bluuebunny/crossref_metadata_2025_split huggingface dataset:
A simulation study of loss to follow up: The impact on time to event and prevention.
Authors: Levy Donna Elise , Wu Bingyan , Quinn Daniel , Jentzsch Sophie , Lusk Christine , Bentley Jane Kristina 
Published: May 2020

e14097 Background: Patient attrition during study follow up is a concern in all clinical trials, although its impact on study results has rarely been assessed. In oncology, in particular, where studies are lengthier and may be extended into longitudinal studies, there is an increased likelihood of loss to follow up (LTFU) (Gill et al., 2018). This creates a heightened need to understand how it affects the trial’s validity. The loss of data from patients who have been LTFU can reduce a study’s precision and power. This imprecision not only impacts the results of the current study but can also affect future research as well as future patient treatment options. Studies have found that participant characteristics differ in individuals LTFU as compared to those who remain in follow up (Childs et al., 2011; Geng et al., 2008; Hochheimer et al., 2016). This further emphasizes how attrition can skew study results and their interpretation and supports the need to minimize patient attrition during follow up in order to reduce bias and generate robust study estimates. Methods: This study assessed the impact of LTFU rates on the study estimates through simulations using SAS software. While all endpoints can be affected by LTFU, this study assessed time-to-event endpoints. Exponential distribution was assumed with varying rates of LTFU. In addition, the work covered suggestions for reducing LTFU. Results: Even for low rates of LTFU, biases are introduced in time-to event endpoints. Conclusions: Researchers should make every effort to minimize the extent of LTFU in the design and of and conduct of their trials.
Optimizing cancer care using digital technologies requires coordinated multi-stakeholder effort.
Authors: Ramalingam Sendhilnathan , Holmgren A Jay , Goldsack Jennifer , Conner-Simons Adam , Robinson Edmondo 
Published: May 2020

e14108 Background: Oncology has unique characteristics that predict early benefit from digital technologies including a culture of patient involvement in trials, genetic testing, and longitudinal assessments including objective measures. However, implementation of digital tools is slow for many reasons including lack of incentives/interoperability, and high-profile cases highlighting inadequate data governance. We report results from the Digital Medicine Society’s study of the stakeholders involved in using digital technologies to optimize health, with a focus on oncology. Methods: We performed 16 interviews with diverse Key Opinion Leaders (KOLs) including physicians, executives, senior government officials, patients, payers, tech innovators, and investors. KOLs received a pre-interview list of topics. We used the Delphi method, an evidence-based approach to compile expert opinions, to iteratively refine recommendations. Results: We identified priorities for 5 stakeholder groups to facilitate digital tool implementation (Table); all groups must also act now to develop a framework for data governance. We describe 4 categories of early success in oncologic digital tools: regimen/drug choice, drug approval efficiency, digital user training, and patient generated health data. Conclusions: Data and technology have great potential to improve cancer care. Multi-stakeholder involvement and a framework for US health data governance are needed. [Table: see text]
Social media and gynecologic cancers: The impact of Twitter #GYNCSM.
Authors: Lizaso Christina , Sparacio Dorinda , Westin Shannon Neville , Boulay Richard Mark , Temkin Sarah Madhu 
Published: May 2020

e14113 Background: Patients (pts) with gynecologic malignancies look for support and information outside traditional clinical settings. We report the results of a needs assessment of the GYN Cancer Social Media (#gyncsm) Twitter community. Methods: An online needs assessment was publicized on Twitter using the #gyncsm hashtag in 2019 for 23 days. Percentages were calculated to provide observational data. Results: Of 33 respondents, 26 (79%) were pts, 7 (21%) healthcare providers, 2 (6%) cancer researchers, and 1 (3%) caregiver. 15 (60%) pts reported having ovarian cancer; 6 (24%) endometrial/uterine cancer; 2 (8%) sarcoma; 2 (8%) breast cancer; and 1 (4%) vulvar cancer. Participating providers were gynecologic oncologists 3 (21%); pharmacists 2 (14%); medical and radiation oncologist, researcher, social worker therapist and genetic counselor 1 (7%) each. 41% (13) reported tweeting and retweeting #gyncsm tweets; 22% (11) read the blog posts or transcripts of a twitter chat; 28% (9) followed or participated in a twitter chat. Chat topics with importance are shown in the Table. Pts reported that #gyncsm twitter chat helped them advocate for themselves (9, 60%); learn about genetic testing (7, 46%); and investigate clinical trials (4, 26%). Conclusions: Social media has a role in healthcare, especially in pt education and empowerment. Side effects, toxicity, and communication were topics of interest. Inclusion of cervical cancer pts and rare malignancies should be a priority. [Table: see text]
Use of artificial intelligence to improve access to initial leukemia diagnosis in low- and middle-income countries.
Authors: Cerrato Tania Raquel 
Published: May 2020

