BMJ  2003;327:557-560 (6 September), doi:10.1136/bmj.327.7414.557

Education and debate

Measuring inconsistency in meta-analyses

¹ MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 2SR, ² Cancer Research UK/NHS Centre for Statistics in Medicine, Institute of Health Sciences, Oxford OX3 7LF

Cochrane Reviews have recently started including the quantity I² to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice?

Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.¹ Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I², which we believe gives a better measure of the consistency between trials in a meta-analysis.

Need for consistency

Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.^2-4

Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.^{5 6} But what does the test achieve in practice, and how should the resulting P values be interpreted?

Testing for heterogeneity

A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic (Cochran's Q) is computed by summing the squared deviations of each study's estimate from the overall meta-analytic estimate, weighting each study's contribution in the same manner as in the meta-analysis.⁷ P values are obtained by comparing the statistic with a ² distribution with k-1 degrees of freedom (where k is the number of studies).

The test is known to be poor at detecting true heterogeneity among studies as significant. Meta-analyses often include small numbers of studies,^{6 8} and the power of the test in such circumstances is low.^{9 10} For example, consider the meta-analysis of randomised controlled trials of amantadine for preventing influenza (fig 1). ¹¹ The treatment effects in the eight trials seem inconsistent: the reduction in odds vary from 16% to 93%, with some of the confidence intervals not overlapping. But the test of heterogeneity yields a P value of 0.09, conventionally interpreted as being non-significant. Because the test is poor at detecting true heterogeneity, a non-significant result cannot be taken as evidence of homogeneity. Using a cut-off of 10% for significance¹² ameliorates this problem but increases the risk of drawing a false positive conclusion (type I error).¹⁰

View larger version (35K): [in this window] [in a new window]   Fig 1 Eight trials of amantadine for prevention of influenza.11 Outcome is cases of influenza. Summary odds ratios calculated with random effects method

 

Conversely, the test arguably has excessive power when there are many studies, especially when those studies are large. One of the largest meta-analyses in the Cochrane Database of Systematic Reviews is of clinical trials of tricyclic antidepressants and selective serotonin reuptake inhibitors for treatment of depression.¹³ Over 15 000 participants from 135 trials are included in the assessment of comparative drop-out rates, and the test for heterogeneity is significant (P = 0.005). However, this P value does not reasonably describe the extent of heterogeneity in the results of the trials. As we show later, a little inconsistency exists among these trials but it does not affect the conclusion of the review (that serotonin reuptake inhibitors have lower discontinuation rates than tricyclic antidepressants).

Since systematic reviews bring together studies that are diverse both clinically and methodologically, heterogeneity in their results is to be expected.⁶ For example, heterogeneity is likely to arise through diversity in doses, lengths of follow up, study quality, and inclusion criteria for participants. So there seems little point in simply testing for heterogeneity when what matters is the extent to which it affects the conclusions of the meta-analysis.

Quantifying heterogeneity: a better approach

We developed an alternative approach that quantifies the effect of heterogeneity, providing a measure of the degree of inconsistency in the studies' results.¹⁴ The quantity, which we call I², describes the percentage of total variation across studies that is due to heterogeneity rather than chance. I² can be readily calculated from basic results obtained from a typical meta-analysis as I² = 100%x(Q - df)/Q, where Q is Cochran's heterogeneity statistic and df the degrees of freedom. Negative values of I² are put equal to zero so that I² lies between 0% and 100%. A value of 0% indicates no observed heterogeneity, and larger values show increasing heterogeneity.

Examples of values of I²

The principal advantage of I² is that it can be calculated and compared across meta-analyses of different sizes, of different types of study, and using different types of outcome data. Table 1 gives I² values for six published meta-analyses along with 95% uncertainty intervals. The upper limits of these intervals show that conclusions of homogeneity in meta-analyses of small numbers of studies are often unjustified.^{11 13 15-19}

View this table: [in this window] [in a new window]   Table 1 Heterogeneity statistics for examples of meta-analyses from the literature. Meta-analyses were conducted using either meta or metan in STATA15

 

The tamoxifen and streptokinase meta-analyses, in which all the included studies found similar effects,^{16 17} have I² values of 3% and 19% respectively. These indicate little variability between studies that cannot be explained by chance. For the review comparing drop-outs on selective serotonin reuptake inhibitors with tricyclic antidepressants, I² is 26%, indicating that although the heterogeneity is highly significant, it is a small effect.

The reviews of trials of magnesium after myocardial infarction (I² = 63%) and case-control studies investigating the effects of electromagnetic radiation on leukaemia (69%) both included studies with diverse results. The high I² values show that most of the variability across studies is due to heterogeneity rather than chance. Although no significant heterogeneity was detected in the review of amantadine,¹¹ the inconsistency was moderately large (I² = 44%).

Figure 2 shows the observed values of I² from 509 meta-analyses in the Cochrane Database of Systematic Reviews. Almost half of these meta-analyses (250) had no inconsistency (I² = 0%). Among meta-analyses with some heterogeneity, the distribution of I² is roughly flat.

View larger version (17K): [in this window] [in a new window]   Fig 2 Distribution of observed values of I2 based on odds ratios from 509 meta-analyses of dichotomous outcomes in the Cochrane Database of Systematic Reviews. Data are from the first subgroup (if any) in the first meta-analysis (if any) in each review, if it involved a dichotomous outcome and at least two trials with events. Meta-analyses conducted with metan in STATA15

 

Further applications of I²

I² can also be helpful in investigating the causes and type of heterogeneity, as in the three examples below.

