Validation of the Symptom Pattern Method for Analyzing Verbal Autopsy Data
Publication Date
November 20, 2007
Journal
PLOS Medicine
Authors
Christopher J. L Murray, Alan D Lopez, Dennis M Feehan, Shanon T Peter, et al
Volume
4
Issue
11
Pages
e327
DOI
http://doi.org/10.1371/journal.pmed.0040327
Publisher URL
http://journals.plos.org/plosmedicine/article?id=10.1371%2Fjournal.pmed.0040327
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/18031196
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2080648
Europe PMC
http://europepmc.org/abstract/MED/18031196
Web of Science
000251874400011
Mendeley
http://www.mendeley.com/research/validation-symptom-pattern-method-analyzing-verbal-autopsy-data
Events
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Mendeley | Further Information

{"title"=>"Validation of the Symptom Pattern Method for Analyzing Verbal Autopsy Data", "type"=>"journal", "authors"=>[{"first_name"=>"Christopher J. L", "last_name"=>"Murray"}, {"first_name"=>"Alan D", "last_name"=>"Lopez"}, {"first_name"=>"Dennis M", "last_name"=>"Feehan"}, {"first_name"=>"Shanon T", "last_name"=>"Peter"}, {"first_name"=>"Gonghuan", "last_name"=>"Yang"}], "year"=>2007, "source"=>"PLoS Medicine", "identifiers"=>{"doi"=>"10.1371/journal.pmed.0040327", "pui"=>"350220528", "issn"=>"1549-1676", "scopus"=>"2-s2.0-36849081980", "sgr"=>"36849081980", "pmid"=>"18031196", "isbn"=>"1549-1676 (Electronic)"}, "id"=>"df3e999e-400a-3005-b5c7-727b876e216e", "abstract"=>"BACKGROUND: Cause of death data are a critical input to formulating good public health policy. In the absence of reliable vital registration data, information collected after death from household members, called verbal autopsy (VA), is commonly used to study causes of death. VA data are usually analyzed by physician-coded verbal autopsy (PCVA). PCVA is expensive and its comparability across regions is questionable. Nearly all validation studies of PCVA have allowed physicians access to information collected from the household members' recall of medical records or contact with health services, thus exaggerating accuracy of PCVA in communities where few deaths had any interaction with the health system. In this study we develop and validate a statistical strategy for analyzing VA data that overcomes the limitations of PCVA. METHODS AND FINDINGS: We propose and validate a method that combines the advantages of methods proposed by King and Lu, and Byass, which we term the symptom pattern (SP) method. The SP method uses two sources of VA data. First, it requires a dataset for which we know the true cause of death, but which need not be representative of the population of interest; this dataset might come from deaths that occur in a hospital. The SP method can then be applied to a second VA sample that is representative of the population of interest. From the hospital data we compute the properties of each symptom; that is, the probability of responding yes to each symptom, given the true cause of death. These symptom properties allow us first to estimate the population-level cause-specific mortality fractions (CSMFs), and to then use the CSMFs as an input in assigning a cause of death to each individual VA response. Finally, we use our individual cause-of-death assignments to refine our population-level CSMF estimates. The results from applying our method to data collected in China are promising. At the population level, SP estimates the CSMFs with 16% average relative error and 0.7% average absolute error, while PCVA results in 27% average relative error and 1.1% average absolute error. At the individual level, SP assigns the correct cause of death in 83% of the cases, while PCVA does so for 69% of the cases. We also compare the results of SP and PCVA when both methods have restricted access to the information from the medical record recall section of the VA instrument. At the population level, without medical record recall, the SP method estimates the CSMFs with 14% average relative error and 0.6% average absolute error, while PCVA results in 70% average relative error and 3.2% average absolute error. For individual estimates without medical record recall, SP assigns the correct cause of death in 78% of cases, while PCVA does so for 38% of cases. CONCLUSIONS: Our results from the data