Skip to main content
Log in

Systematische Fehler in klinischen Studien

Eine Übersicht

Systematic errors in clinical studies

A comprehensive survey

  • Übersichten
  • Published:
Der Ophthalmologe Aims and scope Submit manuscript

Zusammenfassung

Die systematischen Fehler stellen eine ernste Herausforderung für die Qualität der klinischen Forschung dar. Sie können dazu führen, dass selbst sonst methodisch anspruchsvolle Untersuchungen zu Ergebnissen führen, die von den wahren Werten abweichen. In der forschenden Medizin werden die systematischen Fehler nach ihrer Zugehörigkeit zu den zeitlich aufeinanderfolgenden Abschnitten einer Studie in 6 Gruppen eingeteilt. Man unterscheidet dabei die Phasen der literarischen Vorarbeiten, der Gestaltung der Studie und Auswahl der Teilnehmer, der Durchführung und Dokumentation, der Analyse, der Interpretation und schließlich der Veröffentlichung der Ergebnisse. Die für diagnostische und Interventionsstudien wichtigsten Verzerrungen entstehen durch klinische Vorinformationen, gezielte Gestaltung der Studie, zweckbestimmte Auswahl der Teilnehmer, Vergleich mit historischen Kollektiven, Folgen der Vorverlegung des Zeitpunkts der Diagnose und die überproportional große Häufigkeit von Erkrankungsformen, die einen langsamen Verlauf nehmen. Vielfach trifft man bei der Prüfung der Messwerte auf ein Mosaik von systematischen Fehlern, unter denen einer mehr oder weniger dominiert. Die meisten Verzerrungen lassen sich auch durch große Sorgfalt bei der Planung und Durchführung der Studie nicht beseitigen, sondern nur verringern. Es ist unverzichtbar, jeden erkannten systematischen Fehler als mögliche Ursache oder Teilursache einer bei der Untersuchung beobachteten Verknüpfung zu analysieren. Die Auseinandersetzung mit den systematischen Fehlern ist ein substanzielles Element des Diskussionsteils jedes Forschungsberichts und ein Eckpfeiler für die Beurteilung seiner wissenschaftlichen Qualität.

Abstract

Systematic errors and related phenomena represent an intrinsic challenge to the quality of clinical research. As a consequence even otherwise methodologically demanding studies may produce results that systematically differ from the true values. Systematic errors relating to investigative medicine are divided into six groups according to their affiliation with the consecutive chronological sections of the study. Bias can occur in preliminary literature research in the field, specifying the study design and selecting the study sample, measuring exposure and outcome, analyzing the data, interpreting the analyses and publishing the results. The most important systematic errors that concern diagnostic and interventional studies are created by access to the data of previous tests, calculated study design, preselection of the participants, comparison with non-contemporaneous controls, antedating the time of diagnosis and overdiagnosis of slowly progressive forms of diseases examined. Checking the measured values often leads to a mosaic of several biases with one being more or less dominant. Even by exercising due care in the preparation and performance of the study, the majority of distortions cannot be eliminated but only diminished. It is essential to consider each detected bias as a potential full or partial argument in support of an observed correlation. The control of systematic errors and related phenomena is both a significant element of the discussion of the study report and a key element for assessment of its scientific value.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Literatur

  1. Van der Aalst M, van Iersel CA, van Klaveren RJ (2012) Generalisability of the results of the Dutch-Belgian randomised controlled lung cancer CT screening trial (NELSON): does self-selection play a role? Lung Cancer 77:51–57

    Article  PubMed  Google Scholar 

  2. Aberegg SK, Haponik EF, Terry PB (2005) Omission bias and decision making in pulmonary and critical care medicine. Chest 128:1497–1505

    Article  PubMed  Google Scholar 

  3. Adams HJ, Kwee TC, Nievelstein RA (2013) Influence of imperfect reference standard bias on the diagnostic performance of MRI in the detection of lymphomatous bone marrow involvement. Clin Radiol 68:750–751

    Article  CAS  PubMed  Google Scholar 

  4. Austin MA, Criqui MH, Barrett-Connor E, Holdbrook MJ (1981) The effect of response bias on the odds ratio. Am J Epidemiol 114:137–143

    Article  CAS  PubMed  Google Scholar 

  5. Backer MW, Lee KS, Blankenbaker DG, Kijowski R, Keene JS (2014) Correlation of ultrasound-guided corticosteroid injection of the quadratus femoris with MRI findings of ischiofemoral impingement. AJR Am J Roentgenol 203:589–593

    Article  PubMed  Google Scholar 

  6. Baltzer PAT, Dietzel M (2013) Breast lesions: diagnosis by using proton MR spectroscopy at 1.5 and 3.0 T – systematic review and meta-analysis. Radiology 267:735–746

