tbuckley/cabot-search huggingface dataset:
NGS testing patterns in advanced non-small cell lung cancer (aNSCLC) and metastatic breast cancer (mBC): OneOncology (OO) sites compared to Flatiron Health Nationwide (NAT).
Authors: Ari M. Vanderwalde, Esprit Ma, Elaine Yu, Tania Szado, Richard Price, Anuj Shah, Craig S. Meyer, Ibrahim M. Abbass, Axel Grothey, Harry Staszewski, Dennis Slater, L. Johnetta Blakely, Lee S. Schwartzberg
Journal: Journal of Clinical Oncology (2021)

288 Background: Personalized treatment (tx) decisions can be improved through diagnostic tests with NGS by detecting different actionable mutations. OO, a research-focused network of community practices, has a network-wide precision oncology initiative and has advocated for NGS testing in advanced cancers since 2019. This study evaluated NGS testing patterns in aNSCLC and mBC populations descriptively in OO community sites and Flatiron Health NAT. Methods: This study used the Flatiron Health EHR derived de-identified database from [1] four OO sites, and [2] NAT. Patients (pts) diagnosed (Dx) with aNSCLC (stage ≥ IIIb) or mBC from 1/1/2015 to 5/31/2020, aged ≥ 18 years, had ≥ 1 visit ≤ 90 days (d) of advanced or metastatic Dx, and had ≥ 1 biomarker test were included. NAT NGS was confirmed via abstraction from patient records. Descriptive analyses were conducted to assess NGS testing patterns and pts characteristics by tumor type. Results: Of biomarker tested pts at OO vs. NAT (community:academic: 90%:10% aNSCLC; 93%:7% mBC), 2,029 of 3,152 (64%) OO vs. 13,681 of 29,572 (46%) NAT in aNSCLC and 514 of 1,282 (40%) OO vs. 2,458 of 12,175 (20%) NAT in mBC received NGS ± other tests. Testing rate of all 5 aNSCLC biomarkers (ALK, BRAF, EGFR, ROS-1, and KRAS) was higher with NGS vs. other tests for OO (87% vs. 6%) and NAT (87% vs. 11%). In mBC, a higher testing rate of BRCA with NGS vs. other tests (OO: 68% vs. 26%, NAT: 71% vs. 28%) and similar testing rate on HER2 (OO: 98% vs. 98%, NAT: 100% vs. 99%). Median time from Dx to NGS test result at OO vs. NAT was 33 d vs. 32 d in aNSCLC and 70 d vs. 188 d in mBC. NGS testing rates increased over time, with higher rates at OO vs. NAT [Table]. Pts with NGS vs. other tests were slightly younger in aNSCLC (OO: 68 y vs. 70 y, p = 0.001; NAT: 69 y vs. 70 yr, p &lt; 0.001) and mBC (OO: 61 y vs. 67 y, p &lt; 0.001; NAT: 61 y vs. 66 y, p &lt; 0.001), and slightly more commercially insured in aNSCLC (OO: 48% vs. 45%, p = 0.3; NAT: 37% vs. 33%, p &lt; 0.001) and mBC (OO: 54% vs. 48% OO, p = 0.053; NAT: 42 % vs. 36 %, p &lt; 0.001). Conclusions: The adoption of NGS differed by cancer type and NGS testing rates have increased over time in aNSCLC and mBC. While some pts may have received testing outside of the Flatiron network, OO had a higher NGS uptake than NAT, and had a shorter time to testing in mBC that was possibly related to a network wide strategy recommending testing at Dx of advanced disease. Future studies on tx pattern after NGS testing are warranted to improve the actionability of NGS to foster personalized tx. [Table: see text]
Preventing the ‘24-hour Babel’: the need for a consensus on a consistent terminology scheme for physical activity, sedentary behaviour and sleep
Authors: Ryan S Falck, Jennifer C Davis, Linda Li, Emmanuel Stamatakis, Teresa Liu-Ambrose
Journal: British Journal of Sports Medicine (2021)

Clear, concise, and consistent. These qualities (the 3Cs) are critical for effective scientific communication. Plain language enables easy comparisons between study findings, ensures construct uniformity, and enhances communication of scientific discoveries to audiences beyond academia.