e14117 Background: Disparities in access to cancer diagnostic methods affect especially low and middle-income countries (LMIC). Honduras, a country with limited resources of laboratory, and trained personnel to diagnose leukemia have an estimated incidence of leukemia of 5.8 per 100,000 person-years and the mortality is 4.8 per 100,000 person-years. This country has a single immunophenotyping center and similar to many other LMICs, the preliminary diagnosis of leukemia is performed by a morphological study of blood. Machine learning (ML) is a form of artificial intelligence (AI) that has the potential to improve medical attention in several medical fields. The purpose of this study is to evaluate the impact of ML use, as a method to reduce the time interval and the access to a diagnosis of leukemia in Honduras, where the current average time to perform an initial diagnosis of leukemia is from 2 weeks to 3 months. Methods: A quantitative correlational study was designed. With the help of local informatic developers, an automated image processing algorithm was designed, which was fed with a total of 1009, digital images of bone marrow aspirates and peripheral blood of patients with proven leukemia through immunophenotyping. The images were captured using a microscope Carl Zeiss lens with a 100x objective, the process included the segmentation of leukemia cells for its analysis. Bivariate outcomes were assessed using the Pearson chi-squared test. Results: From 2016 to 2018, a total of 341 samples of patients with any symptom of leukemia were included. After anonymization of patient identification, the samples were analyzed using our algorithm by comparing the cells with its database. Posteriorly, an expert hematologist performed an analysis of the sample. A total of 20 samples (5.8%), were diagnosed with a preliminary diagnosis of leukemia. Of the 20 samples, a total of 10(50%) were acute myeloid leukemia, 6 samples (30%) lymphoblastic leukemia and the remaining 4 samples (20%) were compatible with chronic myeloid leukemia. The average time to make an initial diagnosis of leukemia was 75% and 24% in 24 and 48 hours respectively. Local hematologists managed to make treatment decisions earlier with benefit to the patients. In 19 of the samples (95%), there was correspondence between the morphology diagnosis obtained by our algorithm and the immunophenotyping diagnosis. Conclusions: This preliminary study demonstrates that the use of artificial intelligence constitutes an important element to improve access and shortening of the time required to obtain a diagnosis of leukemia in LMCIs, and represents a method to reduce disparities in access to diagnosis of hematological cancers.
The use of patient health information outside the circle of care: Consent preferences of patients from a large academic cancer centre.
Authors: Liu Fei Fei , Tosoni Sarah , Voruganti Indu S , Wong Rebecca , Virtanen Carl , Willison Donald , Heesters Ann 
Published: May 2020

