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Cancer Causes & Control

, Volume 21, Issue 5, pp 709–718 | Cite as

Insulin resistance-related biomarker clustering and subclinical inflammation as predictors of cancer mortality during 21.5 years of follow-up

  • Wann J. Loh
  • Bernard V. North
  • Desmond G. Johnston
  • Ian F. Godsland
Original paper

Abstract

Objectives

Risk of cancer is increased in conditions associated with insulin resistance, but this could be secondary to subclinical inflammation. We evaluated whether insulinemia, indices of insulin resistance or a validated insulin resistance-related biomarker cluster, could predict cancer mortality independently of subclinical inflammation.

Methods

Fasting insulin and glucose concentrations and insulin-related metabolic variables were recorded in 1,016 white males, of whom 718 also had an oral glucose tolerance test (OGTT). Baseline measurements included the following: fasting insulin and the derived insulin resistance index, HOMA-IR; OGTT insulin and the derived insulin resistance index, Matsuda-IS; the factor score for a validated insulin resistance-related biomarker cluster; white blood cell count; erythrocyte sedimentation rate; and serum albumin and globulin concentrations.

Results

There were 105 deaths from cancer during the 21.5-year mean follow-up. Insulin concentrations and insulin resistance were not predictive. Insulin resistance-related biomarker clustering predicted cancer mortality (hazard ratio 1.65, 95% CI 1.26–2.17, p < 0.001). Subclinical inflammation markers were also predictive, but the insulin resistance-related biomarker cluster predicted cancer mortality independently of these and was particularly associated with death from colorectal cancer.

Conclusions

Despite insulin concentrations or derived indices of insulin resistance failing to predict cancer mortality, insulin resistance-related biomarker clustering was highly predictive and predicted independently of simple measures of subclinical inflammation.

Keywords

Insulin resistance Inflammation Biomarkers Cancer mortality 

Notes

Acknowledgments

Professor Victor Wynn initiated the HDDRISC study and directed it for much of its course. Since it began, the study has been sustained by many clinical, scientific, technical, nursing, and administrative staff, to each of whom we extend our thanks. This study was funded by the Atherosclerosis Research Trust, the Heart Disease and Diabetes Research Trust, and the Cecil Rosen Foundation. Salary support for IFG is provided by the Heart Disease and Diabetes Research Trust. The authors have nothing disclose.

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  • Wann J. Loh
    • 1
  • Bernard V. North
    • 2
  • Desmond G. Johnston
    • 1
  • Ian F. Godsland
    • 1
  1. 1.Endocrinology and Metabolic MedicineImperial College LondonLondonUK
  2. 2.Department of Epidemiology and Public HealthImperial College LondonLondonUK

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