Health research has a growing interest in the inter-relationships of physical activity (PA), sedentary behaviour (SB) and sleep. These behaviours occupy most of the 24-hour cycle and are associated with a plethora of health outcomes.1 Consensus statements suggest how to analyse these behaviours.2 Some PA/SB guidelines have incorporated sleep using mostly cross-sectional evidence.1 However, these consensus statements and guidelines fail to acknowledge the interactive and reciprocal relationships between PA, SB and sleep.

As more scientists enter this field (figure 1), terminology is becoming inconsistent and confusing. Here, we outline the disparate vocabulary for the 24-hour cycle, and make the case for a consensus project to address how we collectively think about and refer to PA, SB and sleep using the 3Cs principle.



Figure 1 
PubMed search hits from 2010 to 2020 for each term for collectively defining physical activity, sedentary behaviour and sleep.



Health research has a well-defined vocabulary for behaviours which occupy most of the 24-hour cycle. PA is any bodily movement which increases energy expenditure above 1.5 metabolic equivalents (METs).3 SB is any behaviour performed from a seated/lying position that requires ≤1.5 METs.4 …
Solidarity as an Aspirational Basis for Partnership with Tribal Communities
Authors: Sara Chandros Hull, F. Leah Nez (Diné), Juliana M. Blome
Journal: The American Journal of Bioethics (2021)

Saunkeah et al. (2021) argue convincingly that although respect for Tribal sovereignty is often invoked as a core justification for Tribal research protections, an expanded ethical framework is req...
National benchmarks and practice level variation on eight cross cutting quality measures.
Authors: Tracy E. Spinks, Lindsey Bandini, Amie Cook, Hong Gao, Nicholas Jennings, Ranyan Lu, Michelle Mentel, Jennifer Malin
Journal: Journal of Clinical Oncology (2021)

255 Background: While there is increased attention on the importance of quality measurement in oncology, especially with the rise of value-based payment, limited data exist on national averages and practice level variation for proposed quality measures to establish benchmarks and targets for quality improvement initiatives or value-based contracts. Methods: UnitedHealthcare (UHC) developed peer comparison reports for eight cross cutting quality measures for practices with an active contract for at least one of its commercial, Medicare or Medicaid health plans and ≥1 provider from the following specialties: gynecologic oncology, hematology/oncology, pediatric hematology/oncology, radiation oncology, or surgical oncology. Adherence to the quality measures below was calculated using a mix of claims data, clinical data from a prior authorization for cancer therapy, and CMS MIPS data. Patients were attributed through an algorithm that selected the most probable physician responsible for the patient’s care - responsible prior authorization provider, servicing provider or most recent visited provider prior to the treatment, varying by each measure. Dates of service differ by measure, ranging from 1/1/2019 through 12/31/2020. Results: We identified 5,828 unique tax identification numbers (TINs) with UHC members with cancer attributed to them during 2019-20. The number of practices included in the measurement cohort per measure varied significantly from 301 to 4,120 (tobacco screening and performance status, respectively). 2,422 TINs met the minimum patient count for at least one measure (≥10 patients or events). Overall performance ranged from 13.5% to 77.3% (hospice admission and PS documented) for measures where higher adherence reflects better quality of care. For measures where lower scores represent higher quality of care the range was 11.4% to 22.6% (hospice &lt; 3 days and ED admission, respectively). Observed adherence was statistically better than expected for 0.5%-5.8% and statistically less than expected for 0.9%-5.6% of TINs in UHC’s network; however, more than half of the practices had insufficient sample size to make a determination. Conclusions: We observed substantial variation in quality across a national cohort of oncology practices. However, even for a large national payer, small sample sizes limited the assessment of a substantial number of practices.[Table: see text]
Proteinuric chronic kidney disease is associated with altered red blood cell lifespan, deformability and metabolism
Authors: Rosi Bissinger, Travis Nemkov, Angelo D'Alessandro, Marijke Grau, Thomas Dietz, Bernhard N. Bohnert, Daniel Essigke, Matthias Wörn, Lina Schaefer, Mengyun Xiao, Jonathan M. Beirne, M. Zaher Kalo, Anja Schork, Tamam Bakchoul, Kingsley Omage, Lingsi Kong, Irene Gonzalez-Menendez, Leticia Quintanilla-Martinez, Birgit Fehrenbacher, Martin Schaller, Achal Dhariwal, Andreas L. Birkenfeld, Florian Grahammer, Syed M. Qadri, Ferruh Artunc
Journal: Kidney International (2021)

