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Ranking treatments in frequentist network meta-analysis works without resampling methods
Open accessAbstract
BACKGROUND: Network meta-analysis is used to compare three or more treatments for the same condition. Within a Bayesian framework, for each treatment the probability of being best, or, more general, the probability that it has a certain rank can be derived from the posterior distributions of all treatments. The treatments can then be ranked by the surface under the cumulative ranking curve (SUCRA). For comparing treatments in a network meta-analysis, we propose a frequentist analogue to SUCRA which we call P-score that works without resampling. METHODS: P-scores are based solely on the point estimates and standard errors of the frequentist network meta-analysis estimates under normality assumption and can easily be calculated as means of one-sided p-values. They measure the mean extent of certainty that a treatment is better than the competing treatments. RESULTS: Using case studies of network meta-analysis in diabetes and depression, we demonstrate that the numerical values of SUCRA and P-Score are nearly identical. CONCLUSIONS: Ranking treatments in frequentist network meta-analysis works without resampling. Like the SUCRA values, P-scores induce a ranking of all treatments that mostly follows that of the point estimates, but takes precision into account. However, neither SUCRA nor P-score offer a major advantage compared to looking at credible or confidence intervals.
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“This approach is often misleading, as it considers only the point estimate of effect and not the associated precision or certainty of evidence and ignores absolute differences between treatment alternatives.[56][57][58]”
From Management of chronic pain secondary to temporomandibular disorders: a systematic review and network meta-analysis of randomised trials (2023) · cites this paper as [57]
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“The numerical p score values are nearly identical to the surface under the cumulative ranking curve [23].”
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“For each outcome and time point, we ranked interventions in order of effectiveness using p scores—a frequentist measure of the extent of certainty that an intervention is better than another intervention averaged over all competing interventions [41,42].”
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“The ranking of treatments for each outcome was performed using the P score (the probability that one treatment is better than the others), with higher values corresponding to a higher ranking.(12) The rankings for recurrent VTE, major bleeding, and all-cause mortality were combined in an Haase diagram, which illustrat…”
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“was considered 100% when a treatment was certain to be the best and 0% when a treatment was certain to be the worst.(17) As sensitivity analyses, we conducted analyses (a) excluding the largest study (N = 16,694, 81.”
MethodUsing Normalized Entropy to Measure Uncertainty of Rankings for Network Meta-analyses
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“The bimodal distribution of ranking probabilities is uncommon; however, it may be seen when 2 treatments have similar effect sizes but one has a much wider CI, thereby yielding a greater distribution of ranking probabilities.(20) However, because the bimodal distribution is considered the most uncertain scenario, the…”
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“21,22 The variety of interventions was considered among the best if p -score was ≥0.66; when p -score was 0.65 to 0.33, the combination was judged inferior to the best/better than the worst; when p -score was <0.33, the combination was considered among the worst.”
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“Intervention effects were ranked according to P -scores [49].”
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“Given that P-score took precision into account [25] and sUcRa were unstable based on simulations, we preferentially ranked interventions with P-score like another study [26] and also compared the potential differences between sUcRa and P-score. the key characteristics of included Rcts were…”
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“Ranking of treatments were estimated using P-scores, representing the extent of certainty that an intervention is more effective than another intervention 19 .”
MethodZhou, L., Deng, X., Xu, M., Wu, Y., Shang, X., Fenfen, E., Wang, Y., Liang, S., Yang, K., & Li, X. (2023) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-023-01467-5 · Cited by 33
“SUCRA is an index that can be used as a reference to evaluate the relative position of each treatment and account for inconsistencies between studies [32, 33].”
MethodIntegrating Evidence to Guide Use of Biologics and Small Molecules for Inflammatory Bowel Diseases
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“A P score of 1 indicates that the treatment is certain to be the most effective/safest treatment in the network, while a P score of 0 indicates that the treatment is certain to be the least effective/safe in the network [25].”
BackgroundMarkar, S. R., Andreou, A., Bonavina, L., Flórez, I. D., Huo, B., Kontouli, K., Low, D. E., Mavridis, D., Maynard, N., Moss, A., et al. (2022) · United European Gastroenterology Journal · doi:10.1002/ueg2.12318 · Cited by 28
“We ranked all the available treatments in each outcome, from best to worst, using P‐ scores.(33) A value close to 1 means that the intervention is very efficacious, whereas a value close to 0 means the opposite.”
