Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example
Events
Loading … Spinner

Mendeley | Further Information

{"title"=>"Improving the prognostic ability through better use of standard clinical data - the nottingham prognostic index as an example", "type"=>"journal", "authors"=>[{"first_name"=>"Klaus Jörgen", "last_name"=>"Winzer", "scopus_author_id"=>"7005071272"}, {"first_name"=>"Anika", "last_name"=>"Buchholz", "scopus_author_id"=>"23395789300"}, {"first_name"=>"Martin", "last_name"=>"Schumacher", "scopus_author_id"=>"55520163700"}, {"first_name"=>"Willi", "last_name"=>"Sauerbrei", "scopus_author_id"=>"7006492726"}], "year"=>2016, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "sgr"=>"84961184352", "scopus"=>"2-s2.0-84961184352", "pui"=>"609003256", "doi"=>"10.1371/journal.pone.0149977", "pmid"=>"26938061"}, "id"=>"ed98efeb-34f3-3a39-b304-c10cf032c7c8", "abstract"=>"BACKGROUND Prognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI) is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches. METHODS AND FINDINGS Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index. Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived. CONCLUSIONS The prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other diseases.", "link"=>"http://www.mendeley.com/research/improving-prognostic-ability-through-better-standard-clinical-data-nottingham-prognostic-index-examp", "reader_count"=>14, "reader_count_by_academic_status"=>{"Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>2, "Student > Postgraduate"=>1, "Other"=>1, "Student > Master"=>2}, "reader_count_by_user_role"=>{"Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>2, "Student > Postgraduate"=>1, "Other"=>1, "Student > Master"=>2}, "reader_count_by_subject_area"=>{"Mathematics"=>1, "Medicine and Dentistry"=>8, "Neuroscience"=>1, "Social Sciences"=>1, "Economics, Econometrics and Finance"=>2, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>8}, "Neuroscience"=>{"Neuroscience"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>2}, "Computer Science"=>{"Computer Science"=>1}, "Mathematics"=>{"Mathematics"=>1}}, "reader_count_by_country"=>{"United Kingdom"=>2}, "group_count"=>1}

Scopus | Further Information

{"@_fa"=>"true", "link"=>[{"@_fa"=>"true", "@ref"=>"self", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84961184352"}, {"@_fa"=>"true", "@ref"=>"author-affiliation", "@href"=>"https://api.elsevier.com/content/abstract/scopus_id/84961184352?field=author,affiliation"}, {"@_fa"=>"true", "@ref"=>"scopus", "@href"=>"https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84961184352&origin=inward"}, {"@_fa"=>"true", "@ref"=>"scopus-citedby", "@href"=>"https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84961184352&origin=inward"}], "prism:url"=>"https://api.elsevier.com/content/abstract/scopus_id/84961184352", "dc:identifier"=>"SCOPUS_ID:84961184352", "eid"=>"2-s2.0-84961184352", "dc:title"=>"Improving the prognostic ability through better use of standard clinical data - the nottingham prognostic index as an example", "dc:creator"=>"Winzer K.", "prism:publicationName"=>"PLoS ONE", "prism:eIssn"=>"19326203", "prism:volume"=>"11", "prism:issueIdentifier"=>"3", "prism:pageRange"=>nil, "prism:coverDate"=>"2016-03-01", "prism:coverDisplayDate"=>"March 2016", "prism:doi"=>"10.1371/journal.pone.0149977", "citedby-count"=>"5", "affiliation"=>[{"@_fa"=>"true", "affilname"=>"Charité – Universitätsmedizin Berlin", "affiliation-city"=>"Berlin", "affiliation-country"=>"Germany"}], "pubmed-id"=>"26938061", "prism:aggregationType"=>"Journal", "subtype"=>"ar", "subtypeDescription"=>"Article", "article-number"=>"e0149977", "source-id"=>"10600153309", "openaccess"=>"1", "openaccessFlag"=>true}

