tbuckley/cabot-search huggingface dataset:
BrainApp: Using near-patient sensing through a mobile app and machine learning in brain tumour patients
Authors: Nur Aizaan Anwar, Matthew Williams
Journal: Neuro-Oncology (2021)

Abstract Aims 1. To assess the feasibility, acceptability, and performance of a mobile app, 'BRIAN', developed by The Brain Tumour Charity (BTC), in collecting data on quality of life (QOL), activity and sleep, for predicting disease progression in adult brain tumour patients. 2. To generate a prospectively collected dataset of patient measures obtained through mobile devices in brain tumour patients and healthy volunteers. 3. To assess compliance and performance of micro-challenges (hand coordination, visual memory, speech and facial features) in study participants using a mobile application. 4. To assess differences and systematic variation in micro-challenge performance between healthy volunteers and brain tumour patients. 5. To assess factors associated with micro-challenge performance in brain tumour patients, the relationship between micro-challenges and standard measures of QoL and disease progression. 6. To assess the diagnostic performance of different machine learning models in detecting brain tumour progression. Method This abstract describes the protocol for a multi-centre observational non-randomised phase II trial for adult brain tumour patients and healthy volunteers in the UK. Participants will use the BRIAN mobile app, developed by BTC to help individuals cope with a brain tumour, and share their journey with both researchers and clinicians. Participants will be required to enter information on their medical background, mood, and QOL; have the option to link fitness trackers to the app; as well as perform mini-games which assess speech, coordination, facial features and reaction time. Patients will have their brain imaging and histopathology report submitted to the sponsor. We will then investigate the correlation and temporal relation of these multimodal data with conventional measures of disease progression. We will use traditional statistical methods initially (i.e. descriptive statistics and multilevel modelling), which will then inform the development of a machine learning model in predicting brain tumour progression. Results The BRIAN app is currently being beta-tested by healthy volunteers from the Computational Oncology Lab, Imperial College London. We are in the process of obtaining ethical approval for the trial. Conclusion This study may enable the development of a tool that allows us to detect earlier signs of disease progression, and so offer earlier treatment and preservation of quality of life; and hence the best course of action. Such a tool would also be non-invasive, cheap, quick, and can be used by patients in the comfort of their own homes.
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
Authors: Constanza L Andaur Navarro, Johanna A A Damen, Toshihiko Takada, Steven W J Nijman, Paula Dhiman, Jie Ma, Gary S Collins, Ram Bajpai, Richard D Riley, Karel G M Moons, Lotty Hooft
Journal: BMJ (2021)

Abstract Objective To assess the methodological quality of studies on prediction models developed using machine learning techniques across all medical specialties. Design Systematic review. Data sources PubMed from 1 January 2018 to 31 December 2019. Eligibility criteria Articles reporting on the development, with or without external validation, of a multivariable prediction model (diagnostic or prognostic) developed using supervised machine learning for individualised predictions. No restrictions applied for study design, data source, or predicted patient related health outcomes. Review methods Methodological quality of the studies was determined and risk of bias evaluated using the prediction risk of bias assessment tool (PROBAST). This tool contains 21 signalling questions tailored to identify potential biases in four domains. Risk of bias was measured for each domain (participants, predictors, outcome, and analysis) and each study (overall). Results 152 studies were included: 58 (38%) included a diagnostic prediction model and 94 (62%) a prognostic prediction model. PROBAST was applied to 152 developed models and 19 external validations. Of these 171 analyses, 148 (87%, 95% confidence interval 81% to 91%) were rated at high risk of bias. The analysis domain was most frequently rated at high risk of bias. Of the 152 models, 85 (56%, 48% to 64%) were developed with an inadequate number of events per candidate predictor, 62 handled missing data inadequately (41%, 33% to 49%), and 59 assessed overfitting improperly (39%, 31% to 47%). Most models used appropriate data sources to develop (73%, 66% to 79%) and externally validate the machine learning based prediction models (74%, 51% to 88%). Information about blinding of outcome and blinding of predictors was, however, absent in 60 (40%, 32% to 47%) and 79 (52%, 44% to 60%) of the developed models, respectively. Conclusion Most studies on machine learning based prediction models show poor methodological quality and are at high risk of bias. Factors contributing to risk of bias include small study size, poor handling of missing data, and failure to deal with overfitting. Efforts to improve the design, conduct, reporting, and validation of such studies are necessary to boost the application of machine learning based prediction models in clinical practice. Systematic review registration PROSPERO CRD42019161764.
MA05.01 Patients’ Experiences During COVID-19: Insights from The Second Global Lung Cancer Coalition Patient Experience Survey
Authors: J. Fenemore, M. Rigney, W. Boerckel, A. Mcnamara, M. Hennink, J. Mayans, B. Gaspar, L. Pretorius, M. Daniels, J. Fox, D. Hall, S. Winstone
Journal: Journal of Thoracic Oncology (2021)
Case 31-2021: A 21-Year-Old Man with Sore Throat, Epistaxis, and Oropharyngeal Petechiae
Authors: Hanno Hock, Hillary R. Kelly, Eric A. Meyerowitz, Matthew J. Frigault, Lucas R. Massoth
Journal: New England Journal of Medicine (2021)

