Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a network meta-analysis
Abstract Background In network meta-analysis, estimation of a comparative effect can be performed for treatments that are connected either directly or indirectly. However, disconnected trial networks may arise, which poses a challenge to comparing all available treatments of interest. Several modeli...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2023-04-01
|
| Series: | BMC Medical Research Methodology |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12874-023-01896-7 |
| _version_ | 1797849974152626176 |
|---|---|
| author | Lauren McKeen Paul Morris Chong Wang Max D. Morris Annette M. O’Connor |
| author_facet | Lauren McKeen Paul Morris Chong Wang Max D. Morris Annette M. O’Connor |
| author_sort | Lauren McKeen |
| collection | DOAJ |
| description | Abstract Background In network meta-analysis, estimation of a comparative effect can be performed for treatments that are connected either directly or indirectly. However, disconnected trial networks may arise, which poses a challenge to comparing all available treatments of interest. Several modeling approaches attempt to compare treatments from disconnected networks but not without strong assumptions and limitations. Conducting a new trial to connect a disconnected network can enable calculation of all treatment comparisons and help researchers maximize the value of the existing networks. Here, we develop an approach to finding the best connecting trial given a specific comparison of interest. Methods We present formulas to quantify the variation in the estimation of a particular comparative effect of interest for any possible connecting two-arm trial. We propose a procedure to identify the optimal connecting trial that minimizes this variation in effect estimation. Results We show that connecting two treatments indirectly might be preferred to direct connection through a new trial, by leveraging information from the existing disconnected networks. Using a real network of studies on the use of vaccines in the treatment of bovine respiratory disease (BRD), we illustrate a procedure to identify the best connecting trial and confirm our findings via simulation. Conclusion Researchers wishing to conduct a connecting two-arm study can use the procedure provided here to identify the best connecting trial. The choice of trial that minimizes the variance of a comparison of interest is network dependent and it is possible that connecting treatments indirectly may be preferred to direct connection. |
| first_indexed | 2024-04-09T18:53:57Z |
| format | Article |
| id | doaj.art-83b1f3562cdf44ca931556faeee1d486 |
| institution | Directory Open Access Journal |
| issn | 1471-2288 |
| language | English |
| last_indexed | 2024-04-09T18:53:57Z |
| publishDate | 2023-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Research Methodology |
| spelling | doaj.art-83b1f3562cdf44ca931556faeee1d4862023-04-09T11:20:01ZengBMCBMC Medical Research Methodology1471-22882023-04-0123111310.1186/s12874-023-01896-7Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a network meta-analysisLauren McKeen0Paul Morris1Chong Wang2Max D. Morris3Annette M. O’Connor4Department of Statistics, Iowa State UniversityDepartment of Statistics, Iowa State UniversityDepartment of Statistics, Iowa State UniversityDepartment of Statistics, Iowa State UniversityDepartment of Veterinary Diagnostic and Production Animal Medicine, Iowa State UniversityAbstract Background In network meta-analysis, estimation of a comparative effect can be performed for treatments that are connected either directly or indirectly. However, disconnected trial networks may arise, which poses a challenge to comparing all available treatments of interest. Several modeling approaches attempt to compare treatments from disconnected networks but not without strong assumptions and limitations. Conducting a new trial to connect a disconnected network can enable calculation of all treatment comparisons and help researchers maximize the value of the existing networks. Here, we develop an approach to finding the best connecting trial given a specific comparison of interest. Methods We present formulas to quantify the variation in the estimation of a particular comparative effect of interest for any possible connecting two-arm trial. We propose a procedure to identify the optimal connecting trial that minimizes this variation in effect estimation. Results We show that connecting two treatments indirectly might be preferred to direct connection through a new trial, by leveraging information from the existing disconnected networks. Using a real network of studies on the use of vaccines in the treatment of bovine respiratory disease (BRD), we illustrate a procedure to identify the best connecting trial and confirm our findings via simulation. Conclusion Researchers wishing to conduct a connecting two-arm study can use the procedure provided here to identify the best connecting trial. The choice of trial that minimizes the variance of a comparison of interest is network dependent and it is possible that connecting treatments indirectly may be preferred to direct connection.https://doi.org/10.1186/s12874-023-01896-7Network meta-analysisClinical trial designEvidence synthesis |
| spellingShingle | Lauren McKeen Paul Morris Chong Wang Max D. Morris Annette M. O’Connor Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a network meta-analysis BMC Medical Research Methodology Network meta-analysis Clinical trial design Evidence synthesis |
| title | Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a network meta-analysis |
| title_full | Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a network meta-analysis |
| title_fullStr | Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a network meta-analysis |
| title_full_unstemmed | Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a network meta-analysis |
| title_short | Connecting a disconnected trial network with a new trial: optimizing the estimation of a comparative effect in a network meta-analysis |
| title_sort | connecting a disconnected trial network with a new trial optimizing the estimation of a comparative effect in a network meta analysis |
| topic | Network meta-analysis Clinical trial design Evidence synthesis |
| url | https://doi.org/10.1186/s12874-023-01896-7 |
| work_keys_str_mv | AT laurenmckeen connectingadisconnectedtrialnetworkwithanewtrialoptimizingtheestimationofacomparativeeffectinanetworkmetaanalysis AT paulmorris connectingadisconnectedtrialnetworkwithanewtrialoptimizingtheestimationofacomparativeeffectinanetworkmetaanalysis AT chongwang connectingadisconnectedtrialnetworkwithanewtrialoptimizingtheestimationofacomparativeeffectinanetworkmetaanalysis AT maxdmorris connectingadisconnectedtrialnetworkwithanewtrialoptimizingtheestimationofacomparativeeffectinanetworkmetaanalysis AT annettemoconnor connectingadisconnectedtrialnetworkwithanewtrialoptimizingtheestimationofacomparativeeffectinanetworkmetaanalysis |