Evidence map›Paper›PMID 36913182›Full record

ArticleArthritis care & research2023

Diagnostic Yield of Computed Tomography for Cancer Detection in a Tertiary Referral Population of Idiopathic Inflammatory Myositis Patients.

Christopher A Mecoli, Brant Chee, Mengkun Chen, XingYao Wang, Jemima Albayda, Julie J Paik, Eleni Tiniakou, Brittany Adler, Will Kelly, Andrew L Mammen and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Arthritis care & research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

14 authors at 1 institution in 1 country.

Christopher A MecoliJohns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-1429-8392
Brant CheeJohns Hopkins University School of Medicine, Baltimore, Maryland, and Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland.
Mengkun ChenJohns Hopkins University School of Medicine, Baltimore, Maryland.
XingYao WangJohns Hopkins University School of Medicine, Baltimore, Maryland.
Jemima AlbaydaJohns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-8030-9504
Julie J PaikJohns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0001-8436-1601
Eleni TiniakouJohns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0003-4749-870X
Brittany AdlerJohns Hopkins University School of Medicine, Baltimore, Maryland.
Will KellyJohns Hopkins University School of Medicine, Baltimore, Maryland.
Andrew L MammenJohns Hopkins University School of Medicine, Baltimore, Maryland, and the NIH/National Institute of Arthritis and Musculoskeletal and Skin Diseases, Bethesda, Maryland.ORCID 0000-0003-3732-3252
Elizabeth A PlatzJohns Hopkins Bloomberg School of Public Health and Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University, Baltimore, Maryland.
Livia Casciola-RosenJohns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-4172-1539
Lisa Christopher-StineJohns Hopkins University School of Medicine, Baltimore, Maryland.ORCID 0000-0002-7150-7306
Ami A ShahJohns Hopkins University School of Medicine, Baltimore, Maryland.
Johns Hopkins University · US

Funding

Translational Research Central ServicesP30CA006973 · NCI · JOHNS HOPKINS UNIVERSITY · PI Rosalie Wollett · 1985 to 2026
$208.6M
Muscle Disease UnitZIAAR041203 · NIAMS · NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES · PI MAMMEN, ANDREW · 2015 to 2025
$19.7M
Sample Processing and Immunoassay Research CoreP30AR070254 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI Antony Rosen · 2016 to 2026
$8.9M
Autoantibodies Define Scleroderma Subgroups with Distinct Relationships to CancerR01AR073208 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI LIVIA A CASCIOLA-ROSEN, Ami Aalok Shah · 2018 to 2026
$5.2M
Harnessing multivariate patient- and population-level disease trajectories to predict major clinical events in sclerodermaK24AR080217 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI Ami Aalok Shah · 2022 to 2026
$847k
RNA: Polymerase III specific CD8+ T cells: a mechanistic insight into cancer-induced autoimmunity in sclerodermaK08AR077732 · NIAMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI TINIAKOU, ELENI · 2021 to 2025
$794k
Optimizing the Approach to Identify Cancer-Associated MyositisK23AR075898 · NIAMS · JOHNS HOPKINS UNIVERSITY · PI MECOLI, CHRISTOPHER · 2019 to 2023
$773k
NCI NIH HHS P30 CA006973NIAMS NIH HHS K08 AR077732NIAMS NIH HHS K08AR0777732NIAMS NIH HHS K23AR0739NIAMS NIH HHS K23 AR075898NIAMS NIH HHS K23AR075898NIAMS NIH HHS K24 AR080217NIAMS NIH HHS P30 AR070254NIAMS NIH HHS P30-AR070254NIAMS NIH HHS R01 AR-073208NIAMS NIH HHS R01 AR073208
6 · The paper itself

Abstract

objectiveTo inform guidance for cancer detection in patients with idiopathic inflammatory myopathy (IIM), we evaluated the diagnostic yield of computed tomography (CT) imaging for cancer screening/surveillance within distinct IIM subtypes and myositis-specific autoantibody strata.

methodsWe conducted a single-center, retrospective cohort study in IIM patients. Overall diagnostic yield (number of cancers diagnosed/number of tests performed), percentage of false positives (number of biopsies performed not leading to cancer diagnosis/number of tests performed), and test characteristics were determined on CT of the chest and abdomen/pelvis.

resultsWithin the first 3 years since IIM symptom onset, a total of 9 of 1,011 (0.9%) chest CT scans and 12 of 657 (1.8%) abdomen/pelvis CT scans detected cancer. Diagnostic yields for both CT of the chest and CT of the abdomen/pelvis were highest in dermatomyositis, specifically anti-transcription intermediary factor 1γ (2.9% and 2.4% for CT of the chest and abdomen/pelvis, respectively). The highest percentage of false positives was in patients with antisynthetase syndrome (ASyS) (4.4%) and immune-mediated necrotizing myopathy (4.4%) on CT of the chest, and ASyS (3.8%) on CT of the abdomen/pelvis. Patients ages <40 years old at IIM onset had both low diagnostic yields (0% and 0.5%) and high false-positive rates (1.9% and 4.4%) for CT of the chest and abdomen/pelvis, respectively.

conclusionIn a tertiary referral cohort of IIM patients, CT imaging has a wide range of diagnostic yield and frequency of false positives for contemporaneous cancer. These findings suggest that cancer detection strategies targeted according to IIM subtype, autoantibody positivity, and age may maximize cancer detection while minimizing the harms and costs of over-screening.

Indexed as

MyositisNeoplasmsAdultAutoantibodiesHumansReferral and ConsultationRetrospective StudiesTomography, X-Ray ComputedAutoantibodies

Identifiers

PMID36913182
PMCPMC10497706
OpenAlexW4324017598

What OpenQuestion holds

Textmetadata
LicenceTDM
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.