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
. 2022 Jun 17:15:3573-3586.
doi: 10.2147/JIR.S361300. eCollection 2022.

Prognostic Roles of Inflammation- and Nutrition-Based Indicators for Female Patients with Cancer

Ming Yang  1   2   3 , Qi Zhang  1   2   3 , Yizhong Ge  1   2   3   4 , Meng Tang  1   2   3 , Chunlei Hu  1   2   3 , Ziwen Wang  1   2   3 , Xi Zhang  1   2   3 , Mengmeng Song  1   2   3 , Guotian Ruan  1   2   3 , Xiaowei Zhang  1   2   3 , Tong Liu  1   2   3 , Hailun Xie  1   2   3 , Heyang Zhang  1   2   3 , Kangping Zhang  1   2   3 , Qinqin Li  1   2   3 , Xiangrui Li  1   2   3 , Xiaoyue Liu  1   2   3 , Shiqi Lin  1   2   3   4 , Hanping Shi  1   2   3
Affiliations

Prognostic Roles of Inflammation- and Nutrition-Based Indicators for Female Patients with Cancer

Ming Yang et al. J Inflamm Res. .

Abstract

Purpose: The incidence, progression, and prognosis of cancer could be affected by inflammation and nutrition. Female patients have different inflammatory and nutritional states depending on their age and tumor types. It is important to screen for suitable prognostic indicators in female patients with cancer of different ages and tumor types.

Patients and methods: Baseline clinicopathologic and laboratory characteristics of 1502 female patients with cancer were obtained from a multicenter cohort study. Concordance indices (C-indices) were used to evaluate the prediction accuracy of following inflammation- and nutrition-based indicators: advanced lung cancer inflammation index (ALI), systemic immune inflammation index (SII), modified geriatric nutritional risk index (mGNRI), albumin-to-globulin ratio (AGR), prognostic nutritional index (PNI), lymphocyte-to-C-reactive protein ratio (LCR), controlling nutritional status score (CONUT), modified Glasgow prognostic score (mGPS), and lymphocyte-to-C-reactive protein score (LCS).

Results: The most suitable indicators in different female populations with cancer had C-indices as follows: LCR (0.668; 95% CI, 0.644-0.693) for all females; AGR (0.681; 95% CI, 0.619-0.743) for young females; LCR (0.667; 95% CI, 0.628-0.706) for middle-aged females; ALI (0.597; 95% CI, 0.574-0.620) for elderly females; LCR (0.684; 95% CI, 0.621-0.747) for females with reproductive system cancer; and ALI (0.652; 95% CI, 0.624-0.680) for females with non-reproductive system cancer.

Conclusion: The most suitable indicators for the different female populations with cancer are summarized as follows: LCR for all females, AGR for young females, LCR for middle-aged females, ALI for elderly females, LCR for females with reproductive system cancer, and ALI for females with non-reproductive system cancer.

Keywords: cancer; female; inflammation; nutrition; prognosis.

PubMed Disclaimer

Conflict of interest statement

The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
Flow diagram for the selection of female patients with cancer from a multicenter clinical database.
Figure 2
Figure 2
Kaplan-Meier curves of associations among indicators and OS in females with cancer. (A) ALI. (B) SII. (C) AGR. (D) LCR. (E) mGPS. (F) LCS. (G) PNI. (H) mGNRI. (I) CONUT.
Figure 3
Figure 3
Associations between indicators and OS in different subgroups. (A) for ALI. (B) for SII. (C) for AGR. (D) for LCR. (E) for mGPS. (F) for LCS. (G) for PNI. (H) for mGNRI. (I) for CONUT. (A–I) were adjusted for age, body mass index, type of cancer, smoking status, alcohol consumption, TNM stage, history of surgery, radiotherapy, and chemotherapy, Karnofsky performance status score and Scored Patient-Generated Subjective Global Assessment.
Figure 4
Figure 4
AUCs of indicators in females with cancer.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022;72(1):7–33. doi:10.3322/caac.21708 - DOI - PubMed
    1. Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002;420(6917):860–867. doi:10.1038/nature01322 - DOI - PMC - PubMed
    1. Vander Heiden MG, DeBerardinis RJ. Understanding the intersections between metabolism and cancer biology. Cell. 2017;168(4):657–669. doi:10.1016/j.cell.2016.12.039 - DOI - PMC - PubMed
    1. Sapienza C, Issa JP. Diet, nutrition, and cancer epigenetics. Annu Rev Nutr. 2016;36:665–681. doi:10.1146/annurev-nutr-121415-112634 - DOI - PubMed
    1. Muenst S, Laubli H, Soysal SD, Zippelius A, Tzankov A, Hoeller S. The immune system and cancer evasion strategies: therapeutic concepts. J Intern Med. 2016;279(6):541–562. doi:10.1111/joim.12470 - DOI - PubMed