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You A, Gu J, Wang J, Li J, Zhang Y, Rao G, Ge X, Zhang K, Gao X, Wang D. Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma. Neurologia 2024; 39:353-360. [PMID: 38616063 DOI: 10.1016/j.nrleng.2021.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 06/11/2021] [Indexed: 04/16/2024] Open
Abstract
BACKGROUND Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. METHODS The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan-Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. RESULTS HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis. CONCLUSIONS Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients. Therefore, HAS2-AS1 could be used as a diagnostic and prognostic marker for glioma.
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Affiliation(s)
- A You
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China
| | - J Gu
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China
| | - J Wang
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China
| | - J Li
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China
| | - Y Zhang
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China
| | - G Rao
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China
| | - X Ge
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China
| | - K Zhang
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China
| | - X Gao
- Operating Theatre, Tangshan Central Hospital, 063000 Tangshan, China
| | - D Wang
- The Fourth Department of Neurosurgery, Tangshan Gongren Hospital, 063000 Tangshan, China.
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Yeboa DN, Woodhouse K, Prabhu S, Li J, Beckham T, Weinberg JS, Wang C, McCutcheon IE, Swanson TA, Kim BYS, McGovern SL, North R, McAleer MF, Alvarez-Breckenridge C, Jiang W, Ene C, Ejezie CL, Lang F, Rao G, Ferguson S. MD Anderson Phase III Randomized Preoperative Stereotactic Radiosurgery (SRS) vs. Postoperative SRS for Brain Metastases Trial. Int J Radiat Oncol Biol Phys 2023; 117:e160-e161. [PMID: 37784756 DOI: 10.1016/j.ijrobp.2023.06.990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) Postoperative stereotactic radiation therapy/radiosurgery (SRT/SRS) is being evaluated in comparison to Preoperative SRT for brain metastases (mets) in a limited number of prospective clinical trials. Our objective is to address the significant knowledge gap concerning the logistics of preoperative SRT in comparison to postoperative SRT in a randomized controlled study. MATERIALS/METHODS Patients with brain mets with at least 1 surgically operable met were randomized (1:1) to Preop vs Postop SRT. In this abstract, we present non-primary endpoint data on the trial concept and logistics of treatment for this data safety monitoring board reviewed study. Patients enrolled had 1-2 lesions resected and <15 lesions treated at time of SRT to best reflect the standard population that receive SRT and surgery at our institution. RESULTS From 12/2018 to 12/2022, 99 patients with 1-2 operable brain mets were enrolled and randomized to Preop (n = 49) or Postop (n = 50) SRT. Males represented 56% of the cohort compared to females, and <25% were age 18-49 years, while 27%, 29, and 19% respectively were 50-59, 60-69, and > = 70. The most frequent histologies enrolled were lung (29%), renal cell (15%), melanoma (14%), and breast (11%) cancers. The majority of patients (83%) had 1-4 brain mets on their baseline MRI and 91% subsequently had a single lesion resected. Seventy-nine patients completed both SRT and surgery, while 9% received no therapy due to drop out before study therapy initiation. Among patients receiving both therapies in the combined cohort, 68% received a non-invasive stereotactic radiosurgery instrument to the randomized cavity lesion compared to 32% receiving LINAC based SRT. Treatment of the lesion or cavity with single fraction SRT was 51% in the Preop arm vs 31% in the Postop arm. Multi-fraction (3-5 SRT) was 67% in the Postop cohort in contrast to 47% in the Preop cohort. Time from randomization to RT was 5.6 days and 33.7 days in the Preop and Postop cohorts respectively, and for surgery was 10.2 days vs 12.9 days in the Postop vs Preop cohorts. The average time from RT to surgery was 7.3 days in the Preop arm and 23.5 days in the Postop arm (to allow for incisional healing time). CONCLUSION In one of the early initiated randomized prospective cohorts of Preop vs Postop SRT, we demonstrated logistical feasibility with an efficient clinical trial workflow for study treatment. Differences in Preop vs Postop logistics reflect clinical practice differences in time-to-treatment. Therapy with various modalities reflected real-world practice and possibly provider preferences in technique when addressing the nature of delineating cavities and changes in cavity volume with regard to fractionation. Independent of the primary outcomes, our data provides insights in the practical management of patients receiving these two modalities of therapy, and further data at the completion of trial will address relevant primary outcomes.
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Affiliation(s)
- D N Yeboa
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - S Prabhu
- Department of Neurosurgery, University of Texas MD Anderson Cancer Center, Houston, TX
| | - J Li
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - T Beckham
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - J S Weinberg
- Department of Neurosurgery, University of Texas MD Anderson Cancer Center, Houston, TX
| | - C Wang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - I E McCutcheon
- Department of Neurosurgery, University of Texas MD Anderson Cancer Center, Houston, TX
| | - T A Swanson
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - B Y S Kim
- Department of Neurosurgery, University of Texas MD Anderson Cancer Center, Houston, TX
| | - S L McGovern
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - R North
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - M F McAleer
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - W Jiang
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - C Ene
- Department of Neurosurgery, University of Texas MD Anderson Cancer Center, Houston, TX
| | - C L Ejezie
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - F Lang
- Department of Neurosurgery, University of Texas MD Anderson Cancer Center, Houston, TX
| | - G Rao
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX
| | - S Ferguson
- Department of Neurosurgery, University of Texas MD Anderson Cancer Center, Houston, TX
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Ostropolets A, Albogami Y, Conover M, Banda JM, Baumgartner WA, Blacketer C, Desai P, DuVall SL, Fortin S, Gilbert JP, Golozar A, Ide J, Kanter AS, Kern DM, Kim C, Lai LYH, Li C, Liu F, Lynch KE, Minty E, Neves MI, Ng DQ, Obene T, Pera V, Pratt N, Rao G, Rappoport N, Reinecke I, Saroufim P, Shoaibi A, Simon K, Suchard MA, Swerdel JN, Voss EA, Weaver J, Zhang L, Hripcsak G, Ryan PB. Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study. J Am Med Inform Assoc 2023; 30:859-868. [PMID: 36826399 PMCID: PMC10114120 DOI: 10.1093/jamia/ocad009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 01/04/2023] [Accepted: 01/23/2023] [Indexed: 02/25/2023] Open
Abstract
OBJECTIVE Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations' variability on patient characteristics. MATERIALS AND METHODS Nine teams of highly qualified researchers reproduced a cohort from a study by Albogami et al. The teams were provided the clinical codes and access to the tools to create cohort definitions such that the only variable part was their logic choices. We executed teams' cohort definitions against the database and compared the number of subjects, patient overlap, and patient characteristics. RESULTS On average, the teams' interpretations fully aligned with the master implementation in 4 out of 10 inclusion criteria with at least 4 deviations per team. Cohorts' size varied from one-third of the master cohort size to 10 times the cohort size (2159-63 619 subjects compared to 6196 subjects). Median agreement was 9.4% (interquartile range 15.3-16.2%). The teams' cohorts significantly differed from the master implementation by at least 2 baseline characteristics, and most of the teams differed by at least 5. CONCLUSIONS Independent research teams attempting to reproduce the study based on its free-text description alone produce different implementations that vary in the population size and composition. Sharing analytical code supported by a common data model and open-source tools allows reproducing a study unambiguously thereby preserving initial design choices.
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Affiliation(s)
- Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - Yasser Albogami
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Mitchell Conover
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - Juan M Banda
- Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
| | - William A Baumgartner
- Division of General Internal Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Clair Blacketer
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - Priyamvada Desai
- Research IT, Technology and Digital Solutions, Stanford Medicine, Stanford, California, USA
| | - Scott L DuVall
- VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Stephen Fortin
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - James P Gilbert
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | | | - Joshua Ide
- Johnson & Johnson, Titusville, New Jersey, USA
| | - Andrew S Kanter
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - David M Kern
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - Chungsoo Kim
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea
| | - Lana Y H Lai
- Department of Informatics, Imaging & Data Sciences, University of Manchester, Manchester, UK
| | - Chenyu Li
- Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Feifan Liu
- Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
| | - Kristine E Lynch
- VA Salt Lake City Health Care System, Salt Lake City, Utah, USA
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Evan Minty
- O’Brien Institute for Public Health, Faculty of Medicine, University of Calgary, Calgary, Canada
| | | | - Ding Quan Ng
- Department of Pharmaceutical Sciences, School of Pharmacy & Pharmaceutical Sciences, University of California, Irvine, California, USA
| | - Tontel Obene
- Mississippi Urban Research Center, Jackson State University, Jackson, Mississippi, USA
| | - Victor Pera
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Nicole Pratt
- Quality Use of Medicines and Pharmacy Research Centre, University of South Australia, Adelaide, Australia
| | - Gowtham Rao
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - Nadav Rappoport
- Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel
| | - Ines Reinecke
- Institute for Medical Informatics and Biometry, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Paola Saroufim
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Azza Shoaibi
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - Katherine Simon
- VA Tennessee Valley Health Care System, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Marc A Suchard
- Department of Biostatistics, University of California, Los Angeles, California, USA
- Department of Human Genetics, University of California, Los Angeles, California, USA
| | - Joel N Swerdel
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - Erica A Voss
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - James Weaver
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
| | - Linying Zhang
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
- Medical Informatics Services, New York-Presbyterian Hospital, New York, New York, USA
| | - Patrick B Ryan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA
- Observational Health Data Analytics, Janssen Research & Development, Titusville, New Jersey, USA
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Nang S, Lu J, Yu H, Wickremasinghe H, Azad M, Han M, Rao G, Bergen P, Velkov T, Sherry N, Aslam S, Schooley R, Howden B, Barr J, Zhu Y, Li J. SY4.1: COMBINATION OF BACTERIOPHAGE AND ANTIBIOTIC: IS IT AN ULTIMATE SOLUTION TO MULTIDRUG RESISTANCE? J Glob Antimicrob Resist 2022. [DOI: 10.1016/s2213-7165(22)00278-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
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Nang S, Lin Y, Hanafin P, Wang J, Chen K, Yu H, Wickremasinghe H, Bergen P, Chang R, Rao G, Chan H, Li J. 81: PHARMACOKINETICS/PHARMACODYNAMICS OF ANTI-PSEUDOMONAL PHAGE: LEVERAGING PRECLINCAL MODELS OF INFECTION AND MECHANISM-BASED MODELLING. J Glob Antimicrob Resist 2022. [DOI: 10.1016/s2213-7165(22)00360-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
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Vigouroux L, Cartier T, Rao G, Berton É. Pull-up forms of completion impacts deeply the muscular and articular involvements. Sci Sports 2022. [DOI: 10.1016/j.scispo.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Garcia S, Delattre N, Berton E, Divrechy G, Rao G. Comparison of landing kinematics and kinetics between experienced and novice volleyball players during block and spike jumps. BMC Sports Sci Med Rehabil 2022; 14:105. [PMID: 35690791 PMCID: PMC9188216 DOI: 10.1186/s13102-022-00496-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 06/01/2022] [Indexed: 11/10/2022]
Abstract
BACKGROUND The practice of volleyball requires many jumps. During landing, anterior cruciate ligament injuries may occur with high-risk lower limb kinematics and kinetics. Differences in landing strategies between experienced and novice volleyball players have not been fully explored. The purpose of the study was to compare lower limb kinematics and kinetics in experienced and novice volleyball players when performing volleyball specific jumps. METHODS A total of 30 healthy males, 15 experienced and 15 novice volleyball players, participated in the study. Participants performed block and spike jumps at a controlled jump height. Hip, knee and ankle joints angles at initial ground contact and ranges of motion in the sagittal plane, knee joint angles and moments in the frontal plane, vertical ground reaction force peak and loading rate were analyzed to investigate the expertise effect. RESULTS Experienced volleyball players landed with larger ankle dorsiflexion range of motion compared to novices. For the spike jump, experienced players landed with larger ankle plantarflexion angles at initial contact and larger ankle dorsiflexion ranges of motion, and for the block jump, they landed with larger knee flexion ranges of motion. Experienced players jumped significantly higher than novices. No difference was found in vertical ground reaction force peaks and loading rates. CONCLUSIONS Although the experienced group jumped higher than the novice group, no difference was found in ground reaction force parameters. These findings highlight that the experience of volleyball players acquired during regular trainings and competitions may play an important role in landing kinematics and kinetics to reduce the injury risk.
