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Academia and the Profession |

Exploring the Geometry of Treatment Networks

Georgia Salanti, PhD; Fotini K. Kavvoura, MD; and John P.A. Ioannidis, MD
[+] Article and Author Information

From the University of Ioannina School of Medicine, Ioannina, Greece, and Tufts University School of Medicine, Boston, Massachusetts.


Grant Support: Dr. Kavvoura was funded by a PENED grant, co-financed by the European Union and the Greek Ministry of Development-General Secretariat of Research and Technology.

Potential Financial Conflicts of Interest: None disclosed.

Requests for Single Reprints: John P.A. Ioannidis, MD, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece; e-mail, jioannid@cc.uoi.gr.

Current Author Addresses: Drs. Salanti, Kavvoura, and Ioannidis: Clinical Trials and Evidence-Based Medicine Unit, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina 45110, Greece.


Ann Intern Med. 2008;148(7):544-553. doi:10.7326/0003-4819-148-7-200804010-00011
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Background: Several treatment options exist for many conditions. Randomized trial evidence on the relative merits of various options may be missing or biased.

Purpose: To examine the patterns of trial evidence (network geometry) and explain their implications for the interpretation of the existing evidence on a treatment's relative effectiveness.

Data Sources: PubMed and Thompson ISI Web of Knowledge (last search April 2007).

Study Selection: Published networks of randomized trials that included at least 4 treatments were identified.

Data Extraction: For each network, data on the number of studies per treatment comparison were extracted by one investigator and verified by a second investigator.

Data Synthesis: Indices were adopted from the ecological literature that measure diversity (number of treatments and how often they were tested) and co-occurrence (whether some treatment comparisons were preferred and others avoided). Eighteen eligible treatment networks were identified for different diseases, involving 4 to 16 alternative treatments and 10 to 84 trials. Networks in which 1 option (placebo or no treatment) was the typical comparator were star-shaped, even though several treatments might have had proven effectiveness. Other networks had different shapes. Some showed important co-occurrence that avoided specific head-to-head comparisons. Comparison choices sometimes seemed justified, such as when newer treatments were not compared with older ones already shown to be inferior, whereas other choices seemed to reflect preference bias.

Limitations: Networks evolve over time as new trials accumulate, and their geometry may change. Statistical testing for co-occurrence is underpowered when few trials exist.

Conclusion: Evaluation of the geometry of a treatment network can offer valuable insights for the interpretation of total evidence when many treatment options are available.

Figures

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Figure 1.
Eligible treatment networks.

Shaded nodes indicate placebo or no active treatment. The thickness of the lines is proportional to the number of trials addressing each specific comparison. A. Star-shaped networks. B. Non–star-shaped networks with limited diversity and significant co-occurrence. C. Non–star-shaped networks with limited diversity and nonsignificant co-occurrence. D. Networks with considerable diversity and significant co-occurrence. E. Networks with considerable diversity and nonsignificant co-occurrence. ACE-i = angiotensin-converting enzyme inhibitor; AES = actinomycin D–eluting stents; ARB = angiotensin-receptor blocker; BMS = bare-metal stents; CCB = calcium-channel blockers; EES = everolimus-eluting stents; GART = genotypic antiretroviral resistance testing; ip = intraperitoneal; MES = mycophenolate-eluting stents; PART = phenotypic antiretroviral resistance testing; PES = paclitaxel-eluting stents; SES = sirolimus-eluting stents; TP = trimethoprim and polymyxin; t-PA = tissue plasminogen activator; TSP = trimethoprim, sulfacetamide, polymyxin; vPART = virtual phenotypic antiretroviral resistance testing.

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Figure 2.
Distribution of checkerboard units for all possible comparisons.

Treatment comparisons are shown in order of decreasing checkerboard units. Top. First-line antihypertensive therapy. Bottom. Chemotherapy for ovarian cancer. ACE = angiotensin-converting enzyme; ARB = angiotensin-receptor blocker; CCB = calcium-channel blocker; ip = intraperitoneal.

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Appendix Figure.
Simulated network geometries.

Each diagram represents a hypothetical network in which only 4 treatments have been studied. Top. Symmetric polygonal network in which all treatments are compared in 2-group trials. Middle. Linear network. Bottom. Star-shaped network.

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