Evidence map›Paper›PMID 17005037›Full record

ArticleHealth and quality of life outcomes2006

How a well-grounded minimal important difference can enhance transparency of labelling claims and improve interpretation of a patient reported outcome measure.

Jan L Brozek, Gordon H Guyatt, Holger J Schünemann

Abstract readEditorial
In one paragraph

Article in Health and quality of life outcomes, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 13 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 13 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

77 citing papers in PubMed, 13 syntheses or guidelines pooled it.

  1. Minimal important change (MIC): a conceptual clarification and systematic review of MIC estimates of PROMIS measures.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021
    Pooled it
  2. Botulinum toxin type A versus anticholinergics for cervical dystonia.The Cochrane database of systematic reviews · 2021
    Pooled it
  3. Botulinum toxin type A therapy for hemifacial spasm.The Cochrane database of systematic reviews · 2020
    Pooled it
  4. Botulinum toxin type A therapy for blepharospasm.The Cochrane database of systematic reviews · 2020
    Pooled it
  5. Botulinum toxin type A therapy for cervical dystonia.The Cochrane database of systematic reviews · 2020
    Pooled it
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  9. Deep brain stimulation for dystonia.The Cochrane database of systematic reviews · 2019
    Pooled it
  10. Botulinum toxin type A therapy for cervical dystonia.The Cochrane database of systematic reviews · 2017
    Pooled it
  11. Botulinum toxin type A versus botulinum toxin type B for cervical dystonia.The Cochrane database of systematic reviews · 2016
    Pooled it
  12. Botulinum toxin type B for cervical dystonia.The Cochrane database of systematic reviews · 2016
    Pooled it
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17 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jan L BrozekDepartment of Medicine, Jagiellonian University School of Medicine, Krakow, Poland. brozek@mp.pl
Gordon H Guyatt
Holger J Schünemann

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The evaluation and use of patient reported outcome (PRO) measures requires detailed understanding of the meaning of the outcome of interest. The Food and Drug Administration (FDA) recently presented its draft guidance and view on the use of PRO measures as endpoints in clinical trials. One section of the guidance document specifically deals with advice about the use of the minimal important difference (MID) that we redefined as the smallest difference in score in the outcome of interest that informed patients or informed proxies perceive as important. The advice, however, is short, indeed much too short. We believe that expanding the section and making it more specific will benefit all stakeholders: patients, clinicians, other clinical decision makers, those designing trials and making claims, payers and the FDA. There is no "gold standard" methodology of estimating the MID or achieving the meaningfulness of clinical trial results based on patient reported outcomes. There are many methods of estimating the MID usually grouped into two distinct categories: anchor-based methods, that examine the relationship between scores on the target instrument and some independent measure, and distribution-based methods resorting to the statistical characteristics of the obtained scores. Estimation of an MID and interpretation of clinical trial results that present patient important outcomes is demanding but vital for informing the decision to recommend approve a given intervention. Investigators are encouraged to use reliable and valid methods to achieve meaningfulness of their results, preferably those that rely on patients to estimate what constitutes a minimal important, small, moderate, or large difference. However, acquiring the meaningfulness of PRO measures transcends beyond a concept of the MID and we advocate that dichotomizing the scores of patient-reported outcome measures facilitate interpretability of clinical trial results for those who need to understand trial results after a labelling claim has been granted. Irrespective of the strategy investigators use to estimate these values, from the individual patient perspective it is much more relevant if investigators report both the estimated thresholds and the proportion of patients achieving that benefit.

Indexed as

Data Interpretation, StatisticalEndpoint DeterminationGuidelines as TopicQuality of LifeSelf ConceptClinical Trials as TopicHumansOutcome Assessment, Health CareProxyTreatment OutcomeUnited StatesUnited States Food and Drug Administration

Identifiers

PMID17005037
PMCPMC1599713

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.