meta-analysis: an introduction george a. kelley, da, facsm school of medicine, dept. of community...

Meta-Analysis: An Introduction

George A. Kelley, DA, FACSMSchool of Medicine,

Dept. of Community Medicine,

West Virginia University,

Morgantown, WV

Bio Funding Publications

Interest and Excitement for Meta-Analysis

Proliferation of information on health-related disease

Need to try and “make sense out of nonsense”

Enjoyment for combining and analyzing data

Learning Objectives

Identify what meta-analysis isIdentify the advantages and

different types of meta-analysesIdentify the steps for conducting a

meta-analysis of summary data

Performance Objectives

Define meta-analysisList and describe the advantages

and types of meta-analyses List and describe the steps

necessary for conducting a meta-analysis of summary data

Major Topics Covered

I. Overview of Meta-Analysis

II. Steps for Conducting A Meta-Analysis

I. Overview of Meta-Analysis

A. Meta-Analysis Defined

B. Advantages of Meta-Analysis

C. Types of Meta-Analyses

A. Meta-Analysis – Combining the results from many studies dealing with the same topic.

B. Advantages of Meta-Analysis

1. Study question specific & narrow

2. Data collection comprehensive & specific

3. Study selection based on uniformly applied criteria

4. Data synthesis quantitative

C. Types of Meta-Analyses

1. Summary Data

2. Individual Patient Data

II. Steps for Conducting A Meta-Analysis

A. Data SourcesB. Study SelectionC. Data AbstractionD. Statistical Analysis

A. Data Sources

1. Computer searches

2. Cross-referencing

3. Hand-searching

4. Expert(s) to review list

Data Sources-Example

- Computer searches (Medline, Embase, Sport Discus, Current Contents, Dissertation Abstracts)

- Cross-referencing from review and original articles

- Experts to review list (Drs. James Hagberg & Doug Seals)

B. Study Selection

1. Study designs2. Subjects3. Publication types4. Languages5. Interventions6. Time Frame

Study Selection-Example

- RCTs or CTs with a nonexercise control group

- Progressive resistance training as the only mode of training

- Females > 18 years of age- Journal articles, dissertations, &

masters theses published in English

Study Selection (cont.)

• Studies published & indexed between January 1966 and December 1998

• Bone mineral density assessed at femur, spine, and/or radius

• Training studies > 16 weeks

C. Data Abstraction

1. Number of items coded2. Inter-coder bias3. Items coded

Data Abstraction – Example

242 possible items coded Data independently abstracted

by first two authors Every data point reviewed for

accuracy and consistency Major characteristics coded –

study, physical, exercise, primary & secondary outcomes

D. Statistical Analysis

1. Choice of metric

2. Choice of model/ heterogeneity

3. Publication bias

4. Study quality

5. Moderator analysis

1. Choice of Metric

a. Original

b. Standardized mean difference (Mean/Standard Deviation)

2. Choice of Model/ Heterogeneity

a. Fixed Effects

b. Random Effects

Metric, Model, & Heterogeneity - Example

Study N TE + SD 95% CI

1 68 -2 + 4 -3 to –1

2 92 -1 + 4 -2 to 0

3 78 -4 + 3 -5 to -3

3. Publication Biasa. Graphical methods

b. Quantitative methods

Funnel Plot - Example

0

20

40

60

80

100

120

-25 -20 -15 -10 -5 0 5 10 15 20 25

Systolic ES (mmHg)

Sam

ple

S

am

ple

S

ize

Siz

er = 0.50, p = 0.007

4. Study Quality

a. Difficult to assess

b. Interpret with caution

c. Numerous scales and checklists available

5. Moderator Analysis

a. Categorical Analysis

b. Regression Analysis

Categorical Analysis - Example

Group N + SD 95% CI Qb(p)

USA Other

17 11

-1 + 3 -4 + 4

-3 to -1 -6 to -2

4.00(0.04)*

RCT CT

7 21

-2 + 3 -2 + 4

-3 to -1 -5 to 1

0.08(0.77)

Note: RCT, randomized controlled trials, CT, controlled trials; N, number of effect sizes; * means significantly different at P<0.05

Regression - Example

Variables N r r2 r2adj SE p

IBMI, ISBP 18 0.75 0.57 0.51 3.47 0.002

Notes: IBMI means initial body mass index (kg/m2); ISBP means initial systolic blood pressure (mmHg); N means number of effect sizes.

THANKS FOR VIEWING