Anemia is a common complication of chronic kidney disease, affecting the quality of life of patients. Among various factors, such as iron and erythropoietin deficiency, reduced red blood cell (RBC) lifespan has been implicated in the pathogenesis of anemia. However, mechanistic data on in vivo RBC dysfunction in kidney disease are lacking. Herein, we describe the development of chronic kidney disease-associated anemia in mice with proteinuric kidney disease resulting from either administration of doxorubicin or an inducible podocin deficiency. In both experimental models, anemia manifested at day 10 and progressed at day 30 despite increased circulating erythropoietin levels and erythropoiesis in the bone marrow and spleen. Circulating RBCs in both mouse models displayed altered morphology and diminished osmotic-sensitive deformability together with increased phosphatidylserine externalization on the outer plasma membrane, a hallmark of RBC death. Fluorescence-labelling of RBCs at day 20 of mice with doxorubicin-induced kidney disease revealed premature clearance from the circulation. Metabolomic analyses of RBCs from both mouse models demonstrated temporal changes in redox recycling pathways and Lands' cycle, a membrane lipid remodeling process. Anemic patients with proteinuric kidney disease had an increased proportion of circulating phosphatidylserine-positive RBCs. Thus, our observations suggest that reduced RBC lifespan, mediated by altered RBC metabolism, reduced RBC deformability, and enhanced cell death contribute to the development of anemia in proteinuric kidney disease.
P14.33 Preoperative Lactate Dehydrogenase levels as a predictor of venous thromboembolism development in glioblastoma patients
Authors: A Jacquerie, S Huijs, V M P Moers-Hornikx, A M H G van der Heijden-Montfroy, M P J van Goor, R C O S Pasmans, M H M E Anten, M Verduin, M P G Broen
Journal: Neuro-Oncology (2021)

Abstract BACKGROUND Venous thromboembolism (VTE) is a common complication in patients with glioblastoma. Despite high incidence of up to 30% per year, concerns about bleeding complications have limited the use of primary anticoagulant prophylaxis. Finding a suitable biomarker to assess the risk of occurrence is therefore of utmost clinical interest. We performed an exploratory study of preoperative routinely used haematological markers as predictor for the development of VTE in glioblastoma patients. MATERIAL AND METHODS Data was retrospectively collected from an existing database of 307 patients diagnosed with glioblastoma by the Oncology Network South-East Netherlands (OnzoZON) between 2006 and 2020. Collected preoperative haematological markers included: haemoglobin, platelets, lactate dehydrogenase, neutrophils, lymphocytes, albumin and derived ratios. In addition, type and date of VTE were retrieved from medical records. Receiver operating curve was used to identify the optimal cut-off values of the preoperative haematological markers. Univariate and multivariate logistic regression analyses were performed to predict VTE for each haematologic marker independently. Variables included in the multivariate analyses were age, gender, type of surgery, Karnofsky performance score, MGMT status, weight, height and BMI, already available from the primary database. RESULTS In the total dataset, 45 patients (15%) suffered from a VTE, most common pulmonary embolism (51%) followed by deep vein thrombosis (31%). Mean time from diagnosis until VTE was 4.3 months (SD = 5.5). Preoperative haemoglobin value was available for analyses in 265 patients, platelets value in 226, lactate dehydrogenase in 98, neutrophils in 133, lymphocytes in 133 and albumin in 56 patients. A preoperative lactate dehydrogenase value &amp;gt; 243 U/L was found to increase the risk of VTE in both univariate and multivariate analysis (P &amp;lt;0.05). Seventeen out of 98 patients of whom lactate dehydrogenase level was available suffered from a VTE, most common pulmonary embolism (59%), followed by deep vein thrombosis (29%) and cerebral venous sinus thrombosis (12%). An elevated lactate dehydrogenase in serum increased the odds for getting a VTE by 3.2 (1.1–9.4). None of the other investigated haematological markers or ratios were found to be significantly correlated with the occurrence of VTE in our study. CONCLUSION Glioblastoma initiates locally haemostatic abnormalities, that propagate systemically though circulating mediators. Our exploratory analysis shows for the first time that preoperative lactate dehydrogenase levels might aid clinicians in identifying patients at risk for a venous thromboembolism. Ultimately this could lead to preventive measures and patient education, but larger and prospective validation of these findings is warranted.
New public health body will be responsible for “levelling up” health, health secretary says
Authors: Ingrid Torjesen
Journal: BMJ (2021)