    Article  PubMed  Google Scholar 

  7. Baron J (2008) Thinking and deciding, 4. Aufl. Cambridge University Press, Cambridge, S 157 (171, 177, 406–409, 507–515)

    Google Scholar 

  8. Bashir MR, Sirlin CB, Reeder SB (2015) On confirmation bias in imaging research. J Magn Reson Imaging 41:1163–1164

    Article  PubMed  Google Scholar 

  9. Begg CB, McNeil BJ (1988) Assessment of radiologic tests: control of bias and other design considerations. Radiology 167:565–569

    Article  CAS  PubMed  Google Scholar 

  10. Beggs AD, Dilworth MP, Powell SL, Atherton H, Griffiths EA (2014) A systematic review of transarterial embolization versus emergency surgery in treatment of major nonvariceal upper gastrointestinal bleeding. Clin Exp Gastroenterol 7:93–104

    Article  PubMed  PubMed Central  Google Scholar 

  11. Berry DA (2014) Failure of researchers, reviewers, editors, and the media to understand flaws in cancer screening studies: application to an article in Cancer. Cancer 120:2784–2791

    Article  PubMed  Google Scholar 

  12. Bhatt DL, Kandzari DE, O’Neill WW et al (2014) A controlled trial of renal denervation for resistant hypertension. N Engl J Med 370:1393–1401

    Article  CAS  PubMed  Google Scholar 

  13. Brealey S, Scally AJ (2001) Bias in plain film reading performance studies. BMJ 74:307–316

    CAS  Google Scholar 

  14. Callaham ML, Wears RL, Weber EJ, Barton C, Young G (1998) Positive-outcome bias and other limitations in the outcome of research abstracts submitted to a scientific meeting. JAMA 280:254–257 (Erratum in: JAMA 280:1232)

    Article  CAS  PubMed  Google Scholar 

  15. Cecil MP, Kosinski AS, Jones MT et al (1996) The importance of work-up (verification) bias correction in assessing the accuracy of SPECT-thallium-201 testing for the diagnosis of coronary artery disease. J Clin Epidemiol 49:735–742

    Article  CAS  PubMed  Google Scholar 

  16. Chalmers I (1990) Underreporting research is scientific misconduct. JAMA 263:1405–1408

    Article  CAS  PubMed  Google Scholar 

  17. Champion GA, Piccirillo JF (2004) The impact of computed tomography on pretherapeutic staging in patients with laryngeal cancer: demonstration of the Will Rogers’ phenomenon. Head Neck 26:972–976

    Article  PubMed  Google Scholar 

  18. Coughlin SS (1990) Recall bias in epidemiologic studies. J Clin Epidemiol 43:87–91

    Article  CAS  PubMed  Google Scholar 

  19. Deeks JJ, Macaskill P, Irwig L (2005) The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol 58:882–893

    Article  PubMed  Google Scholar 

  20. Delgado-Rodriguez M, Llorca J (2004) Continuing professional education: bias. J Epidemiol Community Health 58:635–641

    Article  PubMed  PubMed Central  Google Scholar 

  21. Denson AC, Mahipal A (2014) Participation of the elderly population in clinical trials: barriers and solutions. Cancer Control 21:209–214

    PubMed  Google Scholar 

  22. Dismuke CE (2005) Underreporting of computed tomography and magnetic resonance imaging procedures in inpatient claims data. Med Care 43:713–717

    Article  PubMed  Google Scholar 

  23. Egglin TK, Feinstein AR (1996) Context bias. A problem in diagnostic radiology. JAMA 276:1752–1755

    Article  CAS  PubMed  Google Scholar 

  24. Emerson GB, Warme WJ, Wolf FM, Heckman JD, Brand RA, Leopold SS (2010) Testing for the presence of positive-outcome bias in peer review: a randomised controlled trial. Arch Intern Med 170:1934–1939

    Article  PubMed  Google Scholar 

  25. Erly WK, Tran M, Dillon RC, Krupinski E (2010) Impact of hindsight bias on interpretation of nonenhanced computed tomographic head scans for acute stroke. J Comput Assist Tomogr 34:229–232

    Article  PubMed  Google Scholar 

  26. Fox AJ, White GC (1976) Bladder cancer in rubber workers. Do screening and doctor’s awareness distort the statistics? Lancet 307:1009–1011

    Article  Google Scholar 

  27. Golder WA (2009) Das Will-Rogers-Phänomen und seine Bedeutung für die bildgebende Diagnostik. Radiologe 49:348–354

    Article  CAS  PubMed  Google Scholar 

  28. Grimes DA, Schulz KF (2002) Bias and causal associations in observational research. Lancet 359:248–252

    Article  PubMed  Google Scholar 

  29. Herliczek TW, Swenson DW, Mayo-Smith WW (2013) Utility of MRI after inconclusive ultrasound in pediatric patients with suspected appendicitis: retrospective review of 60 consecutive patients. AJR Am J Roentgenol 200:969–973

