on the value and impact of virtual care models in clinical practice. Methods: A semi-structured interview-survey was developed to compare provider practice patterns between May 2019 and May 2020. Questions were designed to determine provider-perceived value and impact of virtual visits on clinical interactions with patients. HCP (including physicians, dentists, and nurse practitioners) at BC Cancer were invited to participate. Responses to the interview questions were de-identified and HCP names were replaced with a study code. Quantitative questions were interpreted with descriptive statistics. Qualitative results were analyzed and iteratively coded by multiple reviewers for emerging themes. Results: Among 531 invited participants, 61 completed the interview-survey and 60 were included in the final analysis. Of those interviewed, 47% were radiation oncologists and 33% were medical oncologists. The remainder of HCP interviewed (n = 12) included functional imaging physicians, general practitioners in oncology, hereditary cancer physicians, nurse practitioners, palliative care physicians, psychiatrists, and surgical oncologists. Most oncology providers (87%) desired the continuation of virtual visits as part of their clinical practice so long as barriers to integration were addressed. Barriers identified included limited access to physical resources, such as hardware (70% responses) and quiet spaces (54% responses), insufficient logistic support such as information technology services (84% responses) and operational workflows (46% responses), the absence of guidelines to select patients for this delivery model (38% responses), and concerns regarding HCP liability, security and privacy (30% responses). Conclusions: Oncology HCP value delivering patient care through virtual means, however, barriers to implementation must be better understood. These data may inform continued use and implementation of virtual care at other oncology centers.
An analysis of the reasons and motives of patients seeking telehealth-based second opinion for cancer.
Authors: Rajan Rejil , Jotwani Amit Kumar , Poovaiah Thirtha , Goud Rakesh Shankar , Waghmare Rama , Gururao Shashidhar
Published: June 2021

e13621

Background: Incidence of cancer is rising with each passing year in India and a majority number of patients get diagnosed in later stages of disease that leads to poor outcomes. Studies have reported that patients and their caregivers feel the need to get more information about their treatment options making them opt for second opinions due to need for reassurance or inadequate time for communication with their treating oncologists. We sought to analyse the primary concerns and motives of patients seeking second opinion services through onco.com. Methods: A cohort of 918 eligible patients who availed online multidisciplinary tumour board opinion through Onco.com was included in the study. We analysed the primary concerns of 918 eligible patients who availed online second opinion through onco.com between January 2019 & December 2020. We looked at the specific questions they had for the multidisciplinary panel of oncologists. We also correlated the concerns with the stage of disease to understand if there was a variation for different stages of disease. Results: Of the total 918 patients, 864 had solid malignancies, out of which 16% had early (stage 1 & 2) disease, 27% had locally advanced (stage III) disease, 47% had metastatic disease & and 16% had recurrent disease. The most frequent motive for seeking a second opinion was the need for validation of ongoing treatment (72.5%) followed by enquiry for more advanced treatment options (37%), and to know any alternative treatment options (19%). Interestingly, only a minority of all patients were keen to know about clinical trials (3%). Conclusions: Our findings suggest that validation of ongoing treatment is the most frequent motive for patient driven second opinions in oncology. There was minimal interest to seek clinical trial options among patients, which could be due to general lack of awareness about clinical trials and some form of stigma associated with clinical trials due to negative perceptions and fears about adverse events. [Table: see text]
Consistency of O6-methylguanine-DNA methyltransferase in intracranial and extracranial lesions and the therapeutic effect of temozolomide in patients with advanced lung cancer and brain metastasis.
Authors: Fan Ying , Shan Qian Yun , Gong Jia Li , Han Na , Lu Hongyang
Published: June 2021

