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Intensive Care Medicine
Published in: Intensive Care Medicine 1/2010

01-01-2010 | Review

Prospective meta-analysis using individual patient data in intensive care medicine

Authors: Michael C. Reade, Anthony Delaney, Michael J. Bailey, David A. Harrison, Donald M. Yealy, Peter G. Jones, Kathryn M. Rowan, Rinaldo Bellomo, Derek C. Angus

Published in: Intensive Care Medicine | Issue 1/2010

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Abstract

Meta-analysis is a technique for combining evidence from multiple trials. However, meta-analyses of studies with substantial heterogeneity among patients within trials—common in intensive care—can lead to incorrect conclusions if performed using aggregate data. Use of individual patient data (IPD) can avoid this concern, increase the power of a meta-analysis, and is useful for exploring subgroup effects. Barriers exist to IPD meta-analysis, most of which are overcome if clinical trials are designed to prospectively facilitate the incorporation of their results with other trials. We review the features of prospective IPD meta-analysis and identify those of relevance to intensive care research. We identify three clinical questions, which are the subject of recent or planned randomised controlled trials where IPD MA offers advantages over approaches using aggregate data.
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Literature
1.
Wunsch H, Angus DC (2006) International comparisons of intensive care: understanding the differences. In: Vincent JL (ed) Yearbook of intensive care and emergency medicine. Springer, Berlin, pp 787–793
2.
Rivers E, Nguyen B, Havstad S, Ressler J, Muzzin A, Knoblich B, Peterson E, Tomlanovich M (2001) Early goal-directed therapy in the treatment of severe sepsis and septic shock. N Engl J Med 345:1368–1377CrossRefPubMed
3.
Orford NR, Faulkner C, Flintoff W, Eddey D, Lamb-Jenkins J, Henry M, Corke C, Stow P, Green D (2008) Implementation and outcomes of a severe sepsis protocol in an Australian tertiary hospital. Crit Care Resusc 10:217–224PubMed
4.
Finfer S, Bellomo R, Boyce N, French J, Myburgh J, Norton R (2004) A comparison of albumin and saline for fluid resuscitation in the intensive care unit. N Engl J Med 350:2247–2256CrossRefPubMed
5.
Myburgh J, Cooper J, Finfer S, Bellomo R, Norton R, Bishop N, Kai LS, Vallance S (2007) Saline or albumin for fluid resuscitation in patients with traumatic brain injury. N Engl J Med 357:874–884CrossRefPubMed
6.
Cook DJ, Reeve BK, Guyatt GH, Heyland DK, Griffith LE, Buckingham L, Tryba M (1996) Stress ulcer prophylaxis in critically ill patients. Resolving discordant meta-analyses. JAMA 275:308–314CrossRefPubMed
7.
Cochrane Injuries Group Albumin Reviewers (1998) Human albumin administration in critically ill patients: systematic review of randomised controlled trials. BMJ 317:235–240
8.
Dulguerov P, Gysin C, Perneger TV, Chevrolet JC (1999) Percutaneous or surgical tracheostomy: a meta-analysis. Crit Care Med 27:1617–1625CrossRefPubMed
9.
Liberati A, D’Amico R, Pifferi S, Telaro E (2000) Antibiotic prophylaxis in intensive care units: meta-analyses versus clinical practice. Intensive Care Med 26(Suppl 1):S38–S44CrossRefPubMed
10.
Gonzales DA, Norsworthy KJ, Kern SJ, Banks S, Sieving PC, Star RA, Natanson C, Danner RL (2007) A meta-analysis of N-acetylcysteine in contrast-induced nephrotoxicity: unsupervised clustering to resolve heterogeneity. BMC Med 5:32CrossRefPubMed
11.
Egger M, Smith GD, Phillips AN (1997) Meta-analysis: principles and procedures. BMJ 315:1533–1537PubMed
12.
Lyman GH, Kuderer NM (2005) The strengths and limitations of meta-analyses based on aggregate data. BMC Med Res Methodol 5:14CrossRefPubMed
13.
Simmonds MC, Higgins JP, Stewart LA, Tierney JF, Clarke MJ, Thompson SG (2005) Meta-analysis of individual patient data from randomized trials: a review of methods used in practice. Clin Trials 2:209–217CrossRefPubMed
14.
Lambert PC, Sutton AJ, Abrams KR, Jones DR (2002) A comparison of summary patient-level covariates in meta-regression with individual patient data meta-analysis. J Clin Epidemiol 55:86–94CrossRefPubMed
15.
