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MCQs in evidence based practice

multiple choice questions in evidence-base practice

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MCQs in evidence based practice

  1. 1. MCQ in evidence-based practice Samir Haffar M.D.
  2. 2. Definition of EBP Evidence-based practice includes which of the following: A. Best available evidence B. Individual clinical experience C. Patient values D. All of the above
  3. 3. Definition of EBP Evidence-based practice includes which of the following: A. Best available evidence B. Individual clinical experience C. Patient values D. All of the above
  4. 4. Five steps of EBP What is the first step in applying EBM concepts to answer a clinical question? A. Ask the question B. Acquire the evidence C. Appraise the evidence D. Apply the evidence C. Assess the whole process
  5. 5. Five steps of EBP What is the first step in applying EBM concepts to answer a clinical question? A. Ask the question B. Acquire the evidence C. Appraise the evidence D. Apply the evidence C. Assess the whole process The five As
  6. 6. Types of clinical studies What is the best design to study the prevalence of a disease? A- Cross-sectional study B- Case-control study C- Cohort study D- RCT
  7. 7. Types of clinical studies What is the best design to study the prevalence of a disease? A- Cross-sectional study B- Case-control study C- Cohort study D- RCT
  8. 8. Types of clinical studies What is the best design to study the incidence of a disease? A- Cross-sectional study B- Case-control study C- Cohort study D- RCT
  9. 9. Types of clinical studies What is the best design to study the incidence of a disease? A- Cross-sectional study B- Case-control study C- Cohort study D- RCT
  10. 10. Types of clinical studies What is the best design to study the efficacy of an intervention? A- Cross-sectional study B- Case-control study C- Cohort study D- RCT
  11. 11. Types of clinical studies What is the best design to study the efficacy of an intervention? A- Cross-sectional study B- Case-control study C- Cohort study D- RCT
  12. 12. Types of clinical studies Which is the best design to study the etiology of a disease? A. Cross-sectional study B. Case-control study C. Cohort study D. RCT
  13. 13. Types of clinical studies Which is the best design to study the etiology of a disease? A. Cross-sectional study B. Case-control study C. Cohort study D. RCT
  14. 14. Case-control & cohort study etiology of a disease Cohort study better than case-control study (less bias)
  15. 15. Types of clinical studies Which is the best trial design to study the prognosis of a disease? A. Cross-sectional study B. Case-control study C. Cohort study D. RCT
  16. 16. Types of clinical studies Which is the best trial design to study the prognosis of a disease? A. Cross-sectional study B. Case-control study C. Cohort study D. RCT
  17. 17. Types of clinical studies • Case report/case series • Ecological study • Cross-sectional study • Case control study • Cohort study • Randomized clinical trial Primary research • Systematic review • Meta-analysis Secondary research
  18. 18. Question type & study design Study DesignQuestion Intervention RCT Incidence & prognosis Cohort study Prevalence Cross-sectional study Etiology & risk factors Cohort or case-control Diagnosis Comparison w gold standard In each case, SR of all available studies better than individual study
  19. 19. Cross-sectional study design Prevalence study At one point of time eg: prevalence of coronary heart disease in smokers
  20. 20. Case-control study design Investigate etiology or outcome of disease
  21. 21. Cohort study Investigate etiology or outcome of disease
  22. 22. Exposure Outcome Cohort Cross-sectional Time is key Case-control
  23. 23. The cohort study is the gold-standard of analytical epidemiology
  24. 24. Diagnostic study Which is the best trial design to study the accuracy of a diagnostic test? A. Cross-sectional study B. Case-control study C. Cohort study D. Comparison of diagnostic test with gold standard test
  25. 25. Diagnostic study Which is the best trial design to study the accuracy of a diagnostic test? A. Cross-sectional study B. Case-control study C. Cohort study D. Comparison of diagnostic test with gold standard test
  26. 26. Structure for a study of diagnostic test Suspected target condition Guyatt G et all. Users’ guides to medical literature: manual for EBP. McGraw-Hill, New York, USA, 2nd edition, 2008. Accuracy of diagnostic test compared to gold standard Gold standard test Positive Negative Diagnostic test Positive Negative
  27. 27. Accuracy of a diagnostic test • Dichotomous test (only 2 results) Sensibility (Sn) & Specificity (Sp) Positive Predictive Value (PPV) Negative Predictive Value (NPV) Likelihood Ratios + & – (LR) Diagnostic Odds Ratio (OR) • Multilevel test (> 2 results) Receiver Operating Characteristic (ROC) Newman TB & Kohn MA. Evidence-based diagnosis. Cambridge University Press, Cambridge, UK, 1st edition, 2009. with 95%CI
  28. 28. Accuracy of a diagnostic study A study of diagnostic accuracy of arterial blood gas for diagnosis of pulmonary embolus (PE) included 212 patients with suspected PE, 49 of whom were subsequently determined to have PE. Of the 49 patients with PE, 41 had abnormal alveolar-arterial oxygen gradient (A-a)DO2. Of the 163 patients without PE, 118 had abnormal (A-a)DO2. What is the sensitivity, specificity, PPV, NPV, LR positive and negative of (A-a) DO2 for the diagnosis of PE?