e14001

Background: Targeted drugs have made a major breakthrough except small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) of brain metastasis (BM) patients with negative driving gene. Because of the difficulty to obtain pathology of intracranial metastases lesions and the low acceptance of patients, the heterogeneity of O6-methylguanine-DNA methyltransferase (MGMT) between extracranial lesions and intracranial metastatic lesions worth exploring. Methods: 10 patients were administered TMZ after the progression of radiotherapy and chemotherapy and included in one group; the efficacy and safety of TMZ were assessed. Moreover, 15 patients who underwent resection of the lung and brain without neoadjuvant therapy formed another cohort. The promoter methylation status of MGMT was analyzed and compared in the paired primary and BM lesions. Results: The overall response (OS) rate of TMZ was 50% and the disease control rate was 80% in patients with BM lesions. The median progression-free survival was 13.6 months, and the median overall survival was 18.9 months after a median follow-up of 120 months. No grade 3 or higher side effects were reported, but grade 1 or 2 side effects, such as leucopenia, nausea, or vomiting, occurred. However, in another cohort, MGMT promoter methylation was detected in 2 patients (with primary lesions; unmethylation was detected in BM lesions, and the methylation status of MGMT promoter was consistent in paired primary and BM lesions).Conclusions: TMZ was effective against SCLC and NSCLC combined with BM having negative driving genes. Whether primary lesions can replace the MGMT methylation level of BM lesions, as well as the consistency of the promoter methylation status of MGMT in patients with advanced lung cancer, needs exploration.[Table: see text]
Progression of tumors with development of cerebral metastases is accompanied by suppression of thyroid and glucocorticoid functions.
Authors: Bandovkina Valeria A. , Frantsiyants Elena M. , Salatova Ayna M. , Kharagezov Dmitry A. , Kit Oleg I.
Published: June 2021

e14005

Background: Cutaneous melanoma (CM), breast cancer (BC) and lung cancer (LC) metastasize to the brain most frequently. Early diagnosis of cerebral metastases is challenging and requires new prognostic criteria. Imbalance of thyroid and glucocorticoid hormones changes the growth and development of malignant tumors. The purpose of the study was to identify readily available prognostic criteria for cerebral metastases in cancer patients at various stages of treatment and follow-up. Methods: Blood levels of cortisol and total triiodothyronine (tT3) were determined by RIA (Immunotech, Czech Republic) in patients with BC (n = 50), LC (n = 50) and CM (n = 50) without brain metastases and in patients with BC (n = 25), LC (n = 25) and CM (n = 25) with cerebral metastases. Results: Blood levels of cortisol in BC, LC and CM patients were normal in 63-84% and elevated on average by 1.7 times in 16-37%. Levels of tT3 in LC were normal, and in BC and CM – within the normal limits, but 1.3 times lower than the mean values. In patients with cerebral metastases, cortisol was lower than the norm by 4.9, 2.5 and 3.6 times in 36% BC, 75% LC and 45% CM cases, respectively. Levels of tT3 in all patients with cerebral metastases were lower than the norm or values in patients without metastases by 2 times and lower. Conclusions: Decreased levels of both cortisol and tT3 in patients with BC, LC and CM may serve as one of prognostic markers of possible development of cerebral metastases. The dynamic determination of levels of thyroid and glucocorticoid hormones is required in cancer patients at various stages of treatment and follow-up.
Outcomes of ER, PR, HER2, and triple-negative mutated breast cancer with brain metastasis.
Authors: O'Shea Patrick Joseph , Tatineni Vineeth , Rauf Yasmeen , Jia Xuefei , Murphy Erin Sennett , Chao Samuel T. , Suh John H. , Peereboom David M. , Ahluwalia Manmeet Singh
Published: June 2021

