Skip to main content

Advertisement

Log in

Cancer-Specific Mortality and Competing Mortality in Patients with Head and Neck Squamous Cell Carcinoma: A Competing Risk Analysis

  • Head and Neck Oncology
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

The objective of this study was to estimate probabilities of cancer-specific death and competing death for patients with head and neck squamous cell carcinoma (HNSCC). In addition, we attempted to construct competing risk nomograms to predict prognosis for patients with HNSCC using a large population-based cohort.

Methods

Patients diagnosed with nonmetastatic HNSCC between 2000 and 2010 were identified from the Surveillance Epidemiology and End Results Program to form the analytic cohort. We estimated cumulative incident function (CIF) of cancer-specific mortality and competing mortality. Nomograms for predicting probability of death were built with proportional subdistribution hazard models.

Results

The study cohort included 23,494 patients with HNSCC. The 5-year CIF for cancer-specific death and competing death were 26.7 % (95 % confidence interval [CI] 26–27.3 %) and 12.7 % (95 % CI 12.2–13.3 %), respectively; 10-year CIF were 32.8 % (95 % CI 31.9–33.6 %) and 23 % (95 % CI 22.1–24 %), respectively. On multivariate analysis, increasing cause-specific mortality was associated with increasing age, increasing tumor size, black race, single status, advanced T and N classifications, and high tumor grade. Increasing probability of competing mortality had a relationship with increasing age, male, black race, single status and nonradiotherapy. Models showed good accuracy with c-index of 0.73 for cause-specific mortality model and 0.69 for competing mortality model.

Conclusions

We constructed competing risk nomograms for HNSCC using population-based data. The model used for building nomograms represented good performance. These nomograms can serve to guide management of patients with HNSCC.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Ferlay J, Shin HR, Bray F, Forman D, Mathers C, Parkin DM. Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008. Int J Cancer. 2010;127(12):2893–917.

    Article  CAS  PubMed  Google Scholar 

  2. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA: Cancer J Clin. 2013;63(1):11–30.

    Google Scholar 

  3. Kuperman DI, Auethavekiat V, Adkins DR, et al. Squamous cell cancer of the head and neck with distant metastasis at presentation. Head Neck. 2011;33(5):714–8.

    Article  PubMed  Google Scholar 

  4. Surveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) SEER*Stat Database: Incidence - SEER 9 Regs Research Data, Nov 2011 Sub (1973-2010) <Katrina/Rita Population Adjustment>- Linked To County Attributes - Total U.S., 1969–2010 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, Surveillance Systems Branch, released April 2013, based on the November 2012 submission.

  5. Argiris A, Brockstein BE, Haraf DJ, et al. Competing causes of death and second primary tumors in patients with locoregionally advanced head and neck cancer treated with chemoradiotherapy. Clin Cancer Res. 2004;10(6):1956–62.

    Article  CAS  PubMed  Google Scholar 

  6. Adelstein DJ, Li Y, Adams GL, et al. An intergroup phase III comparison of standard radiation therapy and two schedules of concurrent chemoradiotherapy in patients with unresectable squamous cell head and neck cancer. J Clin Oncol. 2003;21(1):92–8.

    Article  PubMed  Google Scholar 

  7. Mell LK, Dignam JJ, Salama JK, et al. Predictors of competing mortality in advanced head and neck cancer. J Clin Oncol. 2010;28(1):15–20.

    Article  PubMed  Google Scholar 

  8. Gray RJ. A class of k-sample tests for comparing the cumulative incidence of a competing risk. Ann Stat. 1988;16:1141–54.

    Article  Google Scholar 

  9. Fine JP, Gray RJ. A proportional hazards model for the subdistribution of competing risks in survival analysis. J Am Stat Assoc. 1999;94:496–509.

    Article  Google Scholar 

  10. Harrell FE. Regression modeling strategies: With applications to linear models, logistic regression, and survival analysis. New York: Springer; 2001.

    Book  Google Scholar 

  11. Kattan MW, Heller G, Brennan MF. A competing-risks nomogram for sarcoma-specific death following local recurrence. Stat Med. 2003;22(22):3515–25.

    Article  PubMed  Google Scholar 

  12. Kalbfleisch JD, Prentice RL. The statistical analysis of failure time data. Hoboken, New Jersey: Wiley & Sons, Inc.; 1980.

  13. R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.

  14. Frank E Harrell Jr < f.harrell@vanderbilt.edu > (2011). rms: Regression modeling strategies. R package version 3.3-1. http://CRAN.R-project.org/package=rms.

  15. Bob Gray < gray@jimmy.harvard.edu > (2011). cmprsk: Subdistribution analysis of competing risks. R package version 2.2-2. http://CRAN.R-project.org/package=cmprsk.

  16. Wolbers M, Koller MT, Witteman JC, Steyerberg EW. Prognostic models with competing risks: methods and application to coronary risk prediction. Epidemiology. 2009;20(4):555–61.