Methodological subgroups
Figure 3 shows the six case-control studies of magnetic fields and leukaemia broken down into two subgroups based on assessment of their quality.¹⁹ If heterogeneity is identified in a meta-analysis a common option is to subgroup the studies. Because of loss of power, non-significant heterogeneity within a subgroup may be due not to homogeneity but to the smaller number of studies. Here, the P values for the heterogeneity test are higher for the two subgroups (P = 0.3 and P = 0.009) than for the complete data (P = 0.007), which suggests greater consistency within the subgroups. However, the values of I² show that the three low quality studies are more inconsistent (I² = 79%) than all six (I² = 69%) (table 2). Substantially less inconsistency exists among the high quality studies (I² = 15%), although uncertainty intervals for all of the I² values are wide.

View larger version (36K): [in this window] [in a new window]   Fig 3 Meta-analyses of six case-control studies relating residential exposure to electromagnetic fields to childhood leukaemia.19 Summary odds ratio calculated by random effects method

 

View this table: [in this window] [in a new window]   Table 2 More advanced applications of l2 for assessing heterogeneity in three published meta-analyses. Meta-analyses were conducted with either meta or metan in STATA15

 

Heterogeneity related to choice of effect measure
A systematic review of clinical trials of human albumin administration in critically ill patients concluded that albumin may increase mortality.²⁰ These studies had no inconsistency in risk ratio estimates (I² = 0%) and a narrow uncertainty interval. Table 2 shows the heterogeneity statistics for risk differences as well as for risk ratios. Six trials with no deaths in either treatment group do not contribute information on risk ratios, but they all provide estimates of risk differences. Using P values to decide which scale is more consistent with the data²¹ is inappropriate because of the differing numbers of studies. I² values may validly be compared and show that the risk differences are less homogeneous, as is often the case.²²

Clinically important subgroups
I² can also be used to describe heterogeneity among subgroups. Table 2 includes results for the outcome of recurrence in the meta-analysis of trials of tamoxifen for women with early breast cancer. There was highly significant (P = 0.00002) and important heterogeneity (I² = 50%) among the trials.¹⁶ However, a potentially important source of heterogeneity is the duration of treatment. The authors divided the trials into three duration categories and presented an overall heterogeneity test, a test comparing the three subgroups, and a test for heterogeneity within the subgroups. I² values corresponding to each test show that 96% of the variability observed among the three subgroups cannot be explained by chance. This is not clear from the P values alone. The extreme inconsistency among all 55 trials in the odds ratios for recurrence (I² = 50%) is substantially reduced (I² = 13%) once differences in treatment duration are accounted for.

How much is too much heterogeneity?

A naive categorisation of values for I² would not be appropriate for all circumstances, although we would tentatively assign adjectives of low, moderate, and high to I² values of 25%, 50%, and 75%. Figure 2 shows that about a quarter of meta-analyses have I² values over 50%. Quantification of heterogeneity is only one component of a wider investigation of variability across studies, the most important being diversity in clinical and methodological aspects. Meta-analysts must also consider the clinical implications of the observed degree of inconsistency across studies. For example, interpretation of a given degree of heterogeneity across several studies will differ according to whether the estimates show the same direction of effect.

Advantages of I2 Focuses attention on the effect of any heterogeneity on the meta-analysis Interpretation is intuitive—the percentage of total variation across studies due to heterogeneity Can be accompanied by an uncertainty interval Simple to calculate and can usually be derived from published meta-analyses Does not inherently depend on the number of studies in the meta-analysis May be interpreted similarly irrespective of the type of outcome data (eg dichotomous, quantitative, or time to event) and choice of effect measure (eg odds ratio or hazard ratio) Wide range of applications

Summary points Inconsistency of studies' results in a meta-analysis reduces the confidence of recommendations about treatment Inconsistency is usually assessed with a test for heterogeneity, but problems of power can give misleading results A new quantity I2, ranging from 0-100%, is described that measures the degree of inconsistency across studies in a meta-analysis I2 can be directly compared between meta-analyses with different numbers of studies and different types of outcome data I2 is preferable to a test for heterogeneity in judging consistency of evidence

An alternative quantification of heterogeneity in a meta-analysis is the among-study variance (often called ²), calculated as part of a random effects meta-analysis. This is more useful for comparisons of heterogeneity among subgroups, but values depend on the treatment effect scale. We believe, I² offers advantages over existing approaches to the assessment of heterogeneity (box). Focusing on the effect of heterogeneity also avoids the temptation to perform so called two stage analyses, in which the meta-analysis strategy (fixed or random effects method) is determined by the result of a statistical test. Such strategies have been found to be problematic.^{23 24} We therefore believe that I² is preferable to the test of heterogeneity when assessing inconsistency across studies.

---

We thank Keith O'Rourke and Ian White for useful comments.

Contributors: The authors all work as statisticians and have extensive experience in methodological, empirical and applied research in meta-analysis. JH, JD, and DA are coconvenors of the Cochrane Statistical Methods Group. The views expressed in the paper are those of the authors. All authors contributed to the development of the methods described. JH and ST worked more closely on the development of I². JH is guarantor.

Funding: This work was funded in part by MRC Project Grant G98154 [GenBank] 66.

Competing interests: None declared.