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Affiliation(s)
- Sébastien Garcia
- Movement Sciences Department, Decathlon SportsLab, 59000, Lille, France. .,CNRS, Insitute of Movement Sciences, Aix-Marseille University, 13007, Marseille, France.
| | - N Delattre
- Movement Sciences Department, Decathlon SportsLab, 59000, Lille, France
| | - E Berton
- CNRS, Insitute of Movement Sciences, Aix-Marseille University, 13007, Marseille, France
| | - G Divrechy
- Movement Sciences Department, Decathlon SportsLab, 59000, Lille, France
| | - G Rao
- CNRS, Insitute of Movement Sciences, Aix-Marseille University, 13007, Marseille, France
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Sundaram V, Rao G, Nandi M, Reddy V, pokhala N, Mondal K, Prakash A, Bhattacharjee M. PO-1545 Comparison of PRO and PO algorithms in Rapid arc (VMAT) delivery for Head and Neck SIB treatments. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03509-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Sundaram V, Rao G, Bhattacharjee M, Joseph J, Balaji B, Patil D. PO-1544 The role of dose rate and gantry speed variations in PRO and PO algorithms for rapidarc delivery. Radiother Oncol 2022. [DOI: 10.1016/s0167-8140(22)03508-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Ostropolets A, Li X, Makadia R, Rao G, Rijnbeek PR, Duarte-Salles T, Sena AG, Shaoibi A, Suchard MA, Ryan PB, Prieto-Alhambra D, Hripcsak G. Factors Influencing Background Incidence Rate Calculation: Systematic Empirical Evaluation Across an International Network of Observational Databases. Front Pharmacol 2022; 13:814198. [PMID: 35559254 PMCID: PMC9087898 DOI: 10.3389/fphar.2022.814198] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 03/17/2022] [Indexed: 01/01/2023] Open
Abstract
Objective: Background incidence rates are routinely used in safety studies to evaluate an association of an exposure and outcome. Systematic research on sensitivity of rates to the choice of the study parameters is lacking. Materials and Methods: We used 12 data sources to systematically examine the influence of age, race, sex, database, time-at-risk, season and year, prior observation and clean window on incidence rates using 15 adverse events of special interest for COVID-19 vaccines as an example. For binary comparisons we calculated incidence rate ratios and performed random-effect meta-analysis. Results: We observed a wide variation of background rates that goes well beyond age and database effects previously observed. While rates vary up to a factor of 1,000 across age groups, even after adjusting for age and sex, the study showed residual bias due to the other parameters. Rates were highly influenced by the choice of anchoring (e.g., health visit, vaccination, or arbitrary date) for the time-at-risk start. Anchoring on a healthcare encounter yielded higher incidence comparing to a random date, especially for short time-at-risk. Incidence rates were highly influenced by the choice of the database (varying by up to a factor of 100), clean window choice and time-at-risk duration, and less so by secular or seasonal trends. Conclusion: Comparing background to observed rates requires appropriate adjustment and careful time-at-risk start and duration choice. Results should be interpreted in the context of study parameter choices.
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Affiliation(s)
| | - Xintong Li
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, United Kingdom
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, United States
| | - Gowtham Rao
- Janssen Research and Development, Titusville, NJ, United States
| | - Peter R. Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Talita Duarte-Salles
- Fundacio Institut Universitari per a la Recerca a L’Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Anthony G. Sena
- Janssen Research and Development, Titusville, NJ, United States
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Azza Shaoibi
- Janssen Research and Development, Titusville, NJ, United States
| | - Marc A. Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, United States
| | - Patrick B. Ryan
- Columbia University Medical Center, New York, NY, United States
- Janssen Research and Development, Titusville, NJ, United States
| | | | - George Hripcsak
- Columbia University Medical Center, New York, NY, United States
- New York-Presbyterian Hospital, New York, NY, United States
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Williams RD, Markus AF, Yang C, Duarte-Salles T, DuVall SL, Falconer T, Jonnagaddala J, Kim C, Rho Y, Williams AE, Machado AA, An MH, Aragón M, Areia C, Burn E, Choi YH, Drakos I, Abrahão MTF, Fernández-Bertolín S, Hripcsak G, Kaas-Hansen BS, Kandukuri PL, Kors JA, Kostka K, Liaw ST, Lynch KE, Machnicki G, Matheny ME, Morales D, Nyberg F, Park RW, Prats-Uribe A, Pratt N, Rao G, Reich CG, Rivera M, Seinen T, Shoaibi A, Spotnitz ME, Steyerberg EW, Suchard MA, You SC, Zhang L, Zhou L, Ryan PB, Prieto-Alhambra D, Reps JM, Rijnbeek PR. Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network. BMC Med Res Methodol 2022; 22:35. [PMID: 35094685 PMCID: PMC8801189 DOI: 10.1186/s12874-022-01505-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 01/03/2022] [Indexed: 12/23/2022] Open
Abstract
Background We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. Methods We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. Results Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69–0.81, COVER-I: 0.73–0.91, and COVER-F: 0.72–0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. Conclusions This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use. Supplementary Information The online version contains supplementary material available at 10.1186/s12874-022-01505-z.
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Pollock A, Risher H, Bentzen S, Roque D, Rao G, Nichols E, Mohindra P. Clinical Outcomes of Patients Treated With Intensity Modulated Proton Therapy (IMPT) Re-Irradiation for Gynecologic Malignancies. Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.1667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Garcia E, Muhlebach M, Sharma R, Khoei A, Rao G. 415: Antimicrobial resistance—Modeling of prolonged treatment in vitro. J Cyst Fibros 2021. [DOI: 10.1016/s1569-1993(21)01839-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Lohith G, Sekar K, Patil S, Bandemagal M, Murugan K, M V, Thungappa S, Rao V, Kudpaje A, Ramasamy M, Ramachandrappa S, Bharathan A, Rao G, Rao D, kumar B. A Randomized Control Trial Comparing Time to Healing of Radiation Induced Acute Skin Reactions Using Biological Membrane Dressing or Topical Methyl Pararosaniline Dye. Int J Radiat Oncol Biol Phys 2021. [DOI: 10.1016/j.ijrobp.2021.07.626] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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You A, Gu J, Wang J, Li J, Zhang Y, Rao G, Ge X, Zhang K, Gao X, Wang D. Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma. Neurologia 2021. [DOI: 10.1016/j.nrl.2021.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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Li X, Ostropolets A, Makadia R, Shoaibi A, Rao G, Sena AG, Martinez-Hernandez E, Delmestri A, Verhamme K, Rijnbeek PR, Duarte-Salles T, Suchard MA, Ryan PB, Hripcsak G, Prieto-Alhambra D. Characterising the background incidence rates of adverse events of special interest for covid-19 vaccines in eight countries: multinational network cohort study. BMJ 2021; 373:n1435. [PMID: 35727911 PMCID: PMC8193077 DOI: 10.1136/bmj.n1435] [Citation(s) in RCA: 78] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/03/2021] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To quantify the background incidence rates of 15 prespecified adverse events of special interest (AESIs) associated with covid-19 vaccines. DESIGN Multinational network cohort study. SETTING Electronic health records and health claims data from eight countries: Australia, France, Germany, Japan, the Netherlands, Spain, the United Kingdom, and the United States, mapped to a common data model. PARTICIPANTS 126 661 070 people observed for at least 365 days before 1 January 2017, 2018, or 2019 from 13 databases. MAIN OUTCOME MEASURES Events of interests were 15 prespecified AESIs (non-haemorrhagic and haemorrhagic stroke, acute myocardial infarction, deep vein thrombosis, pulmonary embolism, anaphylaxis, Bell's palsy, myocarditis or pericarditis, narcolepsy, appendicitis, immune thrombocytopenia, disseminated intravascular coagulation, encephalomyelitis (including acute disseminated encephalomyelitis), Guillain-Barré syndrome, and transverse myelitis). Incidence rates of AESIs were stratified by age, sex, and database. Rates were pooled across databases using random effects meta-analyses and classified according to the frequency categories of the Council for International Organizations of Medical Sciences. RESULTS Background rates varied greatly between databases. Deep vein thrombosis ranged from 387 (95% confidence interval 370 to 404) per 100 000 person years in UK CPRD GOLD data to 1443 (1416 to 1470) per 100 000 person years in US IBM MarketScan Multi-State Medicaid data among women aged 65 to 74 years. Some AESIs increased with age. For example, myocardial infarction rates in men increased from 28 (27 to 29) per 100 000 person years among those aged 18-34 years to 1400 (1374 to 1427) per 100 000 person years in those older than 85 years in US Optum electronic health record data. Other AESIs were more common in young people. For example, rates of anaphylaxis among boys and men were 78 (75 to 80) per 100 000 person years in those aged 6-17 years and 8 (6 to 10) per 100 000 person years in those older than 85 years in Optum electronic health record data. Meta-analytic estimates of AESI rates were classified according to age and sex. CONCLUSION This study found large variations in the observed rates of AESIs by age group and sex, showing the need for stratification or standardisation before using background rates for safety surveillance. Considerable population level heterogeneity in AESI rates was found between databases.
