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Medical Biostatistics: Basic Concepts

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Management of Hypertension

Abstract

The goal of this chapter is to provide an overview of essential biostatistical methods available to landmarks trials that investigate hypertension. We begin with an introduction to the basic types of variables and then demonstrate methods for summarizing, visualizing, and understanding data. The chapter continues with basic principles in the context of hypothesis testing and interpretation of effect sizes, confidence intervals and p-values. We also describe the processes of selecting the appropriate statistical test in bivariable analysis (e.g., t-test, ANOVA, chi-squared test) and outline basic regression methods (multivariable analysis), with a focus on survival analysis and Cox proportional hazards model. It also briefly covers topics such as intention-to-treat and per protocol analyses, interim analysis, subgroup and sensitivity analyses, sample size calculation and power of the study. The focus of the chapter is not on computational formulas, but on basic concepts with examples from landmark trials. At the end, the reader will have learned the essential principles and tools of biostatistics required for research in hypertension field.

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References

  1. Everitt BS. Medical statistics from A to Z. Cambridge, UK: Cambridge University Press; 2006.

    Book  Google Scholar 

  2. Peters TJ, Eachus JI. Achieving equal probability of selection under various random sampling strategies. Paediatr Perinat Epidemiol England. 1995;9:219–24.

    Article  CAS  Google Scholar 

  3. Martinez-Mesa J, Gonzalez-Chica DA, Duquia RP, Bonamigo RR, Bastos JL. Sampling: how to select participants in my research study? An Bras Dermatol Brazil. 2016;91:326–30.

    Article  Google Scholar 

  4. Hopewell S, Dutton S, Yu L-M, Chan A-W, Altman DG. The quality of reports of randomised trials in 2000 and 2006: comparative study of articles indexed in PubMed. BMJ [Internet]. 2010;340. Available from: http://www.bmj.com/content/340/bmj.c723.abstract.

  5. Moher D, Hopewell S, Schulz KF, Montori V, Gotzsche PC, Devereaux PJ, et al. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. Int J Surg England. 2012;10:28–55.

    Article  Google Scholar 

  6. Julius S, Weber MA, Kjeldsen SE, McInnes GT, Zanchetti A, Brunner HR, et al. The Valsartan Antihypertensive Long-Term Use Evaluation (VALUE) trial. Hypertension [Internet]. 2006;48:385–391. Available from: http://hyper.ahajournals.org/content/48/3/385.abstract.

  7. Williams B, MacDonald TM, Morant S, Webb DJ, Sever P, McInnes G, et al. Spironolactone versus placebo, bisoprolol, and doxazosin to determine the optimal treatment for drug-resistant hypertension (PATHWAY-2): a randomised, double-blind, crossover trial. Lancet [Internet]. Elsevier; 2017;386:2059–68. Available from: https://doi.org/10.1016/S0140-6736(15)00257-3.

    Article  CAS  Google Scholar 

  8. Campbell MK, Piaggio G, Elbourne DR, Altman DG. Consort 2010 statement: extension to cluster randomised trials. BMJ. England. 2012;345:e5661.

    Article  Google Scholar 

  9. Bosworth HB, Olsen MK, Dudley T, Orr M, Goldstein MK, Datta SK, et al. Patient education and provider decision support to control blood pressure in primary care: a cluster randomized trial. Am Heart J United States. 2009;157:450–6.

    Article  Google Scholar 

  10. Wright JTJ, Bakris G, Greene T, Agodoa LY, Appel LJ, Charleston J, et al. Effect of blood pressure lowering and antihypertensive drug class on progression of hypertensive kidney disease: results from the AASK trial. JAMA. United States. 2002;288:2421–31.

    CAS  Google Scholar 

  11. Vickers AJ. How to randomize. J Soc Integr Oncol Canada. 2006;4:194–8.

    Article  Google Scholar 

  12. Suresh KP. An overview of randomization techniques: an unbiased assessment of outcome in clinical research. J Hum Reprod Sci [Internet]. India: Medknow Publications Pvt Ltd; 2011;4:8–11. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3136079/.

