ArticleiScience2026
AI-augmented MALDI-TOF MS screening reveals a high burden of undiagnosed monoclonal gammopathy in adult patients.
Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Monoclonal gammopathy of undetermined significance is a common precursor of multiple myeloma, yet its prevalence and clinical distribution remain poorly defined due to the limited scalability of conventional electrophoretic workflows. Here, we developed an artificial intelligence-augmented matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platform that integrates machine learning, rule-based detection of weak monoclonal signals and glycosylation assessment for automated M-protein screening. Following training and validation on 5,218 retrospective serum samples, the platform was deployed in a real-world cohort of 12,263 adult patients. Screening identified M-proteins in 7.5% of patients, reaching 10.1% among individuals aged ≥ 50 years, and revealed a substantial burden of previously undetected monoclonal protein abnormalities. Beyond hematologic disorders, M-protein positivity was associated with a broad spectrum of infectious, neoplastic, and metabolic conditions. These findings establish a scalable strategy for population-level M-protein screening and highlight adult patients as an underrecognized high-risk population that may benefit from systematic surveillance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.