---
title: "How to define outcomes completely in clinical trials: six-element guidance"
id: "plos-medicine-1-guidance-for-defining-outcomes-in-clinical-trials"
canonical_url: "https://medichelpline.com/clinical-feed/plos-medicine-1-guidance-for-defining-outcomes-in-clinical-trials"
content_type: "clinical_feed_article"
specialty: "General"
source_name: "PLOS Medicine"
source_url: "https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275"
published_at: "2026-10-21T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# How to define outcomes completely in clinical trials: six-element guidance
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-medicine-1-guidance-for-defining-outcomes-in-clinical-trials
- **Specialty:** [General](https://medichelpline.com/clinical-feed/general.md)
- **Primary Source:** PLOS Medicine
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275)
- **Published At:** 2026-10-21T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The authors developed a structured guidance to define trial outcomes completely, building on a prior 2011 framework and iteratively refining definitions through pilot testing. - They reviewed literature, drafted guidance, and pilot-tested it using a random sample of 225 randomized controlled trials registered on **ClinicalTrials.gov**, evaluating 3,424 outcomes. - Two independent raters followed a structured approach to define each outcome; guidance was revised when raters could not classify outcomes under the existing rules. - The final framework specifies six required elements for a complete outcome definition: **outcome domain**, **specific measurement**, **specific metric**, **cutoff** (if applicable), **variable type**, and **time point**. - The team replaced the prior “method of aggregation” element with two distinct elements — **variable type** and **cutoff** — to describe individual-level values rather than summary measures. - The guidance includes naming rules for both subjective and objective specific measurements and expands categories for specific metrics to improve consistency across trials. - Authors note that the guidance has since been applied in further studies with good agreement between independent human raters and automated systems, suggesting practical usability. - The guidance aims to reduce selective outcome reporting and improve comparability across registrations, protocols, and published results, but the authors acknowledge that complete definitions alone will not eliminate all biased reporting.
## Clinical Analysis & Structured Key Points
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[See all article types » ](https://journals.plos.org/plosmedicine/s/other-article-types) # Guidance for defining outcomes in clinical trials * Xiangji Ying, Affiliation Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-1713-3788 ](https://orcid.org/0000-0002-1713-3788 "ORCID Registry") ⨯ * Tianjing Li, Affiliation Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America ⨯ * Joanne E. McKenzie, Affiliation Methods in Evidence Synthesis Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0003-3534-1641 ](https://orcid.org/0000-0003-3534-1641 "ORCID Registry") ⨯ * Matthew J. Page, Affiliation Methods in Evidence Synthesis Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-4242-7526 ](https://orcid.org/0000-0002-4242-7526 "ORCID Registry") ⨯ * Kiran Ninan, Affiliation Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-8085-6751 ](https://orcid.org/0000-0002-8085-6751 "ORCID Registry") ⨯ * Jean-Pierre Oberste, Affiliation Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0009-0003-2075-5267 ](https://orcid.org/0009-0003-2075-5267 "ORCID Registry") ⨯ * Colby J. Vorland, Affiliation Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0003-4225-372X ](https://orcid.org/0000-0003-4225-372X "ORCID Registry") ⨯ * Andrew W. Brown, Affiliations Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America, Arkansas Children’s Research Institute, Little Rock, Arkansas, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-1758-8205 ](https://orcid.org/0000-0002-1758-8205 "ORCID Registry") ⨯ * Riaz Qureshi, Affiliation Department of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-6670-4874 ](https://orcid.org/0000-0002-6670-4874 "ORCID Registry") ⨯ * Nicholas J. DeVito, Affiliation Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0001-8286-1995 ](https://orcid.org/0000-0001-8286-1995 "ORCID Registry") ⨯ * Ian J. Saldanha, Affiliation Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-2062-3382 ](https://orcid.org/0000-0002-2062-3382 "ORCID Registry") ⨯ * Martin Offringa, Affiliation Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-4402-5299 ](https://orcid.org/0000-0002-4402-5299 "ORCID Registry") ⨯ * Nancy J. Butcher, Affiliations Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-5152-0108 ](https://orcid.org/0000-0002-5152-0108 "ORCID Registry") ⨯ * Sirui Zhang, Affiliation Department of Epidemiology, School of Public Health, Brown University, Providence, Rhode Island, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0009-0002-8410-436X ](https://orcid.org/0009-0002-8410-436X "ORCID Registry") ⨯ * Phi-Yen Nguyen, Affiliation Methods in Evidence Synthesis Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-0476-3385 ](https://orcid.org/0000-0002-0476-3385 "ORCID Registry") ⨯ * Joe Menke, Affiliation School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0002-7374-7549 ](https://orcid.org/0000-0002-7374-7549 "ORCID Registry") ⨯ * Veronica Ka Wai Lai, Affiliation Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0003-3593-9141 ](https://orcid.org/0000-0003-3593-9141 "ORCID Registry") ⨯ * Halil Kilicoglu, Affiliation School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0003-3987-9393 ](https://orcid.org/0000-0003-3987-9393 "ORCID Registry") ⨯ * [ ... ], * Evan Mayo-Wilson * E-mail: evan.mayo-wilson@unc.edu Affiliation Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, United States of America [ ![ORCID logo](https://journals.plos.org/resource/img/orcid_16x16.png) https://orcid.org/0000-0001-6126-2459 ](https://orcid.org/0000-0001-6126-2459 "ORCID Registry") ⨯ * [ view all ] * [ view less ] # Guidance for defining outcomes in clinical trials * Xiangji Ying, * Tianjing Li, * Joanne E. McKenzie, * Matthew J. Page, * Kiran Ninan, * Jean-Pierre Oberste, * Colby J. Vorland, * Andrew W. Brown, … * Riaz Qureshi, * Nicholas J. DeVito ![PLOS](https://journals.plos.org/resource/img/logo-plos-full-color.svg) x * Published: October 21, 2026 * * [Article](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275) * [Authors](https://journals.plos.org/plosmedicine/article/authors?id=10.1371/journal.pmed.1005275) * [Metrics](https://journals.plos.org/plosmedicine/article/metrics?id=10.1371/journal.pmed.1005275) * [Comments](https://journals.plos.org/plosmedicine/article/comments?id=10.1371/journal.pmed.1005275) * [Media Coverage](http://plos.altmetric.com/details/doi/10.1371/journal.pmed.1005275) * [Abstract](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#abstract0) * [Author summary](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#abstract1) * [Introduction](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#sec005) * [Methods](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#sec006) * [A six-element framework to define outcomes](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#sec007) * [Supporting information](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#sec031) * [References](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#references) * [Reader Comments](https://journals.plos.org/plosmedicine/article/comments?id=10.1371/journal.pmed.1005275) * [Figures](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275) [?](https://journals.plos.org/plosmedicine/s/accepted-manuscripts#loc-early-version) ## This is an uncorrected proof. ## Abstract ### Background Defining outcomes completely before conducting clinical trials helps to mitigate concerns about reporting biases; however, there is limited guidance to help investigators define outcomes completely. ### Methods Building on a previous framework, we developed guidance for defining trial outcomes completely and consistently. We reviewed literature, developed preliminary guidance, and refined guidance iteratively through pilot testing. We randomly selected 225 randomized controlled trials (RCTs) from ClinicalTrials.gov, which evaluated 3,424 outcomes. Two raters followed a structured approach to define each outcome. When raters encountered outcomes they could not define, we refined our guidance. We continued this process until no further changes were needed. We finalized the guidance through multiple drafts and discussions among authors. ### Findings In clinical trials, a completely defined outcome includes six elements: outcome domain, specific measurement, specific metric, cutoff (if applicable), variable type, and time point. We developed guidance for naming specific measurements for both subjective and objective outcomes. We expanded on prior work by describing more comprehensive categories for specific metrics. To be consistent with the estimand framework, we replaced “method of aggregation” with two distinct elements that describe values in individuals (rather than summary measures): “variable type” and “cutoff.” We further defined “cutoff” with three sub-elements, and we defined “variable type” as whether the value for each individual is continuous or categorical. ### Conclusions Trialists and sponsors could use this framework and guidance to define outcomes in trial registrations, protocols, and results reports. When all six elements are specified, readers can better determine whether reported outcomes were prespecified and whether different trials assessed the same outcomes. ## Author summary ### Why was this study done? * Clinical trials measure outcomes related to concepts such as pain, blood pressure, or survival to estimate whether treatments help or harm patients. * If an outcome is not defined completely before a trial begins, researchers can later analyze results in multiple ways and select the outcome definition that makes the treatment look best. * There is little practical guidance on how to describe an outcome completely to prevent “reporting bias.” ### What did the researchers do and find? * Building on an earlier framework published in 2011, we identified six pieces of information needed to describe a trial outcome completely: the construct of interest, data collection instruments, method for assigning values to individuals, any threshold used to group people, what type of value it is, and the time of assessment. * The guidance has since been used in two further studies of several thousand outcomes, with good agreement between independent raters and between human raters and an automated