  13. Beckett NS, Peters R, Fletcher AE, Staessen JA, Liu L, Dumitrascu D, et al. Treatment of hypertension in patients 80 years of age or older. N Engl J Med [Internet]. Massachusetts Medical Society; 2008;358:1887–98. Available from: https://doi.org/10.1056/NEJMoa0801369.

    Article  CAS  Google Scholar 

  14. Aviva P, Caroline S. Medical statistics at a glance. 3rd ed. Oxford, UK: Wiley Blackwell; 2009.

    Google Scholar 

  15. Thomas E. An introduction to medical statistics for health care professionals: describing and presenting data. Musculoskeletal Care England. 2004;2:218–28.

    Article  Google Scholar 

  16. Kirkwood BR, Sterne JAC. Essential medical statistics. 2nd ed. Hoboken: Wiley-Blackwell; 2003.

    Google Scholar 

  17. SPRINT Research Group. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med [Internet]. Massachusetts Medical Society; 2015;373:2103–16. Available from: https://doi.org/10.1056/NEJMoa1511939.

  18. Wang D, Bakhai A. Clinical trials: a practical guide to design, analysis, and reporting. London: Remedica; 2006.

    Google Scholar 

  19. Paul S. Clinical endpoint. Encycl Biopharm Stat. 3rd ed. [Internet]. CRC Press; 2012. p. 273–5. Available from: https://doi.org/10.1201/b14674-43.

    Chapter  Google Scholar 

  20. Black HR, Elliott WJ, Grandits G, Grambsch P, Lucente T, White WB, Neaton JD, Grimm Jr. RH, Hansson L, Lacourcière Y, Muller J. Principal results of the controlled onset verapamil investigation of cardiovascular end points (CONVINCE) trial. JAMA [Internet]. 2003;289:2073–82. Available from: https://doi.org/10.1001/jama.289.16.2073.

    Article  CAS  Google Scholar 

  21. Duquia RP, Bastos JL, Bonamigo RR, González-Chica DA, Martínez-Mesa J. Presenting data in tables and charts. An Bras Dermatol [Internet]. Sociedade Brasileira de Dermatologia; 2014;89:280–5. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4008059/.

    Article  Google Scholar 

  22. Rice K, Lumley T. Graphics and statistics for cardiology: comparing categorical and continuous variables. Heart. England. 2016;102:349–55.

    Article  Google Scholar 

  23. Black HR, Elliott WJ, Grandits G, Grambsch P, Lucente T, White WB, et al. Principal results of the controlled onset verapamil investigation of cardiovascular end points (CONVINCE) trial. JAMA. United States. 2003;289:2073–82.

    CAS  Google Scholar 

  24. Krum H, Schlaich MP, Sobotka PA, Böhm M, Mahfoud F, Rocha-Singh K, et al. Percutaneous renal denervation in patients with treatment-resistant hypertension: final 3-year report of the Symplicity HTN-1 study. Lancet [Internet]. Elsevier; 2017;383:622–9. Available from: https://doi.org/10.1016/S0140-6736(13)62192-3.

    Article  Google Scholar 

  25. Annesley TM. Bars and pies make better desserts than figures. Clin Chem United States. 2010;56:1394–400.

    Article  CAS  Google Scholar 

  26. Hink JK, Eustace JK, Wogalter MS. Do grables enable the extraction of quantitative information better than pure graphs or tables? Int J Ind Ergon [Internet]. 1998;22:439–47. Available from: http://www.sciencedirect.com/science/article/pii/S0169814197000176.

    Article  Google Scholar 

  27. Kozak M, Hartley J, Wnuk A, Tartanus M. Multiple pie charts: unreadable, inefficient, and over-used. J Sch Publ [Internet]. University of Toronto Press; 2015;46:282–9. Available from: https://doi.org/10.3138/jsp.46.3.05.

    Article  Google Scholar 

  28. Rosner B. Fundamentals of biostatistics. Boston: Cengage Learning; 2010.

    Google Scholar 

  29. Rumsey DJ. Statistics for dummies. Hoboken: Wiley; 2011.

    Google Scholar 

  30. Biffi A, CD A, TK B, et al. Association between blood pressure control and risk of recurrent intracerebral hemorrhage. JAMA [Internet]. 2015;314:904–12. Available from: https://doi.org/10.1001/jama.2015.10082.