  29. 29. Arterial blood gas for diagnosis of pulmonary embolus Construction of 2 X 2 table Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive Negative Column totals 49 patients had PE, 41 of them had abnormal (A-a) DO2 163 patients without PE, 118 of them had abnormal (A-a) DO2
  30. 30. Arterial blood gas for diagnosis of pulmonary embolus Construction of 2 X 2 table Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive Negative Column totals 49 49 patients had PE, 41 of them had abnormal (A-a) DO2 163 patients without PE, 118 of them had abnormal (A-a) DO2
  31. 31. Arterial blood gas for diagnosis of pulmonary embolus Construction of 2 X 2 table Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 Negative Column totals 49 49 patients had PE, 41 of them had abnormal (A-a) DO2 163 patients without PE, 118 of them had abnormal (A-a) DO2
  32. 32. Arterial blood gas for diagnosis of pulmonary embolus Construction of 2 X 2 table Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 Negative 8 Column totals 49 49 patients had PE, 41 of them had abnormal (A-a) DO2 163 patients without PE, 118 of them had abnormal (A-a) DO2
  33. 33. Arterial blood gas for diagnosis of pulmonary embolus Construction of 2 X 2 table Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 Negative 8 Column totals 49 163 49 patients had PE, 41 of them had abnormal (A-a) DO2 163 patients without PE, 118 of them had abnormal (A-a) DO2
  34. 34. Arterial blood gas for diagnosis of pulmonary embolus Construction of 2 X 2 table Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 118 Negative 8 Column totals 49 163 49 patients had PE, 41 of them had abnormal (A-a) DO2 163 patients without PE, 118 of them had abnormal (A-a) DO2
  35. 35. Arterial blood gas for diagnosis of pulmonary embolus Construction of 2 X 2 table Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 118 Negative 8 45 Column totals 49 163 49 patients had PE, 41 of them had abnormal (A-a) DO2 163 patients without PE, 118 of them had abnormal (A-a) DO2
  36. 36. Arterial blood gas for diagnosis of pulmonary embolus Construction of 2 X 2 table Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 118 159 Negative 8 45 53 Column totals 49 163 212 49 patients had PE, 41 of them had abnormal (A-a) DO2 163 patients without PE, 118 of them had abnormal (A-a) DO2
  37. 37. Arterial blood gas for diagnosis of pulmonary embolus Sensibility Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 118 159 Negative 8 45 53 Column totals 49 163 212 = Denominator = Column totals Sensibility 41 49 = 0.84
  38. 38. Arterial blood gas for diagnosis of pulmonary embolus Specificity Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 118 159 Negative 8 45 53 Column totals 49 163 212 = Denominator = Column totals Specificity 45 163 = 0.28
  39. 39. Arterial blood gas for diagnosis of pulmonary embolus Positive predictive value (PPV) Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 118 159 Negative 8 45 53 Column totals 49 163 212 = Denominator = Row totals PPV 41 159 = 0.26
  40. 40. Arterial blood gas for diagnosis of pulmonary embolus Negative predictive value (NPV) Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 118 159 Negative 8 45 53 Column totals 49 163 212 Denominator = Row totals NPV 45 53 = = 0.85
  41. 41. Arterial blood gas for diagnosis of pulmonary embolus Prevalence Gold standard test CECT Row totals Disease present Disease absent Diagnostic test Arterial blood gas Positive 41 118 159 Negative 8 45 53 Column totals 49 163 212 Prevalence = 0.23= 49 212
  42. 42. LR for a positive test LR + = 0.84 / (1 – 0.28 ) = 1.17 LR + = Sensitivity / (1 – Specificity) Corresponds to clinically “ruling in disease” Probability that the patient has true positive, rather than false positive test