system. ### What do these findings mean? * Defining outcomes using these elements brings trial reporting closer to international standards for stating what a trial is designed to estimate. * The guidance could help researchers and trial sponsors describe outcomes completely and consistently in trial registrations, protocols, and published results. * Complete outcome definitions alone will not prevent all forms of biased reporting; better tools and systems are also needed to help researchers prepare registrations and protocols. ## Figures ![Fig 7](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g007) ![Fig 8](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g008) ![Fig 1](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g001) ![Fig 2](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g002) ![Fig 3](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g003) ![Fig 4](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g004) ![Fig 5](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g005) ![Fig 6](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g006) ![Fig 7](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g007) ![Fig 8](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g008) ![Fig 1](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g001) ![Fig 2](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g002) ![Fig 3](https://journals.plos.org/plosmedicine/article/figure/image?size=inline&id=10.1371/journal.pmed.1005275.g003) **Citation:** Ying X, Li T, McKenzie JE, Page MJ, Ninan K, Oberste J-P, et al. (2026) Guidance for defining outcomes in clinical trials. PLoS Med 23(10): e1005275. https://doi.org/10.1371/journal.pmed.1005275 **Published:** October 21, 2026 **Copyright:** © 2026 Ying et al. This is an open access article distributed under the terms of the [Creative Commons Attribution License](http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. **Funding:** EMW: National Institutes of Health (R01LM014079) ; EMW: UNC Provost’s AI Acceleration program cloud resource grant, . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. **Competing interests:** The authors have declared that no competing interests exist. **Abbreviations:** BMI, body mass index; BPI, Brief Pain Inventory; COMET, Core Outcome Measures for Effectiveness Trials; CTCAE, Common Terminology Criteria for Adverse Events; DBP, diastolic blood pressure; ICMJE, International Committee of Medical Journal Editors; MAGE, Mean Amplitude of Glycemic Excursions; RCTs, randomized controlled trials; RECIST, response evaluation criteria in solid tumors; SBP, Systolic blood pressure. ## Introduction Registering clinical trials and defining outcomes completely can help mitigate reporting biases. That is, different outcome definitions can lead to different numerical results. By pre-specifying outcome definitions, investigators reassure readers that reported results are consistent with planned outcomes and that results were not selected based on their magnitude or statistical significance. Laws and policies [[1](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref001)–[3](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref003)], funders [[4](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref004),[5](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref005)], and journals [[6](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref006)–[8](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref008)] require that clinical trialists register trial outcomes prospectively and report results completely [[9](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref009)]. Notably, the International Committee of Medical Journal Editors (ICMJE) requires that trials be registered “to prevent selective publication and selective reporting of research outcomes” [[8](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref008)]. Registering clinical trials might reduce the risk of two related reporting biases. First, registration enables readers to evaluate whether prespecified outcomes are reported or omitted in subsequent reports (e.g., journal articles reporting results). Second, registration allows users to evaluate whether outcomes are reported using the same or different definitions compared with planned outcome definitions; for example, using the same measurement instruments and time points as planned. In practice, current trial registration requirements might mitigate the first type of bias (non-reporting of outcomes) while failing to address selective reporting related to changes in outcome definitions [[10](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref010)–[12](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref012)]. In addition to the risk of reporting biases, incomplete outcome definitions contribute to two related problems. First, incomplete outcomes might be difficult to compare across different sources for the same trial (e.g., comparing a study protocol with a final report). Second, results might not be combined and interpreted correctly across trials (e.g., in a systematic review) when it is unclear whether trials assessed the same outcomes [[13](https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1005275#pmed.1005275.ref013)]. In 2011, Zarin and colleagues proposed a structured framework to define outcomes on ClinicalTrials.gov [[14](https://journals.plo
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