References

1. Egger M, Davey Smith G. Meta-analysis: potentials and promise. BMJ 1997; 315: 1371-4.[Free Full Text]
2. Liberati A, Buzzetti R, Grilli R, Magrini N, Minozzi S. Which guidelines can we trust? West J Med 2001; 174: 262-5.[CrossRef][ISI][Medline]
3. Harbour R, Miller J for the Scottish Intercollegiate Guidelines Network Grading Review Group. A new system for grading recommendations in evidence based guidelines. BMJ 2001; 323: 334-6.[Free Full Text]
4. Guyatt G, Sinclair J, Cook D, Jaeschke R, Schünemann H, Pauker S. Moving from evidence to action. In: Guyatt G, Rennie D, eds. Users' guides to the medical literature: a manual for evidence-based clinical practice. Chicago: American Medical Association, 2002: 599-608.
5. Petitti DB. Approaches to heterogeneity in meta-analysis. Stat Med 2001; 20: 3625-33.[CrossRef][ISI][Medline]
6. Higgins J, Thompson S, Deeks J, Altman D. Statistical heterogeneity in systematic reviews of clinical trials: a critical appraisal of guidelines and practice. J Health Serv Res Policy 2002; 7: 51-61.[Abstract/Free Full Text]
7. Cochran WG. The combination of estimates from different experiments. Biometrics 1954; 10: 101-29.[CrossRef]
8. Sterne JAC, Egger M. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol 2001; 54: 1046-55.[CrossRef][ISI][Medline]
9. Paul SR, Donner A. Small sample performance of tests of homogeneity of odds ratios in k 2x2 tables. Stat Med 1992; 11: 159-65.[ISI][Medline]
10. Hardy RJ, Thompson SG. Detecting and describing heterogeneity in meta-analysis. Stat Med 1998; 17: 841-56.[CrossRef][ISI][Medline]
11. Jefferson TO, Demicheli V, Deeks JJ, Rivetti D. Amantadine and rimantadine for preventing and treating influenza A in adults. Cochrane Database Syst Rev 2002; (4): CD001169 [GenBank] .
12. Dickersin K, Berlin JA. Meta-analysis: state-of-the-science. Epidemiol Rev 1992; 14: 154-76.[Free Full Text]
13. Barbui C, Hotopf M, Freemantle N, Boynton J, Churchill R, Eccles MP, Geddes JR, et al. Treatment discontinuation with selective serotonin reuptake inhibitors (SSRIs) versus tricyclic antidepressants (TCAs). Cochrane Database Syst Rev 2003; (3): CD002791 [GenBank] .
14. Higgins JPT, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002; 21: 1539-58.[CrossRef][ISI][Medline]
15. Sterne JAC, Bradburn MJ, Egger M. Meta-analysis in STATA. In: Egger M, Davey Smith G, Altman DG, eds. Systematic reviews in health care: meta-analysis in context. 2nd ed. London: BMJ Publications, 2001: 347-69.
16. Early Breast Cancer Trialists' Collaborative Group. Tamoxifen for early breast cancer: an overview of the randomised trials. Lancet 1998; 351: 1451-67.[CrossRef][ISI][Medline]
17. Lau J, Antman EM, Jimenez-Silva J, Kupelink B, Mosteller SF, Chalmers TC. Cumulative meta-analysis of therapeutic trials for myocardial infarction. N Engl J Med 1992; 327: 248-54.[Abstract]
18. Egger M, Davey Smith G. Misleading meta-analysis. BMJ 1995; 310: 752-4.[Free Full Text]
19. Angelillo IF, Villari P. Residential exposure to electromagnetic fields and childhood leukaemia: a meta-analysis. Bull World Health Organ 1999; 77: 906-15.[ISI][Medline]
20. Cochrane Injuries Group Albumin Reviewers. Human albumin administration in critically ill patients: systematic review of randomised controlled trials. BMJ 1998; 317: 235-40.[Abstract/Free Full Text]
21. Engels EA, Schmid CH, Terrin N, Olkin I, Lau J. Heterogeneity and statistical significance in meta-analysis: an empirical study of 125 meta-analyses. Stat Med 2000; 19: 1707-28.[CrossRef][ISI][Medline]
22. Deeks JJ. Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes. Stat Med 2002; 21: 1575-1600.[CrossRef][ISI][Medline]
23. Freeman PR. The performance of the two-stage analysis of two-treatment, two-period crossover trials. Stat Med 1989; 8: 1421-32.[ISI][Medline]
24. Steyerberg EW, Eijkemans MJ, Habbema JD. Stepwise selection in small data sets: a simulation study of bias in logistic regression analysis. J Clin Epidemiol 1999; 52: 935-42.[CrossRef][ISI][Medline]

(Accepted June 16, 2003)

CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    What's this?