Schmid CH, Stark PC, Berlin JA, Landais P, Lau J (2004) Meta-regression detected associations between heterogeneous treatment effects and study-level, but not patient-level, factors. J Clin Epidemiol 57:683–697CrossRefPubMed
16.
Horsey P (2002) Albumin and hypovolaemia: is the Cochrane evidence to be trusted? Lancet 359:70–72CrossRefPubMed
17.
Soni N (1998) Human albumin administration in critically ill patients. Validity of review methods must be assessed. BMJ 317:883–884PubMed
18.
Villar J, Mackey ME, Carroli G, Donner A (2001) Meta-analyses in systematic reviews of randomized controlled trials in perinatal medicine: comparison of fixed and random effects models. Stat Med 20:3635–3647CrossRefPubMed
19.
Wang R, Lagakos SW, Ware JH, Hunter DJ, Drazen JM (2007) Statistics in medicine—reporting of subgroup analyses in clinical trials. N Engl J Med 357:2189–2194CrossRefPubMed
20.
Glenny AM, Altman DG, Song F, Sakarovitch C, Deeks JJ, D’Amico R, Bradburn M, Eastwood AJ (2005) Indirect comparisons of competing interventions. Health Technol Assess 9:1–4PubMed
21.
Song F, Altman DG, Glenny AM, Deeks JJ (2003) Validity of indirect comparison for estimating efficacy of competing interventions: empirical evidence from published meta-analyses. BMJ 326:472CrossRefPubMed
22.
Thompson SG, Higgins JP (2002) How should meta-regression analyses be undertaken and interpreted? Stat Med 21:1559–1573CrossRefPubMed
23.
24.
Berlin JA, Santanna J, Schmid CH, Szczech LA, Feldman HI (2002) Individual patient- versus group-level data meta-regressions for the investigation of treatment effect modifiers: ecological bias rears its ugly head. Stat Med 21:371–387CrossRefPubMed
25.
Stewart LA, Clarke MJ (1995) Practical methodology of meta-analyses (overviews) using updated individual patient data. Cochrane Working Group. Stat Med 14:2057–2079CrossRefPubMed
26.
Thompson SG, Smith TC, Sharp SJ (1997) Investigating underlying risk as a source of heterogeneity in meta-analysis. Stat Med 16:2741–2758CrossRefPubMed
27.
Duchateau L, Pignon JP, Bijnens L, Bertin S, Bourhis J, Sylvester R (2001) Individual patient-versus literature-based meta-analysis of survival data: time to event and event rate at a particular time can make a difference, an example based on head and neck cancer. Control Clin Trials 22:538–547CrossRefPubMed
28.
Earle CC, Pham B, Wells GA (2000) An assessment of methods to combine published survival curves. Med Decis Making 20:104–111CrossRefPubMed
29.
Parmar MK, Torri V, Stewart L (1998) Extracting summary statistics to perform meta-analyses of the published literature for survival endpoints. Stat Med 17:2815–2834CrossRefPubMed
30.
Chalmers I (1993) The Cochrane collaboration: preparing, maintaining, and disseminating systematic reviews of the effects of health care. Ann NY Acad Sci 703:156–163CrossRefPubMed
31.
Stewart LA, Parmar MK (1993) Meta-analysis of the literature or of individual patient data: is there a difference? Lancet 341:418–422CrossRefPubMed
32.
Jeng GT, Scott JR, Burmeister LF (1995) A comparison of meta-analytic results using literature vs individual patient data. Paternal cell immunization for recurrent miscarriage. JAMA 274:830–836CrossRefPubMed
33.
Steinberg KK, Smith SJ, Stroup DF, Olkin I, Lee NC, Williamson GD, Thacker SB (1997) Comparison of effect estimates from a meta-analysis of summary data from published studies and from a meta-analysis using individual patient data for ovarian cancer studies. Am J Epidemiol 145:917–925PubMed
34.
D’Amico R, Pifferi S, Leonetti C, Torri V, Tinazzi A, Liberati A (1998) Effectiveness of antibiotic prophylaxis in critically ill adult patients: systematic review of randomised controlled trials. BMJ 316:1275–1285PubMed
35.
Angelillo IF, Villari P (2003) Meta-analysis of published studies or meta-analysis of individual data? Caesarean section in HIV-positive women as a study case. Public Health 117:323–328CrossRefPubMed
36.
Li Z, Meredith MP (2003) Exploring the relationship between surrogates and clinical outcomes: analysis of individual patient data vs. meta-regression on group-level summary statistics. J Biopharm Stat 13:777–792CrossRefPubMed
37.
McCormack K, Grant A, Scott N (2004) Value of updating a systematic review in surgery using individual patient data. Br J Surg 91:495–499CrossRefPubMed
38.