A Man with Sore Throat, Epistaxis, and Oropharyngeal Petechiae A 21-year-old man with sickle cell trait presented with sore throat, epistaxis, and petechiae of the oropharynx. The hemoglobin level ...
Worldwide incidence of surgical site infections in general surgical patients: A systematic review and meta-analysis of 488,594 patients
Authors: Brigid M. Gillespie, Emma Harbeck, Megan Rattray, Rhea Liang, Rachel Walker, Sharon Latimer, Lukman Thalib, Annette Erichsen Andersson, Bronwyn Griffin, Robert Ware, Wendy Chaboyer
Journal: International Journal of Surgery (2021)
Nutrient supplementation for prevention of viral respiratory tract infections in healthy subjects: A systematic review and meta‐analysis
Authors: Berber Vlieg‐ Boerstra, Nicolette de Jong, Rosan Meyer, Carlo Agostoni, Valentina De Cosmi, Kate Grimshaw, Gregorio Paolo Milani, Antonella Muraro, Hanneke Oude Elberink, Isabella Pali‐ Schöll, Caroline Roduit, Mari Sasaki, Isabel Skypala, Milena Sokolowska, Marloes van Splunter, Eva Untersmayr, Carina Venter, Liam O’Mahony, Bright I Nwaru
Journal: Allergy (2021)

It remains uncertain as to whether nutrient supplementation for the general population considered healthy could be useful in the prevention of RTIs, such as COVID-19. In this systematic review and meta-analysis, the evidence was evaluated for primary prevention of any viral respiratory tract infection (RTI) such as SARS-CoV-2, through supplementation of nutrients with a recognized role in immune function: multiple micronutrients, vitamin A, folic acid, vitamin B12, C, D, E, beta-carotene, zinc, iron and long-chain polyunsaturated fatty acids. The search produced 15,163 records of which 93 papers (based on 115 studies) met the inclusion criteria, resulting in 199,055 subjects (191,636 children and 7,419 adults) from 37 countries. Sixty-three studies were included in the meta-analyses, which was performed for children and adults separately. By stratifying the meta-analysis by world regions, only studies performed in Asia showed a significant but heterogeneous protective effect of zinc supplementation on RTIs (RR 0.86, 95% CI 0.7-0.96, I2 = 79.1%, p = .000). Vitamin D supplementation in adults significantly decreased the incidence of RTI (RR 0.89, 95% CI 0.79-0.99, p = .272), particularly in North America (RR 0.82 95% CI 0.68-0.97), but not in Europe or Oceania. Supplementation of nutrients in the general population has either no or at most a very limited effect on prevention of RTIs. Zinc supplementation appears protective for children in Asia, whilst vitamin D may protect adults in the USA and Canada. In 10/115 (8.7%) studies post-hoc analyses based on stratification for nutritional status was performed. In only one study zinc supplementation was found to be more effective in children with low zinc serum as compared to children with normal zinc serum levels.
P47.02 EV-202: Phase 2 Study of Enfortumab Vedotin for Previously Treated Advanced Solid Tumors Including Non-Small Cell Lung Cancer
Authors: K. Muro, J. Yang Bruce, J. Baranda, T. Feinstein, X. Li, S. Gorla, C. Wu, F. Braiteh
Journal: Journal of Thoracic Oncology (2021)
Computed tomography-based radiomics decodes prognostic and molecular differences in interstitial lung disease related to systemic sclerosis
Authors: Janine Schniering, Malgorzata Maciukiewicz, Hubert S. Gabrys, Matthias Brunner, Christian Blüthgen, Chantal Meier, Sophie Braga-Lagache, Anne-Christine Uldry, Manfred Heller, Matthias Guckenberger, Håvard Fretheim, Christos T. Nakas, Anna-Maria Hoffmann-Vold, Oliver Distler, Thomas Frauenfelder, Stephanie Tanadini-Lang, Britta Maurer
Journal: European Respiratory Journal (2021)