This article has been cited by other articles:

• Aiello, A. E., Coulborn, R. M., Perez, V., Larson, E. L. (2008). Effect of Hand Hygiene on Infectious Disease Risk in the Community Setting: A Meta-Analysis. Am. J. Public Health 98: 1372-1381 [Abstract] [Full text]  
• ter Riet, G. MD PhD, Cnossen, J. S. MD, van der Post, J. A.M. MD PhD, Mol, B. W. MD PhD, Morris, R. K. MD, Khan, K. S. MD (2008). Use of Doppler ultrasonography to predict pre-eclampsia. CMAJ 179: 53-54 [Full text]  
• AlBuhairan, B., Hind, D., Hutchinson, A. (2008). Antibiotic prophylaxis for wound infections in total joint arthroplasty: A SYSTEMATIC REVIEW. J Bone Joint Surg Br 90-B: 915-919 [Abstract] [Full text]  
• Capon, F., Bijlmakers, M.-J., Wolf, N., Quaranta, M., Huffmeier, U., Allen, M., Timms, K., Abkevich, V., Gutin, A., Smith, R., Warren, R. B., Young, H. S., Worthington, J., Burden, A. D., Griffiths, C. E.M., Hayday, A., Nestle, F. O., Reis, A., Lanchbury, J., Barker, J. N., Trembath, R. C. (2008). Identification of ZNF313/RNF114 as a novel psoriasis susceptibility gene. Hum Mol Genet 17: 1938-1945 [Abstract] [Full text]  
• Walther, A, Houlston, R, Tomlinson, I (2008). Association between chromosomal instability and prognosis in colorectal cancer: a meta-analysis. Gut 57: 941-950 [Abstract] [Full text]  
• Duesing, K., Fatemifar, G., Charpentier, G., Marre, M., Tichet, J., Hercberg, S., Balkau, B., Froguel, P., Gibson, F. (2008). Evaluation of the Association of IGF2BP2 Variants With Type 2 Diabetes in French Caucasians. Diabetes 57: 1992-1996 [Abstract] [Full text]  
• Akl, E. A., Terrenato, I., Barba, M., Sperati, F., Sempos, E. V., Muti, P., Cook, D. J., Schunemann, H. J. (2008). Low-Molecular-Weight Heparin vs Unfractionated Heparin for Perioperative Thromboprophylaxis in Patients With Cancer: A Systematic Review and Meta-analysis. Arch Intern Med 168: 1261-1269 [Abstract] [Full text]  
• Ioannidis, J. P A, Patsopoulos, N. A, Rothstein, H. R (2008). Reasons or excuses for avoiding meta-analysis in forest plots. BMJ 336: 1413-1415 [Full text]  
• Thompson, A., Di Angelantonio, E., Sarwar, N., Erqou, S., Saleheen, D., Dullaart, R. P. F., Keavney, B., Ye, Z., Danesh, J. (2008). Association of Cholesteryl Ester Transfer Protein Genotypes With CETP Mass and Activity, Lipid Levels, and Coronary Risk. JAMA 299: 2777-2788 [Abstract] [Full text]  
• Jafri, N. S., Hornung, C. A., Howden, C. W. (2008). Meta-analysis: Sequential Therapy Appears Superior to Standard Therapy for Helicobacter pylori Infection in Patients Naive to Treatment. ANN INTERN MED 148: 923-931 [Abstract] [Full text]  
• Auer, R., Gaume, J., Rodondi, N., Cornuz, J., Ghali, W. A. (2008). Efficacy of In-Hospital Multidimensional Interventions of Secondary Prevention After Acute Coronary Syndrome: A Systematic Review and Meta-Analysis. Circulation 117: 3109-3117 [Abstract] [Full text]  
• Colman, I., Friedman, B. W, Brown, M. D, Innes, G. D, Grafstein, E., Roberts, T. E, Rowe, B. H (2008). Parenteral dexamethasone for acute severe migraine headache: meta-analysis of randomised controlled trials for preventing recurrence. BMJ 336: 1359-1361 [Abstract] [Full text]  
• Yousef, F., Cardwell, C., Cantwell, M. M., Galway, K., Johnston, B. T., Murray, L. (2008). The Incidence of Esophageal Cancer and High-Grade Dysplasia in Barrett's Esophagus: A Systematic Review and Meta-Analysis. Am J Epidemiol 0: kwn121v1-kwn121 [Full text]  
• Ochs, N., Auer, R., Bauer, D. C., Nanchen, D., Gussekloo, J., Cornuz, J., Rodondi, N. (2008). Meta-analysis: Subclinical Thyroid Dysfunction and the Risk for Coronary Heart Disease and Mortality. ANN INTERN MED 148: 832-845 [Abstract] [Full text]  
• Higgins, J. P., White, I. R, Wood, A. M (2008). Imputation methods for missing outcome data in meta-analysis of clinical trials. Clin Trials 5: 225-239 [Abstract]  
• Salanti, G., Higgins, J. P., Ades, A., Ioannidis, J. P. (2008). Evaluation of networks of randomized trials. Stat Methods Med Res 17: 279-301 [Abstract]  
• Chong, E. W-T., Kreis, A. J., Wong, T. Y., Simpson, J. A., Guymer, R. H. (2008). Dietary {omega}-3 Fatty Acid and Fish Intake in the Primary Prevention of Age-Related Macular Degeneration: A Systematic Review and Meta-analysis. Arch Ophthalmol 126: 826-833 [Abstract] [Full text]  
