Evidence map›Paper›PMID 41795172›Full record

ArticleMuscle & nerve2026

Increased Prevalence of Extrathymic Neoplasms in Myasthenia Gravis Patients-A Population-Based, Matched Case-Control Study.

Keshet Pardo, Tasneem Kab, Mark A Hellmann, Itay Lotan, Tzippy Shochat, Nadav Loebl, Bar Yacobi, Yitzhak Friedman, Leor Perl, Nitai Shimon and 4 more

Abstract read
In one paragraph

Article in Muscle & nerve, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Keshet PardoDepartment of Neurology, Rabin Medical Center, Petach Tikva, Israel.ORCID https://orcid.org/0000-0001-5056-2368
Tasneem KabDepartment of Neurology, Rabin Medical Center, Petach Tikva, Israel.
Mark A HellmannDepartment of Neurology, Rabin Medical Center, Petach Tikva, Israel.
Itay LotanDepartment of Neurology, Rabin Medical Center, Petach Tikva, Israel.ORCID https://orcid.org/0000-0002-4015-9783
Tzippy ShochatStatistical Consultant, Rabin Medical Center, Petach Tikva, Israel.
Nadav LoeblBeilinson Medical Center Innovation, Artificial Intelligence Center, Rabin Medical Center, Petah Tikva, Israel.
Bar YacobiBeilinson Medical Center Innovation, Artificial Intelligence Center, Rabin Medical Center, Petah Tikva, Israel.
Yitzhak FriedmanDepartment of Neurology, Rabin Medical Center, Petach Tikva, Israel.
Leor PerlFaculty of Medicine, Tel Aviv University, Petach Tikva, Israel.
Nitai ShimonDepartmet of Neurology, Shamir Medical Center, Beer Yaakov, Israel.
Yiska Loewenberg WeisbandClalit Health Services, Clalit Research Institute, Tel Aviv, Israel.
Liya BieberClalit Health Services, Clalit Research Institute, Tel Aviv, Israel.
Eitan AurielDepartment of Neurology, Rabin Medical Center, Petach Tikva, Israel.ORCID https://orcid.org/0000-0001-6712-5156
Adi Wilf-YarkoniDepartment of Neurology, Rabin Medical Center, Petach Tikva, Israel.ORCID https://orcid.org/0000-0002-2584-5793

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

INTRODUCTION/

aimsMyasthenia gravis (MG) is associated with thymic neoplasms. However, an increased prevalence of extrathymic neoplasms has also been reported. This study aimed to evaluate the rates of malignancy in MG patients while accounting for risk factors such as disease characteristics and immunomodulatory treatments.

methodsWe conducted a case-control study using the Clalit Health Services database, applying a machine learning (ML) algorithm to minimize diagnosis misclassification. We included MG patients aged 18 years and older, with a sex- and age-matched control group in a 1:3 ratio. We compared the prevalence and hazard ratios of extrathymic neoplasms between the groups.

resultsA total of 1558 patients with a high probability of MG, according to our ML model, were included in the cohort, alongside a control group of 4674 individuals. MG patients had a higher prevalence of malignancy prior to MG diagnosis, with an odds ratio of 1.95 (95% CI, 1.65-2.08), and a higher incidence of malignancy after MG diagnosis, with a hazard ratio of 1.56 (95% CI, 1.38-1.77). The most prevalent extrathymic neoplasms after MG diagnosis were respiratory, intrathoracic, skin (specifically non-melanoma), urinary tract, soft tissue, and myelodysplastic syndrome. Risk factors for malignancy included age, male sex, and thymoma. Immunosuppressive treatment did not increase the risk of malignancy. DISCUSSION: MG patients have a higher prevalence of both solid and hematologic neoplasms compared to non-myasthenic controls, regardless of immunosuppressive treatment. This supports the notion that malignancy is related to MG disease itself rather than external factors.

Indexed as

Myasthenia GravisNeoplasmsAdolescentAdultAgedAged, 80 and overCase-Control StudiesFemaleHumansMachine LearningMaleMiddle AgedPrevalenceRisk FactorsYoung Adultartificial intelligenceextra‐thymic malignancymachine learningmalignancymyasthenia gravis

Identifiers

PMID41795172
PMCPMC13138355

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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.