Olkin I, Sampson A (1998) Comparison of meta-analysis versus analysis of variance of individual patient data. Biometrics 54:317–322CrossRefPubMed
39.
Mathew T, Nordstrom K (1999) On the equivalence of meta-analysis using literature and using individual patient data. Biometrics 55:1221–1223CrossRefPubMed
40.
Clarke M, Stewart L, Tierney J, Williamson P (2007) Individual patient data meta-analysis compared with meta-analysis based on aggregate data (Protocol). Cochrane Database Syst Rev 2
41.
Higgins JP, Whitehead A, Turner RM, Omar RZ, Thompson SG (2001) Meta-analysis of continuous outcome data from individual patients. Stat Med 20:2219–2241CrossRefPubMed
42.
Whitehead A, Omar RZ, Higgins JP, Savaluny E, Turner RM, Thompson SG (2001) Meta-analysis of ordinal outcomes using individual patient data. Stat Med 20:2243–2260CrossRefPubMed
43.
Turner RM, Omar RZ, Yang M, Goldstein H, Thompson SG (2000) A multilevel model framework for meta-analysis of clinical trials with binary outcomes. Stat Med 19:3417–3432CrossRefPubMed
44.
Man-Son-Hing M, Wells G (1995) Meta-analysis of efficacy of quinine for treatment of nocturnal leg cramps in elderly people. BMJ 310:13–17PubMed
45.
Koopman L, van der Heijden GJ, Grobbee DE, Rovers MM (2008) Comparison of methods of handling missing data in individual patient data meta-analyses: an empirical example on antibiotics in children with acute otitis media. Am J Epidemiol 167:540–545CrossRefPubMed
46.
Mauer DK, Nolan J, Plaisance P, Sitter H, Benoit H, Stiell IG, Sofianos E, Keiding N, Lurie KG (1999) Effect of active compression–decompression resuscitation (ACD-CPR) on survival: a combined analysis using individual patient data. Resuscitation 41:249–256CrossRefPubMed
47.
Ioannidis JP, Contopoulos-Ioannidis DG, Lau J (1999) Recursive cumulative meta-analysis: a diagnostic for the evolution of total randomized evidence from group and individual patient data. J Clin Epidemiol 52:281–291CrossRefPubMed
48.
Sutton AJ, Kendrick D, Coupland CA (2008) Meta-analysis of individual- and aggregate-level data. Stat Med 27:651–669CrossRefPubMed
49.
Cools F, Askie LM, Offringa M (2009) Elective high-frequency oscillatory ventilation in preterm infants with respiratory distress syndrome: an individual patient data meta-analysis. BMC Pediatr 9:33CrossRefPubMed
50.
Holzer M, Bernard SA, Hachimi-Idrissi S, Roine RO, Sterz F, Mullner M (2005) Hypothermia for neuroprotection after cardiac arrest: systematic review and individual patient data meta-analysis. Crit Care Med 33:414–418CrossRefPubMed
51.
Higgins JP, Green S (2006) Cochrane handbook for systematic reviews of interventions. The Cochrane library. Wiley, Chichester
52.
Moher D, Cook DJ, Eastwood S, Olkin I, Rennie D, Stroup DF (1999) Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Quality of reporting of meta-analyses. Lancet 354:1896–1900CrossRefPubMed
53.
54.
Pogue JM, Yusuf S (1997) Cumulating evidence from randomized trials: utilizing sequential monitoring boundaries for cumulative meta-analysis. Control Clin Trials 18:580–593CrossRefPubMed
55.
Montori VM, Devereaux PJ, Adhikari NK, Burns KE, Eggert CH, Briel M, Lacchetti C, Leung TW, Darling E, Bryant DM, Bucher HC, Schunemann HJ, Meade MO, Cook DJ, Erwin PJ, Sood A, Sood R, Lo B, Thompson CA, Zhou Q, Mills E, Guyatt GH (2005) Randomized trials stopped early for benefit: a systematic review. JAMA 294:2203–2209CrossRefPubMed
56.
Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) (2005) Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365:1687–1717CrossRef
57.
Go PM (1994) Prospective comparison studies on laparoscopic inguinal hernia repair. Surg Endosc 8:719–720CrossRefPubMed
58.
Simes RJ (1995) Prospective meta-analysis of cholesterol-lowering studies: the Prospective Pravastatin Pooling (PPP) Project and the Cholesterol Treatment Trialists (CTT) Collaboration. Am J Cardiol 76:122C–126CCrossRefPubMed
59.
Valsecchi MG, Masera G (1996) A new challenge in clinical research in childhood ALL: the prospective meta-analysis strategy for intergroup collaboration. Ann Oncol 7:1005–1008PubMed
60.
Smith CT, Williamson PR, Marson AG (2005) An overview of methods and empirical comparison of aggregate data and individual patient data results for investigating heterogeneity in meta-analysis of time-to-event outcomes. J Eval Clin Pract 11:468–478CrossRefPubMed