The organisation set to take over Public Health England’s leadership role in health promotion and illness prevention from 1 October will be called the Office for Health Improvement and Disparities to underline the government’s commitment to “level up” health, the health and social care secretary Sajid Javid has announced. It had been expected that it would be called the Office for Health Promotion.

Javid, who took on the health brief on 26 June, said, “When I came into this job, my thoughts turned to what this office—with that weighty responsibility of shifting the dial on how we improve health and prevent disease—would need to focus on to achieve its mission. It’s not just a change of name but a statement of intent—a driving mission to ‘level up’ health and ensure everyone has the chance to live happy and …
BCL-W expression associates with poor outcome in patients with peripheral T-cell lymphoma not otherwise specified
Authors: Mario L. Marques-Piubelli, Luisa M. Solis, Edwin R. Parra, Luis Malpica Castillo, Sushanth Gouni, Ranjit Nair, Dai Chihara, Marina Konopleva, Ignacio I. Wistuba, Swaminathan P. Iyer, Francisco Vega, Paolo Strati
Journal: Blood Cancer Journal (2021)
Comparative performance of risk prediction models for hepatitis B-related hepatocellular carcinoma in the United States
Authors: Hyun-seok Kim, Xian Yu, Jennifer Kramer, Aaron P. Thrift, Pete Richardson, Yao-Chun Hsu, Avegail Flores, Hashem B. El-Serag, Fasiha Kanwal
Journal: Journal of Hepatology (2021)
Social Innovation For Health Research: Development of the SIFHR Checklist
Authors: Eneyi E. Kpokiri, Elizabeth Chen, Jingjing Li, Sarah Payne, Priyanka Shrestha, Kaosar Afsana, Uche Amazigo, Phyllis Awor, Jean-Francois de Lavison, Saqif Khan, Jana Mier-Alpaño, Alberto Ong, Shivani Subhedar, Isabelle Wachmuth, Luis Gabriel Cuervo, Kala M. Mehta, Beatrice Halpaap, Joseph D. Tucker
Journal: PLoS Medicine (2021)

Background Social innovations in health are inclusive solutions to address the healthcare delivery gap that meet the needs of end users through a multi-stakeholder, community-engaged process. While social innovations for health have shown promise in closing the healthcare delivery gap, more research is needed to evaluate, scale up, and sustain social innovation. Research checklists can standardize and improve reporting of research findings, promote transparency, and increase replicability of study results and findings. Methods and findings The research checklist was developed through a 3-step community-engaged process, including a global open call for ideas, a scoping review, and a 3-round modified Delphi process. The call for entries solicited checklists and related items and was open between November 27, 2019 and February 1, 2020. In addition to the open call submissions and scoping review findings, a 17-item Social Innovation For Health Research (SIFHR) Checklist was developed based on the Template for Intervention Description and Replication (TIDieR) Checklist. The checklist was then refined during 3 rounds of Delphi surveys conducted between May and June 2020. The resulting checklist will facilitate more complete and transparent reporting, increase end-user engagement, and help assess social innovation projects. A limitation of the open call was requiring internet access, which likely discouraged participation of some subgroups. Conclusions The SIFHR Checklist will strengthen the reporting of social innovation for health research studies. More research is needed on social innovation for health.
Mechanical Stress Induces a Transient Suppression of Cytokine Secretion in Astrocytes Assessed at the Single‐Cell Level with a High‐Throughput Microfluidic Chip
Authors: Xiaowei Shao, Chunhua Wang, Chao Wang, Lei Han, Yunrui Han, Dean Nižetić, Yu Zhang, Lin Han
Journal: Advanced Healthcare Materials (2021)