  43. 43. LR for a negative test LR – = (1 – 0.84 ) / 0.28 = 0.57 LR – = (1 – Sensitivity ) / specificity Corresponds to clinically “ruling out disease” Probability that the patient has true negative rather than false negative test
  44. 44. Diagnostic study The ideal diagnostic test has a: A. High sensitivity and high specificity B. High sensitivity and low specificity C. Low sensitivity and high specificity D. Low sensitivity and low specificity
  45. 45. Diagnostic study The ideal diagnostic test has a: A. High sensitivity and high specificity B. High sensitivity and low specificity C. Low sensitivity and high specificity D. Low sensitivity and low specificity
  46. 46. ? ? In a diagnostic test if: Pretest probability: 30% Likelihood ratio positive (LR+): 9 What is the post-test probability? ? ? Computing post-test probability
  47. 47. Fagan nomogram Pre-test probability Likelihood ratio Post-test probability
  48. 48. Fagan nomogram Pre-test probability Likelihood ratio Post-test probability Post-test probability 78%
  49. 49. In a diagnostic test if: Pretest probability: 30% Likelihood ratio negative (LR– ): 0.1 What is the post-test probability? Fagan nomogram Pre-test probability Likelihood ratio Post-test probability Computing post-test probability
  50. 50. Fagan nomogram Pre-test probability Likelihood ratio Post-test probability Post-test probability 4%
  51. 51. Randomized controlled trials A recent RCT found that 29% of diabetics with coronary heart disease treated with pravastatin suffered a recurrent coronary event during 5 years of follow-up, while 37% of the placebo group suffered recurrent coronary events. • What is the relative risk for recurrent events? • What is the absolute risk reduction for recurrent events? • What is the number needed to treat to prevent one recurrent event?
  52. 52. RCT/ Relative risk reduction A recent RCT found that 29% of diabetics with coronary heart disease treated with pravastatin suffered a recurrent coronary event during 5 years of follow-up, while 37% of the placebo group suffered recurrent coronary events. Relative risk reduction (RRR) Risk in treatment group / risk in control group (0.37 – 0.29) / 0.37 = 22%
  53. 53. RCT/ Absolute risk reduction A recent RCT found that 29% of diabetics with coronary heart disease treated with pravastatin suffered a recurrent coronary event during 5 years of follow-up, while 37% of the placebo group suffered recurrent coronary events. Absolute risk reduction (ARR) Risk in control group – Risk in treatment group 37% – 29% = 8%
  54. 54. RCT/ Number needed to treat A recent RCT found that 29% of diabetics with coronary heart disease treated with pravastatin suffered a recurrent coronary event during 5 years of follow-up, while 37% of the placebo group suffered recurrent coronary events. Number needed to treat (NNT) 1 / Absolute risk reduction 1 / 0.08 = 12.5
  55. 55. Systematic review & meta-analysis All the followings regarding systematic review and meta-analysis are true EXCEPT: A. a systematic review may include a meta-analysis B. a systematic review may not include a meta-analysis B. a meta-analysis may not include a systematic review D. a systematic review should always include a meta-analysis
  56. 56. Systematic review & meta-analysis All the followings regarding systematic review and meta-analysis are true EXCEPT: A. a systematic review may include a meta-analysis B. a systematic review may not include a meta-analysis B. a meta-analysis may not include a systematic review D. a systematic review should always include a meta-analysis
  57. 57. Systematic review & meta-analysis Systematic reviews (SR) Meta-analyses (MA) MA may, or may not, include a SR Egger M et all. Systematic reviews in health care: Meta-analysis in context. BMJ Publishing Group, London, 2nd edition, 2001.