MethodWang, Z., Zhou, Z., Zhang, L., Li, X., Li, M., Pan, Y., Jiao, T., Shi, X., Liu, Q., Wang, C., et al. (2023) · European journal of medical research · doi:10.1186/s40001-022-00968-6 · Cited by 29
“The larger the percentage is, it means that the intervention has the highest probability and possibility of becoming the most preferred option, and a value of 0 indicates that the intervention may be completely ineffective [23, 24].”
BackgroundBallesio, A., Zagaria, A., Vacca, M., Pariante, C. M., & Lombardo, C. (2023) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2023.05.006 · Cited by 30
“A hierarchy of competing interventions on the basis of their efficacy was established using P-scores, which are considered a frequentist equivalent to the Bayesian network surface under the cumulative ranking curves (SUCRA; Rücker and Schwarzer, 2015).”
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“49 Comparisons were made when more than one study was included for each comparator and were considered statistically significant when the 95% CI did not include the value of zero.”
BackgroundPépin, J., Lehert, P., Messaoud, R. B., Joyeux-faure, M., Caussé, C., Asin, J., Barbé, F., Bonsignore, M., Randerath, W., Verbraecken, J., et al. (2024) · EClinicalMedicine · doi:10.1016/j.eclinm.2024.102843 · Cited by 28
“51 Pi is de fi ned as the mean of all 1 – Pj (Pj = one-sided p value of accepting the alternative hypothesis that ti > tj).”
BackgroundBednárik, D. S., Földvári-Nagy, K. C., Simon, V., Rancz, A., Gede, N., Veres, D. S., Paraskevopoulos, P., Schnabel, T., Erőss, B. M., Hegyi, P., et al. (2025) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2024.101151 · Cited by 30
“P-scores 23 were calculated to indicate which treatments were more or less likely to have the most signi fi cant bene fi ts or negligible adverse effects; the score ranged from 0 to 1, representing the theoretically worst and best treatments, respectively, compared to the other treatments.”
Which are the best Chinese herbal injections combined with XELOX regimen for gastric cancer?
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Agreement between ranking metrics in network meta-analysis: an empirical study
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A Markov chain approach for ranking treatments in network meta‐analysis
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“The P-score represents the probability that the nerve block is the ideal block for optimal pain control, and it provides a method for ranking the possible options.(81) However, the optimal method of comparing treatments should be to look at the odds ratio and confidence interval.”
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Methods of Weaning From Mechanical Ventilation in Adult: A Network Meta-Analysis
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“Higher P-score scores correspond to a greater weaning success rate, lower proportion requiring reintubation and lower mortality (26).”
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“We used P-scores to rank exercise types on the basis of the degree of improvement in each balance outcome categories [31].”
MethodEAES, SAGES, and ESCP rapid guideline: bowel preparation for minimally invasive colorectal resection
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“The SUCRA value ranged from 0 to 100%, with a larger SUCRA value indicating a better treatment option (Rücker and Schwarzer, 2015; Trinquart et al., 2016).”
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Self-citation
Metadata
- Authors
- Rücker, G., & Schwarzer, G.
- Affiliations
- University of Freiburg (DE)
- Corresponding author
- Rücker, Gerta
- Venue
- BMC Medical Research Methodology
- Published
- 2015-07-31
- Volume
- 15
- Issue
- 1
- Pages
- 58-58
- ISSN
- 1471-2288 (ISSN-L)
- PMC
- PMC4521472
- OpenAlex
- W2111999709
- Cited by
- 1,732
- References
- 32
- Citations by year
- 2026: 249 · 2025: 253 · 2024: 267 · 2023: 229 · 2022: 226 · 2021: 191 · 2020: 148 · 2019: 76 · 2018: 52 · 2017: 32 · 2016: 8 · 2015: 1
- FWCI
- 28.58
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- BMC Medical Research Methodology (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- FreiDok plus (Universitätsbibliothek Freiburg) (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (RU1747/1-1)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Sociology and Political Science › Delphi Technique in Research
- Keywords
- treatment ranking, P-score, surface under the cumulative ranking curve, confidence intervals, diabetes mellitus, depression
- MeSH terms
- Algorithms, Bayes Theorem, Biometry, Data Interpretation, Statistical, Humans, Review Literature as Topic, Meta-Analysis as Topic, Reproducibility of Results, Biomedical Research
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