Inspect the data representation shown below.
10.1. What form of data representation is depicted here?
10.2. With respect to the study plots what is represented by:
10.3. From the data depicted what could be inferred with regard to the effectiveness of the treatment under investigation?
10.4. What further information relating to the performance of this analysis would you require in order to gauge the accuracy of the conclusions?
10.1. What form of data representation is depicted here?
Forest Plot or Meta Analysis Graph
10.2. With respect to the study plots what is represented by: The horizontal lines?
The position of the square? The size of the square?
The position of the square and the horizontal line indicate the point estimate and the 95%
confidence intervals of the odds ratio respectively. The size of the square indicates the weight of the study.
10.3. From the data depicted what could be inferred with regard to the effectiveness of the treatment under investigation?
The depicted data suggest the treatment is not more effective than control as the 95% confidence limits of the combined odds ratio cross the vertical line.
10.4. What further information relating to the performance of this analysis would you require in order to gauge the accuracy of the conclusions?
Definition of inclusion criteria for studies
Adequate search protocol
Assessment of methodological quality
Measurement of heterogeneity
Assessment of publication bias
This topic is explored in LITFL, where they call it a "forrest plot", perhaps out of respect for Pat Forrest. This is substantially better than Wikipedia, where this form of data representation is referred to as a blobbogram. The example LITFL use for their explanation is derived from the college question.
Anyway. The college answer is correct but very brief, and probably represents something like the "passing grade" for this 10-mark question. With that in mind, and free from the need to be concise, one can launch into an exhaustingly verbose dissection of this question.
10.1 - This is a forest plot. It represents the results of a meta-analysis of studies.
10.2 - The standards for labelling and graphical representation are well summarised by this Cochrane document (however, it appears that careful adherence to standards is no defence against the absence of useful content).
10.3 - From the forest plot, one can infer that though statistically there is a trend towards a positive treatment effect, it still does not achieve statistical significance because the range of the 95% confidence interval for their odds ratio crosses the vertical line (the vertical line being an OR of 1.0, which means "no association"). Thus, on the basis of this meta-analysis one would be forced to conclude that the treatment has no effect.
10.4 - "What further information relating to the performance of this analysis would you require in order to gauge the accuracy of the conclusions?" This is a thinly veiled question about the assessment of the validity of a meta-analysis. The college answer demonstrates this in the points they used. In that context, one would theoretically be interested in every aspect of the analysis.
Generic points in the assessment of validity of a meta-analysis include the following:
If one were to only consider the presented graph, one would be more likely to respond with relevant questions for the meta-analysis authors.
Schriger, David L., et al. "Forest plots in reports of systematic reviews: a cross-sectional study reviewing current practice." International journal of epidemiology39.2 (2010): 421-429.
Lewis, Steff, and Mike Clarke. "Forest plots: trying to see the wood and the trees." Bmj 322.7300 (2001): 1479-1480.
Anzures‐Cabrera, Judith, and Julian Higgins. "Graphical displays for meta‐analysis: An overview with suggestions for practice." Research Synthesis Methods 1.1 (2010): 66-80.
Cochrane: "Considerations and recommendations for
figures in Cochrane reviews: graphs of statistical data" 4 December 2003 (updated 27 February 2008)
Reade, Michael C., et al. "Bench-to-bedside review: Avoiding pitfalls in critical care meta-analysis–funnel plots, risk estimates, types of heterogeneity, baseline risk and the ecologic fallacy." Critical Care 12.4 (2008): 220.
DerSimonian, Rebecca, and Nan Laird. "Meta-analysis in clinical trials."Controlled clinical trials 7.3 (1986): 177-188.
Biggerstaff, B. J., and R. L. Tweedie. "Incorporating variability in estimates of heterogeneity in the random effects model in meta-analysis." Statistics in medicine 16.7 (1997): 753-768.
The Cochrane Handbook: 9.5.4 "Incorporating heterogeneity into random-effects model"