Literature DB >> 30797315

Research Techniques Made Simple: Interpreting Measures of Association in Clinical Research.

Michelle R Roberts1, Sepideh Ashrafzadeh1, Maryam M Asgari2.   

Abstract

To bring evidence-based improvements in medicine and health care delivery to clinical practice, health care providers must know how to interpret clinical research findings and critically evaluate the strength of evidence. This requires an understanding of differences in clinical study designs and the various statistical methods used to identify associations. We aim to provide a foundation for understanding the common measures of association used in epidemiologic studies to quantify relationships between exposures and outcomes, including relative risks, odds ratios, and hazard ratios. We also provide a framework for critically assessing clinical research findings and highlight specific methodologic concerns.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

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Mesh:

Year:  2019        PMID: 30797315      PMCID: PMC7737849          DOI: 10.1016/j.jid.2018.12.023

Source DB:  PubMed          Journal:  J Invest Dermatol        ISSN: 0022-202X            Impact factor:   8.551


  28 in total

1.  Bias.

Authors:  Miguel Delgado-Rodríguez; Javier Llorca
Journal:  J Epidemiol Community Health       Date:  2004-08       Impact factor: 3.710

Review 2.  Study designs in dermatology: A review for the clinical dermatologist.

Authors:  Jonathan I Silverberg
Journal:  J Am Acad Dermatol       Date:  2015-11       Impact factor: 11.527

3.  Causation and causal inference in epidemiology.

Authors:  Kenneth J Rothman; Sander Greenland
Journal:  Am J Public Health       Date:  2005       Impact factor: 9.308

4.  Fitzpatrick Skin Type, Individual Typology Angle, and Melanin Index in an African Population: Steps Toward Universally Applicable Skin Photosensitivity Assessments.

Authors:  Marcus Wilkes; Caradee Y Wright; Johan L du Plessis; Anthony Reeder
Journal:  JAMA Dermatol       Date:  2015-08       Impact factor: 10.282

5.  A critical evaluation of clinical research study designs.

Authors:  Justin Besen; Stephanie D Gan
Journal:  J Invest Dermatol       Date:  2014-03       Impact factor: 8.551

6.  Prognostic factors and survival in acral lentiginous melanoma.

Authors:  M M Asgari; L Shen; M M Sokil; I Yeh; E Jorgenson
Journal:  Br J Dermatol       Date:  2017-07-28       Impact factor: 9.302

Review 7.  Clinician's checklist for reading and using an article about patient-reported outcomes.

Authors:  Albert W Wu; Anna N Bradford; Vic Velanovich; Mirjam A G Sprangers; Michael Brundage; Claire Snyder
Journal:  Mayo Clin Proc       Date:  2014-04-03       Impact factor: 7.616

8.  A cohort study of vitamin D intake and melanoma risk.

Authors:  Maryam M Asgari; Sonia S Maruti; Lawrence H Kushi; Emily White
Journal:  J Invest Dermatol       Date:  2009-02-05       Impact factor: 8.551

9.  Gene expression imputation identifies candidate genes and susceptibility loci associated with cutaneous squamous cell carcinoma.

Authors:  Nilah M Ioannidis; Wei Wang; Nicholas A Furlotte; David A Hinds; Carlos D Bustamante; Eric Jorgenson; Maryam M Asgari; Alice S Whittemore
Journal:  Nat Commun       Date:  2018-10-15       Impact factor: 17.694

10.  Systemic immune suppression predicts diminished Merkel cell carcinoma-specific survival independent of stage.

Authors:  Kelly G Paulson; Jayasri G Iyer; Astrid Blom; E Margaret Warton; Monica Sokil; Lola Yelistratova; Louise Schuman; Kotaro Nagase; Shailender Bhatia; Maryam M Asgari; Paul Nghiem
Journal:  J Invest Dermatol       Date:  2012-11-29       Impact factor: 8.551

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