Anthony T Nguyen1, Michael Luu2, Diana J Lu1, Omid Hamid3, Jon Mallen-St Clair4, Mark B Faries5, Nima M Gharavi6, Allen S Ho4, Zachary S Zumsteg7. 1. Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California; Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California. 2. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California; Department of Biostatistics and Bioinformatics, Cedars-Sinai Medical Center, Los Angeles, California. 3. Department of Medical Oncology, Cedars-Sinai Medical Center, Los Angeles, California; The Angeles Clinic and Research Institute, Los Angeles, California. 4. Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California; Department of Surgery, Division of Otolaryngology-Head and Neck Surgery, Cedars-Sinai Medical Center, Los Angeles, California. 5. Department of Medical Oncology, Cedars-Sinai Medical Center, Los Angeles, California. 6. Department of Dermatology, Cedars-Sinai Medical Center, Los Angeles, California. 7. Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, California; Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California. Electronic address: zachary.zumsteg@cshs.org.
Abstract
BACKGROUND: Current lymph node (LN) staging for Merkel cell carcinoma (MCC) does not account for the number of metastatic LNs, which is a primary driver of survival in multiple cancers. OBJECTIVE: To determine the impact of the number of metastatic LNs on survival in MCC. METHODS: Patients with MCC undergoing surgery were identified from the National Cancer Database (NCDB). The association between metastatic LN number and survival was modeled with restricted cubic splines. A novel nodal classification system was derived by using recursive partitioning analysis. MCC patients undergoing surgery in the Surveillance, Epidemiology, and End Results (SEER) Program were used as validation cohort. RESULTS: Among 3670 patients in the NCDB, increasing metastatic LN number was associated with decreased survival (P < .001). Mortality risk increased continuously with each additional positive LN when using multivariable, nonlinear modeling. According to a novel staging system derived via recursive partitioning analysis, the hazard ratio for death in multivariable regression compared with patients without LN involvement was 1.24 (P = .049), 2.08 (P < .001), 3.24 (P < .001), and 6.13 (P < .001) for the proposed N1a (1-3 metastatic LNs with microscopic detection), N1b (1-3 metastatic LNs with macroscopic detection), N2 (4-8 metastatic LNs), and N3 (≥9 metastatic LNs), respectively. This system was validated in the SEER cohort and showed improved concordance compared with the American Joint Committee on Cancer, Eighth Edition. LIMITATIONS: Retrospective design. CONCLUSIONS: Number of metastatic LNs is the dominant nodal factor driving survival in patients with MCC.
BACKGROUND: Current lymph node (LN) staging for Merkel cell carcinoma (MCC) does not account for the number of metastatic LNs, which is a primary driver of survival in multiple cancers. OBJECTIVE: To determine the impact of the number of metastatic LNs on survival in MCC. METHODS:Patients with MCC undergoing surgery were identified from the National Cancer Database (NCDB). The association between metastatic LN number and survival was modeled with restricted cubic splines. A novel nodal classification system was derived by using recursive partitioning analysis. MCCpatients undergoing surgery in the Surveillance, Epidemiology, and End Results (SEER) Program were used as validation cohort. RESULTS: Among 3670 patients in the NCDB, increasing metastatic LN number was associated with decreased survival (P < .001). Mortality risk increased continuously with each additional positive LN when using multivariable, nonlinear modeling. According to a novel staging system derived via recursive partitioning analysis, the hazard ratio for death in multivariable regression compared with patients without LN involvement was 1.24 (P = .049), 2.08 (P < .001), 3.24 (P < .001), and 6.13 (P < .001) for the proposed N1a (1-3 metastatic LNs with microscopic detection), N1b (1-3 metastatic LNs with macroscopic detection), N2 (4-8 metastatic LNs), and N3 (≥9 metastatic LNs), respectively. This system was validated in the SEER cohort and showed improved concordance compared with the American Joint Committee on Cancer, Eighth Edition. LIMITATIONS: Retrospective design. CONCLUSIONS: Number of metastatic LNs is the dominant nodal factor driving survival in patients with MCC.
Authors: Richard J Straker; Michael J Carr; Andrew J Sinnamon; Adrienne B Shannon; James Sun; Karenia Landa; Kirsten M Baecher; Christian Wood; Kevin Lynch; Harrison G Bartels; Robyn Panchaud; Michael C Lowe; Craig L Slingluff; Mark J Jameson; Kenneth Tsai; Mark B Faries; Georgia M Beasley; Vernon Sondak; Giorgos C Karakousis; Jonathan S Zager; John T Miura Journal: Ann Surg Oncol Date: 2021-04-22 Impact factor: 5.344
Authors: Adrienne B Shannon; Richard J Straker; Michael J Carr; James Sun; Karenia Landa; Kirsten Baecher; Kevin Lynch; Harrison G Bartels; Robyn Panchaud; Luke J Keele; Michael C Lowe; Craig L Slingluff; Mark J Jameson; Kenneth Y Tsai; Mark B Faries; Georgia M Beasley; Vernon K Sondak; Giorgos C Karakousis; Jonathan S Zager; John T Miura Journal: Ann Surg Oncol Date: 2022-07-22 Impact factor: 4.339
Authors: Anthony T Nguyen; Michael Luu; Vina P Nguyen; Diana J Lu; Stephen L Shiao; Mitchell Kamrava; Katelyn M Atkins; Alain C Mita; Kevin S Scher; Daniel E Spratt; Mark B Faries; Timothy J Daskivich; De-Chen Lin; Michelle M Chen; Jon Mallen-St Clair; Howard M Sandler; Allen S Ho; Zachary S Zumsteg Journal: J Natl Cancer Inst Date: 2022-07-11 Impact factor: 11.816
Authors: Marita Yaghi; Paul Benedetto; John Greskovich; Roger Haber; Barbara Dominguez; Hong Liang; Zeina Nahleh; Rafael Arteta-Bulos Journal: JAAD Int Date: 2022-06-17