    Article  PubMed  Google Scholar 

  30. Higgins JPT, Altman DG, Gøtzsche PC, Cochrane Bias Methods Group, Cochrane Statistical Methods Group et al (2011) The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 343:d5928

    Article  PubMed  PubMed Central  Google Scholar 

  31. Hill G, Connelly J, Hébert R, Lindsay J, Millar W (2003) Neyman’s bias re-visited. J Clin Epidemiol 56:293–296

    Article  PubMed  Google Scholar 

  32. Howitz RI, McFarlane MJ, Brennan TA, Feinstein A (1985) The role of susceptibility bias in epidemiologic research. Arch Intern Med 145:909–912

    Article  Google Scholar 

  33. Hubbard A, Jamshidian F, Jewell N (2012) Adjusting for perception and unmasking effects in longitudinal clinical trials. Int J Biostat 8:7

    Article  PubMed  Google Scholar 

  34. Jha S (2015) Thinking beyond the treatment effect in screening for lung cancer. Acad Radiol 22:983–984

    Article  PubMed  Google Scholar 

  35. Kaptchuk TJ (2003) Effect of interpretive bias on research evidence. BMJ 326:1453–1455

    Article  PubMed  PubMed Central  Google Scholar 

  36. Kennedy MT, Ong JC, Mitra A, Harty JA, Reidy D, Dolan M (2013) The use of weekly departmental review of all orthopaedic intra-operative radiographs in order to improve quality, due do standardized peer expectations and the „Hawthorne effect“. Surgeon 11:10–13

    Article  PubMed  Google Scholar 

  37. Kent DL, Haynor DR, Longstreth WT Jr, Larson EB (1994) The clinical efficacy of magnetic resonance imaging in neuroimaging. Ann Intern Med 120:856–871

    Article  CAS  PubMed  Google Scholar 

  38. Kim HH, Richardson D, Loomis D, Van Tongeren M, Burstyn I (2011) Bias in the estimation of exposure effects with individual- or group-based exposure assessment. J Expo Sci Environ Epidemiol 21:212–221

    Article  PubMed  Google Scholar 

  39. Kleist P (2006) Vier Effekte, Phänomene und Paradoxe in der Medizin. Schweiz Med Forum 6:1023–1027

    Google Scholar 

  40. Kojima S, Zhou B, Teramukam S et al (2007) Cancer screening of healthy volunteers using whole-body 18F-FDG-PET scans: The Nishidai clinic study. Eur J Cancer 43:1842–1848

    Article  PubMed  Google Scholar 

  41. Kok P, Pitman AG, Cawson NJ et al (2010) Diagnostic accuracy of mammography readers and their memory performance have no correlation with each other. J Med Imaging Radiat Oncol 54:315–324

    Article  CAS  PubMed  Google Scholar 

  42. Kramer MS, Boivin J‑F (1987) Toward an „unconfounded“ classification of epidemiologic research design. J Chronic Dis 40:683–688

    Article  CAS  PubMed  Google Scholar 

  43. Lader EW, Cannon CP, Ohman EM et al (2004) The clinician as investigator: participating in clinical trials in the practice setting. Circulation 109:2672–2679

    Article  PubMed  Google Scholar 

  44. Marquering HA, Majoie CB, Smagge L et al (2011) The relation of carotid calcium volume with carotid artery stenosis in symptomatic patients. Am J Neuroradiol 32:1182–1187

    Article  CAS  PubMed  Google Scholar 

  45. Mazzone PJ, Mekhail T (2007) Lung cancer screening. Curr Oncol Rep 9:265–274

    Article  PubMed  Google Scholar 

  46. Moroz V, Wilson JS, Kearns P, Whealey K (2014) Comparison of anticipated and actual control group outcomes in randomised trials in paediatric oncology provides evidence that historically controlled studies are biased in favour of the novel treatment. Trials 15:481

    Article  PubMed  PubMed Central  Google Scholar 

  47. Mullen MT, Cucchiara BL (2011) Redefinition of transient ischemic attack improves prognosis of transient ischemic attack and ischemic stroke: an example of the will rogers phenomenon. Stroke 42:3612–3613