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Affiliation(s)
- Xintong Li
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, USA
| | - Azza Shoaibi
- Janssen Research and Development, Titusville, NJ, USA
| | - Gowtham Rao
- Janssen Research and Development, Titusville, NJ, USA
| | - Anthony G Sena
- Janssen Research and Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | | | | | - Katia Verhamme
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
- Department of Bio-Analysis, Faculty of Pharmaceutical Sciences, Ghent University, Ottergemsesteenweg, Gent, Belgium
| | - Peter R Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Talita Duarte-Salles
- Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Marc A Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, CA, USA
| | - Patrick B Ryan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
- Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
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Li X, Ostropolets A, Makadia R, Shaoibi A, Rao G, Sena AG, Martinez-Hernandez E, Delmestri A, Verhamme K, Rijnbeek PR, Duarte-Salles T, Suchard M, Ryan P, Hripcsak G, Prieto-Alhambra D. Characterizing the incidence of adverse events of special interest for COVID-19 vaccines across eight countries: a multinational network cohort study. medRxiv 2021:2021.03.25.21254315. [PMID: 33791732 PMCID: PMC8010764 DOI: 10.1101/2021.03.25.21254315] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND As large-scale immunization programs against COVID-19 proceed around the world, safety signals will emerge that need rapid evaluation. We report population-based, age- and sex-specific background incidence rates of potential adverse events of special interest (AESI) in eight countries using thirteen databases. METHODS This multi-national network cohort study included eight electronic medical record and five administrative claims databases from Australia, France, Germany, Japan, Netherlands, Spain, the United Kingdom, and the United States, mapped to a common data model. People observed for at least 365 days before 1 January 2017, 2018, or 2019 were included. We based study outcomes on lists published by regulators: acute myocardial infarction, anaphylaxis, appendicitis, Bell's palsy, deep vein thrombosis, disseminated intravascular coagulation, encephalomyelitis, Guillain-Barre syndrome, hemorrhagic and non-hemorrhagic stroke, immune thrombocytopenia, myocarditis/pericarditis, narcolepsy, pulmonary embolism, and transverse myelitis. We calculated incidence rates stratified by age, sex, and database. We pooled rates across databases using random effects meta-analyses. We classified meta-analytic estimates into Council of International Organizations of Medical Sciences categories: very common, common, uncommon, rare, or very rare. FINDINGS We analysed 126,661,070 people. Rates varied greatly between databases and by age and sex. Some AESI (e.g., myocardial infarction, Guillain-Barre syndrome) increased with age, while others (e.g., anaphylaxis, appendicitis) were more common in young people. As a result, AESI were classified differently according to age. For example, myocardial infarction was very rare in children, rare in women aged 35-54 years, uncommon in men and women aged 55-84 years, and common in those aged ≥85 years. INTERPRETATION We report robust baseline rates of prioritised AESI across 13 databases. Age, sex, and variation between databases should be considered if background AESI rates are compared to event rates observed with COVID-19 vaccines.
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Affiliation(s)
- Xintong Li
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, United Kingdom
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, USA
| | - Azza Shaoibi
- Janssen Research and Development, Titusville, NJ, USA
| | - Gowtham Rao
- Janssen Research and Development, Titusville, NJ, USA
| | - Anthony G. Sena
- Janssen Research and Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Antonella Delmestri
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, United Kingdom
| | - Katia Verhamme
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Peter R Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Talita Duarte-Salles
- Fundacio Institut Universitari per a la recerca a l’Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Marc Suchard
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA USA
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, UCLA, Los Angeles, CA, USA
| | - Patrick Ryan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
- Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, United Kingdom
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
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Georgantopoulos P, Eberth JM, Cai B, Rao G, Bennett CL, Emrich CT, Haddock KS, Hébert JR. A spatial assessment of prostate cancer mortality-to-incidence ratios among South Carolina veterans: 1999-2015. Ann Epidemiol 2021; 59:24-32. [PMID: 33836289 DOI: 10.1016/j.annepidem.2021.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 03/23/2021] [Accepted: 03/25/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE To assess veteran-specific prostate cancer (PrCA) mortality-to-incidence ratios (MIR) in South Carolina's (SC) veteran population. METHODS U.S. Veterans Health Administration electronic medical records from January 1999 to December 2015 identified 3,073 PrCA patients residing in 345 ZIP code tabulation areas (ZCTA) within SC. MIRs were calculated for all SC ZCTAs and by key patient- and neighborhood-level risk factors for PrCA. Comparisons between ZCTAs identified as part of a spatial cluster were compared with non-significant ZCTAs using t tests. RESULTS The MIR was 0.17 overall, ranging from a low of 0.15 among Black men to 0.20 among White men. Among metropolitan ZCTAs, the MIR was 0.18 compared to 0.16 in non-metropolitan ZCTAs. Two clusters of higher-than-expected MIRs were found in the Upstate region. CONCLUSIONS Identification of spatial clusters of higher- or lower-than-expected MIRs allows for further testing of possible explanatory factors, and the capacity to target resources and policies according to greatest need.
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Affiliation(s)
- Peter Georgantopoulos
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC; Southern Network on Adverse Reactions (SONAR), South Carolina Center of Economic Excellence for Medication Safety, College of Pharmacy, University of South Carolina, Columbia, SC; Columbia Veterans Affairs Health Care System, Columbia, SC.
| | - Jan M Eberth
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
| | - Bo Cai
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
| | - Gowtham Rao
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
| | - Charles L Bennett
- Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC; Southern Network on Adverse Reactions (SONAR), South Carolina Center of Economic Excellence for Medication Safety, College of Pharmacy, University of South Carolina, Columbia, SC; Columbia Veterans Affairs Health Care System, Columbia, SC
| | - Christopher T Emrich
- College of Community Innovation and Education, University of Central Florida, Orlando, FL
| | | | - James R Hébert
- South Carolina Statewide Cancer Prevention and Control Program, University of South Carolina, Columbia, SC; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC
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Reps JM, Kim C, Williams RD, Markus AF, Yang C, Duarte-Salles T, Falconer T, Jonnagaddala J, Williams A, Fernández-Bertolín S, DuVall SL, Kostka K, Rao G, Shoaibi A, Ostropolets A, Spotnitz ME, Zhang L, Casajust P, Steyerberg EW, Nyberg F, Kaas-Hansen BS, Choi YH, Morales D, Liaw ST, Abrahão MTF, Areia C, Matheny ME, Lynch KE, Aragón M, Park RW, Hripcsak G, Reich CG, Suchard MA, You SC, Ryan PB, Prieto-Alhambra D, Rijnbeek PR. Implementation of the COVID-19 Vulnerability Index Across an International Network of Health Care Data Sets: Collaborative External Validation Study. JMIR Med Inform 2021; 9:e21547. [PMID: 33661754 PMCID: PMC8023380 DOI: 10.2196/21547] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 11/12/2020] [Accepted: 02/27/2021] [Indexed: 11/18/2022] Open
Abstract
Background SARS-CoV-2 is straining health care systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate patients who require hospitalization from those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision-making during the pandemic. However, the model is at high risk of bias according to the “prediction model risk of bias assessment” criteria, and it has not been externally validated. Objective The aim of this study was to externally validate the C-19 index across a range of health care settings to determine how well it broadly predicts hospitalization due to pneumonia in COVID-19 cases. Methods We followed the Observational Health Data Sciences and Informatics (OHDSI) framework for external validation to assess the reliability of the C-19 index. We evaluated the model on two different target populations, 41,381 patients who presented with SARS-CoV-2 at an outpatient or emergency department visit and 9,429,285 patients who presented with influenza or related symptoms during an outpatient or emergency department visit, to predict their risk of hospitalization with pneumonia during the following 0-30 days. In total, we validated the model across a network of 14 databases spanning the United States, Europe, Australia, and Asia. Results The internal validation performance of the C-19 index had a C statistic of 0.73, and the calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data, the model obtained C statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US, and South Korean data sets, respectively. The calibration was poor, with the model underestimating risk. When validated on 12 data sets containing influenza patients across the OHDSI network, the C statistics ranged between 0.40 and 0.68. Conclusions Our results show that the discriminative performance of the C-19 index model is low for influenza cohorts and even worse among patients with COVID-19 in the United States, Spain, and South Korea. These results suggest that C-19 should not be used to aid decision-making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.
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Affiliation(s)
- Jenna M Reps
- Janssen Research & Development, Titusville, NJ, United States
| | - Chungsoo Kim
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea
| | - Ross D Williams
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Aniek F Markus
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Cynthia Yang
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Talita Duarte-Salles
- Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | - Jitendra Jonnagaddala
- School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia
| | - Andrew Williams
- Tufts Institute for Clinical Research and Health Policy Studies, Boston, MA, United States
| | - Sergio Fernández-Bertolín
- Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Scott L DuVall
- Department of Veterans Affairs, University of Utah, Salt Lake City, UT, United States
| | - Kristin Kostka
- Real World Solutions, IQVIA, Cambridge, MA, United States
| | - Gowtham Rao
- Janssen Research & Development, Titusville, NJ, United States
| | - Azza Shoaibi
- Janssen Research & Development, Titusville, NJ, United States
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | - Matthew E Spotnitz
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | - Lin Zhang
- Melbourne School of Public Health, The University of Melbourne, Victoria, Australia.,School of Public Health, Peking Union Medical College, Beijing, China
| | - Paula Casajust
- Department of Real-World Evidence, Trial Form Support, Barcelona, Spain
| | - Ewout W Steyerberg
- Department of Public Health, Erasmus University Medical Center, Rotterdam, Netherlands.,Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Benjamin Skov Kaas-Hansen
- Clinical Pharmacology Unit, Zealand University Hospital, Roskilde, Denmark.,NNF Centre for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Young Hwa Choi
- Department of Infectious Diseases, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Daniel Morales
- Division of Population Health and Genomics, University of Dundee, Dundee, United Kingdom
| | - Siaw-Teng Liaw
- School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia
| | | | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Michael E Matheny
- Department of Veterans Affairs, Vanderbilt University, Nashville, TN, United States
| | - Kristine E Lynch
- Department of Veterans Affairs, University of Utah, Salt Lake City, UT, United States
| | - María Aragón
- Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina, Barcelona, Spain
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, NY, United States
| | | | - Marc A Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, United States
| | - Seng Chan You
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Patrick B Ryan
- Janssen Research & Development, Titusville, NJ, United States
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
| | - Peter R Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, Netherlands
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Weaver J, Shoaibi A, Truong HQ, Larbi L, Wu S, Wildgoose P, Rao G, Freedman A, Wang L, Yuan Z, Barnathan E. Comparative Risk Assessment of Severe Uterine Bleeding Following Exposure to Direct Oral Anticoagulants: A Network Study Across Four Observational Databases in the USA. Drug Saf 2021; 44:479-497. [PMID: 33651368 PMCID: PMC7994226 DOI: 10.1007/s40264-021-01060-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/16/2021] [Indexed: 10/26/2022]
Abstract
BACKGROUND Antithrombotic therapies are associated with an increased bleeding risk. Abnormal uterine bleeding data have been reported in clinical trials of patients with venous thromboembolism (VTE), but data are limited for patients with atrial fibrillation (AF). OBJECTIVE Using real-world data from four US healthcare databases (October 2010 to December 2018), we compared the occurrence of severe uterine bleeding among women newly exposed to rivaroxaban, apixaban, dabigatran, and warfarin stratified by indication. METHODS To reduce potential confounding, patients in comparative cohorts were matched on propensity scores. Treatment effect estimates were generated using Cox proportional hazard models for each indication, in each database, and only for pairwise comparisons that met a priori study diagnostics. If estimates were homogeneous (I2 < 40%), a meta-analysis across databases was performed and pooled hazard ratios reported. RESULTS Data from 363,919 women newly exposed to a direct oral anticoagulant or warfarin with a prior diagnosis of AF (60.8%) or VTE (39.2%) were analyzed. Overall incidence of severe uterine bleeding was low in the populations exposed to direct oral anticoagulants, although relatively higher in the younger VTE population vs the AF population (unadjusted incidence rates: 2.8-33.7 vs 1.9-10.0 events/1000 person-years). In the propensity score-matched AF population, a suggestive, moderately increased risk of severe uterine bleeding was observed for rivaroxaban relative to warfarin [hazard ratios and 95% confidence intervals from 0.83 (0.27-2.48) to 2.84 (1.32-6.23) across databases with significant heterogeneity], apixaban [pooled hazard ratio 1.45 (0.91-2.28)], and dabigatran [2.12 (1.01-4.43)], which were sensitive to the time-at-risk period. In the propensity score-matched VTE population, a consistent increased risk of severe uterine bleeding was observed for rivaroxaban relative to warfarin [2.03 (1.19-3.27)] and apixaban [2.25 (1.45-3.41)], which were insensitive to the time-at-risk period. CONCLUSIONS For women who need antithrombotic therapy, personalized management strategies with careful evaluation of benefits and risks are required. CLINICALTRIALS. GOV REGISTRATION NCT04394234; registered in May 2020.