  58. 58. Systematic review & meta-analysis When data are combined from smaller studies into a larger sample size, which can then be statistically evaluated in a more robust fashion than the smaller samples, the following term is applied: A. Prospective study B. Case-control study C. Cohort study D. Double-blind clinical trial E. Meta-analysis
  59. 59. Systematic review & meta-analysis When data are combined from smaller studies into a larger sample size, which can then be statistically evaluated in a more robust fashion than the smaller samples, the following term is applied: A. Prospective study B. Case-control study C. Cohort study D. Double-blind clinical trial E. Meta-analysis
  60. 60. Forest plot in meta-analysis The diamond of a meta-analysis of RCTs reveals these results: Odds ratio: 1.75 – 95% confidence interval: 1.69 , 1.79 • Are the results statistically significant? A- Yes B- No C- cannot tell • Are the results precise? A- Yes B- No C- cannot tell • Is there a publication bias? A- Yes B- No C- cannot tell
  61. 61. Forest plot in meta-analysis The diamond of a meta-analysis of RCTs reveals these results: Odds ratio: 1.75 – 95% confidence interval: 1.69 , 1.79 • Are the results statistically significant? A- Yes B- No C- cannot tell • Are the results precise? A- Yes B- No C- cannot tell • Is there a publication bias? A- Yes B- No C- cannot tell
  62. 62. Clinical scenario -1 • You have a 60-year-old patient with acute biliary pancreatitis and non-infected pancreatic necrosis on CECT. You wonder if prophylactic antibiotics prevents infection of non-infected pancreatic necrosis & decreases mortality. • You identify a meta-analysis of RCTs evaluating the effect of prophylactic antibiotics to prevent infected necrosis and decrease mortality. Bai Yu & al. Am J Gastroenterol 2008 ; 103 : 104 – 110.
  63. 63. Antibiotic prophylaxis & pancreatic necrosis Bai Y et al. Am J Gastroenterol 2008 ; 103 : 104 – 110. Forest plot Is the result statistically significant? Is the result precise? Is there heterogeneity?
  64. 64. • Diamond cross horizontal line Not statistically significant • Wide confidence interval Low precision • I2 = 23.2% Low level of heterogeneity Antibiotic prophylaxis & pancreatic necrosis OR: 0.81 – 95% CI: 0.54-1.22 – I2: 23.2% Bai Y et al. Am J Gastroenterol 2008 ; 103 : 104 – 110.
  65. 65. Bai Y et al. Am J Gastroenterol 2008 ; 103 : 104 – 110. Antibiotic prophylaxis & pancreatic necrosis Funnel plot/Publication bias Is there a publication bias?
  66. 66. Is there a publication bias? Funnel plot did not show significant asymmetry, but the number of included studies is low (7 studies)
  67. 67. Clinical scenario -2 • You are consulted regarding the peri-operative management of a 66- year-old man undergoing hip replacement. He is a smoker and has a history of type 2 diabetes & hypertension. Because he has multiple cardiovascular risk factors, you consider using perioperative β-blockers to reduce the risk of postoperative cardiovascular complications and death. • You identify a recently published systematic review and meta- analysis evaluating the effect of perioperative β-blockers on nonfatal myocardial infarction, stroke and death. Bouri S et al. Heart. 2014;100(6):456-464
  68. 68. Death in patients receiving perioperative β-blockers Bouri S et al. Heart. 2014;100(6):456-464
  69. 69. Is the result statistically significant? Is the result precise? Is there heterogeneity?
  70. 70. Is the result statistically significant? Diamond doesn’t cross line of no effect: statistically significant Diamond cross line of no effect: not statistically significant Look at the diamond with the point estimate & 95% CI
  71. 71. The diamond Perera R, Heneghan C, Badenoch D. Statistics Toolkit. Blackwell Publishing Ltd, Oxford, 1st edition, 2008. Shows combined point estimate (RR or OR) with 95% CI
  72. 72. Death in patients receiving perioperative β-blockers Bouri S et al. Heart. 2014;100(6):456-464
  73. 73. Is the result precise? Look at the diamond with the point estimate & 95% CI Narrow confidence interval: High precision Wide confidence interval: Low precision
  74. 74. Death in patients receiving perioperative β-blockers Bouri S et al. Heart. 2014;100(6):456-464
  75. 75. Statistical significance & CI (a) Statistically significant, low precision (b) Statistically significant, high precision (c) Not statistically significant, low precision (d) Not statistically significant, high precision Glasziou P et al. Evidence based practice workbook. Blackwell, 2nd edition, 2007.