    Article  CAS  PubMed  Google Scholar 

  48. Murphy EA (1997) The logic of medicine, 2. Aufl. Johns Hopkins University Press, Baltimore, S 345–370

    Google Scholar 

  49. Nio CY, De Vries AH, Stoker J (2007) Perceptive errors in CT colonography. Abdom Imaging 32:556–570

    Article  CAS  PubMed  Google Scholar 

  50. Njor SH, Olsen AH, Blichert-Toft M, Schwartz W, Vejborg I, Lynge E (2013) Overdiagnosis in screening mammography in Denmark: population based cohort study. BMJ 346:f1064. doi:10.1136/bmj.f.1064

    Article  PubMed  PubMed Central  Google Scholar 

  51. Obuchowski NA (2003) Special topics III: bias. Radiology 229:617–621

    Article  PubMed  Google Scholar 

  52. Petscavage JM, Richardson ML, Carr RB (2011) Verification bias an underrecognized source of error in assessing the efficacy of medical imaging. Acad Radiol 18:343–346

    Article  PubMed  Google Scholar 

  53. Pua U, Tan CH, Ho HH, Tan JK, Ong PJ (2014) Revisiting renovascular imaging for renal sympathetic denervation: current techniques and applications. Eur Radiol 25:444–453

    Article  PubMed  Google Scholar 

  54. Reid MC, Lachs MS, Feinstein AR (1995) Use of methodological standards in diagnostic test research. Getting better but still not good. JAMA 274:645–651

    Article  CAS  PubMed  Google Scholar 

  55. Resch KI, Ernst E, Garrow J (2000) A randomized controlled study of reviewer bias against an unconventional therapy. J R Soc Med 93:164–167

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Richardson ML, Petscavage JM (2011) Verification bias: an under-recognized source of error in assessing the efficacy of MRI in the meniscii. Acad Radiol 18:1376–1381

    Article  PubMed  Google Scholar 

  57. Sackett DL (1979) Bias in analytic research. J Chronic Dis 32:51–63

    Article  CAS  PubMed  Google Scholar 

  58. Sica GT (2006) Bias in research studies. Radiology 238:780–789

    Article  PubMed  Google Scholar 

  59. Soda H, Oka M, Tomita H, Nagashima S, Soda M, Kohno S (1999) Length and lead time biases in radiologic screening for lung cancer. Respiration 66:511–517

    Article  CAS  PubMed  Google Scholar 

  60. Soh BP, Lee W, Kench PL et al (2012) Assessing reader performance in radiology, an imperfect science: lessons from breast screening. Clin Radiol 67:623–628

    Article  CAS  PubMed  Google Scholar 

  61. Sterne JA, Hernán MA, Reedyes BC et al (2016) ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ 355:i4919

    Article  PubMed  PubMed Central  Google Scholar 

  62. Sun H, Xue HD, Wang YN et al (2013) Dual-source dual-energy computed tomography angiography for active gastrointestinal bleeding: a preliminary study. Clin Radiol 68:139–147

    Article  CAS  PubMed  Google Scholar 

  63. Tabar L, Duffy SW, Yen MF et al (2002) All-cause mortality among breast cancer patients in a screening trial: support for breast cancer mortality as an end point. J Med Screen 9:159–162

    Article  CAS  PubMed  Google Scholar 

  64. Torgerson DJ (2001) Contamination in trials: is cluster randomisation the answer? BMJ 322:355–357

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Vestbo J, Anderson JA, Calverley PM et al (2011) Bias due to withdrawal in long-term randomised trials in COPD: evidence from the TORCH study. Clin Respir J 5:44–49

    Article  PubMed  Google Scholar 

  66. Walsh MC, Trentham-Dietz A, Gangnon RE, Nieto FJ, Newcomb PA, Palta M (2012) Selection bias in population-based cancer case-control studies due to incomplete sampling frame coverage. Cancer Epidemiol Biomarkers Prev 21:881–886

    Article  PubMed  PubMed Central  Google Scholar 

  67. Whiting PF, Rutjes AW, Westwood ME et al (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155:529–536

    Article  PubMed  Google Scholar 

  68. Whiting P, Savokič J, Higgins JPT et al (2016) ROBIS: A new tool to assess risk of bias in systematic reviews was developed. J Clin Epidemiol 69:225–234

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to W. A. Golder.

Ethics declarations

Interessenkonflikt

W.A. Golder gibt an, dass kein Interessenkonflikt besteht.

Dieser Beitrag beinhaltet keine vom Autor durchgeführten Studien an Menschen oder Tieren.

Additional information

Dieser Beitrag ist eine Kurzfassung des erstpublizierten Beitrags Golder, W.A. Z Rheumatol (2017) Systematische Fehler in klinischen Studien. Eine Übersicht. doi:10.1007/s00393-016-0253-5

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Golder, W.A. Systematische Fehler in klinischen Studien. Ophthalmologe 114, 215–223 (2017). https://doi.org/10.1007/s00347-017-0471-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00347-017-0471-5

Schlüsselwörter

Keywords

Navigation