2018-19 Section 7-Neoplastic and Inflammatory Diseases of the Head and Neck eBook

Lymph Node Staging for Salivary Cancer/Aro et al

not available for all patients, including tumor grade, ENE, and surgical margins. We used multiple imputation to account for this, but any methodology to account for missing data has limitations and the potential for bias. Last, the NCDB has no information regarding patterns of disease recurrence, and therefore it is not clear whether the increased mortality risk conveyed by increasing numbers of pathologic LNs is a result of regional disease recurrence, distant disease recurrence, or both. This would be an interesting topic for investigation in other large data sets of salivary cancer cases. Despite these limitations, we believe the central findings of the current study, among them that the number of positive LNs is strongly associ- ated with survival and can improve LN staging in patients with SGC, are robust. Conclusions Quantitative metastatic LN burden is strongly associated with mortality in patients with SGC, with each additional metastatic LN conferring an increased risk of death with- out plateau. Staging parameters currently in use, includ- ing LN size, contralaterality, and ENE, lack independent prognostic value when accounting for the number of met- astatic LNs. This information ultimately will help triage high-risk patients who may benefit from more aggressive adjuvant therapy. FUNDING SUPPORT Supported in part by the National Institutes of Health (grant R01 CA188480-01A1) and the National Center for Advancing Transla- tional Sciences (grants UL1TR000124 and UL1TR001881-01). CONFLICT OF INTEREST DISCLOSURES Zachary S. Zumsteg is on the external advisory board for the Scripps Proton Therapy Center and has been a paid consultant for EMD Serono for work performed outside of the current study. Katri Aro is supported by the Sigrid Juselius Foundation and the Finnish Otorhinolaryngology Research Foundation for work per- formed outside of the current study. AUTHOR CONTRIBUTIONS: Conceptualization: Allen S. Ho and Zachary S. Zumsteg . Data curation: Michael Luu and Zachary S. Zumsteg . Formal analysis: Michael Luu . Methodology: Allen S. Ho, Michael Luu, Sungjin Kim, Mourad Tighiouart , and Zachary S. Zumsteg . Supervision: Zachary S. Zumsteg . Data interpretation: All authors . Writing- original draft: Katri Aro, Allen S. Ho , and Zachary S. Zumsteg . Writing-review and editing: All authors . REFERENCES 1. Lloyd S, Yu JB, Ross DA, Wilson LD, Decker RH. A prognostic index for predicting lymph node metastasis in minor salivary gland cancer. Int J Radiat Oncol Biol Phys . 2010;76:169-175.

2. Armstrong JG, Harrison LB, Thaler HT, et al. The indications for elective treatment of the neck in cancer of the major salivary glands. Cancer . 1992;69:615-619. 3. Yoo SH, Roh JL, Kim SO, et al. Patterns and treatment of neck metastases in patients with salivary gland cancers. J Surg Oncol . 2015;111:1000-1006. 4. Ali S, Palmer FL, Yu C, et al. A predictive nomogram for recurrence of carcinoma of the major salivary glands. JAMA Otolaryngol Head Neck Surg . 2013;139:698-705. 5. Zeidan YH, Pekelis L, An Y, et al. Survival benefit for adjuvant radi- ation therapy in minor salivary gland cancers. Oral Oncol . 2015;51: 438-445. 6. Aro K, Tarkkanen J, Saat R, Saarilahti K, Makitie A, Atula T. Sub- mandibular gland cancer: specific features and treatment consider- ations. Head Neck . 2018;40:154-162. 7. Amin MB, Edge SB, Greene FL, et al, eds. AJCC Cancer Staging Manual. 8th ed. New York: Springer; 2017. 8. Ho AS, Kim S, Tighiouart M, et al. Metastatic lymph node bur- den and survival in oral cavity cancer. J Clin Oncol . 2017;35:3601- 3609. 9. Roberts TJ, Colevas AD, Hara W, Holsinger FC, Oakley-Girvan I, Divi V. Number of positive nodes is superior to the lymph node ratio and American Joint Committee on Cancer N staging for the prognosis of surgically treated head and neck squamous cell carcino- mas. Cancer . 2016;122:1388-1397. 10. Divi V, Chen MM, Nussenbaum B, et al. Lymph node count from neck dissection predicts mortality in head and neck cancer. J Clin Oncol . 2016;34:3892-3897. 11. Ho AS, Kim S, Tighiouart M, et al. Association of quantitative met- astatic lymph node burden with survival in hypopharyngeal and laryngeal cancer [published online ahead of print November 30, 2017]. JAMA Oncol . doi: 10.1001/jamaoncol.2017.3852. 12. Steele GD Jr, Osteen RT, Winchester DP, Murphy GP, Menck HR. Clinical highlights from the National Cancer Data Base: 1994. CA Cancer J Clin . 1994;44:71-80. 13. Barnes L, Eveson JW, Reichart P, Sidransky D, eds. Pathology and Genetics of Head and Neck Tumours WHO Classification of Tumours. 3rd Ed. Lyon, France: IARC Press; 2005;9:209– 210. 14. El-Naggar AK, Chan JKC, Gramdis JR, Takata T, Slootweg PJ, eds. WHO Classification of Head and Neck Tumours WHO Classification of Tumours. 4th Ed. Lyon, France: IARC Press; 2017;9:159–160. 15. Little R. A test of missing completely at random for multivariable data with missing values. J Am Stat Assoc . 1988;83:1198-1202. 16. van Buuren S. Multiple imputation of discrete and continuous data by fully conditional specification. Stat Methods Med Res . 2007;16: 219-242. 17. Rubin D. Statistical matching using file concatenation with adjusted weights and multiple imputations. J Business Econ Stat . 1986;4:87- 94. 18. Kalbfleisch JD, Prentice RL. The Statistical Analysis of Failure Time Data. Wiley Series in Probability and Mathematical Statistics. New York: John Wiley & Sons Inc; 1980. 19. Cox DR. Regression models and life tables. J R Stat Soc B . 1972; B34:187-220. 20. Grambsch P, Therneau T. Proportional hazards tests and diagnostics based on weighted residuals. Biometrika . 1994;81:515-526. 21. Harrell FE Jr, ed. Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. New York: Springer; 2015. 22. Muggeo V. Segmented: an R package to fit regression models with broken-line relationships. R News . 2008;8:20-25. 23. Muggeo VM. Estimating regression models with unknown break- points. Stat Med . 2003;22:3055-3071. 24. Hothorn T, Hornik K, Zeileis A. Unbiased recursive partitioning: a conditional inference framework. J Comput Graph Stat . 2006;15: 651-674. 25. Hothorn T, Zeileis A. Partykit: a modular toolkit for recursive parti- tioning in R. J Machine Learn Res . 2015;16:3905-3909. 26. Strasser H, Weber C. On the asymptotic theory of permutation sta- tistics. Math Methods Stat . 1999;8:220-250.

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