e14009

Background: Breast cancer is the second most common cause of metastatic brain tumors. The presence of estrogen receptors (ER), and progesterone receptors (PR), and HER2 receptors have been used to guide both hormonal and targeted therapies for breast cancer. The presence or absence of these receptors may impact patient outcomes in breast cancer brain metastasis (BCBM). Methods: Patients with BCBM and known tumor marker status treated at our tertiary care center from 2010-2019 were evaluated. Overall Survival (OS) was measured from diagnosis of BCBM to date of death or last follow up. Many of these patients received multiple lines of treatment including hormonal and targeted therapies at some point during their care. The Cox proportional hazard model was used to determine differences in OS. Results: 137 patients with BCBM were included. Of these, 48 were ER or ER/PR positive (ER+), 3 were PR positive (PR+), and 47 were HER2, HER2/PR, HER2/ER, or HER2/ER/PR positive (HER2+), and 37 were triple-negative. For ER+ tumors the median age at diagnosis was 60 years (Interquartile range (IQR) 31-87) and 86% were white. For PR+ tumors the median age at diagnosis was 67 years (IQR 66-74) and 75% were white. For HER2+ tumors the median age at diagnosis was 55 years (IQR 31-84) and 79% were white. For triple-negative tumors the median age at diagnosis was 56 years (IQR 34-91) and 83% were white. OS for ER+, PR+, HER2+, and triple-negative patients had a median of 57.7, 19.8, 137.4, and 54.6 months and a 2-year rate of 76%, 33%, 82%, and 73%, respectively. With ER+ patients as a reference, PR+ patients had an OS hazard ratio of 1.49 (95% CI = 0.35 - 6.23, p = 0.59), HER2+ patients had an OS hazard ratio of 0.62 (95% CI = 0.36 - 1.06, p = 0.082), and triple-negative patients had an OS hazard ratio of 0.92 (95% CI = 0.54 - 1.57, p = 0.77). Conclusions: HER2+ tumors were associated with an increase in OS when compared to ER+, PR+, and triple-negative tumors in patients with BCBM. The OS of the other three tumor marker groups was not significantly different from one another. Further studies need to be done within tumor marker cohorts to determine the most effective treatments within those cohorts.[Table: see text]
Successful salvage therapy with cetuximab-based modalities in the non-sensitive EGFR-mutant lung cancer patients with leptomeningeal metastasis who have heavily pretreated histories.
Authors: Wu Jinchun , Zhao Jie , Li Xiangping , Zhang Jin , Zeng Shan , Zhou Rongrong , Li Bin
Published: June 2021

e14011

Background: Leptomeningeal metastasis (LM) is the deadliest complication of lung cancer. No standard therapy for the LM harbor non-sensitive epidermal growth factor receptor (EGFR)-mutant|(neither E19 del, E21 p.L858R nor E18 p. G719X mutation ). Previous studies showed cetuximab held the potential for treating the EGFR mutants who had failed 2 or more lines of standard cytotoxic chemotherapy and reversible EGFR TKIs. Methods: We screen the lung cancer patients with LM treated with Cetuximab-based regimen from July 1st, 2020 to Dec 31th 2020. The medical records were retrospectively reviewed and analyzed. Results: Three lung cancer patients with LM were included. All of them were heavily pretreated with various TKIs, chemotherapy, or/and with antiangiogenesis and PD-1 antibodies. When they were referred to our department, all these patients were in severe medical conditions. Case 1 has severe multiple cranial nerve impairment with cauda equina syndrome and massive malignant pleural effusion. Case 2 has intensively violent headaches with vomit and lumbosacral pain due to more than 500mm H2O of intracranial hypertension. Case 3 has acute pancreatitis due to oppressive obstruction of pancreatic duct by multiple metastatic tumors. The molecule test of tumor tissue or liquid from malignant pleural fluid have revealed E20 p.C797S in cis with p.T790M accompanied E19 del of EGFR gene in case 1, E21 p. R831H with E19 p.L747P of EGFR gene in case 2, and E20 p.S768_D770dup of EGFR gene in case 3, respectively. Their therapies were changed to cetuximab combined with TKI of afatinib or osimertinib, and local treatment including local radiation, intraventricular pemetrexed administration, or with intrathoracic drain. The disease control rate (DCR) was 100% of one partial remission (PR) and two stable disease (SD). The intracranial response was also observed in all the 3 patients showing CSF cytology turning negative or enhanced meningeal disappearance in MRI image with obviously relieved headache or/and improved cranial nerve palsy. The performance status of two patients was largely improved from Karnofsky Performance Status (KPS) scoring 20 to 90 and 50, respectively, and that of the other patient was stable with KPS scoring 50. The side effect is manageable skin rashes (grade II-III). Until this abstract was written, all the 3 patients were still alive. Conclusions: Cetuximab-based systemic therapy combined with local treatment demonstrated preliminary clinical activity in the rare EGFR-mutant lung cancer with LM who have already undergone heavily previous therapy, warranting further investigation.
Upfront stereotactic radiosurgery for brain metastases from triple-negative breast cancer.
Authors: An Ran , Wang Yan , Wang Fuchenchu , Singareeka Raghavendra Akshara , Gao Chao , Amaya Diana , Ibrahim Nuhad K. , Li Jing
Published: June 2021