    Article  CAS  Google Scholar 

  31. Nuzzo RL. The box plots alternative for visualizing quantitative data. PM&R [Internet]. 2016;8:268–72. Available from: http://www.sciencedirect.com/science/article/pii/S1934148216000678.

    Article  Google Scholar 

  32. Thabane L, Akhtar-Danesh N. Guidelines for reporting descriptive statistics in health research. Nurse Res England. 2008;15:72–81.

    Article  Google Scholar 

  33. Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. BMJ [Internet]. 1998;317:703–713. Available from: http://www.bmj.com/content/317/7160/703.abstract.

  34. Duran-Cantolla J, Aizpuru F, Montserrat JM, Ballester E, Teran-Santos J, Aguirregomoscorta JI, et al. Continuous positive airway pressure as treatment for systemic hypertension in people with obstructive sleep apnoea: randomised controlled trial. BMJ. England. 2010;341:c5991.

    Article  Google Scholar 

  35. Effects of intensive blood-pressure control in type 2 diabetes mellitus. N Engl J Med [Internet]. Massachusetts Medical Society; 2010;362:1575–85. Available from: https://doi.org/10.1056/NEJMoa1001286.

  36. Mancia G, Facchetti R, Parati G, Zanchetti A. Effect of long-term antihypertensive treatment on white-coat hypertension. Hypertens (Dallas, Tex 1979) United States. 2014;64:1388–98.

    Article  CAS  Google Scholar 

  37. Logan M. Biostatistical design and analysis using R: a practical guide. Chichester: Wiley; 2011.

    Google Scholar 

  38. Lobo MD, Sobotka PA, Stanton A, Cockcroft JR, Sulke N, Dolan E, et al. Central arteriovenous anastomosis for the treatment of patients with uncontrolled hypertension (the ROX CONTROL HTN study): a randomised controlled trial. Lancet (London, England) England. 2015;385:1634–41.

    Article  Google Scholar 

  39. Kirkwood BR, Sterne JAC. Essential medical statistics. Hoboken: Wiley; 2010.

    Google Scholar 

  40. Major outcomes in high-risk hypertensive patients randomized to angiotensin-converting enzyme inhibitor or calcium channel blocker vs diuretic: The Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). JAMA United States. 2002;288:2981–97.

    Google Scholar 

  41. Chernick MR, Friis RH. Introductory biostatistics for the health sciences: modern applications including bootstrap. Hoboken: Wiley; 2003.

    Book  Google Scholar 

  42. Dunn OJ, Clark VA. Basic statistics: a primer for the biomedical sciences. Hoboken: Wiley; 2009.

    Book  Google Scholar 

  43. Sedgwick P. A comparison of parametric and non-parametric statistical tests. BMJ. England. 2015;350:h2053.

    Article  Google Scholar 

  44. du Prel J-B, Rohrig B, Hommel G, Blettner M. Choosing statistical tests: part 12 of a series on evaluation of scientific publications. Dtsch Arztebl Int Germany. 2010;107:343–8.

    Google Scholar 

  45. Cao J, Zhang S. Multiple comparison procedures. JAMA. United States. 2014;312:543–4.

    CAS  Google Scholar 

  46. Kim H-Y. Statistical notes for clinical researchers: post-hoc multiple comparisons. Restor Dent Endod Korea (South). 2015;40:172–6.

    Article  Google Scholar 

  47. Write PS. Adjusted P-values for simultaneous inference. Biometrics. 1992;43:1005–13.

    Google Scholar 

  48. George B, Seals S, Aban I. Survival analysis and regression models. J Nucl Cardiol [Internet]. 2014;21:686–94. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4111957/.

    Article  Google Scholar 

  49. Kleinbaum D, Klein M. Survival analysis: a self-learning text (Statistics for Biology and Health) [Internet]. Springer; 2005. Available from: citeulike-article-id:3504416.

