ArticleFrontiers in immunology2025
Liver metastases in thyroid cancer: epidemiology, risk stratification and survival outcomes in the immunotherapy era.
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Calcified liver metastases from medullary thyroid carcinoma in a Multiple Endocrine Neoplasia Type 2A patient.Radiology case reports · 2026Article
- Risk factors and predictive nomograms for early mortality in patients with thyroid cancer lung metastasis based on the SEER database and a Chinese population study.Gland surgery · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Liver metastases in thyroid cancer are rare but fatal, with poorly defined risk profiles and survival outcomes. This study aimed to characterize epidemiology, risk factors and outcomes of this disease using a population-based approach, further explore the potential impact of the immunotherapy era on the prognosis of these patients. Methods: Data on 116,801 thyroid cancer cases from SEER program (2010-2021) were analyzed. The clinicopathological features of patients with and without liver metastases were compared. Logistic regression analyses were employed to identify the predictors for liver metastases, while survival determinants were determined using Cox regression models. The predictive nomogram was developed for liver metastasis risk assessment, validated using concordance index, calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). In addition, we further compared the prognostic outcomes of these patients in the immunotherapy era. Results: The prevalence of liver metastasis in thyroid cancer was 0.22% (95%CI 0.20%-0.25%), predominantly in medullary thyroid carcinoma (MTC) and anaplastic thyroid carcinoma (ATC). MTC exhibited the highest risk of metastasis (OR=35.7, 95%CI 24.1-52.8). The nomogram for liver metastasis risk (C-index=0.98) demonstrated robust discriminatory ability and clinical utility. The median overall survival (OS) was 6.0 months (95%CI 4.0-8.0), with survival rates of 38.1% at 1 year, 28.3% at 3 years, and 16.5% at 5 years. Patients with ATC and rare histology types experienced significantly shorter survival. No statistically significant difference in mOS and median cancer-specific survival (mCSS) of these patients between the pre- and post-immunotherapy eras were observed (P>0.05 for both). Conclusion: This study establishes the first population-based predictive framework for liver metastases in thyroid cancer, underscoring risk stratification and survival. These findings also highlight the critical need to optimize survival outcomes for this aggressive metastatic phenotype in immunotherapy era.
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.