  76. 76. Influence of sample size on CI precision Width of CI (precision of the estimate) decreases with increasing sample size Peat JK, et al. Health science research. Allen & Unwin, Australia, 1st ed, 2001.
  77. 77. Is there heterogeneity? Visual evidence of heterogeneity in the forest plot Simon SD. Statistical evidence in medical trials: What do the data really tell us? Oxford University Press, Oxford, 1st edition, 2006 Qualitative assessment Quantitative assessment I-squared ˂ 25% Low heterogeneity I-squared 25 – 50% Moderate level of heterogeneity I-squared ˃ 50% High level of heterogeneity
  78. 78. Heterogeneity Do the pieces fit together? Simon SD. Statistical evidence in medical trials: What do the data really tell us? Oxford University Press, Oxford, 1st edition, 2006
  79. 79. Heterogeneity Problem of combining information Mixing apples & oranges
  80. 80. Death in patients receiving perioperative β-blockers Bouri S et al. Heart. 2014;100(6):456-464
  81. 81. • Not statistically significant • Low precision • Moderate level of heterogeneity Death in patients receiving perioperative β-blockers Bouri S et al. Heart. 2014;100(6):456-464 OR: 0.94 – 95% CI: 0.63-1.40 – I2: 30%
  82. 82. Death in patients receiving perioperative β-blockers Funnel plot/Publication bias Bouri S et al. Heart. 2014;100(6):456-464 Is there a publication bias?
  83. 83. Is there a publication bias? “Funnel plot did not show significant asymmetry, but this cannot definitively exclude publication bias” Number of included studies is low (˂ 30 studies)
  84. 84. Funnel plot
  85. 85. Funnel plot
  86. 86. Clinical scenario -3 • HEV seroprevalence (anti-HEV IgG) in patients on maintenance hemodialysis (HD) ranges from 0% to 44%. Chronic hepatits E is encountered in immunocompromized patients. You wonder if it is worthy to test your HD patients for HEV markers especially for those who are planned to receive renal transplantation. • You identify a recently published systematic review and meta-analysis evaluating the seroprevalence of HEV in HD patients. Haffar et al. Aliment Pharmacol Ther 2017;46:790-799.
  87. 87. Haffar et al. Aliment Pharmacol Ther 2017;46:790-799.
  88. 88. Is the result statistically significant? Is the result precise? Is there heterogeneity?
  89. 89. • Statistically significant • Low precision • High level of heterogeneity HEV seroprevalence in hemodialysis patients OR: 2.47 – 95% CI: 1.79-3.40 – I2: 75.2% Haffar et al. Aliment Pharmacol Ther 2017;46:790-799.
  90. 90. How to address heterogeneity among studies?
  91. 91. How to address heterogeneity among studies? Conducting sensitivity (subgroup) analyses
  92. 92. OR: odds ratio RD: risk difference Haffar et al. Aliment Pharmacol Ther 2017;46:790-799. HEV seroprevalence in hemodialysis patients Sensitivity (subgroup) analyses
  93. 93. OR: odds ratio RD: risk difference Haffar et al. Aliment Pharmacol Ther 2017;46:790-799. HEV seroprevalence in hemodialysis patients Subgroup (sensitivity) analyses
  94. 94. OR: odds ratio RD: risk difference Haffar et al. Aliment Pharmacol Ther 2017;46:790-799. HEV seroprevalence in hemodialysis patients Subgroup (sensitivity) analyses
  95. 95. OR: odds ratio RD: risk difference Haffar et al. Aliment Pharmacol Ther 2017;46:790-799. HEV seroprevalence in hemodialysis patients Subgroup (sensitivity) analyses
  96. 96. OR: odds ratio RD: risk difference Haffar et al. Aliment Pharmacol Ther 2017;46:790-799. HEV seroprevalence in hemodialysis patients Subgroup (sensitivity) analyses
  97. 97. Heterogeneity not explained by sensitivity analyses
  98. 98. HEV seroprevalence in hemodialysis patients Funnel plot/Publication bias Haffar et al. Aliment Pharmacol Ther 2017;46:790-799. Egger test: p = 0.83 Is there a publication bias?
