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Cochrane Methodology Reviews

                 Lisa Bero
    San Francisco Branch, US Cochrane
                  Center
                   UCSF

 CER Symposium, January 2012
Case study: Methodology Reviews
Methodology Reviews
• A "methodology study" is a study of the
  methods used in randomized trials, other
  healthcare evaluations or systematic reviews.
  – Consent procedures
  – Recruitment methods
  – Association of allocation concealment with
    estimates of treatment effect
• A "methodology review" is a systematic
  review of methodology studies
Study Designs for CER/ PCOR
•head to head randomized trials,        • observational study analysis
•cluster randomized trials,               approaches employing so-called
•adaptive designs,                        causal inference techniques,
                                          which can include instrumental
•practice / pragmatic trials,             variables, marginal structural
• PBE-CPI “practice based evidence        models, propensity scores,
for clinical practice improvement,”       among others.
•natural experiments,
•observational or cross-sectional       • “NEW” design terms such as
studies of registries and databases       “observational randomization
including electronic medical records,     study”
•meta-analysis,
•network meta-analysis,
•modelling and simulation
                                        Source: IOM-National Priorities Committee 2009

                                                                                         4
“Best “ study design for CER?
•A number of reviews comparing the effect sizes and biases in
randomized and non-randomized studies have been conducted.
    •Most compared randomized to non-randomized trials.
    •Most often limited the comparison with observational
    studies to cohort studies, or the types of observational
    designs included were not specified.
    •Most published between 1982 and 2003

•Compared to RCTs, observational designs have been found to
overestimate treatment effects ; underestimate treatment
effects; or show no difference.
Protocol: in press, Cochrane Library


           Health care outcomes assessed with non-
           experimental designs compared with
           those assessed in randomized trials


                                 Lisa Bero
                                 Andrew Anglemyer
                                 Tara Horvath

               San Francisco Branch of the US Cochrane Center
               HIV / AIDS Cochrane Review Group
               UCSF
 Funding: Clinical and Translational Sciences Institute (CTSI), University of California,
 San Francisco (UCSF), USA
Objectives
• To assess the impact of study design--to include
  RCTs vs observational study designs, different
  types of observational studies, and/or choice of
  analytic techniques -- on the effect measures
  estimated in observational and randomized
  studies
• To explore methodological variables that might
  explain any differences identified
• To identify gaps in the existing research
  comparing study designs
Inclusion criteria
• Systematic or non-systematic reviews
  designed as methodological studies to
  compare study designs
• Clinical outcomes: efficacy or harms of
  alternative interventions to prevent or treat a
  clinical condition or improve the delivery of
  care
A priori subgroup analyses
• Comparisons of drug interventions
• Clinical topic
• Heterogeneity of included methodological
  studies
PRELIMINARY DATA:

 Included studies – RCT vs. observational
PRELIMINARY DATA:

          9 studies in meta-analysis
• Included 19 – 276 studies
• Evaluated a mix of interventions
    – Lower back pain
    – Digestive surgery
    – Various interventions
• One focused on drug –drug comparisons
  (Naudet)
• One focused on adverse events from (mostly)
  pharmacological treatements (Golder)
PRELIMINARY DATA:
                                           Risk Ratio                                              Risk Ratio
   Study or Subgroup        Weight     IV, Random, 95% CI Year                                IV, Random, 95% CI
   1.1.1 RCT vs All Observational
   Concato 2000              15.3%         1.07 [0.95, 1.21] 2000
   Benson 2000                 7.2%        0.95 [0.58, 1.56] 2000
   Bhandari 2004             11.1%         0.70 [0.52, 0.95] 2004
   Shikata 2006              12.9%         0.97 [0.77, 1.22] 2006
   Furlan 2008                 4.3%        1.94 [0.93, 4.05] 2008
   Beynon 2008               14.9%         0.87 [0.75, 1.00] 2008
   Mueller 2010              13.7%         1.48 [1.22, 1.80] 2010
   Golder 2011               15.1%         1.08 [0.95, 1.23] 2011
   Naudet 2011                5.6%         3.55 [1.94, 6.50] 2011
   Subtotal (95% CI)        100.0%         1.11 [0.93, 1.33]
   Heterogeneity: Tau² = 0.05; Chi² = 44.79, df = 8 (P < 0.00001); I² = 82%
   Test for overall effect: Z = 1.19 (P = 0.23)