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Affiliation(s)
- James Weaver
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
| | - Azza Shoaibi
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
| | - Huy Q Truong
- Janssen Research & Development, LLC, Raritan, NJ, USA
| | - Leila Larbi
- Janssen Research & Development, LLC, Raritan, NJ, USA
| | - Shujian Wu
- Janssen Research & Development, LLC, Horsham, PA, USA
| | - Peter Wildgoose
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
| | - Gowtham Rao
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
| | - Amy Freedman
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
| | - Lu Wang
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA
| | - Zhong Yuan
- Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA.
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Mohindra P, Pollock A, Patel A, Roque D, Rao G, Nichols E. First Clinical Experience of Quality Assurance CT Scan Adapted Intensity Modulated Proton Therapy for Utero-cervical Cancers. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.1537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Li J, Ludmir E, Wang Y, Guha-Thakurta N, McAleer M, Settle S, Yeboa D, Ghia A, McGovern S, Chung C, Woodhouse K, Briere T, Sullaway C, Liu D, Rao G, Chang E, Mahajan A, Sulman E, Brown P, Wefel J. Stereotactic Radiosurgery versus Whole-brain Radiation Therapy for Patients with 4-15 Brain Metastases: A Phase III Randomized Controlled Trial. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2108] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Sridhar P, Roopesh K, Anuradha P, Deputy M, Bharathan A, Senapati M, Ram A, Gupta M, Muttagi V, Rao G, Patil S, Chirodoni Thungappa S, Hussain S, Ajai kumar B. Understanding the Immune Profile of SBRT – Could It Evolve Into Becoming A Surrogate Biomarkers To Treatment Response. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.1598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Soliman M, Wang Y, Farooqi A, Bishop A, Yeboa D, McGovern S, McAleer M, Briere T, Campbell M, Tu S, Ferguson S, Rao G, Nieto Y, Li J. Primary Management of Non-Seminomatous Germ Cell Brain Metastases with Stereotactic Radiosurgery: A Case Series. Int J Radiat Oncol Biol Phys 2020. [DOI: 10.1016/j.ijrobp.2020.07.2035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Burn E, You SC, Sena AG, Kostka K, Abedtash H, Abrahão MTF, Alberga A, Alghoul H, Alser O, Alshammari TM, Aragon M, Areia C, Banda JM, Cho J, Culhane AC, Davydov A, DeFalco FJ, Duarte-Salles T, DuVall S, Falconer T, Fernandez-Bertolin S, Gao W, Golozar A, Hardin J, Hripcsak G, Huser V, Jeon H, Jing Y, Jung CY, Kaas-Hansen BS, Kaduk D, Kent S, Kim Y, Kolovos S, Lane JCE, Lee H, Lynch KE, Makadia R, Matheny ME, Mehta PP, Morales DR, Natarajan K, Nyberg F, Ostropolets A, Park RW, Park J, Posada JD, Prats-Uribe A, Rao G, Reich C, Rho Y, Rijnbeek P, Schilling LM, Schuemie M, Shah NH, Shoaibi A, Song S, Spotnitz M, Suchard MA, Swerdel JN, Vizcaya D, Volpe S, Wen H, Williams AE, Yimer BB, Zhang L, Zhuk O, Prieto-Alhambra D, Ryan P. Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study. Nat Commun 2020; 11:5009. [PMID: 33024121 PMCID: PMC7538555 DOI: 10.1038/s41467-020-18849-z] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 09/10/2020] [Indexed: 01/08/2023] Open
Abstract
Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.
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Affiliation(s)
- Edward Burn
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Seng Chan You
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
| | - Anthony G Sena
- Janssen Research and Development, Titusville, NJ, USA
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | | | | | - Amanda Alberga
- Observational Health Data Sciences and Informatics Network, Alberta, Canada
| | - Heba Alghoul
- Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine
| | - Osaid Alser
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Thamir M Alshammari
- Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia
| | - Maria Aragon
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Carlos Areia
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Juan M Banda
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Jaehyeong Cho
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
| | - Aedin C Culhane
- Data Science, Dana-Farber Cancer Institute. Biostatistics, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Alexander Davydov
- Odysseus Data Services, Inc., Cambridge, MA, USA
- Department for Microbiology, Virology and Immunology, Belarusian State Medical University, Minsk, Belarus
| | | | - Talita Duarte-Salles
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Scott DuVall
- Department of Veterans Affairs, Salt Lake City, UT, USA
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Thomas Falconer
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Sergio Fernandez-Bertolin
- Fundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | - Weihua Gao
- Health Economics and Outcomes Research, AbbVie, North Chicago, IL, USA
| | - Asieh Golozar
- Pharmacoepidemiology, Regeneron, NY, USA
- Department of Epidemiology, Johns Hopkins School of Public, Baltimore, MD, USA
| | - Jill Hardin
- Janssen Research and Development, Titusville, NJ, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Vojtech Huser
- National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Hokyun Jeon
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Yonghua Jing
- Health Economics and Outcomes Research, AbbVie, North Chicago, IL, USA
| | - Chi Young Jung
- Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Daegu Catholic University Medical Center, Daegu, Korea
| | - Benjamin Skov Kaas-Hansen
- Clinical Pharmacology Unit, Zealand University Hospital, Køge, Denmark
- NNF Centre for Protein Research, University of Copenhagen, København, Denmark
| | - Denys Kaduk
- Odysseus Data Services, Inc., Cambridge, MA, USA
- Department of Pediatrics № 2, V. N. Karazin Kharkiv National University, Kharkiv, Ukraine
| | - Seamus Kent
- Science Policy and Research, National Institute for Health and Care Excellence, London, UK
| | - Yeesuk Kim
- Department of Orthopaedic Surgery, College of Medicine, Hanyang University, Seoul, Korea
| | - Spyros Kolovos
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Jennifer C E Lane
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Hyejin Lee
- Bigdata Department, Health Insurance Review & Assessment Service, Wonju, Korea
| | - Kristine E Lynch
- Department of Veterans Affairs, Salt Lake City, UT, USA
- University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Rupa Makadia
- Janssen Research and Development, Titusville, NJ, USA
| | - Michael E Matheny
- GRECC, Tennessee Valley Healthcare System VA, Nashville, TN, USA
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Paras P Mehta
- College of Medicine-Tucson, University of Arizona, Tucson, AZ, USA
| | - Daniel R Morales
- Division of Population Health and Genomics, University of Dundee, Dundee, UK
| | - Karthik Natarajan
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Fredrik Nyberg
- School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Ostropolets
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Rae Woong Park
- Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Jimyung Park
- Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Jose D Posada
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Albert Prats-Uribe
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Gowtham Rao
- Janssen Research and Development, Titusville, NJ, USA
| | | | - Yeunsook Rho
- Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK
| | - Peter Rijnbeek
- Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Lisa M Schilling
- Data Science to Patient Value Program, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Martijn Schuemie
- Janssen Research and Development, Titusville, NJ, USA
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | - Nigam H Shah
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Azza Shoaibi
- Janssen Research and Development, Titusville, NJ, USA
| | - Seokyoung Song
- Department of Anesthesiology and Pain Medicine, Catholic University of Daegu, School of Medicine, Gyeongsan, Korea
| | - Matthew Spotnitz
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Marc A Suchard
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, CA, USA
| | | | | | - Salvatore Volpe
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Haini Wen
- Shuguang Hospital affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Andrew E Williams
- Tufts Institute for Clinical Research and Health Policy Studies, Boston, MA, USA
| | - Belay B Yimer
- Centre for Epidemiology Versus Arthritis, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK
| | - Lin Zhang
- School of Public Health, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Oleg Zhuk
- Odysseus Data Services, Inc., Cambridge, MA, USA
| | - Daniel Prieto-Alhambra
- Centre for Statistics in Medicine (CSM), Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDROMS), University of Oxford, Oxford, UK.