collected in China suggest that the SP method outperforms PCVA, both at the population and especially at the individual level. Further study is needed on additional VA datasets in order to continue validation of the method, and to understand how the symptom properties vary as a function of culture, language, and other factors. Our results also suggest that PCVA relies heavily on household recall of medical records and related information, limiting its applicability in low-resource settings. SP does not require that additional information to adequately estimate causes of death.", "link"=>"http://www.mendeley.com/research/validation-symptom-pattern-method-analyzing-verbal-autopsy-data", "reader_count"=>93, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Librarian"=>1, "Researcher"=>22, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>7, "Other"=>11, "Student > Master"=>11, "Student > Bachelor"=>5, "Lecturer > Senior Lecturer"=>2, "Professor"=>6}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Librarian"=>1, "Researcher"=>22, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>16, "Student > Postgraduate"=>7, "Other"=>11, "Student > Master"=>11, "Student > Bachelor"=>5, "Lecturer > Senior Lecturer"=>2, "Professor"=>6}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Agricultural and Biological Sciences"=>13, "Arts and Humanities"=>2, "Business, Management and Accounting"=>3, "Chemistry"=>2, "Computer Science"=>6, "Earth and Planetary Sciences"=>2, "Economics, Econometrics and Finance"=>1, "Engineering"=>2, "Environmental Science"=>1, "Nursing and Health Professions"=>3, "Mathematics"=>2, "Medicine and Dentistry"=>40, "Psychology"=>2, "Social Sciences"=>9, "Linguistics"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>40}, "Social Sciences"=>{"Social Sciences"=>9}, "Psychology"=>{"Psychology"=>2}, "Mathematics"=>{"Mathematics"=>2}, "Unspecified"=>{"Unspecified"=>4}, "Environmental Science"=>{"Environmental Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>2}, "Engineering"=>{"Engineering"=>2}, "Chemistry"=>{"Chemistry"=>2}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>2}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>13}, "Computer Science"=>{"Computer Science"=>6}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>3}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>3}, "Linguistics"=>{"Linguistics"=>1}}, "reader_count_by_country"=>{"Austria"=>1, "United States"=>3, "Guatemala"=>1, "Denmark"=>1, "United Kingdom"=>3, "South Africa"=>2, "France"=>2, "Switzerland"=>2}, "group_count"=>6}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/941862"], "description"=>"<div><p>Results are from the SP method and PCVA, with and without the symptoms derived from medical record recall.</p>\n <p>(A) Average relative error in population-level CSMF estimates for WPR-B.</p>\n <p>(B) Average absolute error in population-level CSMF estimates for simulated WPR-B data.</p>\n <p>(C) Percent concordance (percent of deaths agreeing with gold standard) for individual-level cause of death assignments in WPR-B data.</p></div>", "links"=>[], "tags"=>["measures", "individual-level", "cause-of-death", "changed", "simulate", "subregion"], "article_id"=>612261, "categories"=>["Biotechnology"], "users"=>["Christopher J. L Murray", "Alan D Lopez", "Dennis M Feehan", "Shanon T Peter", "Gonghuan Yang"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0040327.g003", "stats"=>{"downloads"=>3, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_Measures_of_Error_in_Population_and_Individual_Level_Cause_of_Death_Estimates_Background_Cause_Composition_of_Mortality_Changed_to_Simulate_Distribution_in_WHO_Subregion_WPR_B_/612261", "title"=>"Summary Measures of Error in Population and Individual-Level Cause-of-Death Estimates, Background Cause Composition of Mortality Changed to Simulate Distribution in WHO Subregion WPR-B", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 11:30:49"}