  99. 99. Is there a publication bias? Funnel plot: no publication bias Egger test (p = 0.83): no publication bias
  100. 100. Publication bias (Funnel plot) Funnel plot is used to detect publication bias in trials included in a meta-analysis. A. True B. False Publication bias will result in asymmetry of funnel plot. A. True B. False The p value of Egger test is 0.932 which indicates that publication bias exists in trials included in the meta-analysis. A. True B. False Sedgwick P et al. How to read a funnel plot. BMJ 2013;346:f1342.
  101. 101. Publication bias (Funnel plot) Funnel plot is used to detect publication bias in trials included in a meta-analysis. A. True B. False Publication bias will result in asymmetry of funnel plot. A. True B. False The p value of Egger test is 0.932 which indicates that publication bias exists in trials included in the meta-analysis. A. True B. False Sedgwick P et al. How to read a funnel plot. BMJ 2013;346:f1342.
  102. 102. • We have non-invasive means of early detection of HEV infection with sensitive and specific assays • Benefits of such testing clearly outweigh its risks • Cost-effectiveness of such approach remains to be elucidated HEV seroprevalence in hemodialysis patients Conclusion Haffar et al. Aliment Pharmacol Ther 2017;46:790-799.
  103. 103. How to critically appraise a SR?
  104. 104. Critical appraisal of a systematic review -1 Murad MH et al. JAMA. 2014;312(2):171-179  Address sensible clinical question Focused question  Search for relevant studies exhaustive PubMed, Embase,…  Selection/assessment of studies reproducible κ agreement  Results ready for clinical application yes  Address confidence in estimates of effect Assess risk of bias Address heterogeneity Evaluate credibility of the methods of SR If no, the second judgment will not be possible Questions Answers
  105. 105. Medline Embase Cochrane Trials Registry Comparing PubMed, Embase & Cochrane Overlap of 2 databases: 34% PubMed: better coverage of US journals EMBASE: better coverage of European journals Smith BJ et al. Med J Aust 1992 ; 157 : 603 – 11.
  106. 106. Interpretation of different values of kappa Kappa from Greek letter κ Value of kappa Strength of agreement 0 – 0.20 Poor 0.21– 0.40 Fair 0.41– 0.60 Moderate 0.61– 0.80 Good 0.81–1.00 Very good Perera R, Heneghan C & Badenoch D. Statistics toolkit. Blackwell Publishing & BMJ Books, Oxford, 1st edition, 2008. kappa score of 0.6 indicates good agreement
  107. 107. Critical appraisal of systematic review -2 Murad MH et al. JAMA. 2014;312(2):171-179  Risk of bias across studies Cochrane tool of bias  Results consistent in studies (heterogeneity) I-squared & p value  Precision of the results Wideness of 95% CI  Results apply to my patient (indirectness) Age, sicker,….  Concern about reporting bias Funnel plot, Egger test Rate the confidence in the effect estimates Questions Answers  Reasons to increase the confidence rating “Large treatment effect over a short time”
  108. 108. Cochrane tool for bias risk Higgins JPT et al. BMJ 2011;343:1-9.
  109. 109. Cochrane tool for bias risk Higgins JPT et al. BMJ 2011;343:1-9.
  110. 110. Imprecision • Small sample size • Small number of events • Wide confidence intervals
  111. 111. The Trial patients The trial report The actual patients The problem of applying trial results
  112. 112. Directness of evidence Four types Examples Populations Older, sicker or more co-morbidity Oseltamivir for prophylaxis of avian flu Interventions Surgery undertaken by subspecialists in referral centers vs general surgeons in the community Outcomes Surrogate outcome Digestive side effects of NSAIDs Indirect comparison No head-to-head comparisons between several drugs of the same class (eg: biphosphonates) Guyat GH et al. Journal of Clinical Epidemiology 2011;64:1303-1310.
  113. 113. Serious GI events: perforation -bleeding Clinical ulcers Endoscopic ulcers Relative severity GI Symptoms Relative frequency NSAID-related GI side effects
  114. 114. Indirect comparison Alendronate Risedronate Placebo ?---------------------------------------- Head-to- head comparison Head-to- head comparison
  115. 115. Thank You

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