A Patient-Centered Methodology That Improves the Accuracy of Prognostic Predictions in Cancer
Publication Date
February 27, 2013
Journal
PLOS ONE
Authors
Mohammed Kashani Sabet, Richard W. Sagebiel, Heikki Joensuu & James R. Miller Iii
Volume
8
Issue
2
Pages
e56435
DOI
https://dx.plos.org/10.1371/journal.pone.0056435
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0056435
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/23460802
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3584071
Europe PMC
http://europepmc.org/abstract/MED/23460802
Web of Science
000315519000025
Scopus
84874536611
Mendeley
http://www.mendeley.com/research/patientcentered-methodology-improves-accuracy-prognostic-predictions-cancer
Events
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Mendeley | Further Information

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Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/972134"], "description"=>"<p>Kaplan-Meier analysis of DSS of high-risk patients identified by traditional eligibility for high-dose IFN only (curve 1), those identified by both criteria (curve 2), and those identified by the tailored prognostic model only (curve 3).</p>", "links"=>[], "tags"=>["dss", "high-risk", "patients", "eligibility", "high-dose", "ifn", "tailored", "prognostic"], "article_id"=>640896, "categories"=>["Cancer", "Developmental Biology", "Biotechnology"], "users"=>["Mohammed Kashani-Sabet", "Richard W. Sagebiel", "Heikki Joensuu", "James R. Miller III"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0056435.g003", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Kaplan_Meier_analysis_of_DSS_of_high_risk_patients_identified_by_traditional_eligibility_for_high_dose_IFN_only_curve_1_those_identified_by_both_criteria_curve_2_and_those_identified_by_the_tailored_prognostic_model_only_curve_3_/640896", "title"=>"Kaplan-Meier analysis of DSS of high-risk patients identified by traditional eligibility for high-dose IFN only (curve 1), those identified by both criteria (curve 2), and those identified by the tailored prognostic model only (curve 3).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-28 09:53:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/972127"], "description"=>"<p>Panel B. Kaplan-Meier analysis of DSS by prognostic subgroup in the breast cancer cohort.</p>", "links"=>[], "tags"=>["kaplan-meier", "dss", "prognostic", "subgroup", "melanoma"], "article_id"=>640890, "categories"=>["Cancer", "Developmental Biology", "Biotechnology"], "users"=>["Mohammed Kashani-Sabet", "Richard W. Sagebiel", "Heikki Joensuu", "James R. Miller III"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0056435.g001", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Panel_A_Kaplan_Meier_analysis_of_DSS_by_prognostic_subgroup_in_the_melanoma_cohort_/640890", "title"=>"Panel A. Kaplan-Meier analysis of DSS by prognostic subgroup in the melanoma cohort.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-28 09:52:29"}
  • {"files"=>["https://ndownloader.figshare.com/files/1005461"], "description"=>"<p>Note: T values and accompanying 2-tail P values refer to reductions in mean absolute probabilistic error achieved relative to the prognostic methodology tabled in the line immediately above, where each matched-pair T test is applied to the indicated 1,222 matched pairs of individual probabilistic prediction errors.</p>", "links"=>[], "tags"=>["predictive", "achieved", "melanoma", "differing", "prognostic", "methodologies"], "article_id"=>666083, "categories"=>["Cancer", "Developmental Biology", "Biotechnology"], "users"=>["Mohammed Kashani-Sabet", "Richard W. Sagebiel", "Heikki Joensuu", "James R. Miller III"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0056435.t001", "stats"=>{"downloads"=>2, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_predictive_accuracy_achieved_in_melanoma_through_differing_prognostic_methodologies_N_8202_8202_1_222_/666083", "title"=>"Comparison of predictive accuracy achieved in melanoma through differing prognostic methodologies (N = 1,222).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-27 01:41:23"}
  • {"files"=>["https://ndownloader.figshare.com/files/972129"], "description"=>"<p>Panel B. ROC plots of 5-year breast cancer-specific death probabilities estimated by different logistic regression analyses. In each panel, curve 1 represents the ROC plot using initial AJCC stage (unstratified), curve 2 the ROC plot stratified by AJCC stage, and curve 3 the ROC plot determined by the composite weighted index.</p>", "links"=>[], "tags"=>["roc", "5-year", "melanoma-specific", "probabilities", "logistic", "regression"], "article_id"=>640892, "categories"=>["Cancer", "Developmental Biology", "Biotechnology"], "users"=>["Mohammed Kashani-Sabet", "Richard W. Sagebiel", "Heikki Joensuu", "James R. Miller III"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0056435.g002", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Panel_A_ROC_plots_of_5_year_melanoma_specific_death_probabilities_estimated_by_different_logistic_regression_analyses_/640892", "title"=>"Panel A. ROC plots of 5-year melanoma-specific death probabilities estimated by different logistic regression analyses.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-28 09:53:01"}
