Prognostic Case Volume Thresholds in Patients With Head and Neck Squamous Cell Carcinoma | Head and Neck Cancer | JAMA Otolaryngology–Head & Neck Surgery | JAMA Network
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Figure 1.  Flow Diagram
Flow Diagram

AJCC indicates American Joint Committee on Cancer; HNSCC, head and neck squamous cell carcinoma; HPV, human papillomavirus; M0, without distant metastases; and M1, with distant metastases.

Figure 2.  Proportion of Patients Treated Stratified by Facility Volume
Proportion of Patients Treated Stratified by Facility Volume

The number of cases per year is defined in the Results subsection Facility Volume Thresholds.

Figure 3.  Kaplan-Meier Curve Stratified by Facility Volume
Kaplan-Meier Curve Stratified by Facility Volume

The number of cases per year is defined in the Results subsection Facility Volume Thresholds.

Figure 4.  Adjusted Hazard Ratios of Stratified Facility Volume by Specific Subset of Patients
Adjusted Hazard Ratios of Stratified Facility Volume by Specific Subset of Patients

The number of cases per year is defined in the Results subsection Facility Volume Thresholds. Moderate-volume facilities (MVFs) were the reference for comparison. CoC indicates Commission on Cancer; Nonoropharyngeal HNSCC, nonoropharyngeal head and neck squamous cell carcinoma; HPV, human papillomavirus; HVF, high-volume facility; LVF, low-volume facility; oropharyngeal HNSCC, oropharyngeal head and neck squamous cell carcinoma. Full Cox regressions may be found in eTables 6, 9, 12, and 15 in the Supplement.

Figure 5.  Kaplan-Meier Curve Stratified by Facility Volume for Head and Neck Squamous Cell Carcinoma (HNSCC)
Kaplan-Meier Curve Stratified by Facility Volume for Head and Neck Squamous Cell Carcinoma (HNSCC)
Supplement.

eTable 1. Survival for 10 Groups With an Approximately Equal Number of Events

eTable 2. Survival for Low-, Moderate-, and High-volume Facilities

eTable 3. Facility Characteristics Stratified by Facility Volume for the Eligible Cohort

eTable 4. Patient Demographics, Facility Characteristics, and Oncologic Factors Stratified by Facility Volume for the Whole Cohort

eTable 5. Patient Demographics, Facility Characteristics, and Oncologic Factors Stratified by Facility Volume for the All Patients Treated at 1 CoC Facility

eTable 6. Multivariate Cox Regression For Survival for All Patients and All Patients Treated at 1 CoC Facility

eTable 7. Localized Stage (I/II) Patient Demographics, Facility Characteristics, and Oncologic Factors Stratified by Facility Volume

eTable 8. Advanced Stage (III/IV) Patient Demographics, Facility Characteristics, and Oncologic Factors Stratified by Facility Volume

eTable 9. Multivariate Cox Regression Stratified by Localized/Advanced Status

eTable 10. Nondistant Metastatic Patient Demographics, Facility Characteristics, and Oncologic Factors Stratified by Facility Volume

eTable 11. Distant Metastatic Patient Demographics, Facility Characteristics, and Oncologic Factors Stratified by Facility Volume

eTable 12. Multivariate Cox Regression Stratified by M Status

eTable 13. Nonoropharyngeal HNSCC Demographics, Facility Characteristics, and Oncologic Factors Stratified by Facility Volume

eTable 14. 2010-2014 Oropharyngeal HNSCC With Known HPV Status Demographics, Facility Characteristics, and Oncologic Factors Stratified by Facility Volume

eTable 15. Multivariate Cox Regression Stratified by Nonoropharyngeal HNSCC and Oropharyngeal HNSCC With Known HPV Status)