e14122 Background: Massive volumes of patient health information (PHI) are required to realize the anticipated benefits of artificial intelligence in future clinical medicine. To maintain public trust in medical research however, consent policies must evolve to reflect contemporary patient preferences. Methods: From January-December 2019, patients attending clinics at a large academic cancer centre were invited to complete a 27-item iPad survey on consent preferences. Survey items focused on: (a) broad vs. specific consent; (b) opt-in vs. opt-out approaches for research contact; (c) comfort sharing with different recipients; (d) perceptions on commercialization; and (e) options to track information use and study results. Demographic questions addressed cancer type, treatment stage, age, gender, ethnicity, education level, and household income. Results: A total of 222 participants were included in the analysis (112 males, 108 females; 2 rather not say); 83% were comfortable sharing PHI with researchers at their own hospital. While 56% of patients preferred broad consent, 38% preferred to be contacted with study details and asked to consent every time (specific consent); 6% prefer not to share at all. Younger patients ( < 49 years) most often chose specific consent (50%); significantly more than those 75+ years (24%; p < .05). Younger patients ( < 49 years) were also significantly more uncomfortable than older patients (50+ years) sharing even within their own hospital (13% uncomfortable vs. 1% uncomfortable; p < .05). A significant majority of patients (63%, p = .0001) preferred to be asked for permission before being entered into a contact pool vs. automatic entry with opportunity to opt-out. The majority of patients were uncomfortable sharing PHI with commercial enterprises (51% uncomfortable, 27% comfortable, 22% neutral). A significant majority expressed the desire to track who is using their PHI (61%, p < .0001), and be notified regarding study results (70%, p < .0001). Conclusions: While most patients were willing to share their PHI with researchers at their own hospital, many preferred a transparent and reciprocal consent process. These data also suggest a generational shift, wherein younger patients preferred more informed consent options. Modernizing consent policies to reflect increased patient interest in the exercise of their autonomy is crucial in fostering sustained public engagement in medical research.
Reimbursement recommendations for cancer drugs supported by phase II evidence in Canada.
Authors: Li Regina , Mai Helen , Chiasson Kaitlyn , Trudeau Maureen E. , Chan Kelvin K. , Cheung Matthew C. 
Published: May 2020

e14133 Background: Historically, pharmaceutical companies submitted phase III evidence for consideration of public reimbursement; however, phase II data is being more commonly used as primary evidence. Whether submissions with phase II data lead to similar rates of positive reimbursement recommendations as phase III data has not been comprehensively investigated. We compared frequency of reimbursement recommendations between phase II and phase III submissions for oncologic drugs and assessed for factors associated with a positive or conditional recommendation. Methods: We identified all submissions with phase II data from the CADTH pCODR’s expert review committee (pERC) recommendations from July 2011 to July 2019. We identified fourteen binary variables relating to clinical benefit, patient-based values, economic impact, and adoption feasibility. We used Fisher’s exact test to characterize associations between all variables and the final recommendation. We conducted multivariable analysis with logistic regression for three variables: feasibility of phase III study, hematologic indication, and unmet need. Results: We identified 139 submissions with a pERC final recommendation. Twenty-seven (19%) submissions were supported by phase II evidence, with 63% having a positive recommendation in comparison to 82% among submissions with phase III evidence. Clinical benefit (p < 0.001), gap in current treatment standards (p = 0.047), and patient alignment (p = 0.015) were associated with a positive recommendation, whereas the future feasibility of conducting a phase III study was associated with a negative recommendation (p = 0.040). No significant association was found between the recommendation and factors related to cost effectiveness or adoption feasibility. In multivariable analysis, only feasibility of a phase III study was significantly associated with a negative recommendation (p = 0.024, OR = 0.132). Conclusions: Oncologic submissions with phase II data were less likely to be recommended for public reimbursement than phase III studies. Positive or conditional recommendation was more likely if they demonstrated clinical benefit and aligned with patient values. pERC was less likely to recommend a submission with phase II if a phase III trial was either possible or already initiated.
Saudi Cancer Patient Experience: Benchmarking a single center report to the United Kingdom National Experience.
Authors: Jradi Hoda , Alharbi Alanood Abdulaziz , Alrashed Maali Omar , Alshoaibi Mishael Ali , Alkaiyat Mohammad , Jazieh Abdul Rahman 
Published: May 2020

