Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comment
. 2025 Jun 17:16:1577773.
doi: 10.3389/fimmu.2025.1577773. eCollection 2025.

Commentary: Molecular and immunological features of TREM1 and its emergence as a prognostic indicator in glioma

Jihao Xue #  1 , Zhilin Luo #  2 , Tao Wang #  1 , Qijia Yin  1 , Ligang Chen  1
Affiliations
Comment

Commentary: Molecular and immunological features of TREM1 and its emergence as a prognostic indicator in glioma

Jihao Xue et al. Front Immunol. .
No abstract available

Keywords: Cox regression; glioma; nomogram; prediction; proportional hazards (PH) assumption.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Development and evaluation of the nomogram. (A) Multivariate Cox regression analysis in the TCGA cohort. (B) Nomogram for predicting the survival probability of glioma patients. (C) Calibration curves for predicting the 1-year, 3-year, and 5-year survival probability of glioma patients.
See this image and copyright information in PMC

Comment on

Similar articles

See all similar articles

References

    1. Zhang L, Qu X, Xu Y. Molecular and immunological features of trem1 and its emergence as a prognostic indicator in glioma. Front Immunol. (2024) 15:1324010. doi: 10.3389/fimmu.2024.1324010 - DOI - PMC - PubMed
    1. Thomas LE, Turakhia MP, Pencina MJ. Competing risks, treatment switching, and informative censoring. JAMA Cardiol. (2021) 6:871–3. doi: 10.1001/jamacardio.2021.1239 - DOI - PubMed
    1. Lee KH, Rondeau V, Haneuse S. Accelerated failure time models for semi-competing risks data in the presence of complex censoring. Biometrics. (2017) 73:1401–12. doi: 10.1111/biom.12696 - DOI - PMC - PubMed
    1. Ning J, Qin J, Shen Y. Score estimating equations from embedded likelihood functions under accelerated failure time model. J Am Stat Assoc. (2014) 109:1625–35. doi: 10.1080/01621459.2014.946034 - DOI - PMC - PubMed
    1. Crowther MJ, Royston P, Clements M. A flexible parametric accelerated failure time model and the extension to time-dependent acceleration factors. Biostatistics. (2023) 24:811–31. doi: 10.1093/biostatistics/kxac009 - DOI - PMC - PubMed

LinkOut - more resources