Background Radiomic features calculated from routine medical images show great potential for personalised medicine in cancer. Patients with systemic sclerosis (SSc), a rare, multiorgan autoimmune disorder, have a similarly poor prognosis due to interstitial lung disease (ILD). Here, our objectives were to explore computed tomography (CT)-based high-dimensional image analysis (“radiomics”) for disease characterisation, risk stratification and relaying information on lung pathophysiology in SSc-ILD. Methods We investigated two independent, prospectively followed SSc-ILD cohorts (Zurich, derivation cohort, n=90; Oslo, validation cohort, n=66). For every subject, we defined 1355 robust radiomic features from standard-of-care CT images. We performed unsupervised clustering to identify and characterise imaging-based patient clusters. A clinically applicable prognostic quantitative radiomic risk score (qRISSc) for progression-free survival (PFS) was derived from radiomic profiles using supervised analysis. The biological basis of qRISSc was assessed in a cross-species approach by correlation with lung proteomic, histological and gene expression data derived from mice with bleomycin-induced lung fibrosis. Results Radiomic profiling identified two clinically and prognostically distinct SSc-ILD patient clusters. To evaluate the clinical applicability, we derived and externally validated a binary, quantitative radiomic risk score (qRISSc) composed of 26 features that accurately predicted PFS and significantly improved upon clinical risk stratification parameters in multivariable Cox regression analyses in the pooled cohorts. A high qRISSc score, which identifies patients at risk for progression, was reverse translatable from human to experimental ILD and correlated with fibrotic pathway activation. Conclusions Radiomics-based risk stratification using routine CT images provides complementary phenotypic, clinical and prognostic information significantly impacting clinical decision making in SSc-ILD.
DNA aptamer S11e recognizes fibrosarcoma and acts as a tumor suppressor
Authors: Yunyi Liu, Cheng Peng, Hui Zhang, Juan Li, Hailong Ou, Yang Sun, Chaoqi Wen, Dan Qi, Xiaoxiao Hu, Erxi Wu, Weihong Tan
Journal: Bioactive Materials (2021)

Fibrosarcoma is a serious malignant mesenchymal tumor with strong invasiveness, high recurrence, and poor prognosis. Currently, surgical resection is the main treatment for fibrosarcoma. However, due to the lack of specific biomarkers, the inability to accurately diagnose fibrosarcoma can lead to sub-optimal surgical outcomes and decreased survival. Here, we seek to address this translational barrier and we show that DNA aptamer S11e was able to recognize fibrosarcoma cells (HT1080) but not human embryonic lung fibroblast cells with Kd values in the nanomolar range. In addition, we found that S11e discerned tumors in HT1080 xenograft mouse models and tumor tissues from fibrosarcoma patients. Furthermore, we demonstrated that S11e internalized into HT1080 cells independent of the lysosome pathway and located in mitochondria. Moreover, we revealed that S11e promoted the apoptosis of HT1080 cells and inhibited HT1080 cell migration. Finally, we investigated the biologically functional cellular target of S11e using a mass spectrometry approach, and identified that Diablo/SMAC protein is a cellular binding protein of S11e, by interacting to which S11e inhibited HT1080 cell migration and invasion. Taken together, these results provide the evidence that S11e may be useful for early diagnosis, targeted therapy, and prognostication of fibrosarcoma.
The molecular and cellular mechanisms associated with the destruction of terminal bronchioles in COPD
Authors: Feng Xu, Dragoş M. Vasilescu, Daisuke Kinose, Naoya Tanabe, Kevin W. Ng, Harvey O. Coxson, Joel D. Cooper, Tillie-Louise Hackett, Stijn E. Verleden, Bart M. Vanaudenaerde, Christopher S. Stevenson, Marc E. Lenburg, Avrum Spira, Wan C. Tan, Don D. Sin, Raymond T. Ng, James C. Hogg
Journal: European Respiratory Journal (2021)