  • {"files"=>["https://ndownloader.figshare.com/files/1005482"], "description"=>"<p>Note: T values and accompanying 2-tail P values refer to reductions in mean absolute probabilistic error achieved relative to the prognostic methodology tabled in the line immediately above, where each matched-pair T test is applied to the indicated 1,225 matched pairs of individual probabilistic prediction errors.</p>", "links"=>[], "tags"=>["predictive", "achieved", "cancer", "differing", "prognostic", "methodologies"], "article_id"=>666103, "categories"=>["Cancer", "Developmental Biology", "Biotechnology"], "users"=>["Mohammed Kashani-Sabet", "Richard W. Sagebiel", "Heikki Joensuu", "James R. Miller III"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0056435.t002", "stats"=>{"downloads"=>0, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_predictive_accuracy_achieved_in_breast_cancer_through_differing_prognostic_methodologies_N_8202_8202_1_225_/666103", "title"=>"Comparison of predictive accuracy achieved in breast cancer through differing prognostic methodologies (N = 1,225).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-27 01:41:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/972142", "https://ndownloader.figshare.com/files/972152", "https://ndownloader.figshare.com/files/972157", "https://ndownloader.figshare.com/files/972159", "https://ndownloader.figshare.com/files/972163"], "description"=>"<div><p>Individualized approaches to prognosis are crucial to effective management of cancer patients. We developed a methodology to assign individualized 5-year disease-specific death probabilities to 1,222 patients with melanoma and to 1,225 patients with breast cancer. For each cancer, three risk subgroups were identified by stratifying patients according to initial stage, and prediction probabilities were generated based on the factors most closely related to 5-year disease-specific death. Separate subgroup probabilities were merged to form a single composite index, and its predictive efficacy was assessed by several measures, including the area (AUC) under its receiver operating characteristic (ROC) curve. The patient-centered methodology achieved an AUC of 0.867 in the prediction of 5-year disease-specific death, compared with 0.787 using the AJCC staging classification alone. When applied to breast cancer patients, it achieved an AUC of 0.907, compared with 0.802 using the AJCC staging classification alone. A prognostic algorithm produced from a randomly selected training subsample of 800 melanoma patients preserved 92.5% of its prognostic efficacy (as measured by AUC) when the same algorithm was applied to a validation subsample containing the remaining patients. Finally, the tailored prognostic approach enhanced the identification of high-risk candidates for adjuvant therapy in melanoma. These results describe a novel patient-centered prognostic methodology with improved predictive efficacy when compared with AJCC stage alone in two distinct malignancies drawn from two separate populations.</p> </div>", "links"=>[], "tags"=>["patient-centered", "methodology", "improves", "prognostic", "predictions", "cancer"], "article_id"=>640901, "categories"=>["Cancer", "Developmental Biology", "Biotechnology"], "users"=>["Mohammed Kashani-Sabet", "Richard W. Sagebiel", "Heikki Joensuu", "James R. Miller III"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0056435.s001", "https://dx.doi.org/10.1371/journal.pone.0056435.s002", "https://dx.doi.org/10.1371/journal.pone.0056435.s003", "https://dx.doi.org/10.1371/journal.pone.0056435.s004", "https://dx.doi.org/10.1371/journal.pone.0056435.s005"], "stats"=>{"downloads"=>11, "page_views"=>26, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/A_Patient_Centered_Methodology_That_Improves_the_Accuracy_of_Prognostic_Predictions_in_Cancer__/640901", "title"=>"A Patient-Centered Methodology That Improves the Accuracy of Prognostic Predictions in Cancer", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-02-28 09:55:03"}

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  • {"unique-ip"=>"1", "full-text"=>"0", "pdf"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"5", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}
  • {"unique-ip"=>"6", "full-text"=>"4", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"1", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"8"}
  • {"unique-ip"=>"4", "full-text"=>"3", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"9"}

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Medicine and health sciences/Anatomy and physiology", "average_usage"=>[253, 430]}, {"subject_area"=>"/Medicine and health sciences/Dermatology", "average_usage"=>[263, 475, 610, 728, 827, 905, 998, 1117, 1223, 1313, 1412, 1514, 1619, 1709]}, {"subject_area"=>"/Medicine and health sciences/Diagnostic medicine", "average_usage"=>[244, 425, 535, 636, 728, 814, 900, 982, 1063, 1139, 1221, 1296, 1361]}, {"subject_area"=>"/Medicine and health sciences/Pharmaceutics", "average_usage"=>[254, 457, 591, 700, 808, 906, 1001, 1093, 1185, 1276, 1373, 1457, 1535]}]}
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