    Article  PubMed  Google Scholar 

  17. Pintilie M. Competing risks: a practical perspective. Chichester, West Sussex, England: John Wiley & Sons Ltd.; 2006.

  18. Hinchliffe SR, Lambert PC. Flexible parametric modelling of cause-specific hazards to estimate cumulative incidence functions. BMC Med Res Methodol. 2013;13:13.

    Article  PubMed Central  PubMed  Google Scholar 

  19. Yang L, Shen W, Sakamoto N. Population-based study evaluating and predicting the probability of death resulting from thyroid cancer and other causes among patients with thyroid cancer. J Clin Oncol. 2013;31(4):468–74.

    Article  PubMed  Google Scholar 

  20. Rose BS, Jeong JH, Nath SK, Lu SM, Mell LK. Population-based study of competing mortality in head and neck cancer. J Clin Oncol. 2011;29(26):3503–9.

    Article  PubMed  Google Scholar 

  21. Iasonos A, Schrag D, Raj GV, Panageas KS. How to build and interpret a nomogram for cancer prognosis. J Clin Oncol. 2008;26(8):1364–70.

    Article  PubMed  Google Scholar 

  22. Hanrahan EO, Gonzalez-Angulo AM, Giordano SH, et al. Overall survival and cause-specific mortality of patients with stage T1a,bN0M0 breast carcinoma. J Clin Oncol. 2007;25(31):4952–60.

    Article  PubMed  Google Scholar 

  23. Porter CR, Suardi N, Capitanio U, et al. A nomogram predicting prostate cancer-specific mortality after radical prostatectomy. Urol Int. 2010;84(2):132–40.

    Article  PubMed  Google Scholar 

  24. Stephenson AJ, Kattan MW, Eastham JA, et al. Prostate cancer-specific mortality after radical prostatectomy for patients treated in the prostate-specific antigen era. J Clin Oncol. 2009;27(26):4300–5.

    Article  PubMed Central  PubMed  Google Scholar 

  25. Kutikov A, Egleston BL, Wong YN, Uzzo RG. Evaluating overall survival and competing risks of death in patients with localized renal cell carcinoma using a comprehensive nomogram. J Clin Oncol. Jan 10 2010;28(2):311–7.

    Article  PubMed Central  PubMed  Google Scholar 

  26. Pathak KA, Mazurat A, Lambert P, Klonisch T, Nason RW. Prognostic nomograms to predict oncological outcome of thyroid cancers. J Clin Endocrinol Metab. 2013;98(12):4768–75.

    Article  CAS  PubMed  Google Scholar 

  27. Kutikov A, Cooperberg MR, Paciorek AT, Uzzo RG, Carroll PR, Boorjian SA. Evaluating prostate cancer mortality and competing risks of death in patients with localized prostate cancer using a comprehensive nomogram. Prostate Cancer Prostatic Dis. 2012;15(4):374–9.

    Article  CAS  PubMed  Google Scholar 

  28. Montero PH, Yu C, Palmer FL, et al. Nomograms for preoperative prediction of prognosis in patients with oral cavity squamous cell carcinoma. Cancer. 2014;120(2):214–21.

    Article  PubMed  Google Scholar 

  29. Ali S, Palmer FL, Yu C, et al. Postoperative nomograms predictive of survival after surgical management of malignant tumors of the major salivary glands. Ann Surg Oncol. 2014;21(2):637–42.

  30. Du XL, Fox EE, Lai D. Competing causes of death for women with breast cancer and change over time from 1975 to 2003. Am J Clin Oncol. 2008;31(2):105–16.

    Article  PubMed Central  PubMed  Google Scholar 

  31. Kircher T, Nelson J, Burdo H. The autopsy as a measure of accuracy of the death certificate. N Engl J Med. 1985;313(20):1263–9.

    Article  CAS  PubMed  Google Scholar 

  32. Lughezzani G, Sun M, Shariat SF, et al. A population-based competing-risks analysis of the survival of patients treated with radical cystectomy for bladder cancer. Cancer. 2011;117(1):103–9.

    Article  PubMed  Google Scholar 

  33. Beyersmann J, Schumacher M, Allignol A. Competing risks and multistate Models with R (Use R!). New York, NY: Springer Science + Business Media; 2012.

    Book  Google Scholar 

  34. Steyerberg EW. Clinical prediction models: a practical approach to development, validation, and updating. New York: Springer; 2009.

    Book  Google Scholar 

Download references

Acknowledgment

The authors thank Dr. Wolbers for providing guidance in calculating the c-index. The authors also thank SEER for open access to their database.

Disclosure

None.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Limin Yang MD, PhD.

Additional information

Weidong Shen and Limin Yang have contributed equally to this work.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shen, W., Sakamoto, N. & Yang, L. Cancer-Specific Mortality and Competing Mortality in Patients with Head and Neck Squamous Cell Carcinoma: A Competing Risk Analysis. Ann Surg Oncol 22, 264–271 (2015). https://doi.org/10.1245/s10434-014-3951-8

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1245/s10434-014-3951-8

Keywords

Navigation