1.
Siegel  RL, Miller  KD, Jemal  A.  Cancer statistics, 2018.  CA Cancer J Clin. 2018;68(1):7-30. doi:10.3322/caac.21442PubMedGoogle ScholarCrossref
2.
National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology. Head and Neck Cancers, version 2. 2018. National Comprehensive Cancer Network. http://oncolife.com.ua/doc/nccn/Head_and_Neck_Cancers.pdf Accessed May 12, 2019.
3.
David  JM, Ho  AS, Luu  M,  et al.  Treatment at high-volume facilities and academic centers is independently associated with improved survival in patients with locally advanced head and neck cancer.  Cancer. 2017;123(20):3933-3942. doi:10.1002/cncr.30843PubMedGoogle ScholarCrossref
4.
Gourin  CG, Stewart  CM, Frick  KD,  et al.  Association of hospital volume with laryngectomy outcomes in patients with larynx cancer.  JAMA Otolaryngol Head Neck Surg. 2019;145(1):62-70. doi:10.1001/jamaoto.2018.2986PubMedGoogle Scholar
5.
Gourin  CG, Dy  SM, Herbert  RJ,  et al.  Treatment, survival, and costs of laryngeal cancer care in the elderly.  Laryngoscope. 2014;124(8):1827-1835. doi:10.1002/lary.24574PubMedGoogle ScholarCrossref
6.
Cheraghlou  S, Kuo  P, Judson  BL.  Treatment delay and facility case volume are associated with survival in early-stage glottic cancer.  Laryngoscope. 2017;127(3):616-622. doi:10.1002/lary.26259PubMedGoogle ScholarCrossref
7.
Chen  AY, Pavluck  A, Halpern  M, Ward  E.  Impact of treating facilities’ volume on survival for early-stage laryngeal cancer.  Head Neck. 2009;31(9):1137-1143. doi:10.1002/hed.21072PubMedGoogle ScholarCrossref
8.
Mulvey  CL, Pronovost  PJ, Gourin  CG.  Hospital volume and failure to rescue after head and neck cancer surgery.  Otolaryngol Head Neck Surg. 2015;152(5):783-789. doi:10.1177/0194599815570026PubMedGoogle ScholarCrossref
9.
Nieman  CL, Stewart  CM, Eisele  DW, Pronovost  PJ, Gourin  CG.  Frailty, hospital volume, and failure to rescue after head and neck cancer surgery.  Laryngoscope. 2018;128(6):1365-1370. doi:10.1002/lary.26952PubMedGoogle ScholarCrossref
10.
Wuthrick  EJ, Zhang  Q, Machtay  M,  et al.  Institutional clinical trial accrual volume and survival of patients with head and neck cancer.  J Clin Oncol. 2015;33(2):156-164. doi:10.1200/JCO.2014.56.5218PubMedGoogle ScholarCrossref
11.
Gourin  CG, Frick  KD, Blackford  AL,  et al.  Quality indicators of laryngeal cancer care in the elderly.  Laryngoscope. 2014;124(9):2049-2056. doi:10.1002/lary.24593PubMedGoogle ScholarCrossref
12.
Morse  E, Fujiwara  RJT, Judson  B, Mehra  S.  Treatment delays in laryngeal squamous cell carcinoma: a national cancer database analysis.  Laryngoscope. 2018;128(12):2751-2758. doi:10.1002/lary.27247PubMedGoogle ScholarCrossref
13.
Morse  E, Berson  E, Fujiwara  R, Judson  B, Mehra  S.  Hypopharyngeal cancer treatment delays: benchmarks and survival association.  Otolaryngol Head Neck Surg. 2019;160(2):267-276. doi:10.1177/0194599818797605PubMedGoogle Scholar
14.
Morse  E, Judson  B, Husain  Z,  et al.  National treatment times in oropharyngeal cancer treated with primary radiation or chemoradiation.  Oral Oncol. 2018;82:122-130. doi:10.1016/j.oraloncology.2018.02.010PubMedGoogle ScholarCrossref
15.
Morse  E, Fujiwara  RJT, Judson  B, Prasad  ML, Mehra  S.  Positive surgical margins in parotid malignancies: institutional variation and survival association.  Laryngoscope. 2019; 129(1):129-137. doi:10.1002/lary.27221PubMedGoogle Scholar
16.
Luryi  AL, Chen  MM, Mehra  S, Roman  SA, Sosa  JA, Judson  BL.  Positive surgical margins in early stage oral cavity cancer: an analysis of 20,602 cases.  Otolaryngol Head Neck Surg. 2014;151(6):984-990. doi:10.1177/0194599814551718PubMedGoogle ScholarCrossref
17.