  • {"files"=>["https://ndownloader.figshare.com/files/942016"], "description"=>"<p>The means were computed over the 100 draws of the China data.</p>", "links"=>[], "tags"=>["csmf", "probable", "posterior", "23"], "article_id"=>612423, "categories"=>["Biotechnology"], "users"=>["Christopher J. L Murray", "Alan D Lopez", "Dennis M Feehan", "Shanon T Peter", "Gonghuan Yang"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0040327.g005", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_the_Average_CSMF_Estimated_Using_the_Single_Most_Probable_Posterior_Cause_and_the_Average_CSMF_Estimated_Using_the_Posterior_Distribution_of_All_23_Causes_/612423", "title"=>"Comparison of the Average CSMF Estimated Using the Single Most Probable Posterior Cause and the Average CSMF Estimated Using the Posterior Distribution of All 23 Causes", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 11:31:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/941936"], "description"=>"<p>The height of each bar over each cause of death represents the probability, estimated using the SP method, of the individual having died of that cause.</p>", "links"=>[], "tags"=>["posterior", "cause-of-death", "probabilities", "produced", "deaths", "cirrhosis"], "article_id"=>612340, "categories"=>["Biotechnology"], "users"=>["Christopher J. L Murray", "Alan D Lopez", "Dennis M Feehan", "Shanon T Peter", "Gonghuan Yang"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0040327.g004", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sample_Posterior_Cause_of_Death_Probabilities_Produced_by_the_Symptom_Pattern_Method_for_Two_Deaths_Whose_True_Cause_Was_Cirrhosis_of_the_Liver_/612340", "title"=>"Sample Posterior Cause-of-Death Probabilities Produced by the Symptom Pattern Method for Two Deaths Whose True Cause Was Cirrhosis of the Liver", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 11:31:15"}
  • {"files"=>["https://ndownloader.figshare.com/files/941775"], "description"=>"<div><p>Results are from the SP method and PCVA, with and without the symptoms derived from medical record recall.</p>\n <p>(A) Average relative error in population-level CSMF estimates for SEAR-D.</p>\n <p>(B) Average absolute error in population-level CSMF estimates for simulated SEAR-D data.</p>\n <p>(C) Percent concordance (percent of deaths agreeing with gold standard) for individual-level cause of death (COD) assignments in SEAR-D data.</p></div>", "links"=>[], "tags"=>["measures", "individual-level", "cause-of-death", "changed", "simulate", "subregion"], "article_id"=>612185, "categories"=>["Biotechnology"], "users"=>["Christopher J. L Murray", "Alan D Lopez", "Dennis M Feehan", "Shanon T Peter", "Gonghuan Yang"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0040327.g002", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_Measures_of_Error_in_Population_and_Individual_Level_Cause_of_Death_Estimates_Background_Cause_Composition_of_Mortality_Changed_to_Simulate_Distribution_in_WHO_Subregion_SEAR_D_/612185", "title"=>"Summary Measures of Error in Population and Individual-Level Cause-of-Death Estimates, Background Cause Composition of Mortality Changed to Simulate Distribution in WHO Subregion SEAR-D", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 11:30:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/941691"], "description"=>"<div><p>Results are from the SP method and PCVA with and without the symptoms derived from recall of medical records.</p>\n <p>(A) Average relative error in population-level CSMF estimates for China data.</p>\n <p>(B) Average absolute error in population-level CSMF estimates for China data.</p>\n <p>(C) Percent concordance (percent of deaths agreeing with gold standard) for individual-level cause-of-death (COD) assignments in China data.</p></div>", "links"=>[], "tags"=>["measures", "individual-level", "cause-of-death", "estimates", "china"], "article_id"=>612103, "categories"=>["Biotechnology"], "users"=>["Christopher J. L Murray", "Alan D Lopez", "Dennis M Feehan", "Shanon T Peter", "Gonghuan Yang"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.0040327.g001", "stats"=>{"downloads"=>2, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_Measures_of_Error_in_Population_and_Individual_Level_Cause_of_Death_Estimates_for_China_Data_/612103", "title"=>"Summary Measures of Error in Population and Individual-Level Cause-of-Death Estimates for China Data", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-21 11:29:49"}

PMC Usage Stats | Further Information

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Relative Metric

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