Facebook

  • {"url"=>"http%3A%2F%2Fjournals.plos.org%2Fplosone%2Farticle%3Fid%3D10.1371%252Fjournal.pone.0149977", "share_count"=>0, "like_count"=>0, "comment_count"=>0, "click_count"=>0, "total_count"=>0}

Counter

  • {"month"=>"3", "year"=>"2016", "pdf_views"=>"34", "xml_views"=>"0", "html_views"=>"414"}
  • {"month"=>"4", "year"=>"2016", "pdf_views"=>"20", "xml_views"=>"1", "html_views"=>"46"}
  • {"month"=>"5", "year"=>"2016", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"30"}
  • {"month"=>"6", "year"=>"2016", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"50"}
  • {"month"=>"7", "year"=>"2016", "pdf_views"=>"12", "xml_views"=>"0", "html_views"=>"42"}
  • {"month"=>"8", "year"=>"2016", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"24"}
  • {"month"=>"9", "year"=>"2016", "pdf_views"=>"8", "xml_views"=>"0", "html_views"=>"26"}
  • {"month"=>"10", "year"=>"2016", "pdf_views"=>"11", "xml_views"=>"0", "html_views"=>"56"}
  • {"month"=>"11", "year"=>"2016", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"46"}
  • {"month"=>"12", "year"=>"2016", "pdf_views"=>"5", "xml_views"=>"1", "html_views"=>"36"}
  • {"month"=>"1", "year"=>"2017", "pdf_views"=>"10", "xml_views"=>"1", "html_views"=>"23"}
  • {"month"=>"2", "year"=>"2017", "pdf_views"=>"19", "xml_views"=>"1", "html_views"=>"38"}
  • {"month"=>"3", "year"=>"2017", "pdf_views"=>"5", "xml_views"=>"2", "html_views"=>"45"}
  • {"month"=>"4", "year"=>"2017", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"45"}
  • {"month"=>"5", "year"=>"2017", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"39"}
  • {"month"=>"6", "year"=>"2017", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"23"}
  • {"month"=>"7", "year"=>"2017", "pdf_views"=>"16", "xml_views"=>"2", "html_views"=>"15"}
  • {"month"=>"8", "year"=>"2017", "pdf_views"=>"9", "xml_views"=>"1", "html_views"=>"25"}
  • {"month"=>"9", "year"=>"2017", "pdf_views"=>"1", "xml_views"=>"2", "html_views"=>"13"}
  • {"month"=>"10", "year"=>"2017", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"37"}
  • {"month"=>"11", "year"=>"2017", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"118"}
  • {"month"=>"12", "year"=>"2017", "pdf_views"=>"4", "xml_views"=>"2", "html_views"=>"232"}
  • {"month"=>"1", "year"=>"2018", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"25"}
  • {"month"=>"2", "year"=>"2018", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"6"}
  • {"month"=>"3", "year"=>"2018", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"4"}
  • {"month"=>"4", "year"=>"2018", "pdf_views"=>"1", "xml_views"=>"1", "html_views"=>"13"}
  • {"month"=>"5", "year"=>"2018", "pdf_views"=>"1", "xml_views"=>"1", "html_views"=>"6"}
  • {"month"=>"6", "year"=>"2018", "pdf_views"=>"3", "xml_views"=>"1", "html_views"=>"6"}
  • {"month"=>"7", "year"=>"2018", "pdf_views"=>"4", "xml_views"=>"5", "html_views"=>"12"}
  • {"month"=>"8", "year"=>"2018", "pdf_views"=>"8", "xml_views"=>"1", "html_views"=>"10"}
  • {"month"=>"9", "year"=>"2018", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"10"}
  • {"month"=>"10", "year"=>"2018", "pdf_views"=>"5", "xml_views"=>"4", "html_views"=>"13"}
  • {"month"=>"11", "year"=>"2018", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"9"}
  • {"month"=>"12", "year"=>"2018", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"13"}
  • {"month"=>"1", "year"=>"2019", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"6"}
  • {"month"=>"2", "year"=>"2019", "pdf_views"=>"2", "xml_views"=>"0", "html_views"=>"10"}
  • {"month"=>"3", "year"=>"2019", "pdf_views"=>"6", "xml_views"=>"0", "html_views"=>"13"}
  • {"month"=>"4", "year"=>"2019", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"10"}
  • {"month"=>"5", "year"=>"2019", "pdf_views"=>"7", "xml_views"=>"0", "html_views"=>"19"}
  • {"month"=>"6", "year"=>"2019", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"8"}
  • {"month"=>"7", "year"=>"2019", "pdf_views"=>"5", "xml_views"=>"0", "html_views"=>"8"}
  • {"month"=>"8", "year"=>"2019", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"10"}
  • {"month"=>"9", "year"=>"2019", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"9"}
  • {"month"=>"10", "year"=>"2019", "pdf_views"=>"4", "xml_views"=>"0", "html_views"=>"18"}
  • {"month"=>"11", "year"=>"2019", "pdf_views"=>"10", "xml_views"=>"0", "html_views"=>"21"}
  • {"month"=>"12", "year"=>"2019", "pdf_views"=>"3", "xml_views"=>"0", "html_views"=>"8"}
  • {"month"=>"1", "year"=>"2020", "pdf_views"=>"13", "xml_views"=>"0", "html_views"=>"10"}
  • {"month"=>"2", "year"=>"2020", "pdf_views"=>"13", "xml_views"=>"1", "html_views"=>"11"}

Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/4810795"], "description"=>"<p>Estimated effects of NPI components.</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095872, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.t004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Estimated_effects_of_NPI_components_/3095872", "title"=>"Estimated effects of NPI components.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810768"], "description"=>"<p>Predictor for univariable analysis of no. of positive lymph nodes derived by two Cox models assuming a linear effect (dashed line) or the significant improvement from the class of FP models (solid line).</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095845, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.g003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Functional_form_for_no_of_positive_nodes_for_two_models_/3095845", "title"=>"Functional form for no. of positive nodes for two models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810801"], "description"=>"<p>Estimated effects of additional variables.</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095878, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.t005", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Estimated_effects_of_additional_variables_/3095878", "title"=>"Estimated effects of additional variables.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810738"], "description"=>"<p>Top NPI(3)– 3 groups, below NPI(6)– 6 groups.</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095815, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.g001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Kaplan_Meier_estimates_of_survival_probabilities_for_prognostic_groups_defined_by_the_Nottingham_Prognostic_Index_/3095815", "title"=>"Kaplan-Meier estimates of survival probabilities for prognostic groups defined by the Nottingham Prognostic Index.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810771"], "description"=>"<p>NPI groups are defined as 1: NPI<3.4; 2: 3.4≤NPI≤5.4; 3: NPI>5.4.</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095848, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.g004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Kaplan_Meier_curve_for_combinations_of_NPI_3_and_hormone_receptor_/3095848", "title"=>"Kaplan-Meier curve for combinations of NPI(3) and hormone receptor.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810804"], "description"=>"<p>MFP model.</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095881, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.t006", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/MFP_model_/3095881", "title"=>"MFP model.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810807"], "description"=>"<p>Summary of ‘major’ models and corresponding measures of separation.</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095884, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.t007", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Summary_of_major_models_and_corresponding_measures_of_separation_/3095884", "title"=>"Summary of ‘major’ models and corresponding measures of separation.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810675", "https://ndownloader.figshare.com/files/4810687", "https://ndownloader.figshare.com/files/4810699", "https://ndownloader.figshare.com/files/4810714", "https://ndownloader.figshare.com/files/4810726", "https://ndownloader.figshare.com/files/4810729"], "description"=>"<div><p>Background</p><p>Prognostic factors and prognostic models play a key role in medical research and patient management. The Nottingham Prognostic Index (NPI) is a well-established prognostic classification scheme for patients with breast cancer. In a very simple way, it combines the information from tumor size, lymph node stage and tumor grade. For the resulting index cutpoints are proposed to classify it into three to six groups with different prognosis. As not all prognostic information from the three and other standard factors is used, we will consider improvement of the prognostic ability using suitable analysis approaches.