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El-Zein RA, Lopez MS, D'Amelio AM, et al. The cytokinesis-blocked micronucleus assay as a strong predictor of lung cancer: extension of a lung cancer risk prediction model. Cancer Epidemiol Biomarkers Prev. 2014;23(11):2462-70doi: 10.1158/1055-9965.EPI-14-0462.
El-Zein, R. A., Lopez, M. S., D'Amelio, A. M., Liu, M., Munden, R. F., Christiani, D., Su, L., Tejera-Alveraz, P., Zhai, R., Spitz, M. R., & Etzel, C. J. (2014). The cytokinesis-blocked micronucleus assay as a strong predictor of lung cancer: extension of a lung cancer risk prediction model. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 23(11), 2462-70. https://doi.org/10.1158/1055-9965.EPI-14-0462
El-Zein, Randa A, et al. "The cytokinesis-blocked micronucleus assay as a strong predictor of lung cancer: extension of a lung cancer risk prediction model." Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology vol. 23,11 (2014): 2462-70. doi: https://doi.org/10.1158/1055-9965.EPI-14-0462
El-Zein RA, Lopez MS, D'Amelio AM, Liu M, Munden RF, Christiani D, Su L, Tejera-Alveraz P, Zhai R, Spitz MR, Etzel CJ. The cytokinesis-blocked micronucleus assay as a strong predictor of lung cancer: extension of a lung cancer risk prediction model. Cancer Epidemiol Biomarkers Prev. 2014 Nov;23(11):2462-70. doi: 10.1158/1055-9965.EPI-14-0462. Epub 2014 Aug 29. PMID: 25172871; PMCID: PMC4487661.
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Cancer Epidemiol Biomarkers Prev. 2014 Nov;23(11):2462-70. doi: 10.1158/1055-9965.EPI-14-0462. Epub 2014 Aug 29.

The cytokinesis-blocked micronucleus assay as a strong predictor of lung cancer: extension of a lung cancer risk prediction model.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology

Randa A El-Zein, Mirtha S Lopez, Anthony M D'Amelio, Mei Liu, Reginald F Munden, David Christiani, Li Su, Paula Tejera-Alveraz, Rihong Zhai, Margaret R Spitz, Carol J Etzel

Affiliations

  1. Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas. [email protected].
  2. Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  3. Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, Texas. CORRONA, Inc., Southborough, Massachusetts.
  4. Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas. Houston Methodist, Houston, Texas.
  5. Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts.
  6. Dan L. Duncan Cancer Center, Houston, Texas.

PMID: 25172871 PMCID: PMC4487661 DOI: 10.1158/1055-9965.EPI-14-0462

Abstract

BACKGROUND: There is an urgent need to improve lung cancer outcome by identifying and validating markers of risk. We previously reported that the cytokinesis-blocked micronucleus assay (CBMN) is a strong predictor of lung cancer risk. Here, we validate our findings in an independent external lung cancer population and test discriminatory power improvement of the Spitz risk prediction model upon extension with this biomarker.

METHODS: A total of 1,506 participants were stratified into a test set of 995 (527 cases/468 controls) from MD Anderson Cancer Center (Houston, TX) and a validation set of 511 (239 cases/272 controls) from Massachusetts General Hospital (Boston, MA). An epidemiologic questionnaire was administered and genetic instability was assessed using the CBMN assay.

RESULTS: Excellent concordance was observed between the two populations in levels and distribution of CBMN endpoints [binucleated-micronuclei (BN-MN), binucleated-nucleoplasmic bridges (BN-NPB)] with significantly higher mean BN-MN and BN-NPB values among cases (P < 0.0001). Extension of the Spitz model led to an overall improvement in the AUC (95% confidence intervals) from 0.61 (55.5-65.7) with epidemiologic variables to 0.92 (89.4-94.2) with addition of the BN-MN endpoint. The most dramatic improvement was observed with the never-smokers extended model followed by the former and current smokers.

CONCLUSIONS: The CBMN assay is a sensitive and specific predictor of lung cancer risk, and extension of the Spitz risk prediction model led to an AUC that may prove useful in population screening programs to identify the "true" high-risk individuals.

IMPACT: Identifying high-risk subgroups that would benefit from screening surveillance has immense public health significance.

©2014 American Association for Cancer Research.

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