Nocon  CC, Ajmani  GS, Bhayani  MK.  Association of facility volume with positive margin rate in the surgical treatment of head and neck cancer.  JAMA Otolaryngol Head Neck Surg. 2018;144(12):1090-1097. doi:10.1001/jamaoto.2018.2421PubMedGoogle Scholar
18.
Bilimoria  KY, Stewart  AK, Winchester  DP, Ko  CY.  The National Cancer Data Base: a powerful initiative to improve cancer care in the United States.  Ann Surg Oncol. 2008;15(3):683-690. doi:10.1245/s10434-007-9747-3PubMedGoogle ScholarCrossref
19.
Cheraghlou  S, Kuo  P, Mehra  S, Yarbrough  WG, Judson  BL.  Untreated oral cavity cancer: long-term survival and factors associated with treatment refusal.  Laryngoscope. 2018;128(3):664-669. doi:10.1002/lary.26809PubMedGoogle ScholarCrossref
20.
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(32):3892-3897. doi:10.1200/JCO.2016.67.3863PubMedGoogle ScholarCrossref
21.
Cheraghlou  S, Torabi  SJ, Husain  ZA,  et al.  HPV status in unknown primary head and neck cancer: prognosis and treatment outcomes.  Laryngoscope. 2019;129(3):684-691. doi:10.1002/lary.27475PubMedGoogle Scholar
22.
Torabi  SJ, Cheraghlou  S, Kasle  DA, Savoca  EL, Judson  BL.  Nonsquamous cell laryngeal cancers: incidence, demographics, care patterns, and effect of surgery  [published online January 10, 2019].  Laryngoscope. PubMedGoogle Scholar
23.
US Census Bureau. American Community Survey Data. https://www.census.gov/programs-surveys/acs/data.html Accessed May 12, 2019.
24.
Lidor  A, Telem  D, Bower  C, Sinha  P, Orlando  R  III, Romanelli  J.  SAGES quality initiative: an introduction.  Surg Endosc. 2017;31(8):3072-3077. doi:10.1007/s00464-017-5627-5PubMedGoogle ScholarCrossref
25.
Mesman  R, Westert  GP, Berden  BJMM, Faber  MJ.  Why do high-volume hospitals achieve better outcomes? A systematic review about intermediate factors in volume-outcome relationships.  Health Policy. 2015;119(8):1055-1067. doi:10.1016/j.healthpol.2015.04.005PubMedGoogle ScholarCrossref
26.
Finlayson  SR.  The volume-outcome debate revisited.  Am Surg. 2006;72(11):1038-1042.PubMedGoogle Scholar
27.
Abrams  TA, Meyer  G, Meyerhardt  JA, Wolpin  BM, Schrag  D, Fuchs  CS.  Patterns of chemotherapy use in a US-based cohort of patients with metastatic pancreatic cancer.  Oncologist. 2017;22(8):925-933. doi:10.1634/theoncologist.2016-0447PubMedGoogle ScholarCrossref
28.
Huntington  SF, Hoag  JR, Zhu  W,  et al.  Oncologist volume and outcomes in older adults diagnosed with diffuse large B cell lymphoma.  Cancer. 2018;124(21):4211-4220. doi:10.1002/cncr.31688PubMedGoogle ScholarCrossref
29.
Buist  DSM, Anderson  ML, Haneuse  SJPA,  et al.  Influence of annual interpretive volume on screening mammography performance in the United States.  Radiology. 2011;259(1):72-84. doi:10.1148/radiol.10101698PubMedGoogle ScholarCrossref
30.
Chowdhury  MM, Dagash  H, Pierro  A.  A systematic review of the impact of volume of surgery and specialization on patient outcome.  Br J Surg. 2007;94(2):145-161. doi:10.1002/bjs.5714PubMedGoogle ScholarCrossref
31.
Hodgson  DC, Fuchs  CS, Ayanian  JZ.  Impact of patient and provider characteristics on the treatment and outcomes of colorectal cancer.  J Natl Cancer Inst. 2001;93(7):501-515. doi:10.1093/jnci/93.7.501PubMedGoogle ScholarCrossref
32.
Enestvedt  CK, Perry  KA, Kim  C,  et al.  Trends in the management of esophageal carcinoma based on provider volume: treatment practices of 618 esophageal surgeons.  Dis Esophagus. 2010;23(2):136-144. doi:10.1111/j.1442-2050.2009.00985.xPubMedGoogle ScholarCrossref
33.
Chen  AB, D’Amico  AV, Neville  BA, Steyerberg  EW, Earle  CC.  Provider case volume and outcomes following prostate brachytherapy.  J Urol. 2009;181(1):113-118. doi:10.1016/j.juro.2008.09.034PubMedGoogle ScholarCrossref
34.