   1.1.2 RCT vs Cohort
   Benson 2000               11.1%         1.52 [0.87, 2.64] 2000
   Concato 2000              32.9%         1.04 [0.91, 1.18] 2000
   Bhandari 2004             21.9%         0.70 [0.52, 0.95] 2004
   Furlan 2008                 7.2%        1.94 [0.93, 4.05] 2008
   Golder 2011               26.9%         1.02 [0.82, 1.27] 2011
   Subtotal (95% CI)        100.0%         1.03 [0.83, 1.29]
   Heterogeneity: Tau² = 0.03; Chi² = 10.95, df = 4 (P = 0.03); I² = 63%
   Test for overall effect: Z = 0.30 (P = 0.76)

   1.1.3 RCT vs Case Control
   Concato 2000              58.9%         1.20 [0.94, 1.54] 2000
   Golder 2011               41.1%         0.84 [0.57, 1.23] 2011
   Subtotal (95% CI)        100.0%         1.04 [0.73, 1.46]
   Heterogeneity: Tau² = 0.04; Chi² = 2.34, df = 1 (P = 0.13); I² = 57%
   Test for overall effect: Z = 0.20 (P = 0.84)



                                                                              0.2           0.5         1         2              5
                                                                                Obs Reflect Greater Risk RCTs Reflect Greater Risk
   Test for subgroup differences: Chi² = 0.49, df = 2 (P = 0.78), I² = 0%
Preliminary Findings
• Differences in effect measures not associated
  with study design – explore other reasons
• Conduct subgroup analyses
• Need methodological studies comparing trials
  with other observational designs (not just
  cohorts, case control) and different analytic
  methods for observational data

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Case study: Methodology Reviews

