ArticleTranslational cancer research2026
Clinical characteristics, prognosis, and nomograms for lung invasive mucinous adenocarcinoma with distant metastasis: a population-based study.
Article in Translational cancer research, 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Lung invasive mucinous adenocarcinoma (LIMA) is a rare and distinct subtype of lung cancer, characterized by a relatively poor prognosis. Among LIMA patients, distant metastasis (DM) is a commonly observed and fatal feature, however, the prognostic patterns in these patients remain poorly understood. Identifying the factors influencing DM and prognosis in LIMA patients is crucial for improving individualized management and treatment strategies. This study aimed to identify key factors associated with LIMA-related DM and prognosis, and construct predictive nomograms to guide clinical practice. Methods: This retrospective cohort study utilized data from the Surveillance, Epidemiology, and End Results (SEER) database, including LIMA patients diagnosed between 2004 and 2015. Logistic regression analysis was conducted to identify independent risk factors for DM in LIMA patients, while Cox regression analysis was used to determine independent prognostic factors for LIMA patients with DM. Based on these analyses, two nomograms were developed to predict the incidence and prognosis of DM in LIMA patients. The performance of these monograms was evaluated using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), calibration curves, and Kaplan-Meier (K-M) analyses. Results: A total of 4,439 LIMA patients were included in the study, of which 830 patients presented with DM at the time of diagnosis. Independent risk factors for DM in LIMA patients included primary tumor site, histological grade, T-stage, and N-stage. Prognostic factors for LIMA patients with DM were age, sex, grade, tumor size, T-stage, N-stage, receipt of surgery, and chemotherapy. The validation of the nomograms in both the training and validation cohorts demonstrated robust predictive accuracy for the incidence and prognosis of DM in LIMA patients, as evidenced by the ROC curves, calibration curves, DCA, and K-M analysis. Conclusions: Two nomograms were developed to predict the risk of DM and the prognosis of LIMA patients with DM. Both nomograms demonstrated high predictive accuracy and may serve as useful tools for personalized clinical decision-making, facilitating the management of LIMA patients with DM.
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.