• Duffield, T. F., Rabiee, A. R., Lean, I. J. (2008). A Meta-Analysis of the Impact of Monensin in Lactating Dairy Cattle. Part 3. Health and Reproduction. J DAIRY SCI 91: 2328-2341 [Abstract] [Full text]  
• Lau, J T F, Choi, K C, Tsui, H Y, Zhang, L, Zhang, J, Lan, Y, Zhang, Y, Wang, N, Cheng, F, Gu, J (2008). Changes in HIV-related behaviours over time and associations with rates of HIV-related services coverage among female sex workers in Sichuan, China. Sex. Transm. Infect. 84: 212-216 [Abstract] [Full text]  
• Dahabreh, I. J., Linardou, H., Siannis, F., Fountzilas, G., Murray, S. (2008). Trastuzumab in the Adjuvant Treatment of Early-Stage Breast Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. The Oncologist 13: 620-630 [Abstract] [Full text]  
• Canonico, M., Plu-Bureau, G., Lowe, G. D O, Scarabin, P.-Y. (2008). Hormone replacement therapy and risk of venous thromboembolism in postmenopausal women: systematic review and meta-analysis. BMJ 336: 1227-1231 [Abstract] [Full text]  
• Natanson, C., Kern, S. J., Lurie, P., Banks, S. M., Wolfe, S. M. (2008). Cell-Free Hemoglobin-Based Blood Substitutes and Risk of Myocardial Infarction and Death: A Meta-analysis. JAMA 299: 2304-2312 [Abstract] [Full text]  
• Meta-Analysis Research Group in Echocardiography (, (2008). Independent Prognostic Importance of a Restrictive Left Ventricular Filling Pattern After Myocardial Infarction: An Individual Patient Meta-Analysis: Meta-Analysis Research Group in Echocardiography Acute Myocardial Infarction. Circulation 117: 2591-2598 [Abstract] [Full text]  
• Chapman, K., Takahashi, A., Meulenbelt, I., Watson, C., Rodriguez-Lopez, J., Egli, R., Tsezou, A., Malizos, K. N., Kloppenburg, M., Shi, D., Southam, L., van der Breggen, R., Donn, R., Qin, J., Doherty, M., Slagboom, P. E., Wallis, G., Kamatani, N., Jiang, Q., Gonzalez, A., Loughlin, J., Ikegawa, S. (2008). A meta-analysis of European and Asian cohorts reveals a global role of a functional SNP in the 5' UTR of GDF5 with osteoarthritis susceptibility. Hum Mol Genet 17: 1497-1504 [Abstract] [Full text]  
• Krebs, E. E., Gaynes, B. N., Gartlehner, G., Hansen, R. A., Thieda, P., Morgan, L. C., DeVeaugh-Geiss, A., Lohr, K. N. (2008). Treating the Physical Symptoms of Depression With Second-Generation Antidepressants: A Systematic Review and Metaanalysis. Psychosomatics 49: 191-198 [Abstract] [Full text]  
• Baker, W. L., White, C. M., Coleman, C. I. (2008). Effect of Nonergot Dopamine Agonists on Symptoms of Restless Legs Syndrome. Ann Fam Med 6: 253-262 [Abstract] [Full text]  
• Rodrigo, G. J., Nannini, L. J., Rodriguez-Roisin, R. (2008). Safety of Long-Acting {beta}-Agonists in Stable COPD: A Systematic Review. Chest 133: 1079-1087 [Abstract] [Full text]  
• Elamin, M. B., Murad, M. H., Mullan, R., Erickson, D., Harris, K., Nadeem, S., Ennis, R., Erwin, P. J., Montori, V. M. (2008). Accuracy of Diagnostic Tests for Cushing's Syndrome: A Systematic Review and Metaanalyses. J. Clin. Endocrinol. Metab. 93: 1553-1562 [Abstract] [Full text]  
• Shah, N. R., Jones, J. B., Aperi, J., Shemtov, R., Karne, A., Borenstein, J. (2008). Selective Serotonin Reuptake Inhibitors for Premenstrual Syndrome and Premenstrual Dysphoric Disorder: A Meta-Analysis. Obstet Gynecol 111: 1175-1182 [Abstract] [Full text]  
• Testa, L., van Gaal, W.J., Biondi-Zoccai, G.G.L., Abbate, A., Agostoni, P., Bhindi, R., Banning, A.P. (2008). Repeat thrombolysis or conservative therapy vs. rescue percutaneous coronary intervention for failed thrombolysis: systematic review and meta-analysis. QJM 101: 387-395 [Abstract] [Full text]  
• Vercammen, M.J., Verloes, A., Van de Velde, H., Haentjens, P. (2008). Accuracy of soluble human leukocyte antigen-G for predicting pregnancy among women undergoing infertility treatment: meta-analysis. Hum Reprod Update 14: 209-218 [Abstract] [Full text]  
• Freathy, R. M., Timpson, N. J., Lawlor, D. A., Pouta, A., Ben-Shlomo, Y., Ruokonen, A., Ebrahim, S., Shields, B., Zeggini, E., Weedon, M. N., Lindgren, C. M., Lango, H., Melzer, D., Ferrucci, L., Paolisso, G., Neville, M. J., Karpe, F., Palmer, C. N.A., Morris, A. D., Elliott, P., Jarvelin, M.-R., Davey Smith, G., McCarthy, M. I., Hattersley, A. T., Frayling, T. M. (2008). Common Variation in the FTO Gene Alters Diabetes-Related Metabolic Traits to the Extent Expected Given Its Effect on BMI. Diabetes 57: 1419-1426 [Abstract] [Full text]  