Boero  IJ, Paravati  AJ, Xu  B,  et al.  Importance of radiation oncologist experience among patients with head-and-neck cancer treated with intensity-modulated radiation therapy.  J Clin Oncol. 2016;34(7):684-690. doi:10.1200/JCO.2015.63.9898PubMedGoogle ScholarCrossref
35.
Jeldres  C, Suardi  N, Saad  F,  et al.  High provider volume is associated with lower rate of secondary therapies after definitive radiotherapy for localized prostate cancer.  Eur Urol. 2008;54(1):97-105. doi:10.1016/j.eururo.2007.10.070PubMedGoogle ScholarCrossref
36.
Soofi  Y, Khoury  T.  Inter-institutional pathology consultation: the importance of breast pathology subspecialization in a setting of tertiary cancer center.  Breast J. 2015;21(4):337-344. doi:10.1111/tbj.12420PubMedGoogle ScholarCrossref
37.
Morse  E, Henderson  C, Carafeno  T,  et al.  A clinical care pathway to reduce ICU usage in head and neck microvascular reconstruction.  Otolaryngol Head Neck Surg. 2018:194599818782404.PubMedGoogle Scholar
38.
Newman  EA, Guest  AB, Helvie  MA,  et al.  Changes in surgical management resulting from case review at a breast cancer multidisciplinary tumor board.  Cancer. 2006;107(10):2346-2351. doi:10.1002/cncr.22266PubMedGoogle ScholarCrossref
39.
Sher  DJ, Rusthoven  CG, Khan  SA, Fidler  MJ, Zhu  H, Koshy  M.  National patterns of care and predictors of neoadjuvant and concurrent chemotherapy use with definitive radiotherapy in the treatment of patients with oropharyngeal squamous cell carcinoma.  Cancer. 2017;123(2):273-282. doi:10.1002/cncr.30255PubMedGoogle ScholarCrossref
40.
Isenring  EA, Capra  S, Bauer  JD.  Nutrition intervention is beneficial in oncology outpatients receiving radiotherapy to the gastrointestinal or head and neck area.  Br J Cancer. 2004;91(3):447-452. doi:10.1038/sj.bjc.6601962PubMedGoogle ScholarCrossref
41.
Moffatt  S, Noble  E, White  M.  Addressing the financial consequences of cancer: qualitative evaluation of a welfare rights advice service.  PLoS One. 2012;7(8):e42979. doi:10.1371/journal.pone.0042979PubMedGoogle ScholarCrossref
42.
Roland  KB, Milliken  EL, Rohan  EA,  et al.  Use of community health workers and patient navigators to improve cancer outcomes among patients served by federally qualified health centers: a systematic literature review.  Health Equity. 2017;1(1):61-76. doi:10.1089/heq.2017.0001PubMedGoogle ScholarCrossref
43.
Price  KA, Cohen  EE.  Current treatment options for metastatic head and neck cancer.  Curr Treat Options Oncol. 2012;13(1):35-46. doi:10.1007/s11864-011-0176-yPubMedGoogle ScholarCrossref
44.
Li  H, Torabi  SJ, Yarbrough  WG, Mehra  S, Osborn  HA, Judson  B.  Association of human papillomavirus status at head and neck carcinoma subsites with overall survival.  JAMA Otolaryngol Head Neck Surg. 2018;144(6):519-525. doi:10.1001/jamaoto.2018.0395PubMedGoogle ScholarCrossref
45.
Amini  A, Jasem  J, Jones  BL,  et al.  Predictors of overall survival in human papillomavirus-associated oropharyngeal cancer using the National Cancer Data Base.  Oral Oncol. 2016;56:1-7. doi:10.1016/j.oraloncology.2016.02.011PubMedGoogle ScholarCrossref
46.
Greene  FL.  Is volume the most important predictor of outcome in cancer management?  J Surg Oncol. 2008;97(2):97-98. doi:10.1002/jso.20833PubMedGoogle ScholarCrossref
47.
Marshall  CL, Petersen  NJ, Naik  AD,  et al.  Implementation of a regional virtual tumor board: a prospective study evaluating feasibility and provider acceptance.  Telemed J E Health. 2014;20(8):705-711. doi:10.1089/tmj.2013.0320PubMedGoogle ScholarCrossref
48.
Salami  AC, Barden  GM, Castillo  DL,  et al.  Establishment of a regional virtual tumor board program to improve the process of care for patients With hepatocellular carcinoma.  J Oncol Pract. 2015;11(1):e66-e74. doi:10.1200/JOP.2014.000679PubMedGoogle ScholarCrossref
Original Investigation
June 13, 2019