| | - Patrick Ryan
- Janssen Research and Development, Titusville, NJ, USA
- Columbia University, New York, NY, USA
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Elisofon SA, Magee JC, Ng VL, Horslen SP, Fioravanti V, Economides J, Erinjeri J, Anand R, Mazariegos GV, Martin A, Mannino D, Flynn L, Mohammad S, Alonso E, Superina R, Brandt K, Riordan M, Lokar J, Ito J, Elisofon S, Zapata L, Jain A, Foristal E, Gupta N, Whitlow C, Naik K, Espinosa H, Miethke A, Hawkins A, Hardy J, Engels E, Schreibeis A, Ovchinsky N, Kogan‐Liberman D, Cunningham R, Malik P, Sundaram S, Feldman A, Garcia B, Yanni G, Kohli R, Emamaullee J, Secules C, Magee J, Lopez J, Bilhartz J, Hollenbeck J, Shaw B, Bartow C, Forest S, Rand E, Byrne A, Linguiti I, Wann L, Seidman C, Mazariegos G, Soltys K, Squires J, Kepler A, Vitola B, Telega G, Lerret S, Desai D, Moghe J, Cutright L, Daniel J, Andrews W, Fioravanti V, Slowik V, Cisneros R, Faseler M, Hufferd M, Kelly B, Sudan D, Mavis A, Moats L, Swan‐Nesbit S, Yazigi N, Buranych A, Hobby A, Rao G, Maccaby B, Gopalareddy V, Boulware M, Ibrahim S, El Youssef M, Furuya K, Schatz A, Weckwerth J, Lovejoy C, Kasi N, Nadig S, Law M, Arnon R, Chu J, Bucuvalas J, Czurda M, Secheli B, Almy C, Haydel B, Lobritto S, Emand J, Biney‐Amissah E, Gamino D, Gomez A, Himes R, Seal J, Stewart S, Bergeron J, Truxillo A, Lebel S, Davidson H, Book L, Ramstack D, Riley A, Jennings C, Horslen S, Hsu E, Wallace K, Turmelle Y, Nadler M, Postma S, Miloh T, Economides J, Timmons K, Ng V, Subramonian A, Dharmaraj B, McDiarmid S, Feist S, Rhee S, Perito E, Gallagher L, Smith K, Ebel N, Zerofsky M, Nogueira J, Greer R, Gilmour S, Robert C, Cars C, Azzam R, Boone P, Garbarino N, Lalonde M, Kerkar N, Dokus K, Helbig K, Grizzanti M, Tomiyama K, Cocking J, Alexopoulos S, Bhave C, Schillo R, Bailey A, Dulek D, Ramsey L, Ekong U, Valentino P, Hettiarachchi D, Tomlin R. Society of pediatric liver transplantation: Current registry status 2011-2018. Pediatr Transplant 2020; 24:e13605. [PMID: 31680409 DOI: 10.1111/petr.13605] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 08/08/2019] [Accepted: 09/27/2019] [Indexed: 11/29/2022]
Abstract
BACKGROUND SPLIT was founded in 1995 in order to collect comprehensive prospective data on pediatric liver transplantation, including waiting list data, transplant, and early and late outcomes. Since 2011, data collection of the current registry has been refined to focus on prospective data and outcomes only after transplant to serve as a foundation for the future development of targeted clinical studies. OBJECTIVE To report the outcomes of the SPLIT registry from 2011 to 2018. METHODS This is a multicenter, cross-sectional analysis characterizing patients transplanted and enrolled in the SPLIT registry between 2011 and 2018. All patients, <18 years of age, received a first liver-only, a combined liver-kidney, or a combined liver-pancreas transplant during this study period. RESULTS A total of 1911 recipients from 39 participating centers in North America were registered. Indications included biliary atresia (38.5%), metabolic disease (19.1%), tumors (11.7%), and fulminant liver failure (11.5%). Greater than 50% of recipients were transplanted as either Status 1A/1B or with a MELD/PELD exception score. Incompatible transplants were performed in 4.1%. Kaplan-Meier estimates of 1-year patient and graft survival were 97.3% and 96.6%. First 30 days of surgical complications included reoperation (31.7%), hepatic artery thrombosis (6.3%), and portal vein thrombosis (3.2%). In the first 90 days, biliary tract complications were reported in 13.6%. Acute cellular rejection during first year was 34.7%. At 1 and 2 years of follow-up, 39.2% and 50.6% had normal liver tests on monotherapy (tacrolimus or sirolimus). Further surgical, survival, allograft function, and complications are detailed.
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Affiliation(s)
- Scott A Elisofon
- Division of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, Massachusetts
| | - John C Magee
- Division of Surgery, University of Michigan Transplant Center, Ann Arbor, Michigan
| | - Vicky L Ng
- Division of Pediatric Gastroenterology, Hepatology, and Nutrition, Transplant and Regenerative Medicine Center, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Simon P Horslen
- Department of Pediatrics, Seattle Children's Hospital, University of Washington School of Medicine, Seattle, Washington
| | - Vicki Fioravanti
- Section of Hepatology and Liver Transplantation, Children's Mercy Hospital, Kansas City, Missouri
| | | | | | | | - George V Mazariegos
- Division of Pediatric Transplant Surgery, Hillman Center for Pediatric Transplantation, UPMC Children's Hospital of Pittsburgh, Pittsburgh, PA, USA
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Georgantopoulos P, Eberth JM, Cai B, Emrich C, Rao G, Bennett CL, Haddock KS, Hébert JR. Patient- and area-level predictors of prostate cancer among South Carolina veterans: a spatial analysis. Cancer Causes Control 2020; 31:209-220. [DOI: 10.1007/s10552-019-01263-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 12/21/2019] [Indexed: 12/29/2022]
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Chadefaux D, Gueguen N, Thouze A, Rao G. 3D propagation of the shock-induced vibrations through the whole lower-limb during running. J Biomech 2019; 96:109343. [PMID: 31558309 DOI: 10.1016/j.jbiomech.2019.109343] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 09/10/2019] [Accepted: 09/11/2019] [Indexed: 11/30/2022]
Affiliation(s)
- D Chadefaux
- Aix-Marseille Univ, CNRS, ISM, Marseille, France; Université Paris 13 - Institut de Biomécanique Humaine Georges Charpak (EA 4494), Paris, France.
| | - N Gueguen
- Department of Movement Sciences, Décathlon, Villeneuve d'Ascq, France
| | - A Thouze
- Department of Movement Sciences, Décathlon, Villeneuve d'Ascq, France
| | - G Rao
- Aix-Marseille Univ, CNRS, ISM, Marseille, France
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Muhammad Adil ZA, Nur Zawani J, Hazariah AH, Rao G, Zailiza S, Mohd Nasir H. Methanol outbreak in the district of Hulu Langat, 2018. Med J Malaysia 2019; 74:413-417. [PMID: 31649218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
INTRODUCTION A methanol outbreak occurred in the district of Hulu Langat on 16 September 2018. The Hulu Langat District Health Office received 25 notifications of a suspected methanol poisoning from Kajang and Ampang Hospital. An outbreak investigation was done to determine the source followed by a preventive and control measure. METHOD Active case detection was done on cases living quarters and workplaces. Patients were interviewed, and their blood and urine samples were sent for methanol analysis. Samples of suspected alcoholic beverages were also sent for analysis. A suspected case was defined as any person presented with clinical symptoms with a history of consuming alcoholic beverages within five days before symptoms and high anion gap metabolic acidosis. A confirmed case was defined as a suspected case with positive blood and urine methanol. RESULTS In total, there were 25 suspected cases, of which 12 cases were confirmed. The calculated attack rate was 48%. There were six mortalities (50%) secondary to severe metabolic acidosis. The most common presenting symptom was vomiting (75%) and abdominal pain (41.7%). These cases were linked to consumption of illicitly produced alcohol. Samples of the alcoholic drinks were positive containing high level of methanol. CONCLUSION The methanol outbreak in the Hulu Langat was successfully managed. Appropriate control and prevention measures were taken, including health promotion and joint enforcement activities. Steps were taken successfully through collaborations with multiple agencies and cooperation with Selangor Health Departments and the Ministry of Health. Continuous surveillance on the product of liquor, and health promotion are essential to prevent a similar outbreak from happening again in future.
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Affiliation(s)
- Z A Muhammad Adil
- Ministry of Health Malaysia, Hulu Langat District Health Office, Kajang, Selangor, Malaysia.
| | - J Nur Zawani
- Ministry of Health Malaysia, Hulu Langat District Health Office, Kajang, Selangor, Malaysia
| | - A H Hazariah
- Ministry of Health Malaysia, Hulu Langat District Health Office, Kajang, Selangor, Malaysia
| | - G Rao
- Ministry of Health Malaysia, Hulu Langat District Health Office, Kajang, Selangor, Malaysia
| | - S Zailiza
- Ministry of Health Malaysia, Hulu Langat District Health Office, Kajang, Selangor, Malaysia
| | - H Mohd Nasir
- Ministry of Health Malaysia, Hulu Langat District Health Office, Kajang, Selangor, Malaysia
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Traylor JI, Bastos DCA, Fuentes D, Muir M, Patel R, Kumar VA, Stafford RJ, Rao G, Prabhu SS. Dynamic Contrast-Enhanced MRI in Patients with Brain Metastases Undergoing Laser Interstitial Thermal Therapy: A Pilot Study. AJNR Am J Neuroradiol 2019; 40:1451-1457. [PMID: 31371353 DOI: 10.3174/ajnr.a6144] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Accepted: 06/19/2019] [Indexed: 12/19/2022]
Abstract
BACKGROUND AND PURPOSE Tumor recurrence is difficult to predict in patients receiving laser ablation for intracranial malignancy. We assessed the efficacy of the initial area under the time-to-signal intensity curve at 60 seconds (iAUC60) from dynamic contrast-enhanced MR imaging in predicting progression-free survival in patients with brain metastases following laser interstitial thermal therapy. MATERIALS AND METHODS The study population was a consecutive series of patients undergoing laser interstitial thermal therapy for brain metastases. Patient demographics including age, sex, tumor histology, and Karnofsky Performance Scale were collected prospectively. Preoperative, postoperative, and 1-month follow-up dynamic contrast-enhanced MRIs were analyzed. Values of iAUC60 were computed using a trapezoidal rule applied to the time history of contrast uptake over the first 60 seconds postenhancement. The change in iAUC60 (ΔiAUC60) was calculated by taking the difference between the values of iAUC60 from 2 time points. Pearson correlation coefficients were calculated between progression-free survival, defined as the time from laser interstitial thermal therapy to tumor recurrence, and iAUC60 or ΔiAUC60 values. RESULTS Thirty-three cases of laser interstitial thermal therapy for 32 brain metastases in a cohort of 27 patients were prospectively analyzed. A significant relationship was observed between the values of iAUC60 from postoperative dynamic contrast-enhanced MR imaging and progression-free survival with Pearson correlation (P = .03) and Cox univariate analysis (P = .01). The relationship between preoperative and 1-month follow-up dynamic contrast-enhanced MR imaging was not significantly correlated with progression-free survival. Similarly, no statistically significant relationship was observed with ΔiAUC60 and progression-free survival between any time points. CONCLUSIONS Progression-free survival is difficult to predict in patients undergoing laser interstitial thermal therapy for brain metastases due to confounding with posttreatment change. iAUC60 extracted from postoperative dynamic contrast-enhanced MR imaging shows promise for accurately prognosticating patients following this operative therapy.