• Barbui, C., Signoretti, A., Mule, S., Boso, M., Cipriani, A. (2008). Does the Addition of a Second Antipsychotic Drug Improve Clozapine Treatment?. Schizophr Bull 0: sbn030v1-sbn030 [Abstract] [Full text]  
• Sud, S. MD, Sud, M. BSc, Friedrich, J. O. MD DPhil, Adhikari, N. K.J. MDCM MSc (2008). Effect of mechanical ventilation in the prone position on clinical outcomes in patients with acute hypoxemic respiratory failure: a systematic review and meta-analysis. CMAJ 178: 1153-1161 [Abstract] [Full text]  
• Correll, C. U., Rummel-Kluge, C., Corves, C., Kane, J. M., Leucht, S. (2008). Antipsychotic Combinations vs Monotherapy in Schizophrenia: A Meta-analysis of Randomized Controlled Trials. Schizophr Bull 0: sbn018v2-sbn018 [Abstract] [Full text]  
• Patsopoulos, N. A, Evangelou, E., Ioannidis, J. P. (2008). Sensitivity of between-study heterogeneity in meta-analysis: proposed metrics and empirical evaluation. Int J Epidemiol 0: dyn065v1-dyn065 [Abstract] [Full text]  
• Zohlnhofer, D., Dibra, A., Koppara, T., de Waha, A., Ripa, R. S., Kastrup, J., Valgimigli, M., Schomig, A., Kastrati, A. (2008). Stem Cell Mobilization by Granulocyte Colony-Stimulating Factor for Myocardial Recovery After Acute Myocardial Infarction: A Meta-Analysis. J Am Coll Cardiol 51: 1429-1437 [Abstract] [Full text]  
• Gilbody, S. DPhil, Sheldon, T. DSc, House, A. DM (2008). Screening and case-finding instruments for depression: a meta-analysis. CMAJ 178: 997-1003 [Abstract] [Full text]  
• Vescio, M F, Longo, B, Babudieri, S, Starnini, G, Carbonara, S, Rezza, G, Monarca, R (2008). Correlates of hepatitis C virus seropositivity in prison inmates: a meta-analysis. J. Epidemiol. Community Health 62: 305-313 [Abstract] [Full text]  
• Dahabreh, I. J (2008). Meta-analysis of rare events: an update and sensitivity analysis of cardiovascular events in randomized trials of rosiglitazone. Clin Trials 5: 116-120 [Abstract]  
• Bollen, A.-M., Cunha-Cruz, J., Bakko, D. W., Huang, G. J., Hujoel, P. P. (2008). The Effects of Orthodontic Therapy on Periodontal Health: A Systematic Review of Controlled Evidence. Journal of the American Dental Association 139: 413-422 [Abstract] [Full text]  
• Meilink, A., Hemmen, B., Seelen, H., Kwakkel, G. (2008). Impact of EMG-triggered neuromuscular stimulation of the wrist and finger extensors of the paretic hand after stroke: a systematic review of the literature. Clin Rehabil 22: 291-305 [Abstract]  
• Duffield, T. F., Rabiee, A. R., Lean, I. J. (2008). A Meta-Analysis of the Impact of Monensin in Lactating Dairy Cattle. Part 1. Metabolic Effects. J DAIRY SCI 91: 1334-1346 [Abstract] [Full text]  
• Duffield, T. F., Rabiee, A. R., Lean, I. J. (2008). A Meta-Analysis of the Impact of Monensin in Lactating Dairy Cattle. Part 2. Production Effects. J DAIRY SCI 91: 1347-1360 [Abstract] [Full text]  
• Blozik, E., Scherer, M. (2008). Skin Replacement Therapies for Diabetic Foot Ulcers: Systematic review and meta-analysis. Diabetes Care 31: 693-694 [Full text]  
• Garcia, A. M, Sisternas, A., Hoyos, S. P. (2008). Occupational exposure to extremely low frequency electric and magnetic fields and Alzheimer disease: a meta-analysis. Int J Epidemiol 37: 329-340 [Abstract] [Full text]  
• Carlsten, C., Sagoo, G. S., Frodsham, A. J., Burke, W., Higgins, J. P. T. (2008). Glutathione S-Transferase M1 (GSTM1) Polymorphisms and Lung Cancer: A Literature-based Systematic HuGE Review and Meta-Analysis. Am J Epidemiol 167: 759-774 [Abstract] [Full text]  
• Karageorgopoulos, D. E. MD, Giannopoulou, K. P. MD, Grammatikos, A. P. MD MSc, Dimopoulos, G. MD, Falagas, M. E. MD DSc (2008). Fluoroquinolones compared with {beta}-lactam antibiotics for the treatment of acute bacterial sinusitis: a meta-analysis of randomized controlled trials. CMAJ 178: 845-854 [Abstract] [Full text]  
• Horvath, K., Jeitler, K., Siering, U., Stich, A. K., Skipka, G., Gratzer, T. W., Siebenhofer, A. (2008). Long-term Effects of Weight-Reducing Interventions in Hypertensive Patients: Systematic Review and Meta-analysis. Arch Intern Med 168: 571-580 [Abstract] [Full text]  
• Bennet, A., Di Angelantonio, E., Erqou, S., Eiriksdottir, G., Sigurdsson, G., Woodward, M., Rumley, A., Lowe, G. D. O., Danesh, J., Gudnason, V. (2008). Lipoprotein(a) Levels and Risk of Future Coronary Heart Disease: Large-Scale Prospective Data. Arch Intern Med 168: 598-608 [Abstract] [Full text]  