Prognostic Case Volume Thresholds in Patients With Head and Neck Squamous Cell Carcinoma

Author Affiliations
  • 1Section of Otolaryngology, Department of Surgery, Yale University School of Medicine, New Haven, Connecticut
  • 2Department of Otolaryngology, Harvard University School of Medicine, Boston, Massachusetts
  • 3Department of Internal Medicine, Yale University School of Medicine, Veterans Affairs Connecticut Healthcare System, West Haven
  • 4Yale Cancer Center, New Haven, Connecticut
JAMA Otolaryngol Head Neck Surg. 2019;145(8):708-715. doi:10.1001/jamaoto.2019.1187
Key Points

Question  Are prognostic thresholds identifiable for facility case volume in the treatment of patients with head and neck squamous cell carcinoma?

Findings  In this US nationally based cohort study of 250 229 patients at 1229 facilities with head and neck squamous cell carcinoma, improvements in patient survival were reported at moderate-volume facilities (>54 to ≤165 cases per year). Additional improvements in survival were reported at high-volume facilities (>165 cases per year).

Meaning  Facility case volume thresholds that may support the use of quality benchmarks for treatment of patients with head and neck squamous cell carcinoma.

Abstract

Importance  Though described as an important prognostic indicator, facility case volume thresholds for patients with head and neck squamous cell carcinoma (HNSCC) have not been previously developed to date.

Objective  To identify prognostic case volume thresholds of facilities that manage HNSCC.

Design, Setting, and Participants  Retrospective analysis of 351 052 HNSCC cases reported from January 1, 2004, through December 31, 2014, by Commission of Cancer–accredited cancer centers from the US National Cancer Database. Data were analyzed from August 1, 2018, to April 5, 2019.

Exposures  Treatment of HNSCC at facilities with varying case volumes.

Main Outcomes and Measures  Using all-cause mortality outcomes among adult patients with HNSCC, 10 groups with increasing facility case volume were created and thresholds were identified where group survival differed compared with each of the 2 preceding groups (univariate log-rank analysis). Groups were collapsed at these thresholds and the prognostic value was confirmed using multivariable Cox regression. Prognostic meaning of these thresholds was assessed in subgroups by category (localized [I/II] and advanced [III/IV]), without metastasis (M0), with metastasis (M1), and anatomic subsites (nonoropharyngeal HNSCC and oropharyngeal HNSCC with known human papillomavirus status).

Results  Of 250 229 eligible patients treated at 1229 facilities in the United States, there were 185 316 (74.1%) men and 64 913 (25.9%) women and the mean (SD) age was 62.8 (12.1) years. Three case volume thresholds were identified (low: ≤54 cases per year; moderate: >54 to ≤165 cases per year; and high: >165 cases per year). Compared with the moderate-volume group, multivariate analysis found that treatment at low-volume facilities (LVFs) was associated with a higher risk of mortality (hazard ratio [HR], 1.09; 99% CI, 1.07-1.11), whereas treatment at high-volume facilities (HVFs) was associated with a lower risk of mortality (HR, 0.92; 99% CI, 0.89-0.94). Subgroup analysis with Bonferroni correction revealed that only the moderate- vs low- threshold had meaningful differences in outcomes in localized stage (I/II) cancers, (LVFs vs moderate-volume facilities [MVFs]: HR, 1.09 [99% CI, 1.05-1.13]; HVF vs MVF: HR, 0.95 [99% CI, 0.90-1.00]), whereas both thresholds were meaningful in advanced stage (III/IV) cancers (LVF vs MVF: HR, 1.09 [99% CI, 1.06-1.12]; HVF vs MVF: HR, 0.91 [99% CI, 0.88-0.94]). Survival differed by prognostic thresholds for both M0 (LVF vs MVF: HR, 1.09 [99% CI, 1.07-1.12]; HVF vs MVF: HR, 0.91 [99% CI, 0.89-0.94]) and nonoropharyngeal HNSCC (LVF vs MVF: HR, 1.10 [99% CI, 1.07-1.13]; HVF vs MVF: HR, 0.93 [99% CI, 0.90-0.97]) site cases, but not for M1 (LVF vs MVF: HR, 1.00 [99% CI, 0.92-1.09]; HVF vs MVF: HR, 0.94 [99% CI, 0.83-1.07]) or oropharyngeal HNSCC cases (when controlling for human papillomavirus status) (LVF vs MVF: HR, 1.10 [99% CI, 0.99-1.23]; HVF vs MVF: HR, 1.07 [99% CI, 0.94-1.22]).

Conclusions and Relevance  Higher volume facility threshold results appear to be associated with increases in survival rates for patients treated for HNSCC at MVFs or HVFs compared with LVFs, which suggests that these thresholds may be used as quality markers.

Introduction

Head and neck cancer incidence is estimated at 64 690 cases per year in the United States and resulted in more than 13 000 deaths reported in 2018.1 Because of disease heterogeneity and intricate anatomy, treatment depends on highly specialized clinicians and advanced multidisciplinary teams to coordinate surgery, radiotherapy, and chemotherapy. The National Comprehensive Cancer Network guidelines specify that “outcomes are improved when patients with head and neck cancers are treated in high-volume centers.”2 and a rapidly expanding body of literature3-17 supports this statement.