e14138 Background: Diagnosis and treatment of cancer are regarded as stressful experiences impacting the patients and their families. This study aims at comparing the Saudi cancer patient experience with the United Kingdom cancer patient experience throughout their continuum of care. Methods: Results from the United Kingdom (UK) National Cancer Patient Experience Survey (NCPES 2017) were compared to the reported results from the experience of 100 cancer patients for the same year at the National Guard Health affairs Health system in Riyadh, Saudi Arabia. Similar concepts relating to the experience were investigated and compared. Results: Compared to the UK survey, the Saudi survey had mainly higher score regarding receiving an overall positive cancer care. Scores related to provision of clear answers to all important questions, judging the hospital staff as always working well together, and family members being given the opportunity to communicate with the doctor were significantly higher among Saudis. The UK patient scored significantly higher on receiving information about diagnostic tests, treatment side effects, and discharge instructions, and being informed about support groups and on-going cancer research. Conclusions: The overall experience of the Saudi cancer patients compared favorably to the UK cancer patients; however, in the domain of information provision as an essential part of the cancer experience is still lacking in the Saudi cancer care approach. Quality improvement should focus on the findings of this study for better health outcomes. [Table: see text]
Substantial ninety-nine percent reduction of turnaround time for QTc diagnostics using smartphone-based tele-cardiology.
Authors: Fink Lena-Sophie , Schinkoethe Timo , Wuerstlein Rachel , Harbeck Nadia 
Published: May 2020

e14155 Background: Numerous anti-cancer drugs may lead to long QT syndrome as a cardiotoxic side effect, which could lead to sudden cardiac death. But the outcome of a long QT syndrome is not necessarily fatal. When diagnosed and managed in time, prolongation of the QT interval is reversible. Regular QT interval assessment is, therefore, necessary to ensure the optimal care for these patients. Evaluation of the QT interval requires timely support of the attending oncologist by a cardiologist. The idea for the presented solution was to replace the conventional interaction between oncologists and cardiologists by a smartphone APP solution supporting single-lead ECG records directly at the cancer center and sent from APP to APP to a cardiologist for immediate diagnostic (named as ‘QTc Tracker’). Methods: 54 cancer centers in Germany were equipped with the ‘QTc Tracker’ and a connected single-lead ECG device. Before implementation, all participants were asked in a structured interview about their routine ECG workflow, turnaround time, and satisfaction. After implementation, the centers were contacted again for a comparative evaluation of the turnaround time and satisfaction. Results: The mean total turnaround time of the routine QT/QTc evaluation was 140 h (± 333 h, range 0.3 - 1993 h). 25 cancer centers had direct access to a cardiologist. In these centers, the mean turnaround time was 1.2 h (± 1.3 h, range 0.33-6.5 h), whereas 9 centers with a cardiologist but no direct access needed a mean of 78 h (± 74 h, range 24-192 h). Centers without a cardiologist needed a mean of 354 h (± 490 h, range 24-1993 h) to receive their ECG report. Using the QTc Tracker APP, the mean turnaround time for all centers went down to 47 minutes. Conclusions: A reduction of the mean ECG turnaround time from 140 h down to 47 minutes equals a reduction of 99 %. This also enables centers without a cardiologist on site to provide the QT/QTc report within a single patient visit. Having the ECG result on the same day reduces uncertainties for the patients, and increases treatment continuity and patient safety. In particular as a regular side-effect monitoring, this application promises more convenience for patients and their physicians. The tool is currently integrated in several phase III-IV clinical trials in Germany.
The next generation of cerebrospinal fluid (CSF)-based molecular diagnostics: Improving sensitivity and actionability in breast and lung cancer patients with CNS involvement.
Authors: Singh Veena M. , Fisher Deanna M , Berz David , Schultz Robbie , Mayer Julie A , Boorgula Smitha , Nguyen Minhdan , Troung Judy , Dobrawa Lucia , Gill Jaya , Carrillo Jose Arganda , Kesari Santosh 
Published: May 2020

