Evidence map›Paper›PMID 37818362›Full record

ReviewFrontiers in immunology2023

Precision in treatment evaluation: importance of minimal clinically important differences (MCIDs) of outcome measures for autoimmune blistering diseases.

Henry Tseng, Corey Stone, Dédée F Murrell

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Review
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 at 2 institutions in 1 country.

Henry TsengDepartment of Dermatology, St. George Hospital, Sydney, NSW, Australia.
Corey StoneDepartment of Dermatology, St. George Hospital, Sydney, NSW, Australia.
Dédée F MurrellDepartment of Dermatology, St. George Hospital, Sydney, NSW, Australia.
UNSW Sydney · AUSt George Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autoimmune blistering diseases (AIBDs) comprise a group of rare conditions marked by autoantibodies that specifically target intercellular adhesion molecules. Despite the progress made in comprehending the disease and the increasing number of treatment options available, there is still no definitive cure for AIBDs such as pemphigus, and it continues to have a devastating impact on those affected. The challenges in achieving new approved therapies for AIBDs are complex and multifaceted. One significant obstacle was the prior lack of validated and standardized outcome measures, which are crucial for ensuring precise comparisons between new and traditional therapies. This gap in knowledge has prompted the development of minimal clinically important differences (MCIDs), which enable efficient and reliable comparison of therapeutic outcomes between trials. MCID is defined as the minimum difference in an outcome measure that indicates a clinically significant improvement/deterioration in disease severity. Additionally, MCIDs provide a patient-centered approach to evaluating treatment efficacy, by considering whether patients experience a subjective improvement in their symptoms. Therefore, this literature review will examine the derivation and significance of MCIDs for various scoring systems in AIBDs.

Indexed as

Autoimmune DiseasesPemphigusBlisterHumansMinimal Clinically Important DifferenceOutcome Assessment, Health CareTreatment Outcomeautoimmune blistering diseasesinvestigator global assessmentMCIDoutcome measurespemphiguspemphigus disease area index

Identifiers

PMID37818362
PMCPMC10560849
OpenAlexW4387057732

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.