Literature DB >> 20171511

Improving normal tissue complication probability models: the need to adopt a "data-pooling" culture.

Joseph O Deasy1, Søren M Bentzen, Andrew Jackson, Randall K Ten Haken, Ellen D Yorke, Louis S Constine, Ashish Sharma, Lawrence B Marks.   

Abstract

Clinical studies of the dependence of normal tissue response on dose-volume factors are often confusingly inconsistent, as the QUANTEC reviews demonstrate. A key opportunity to accelerate progress is to begin storing high-quality datasets in repositories. Using available technology, multiple repositories could be conveniently queried, without divulging protected health information, to identify relevant sources of data for further analysis. After obtaining institutional approvals, data could then be pooled, greatly enhancing the capability to construct predictive models that are more widely applicable and better powered to accurately identify key predictive factors (whether dosimetric, image-based, clinical, socioeconomic, or biological). Data pooling has already been carried out effectively in a few normal tissue complication probability studies and should become a common strategy. Copyright 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20171511      PMCID: PMC2854162          DOI: 10.1016/j.ijrobp.2009.06.094

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  12 in total

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3.  The impact of dose on parotid salivary recovery in head and neck cancer patients treated with radiation therapy.

Authors:  Yun Li; Jeremy M G Taylor; Randall K Ten Haken; Avraham Eisbruch
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Review 5.  Mapping the human brain: new insights from FMRI data sharing.

Authors:  John Darrell Van Horn; Alumit Ishai
Journal:  Neuroinformatics       Date:  2007

6.  Epidemiology, data sharing, and the challenge of scientific replication.

Authors:  Miguel A Hernán; Allen J Wilcox
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7.  Envisioning a biomedical data reuse registry.

Authors:  Heather A Piwowar; Wendy W Chapman
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8.  e-Science, caGrid, and Translational Biomedical Research.

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Journal:  Computer (Long Beach Calif)       Date:  2008-11       Impact factor: 2.683

9.  Radiation pneumonitis as a function of mean lung dose: an analysis of pooled data of 540 patients.

Authors:  S L Kwa; J V Lebesque; J C Theuws; L B Marks; M T Munley; G Bentel; D Oetzel; U Spahn; M V Graham; R E Drzymala; J A Purdy; A S Lichter; M K Martel; R K Ten Haken
Journal:  Int J Radiat Oncol Biol Phys       Date:  1998-08-01       Impact factor: 7.038

10.  A nomogram to predict radiation pneumonitis, derived from a combined analysis of RTOG 9311 and institutional data.

Authors:  Jeffrey D Bradley; Andrew Hope; Issam El Naqa; Aditya Apte; Patricia E Lindsay; Walter Bosch; John Matthews; William Sause; Mary V Graham; Joseph O Deasy
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-08-06       Impact factor: 7.038

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  33 in total

1.  Demonstration of a software design and statistical analysis methodology with application to patient outcomes data sets.

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Journal:  Med Phys       Date:  2013-11       Impact factor: 4.071

2.  Central Airway Toxicity After High Dose Radiation: A Combined Analysis of Prospective Clinical Trials for Non-Small Cell Lung Cancer.

Authors:  Weili Wang; Martha M Matuszak; Chen Hu; Ke Colin Huang; Eileen Chen; Douglas Arenberg; Jeffrey L Curtis; Shruti Jolly; Jian-Yue Jin; Mitchell Machtay; Randall K Ten Haken; Feng-Ming Spring Kong
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3.  Dosimetric predictors of esophageal toxicity after stereotactic body radiotherapy for central lung tumors.

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Review 5.  Predicting outcomes in radiation oncology--multifactorial decision support systems.

Authors:  Philippe Lambin; Ruud G P M van Stiphout; Maud H W Starmans; Emmanuel Rios-Velazquez; Georgi Nalbantov; Hugo J W L Aerts; Erik Roelofs; Wouter van Elmpt; Paul C Boutros; Pierluigi Granone; Vincenzo Valentini; Adrian C Begg; Dirk De Ruysscher; Andre Dekker
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Review 6.  Radiomics: the bridge between medical imaging and personalized medicine.

Authors:  Philippe Lambin; Ralph T H Leijenaar; Timo M Deist; Jurgen Peerlings; Evelyn E C de Jong; Janita van Timmeren; Sebastian Sanduleanu; Ruben T H M Larue; Aniek J G Even; Arthur Jochems; Yvonka van Wijk; Henry Woodruff; Johan van Soest; Tim Lustberg; Erik Roelofs; Wouter van Elmpt; Andre Dekker; Felix M Mottaghy; Joachim E Wildberger; Sean Walsh
Journal:  Nat Rev Clin Oncol       Date:  2017-10-04       Impact factor: 66.675

7.  Dose-volume parameters predict for the development of chest wall pain after stereotactic body radiation for lung cancer.

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8.  Influence of image slice thickness on rectal dose-response relationships following radiotherapy of prostate cancer.

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9.  Impact of Fractionation and Dose in a Multivariate Model for Radiation-Induced Chest Wall Pain.

Authors:  Shaun U Din; Eric L Williams; Andrew Jackson; Kenneth E Rosenzweig; Abraham J Wu; Amanda Foster; Ellen D Yorke; Andreas Rimner
Journal:  Int J Radiat Oncol Biol Phys       Date:  2015-06-14       Impact factor: 7.038

10.  Dose/volume-response relations for rectal morbidity using planned and simulated motion-inclusive dose distributions.

Authors:  Maria Thor; Aditya Apte; Joseph O Deasy; Àsa Karlsdóttir; Vitali Moiseenko; Mitchell Liu; Ludvig Paul Muren
Journal:  Radiother Oncol       Date:  2013-11-11       Impact factor: 6.280

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