Abstract Brain cells are constantly subjected to mechanical signals. Astrocytes are the most abundant glial cells of the central nervous system (CNS), which display immunoreactivity and have been suggested as an emerging disease focus in the recent years. However, how mechanical signals regulate astrocyte immunoreactivity, and the cytokine release in particular, remains to be fully characterized. Here, human neural stem cells are used to induce astrocytes, from which the release of 15 types of cytokines are screened, and nine of them are detected using a protein microfluidic chip. When a gentle compressive force is applied, altered cell morphology and reinforced cytoskeleton are observed. The force induces a transient suppression of cytokine secretions including IL‐6, MCP‐1, and IL‐8 in the early astrocytes. Further, using a multiplexed single‐cell culture and protein detection microfluidic chip, the mechanical effects at a single‐cell level are analyzed, which validates a concerted downregulation by force on IL‐6 and MCP‐1 secretions in the cells releasing both factors. This work demonstrates an original attempt of employing the protein detection microfluidic chips in the assessment of mechanical regulation on the brain cells at a single‐cell resolution, offering novel approach and unique insights for the understanding of the CNS immune regulation.
The Oncology Care Model and lung cancer: Retrospective review of claims and clinical data at a large academic medical center.
Authors: Chetan Vakkalagadda, Bijal Desai, Nisha Anjali Mohindra, Sheetal Mehta Kircher
Journal: Journal of Clinical Oncology (2021)

62 Background: The Oncology Care Model (OCM) is a Center for Medicare and Medicaid Innovation (CMMI) alternative payment model designed to enhance value in cancer care. Based on a practice’s historical performance, the model predicts a target price for a 6-month episode of care and adjusts for factors such as age, modality received, geographic location, trend factor, and receipt of a novel therapy. Practices are incentivized to reduce costs of care, allowing for a performance based payment if the total cost of care is below the predicted OCM target price. At our OCM practice, when compared to other malignancy types, lung cancer has disproportionately failed to meet the OCM target. The purpose of our review was to explore the contribution of systemic therapy to total cost within the OCM model for lung cancer episodes. Methods: We reviewed claims and clinical data for the OCM Performance Period 6 (PP6), which corresponds to episodes beginning between 1/2/19-7/1/19 and ending between 7/2/19-12/31/19, for all OCM lung cancer episodes at Northwestern Medical Group. Results: 142 patients were identified with non-small cell (n = 128, 91%) and small cell lung cancer (n = 14, 9%). Patients received a PD1 inhibitor either alone or in combination with chemotherapy (n = 87), tyrosine kinase inhibitors (n = 18), both a PD1 inhibitor and a TKI (n = 2), or chemotherapy alone (n = 35). All systemic therapy use was deemed guideline compliant. 46 patients (33%) had at least 1 cancer-related hospital admission during the episode. 19 patients (13.4%) died during the OCM performance period. 39/142 (27.5%) of patients’ episode costs achieved the OCM target. Among the 103 patients whose total costs exceeded the target, drug costs alone exceeded the target in 67 (65%). Drug costs alone exceeded the total target in 59% (n = 63/107) of those who received PD1 inhibitor or TKI therapy and 11.4% (4/35) of those who received chemotherapy alone. 94% (n = 63/67) of patients for whom drug costs alone exceeded the OCM target received anti-PD1 therapy or a TKI. Conclusions: Drug cost alone exceeded the total target in the majority of OCM lung cancer episodes that did not achieve savings, highlighting the dominant role drugs play in the OCM model. With targeted therapy and immunotherapy already the standard of care in metastatic non-small cell lung cancer, and gaining a foothold in earlier stages of disease, accounting for these therapies in the OCM target price methodology will be critical for oncology practices to be successful within such value-based payment models.
Letter to the editor: Autoimmune hepatitis after COVID‐19 vaccination: A rare adverse effect?
Authors: Panagiota Palla, Chrysovalantis Vergadis, Stratigoula Sakellariou, Theodoros Androutsakos
Journal: Hepatology (2021)

Palla, Panagiota; Vergadis, Chrysovalantis; Sakellariou, Stratigoula; Androutsakos, Theodoros Author Information