• Strippoli, G. F M, Navaneethan, S. D, Johnson, D. W, Perkovic, V., Pellegrini, F., Nicolucci, A., Craig, J. C (2008). Effects of statins in patients with chronic kidney disease: meta-analysis and meta-regression of randomised controlled trials. BMJ 336: 645-651 [Abstract] [Full text]  
• van Meurs, J. B. J., Trikalinos, T. A., Ralston, S. H., Balcells, S., Brandi, M. L., Brixen, K., Kiel, D. P., Langdahl, B. L., Lips, P., Ljunggren, O., Lorenc, R., Obermayer-Pietsch, B., Ohlsson, C., Pettersson, U., Reid, D. M., Rousseau, F., Scollen, S., Van Hul, W., Agueda, L., Akesson, K., Benevolenskaya, L. I., Ferrari, S. L., Hallmans, G., Hofman, A., Husted, L. B., Kruk, M., Kaptoge, S., Karasik, D., Karlsson, M. K., Lorentzon, M., Masi, L., McGuigan, F. E. A., Mellstrom, D., Mosekilde, L., Nogues, X., Pols, H. A. P., Reeve, J., Renner, W., Rivadeneira, F., van Schoor, N. M., Weber, K., Ioannidis, J. P. A., Uitterlinden, A. G., for the GENOMOS Study, (2008). Large-Scale Analysis of Association Between LRP5 and LRP6 Variants and Osteoporosis. JAMA 299: 1277-1290 [Abstract] [Full text]  
• Wilt, T. J., MacDonald, R., Rutks, I., Shamliyan, T. A., Taylor, B. C., Kane, R. L. (2008). Systematic Review: Comparative Effectiveness and Harms of Treatments for Clinically Localized Prostate Cancer. ANN INTERN MED 148: 435-448 [Abstract] [Full text]  
• Broadbent, H. M., Peden, J. F., Lorkowski, S., Goel, A., Ongen, H., Green, F., Clarke, R., Collins, R., Franzosi, M. G., Tognoni, G., Seedorf, U., Rust, S., Eriksson, P., Hamsten, A., Farrall, M., Watkins, H., for the PROCARDIS consortium, (2008). Susceptibility to coronary artery disease and diabetes is encoded by distinct, tightly linked SNPs in the ANRIL locus on chromosome 9p. Hum Mol Genet 17: 806-814 [Abstract] [Full text]  
• Manheimer, E., Zhang, G., Udoff, L., Haramati, A., Langenberg, P., Berman, B. M, Bouter, L. M (2008). Effects of acupuncture on rates of pregnancy and live birth among women undergoing in vitro fertilisation: systematic review and meta-analysis. BMJ 336: 545-549 [Abstract] [Full text]  
• Wang, F., Chang, D., Hu, F.-l., Sui, H., Han, B., li, D.-d., Zhao, Y.-s. (2008). DNA Repair Gene XPD Polymorphisms and Cancer Risk: A Meta-analysis Based on 56 Case-Control Studies. Cancer Epidemiol. Biomarkers Prev. 17: 507-517 [Abstract] [Full text]  
• Ranucci, M., Isgro, G., Soro, G., Conti, D., De Toffol, B. (2008). Efficacy and Safety of Recombinant Activated Factor VII in Major Surgical Procedures: Systematic Review and Meta-analysis of Randomized Clinical Trials. Arch Surg 143: 296-304 [Abstract] [Full text]  
• Penagos, M., Passalacqua, G., Compalati, E., Baena-Cagnani, C. E., Orozco, S., Pedroza, A., Canonica, G. W. (2008). Metaanalysis of the Efficacy of Sublingual Immunotherapy in the Treatment of Allergic Asthma in Pediatric Patients, 3 to 18 Years of Age. Chest 133: 599-609 [Abstract] [Full text]  
• Smith, B. R., Blumstein, D. T. (2008). Fitness consequences of personality: a meta-analysis. Behav Ecol 19: 448-455 [Abstract] [Full text]  
• Cronin, P., Dwamena, B. A., Kelly, A. M., Carlos, R. C. (2008). Solitary Pulmonary Nodules: Meta-analytic Comparison of Cross-sectional Imaging Modalities for Diagnosis of Malignancy. Radiology 246: 772-782 [Abstract] [Full text]  
• Josan, K. MD, Majumdar, S. R. MD MPH, McAlister, F. A. MD MSc (2008). The efficacy and safety of intensive statin therapy: a meta-analysis of randomized trials. CMAJ 178: 576-584 [Abstract] [Full text]  
• Pannu, N., Klarenbach, S., Wiebe, N., Manns, B., Tonelli, M., for the Alberta Kidney Disease Network, (2008). Renal Replacement Therapy in Patients With Acute Renal Failure: A Systematic Review. JAMA 299: 793-805 [Abstract] [Full text]  
• Kelly, A. M., Dwamena, B., Cronin, P., Bernstein, S. J., Carlos, R. C. (2008). Meta-analysis: Effectiveness of Drugs for Preventing Contrast-Induced Nephropathy. ANN INTERN MED 148: 284-294 [Abstract] [Full text]  
• Nygren, P., Fu, R., Freeman, M., Bougatsos, C., Klebanoff, M., Guise, J.-M. (2008). Evidence on the Benefits and Harms of Screening and Treating Pregnant Women Who Are Asymptomatic for Bacterial Vaginosis: An Update Review for the U.S. Preventive Services Task Force. ANN INTERN MED 148: 220-233 [Abstract] [Full text]  