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Affiliation(s)
- J I Traylor
- From the Departments of Neurosurgery (J.I.T., D.C.A.B., M.M., R.P., G.R., S.S.P.)
| | - D C A Bastos
- From the Departments of Neurosurgery (J.I.T., D.C.A.B., M.M., R.P., G.R., S.S.P.)
| | | | - M Muir
- From the Departments of Neurosurgery (J.I.T., D.C.A.B., M.M., R.P., G.R., S.S.P.)
| | - R Patel
- From the Departments of Neurosurgery (J.I.T., D.C.A.B., M.M., R.P., G.R., S.S.P.)
| | - V A Kumar
- Diagnostic Radiology (V.A.K.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | - G Rao
- From the Departments of Neurosurgery (J.I.T., D.C.A.B., M.M., R.P., G.R., S.S.P.)
| | - S S Prabhu
- From the Departments of Neurosurgery (J.I.T., D.C.A.B., M.M., R.P., G.R., S.S.P.)
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Room R, Callinan S, Greenfield T, Rekve D, Waleewong O, Stanesby O, Thamarangsi T, Benegal V, Casswell S, Florenzano R, Hanh T, Hettige S, Karriker-Jaffe K, Obot I, Rao G, Siengsounthone L, Laslett AM. The social location of harm from others' drinking in 10 societies. Addiction 2019; 114:425-433. [PMID: 30248718 PMCID: PMC6377290 DOI: 10.1111/add.14447] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 08/02/2018] [Accepted: 09/20/2018] [Indexed: 01/23/2023]
Abstract
AIMS Survey data from 10 diverse countries were used to analyse the social location of harms from others' drinking: which segments of the population are more likely to be adversely affected by such harm, and how does this differ between societies? METHODS General-population surveys in Australia, Chile, India, Laos, New Zealand, Nigeria, Sri Lanka, Thailand, United States and Vietnam, with a primary focus on the social location of the harmed person by gender, age groups, rural/urban residence and drinking status. Harms from known drinkers were analysed separately from harms from strangers. RESULTS In all sites, risky or moderate drinkers were more likely than abstainers to report harm from the drinking of known drinkers, with risky drinkers the most likely to report harm. This was also generally true for harm from strangers' drinking, although the patterns were more mixed in Vietnam and Thailand. Harm from strangers' drinking was more often reported by males, while gender disparity in harm from known drinkers varied between sites. Younger adults were more likely to experience harm both from known drinkers and from strangers in some, but not all, societies. Only a few sites showed significant urban/rural differences, with disparities varying in direction. In multivariate analyses, most relationships remained, although some were no longer significant. CONCLUSION The social location of harms from others' drinking, whether known or a stranger, varies considerably between societies. One near-commonality among the societies is that those who are themselves risky drinkers are more likely to suffer harm from others' drinking.
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Affiliation(s)
- R. Room
- Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia; Centre for Social Research on Alcohol and Drugs, Stockholm University, Stockholm, Sweden,
| | - S. Callinan
- Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia,
| | - T.K. Greenfield
- Alcohol Research Group, Public Health Institute, Emeryville, California, USA,
| | - D. Rekve
- Mental Health and Substance Abuse, WHO, Geneva, Switzerland
| | - O. Waleewong
- Health Promotion Policy Research Center; International Health Policy Program, Ministry of Public Health, Nonthaburi Thailand,
| | - O. Stanesby
- Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia,
| | - T. Thamarangsi
- Department of Non-Communicable Diseases and Environmental Health, World Health Organization Regional Office for South-East Asia, New Delhi, India,
| | - V. Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and NeuroSciences, Bangalore, India,
| | - S. Casswell
- SHORE and Whariki Research Centre, School of Public Health, Massey University, Auckland, New Zealand,
| | - R. Florenzano
- Universidad del Desarrollo, Facultades de Psicología y de Ciencia Social; Universidades de Chile y de los Andes, Departamento de Psiquiatría, Santiago de Chile, Chile,
| | - T.M.H. Hanh
- Health Strategy and Policy Institute, Ministry of Health, Vietnam,
| | - S. Hettige
- Department of Sociology, University of Colombo, Colombo, Sri Lanka and Adjunct Professor, Globalism Research Centre, School of Social Sciences, RMIT University, Melbourne, Australia,
| | - K.J. Karriker-Jaffe
- Alcohol Research Group, Public Health Institute, Emeryville, California, USA,
| | - I. Obot
- Department of Psychology, University of Uyo, Uyo, Nigeria & Centre for Research and Information on Substance Abuse (CRISA), Uyo, Nigeria,
| | - G. Rao
- Centre for Public Health, National Institute of Mental Health and NeuroSciences, Bangalore, India,
| | - L. Siengsounthone
- Research Outcomes Management Department, National Institute of Public Health, Ministry of Health, Vientiane Capital, Lao PDR,
| | - A.-M. Laslett
- Centre for Alcohol Policy Research, La Trobe University, Melbourne, Australia; National Drug Research Institute, Curtin University, Fitzroy, Victoria, Australia,
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Shillo P, Selvarajah D, Greig M, Gandhi R, Rao G, Wilkinson ID, Anand P, Tesfaye S. Reduced vitamin D levels in painful diabetic peripheral neuropathy. Diabet Med 2019; 36:44-51. [PMID: 30102801 DOI: 10.1111/dme.13798] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/08/2018] [Indexed: 12/25/2022]
Abstract
AIM Recent studies have reported an association between low vitamin D levels and diabetic peripheral neuropathy. However, many of these did not differentiate between people with painful diabetic peripheral neuropathy and those with painless diabetic peripheral neuropathy, or assess major confounding factors including sunlight exposure and daily activity. Our study addressed these limitations and evaluated vitamin D levels in people with carefully phenotyped diabetic peripheral neuropathy and controls. METHODS Forty-five white Europeans with Type 2 diabetes and 14 healthy volunteers underwent clinical and neurophysiological assessments. People with Type 2 diabetes were then divided into three groups (17 with painful diabetic peripheral neuropathy, 14 with painless diabetic peripheral neuropathy and 14 with no diabetic peripheral neuropathy). All had seasonal sunlight exposure and daily activity measured, underwent a lower limb skin biopsy and had 25-hydroxyvitamin D measured during the summer months, July to September. RESULTS After adjusting for age, BMI, activity score and sunlight exposure, 25-hydroxyvitamin D levels (nmol/l) (se) were significantly lower in people with painful diabetic peripheral neuropathy [painful diabetic peripheral neuropathy 34.9 (5.8), healthy volunteers 62.05 (6.7), no diabetic peripheral neuropathy 49.6 (6.1), painless diabetic peripheral neuropathy 53.1 (6.2); ANCOVAP = 0.03]. Direct logistic regression was used to assess the impact of seven independent variables on painful diabetic peripheral neuropathy. Vitamin D was the only independent variable to make a statistically significant contribution to the model with an inverted odds ratio of 1.11. Lower 25-hydroxyvitamin D levels also correlated with lower cold detection thresholds (r = 0.39, P = 0.02) and subepidermal nerve fibre densities (r = 0.42, P = 0.01). CONCLUSIONS We have demonstrated a significant difference in 25-hydroxyvitamin D levels in well-characterized people with painful diabetic peripheral neuropathy, while accounting for the main confounding factors. This suggests a possible role for vitamin D in the pathogenesis of painful diabetic peripheral neuropathy. Further prospective and intervention trials are required to prove causality between low vitamin D levels and painful diabetic peripheral neuropathy.
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Affiliation(s)
- P Shillo
- Diabetes Research Unit, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield
| | - D Selvarajah
- Department of Oncology and Human Metabolism, University of Sheffield, Sheffield
| | - M Greig
- Diabetes Research Unit, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield
| | - R Gandhi
- Diabetes Research Unit, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield
| | - G Rao
- Diabetes Research Unit, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield
| | - I D Wilkinson
- Academic Unit of Radiology, University of Sheffield, Sheffield
| | - P Anand
- Peripheral Neuropathy Unit, Imperial College London, London, UK
| | - S Tesfaye
- Diabetes Research Unit, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield
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Callinan S, Rankin G, Room R, Stanesby O, Rao G, Waleewong O, Greenfield TK, Hope A, Laslett AM. Harms from a partner's drinking: an international study on adverse effects and reduced quality of life for women. Am J Drug Alcohol Abuse 2018; 45:170-178. [PMID: 30495983 DOI: 10.1080/00952990.2018.1540632] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
BACKGROUND Partners of heavy drinking individuals can be detrimentally affected as a result of their partner's drinking. OBJECTIVES The aim of this study was to identify the proportion of heterosexual intimate partner relationships with a heavy drinking male that resulted in reported alcohol-related harm and to investigate the impact of this on well-being in 9 countries. METHODS This study used survey data from the Gender and Alcohol's Harm to Others (GENAHTO) Project on Alcohol's Harm to Others in 9 countries (10,613 female respondents, 7,091 with intimate live-in partners). Respondents were asked if their partners drinking had negatively affected them as well as questions on depression, anxiety, and satisfaction with life. RESULTS The proportion of partnered respondents that reported having a harmful heavy drinking partner varied across countries, from 4% in Nigeria and the US to 33% in Vietnam. The most consistent correlate of experiencing harm was being oneself a heavy episodic drinker, most likely as a proxy measure for the acceptability of alcohol consumption in social circles. Women with a harmful heavy drinking partner reported significantly lower mean satisfaction with life than those with a partner that did not drink heavily. CONCLUSIONS Harms to women from heavy drinking intimate partners appear across a range of subgroups and impact on a wide range of women, at least demographically speaking. Women living with a heavy drinking spouse experience higher levels of anxiety and depression symptoms and lower satisfaction with life.