</p><p>Methods and Findings</p><p>Reanalyzing overall survival data of 1560 patients from a clinical database by using multivariable fractional polynomials and further modern statistical methods we illustrate suitable multivariable modelling and methods to derive and assess the prognostic ability of an index. Using a REMARK type profile we summarize relevant steps of the analysis. Adding the information from hormonal receptor status and using the full information from the three NPI components, specifically concerning the number of positive lymph nodes, an extended NPI with improved prognostic ability is derived.</p><p>Conclusions</p><p>The prognostic ability of even one of the best established prognostic index in medicine can be improved by using suitable statistical methodology to extract the full information from standard clinical data. This extended version of the NPI can serve as a benchmark to assess the added value of new information, ranging from a new single clinical marker to a derived index from omics data. An established benchmark would also help to harmonize the statistical analyses of such studies and protect against the propagation of many false promises concerning the prognostic value of new measurements. Statistical methods used are generally available and can be used for similar analyses in other diseases.</p></div>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095791, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0149977.s001", "https://dx.doi.org/10.1371/journal.pone.0149977.s002", "https://dx.doi.org/10.1371/journal.pone.0149977.s003", "https://dx.doi.org/10.1371/journal.pone.0149977.s004", "https://dx.doi.org/10.1371/journal.pone.0149977.s005", "https://dx.doi.org/10.1371/journal.pone.0149977.s006"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Improving_the_Prognostic_Ability_through_Better_Use_of_Standard_Clinical_Data_The_Nottingham_Prognostic_Index_as_an_Example/3095791", "title"=>"Improving the Prognostic Ability through Better Use of Standard Clinical Data - The Nottingham Prognostic Index as an Example", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810780"], "description"=>"<p>REMARK type profile.</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095857, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.t001", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/REMARK_type_profile_/3095857", "title"=>"REMARK type profile.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810783"], "description"=>"<p>Survival rates after 5, 10 and 15 years for the categories from NPI(3).</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095860, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.t002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Survival_rates_after_5_10_and_15_years_for_the_categories_from_NPI_3_/3095860", "title"=>"Survival rates after 5, 10 and 15 years for the categories from NPI(3).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810756"], "description"=>"<p>Log-log plot to check the proportional hazards assumption of the Cox-model for three prognostic groups according to NPI(3).</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095833, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.g002", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Log_log_plot_for_NPI_3_/3095833", "title"=>"Log-log plot for NPI(3).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-03-03 08:01:41"}
  • {"files"=>["https://ndownloader.figshare.com/files/4810789"], "description"=>"<p>Hazard ratios and discriminative ability of NPI.</p>", "links"=>[], "tags"=>["prognostic ability", "NPI", "REMARK type profile", "Nottingham Prognostic Index", "Standard Clinical Data", "Example BackgroundPrognostic factors", "derived.ConclusionsThe prognostic ability", "lymph node stage", "information", "prognostic classification scheme"], "article_id"=>3095866, "categories"=>["Cell Biology", "Biotechnology", "Mathematical Sciences not elsewhere classified", "Cancer", "Hematology"], "users"=>["Klaus-Jürgen Winzer", "Anika Buchholz", "Martin Schumacher", "Willi Sauerbrei"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0149977.t003", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Hazard_ratios_and_discriminative_ability_of_NPI_/3095866", "title"=>"Hazard ratios and discriminative ability of NPI.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-03-03 08:01:41"}