61.
Thompson SG, Higgins JP (2005) Treating individuals 4: can meta-analysis help target interventions at individuals most likely to benefit? Lancet 365:341–346PubMed
62.
Koopman L, van der Heijden GJ, Hoes AW, Grobbee DE, Rovers MM (2008) Empirical comparison of subgroup effects in conventional and individual patient data meta-analyses. Int J Technol Assess Health Care 24:358–361CrossRefPubMed
63.
Barton I (2004) The relationship between osteoporotic fracture risk and a surrogate: apparent discrepancies between analyses based in individual patient data and summary statistics. Pharm Stat 3:205–212CrossRef
64.
Palevsky PM, Zhang JH, O’Connor TZ, Chertow GM, Crowley ST, Choudhury D, Finkel K, Kellum JA, Paganini E, Schein RM, Smith MW, Swanson KM, Thompson BT, Vijayan A, Watnick S, Star RA, Peduzzi P (2008) Intensity of renal support in critically ill patients with acute kidney injury. N Engl J Med 359:7–20CrossRefPubMed
65.
66.
67.
68.
Brunkhorst FM, Engel C, Bloos F, Meier-Hellmann A, Ragaller M, Weiler N, Moerer O, Gruendling M, Oppert M, Grond S, Olthoff D, Jaschinski U, John S, Rossaint R, Welte T, Schaefer M, Kern P, Kuhnt E, Kiehntopf M, Hartog C, Natanson C, Loeffler M, Reinhart K (2008) Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N Engl J Med 358:125–139CrossRefPubMed
69.
70.
71.
Wade CE, Grady JJ, Kramer GC, Younes RN, Gehlsen K, Holcroft JW (1997) Individual patient cohort analysis of the efficacy of hypertonic saline/dextran in patients with traumatic brain injury and hypotension. J Trauma 42:S61–S65CrossRefPubMed
72.
Wade C, Grady J, Kramer G (1997) Efficacy of hypertonic saline dextran (HSD) in patients with traumatic hypotension: meta-analysis of individual patient data. Acta Anaesthesiol Scand Suppl 110:77–79PubMed
73.
Connolly SJ, Hallstrom AP, Cappato R, Schron EB, Kuck KH, Zipes DP, Greene HL, Boczor S, Domanski M, Follmann D, Gent M, Roberts RS (2000) Meta-analysis of the implantable cardioverter defibrillator secondary prevention trials. AVID, CASH and CIDS studies. Antiarrhythmics vs Implantable Defibrillator study. Cardiac Arrest Study Hamburg. Canadian Implantable Defibrillator Study. Eur Heart J 21:2071–2078CrossRefPubMed
74.
Hukkelhoven CW, Steyerberg EW, Rampen AJ, Farace E, Habbema JD, Marshall LF, Murray GD, Maas AI (2003) Patient age and outcome following severe traumatic brain injury: an analysis of 5600 patients. J Neurosurg 99:666–673CrossRefPubMed
75.
Yap YG, Duong T, Bland M, Malik M, Torp-Pedersen C, Kober L, Connolly SJ, Marchant B, Camm J (2005) Temporal trends on the risk of arrhythmic vs. non-arrhythmic deaths in high-risk patients after myocardial infarction: a combined analysis from multicentre trials. Eur Heart J 26:1385–1393CrossRefPubMed
76.
Murray GD, Butcher I, McHugh GS, Lu J, Mushkudiani NA, Maas AI, Marmarou A, Steyerberg EW (2007) Multivariable prognostic analysis in traumatic brain injury: results from the IMPACT study. J Neurotrauma 24:329–337CrossRefPubMed
77.
Pearse RM, Belsey JD, Cole JN, Bennett ED (2008) Effect of dopexamine infusion on mortality following major surgery: individual patient data meta-regression analysis of published clinical trials. Crit Care Med 36:1323–1329CrossRefPubMed
78.
Johnson ES, Lanes SF, Wentworth CE III, Satterfield MH, Abebe BL, Dicker LW (1999) A metaregression analysis of the dose–response effect of aspirin on stroke. Arch Intern Med 159:1248–1253CrossRefPubMed
79.
Zufferey P, Laporte S, Quenet S, Molliex S, Auboyer C, Decousus H, Mismetti P (2003) Optimal low-molecular-weight heparin regimen in major orthopaedic surgery. A meta-analysis of randomised trials. Thromb Haemost 90:654–661PubMed
Metadata
Title
Prospective meta-analysis using individual patient data in intensive care medicine
Authors
Michael C. Reade
Anthony Delaney
Michael J. Bailey
David A. Harrison
Donald M. Yealy
Peter G. Jones
Kathryn M. Rowan
Rinaldo Bellomo
Derek C. Angus
Publication date
01-01-2010
Publisher
Springer-Verlag
Published in
Intensive Care Medicine / Issue 1/2010
Print ISSN: 0342-4642
Electronic ISSN: 1432-1238
DOI
https://doi.org/10.1007/s00134-009-1650-x

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