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Article: Reduction in number to treat versus number needed to treat

TitleReduction in number to treat versus number needed to treat
Authors
KeywordsAbsolute risk reduction
Number needed to treat
Randomized controlled trials
Restricted mean survival time
Treatment effect
Issue Date2021
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcmedresmethodol/
Citation
BMC Medical Research Methodology, 2021, v. 21, p. article no. 48 How to Cite?
AbstractBackground: We propose a new measure of treatment effect based on the expected reduction in the number of patients to treat (RNT) which is defined as the difference of the reciprocals of clinical measures of interest between two arms. Compared with the conventional number needed to treat (NNT), RNT shows superiority with both binary and time-to-event endpoints in randomized controlled trials (RCTs). Methods: Five real RCTs, two with binary endpoints and three with survival endpoints, are used to illustrate the concept of RNT and compare the performances between RNT and NNT. For survival endpoints, we propose two versions of RNT: one is based on the survival rate and the other is based on the restricted mean survival time (RMST). Hypothetical scenarios are also constructed to explore the advantages and disadvantages of RNT and NNT. Results: Because there is no baseline for computation of NNT, it fails to differentiate treatment effect in the absolute scale. In contrast, RNT conveys more information than NNT due to its reversed order of differencing and inverting. For survival endpoints, two versions of RNT calculated as the difference of the reciprocals of survival rates and RMSTs are complementary to each other. The RMST-based RNT can capture the entire follow-up profile and thus is clinically more intuitive and meaningful, as it inherits the time-to-event characteristics for survival endpoints instead of using truncated binary endpoints at a specific time point. Conclusions: The RNT can serve as an alternative measure for quantifying treatment effect in RCTs, which complements NNT to help patients and clinicians better understand the magnitude of treatment benefit.
Persistent Identifierhttp://hdl.handle.net/10722/300548
ISSN
2023 Impact Factor: 3.9
2023 SCImago Journal Rankings: 1.632
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorZHANG, C-
dc.contributor.authorYin, G-
dc.date.accessioned2021-06-18T14:53:33Z-
dc.date.available2021-06-18T14:53:33Z-
dc.date.issued2021-
dc.identifier.citationBMC Medical Research Methodology, 2021, v. 21, p. article no. 48-
dc.identifier.issn1471-2288-
dc.identifier.urihttp://hdl.handle.net/10722/300548-
dc.description.abstractBackground: We propose a new measure of treatment effect based on the expected reduction in the number of patients to treat (RNT) which is defined as the difference of the reciprocals of clinical measures of interest between two arms. Compared with the conventional number needed to treat (NNT), RNT shows superiority with both binary and time-to-event endpoints in randomized controlled trials (RCTs). Methods: Five real RCTs, two with binary endpoints and three with survival endpoints, are used to illustrate the concept of RNT and compare the performances between RNT and NNT. For survival endpoints, we propose two versions of RNT: one is based on the survival rate and the other is based on the restricted mean survival time (RMST). Hypothetical scenarios are also constructed to explore the advantages and disadvantages of RNT and NNT. Results: Because there is no baseline for computation of NNT, it fails to differentiate treatment effect in the absolute scale. In contrast, RNT conveys more information than NNT due to its reversed order of differencing and inverting. For survival endpoints, two versions of RNT calculated as the difference of the reciprocals of survival rates and RMSTs are complementary to each other. The RMST-based RNT can capture the entire follow-up profile and thus is clinically more intuitive and meaningful, as it inherits the time-to-event characteristics for survival endpoints instead of using truncated binary endpoints at a specific time point. Conclusions: The RNT can serve as an alternative measure for quantifying treatment effect in RCTs, which complements NNT to help patients and clinicians better understand the magnitude of treatment benefit.-
dc.languageeng-
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcmedresmethodol/-
dc.relation.ispartofBMC Medical Research Methodology-
dc.rightsBMC Medical Research Methodology. Copyright © BioMed Central Ltd.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectAbsolute risk reduction-
dc.subjectNumber needed to treat-
dc.subjectRandomized controlled trials-
dc.subjectRestricted mean survival time-
dc.subjectTreatment effect-
dc.titleReduction in number to treat versus number needed to treat-
dc.typeArticle-
dc.identifier.emailYin, G: gyin@hku.hk-
dc.identifier.authorityYin, G=rp00831-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/s12874-021-01246-5-
dc.identifier.pmid33750292-
dc.identifier.pmcidPMC7945324-
dc.identifier.scopuseid_2-s2.0-85102244010-
dc.identifier.hkuros322813-
dc.identifier.volume21-
dc.identifier.spagearticle no. 48-
dc.identifier.epagearticle no. 48-
dc.identifier.isiWOS:000627886500003-
dc.publisher.placeUnited Kingdom-

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