Treatment at a high-volume facility (HVF) was reported to be associated with improved long-term survival in patients with locally advanced head and neck squamous cell carcinoma (HNSCC), including patients undergoing definitive radiotherapy3 or laryngectomy,4 elderly patients with surgically treated laryngeal cancer,5 and patients with localized laryngeal cancer.6,7 Care at HVFs was also reported to be associated with improvements in short-term mortality for patients with surgically treated head and neck cancers.8,9 In practice, HVFs reported better health care professional adherence to radiotherapy protocols for advanced-stage HNSCC,10 and to guidelines for treatment of elderly patients with laryngeal cancer.11 Cases at HVFs were associated with fewer delays in initiation of radiotherapy treatment for laryngeal cancer12 and decreased prolongation of radiotherapy treatment duration of hypopharyngeal and oropharyngeal cancers.13,14 In addition, high volume was independently associated with reduced rates of positive surgical margins in HNSCC and salivary malignancies.15-17

However, case volume definitions span a wide range and lack specific thresholds. Low-volume facilities (LVFs) are defined as facilities with fewer than 1 to 20 cases per year, and HVFs manage a minimum of 3 to 66 cases per year,3,5-16 making generalizability or standardization for policy or clinical decision making particularly challenging. Research toward establishing volume thresholds associated with survival outcomes across all HNSCC subsites and treatments is lacking. We aimed to identify prognostic thresholds for facility case volume in the treatment of HNSCC.

Methods
Data

Data were obtained from the National Cancer Database (NCDB) from January 1, 2004, through December 31, 2014. Data were analyzed from August 1, 2018, to April 5, 2019. This database collaboration between the American College of Surgeons and the Commission on Cancer (CoC) collected data from more than 1500 US hospitals, representing more than 70% of all new diagnoses of cancer as previously described.18 The NCDB has been used in a number of studies of head and neck cancers.19-22 This study was exempt from institutional review by the Yale Human Investigation Committee because of use of deidentified data.

Patient Population

The study population included patients of all ages with squamous cell carcinoma at any head and neck subsite, identified by histology codes 8070-8073 from the International Classification of Disease for Oncology, Third Edition (ICD-O-3). Patients were categorized using the ICD-O-3 topologic site codes by subsites: oral cavity codes C00.0-C00.9 (lip), C02.0-C02.9 (all tongue sites excluding base of tongue), C03.0-C03.9 (gums), C04.0-C04.9 (floor of mouth), C05.0-C05.9 (palate), and C06.0-C06.9 (other and unspecified parts of mouth); oropharynx codes C01.9 (base of tongue), C09.0-C09.9 (tonsil), and C10.0-C10.9 (oropharynx); parotid and other major salivary glands codes C07.9 (parotid) and C08.0-C08.9 (other and unspecified major salivary glands); nasopharynx codes C11.0-C11.9; hypopharynx codes C12.9 (pyriform sinus) and C13.0-13.9 (hypopharynx); ill-defined areas in oral cavity and pharynx codes (C14.0-C14.8); sinonasal tract codes C30.0-C30.1 (nasal cavity) and C31.0-C31.9 (accessory sinuses); and larynx codes C32.0-C32.9. Patients with unknown or unclear (ie, classified as stage IV, not otherwise specified) American Joint Committee on Cancer (AJCC) clinical staging, missing vital status, unknown facility location and type, or missing follow-up were excluded (Figure 1). In subgroup analyses, patients were also excluded for unknown metastasis in metastatic (M1) and nonmetastatic (M0) subgroups, for an AJCC clinical stage of 0 in localized or advanced stage subgroups, or for unknown, unclear (human papillomavirus [HPV]–positive [risk and type not stated]), or low-risk HPV status in the oropharyngeal HNSCC subgroup.

Variable Definitions

Insurance was categorized as government (Medicaid, Medicare, or other government insurance), private (private insurance or managed care), or uninsured patients and patients with unknown insurance status. Facilities were categorized into academic facilities (academic or research programs including National Cancer Institute–designated comprehensive cancer centers) and nonacademic facilities (community cancer programs, comprehensive community cancer programs, and integrated network cancer programs). Facility location was grouped by region: North East (New England and Middle Atlantic); South (South Atlantic); Central (East North Central, East South Central, West North Central, and East North Central); and West (Mountain and Pacific). Income quartile was reported as the median household income from the patient’s area of residence, based on the 2012 American Community Survey.23 For subgroup analysis on oropharyngeal HNSCC, HPV status was assigned as either HPV-negative cases including those diagnosed without HPV-disease or HPV-positive cases including those with non-16–, non-18–high-risk HPV, HPV-16, HPV-18, HPV-16 and HPV-18, and high-risk HPV, not otherwise specified.