Peripheral airway obstruction is a key feature of chronic obstructive pulmonary disease (COPD), but the mechanisms of airway loss are unknown. This study aims to identify the molecular and cellular mechanisms associated with peripheral airway obstruction in COPD.Ten explanted lung specimens donated by patients with very severe COPD treated by lung transplantation and five unused donor control lungs were sampled using systematic uniform random sampling (SURS), resulting in 240 samples. These samples were further examined by micro-computed tomography (CT), quantitative histology and gene expression profiling.Micro-CT analysis showed that the loss of terminal bronchioles in COPD occurs in regions of microscopic emphysematous destruction with an average airspace size of ≥500 and <1000 µm, which we have termed a "hot spot". Based on microarray gene expression profiling, the hot spot was associated with an 11-gene signature, with upregulation of pro-inflammatory genes and downregulation of inhibitory immune checkpoint genes, indicating immune response activation. Results from both quantitative histology and the bioinformatics computational tool CIBERSORT, which predicts the percentage of immune cells in tissues from transcriptomic data, showed that the hot spot regions were associated with increased infiltration of CD4 and CD8 T-cell and B-cell lymphocytes.The reduction in terminal bronchioles observed in lungs from patients with COPD occurs in a hot spot of microscopic emphysema, where there is upregulation of IFNG signalling, co-stimulatory immune checkpoint genes and genes related to the inflammasome pathway, and increased infiltration of immune cells. These could be potential targets for therapeutic interventions in COPD.
7P Predictive and prognostic value of cell-free DNA in plasma and pleural lavage among surgically treated adenocarcinomas of the lung (ADCL)
Authors: J. Saikia, P.S. Malik, S. Kumar, D. Jain, K. Madan, S.J. Bharati, S. Deo, S. Kumar
Journal: Annals of Oncology (2021)
P62.09 A Prospective Cohort Evaluation of the Sensitivity and Specificity of the Chest X-Ray for the Detection of Lung Cancer in Symptomatic Adults
Authors: N. Hatton, B. Bhartia, R. Aslam, S. Bradley, M. Darby, W. Hamilton, E. Hurst, M. Kennedy, L. Mounce, R. Neil, B. Shinkins, M. Callister
Journal: Journal of Thoracic Oncology (2021)
Patient and Payer Incentives to Use Patented Brand-Name Drugs vs Authorized Generic Drugs in Medicare Part D
Authors: Stacie B. Dusetzina, Ameet Sarpatwari, Michael A. Carrier, Richard A. Hansen, Nancy L. Keating, Haiden A. Huskamp
Journal: JAMA Internal Medicine (2021)