  • 1. Cochrane Methodology Reviews Lisa Bero San Francisco Branch, US Cochrane Center UCSF CER Symposium, January 2012
  • 3. Methodology Reviews • A "methodology study" is a study of the methods used in randomized trials, other healthcare evaluations or systematic reviews. – Consent procedures – Recruitment methods – Association of allocation concealment with estimates of treatment effect • A "methodology review" is a systematic review of methodology studies
  • 4. Study Designs for CER/ PCOR •head to head randomized trials, • observational study analysis •cluster randomized trials, approaches employing so-called •adaptive designs, causal inference techniques, which can include instrumental •practice / pragmatic trials, variables, marginal structural • PBE-CPI “practice based evidence models, propensity scores, for clinical practice improvement,” among others. •natural experiments, •observational or cross-sectional • “NEW” design terms such as studies of registries and databases “observational randomization including electronic medical records, study” •meta-analysis, •network meta-analysis, •modelling and simulation Source: IOM-National Priorities Committee 2009 4
  • 5. “Best “ study design for CER? •A number of reviews comparing the effect sizes and biases in randomized and non-randomized studies have been conducted. •Most compared randomized to non-randomized trials. •Most often limited the comparison with observational studies to cohort studies, or the types of observational designs included were not specified. •Most published between 1982 and 2003 •Compared to RCTs, observational designs have been found to overestimate treatment effects ; underestimate treatment effects; or show no difference.
  • 6. Protocol: in press, Cochrane Library Health care outcomes assessed with non- experimental designs compared with those assessed in randomized trials Lisa Bero Andrew Anglemyer Tara Horvath San Francisco Branch of the US Cochrane Center HIV / AIDS Cochrane Review Group UCSF Funding: Clinical and Translational Sciences Institute (CTSI), University of California, San Francisco (UCSF), USA
  • 7. Objectives • To assess the impact of study design--to include RCTs vs observational study designs, different types of observational studies, and/or choice of analytic techniques -- on the effect measures estimated in observational and randomized studies • To explore methodological variables that might explain any differences identified • To identify gaps in the existing research comparing study designs
  • 8. Inclusion criteria • Systematic or non-systematic reviews designed as methodological studies to compare study designs • Clinical outcomes: efficacy or harms of alternative interventions to prevent or treat a clinical condition or improve the delivery of care
  • 9. A priori subgroup analyses • Comparisons of drug interventions • Clinical topic • Heterogeneity of included methodological studies
  • 10. PRELIMINARY DATA: Included studies – RCT vs. observational
  • 11. PRELIMINARY DATA: 9 studies in meta-analysis • Included 19 – 276 studies • Evaluated a mix of interventions – Lower back pain – Digestive surgery – Various interventions • One focused on drug –drug comparisons (Naudet) • One focused on adverse events from (mostly) pharmacological treatements (Golder)
  • 12. PRELIMINARY DATA: Risk Ratio Risk Ratio Study or Subgroup Weight IV, Random, 95% CI Year IV, Random, 95% CI 1.1.1 RCT vs All Observational Concato 2000 15.3% 1.07 [0.95, 1.21] 2000 Benson 2000 7.2% 0.95 [0.58, 1.56] 2000 Bhandari 2004 11.1% 0.70 [0.52, 0.95] 2004 Shikata 2006 12.9% 0.97 [0.77, 1.22] 2006 Furlan 2008 4.3% 1.94 [0.93, 4.05] 2008 Beynon 2008 14.9% 0.87 [0.75, 1.00] 2008 Mueller 2010 13.7% 1.48 [1.22, 1.80] 2010 Golder 2011 15.1% 1.08 [0.95, 1.23] 2011 Naudet 2011 5.6% 3.55 [1.94, 6.50] 2011 Subtotal (95% CI) 100.0% 1.11 [0.93, 1.33] Heterogeneity: Tau² = 0.05; Chi² = 44.79, df = 8 (P < 0.00001); I² = 82% Test for overall effect: Z = 1.19 (P = 0.23) 1.1.2 RCT vs Cohort Benson 2000 11.1% 1.52 [0.87, 2.64] 2000 Concato 2000 32.9% 1.04 [0.91, 1.18] 2000 Bhandari 2004 21.9% 0.70 [0.52, 0.95] 2004 Furlan 2008 7.2% 1.94 [0.93, 4.05] 2008 Golder 2011 26.9% 1.02 [0.82, 1.27] 2011 Subtotal (95% CI) 100.0% 1.03 [0.83, 1.29] Heterogeneity: Tau² = 0.03; Chi² = 10.95, df = 4 (P = 0.03); I² = 63% Test for overall effect: Z = 0.30 (P = 0.76) 1.1.3 RCT vs Case Control Concato 2000 58.9% 1.20 [0.94, 1.54] 2000 Golder 2011 41.1% 0.84 [0.57, 1.23] 2011 Subtotal (95% CI) 100.0% 1.04 [0.73, 1.46] Heterogeneity: Tau² = 0.04; Chi² = 2.34, df = 1 (P = 0.13); I² = 57% Test for overall effect: Z = 0.20 (P = 0.84) 0.2 0.5 1 2 5 Obs Reflect Greater Risk RCTs Reflect Greater Risk Test for subgroup differences: Chi² = 0.49, df = 2 (P = 0.78), I² = 0%
  • 13. Preliminary Findings • Differences in effect measures not associated with study design – explore other reasons • Conduct subgroup analyses • Need methodological studies comparing trials with other observational designs (not just cohorts, case control) and different analytic methods for observational data