Evidence map›Paper›PMID 40469182›Full record

SynthesisFrontiers in oncology2025

Analysis of prognostic factors and risk prediction in brain metastases: a SEER population-based study.

Qiang Ji, Zixuan Yang, Xun Kang, Lili Zhou, Feng Chen, Wenbin Li

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2025. 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
–field-weighted citation impact
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.

  1. Article
  2. Article
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

6 authors.

Qiang Ji *Department of Neuro-oncology, Cancer Center, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Zixuan Yang *Department of Neuro-oncology, Cancer Center, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xun KangDepartment of Neuro-oncology, Cancer Center, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Lili ZhouDepartment of Neuro-oncology, Cancer Center, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Feng ChenDepartment of Neuro-oncology, Cancer Center, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Wenbin LiDepartment of Neuro-oncology, Cancer Center, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study investigates survival disparities and prognostic factors in patients with brain metastases originating from various primary cancers to facilitate risk stratification and enhance precision in diagnosis and treatment. Methods: Patients diagnosed with brain metastases between 2010 and 2018 were identified from the SEER database for analysis. Overall survival (OS) was evaluated using Kaplan-Meier curves and log-rank tests, complemented by multivariate Cox regression analysis. The impact of age on the risk and survival of brain metastases was examined using Restricted Cubic Splines (RCS) in Cox regression models. Results: A total of 55,094 patients diagnosed with brain metastases between 2010 and 2018 were retrospectively identified from the SEER database for inclusion in this study. It was found that the median survival times were 2 months (95% CI: 2-3 months) for liver cancer, 3 months (95% CI: 3-4 months) for stomach cancer, and 5 months (95% CI: 4-5 months) for lung cancer. Survival was influenced by factors such as sex, age, primary cancer site, race, income, marital status, and treatment approaches. Surgical treatment notably decreased the mortality risk, with a hazard ratio (HR) of 0.49 (95% CI: 4-5 months) for lung cancer, 0.43 (95% CI:3-4 months) for kidney cancer, and 0.63 (95% CI: 5-7 months) for breast cancer. The predictive model created with these variables achieved a C-index of 0.723 and 0.722 in the training and test sets, respectively, indicating vital accuracy. Calibration curves displayed minimal errors, and the area under the curve (AUC) values showed excellent performance at 3 months (training: 0.83, test: 0.83), 6 months (training: 0.80, test: 0.80), and 12 months (training: 0.77, test: 0.76). Conclusion: Brain metastases from liver, stomach, and lung cancers are linked to a poor prognosis. Surgical intervention significantly lowers mortality risk. The predictive model, which incorporates vital survival factors, demonstrates high accuracy and reliable performance, supporting the clinical management of patients with brain metastases. Systematic Review Registration: https://www.crd.york.ac.uk/prospero, identifier CRD420251054176.

Indexed as

brain metastasesprediction modelprognosisrisk factorsSEER

Identifiers

PMID40469182
PMCPMC12134067

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.