    Google Scholar 

  50. May S, McKnight B. Graphics and statistics for cardiology: survival analysis. Heart England. 2017;103:335–40.

    Article  Google Scholar 

  51. Altman DG. Practical statistics for medical research. 1st ed. London/New York: Chapman and Hall; 1991.

    Google Scholar 

  52. Selvin S. Survival analysis for epidemiologic and medical research [Internet]. Pract Guid Biostat Epidemiol. Cambridge: Cambridge University Press; 2008. Available from: https://www.cambridge.org/core/books/survival-analysis-for-epidemiologic-and-medical-research/021027404E37FCD99D5A9176D9EAB051.

  53. Jager KJ, van Dijk PC, Zoccali C, Dekker FW. The analysis of survival data: the Kaplan-Meier method. Kidney Int United States. 2008;74:560–5.

    Article  Google Scholar 

  54. Österlund P, Soveri L-M, Isoniemi H, Poussa T, Alanko T, Bono P. Hypertension and overall survival in metastatic colorectal cancer patients treated with bevacizumab-containing chemotherapy. Br J Cancer [Internet]. Nature Publishing Group; 2011;104:599–604. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3049598/.

    Article  Google Scholar 

  55. Upadhya B, Rocco M, Lewis CE, Oparil S, Lovato LC, Cushman WC, et al. Effect of intensive blood pressure treatment on heart failure events in the systolic blood pressure reduction intervention trial. Circ Heart Fail United States. 2017;10:e003613.

    Article  Google Scholar 

  56. Clark TG, Bradburn MJ, Love SB, Altman DG. Survival analysis part I: basic concepts and first analyses. Br J Cancer England. 2003;89:232–8.

    Article  CAS  Google Scholar 

  57. Estruch R, Ros E, Salas-Salvado J, Covas M-I, Corella D, Aros F, et al. Primary Prevention of Cardiovascular Disease with a Mediterranean Diet Supplemented with Extra-Virgin Olive Oil or Nuts. N Engl J Med [Internet]. 2018;378(25):e34. Available from: https://doi.org/10.1056/NEJMoa1800389.

    Article  CAS  Google Scholar 

  58. Tolles J, Lewis RJ. Time-to-event analysis. JAMA. United States. 2016;315:1046–7.

    CAS  Google Scholar 

  59. Bradburn MJ, Clark TG, Love SB, Altman DG. Survival analysis Part III: multivariate data analysis – choosing a model and assessing its adequacy and fit. Br J Cancer [Internet]. Nature Publishing Group; 2003;89:605–11. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2376927/.

    Article  CAS  Google Scholar 

  60. Weber MA, Jamerson K, Bakris GL, Weir MR, Zappe D, Zhang Y, et al. Effects of body size and hypertension treatments on cardiovascular event rates: subanalysis of the ACCOMPLISH randomised controlled trial. Lancet [Internet]. Elsevier; 2017;381:537–45. Available from: https://doi.org/10.1016/S0140-6736(12)61343-9.

    Article  Google Scholar 

  61. Newell DJ. Intention-to-treat analysis: implications for quantitative and qualitative research. Int J Epidemiol England. 1992;21:837–41.

    Article  CAS  Google Scholar 

  62. Moher D, Hopewell S, Schulz KF. CONSORT 2010 explanation and elaboration: updated guidelines for reporting parallel group randomised trials. BMJ [Internet]. 2010;340. Available from: https://doi.org/10.1136/bmj.c869.

    Article  Google Scholar 

  63. Lewis JA, Machin D. Intention to treat--who should use ITT? Br J Cancer England. 1993;68:647–50.

    Article  CAS  Google Scholar 

  64. Shah PB. Intention-to-treat and per-protocol analysis. C Can Med Assoc J [Internet]. Canadian Medical Association; 2011;183:696. Available from: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3071397/.

    Article  Google Scholar 

  65. Friedman LM, Furberg CD, DeMets DL. Fundamentals of clinical trials. New York: Springer; 2010.

    Book  Google Scholar 

  66. Spieth PM, Kubasch AS, Penzlin AI, Illigens BM-W, Barlinn K, Siepmann T. Randomized controlled trials – a matter of design. Neuropsychiatr Dis Treat New Zealand. 2016;12:1341–9.

