You are here

Article Text

Article menu
Download PDFPDF
Original research
Low level of complement factor H increases the risk of cancer-related death in patients with small-cell lung cancer
  1. Mengqi Xiang1,
  2. Huachuan Zhang2,
  3. Lingna Kou1,
  4. Jing Chen1,
  5. Zhihua Xu3,
  6. Jintao He2
  1. 1 Department of Medical Oncology, Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
  2. 2 Department of Thoracic Surgery, Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China
  3. 3 General Surgery, First Affiliated Hospital of Soochow University, Suzhou, China
  1. Correspondence to Dr Jintao He, Department of Thoracic Surgery, Sichuan Cancer Hospital and Institute, Chengdu, Sichuan, China; zlyytsg{at}sichuancancer.org

Abstract

Introduction Pulmonary cancer is a kind of deeply invasive tumour which is difficult to treat, and its mortality rate is high. Previous research has shown that activation of complement could contribute to the progression of non-small-cell lung cancer (SCLC). However, little research has been done on SCLC.

Methods Complement factor H (CFH), complements C3 as well as C4 were measured in patients, and the prognostic impact of different parameters was assessed by log-rank function analysis and Cox multifactor models. Besides, we constructed a predictive model based on complement fractions and validated the accuracy of the model.

Results Among these 242 patients, 200 (82.6%) died. The median survival time was 18.3 months. We found by multifactorial analysis that high levels of CFH decreased the risk of death (HR 0.23, 95% CI 0.10 to 0.57, p<0.001), while elevated complement C4 displayed poor prognosis (HR 2.28, 95% CI 1.66 to 3.13, p<0.001). We screened variables by Cox models and constructed CFH-based prediction models to plot a nomogram by internal validation. The nomogram showed excellent accuracy in assessing the probability of death, yielding an adjusted C-statistics of 0.905.

Conclusions CFH can be recognised as a biomarker to predict the risk of death in SCLC. The prediction model established based on CFH, C3 and C4 levels has good accuracy in patients’ prognostic assessment.

  • complementary medicine
  • oncology

Data availability statement

Data are available upon reasonable request.

http://dx.doi.org/10.1136/postgradmedj-2021-141186

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Data availability statement

    Data are available upon reasonable request.

    View Full Text

    Footnotes

    • MX and HZ are joint first authors.

    • Contributors MX designed and performed research studies, collected and analysed the data, and wrote the manuscript. HZ and LK ordered and analysed the data. JC contributed to the data analysis. ZX and JH contributed to research design, writing the document and supervision of the study.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Disclaimer This work was supported by the Sichuan Cancer Hospital.

    • Competing interests None declared.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.