If you don't remember your password, you can reset it by entering your email address and clicking the Reset Password button. You will then receive an email that contains a secure link for resetting your password
If the address matches a valid account an email will be sent to __email__ with instructions for resetting your password
Recent research has examined the comparative effectiveness of nonoperative treatments for patellar tendinopathy using a network meta-analysis method. This method allows analysis of a network of clinical trials individually studying different treatment options in comparison to an eccentric exercise control; however, most treatments have not been compared head to head. Although leukocyte-rich platelet-rich plasma is statistically ranked as the treatment with the highest improvements in pain and function, concerns over the assumption of transitivity (on which network meta-analysis is based) and the lack of connection or comparisons among treatments suggest that future studies comparing treatments head to head are needed.
In the article “Comparative Effectiveness of Different Nonsurgical Treatments for Patellar Tendinopathy: A Systematic Review and Network Meta-analysis,” Chen, Wu, Huang, Chou, Wang, Yang, Siu, and Tu
conduct a thorough review of nonoperative treatments for patellar tendinopathy. Network meta-analyses are fast becoming all the rage. Whereas a traditional meta-analysis is limited to a pair-wise comparison of 2 treatments, a network meta-analysis can consider all treatment comparisons for a given problem in the same review. From a clinical perspective, this seems to be a sensible approach because patient care often involves weighing several treatment options. However, without an understanding of the concepts underlying the methodology, the findings can be easy to misinterpret.
provides great examples of these concepts. Perhaps the most useful aspect of a network meta-analysis is the graphical representation of the available evidence. Figure 1A provides a simple and hypothetical example of the “network geometry” of randomized clinical trials regarding torn tendons. Each circle, or node, represents a treatment, and the lines connecting the nodes represent which treatments have been directly compared.
In this example network, there are 8 clinical trials. Nonoperative treatment has been compared with arthroscopic repair in 6 trials and with open repair in 2. Arthroscopic repair and open repair have not been compared directly, but they share the common comparator of nonoperative treatment.
present the network in a manner that allows the strength of the evidence to be examined. Figure 1B is adapted from their review and depicts the network of trials examining the comparative effectiveness of nonoperative treatments for anterior knee pain in patients with patellar tendinopathy. From this figure, it is clear that several treatment options have been examined in clinical trials; however, aside from focused extracorporeal shock wave therapy, they are all supported by a single clinical trial. Furthermore, many of these treatments have been compared with an eccentric exercise control group rather than head to head. Given the lack of connection between the treatment nodes, inferences regarding the effectiveness of one treatment over another should be made with caution.
proceed with a statistical analysis of the data. Their thoughtful approach highlights the importance of the assumption of transitivity in a network meta-analysis. Transitivity is the idea that indirect comparisons provide a valid estimate of the unobserved head-to-head comparison.
Figure 2 illustrates the concept of transitivity. If nonoperative treatment is consistent across all clinical trials, then there may be a reasonable expectation that the patients in the nonoperative group are transitive and the net effect of arthroscopic repair can be indirectly compared with the net effect of open repair. However, if nonoperative treatment consisted of rest and over-the-counter medication in some studies and physical therapy in other studies, then the assumption of transitivity does not hold.
In the clinical trials of nonoperative treatments for patellar tendinopathy, the control group consisted of eccentric exercise training. Chen et al.
recognize that although the approach is the same, potential diversity in the protocols, including the duration, frequency, and intensity of exercise, bring into question the assumption of transitivity. Although leukocyte-rich platelet-rich plasma was statistically ranked as the treatment with the highest improvement in pain and function, questions over transitivity coupled with the lack of connection among treatment nodes indicate that future studies comparing treatments head to head are needed.
The prevalence of network meta-analyses in the literature will likely continue to increase. The concepts discussed here only scratch the surface of the inner workings of this methodology. In areas in which the network contains well-connected nodes that are transitive, a network meta-analysis can be powerful. However, when the network geometry is less connected, meaningful conclusions can still be gleaned. Chen et al.
provide a broad view of the evidence that allows the strength of the evidence to be appreciated. Furthermore, by carefully considering the assumption of transitivity, Chen et al. avoid overstating their results. It is clear from their review that several treatments have been compared with eccentric exercise in clinical trials; however, head-to-head trials are lacking. It is also clear that not every network meta-analysis needs well-connected, statistically robust networks to be informative.
The author reports the following potential conflicts of interest or sources of funding: M.P.C. receives personal fees from Arthroscopy ( Arthroscopy Association of North America ). Full ICMJE author disclosure forms are available for this article online, as supplementary material.