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Affiliation(s)
- S Callinan
- a Centre for Alcohol Policy Research , La Trobe University , Bundoora , Australia
| | - G Rankin
- a Centre for Alcohol Policy Research , La Trobe University , Bundoora , Australia
| | - R Room
- a Centre for Alcohol Policy Research , La Trobe University , Bundoora , Australia.,b Centre for Social Research on Alcohol & Drugs , Stockholm University , Stockholm , Sweden
| | - O Stanesby
- a Centre for Alcohol Policy Research , La Trobe University , Bundoora , Australia
| | - G Rao
- c Centre for Public Health , National Institute of Mental Health and NeuroSciences , Bangalore , India
| | - O Waleewong
- a Centre for Alcohol Policy Research , La Trobe University , Bundoora , Australia.,d School of Population and Global Health , University of Melbourne , Melbourne , Australia.,e International Health Policy Program (IHPP) , Ministry of Public Health , Nonthaburi , Thailand
| | - T K Greenfield
- f Alcohol Research Group , Public Health Institute , Emeryville , CA , USA
| | - A Hope
- g Department of Public Health and Primary Care , Trinity College , Dublin , Ireland
| | - A-M Laslett
- a Centre for Alcohol Policy Research , La Trobe University , Bundoora , Australia.,d School of Population and Global Health , University of Melbourne , Melbourne , Australia.,h National Drug Research Institute , Curtin University , Perth , Australia
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Mastall M, Majd N, Fuller G, Gule-Monroe M, Huse J, Khatua S, Rao G, Sandberg D, Wefel J, Yeboa D, Zaky W, Mahajan A, Puduvalli V, Suki D, Alfaro K, Weathers S, Harrison R, de Groot J, Penas-Prado M. P05.93 Adult medulloblastoma: analysis of use of chemotherapy in clinical practice. Neuro Oncol 2018. [DOI: 10.1093/neuonc/noy139.419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- M Mastall
- University of Heidelberg, Heidelberg, Germany
| | - N Majd
- MD Anderson Cancer Center, Houston, TX, United States
| | - G Fuller
- MD Anderson Cancer Center, Houston, TX, United States
| | - M Gule-Monroe
- MD Anderson Cancer Center, Houston, TX, United States
| | - J Huse
- MD Anderson Cancer Center, Houston, TX, United States
| | - S Khatua
- MD Anderson Cancer Center, Houston, TX, United States
| | - G Rao
- MD Anderson Cancer Center, Houston, TX, United States
| | - D Sandberg
- MD Anderson Cancer Center, Houston, TX, United States
| | - J Wefel
- MD Anderson Cancer Center, Houston, TX, United States
| | - D Yeboa
- MD Anderson Cancer Center, Houston, TX, United States
| | - W Zaky
- MD Anderson Cancer Center, Houston, TX, United States
| | - A Mahajan
- Mayo Clinic, Rochester, MN, United States
| | - V Puduvalli
- Ohio State University, Columbus, OH, United States
| | - D Suki
- MD Anderson Cancer Center, Houston, TX, United States
| | - K Alfaro
- MD Anderson Cancer Center, Houston, TX, United States
| | - S Weathers
- MD Anderson Cancer Center, Houston, TX, United States
| | - R Harrison
- MD Anderson Cancer Center, Houston, TX, United States
| | - J de Groot
- MD Anderson Cancer Center, Houston, TX, United States
| | - M Penas-Prado
- MD Anderson Cancer Center, Houston, TX, United States
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Abstract
Herein, the first diazomethane-mediated synthesis of azetidine-embedded tetracyclic ketal systems is reported. Reactions of norbornyl hemiaminal acetals with diazomethane afford azetidine-embedded tetracyclic ketals in good to excellent yields. The bridgehead-bromo-substituted hemiaminal acetals give higher yields compared to the corresponding bridgehead-chloro-substituted hemiaminal acetals. The hemiaminal acetals are prepared stereoselectively via nucleophilic addition of various amines to norbornyl α-diketones from the exo face.
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Affiliation(s)
- G. Rao
- Department of Chemistry, Indian Institute of Technology Kanpur
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37
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Hamdan A, Saxena A, Rao G, Ivanov M. Compression of a giant pseudomeningocele causing transient anoxic seizures-a case report. Acta Neurochir (Wien) 2018; 160:479-485. [PMID: 29299677 DOI: 10.1007/s00701-017-3446-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Accepted: 12/21/2017] [Indexed: 11/28/2022]
Abstract
Transient anoxic seizure upon application of pressure on a giant pseudomeningocele has never been reported in the literature; such abrupt changes in intracranial pressure due to large volume of cerebrospinal fluid (CSF) translocation, if left untreated may lead to permanent cerebral hypoxic injury and death. Here we describe a case of a 26-year-old woman who had undergone lumbar disc surgery in another unit few months ago and developed a large lump around her back. Any pressure on the lump resulted in headaches and at times episodes of seizures. Clinical examination revealed a very large fluid-filled lump consistent with a giant pseudomeningocele, confirmed by an MRI. A video EEG while applying pressure on the lump was recorded. The patient developed a typical seizure attack with a characteristic pattern of cerebral anoxia, and a paired ECG showed irregular rhythm with junctional and ventricular ectopic beats during the latter part of the attack, raising a suspicion of asystole. Upon relieving the pressure off the lump, the patient gradually regained consciousness with no permanent neurological deficit. We then discuss the pathophysiology of anoxic seizures and highlight the need to be vigilant in managing patients with such lesions in order to prevent permanent cerebral hypoxic injury and death.
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Affiliation(s)
- Alhafidz Hamdan
- Department of Spinal Surgery, Northern General Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.
| | - A Saxena
- Department of Neurosurgery, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - G Rao
- Department of Neurosurgery, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - M Ivanov
- Department of Spinal Surgery, Northern General Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
- Department of Neurosurgery, Royal Hallamshire Hospital, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
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38
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Bashour SI, Ibrahim NK, Schomer DF, Colen RR, Sawaya R, Suki D, Rao G, Murthy RK, Moulder SL, Abugabal Y, Hess KR, Fuller GN. Abstract P6-03-04: Central nervous system miliary metastasis in breast cancer patients. Cancer Res 2018. [DOI: 10.1158/1538-7445.sabcs17-p6-03-04] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: Little is known regarding central nervous system (CNS) miliary metastasis (MiM), which was first described as “carcinomatous encephalitis” by Madow and Alpers in 1951. The majority of reported cases arise from primary lung and gastrointestinal adenocarcinomas, with occasional melanoma primaries and one reported case in breast cancer. Moreover, clinicopathologic correlates, disease outcomes and prognostic factors in these patients are poorly understood. Although identified most frequently on neuroimaging, radiographic criteria to objectively diagnose MiM do not exist. In this analysis of patients with brain metastasis from primary breast cancer, we propose objective, stringent radiographic criteria for CNS MiM diagnosis and identify clinicopathologic factors contributing to disease outcomes.
Methods: Using a prospectively maintained electronic database, 1,002 female patients diagnosed with brain metastasis from primary breast cancer between 2000 and 2015 were identified. Only patients with neuroimaging available for direct review (CT or MRI) were included. Our radiographic criteria for MiM diagnosis were: 1) ≥20 metastatic lesions per image slice on ≥2 noncontiguous image slices by MRI, or 2) ≥10 lesions per image slice on ≥2 noncontiguous image slices by CT, and 3) MiM lesions were required to be present bilaterally and in both the supra- and infratentorial compartments. These criteria were established upon direct review of all neuroimaging by a neuroradiologist. Number and anatomic distribution of metastatic lesions were the patterns best observed to identify cases of CNS MiM on case review; lesion size was not a reliable pattern for MiM identification. Log rank tests were used for statistical analyses.
Results: Using stringent criteria, 486 patients were included in this analysis. Twenty patients with MiM were identified (4.1%). Ten patients were diagnosed with MiM at initial brain metastasis presentation; 10 developed MiM after known brain metastasis. Biomarker based subtype distribution was as follows: HR-/HER2- (TNBC) (n=8), HR+/HER2+ (n=3), HR+/HER2- (n=4), HR-/HER2+ (n=4), unknown (n=1).
Table 1: Disease Outcomes Based on Biomarker SubtypeBiomarker SubtypeMedian Time to MiM (months) (p=0.104)Median Survival after MiM (months) (p=0.008)TNBC (n=8)32.3 (12.1-132.5)1.8 (0.5-4.0)HR+/HER2+ (n=3)44.2 (33.2-71.5)10.8 (10.2-13.3)HR+/HER2- (n=4)110.2 (23.0-156.0)4.8 (0.8-9.8)HR-/HER2+ (n=4)27.1 (3.7-39.4)4.0 (1.8-5.0)All* (n=20)37.4 (3.7-156.0)3.7 (0.4-12.3)Key: BM: Brain metastasis; * Includes 1 patient with unknown subtype.
Conclusions: Reports of MiM consist overwhelmingly of lung and gastrointestinal adenocarcinoma primaries. This retrospective, observational study is the first to establish that CNS MiM occurs in breast cancer with an incidence of roughly 4%. Review of an additional 1,600 patient charts is underway, but this preliminary study is the first to identify clinicopathologic correlates and determine disease outcomes in patients with MiM; it is also the first to propose stringent radiographic criteria for the diagnosis of CNS MiM, and further updated data will be presented at the meeting.
Citation Format: Bashour SI, Ibrahim NK, Schomer DF, Colen RR, Sawaya R, Suki D, Rao G, Murthy RK, Moulder SL, Abugabal Y, Hess KR, Fuller GN. Central nervous system miliary metastasis in breast cancer patients [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P6-03-04.
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Affiliation(s)
- SI Bashour
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - NK Ibrahim
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - DF Schomer
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - RR Colen
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - R Sawaya
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - D Suki
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - G Rao
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - RK Murthy
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - SL Moulder
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Y Abugabal
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - KR Hess
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | - GN Fuller
- The University of Texas MD Anderson Cancer Center, Houston, TX
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Jenkins T, Alix J, Rao G, Hoggard N, O'Brien E, Baster K, Bradburn M, Bigley J, McDermott C, Wilkinson I, Shaw P. Imaging denervation in motor neuron disease for future clinical trials: a longitudinal cohort study. J Neurol Sci 2017. [DOI: 10.1016/j.jns.2017.08.328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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40
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Guerrero PA, Tchaicha JH, Chen Z, Morales JE, McCarty N, Wang Q, Sulman EP, Fuller G, Lang FF, Rao G, McCarty JH. Glioblastoma stem cells exploit the αvβ8 integrin-TGFβ1 signaling axis to drive tumor initiation and progression. Oncogene 2017; 36:6568-6580. [PMID: 28783169 DOI: 10.1038/onc.2017.248] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Revised: 06/16/2017] [Accepted: 06/19/2017] [Indexed: 12/13/2022]
Abstract
Glioblastoma (GBM) is a primary brain cancer that contains populations of stem-like cancer cells (GSCs) that home to specialized perivascular niches. GSC interactions with their niche influence self-renewal, differentiation and drug resistance, although the pathways underlying these events remain largely unknown. Here, we report that the integrin αvβ8 and its latent transforming growth factor β1 (TGFβ1) protein ligand have central roles in promoting niche co-option and GBM initiation. αvβ8 integrin is highly expressed in GSCs and is essential for self-renewal and lineage commitment in vitro. Fractionation of β8high cells from freshly resected human GBM samples also reveals a requirement for this integrin in tumorigenesis in vivo. Whole-transcriptome sequencing reveals that αvβ8 integrin regulates tumor development, in part, by driving TGFβ1-induced DNA replication and mitotic checkpoint progression. Collectively, these data identify the αvβ8 integrin-TGFβ1 signaling axis as crucial for exploitation of the perivascular niche and identify potential therapeutic targets for inhibiting tumor growth and progression in patients with GBM.
