A Review of the Study Designs and Statistical Methods Used in the Determination of Predictors of All-Cause Mortality in HIV-Infected Cohorts: 2002–2011
- Publication Date
- February 03, 2014
- Journal
- PLOS ONE
- Authors
- Kennedy N. Otwombe, Max Petzold, Neil Martinson & Tobias Chirwa
- Volume
- 9
- Issue
- 2
- Pages
- e87356
- DOI
- https://dx.plos.org/10.1371/journal.pone.0087356
- Publisher URL
- http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0087356
- PubMed
- http://www.ncbi.nlm.nih.gov/pubmed/24498313
- PubMed Central
- http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3911971
- Europe PMC
- http://europepmc.org/abstract/MED/24498313
- Web of Science
- 000330626900059
- Scopus
- 84896817265
- Mendeley
- http://www.mendeley.com/research/review-study-designs-statistical-methods-used-determination-predictors-allcause-mortality-hivinfecte-2
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Mendeley | Further Information
{"title"=>"A review of the study designs and statistical methods used in the determination of predictors of all-cause mortality in HIV-infected cohorts: 2002-2011", "type"=>"generic", "authors"=>[{"first_name"=>"Kennedy N.", "last_name"=>"Otwombe", "scopus_author_id"=>"8923896500"}, {"first_name"=>"Max", "last_name"=>"Petzold", "scopus_author_id"=>"7003628893"}, {"first_name"=>"Neil", "last_name"=>"Martinson", "scopus_author_id"=>"13907655800"}, {"first_name"=>"Tobias", "last_name"=>"Chirwa", "scopus_author_id"=>"24075268000"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"sgr"=>"84896817265", "doi"=>"10.1371/journal.pone.0087356", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"24498313", "issn"=>"19326203", "scopus"=>"2-s2.0-84896817265", "pui"=>"372485653"}, "id"=>"7dbc8a0c-1f9a-3b8d-809b-4423555482fe", "abstract"=>"BACKGROUND: Research in the predictors of all-cause mortality in HIV-infected people has widely been reported in literature. Making an informed decision requires understanding the methods used.\\n\\nOBJECTIVES: We present a review on study designs, statistical methods and their appropriateness in original articles reporting on predictors of all-cause mortality in HIV-infected people between January 2002 and December 2011. Statistical methods were compared between 2002-2006 and 2007-2011. Time-to-event analysis techniques were considered appropriate.\\n\\nDATA SOURCES: Pubmed/Medline.\\n\\nSTUDY ELIGIBILITY CRITERIA: Original English-language articles were abstracted. Letters to the editor, editorials, reviews, systematic reviews, meta-analysis, case reports and any other ineligible articles were excluded.\\n\\nRESULTS: A total of 189 studies were identified (n = 91 in 2002-2006 and n = 98 in 2007-2011) out of which 130 (69%) were prospective and 56 (30%) were retrospective. One hundred and eighty-two (96%) studies described their sample using descriptive statistics while 32 (17%) made comparisons using t-tests. Kaplan-Meier methods for time-to-event analysis were commonly used in the earlier period (n = 69, 76% vs. n = 53, 54%, p = 0.002). Predictors of mortality in the two periods were commonly determined using Cox regression analysis (n = 67, 75% vs. n = 63, 64%, p = 0.12). Only 7 (4%) used advanced survival analysis methods of Cox regression analysis with frailty in which 6 (3%) were used in the later period. Thirty-two (17%) used logistic regression while 8 (4%) used other methods. There were significantly more articles from the first period using appropriate methods compared to the second (n = 80, 88% vs. n = 69, 70%, p-value = 0.003).\\n\\nCONCLUSION: Descriptive statistics and survival analysis techniques remain the most common methods of analysis in publications on predictors of all-cause mortality in HIV-infected cohorts while prospective research designs are favoured. Sophisticated techniques of time-dependent Cox regression and Cox regression with frailty are scarce. This motivates for more training in the use of advanced time-to-event methods.", "link"=>"http://www.mendeley.com/research/review-study-designs-statistical-methods-used-determination-predictors-allcause-mortality-hivinfecte-2", "reader_count"=>34, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>4, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>6, "Student > Master"=>10, "Student > Bachelor"=>1, "Lecturer"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Researcher"=>4, "Student > Ph. D. Student"=>10, "Student > Postgraduate"=>6, "Student > Master"=>10, "Student > Bachelor"=>1, "Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Engineering"=>1, "Environmental Science"=>1, "Nursing and Health Professions"=>5, "Medicine and Dentistry"=>18, "Agricultural and Biological Sciences"=>1, "Pharmacology, Toxicology and Pharmaceutical Science"=>2, "Business, Management and Accounting"=>1, "Social Sciences"=>1, "Computer Science"=>1, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>18}, "Social Sciences"=>{"Social Sciences"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>1}, "Computer Science"=>{"Computer Science"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>5}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>1}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>2}}, "group_count"=>1}Scopus | Further Information
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