e14014

Background: Triple-negative breast cancer (TNBC) is an aggressive subtype with high propensity of brain metastases (BM). Outcomes after upfront stereotactic radiosurgery (SRS) for BM from TNBC patients are not well defined. We evaluated outcomes and identified prognostic factors for such patients. Methods: We reviewed 57 consecutive patients treated with upfront SRS for BM from TNBC in May 2008–April 2018 at a large-volume cancer center. Endpoints were overall survival (OS) from BM diagnosis and freedom from BM progression (FFBMP) after initial SRS. BM progression was defined as local and/or distant brain failure (LBF or DBF) after initial SRS; LBF was radiographic progression of treated lesions, assessed by a neuroradiologist or treating physician excluding post-radiation changes or radiation necrosis. Kaplan-Meier and Cox proportional hazard regression analyses were used to estimate survival outcomes and identify prognostic factors. Results: In this cohort of 57 patients with a median age of 53 y (range 26–82) at BM diagnosis and follow-up time of 12.2 months (mo, range 0.8–97.5), median time to BM development from TNBC diagnosis was 23.7 mo (range 0.7‒271.1). Estimated median OS time from initial BM diagnosis was 13.1 mo (95% CI 8.0‒19.5). In univariate analysis, Karnofsky performance score (KPS) > 70 (p = 0.03), having < 3 BMs (p = 0.016) at BM diagnosis, and BM as first site of metastasis (p = 0.041) were associated with longer OS. On multivariate analysis, KPS ≤70 was associated with higher risk of death (HR 3.0, p = 0.03). Of 46 patients with imaging follow-up for FFBMP assessment, 29 (63%) developed BM progression after initial SRS with an estimated median FFBMP of 7.4 mo (95% CI 5.7–12.7). Median times to LBF and DBF were 10 mo (range 0.3–97) and 5.9 mo (range 0.3–90.8). Estimated cumulative LBF rate was 17.8% (95% CI 2%–31.1%) and DBF 61.1% (95% CI 40.8%–74.4%) at 12 mo. Number of BMs at BM diagnosis (≥3 vs < 3) was not associated with FFBMP (p = 0.7). Of the 29 patients with BM progression, 5 did not receive salvage radiation therapy (RT) and 24 received salvage RT (SRS, whole-brain radiation [WBRT], or both SRS+WBRT). Receipt of salvage RT was associated with longer survival (median 21.7 mo vs. 7.0 mo for no salvage RT, p < 0.0001) and did not differ by type of salvage RT (median OS 18.6 mo for WBRT; 26.2 mo for SRS+WBRT; 35.9 mo for SRS, p = 0.08). Conclusions: We reported a median OS of 13.1 mo and FFBMP of 7.4 mo in TNBC patients with good local control. Good KPS was independent prognostic factor for better OS. FFBMP did not differ by number of SRS-treated brain lesions ( < 3 vs ≥3). Further prospective studies of larger numbers of patients needed for more accurate comparisons of treatment types.