PMC Usage Stats | Further Information

  • {"unique-ip"=>"16", "full-text"=>"16", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2016", "month"=>"3"}
  • {"unique-ip"=>"22", "full-text"=>"21", "pdf"=>"15", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"4"}
  • {"unique-ip"=>"19", "full-text"=>"24", "pdf"=>"7", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2016", "month"=>"5"}
  • {"unique-ip"=>"29", "full-text"=>"26", "pdf"=>"10", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"6", "cited-by"=>"0", "year"=>"2016", "month"=>"6"}
  • {"unique-ip"=>"19", "full-text"=>"23", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"7"}
  • {"unique-ip"=>"18", "full-text"=>"15", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"8"}
  • {"unique-ip"=>"18", "full-text"=>"21", "pdf"=>"11", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"16", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2016", "month"=>"9"}
  • {"unique-ip"=>"15", "full-text"=>"16", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"10", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
  • {"unique-ip"=>"9", "full-text"=>"10", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"11"}
  • {"unique-ip"=>"12", "full-text"=>"10", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
  • {"unique-ip"=>"20", "full-text"=>"12", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"1"}
  • {"unique-ip"=>"13", "full-text"=>"13", "pdf"=>"6", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"2"}
  • {"unique-ip"=>"28", "full-text"=>"26", "pdf"=>"5", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"3"}
  • {"unique-ip"=>"7", "full-text"=>"14", "pdf"=>"3", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"4"}
  • {"unique-ip"=>"10", "full-text"=>"10", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2017", "month"=>"5"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"6"}
  • {"unique-ip"=>"10", "full-text"=>"12", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"9", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"7"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"8"}
  • {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"9"}
  • {"unique-ip"=>"6", "full-text"=>"6", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"3", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"10"}
  • {"unique-ip"=>"25", "full-text"=>"15", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"4", "cited-by"=>"0", "year"=>"2017", "month"=>"11"}
  • {"unique-ip"=>"11", "full-text"=>"11", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2017", "month"=>"12"}
  • {"unique-ip"=>"4", "full-text"=>"5", "pdf"=>"1", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"8", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"1"}
  • {"unique-ip"=>"14", "full-text"=>"8", "pdf"=>"2", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"3"}
  • {"unique-ip"=>"8", "full-text"=>"7", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"1"}
  • {"unique-ip"=>"7", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"5", "cited-by"=>"0", "year"=>"2018", "month"=>"11"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"4"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"5"}
  • {"unique-ip"=>"3", "full-text"=>"3", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"6"}
  • {"unique-ip"=>"7", "full-text"=>"10", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"12"}
  • {"unique-ip"=>"12", "full-text"=>"5", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"4", "supp-data"=>"3", "cited-by"=>"0", "year"=>"2018", "month"=>"7"}
  • {"unique-ip"=>"11", "full-text"=>"9", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"6", "cited-by"=>"0", "year"=>"2018", "month"=>"8"}
  • {"unique-ip"=>"8", "full-text"=>"10", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"1", "cited-by"=>"0", "year"=>"2018", "month"=>"10"}
  • {"unique-ip"=>"5", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2018", "month"=>"9"}
  • {"unique-ip"=>"6", "full-text"=>"7", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"2"}
  • {"unique-ip"=>"5", "full-text"=>"6", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"1", "full-text"=>"1", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"12", "full-text"=>"15", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"12", "full-text"=>"11", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"6", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}
  • {"unique-ip"=>"19", "full-text"=>"24", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"7", "cited-by"=>"1", "year"=>"2019", "month"=>"10"}
  • {"unique-ip"=>"4", "full-text"=>"2", "pdf"=>"3", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"12"}

Relative Metric

{"start_date"=>"2016-01-01T00:00:00Z", "end_date"=>"2016-12-31T00:00:00Z", "subject_areas"=>[]}
Loading … Spinner
There are currently no alerts