Evidence map›Paper›PMID 34113351›Full record

SynthesisFrontiers in immunology2021

When the Good Syndrome Goes Bad: A Systematic Literature Review.

Yiyun Shi, Chen Wang

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
3.0field-weighted citation impact, top 8% 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

32 citing papers in PubMed, 46 citations in OpenAlex.

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  4. Oligoclonal expansion of atypical Vδ2Nature communications · 2026
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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

2 authors at 2 institutions in 1 country.

Yiyun ShiDepartment of Medicine, The Warren Alpert Medical School of Brown University, Providence, RI, United States.
Chen WangDepartment of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, United States.
Brown University · USUniversity of South Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Good syndrome is a rare adult-onset immunodeficiency characterized by thymoma and hypogammaglobulinemia. Its clinical manifestations are highly heterogeneous, ranging from various infections to autoimmunity. Objective: This study was to summarize patient characteristics, identify prognostic factors and define clinical subgroups of Good syndrome. Methods: A systematic literature review was conducted to include patients with Good syndrome identified in PubMed, Embase and Cochrane databases between January 2010 and November 2020. Logistic and Cox regressions were used to identify prognostic factors impacting outcomes. Clinical subgroups were defined by multiple correspondence analysis and unsupervised hierarchical clustering. A decision tree was constructed to characterize the subgroup placement of cases. Results: Of 162 patients included in the current study, the median age at diagnosis was 58 years and 51% were male. Type AB was the most common histological subtype of thymoma, and infections as well as concurrent autoimmune disorders were identified in 92.6% and 51.2% patients, respectively. Laboratory workup showed typical findings of combined immunodeficiency. Thymoma status (odds ratio [OR] 4.157, confidence interval [CI] 1.219-14.177, Conclusions: Infection type and site were the main prognostic factors impacting survival of patients with Good syndrome. We identified three subgroups within Good syndrome associated with distinct clinical features, which may facilitate the study of underlying pathogenesis as well as development of targeted therapy.

Indexed as

AutoimmunityDisease ManagementDisease SusceptibilityGlobal HealthHumansImmunologic Deficiency SyndromesNeoplasms, Second PrimaryOdds RatioPhenotypePopulation SurveillancePrognosisSymptom Assessmentclinical subgroupsGood syndromeimmunodeficiencyinfectionsprognosis

Identifiers

PMID34113351
PMCPMC8185358
OpenAlexW3165282247

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.