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Affiliation(s)
- P A Guerrero
- Department of Neurosurgery, M. D. Anderson Cancer Center, Houston, TX, USA
| | - J H Tchaicha
- Department of Neurosurgery, M. D. Anderson Cancer Center, Houston, TX, USA
| | - Z Chen
- Department of Neurosurgery, M. D. Anderson Cancer Center, Houston, TX, USA
| | - J E Morales
- Department of Neurosurgery, M. D. Anderson Cancer Center, Houston, TX, USA
| | - N McCarty
- The Brown Institute for Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Q Wang
- Department of Radiation Oncology, M. D. Anderson Cancer Center, Houston, TX, USA.,Department of Genomic Medicine, M. D. Anderson Cancer Center, Houston, TX, USA
| | - E P Sulman
- Department of Radiation Oncology, M. D. Anderson Cancer Center, Houston, TX, USA.,Department of Genomic Medicine, M. D. Anderson Cancer Center, Houston, TX, USA.,Department of Translational Molecular Pathology, M. D. Anderson Cancer Center, Houston, TX, USA
| | - G Fuller
- Departments of Pathology, M. D. Anderson Cancer Center, Houston, TX, USA
| | - F F Lang
- Department of Neurosurgery, M. D. Anderson Cancer Center, Houston, TX, USA
| | - G Rao
- Department of Neurosurgery, M. D. Anderson Cancer Center, Houston, TX, USA
| | - J H McCarty
- Department of Neurosurgery, M. D. Anderson Cancer Center, Houston, TX, USA
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Madankan R, Stefan W, Fahrenholtz SJ, MacLellan CJ, Hazle JD, Stafford RJ, Weinberg JS, Rao G, Fuentes D. Accelerated magnetic resonance thermometry in the presence of uncertainties. Phys Med Biol 2017; 62:214-245. [PMID: 27991449 DOI: 10.1088/1361-6560/62/1/214] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
A model-based information theoretic approach is presented to perform the task of magnetic resonance (MR) thermal image reconstruction from a limited number of observed samples on k-space. The key idea of the proposed approach is to optimally detect samples of k-space that are information-rich with respect to a model of the thermal data acquisition. These highly informative k-space samples can then be used to refine the mathematical model and efficiently reconstruct the image. The information theoretic reconstruction was demonstrated retrospectively in data acquired during MR-guided laser induced thermal therapy (MRgLITT) procedures. The approach demonstrates that locations with high-information content with respect to a model-based reconstruction of MR thermometry may be quantitatively identified. These information-rich k-space locations are demonstrated to be useful as a guide for k-space undersampling techniques. The effect of interactively increasing the predicted number of data points used in the subsampled model-based reconstruction was quantified using the L2-norm of the distance between the subsampled and fully sampled reconstruction. Performance of the proposed approach was also compared with uniform rectilinear subsampling and variable-density Poisson disk subsampling techniques. The proposed subsampling scheme resulted in accurate reconstructions using a small fraction of k-space points, suggesting that the reconstruction technique may be useful in improving the efficiency of thermometry data temporal resolution.
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Affiliation(s)
- R Madankan
- Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Elwell M, Mahler J, Rao G. Invited Commentary. Toxicol Pathol 2016. [DOI: 10.1177/019262339802600521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Mohindra P, Bentzen S, Giacomelli I, Scartoni D, Roque D, Rao G, Hanna N, Nichols E. Adjuvant Whole-Pelvic Radiation Therapy (WPRT) for Endometrioid Adenocarcinoma (EA): 45 Gy or 50/50.4 Gy? Int J Radiat Oncol Biol Phys 2016. [DOI: 10.1016/j.ijrobp.2016.06.1378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Mohindra P, Bentzen S, Scartoni D, Giacomelli I, Rao G, Roque D, Hanna N, Nichols E. Adjuvant Therapy for Locoregionally Advanced Endometrioid Adenocarcinoma (EA): Upfront Chemotherapy (UC) or Upfront Radiation Therapy (UR)? Int J Radiat Oncol Biol Phys 2016. [DOI: 10.1016/j.ijrobp.2016.06.1353] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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45
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MacLellan C, Fuentes D, Espinoza H, Prabhu S, Rao G, Weinberg J, Stafford R. WE-AB-BRA-04: Investigation of MRI Derived Thermal Dose Models. Med Phys 2016. [DOI: 10.1118/1.4957733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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46
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Madankan R, MacLellan C, Fahrenholtz S, Weinberg J, Rao G, Hazle J, Stafford R, Fuentes D. SU-F-J-03: Treatment Planning for Laser Ablation Therapy in Presence of Heterogeneous Tissue: A Retrospective Study. Med Phys 2016. [DOI: 10.1118/1.4955911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
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Kaur K, Fayad R, Saxena A, Frizzell N, Chanda A, Das S, Chatterjee S, Hegde S, Baliga M, Ponemone V, Rorro M, Greene J, Elraheb Y, Redd A, Bian J, Restaino J, Norris L, Qureshi Z, Love B, Bookstaver B, Georgantopoulos P, Sartor O, Raisch D, Rao G, Lu K, Ray P, Hrusheshky W, Schulz R, Ablin R, Noxon V, Bennett C. Fluoroquinolone-related neuropsychiatric and mitochondrial toxicity: a collaborative investigation by scientists and members of a social network. J Community Support Oncol 2016; 14:54-65. [DOI: 10.12788/jcso.0167] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/31/2015] [Indexed: 11/20/2022]
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Lee J, Jain R, Khalil K, Griffith B, Bosca R, Rao G, Rao A. Texture Feature Ratios from Relative CBV Maps of Perfusion MRI Are Associated with Patient Survival in Glioblastoma. AJNR Am J Neuroradiol 2015; 37:37-43. [PMID: 26471746 DOI: 10.3174/ajnr.a4534] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 05/26/2015] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Texture analysis has been applied to medical images to assist in tumor tissue classification and characterization. In this study, we obtained textural features from parametric (relative CBV) maps of dynamic susceptibility contrast-enhanced MR images in glioblastoma and assessed their relationship with patient survival. MATERIALS AND METHODS MR perfusion data of 24 patients with glioblastoma from The Cancer Genome Atlas were analyzed in this study. One- and 2D texture feature ratios and kinetic textural features based on relative CBV values in the contrast-enhancing and nonenhancing lesions of the tumor were obtained. Receiver operating characteristic, Kaplan-Meier, and multivariate Cox proportional hazards regression analyses were used to assess the relationship between texture feature ratios and overall survival. RESULTS Several feature ratios are capable of stratifying survival in a statistically significant manner. These feature ratios correspond to homogeneity (P = .008, based on the log-rank test), angular second moment (P = .003), inverse difference moment (P = .013), and entropy (P = .008). Multivariate Cox proportional hazards regression analysis showed that homogeneity, angular second moment, inverse difference moment, and entropy from the contrast-enhancing lesion were significantly associated with overall survival. For the nonenhancing lesion, skewness and variance ratios of relative CBV texture were associated with overall survival in a statistically significant manner. For the kinetic texture analysis, the Haralick correlation feature showed a P value close to .05. CONCLUSIONS Our study revealed that texture feature ratios from contrast-enhancing and nonenhancing lesions and kinetic texture analysis obtained from perfusion parametric maps provide useful information for predicting survival in patients with glioblastoma.
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Affiliation(s)
- J Lee
- From the Departments of Bioinformatics and Computational Biology (J.L., A.R.)
| | - R Jain
- Department of Radiology (R.J.), New York University School of Medicine, Langone Medical Center, New York, New York
| | - K Khalil
- Department of Radiology (K.K., B.G.), Henry Ford Hospital, Detroit, Michigan
| | - B Griffith
- Department of Radiology (K.K., B.G.), Henry Ford Hospital, Detroit, Michigan
| | - R Bosca
- Department of Medical Physics (R.B.), University of Wisconsin, Madison, Wisconsin
| | - G Rao
- Neurosurgery (G.R.), The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - A Rao
- From the Departments of Bioinformatics and Computational Biology (J.L., A.R.)
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Chatterjee M, Ge X, Kostov Y, Luu P, Tolosa L, Woo H, Viscardi R, Falk S, Potts R, Rao G. A rate-based transcutaneous CO2 sensor for noninvasive respiration monitoring. Physiol Meas 2015; 36:883-94. [PMID: 25832294 PMCID: PMC4417034 DOI: 10.1088/0967-3334/36/5/883] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The pain and risk of infection associated with invasive blood sampling for blood gas measurements necessitate the search for reliable noninvasive techniques. In this work we developed a novel rate-based noninvasive method for a safe and fast assessment of respiratory status. A small sampler was built to collect the gases diffusing out of the skin. It was connected to a CO2 sensor through gas-impermeable tubing. During a measurement, the CO2 initially present in the sampler was first removed by purging it with nitrogen. The gases in the system were then recirculated between the sampler and the CO2 sensor, and the CO2 diffusion rate into the sampler was measured. Because the measurement is based on the initial transcutaneous diffusion rate, reaching mass transfer equilibrium and heating the skin is no longer required, thus, making it much faster and safer than traditional method. A series of designed experiments were performed to analyze the effect of the measurement parameters such as sampler size, measurement location, subject positions, and movement. After the factor analysis tests, the prototype was sent to a level IV NICU for clinical trial. The results show that the measured initial rate of increase in CO2 partial pressure is linearly correlated with the corresponding arterial blood gas measurements. The new approach can be used as a trending tool, making frequent blood sampling unnecessary for respiratory status monitoring.
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Affiliation(s)
- M Chatterjee
- Center for Advanced Sensor Technology, Department of Chemical, Biochemical and Environmental Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, Maryland 21250, United States
| | - X Ge
- Center for Advanced Sensor Technology, Department of Chemical, Biochemical and Environmental Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, Maryland 21250, United States
| | - Y Kostov
- Center for Advanced Sensor Technology, Department of Chemical, Biochemical and Environmental Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, Maryland 21250, United States
| | - P Luu
- Center for Advanced Sensor Technology, Department of Chemical, Biochemical and Environmental Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, Maryland 21250, United States
| | - L Tolosa
- Center for Advanced Sensor Technology, Department of Chemical, Biochemical and Environmental Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, Maryland 21250, United States
| | - H Woo
- Department of Pediatrics, University of Maryland School of Medicine, 685 W Baltimore St., Baltimore, MD 21201, United States
| | - R Viscardi
- Department of Pediatrics, University of Maryland School of Medicine, 685 W Baltimore St., Baltimore, MD 21201, United States
| | - S Falk
- GE Healthcare, 8880 Gorman Rd Laurel, MD 20723, United States
| | - R Potts
- Fluorometrix Biomedical, 517 Court Pl, Pittsburgh, PA 15210, United States
| | - G Rao
- Center for Advanced Sensor Technology, Department of Chemical, Biochemical and Environmental Engineering, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, Maryland 21250, United States
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50
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Jung B, Gleeton D, Daurat A, Conseil M, Mahul M, Rao G, Matecki S, Lacampagne A, Jaber S. Conséquences de la ventilation mécanique sur le diaphragme. Rev Mal Respir 2015; 32:370-80. [DOI: 10.1016/j.rmr.2014.08.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2014] [Accepted: 08/25/2014] [Indexed: 01/23/2023]
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