• Griffin, S.O., Oong, E., Kohn, W., Vidakovic, B., Gooch, B.F., CDC Dental Sealant Systematic Review Work Group, , Bader, J., Clarkson, J., Fontana, M.R., Meyer, D.M., Rozier, R.G., Weintraub, J.A., Zero, D.T. (2008). The Effectiveness of Sealants in Managing Caries Lesions. J. Dent. Res. 87: 169-174 [Abstract] [Full text]  
• Weischer, M., Bojesen, S. E., Ellervik, C., Tybjaerg-Hansen, A., Nordestgaard, B. G. (2008). CHEK2*1100delC Genotyping for Clinical Assessment of Breast Cancer Risk: Meta-Analyses of 26,000 Patient Cases and 27,000 Controls. JCO 26: 542-548 [Abstract] [Full text]  
• van Rijen, M. M. L., Bonten, M., Wenzel, R. P., Kluytmans, J. A. J. W. (2008). Intranasal mupirocin for reduction of Staphylococcus aureus infections in surgical patients with nasal carriage: a systematic review. J Antimicrob Chemother 61: 254-261 [Abstract] [Full text]  
• Koopman, L., Hoes, A. W., Glasziou, P. P., Appelman, C. L., Burke, P., McCormick, D. P., Damoiseaux, R. A., Le Saux, N., Rovers, M. M. (2008). Antibiotic Therapy to Prevent the Development of Asymptomatic Middle Ear Effusion in Children With Acute Otitis Media: A Meta-analysis of Individual Patient Data. Arch Otolaryngol Head Neck Surg 134: 128-132 [Abstract] [Full text]  
• Zemek, R. L., Bhogal, S. K., Ducharme, F. M. (2008). Systematic Review of Randomized Controlled Trials Examining Written Action Plans in Children: What Is the Plan?. Arch Pediatr Adolesc Med 162: 157-163 [Abstract] [Full text]  
• Hegedus, E J, Goode, A, Campbell, S, Morin, A, Tamaddoni, M, Moorman, C T III, Cook, C (2008). Physical examination tests of the shoulder: a systematic review with meta-analysis of individual tests. Br. J. Sports. Med. 42: 80-92 [Abstract] [Full text]  
• Ioannidis, J. P., Boffetta, P., Little, J., O'Brien, T. R, Uitterlinden, A. G, Vineis, P., Balding, D. J, Chokkalingam, A., Dolan, S. M, Flanders, W D., Higgins, J. P., McCarthy, M. I, McDermott, D. H, Page, G. P, Rebbeck, T. R, Seminara, D., Khoury, M. J (2008). Assessment of cumulative evidence on genetic associations: interim guidelines. Int J Epidemiol 37: 120-132 [Abstract] [Full text]  
• Barbui, C. MD, Furukawa, T. A. MD, Cipriani, A. MD (2008). Effectiveness of paroxetine in the treatment of acute major depression in adults: a systematic re-examination of published and unpublished data from randomized trials. CMAJ 178: 296-305 [Abstract] [Full text]  
• Jenkins, D. J.A. MD PhD, Josse, A. R. MSc, Beyene, J. PhD, Dorian, P. MD MSc, Burr, M. L. MD DSc (Me, LaBelle, R. BSc, Kendall, C. W.C. PhD, Cunnane, S. C. PhD (2008). Fish-oil supplementation in patients with implantable cardioverter defibrillators: a meta-analysis. CMAJ 178: 157-164 [Abstract] [Full text]  
• Smith, L., Watson, M., Gates, S., Ball, D., Foxcroft, D. (2008). Meta-Analysis of the Association of the Taq1A Polymorphism with the Risk of Alcohol Dependency: A HuGE Gene-Disease Association Review. Am J Epidemiol 167: 125-138 [Abstract] [Full text]  
• Jefferson, T., Foxlee, R., Mar, C. D., Dooley, L., Ferroni, E., Hewak, B., Prabhala, A., Nair, S., Rivetti, A. (2008). Physical interventions to interrupt or reduce the spread of respiratory viruses: systematic review. BMJ 336: 77-80 [Abstract] [Full text]  
• Dekkers, O. M., Biermasz, N. R., Pereira, A. M., Romijn, J. A., Vandenbroucke, J. P. (2008). Mortality in Acromegaly: A Metaanalysis. J. Clin. Endocrinol. Metab. 93: 61-67 [Abstract] [Full text]  
• Arbyn, M., Bergeron, C., Klinkhamer, P., Martin-Hirsch, P., Siebers, A. G., Bulten, J. (2008). Liquid Compared With Conventional Cervical Cytology: A Systematic Review and Meta-analysis. Obstet Gynecol 111: 167-177 [Abstract] [Full text]  
• Cosgrove, M. P., Sargeant, L. A., Griffin, S. J. (2008). Does depression increase the risk of developing type 2 diabetes?. Occup Med (Lond) 58: 7-14 [Abstract] [Full text]  
• Beynon, S., Soares-Weiser, K., Woolacott, N., Duffy, S., Geddes, J. R. (2008). Psychosocial interventions for the prevention of relapse in bipolar disorder: systematic review of controlled trials. Br. J. Psychiatry 192: 5-11 [Abstract] [Full text]  

Rapid Responses:

Read all Rapid Responses

I2 Is Subject to the Same Statistical Power Problems as Cochran's Q

Tania Huedo-Medina, et al.
bmj.com, 4 Jan 2007 [Full text]

A better method of dealing with inconsistency in meta-analyses

Suhail Doi
bmj.com, 4 Jan 2008 [Full text]