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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

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  • Kennedy N Otwombe
  • Max Petzold
  • Neil Martinson
  • Tobias Chirwa

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. Objectives: 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. Data Sources: Pubmed/Medline. Study 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. Results: 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). Conclusion: 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.

Suggested Citation

  • Kennedy N Otwombe & Max Petzold & Neil Martinson & Tobias Chirwa, 2014. "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," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-6, February.
  • Handle: RePEc:plo:pone00:0087356
    DOI: 10.1371/journal.pone.0087356
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    References listed on IDEAS

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    1. Strasak, Alexander M. & Zaman, Qamruz & Marinell, Gerhard & Pfeiffer, Karl P. & Ulmer, Hanno, 2007. "[MEDICINE] The Use of Statistics in Medical Research: A Comparison of The New England Journal of Medicine and Nature Medicine," The American Statistician, American Statistical Association, vol. 61, pages 47-55, February.
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    1. Adeniyi Francis Fagbamigbe & Emma Norrman & Christina Bergh & Ulla-Britt Wennerholm & Max Petzold, 2021. "Comparison of the performances of survival analysis regression models for analysis of conception modes and risk of type-1 diabetes among 1985–2015 Swedish birth cohort," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-23, June.

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