e14502 Background: Liquid biopsy has emerged as a minimally invasive and cost-effective strategy to assess cancer biomarkers without the risk of complications associated with surgical biopsies. Once a tumor has metastasized to the brain, circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) can be found in the cerebrospinal fluid (CSF). We analyzed CSF samples from patients(pts) with primary lung or breast cancer with either brain (BM) or leptomeningeal metastases (LM). Here we report the analytical and clinical validation of Target Selector CSF assays. Validation testing included pre-analytical and analytical steps. Methods: CSF was collected prospectively from pts with a prior solid tumor diagnosis and suspected BM or LM. CTCs were captured utilizing a primary ten antibody cocktail followed by biotinylated secondary antibodies that bind selectively to CTCs followed by staining with cytokeratin (CK), CD45, streptavidin and DAPI. CTCs were captured in a microfluidic channel,classified as either CK+ or CK-. Cell-free total nucleic acids (cfTNA) was extracted from CSF supernatant and underwent both Target Selector™ single gene and next-generation sequencing (NGS) lung and breast multi-gene testing to assess for molecular alterations. For NGS, data analysis was performed using Torrent Suite with annotation and curation by Ion Reporter and Oncomine Knowledgebase Reporter software. Results: The Target Selector CTC platform assays performed on clinical samples (n = 89) resulted in clinical accuracy = 85.4%, clinical precision (intra-assay, inter-assay, inter-operator, and inter-instrument) = 100% for each measure, clinical sensitivity = 80.0%, clinical specificity = 96.6%, positive predictive value (PPV) = 98%, negative predictive value (NPV) = 70.0%, and analytical specificity = 96.0% (acceptance criteria was 95%) at a limit of detection of 2 CTCs. For molecular analyses, Target Selector™ platform assays resulted in clinical accuracy = 87.4%, clinical sensitivity = 85.2%, clinical specificity = 88.3%, PPV = 76.7%, and NPV = 93.0%. Conclusions: Target Selector is a viable, sensitive, reproducible platform for CTC detection and molecular analysis of CSF samples from patients with breast or lung cancer with CNS metastases especially as the sensitivity of CSF cytology is low and MRI findings can be equivocal. Identifying CTCs and molecular alterations can help characterize both tumor genomic evolution as well as guide treatment following cancer metastasis to the CNS.
Institutional outcomes of whole brain radiotherapy for metastatic melanoma brain metastases.
Authors: Jiang Cecilia , Switchenko Jeffrey M. , Lawson David H. , Yushak Melinda Lynne , Khan Mohammad Khurram 
Published: May 2020

e14504 Background: The management of melanoma with multiple brain metastases (MBM) is complex given improvements in targeted agents, immunotherapy, and radiotherapy. Whole brain radiation therapy (WBRT) is a radiotherapy technique with limited outcomes data. We report our institutional outcomes for MBM patients receiving WBRT and assess whether certain clinical factors impact prognosis. Methods: A retrospective review of a single institution database was performed. Patients diagnosed with MBM from 2000-2018 treated with WBRT, with or without systemic treatments, were included. Post-WBRT brain MRI scans were assessed at timed intervals for radiographic response. Clinical and treatment variables associated with overall survival (OS), progression free survival (PFS), intracranial failure-free survival (IFFS), and local failure-free survival (LFFS) were assessed. Data was collected on radiation-induced side effects, including radionecrosis, hemorrhage, and memory deficits. Results: Of 1347 patients treated with WBRT from 2000-2018, 63 patients had melanoma. 69% of patients had ≥5 brain metastases at the time of WBRT, 68% had extracranial disease, and 71% received steroids during their overall treatment course. Most had received previous therapies and had WBRT as a last resort. Median WBRT dose was 30 Gray over 10 fractions. Median follow-up was 4.0 months. Six-month OS, PFS, IFFS, and LFFS were 52.7%, 20.4%, 52.3%, and 43%. Median OS, PFS, IFFS, and LFFS were 7.0 months, 2.2 months, 6.1 months, and 4.9 months. Performance status correlated with OS on univariate and multivariate analysis. BRAFi was the only systemic therapy to significantly impact OS on univariate analysis (HR 0.24, 95% CI 0.07-0.79, p = 0.019), although this was not seen on multivariate analysis. There was a 19% rate of memory deficits. Among the 46 patients with post-WBRT brain scans, 17% had radionecrosis and 28% had intralesional hemorrhage. Not all radiographically noted radiotoxicities were clinically significant, although hemorrhage decreased IFFS on both univariate and multivariate analysis. Conclusions: Outcomes for MBM patients receiving WBRT indicate that WBRT remains a worthy option to control intracranial disease. Treatment-related effects such as hemorrhage, necrosis, or cognitive changes are considerations. Median PFS and IFFS suggest that systemic disease control continues to be the greater issue. The role of WBRT should be re-evaluated in the modern era, which features advanced imaging detection ability, newer systemic agents, and improved steroid avoidance strategies.