The SAGES Manual Transitioning to Practice pp 217-242 | Cite as
The Application of Biostatistics to Your Surgical Practice
Chapter
First Online:
Abstract
Whether moderating a journal club, reviewing scientific meeting abstracts, considering new evidence to integrate into your practice, or tracking your own outcomes, this chapter aims to provide a pragmatic guide to the considerations of studies relating to surgical practice. To that end, this chapter is framed through questions that a young surgeon should ask when reading, reviewing, or designing a research study. We highlight the biostatistical issues that should be considered as part of that evaluation.
Keywords
Propensity Score Central Tendency Bile Leak Negative Likelihood Ratio Journal Club
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
- 1.Richardson WS, Wilson MC, Nishikawa J, Hayward RS. The well-built clinical question: a key to evidence-based decisions. ACP J Club. 1995;123(3):A12–3.PubMedGoogle Scholar
- 2.Schardt C, Adams MB, Owens T, Keitz S, Fontelo P. Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med Inform Decis Mak. 2007;7:16.CrossRefPubMedPubMedCentralGoogle Scholar
- 3.Rosenthal R, Schafer J, Briel M, Bucher HC, Oertli D, Dell-Kuster S. How to write a surgical clinical research protocol: literature review and practical guide. Am J Surg. 2014;207(2):299–312.CrossRefPubMedGoogle Scholar
- 4.Fleming TR, Powers JH. Biomarkers and surrogate endpoints in clinical trials. Stat Med. 2012;31(25):2973–84.CrossRefPubMedPubMedCentralGoogle Scholar
- 5.Jaeschke R, Singer J, Guyatt GH. Measurement of health status. Ascertaining the minimal clinically important difference. Control Clin Trials. 1989;10(4):407–15.CrossRefPubMedGoogle Scholar
- 6.Turner L, Shamseer L, Altman DG, Weeks L, Peters J, Kober T, et al. Consolidated standards of reporting trials (CONSORT) and the completeness of reporting of randomised controlled trials (RCTs) published in medical journals. Cochrane Database Syst Rev. 2012;11:MR000030.PubMedGoogle Scholar
- 7.Nagendran M, Harding D, Teo W, Camm C, Maruthappu M, McCulloch P, et al. Poor adherence of randomised trials in surgery to CONSORT guidelines for non-pharmacological treatments (NPT): a cross-sectional study. BMJ Open. 2013;3(12):e003898,2013–003898.CrossRefGoogle Scholar
- 8.Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, Stroup DF. Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. quality of reporting of meta-analyses. Lancet. 1999;354(9193):1896–900.CrossRefPubMedGoogle Scholar
- 9.Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. meta-analysis of observational studies in epidemiology (MOOSE) group. JAMA. 2000;283(15):2008–12.CrossRefPubMedGoogle Scholar
- 10.Resche-Rigon M, Azoulay E, Chevret S. Evaluating mortality in intensive care units: contribution of competing risks analyses. Crit Care. 2006;10(1):R5.CrossRefPubMedGoogle Scholar
- 11.Chen W, Shi J, Qian L, Azen SP. Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study. BMC Med Res Methodol. 2014;14:–82. doi: 10.1186/1471-2288-14-82.
- 12.Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996;49(12):1373–9.CrossRefPubMedGoogle Scholar
- 13.Babyak MA. What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models. Psychosom Med. 2004;66(3):411–21.PubMedGoogle Scholar
- 14.Mehio-Sibai A, Feinleib M, Sibai TA, Armenian HK. A positive or a negative confounding variable? A simple teaching aid for clinicians and students. Ann Epidemiol. 2005;15(6):421–3.CrossRefPubMedGoogle Scholar
- 15.Haukoos JS, Lewis RJ. The propensity score. JAMA. 2015;314(15):1637–8.CrossRefPubMedPubMedCentralGoogle Scholar
- 16.Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivar Behav Res. 2011;46(3):399–424.CrossRefGoogle Scholar
- 17.Simianu VV, Farjah F, Flum D. Evidence-based surgery: critically assessing surgical literature (Chapter 8). In: Townsend CM, Beauchamp RD, Evers BM, Mattox KL, editors. Sabiston textbook of surgery. Philadelphia: Elsevier; 2016.Google Scholar
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