Facility Volume Calculation

Mean annual facility volume was calculated before applying exclusion criteria to accurately characterize the values. Number of cases per facility was summed and divided by the number of years since the institution initially entered data in the NCDB, which may have been as early as 2004, up to a maximum of 11 years. Since the NCDB collected all cancer cases from its contributing hospitals, these values represented actual case volume.18

Threshold Determination

After applying exclusion criteria, patients were divided into 10 groups according to increasing facility volume (eTable 1 in the Supplement). These groups were determined by setting an approximately equal number of events (deaths) per group before application of exclusion criteria. Each group’s survival was compared with the preceding 2 groups via univariate log-rank analysis. Whenever a group had significantly increased survival compared with both of the preceding groups, a threshold was created. A certain number of thresholds were not set a priori. We used the aforementioned methods as a pragmatic way to minimize differences within groups and maximize differences between groups, while maintaining a large sample size in each of the initial volume groupings. Groups were then collapsed according to the identified thresholds and compared with one another via univariate log-rank analysis.

Threshold Validation and Other Statistical Analyses

Age, sex, race/ethnicity, insurance, income, facility type, facility location, Charlson-Deyo comorbidity condition score, year of diagnosis, primary tumor site, clinical stage, tumor grade, facility type, and facility locations were compared by facility volume using χ2 analyses. Univariate survival analyses comparing the prognostic groups were performed via Kaplan-Meier 2-tailed log-rank tests. Thresholds were validated using the multivariate Cox proportional hazards regression model controlling for variables. Human papillomavirus was also analyzed within the oropharyngeal HNSCC subgroup. Effect size and 99% CIs were used where appropriate to express the magnitude of the difference and precision of the estimate. Because the NCDB may receive multiple records for the same patient treated by multiple institutions, it assigned the facility based on recency of patient contact or the most complete record; thus, thresholds were validated among patients reportedly treated at only 1 CoC facility. Subgroup analyses were also performed for patients with (M1) and without (M0) distant metastases, localized stage (I/II) and advanced stage (III/IV) cancers, and nonoropharyngeal HNSCC sites and oropharyngeal HNSCC sites with known HPV status. Data analyses was performed using SPSS, version 25.0 (IBM Corporation). Statistical significance was set at P < .00122 after a Bonferroni correction adjusting for the number of comparisons in a single Cox regression was applied.

Results
Facility Volume Thresholds

Of 351 052 HNSCC cases identified from 1234 facilities, facility volume ranged from 0.13 to 342.18 cases per year, with a median of 15.36 (interquartile range [IQR], 8.44-29.82) cases and a mean (SD) of 26.82 (36.51) cases. After exclusions, 250 229 cases from 1229 facilities remained, ranging from 0.50 to 342.18 cases per year, with a median of 15.36 (IQR, 8.52-29.82) cases and a mean (SD) of 26.93 (36.54) cases.

Patients were allocated into 10 groups as described in the Methods section (eTable 1 in the Supplement). In univariate analysis, group 6, which contained 11 facilities that treated from 54.45 cases to fewer than 81.64 cases per year, had a meaningfully improved mean (SE) survival of 6.45 (0.04) years compared with group 5 (40.00 to <54.45 cases per year; mean [SE], 6.01 [0.04] years) and group 4 (31.09 to <40.00 cases per year; mean [SE], 6.02 [0.04] years). We found similar survival difference between group 9 (165.45-342.18 cases per year; mean [SE], 6.58 [0.04] cases per year) and groups 8 (121.09 to <165.45 cases per year; 6.23 [0.04] cases per year) and 7 (81.64 to <121.09 cases per year; 6.19 [0.04] cases per year). Thus, thresholds were created between groups 5 and 6 and between groups 8 and 9, and were collapsed accordingly.

Collapsing categories left 3 facility-volume groups. After exclusion criteria, LVFs (treating <54.45 cases per year) contained a total of 1099 facilities (of 1104 LVFs reported in the database) that treated 144 016 eligible patients. The LVFs treated a median number of 13.71 (IQR, 7.82-23.55) cases per year and the mean (SD) was 17.06 (11.94) cases per year. Moderate-volume facilities (MVFs) (managing from 54.45 to <165.45 cases per year) contained 111 facilities that treated 76 460 patients. The MVFs managed a median of 81.64 (IQR, 63.18-109.36) cases per year and a mean (SD) of 89.70 (29.63) cases per year. The HVFs (managing ≥165.45 cases per year) contained 19 facilities that treated 29 753 cases per year. The HVFs treated a median of 216.82 (IQR, 193.45-272.33) cases per year and a mean (SD) of 231.10 (52.96) cases per year. As shown in Figure 2, a smaller proportion of patients were treated at LVFs in 2014 compared with 2004 (54.2% vs 60.1%), whereas the proportion of patients treated in MVFs (32.1% vs 28.4%) and HVFs (13.7% vs 11.5%) increased during this time. Survival differences were found between the groups. Mean (SE) survival was 6.01 (0.02) years in the LVF group, 6.31 (0.02) years in the MVF group, and 6.58 (0.04) years in the HVF group. Univariate survival curves for these groups are presented in Figure 3. Among the 3 volume groups, no differences were noted in facility location; notably, no HVFs were located in the West. A large percentage of HVFs (≥47.5%) and MVFs (70.3%) were academic, whereas most LVFs (87.8%) were nonacademic.

