mtrank-package: mtrank: Brief overview

In mtrank: Ranking using Probabilistic Models and Treatment Choice Criteria

mtrank: Brief overview

Description

R package mtrank enables the estimation of treatment hierarchies in network meta-analysis using a novel frequentist approach based on treatment choice criteria (TCC) and probabilistic ranking models, as described by Evrenoglou et al. (2024). The TCC are defined using a rule based on the smallest worthwhile difference (SWD). Using the defined TCC, the NMA estimates (i.e., treatment effects and standard errors) are first transformed into treatment preferences, indicating either a treatment preference (e.g., treatment A > treatment B) or a tie (treatment A = treatment B). These treatment preferences are then synthesized using a probabilistic ranking model, which estimates the latent ability parameter of each treatment and produces the final treatment hierarchy. This parameter represents each treatments ability to outperform all the other competing treatments in the network. Here the terms "ability to outperform" indicates the propensity of each treatment to yield clinically important and beneficial effects when compared to all the other treatments in the network. Consequently, larger ability estimates indicate higher positions in the ranking list.

Details

The R package mtrank provides the following functions:

• Function tcc defines the TCC and produces a treatment preference format based on network meta-analysis estimates.

• Function mtrank synthesizes the output of the tcc function and estimates the final treatment ability.

• Forest plots are created either for the results of the TCC (forest.tcc) or the final ability estimates (forest.mtrank).

• Function fitted.mtrank uses the ability estimates obtained from mtrank to calculate pairwise probabilities that any treatment 'A' can be better, equal, or worse than any other treatment 'B' in the network.

• The function linegraph visualizes the output of mtrank across different SWD values. It serves as a sensitivity analysis to the initial choice of SWD.

Type help(package = "mtrank") for a listing of R functions available in mtrank.

Type citation("mtrank") on how to cite mtrank in publications.

To report problems and bugs, please send an email to Theodoros Evrenoglou <[e-mail]>.

The development version of mtrank is available on GitHub https://github.com/TEvrenoglou/mtrank.

Author(s)

Theodoros Evrenoglou <[e-mail]>, Guido Schwarzer <[e-mail]>

References

Evrenoglou T, Nikolakopoulou A, Schwarzer G, Rücker G, Chaimani A (2024): Producing treatment hierarchies in network meta-analysis using probabilistic models and treatment-choice criteria, https://arxiv.org/abs/2406.10612

See Also

Useful links:

• https://github.com/TEvrenoglou/mtrank

mtrank documentation built on June 8, 2025, 11:12 a.m.