<h3>Importance</h3> In response to scrutiny over high drug prices, manufacturers of insulin and direct-acting antiviral agents for treating hepatitis C have recently introduced authorized generic alternatives to their patented brand-name products. These authorized generic drugs have list prices at least 50% lower than the list price of the brand-name drugs, which should result in savings to patients. However, it is unclear whether these authorized generic drugs are offered on Medicare Part D formularies because they may not provide savings to plans or Medicare. <h3>Objective</h3> To assess Medicare Part D formulary coverage for 4 brand-name formulations of insulin and direct-acting antiviral agents and their authorized generic formulations. <h3>Design, Setting, and Participants</h3> This cross-sectional study used Medicare Prescription Drug Plan Formulary and Pricing Information Files from quarter 3 of 2020 and Medicare Part D plan enrollment for September 2020. Four patented brand-name drugs (sofosbuvir and velpatasvir fixed-dose combination tablets [Epclusa], ledipasvir and sofosbuvir tablets [Harvoni], insulin lispro [Humalog], and insulin aspart [Novolog]) and their authorized generic formulations for all Part D stand-alone prescription drug plans (n = 959) and Medicare Advantage prescription drug plans (n = 3148) were studied. <h3>Main Outcomes and Measures</h3> Beneficiary-weighted formulary coverage of brand-name and authorized generic products; beneficiary out-of-pocket costs; and prerebate plan, manufacturer, and Medicare spending on brand-name and authorized generic products. <h3>Results</h3> In quarter 3 of 2020, 97% of beneficiaries were in plans that covered brand-name drugs only or both brand-name and authorized generic drugs; approximately 3% were in plans that covered authorized generic drugs only. Observed authorized generic drug list prices were 67%, 62%, and 50% lower than list prices for Epclusa, Harvoni, and each brand-name insulin product, respectively. Medicare beneficiaries using authorized generic drugs could save $270 per year for 12 vials of Humalog and $2974 for a full course of Harvoni. Plans, however, have limited incentives to encourage authorized generic drug use because rebates for brands likely exceed savings available with authorized generic drugs, particularly for beneficiaries with spending that reaches the Medicare Part D coverage gap. <h3>Conclusions and Relevance</h3> The results of this cross-sectional study suggest that authorized generic drugs for insulin and direct-acting antiviral agents may lower out-of-pocket spending for patients but are unlikely to provide savings for Part D plans or Medicare. Instead, these drugs allow manufacturers to offer products at a lower list price without materially lowering net prices or profits.
Association of Social Support With Overall Survival and Healthcare Utilization in Patients With Aggressive Hematologic Malignancies
Authors: P. Connor Johnson, Netana H. Markovitz, Tamryn F. Gray, Sunil Bhatt, Ryan D. Nipp, Nneka Ufere, Julia Rice, Matthew J. Reynolds, Mitchell W. Lavoie, Carlisle E.W. Topping, Madison A. Clay, Charlotta Lindvall, Areej El-Jawahri
Journal: Journal of the National Comprehensive Cancer Network (2021)

Background: Social support plays a crucial role for patients with aggressive hematologic malignancies as they navigate their illness course. The aim of this study was to examine associations of social support with overall survival (OS) and healthcare utilization in this population. Methods: A cross-sectional secondary analysis was conducted using data from a prospective longitudinal cohort study of 251 hospitalized patients with aggressive hematologic malignancies at Massachusetts General Hospital from 2014 through 2017. Natural Language Processing (NLP) was used to identify the extent of patients’ social support (limited vs adequate as defined by NLP-aided chart review of the electronic health record). Multivariable regression models were used to examine associations of social support with (1) OS, (2) death or readmission within 90 days of discharge from index hospitalization, (3) time to readmission within 90 days, and (4) index hospitalization length of stay. Results: Patients had a median age of 64 years (range, 19–93 years), and most were White (89.6%), male (68.9%), and married (65.3%). A plurality of patients had leukemia (42.2%) followed by lymphoma (37.9%) and myelodysplastic syndrome/myeloproliferative neoplasm (19.9%). Using NLP, we identified that 8.8% (n=22) of patients had limited social support. In multivariable analyses, limited social support was associated with worse OS (hazard ratio, 2.00; P =.042) and a higher likelihood of death or readmission within 90 days of discharge (odds ratio, 3.11; P =.043), but not with time to readmission within 90 days or with index hospitalization length of stay. Conclusions: In this cohort of hospitalized patients with aggressive hematologic malignancies, we found associations of limited social support with lower OS and a higher likelihood of death or readmission within 90 days of hospital discharge. These findings underscore the utility of NLP for evaluating the extent of social support and the need for larger studies evaluating social support in patients with aggressive hematologic malignancies.
Reply to “Caution in underrepresentation of older adults in clinical trials on COVID-19 vaccines”
Authors: Nicola Veronese, Mirko Petrovic, Athanase Benetos, Michael Denkinger, Adalsteinn Gudmundsson, Wilma Knol, Christine Marking, George Soulis, Stefania Maggi, Antonio Cherubini
Journal: Ageing Research Reviews (2021)
A Patient in Their 30s With Dyspnea and a Spongy Heart
Authors: Shahryar G. Saba, Andrew E. Arai
Journal: JAMA Cardiology (2021)

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