    Google Scholar 

  67. Jamerson K, Weber MA, Bakris GL, Dahlöf B, Pitt B, Shi V, et al. Benazepril plus amlodipine or hydrochlorothiazide for hypertension in high-risk patients. N Engl J Med [Internet]. Massachusetts Medical Society; 2008;359:2417–28. Available from: https://doi.org/10.1056/NEJMoa0806182.

    Article  CAS  Google Scholar 

  68. POCOCK SJ. Group sequential methods in the design and analysis of clinical trials. Biometrika [Internet]. 1977;64:191–9. Available from: https://doi.org/10.1093/biomet/64.2.191.

    Article  Google Scholar 

  69. Pocock SJ. Interim analyses for randomized clinical trials: the group sequential approach. Biometrics [Internet]. [Wiley, International Biometric Society]; 1982;38:153–62. Available from: http://www.jstor.org/stable/2530298.

    Article  CAS  Google Scholar 

  70. O’Brien PC, Fleming TR. A multiple testing procedure for clinical trials. Biometrics [Internet]. [Wiley, International Biometric Society]; 1979;35:549–56. Available from: http://www.jstor.org/stable/2530245.

    Article  CAS  Google Scholar 

  71. Gordon Lan KK, Demets DL. Discrete sequential boundaries for clinical trials. Biometrika [Internet]. 1983;70:659–63. Available from: https://doi.org/10.1093/biomet/70.3.659.

    Article  Google Scholar 

  72. Pocock SJ, McMurray JJV, Collier TJ. Statistical controversies in reporting of clinical trials: part 2 of a 4-part series on statistics for clinical trials. J Am Coll Cardiol United States. 2015;66:2648–62.

    Article  Google Scholar 

  73. Matthews JN, Altman DG. Statistics notes. Interaction 2: compare effect sizes not P values. BMJ England. 1996;313:808.

    Article  CAS  Google Scholar 

  74. Lagakos SW. The challenge of subgroup analyses--reporting without distorting. N Engl J Med United States. 2006;354:1667–9.

    Article  CAS  Google Scholar 

  75. Hommel G. A stagewise rejective multiple test procedure based on a modified Bonferroni test. Biometrika [Internet]. 1988;75:383–6. Available from: https://doi.org/10.1093/biomet/75.2.383.

    Article  Google Scholar 

  76. Thabane L, Mbuagbaw L, Zhang S, Samaan Z, Marcucci M, Ye C, et al. A tutorial on sensitivity analyses in clinical trials: the what, why, when and how. BMC Med Res Methodol England. 2013;13:92.

    Article  Google Scholar 

  77. Noordzij M, Tripepi G, Dekker FW, Zoccali C, Tanck MW, Jager KJ. Sample size calculations: basic principles and common pitfalls. Nephrol Dial Transplant England. 2010;25:1388–93.

    Article  Google Scholar 

  78. Eng J. Sample size estimation: how many individuals should be studied? Radiology United States. 2003;227:309–13.

    Google Scholar 

  79. Krzywinski M, Altman N. Points of significance: Power and sample size. Nat Meth [Internet]. Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.; 2013;10:1139–40. Available from: https://doi.org/10.1038/nmeth.2738.

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Hygiene, Social-Preventive Medicine and Medical Statistics, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Konstantinos I. Bougioukas & Anna-Bettina Haidich

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  1. Konstantinos I. Bougioukas
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  2. Anna-Bettina Haidich
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Correspondence to Anna-Bettina Haidich .

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Editors and Affiliations

  1. Georgetown University and VA Medical Center, Washington, DC, USA

    Vasilios Papademetriou

  2. Fourth Internal Medicine Department, Evangelismos State General Hospital, Athens, Greece

    Emmanuel A. Andreadis

  3. Fourth Internal Medicine Department, Evangelismos State General Hospital, Athens, Greece

    Charalampia Geladari

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Bougioukas, K.I., Haidich, AB. (2019). Medical Biostatistics: Basic Concepts. In: Papademetriou, V., Andreadis, E., Geladari, C. (eds) Management of Hypertension. Springer, Cham. https://doi.org/10.1007/978-3-319-92946-0_2

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  • DOI: https://doi.org/10.1007/978-3-319-92946-0_2

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