Threshold Utility Among All Patients and Those Treated at 1 CoC Facility

The LVFs cared for older patients (≥64 years: LVF, 45.5%; MVF, 39.4%; and HVF, 39.1%), patients from a zip code with a lower socioeconomic status (≥$63 000 median income: LVF, 25.7%; MVF, 29.9%; and HVF, 27.4%), and patients with government insurance (LVF, 55.8%; MVF, 51.8%; and HVF, 48.2%), as opposed to private insurance. After controlling for these characteristics in a multivariate Cox proportional hazards model, treatment at LVFs was associated with higher risk of mortality vs treatment at MVFs (HR, 1.09; 99% CI, 1.07-1.11). Treatment at HVFs was associated with a lower risk of mortality vs MVFs (HR, 0.92; 99% CI, 0.89-0.94) (Figure 4). When looking specifically at cases treated at only 1 CoC facility (n = 204 537), the thresholds held (LVF vs MVF: HR, 1.09 [99% CI, 1.07-1.12] and HVF vs MVF: HR, 0.90 [99% CI, 0.87-0.93]) (Figure 5).

Threshold Utility in Patients With Localized (I/II) and Advanced (III/IV) Stage Cancers

We identified 93 865 patients with localized stage cancer. In univariate analysis, we found meaningful survival difference based on facility volume in patients with localized stage disease. The 5-year survival (SE) in HVFs was 65.8% (0.6%); in MVFs, 64.4% (0.3%); and in LVFs, 60.6% (0.2%) (Figure 5A). The LVFs were independently associated with decreased survival compared with MVFs after Bonferroni correction (HR, 1.09; 99% CI, 1.05-1.13). However, no survival difference was found between HVFs and MVFs after Bonferroni correction (HR, 0.95; 99% CI, 0.90-1.00) (Figure 4).

We identified 148 066 patients with advanced stage cancer. The MVFs and HVFs had a higher proportion of stage IV cases compared with LVFs (LVF, 66.8%; MVF, 72.6%; and HVF, 71.5%). Univariate analysis identified a meaningful survival difference based on facility volume in this cohort. The 5-year survival (SE) in HVFs was 50.7% (0.4%); in MVFs, 46.5% (0.3%); and in LVFs, 43.5% (0.2%) (Figure 5B). After Bonferroni correction, LVFs were associated with decreases in survival compared with MVFs (HR, 1.09; 99% CI, 1.06-1.12), and HVFs were associated with increased survival compared with MVFs (HR, 0.91; 99% CI, 0.88-0.94) (Figure 4).

Threshold Utility in Patients With M0 and M1 Cancer

We identified 236 172 patients with M0 cancer. Univariate analysis revealed meaningful survival differences based on facility volume in the M0 cohort. The 5-year survival (SE) was 57.9% (0.3%) in HVFs; 54.8% (0.2%) in MVFs; and 52.5% (0.2%) in LVFs (Figure 5C). These prognostic thresholds were also significant on multivariate analysis in these patients. Compared with MVFs, treatment at LVFs was independently associated with decreased survival (HR, 1.09; 99% CI, 1.07-1.12), while treatment at HVFs was associated with increased survival (HR, 0.91; 99% CI, 0.89-0.94) (Figure 4).

We identified 7490 patients with M1 cancer. The 5-year survival (SE) was 12.4% (1.5%) in HVFs, 11.7% (0.8%) in MVFs, and 11.7% (0.5%) in LVFs (Figure 5D). Multivariate analysis also showed no difference in survival based on the thresholds before Bonferroni correction (LVF vs MVF: HR, 1.00 [99% CI, 0.92-1.09] and HVF vs MVF: HR, 0.94 [99% CI, 0.83-1.06]) (Figure 4).

Threshold Utility in Patients With Nonoropharyngeal HNSCC and HPV-tested Oropharyngeal HNSCC

We identified 172 638 patients with nonoropharyngeal HNSCC as well as 16 350 patients with oropharyngeal HNSCC with known HPV status. After excluding cases with unknown HPV status, HVFs were more likely to treat HPV-positive patients compared with MVFs and LVFs within the oropharyngeal HNSCC cohort (HPV-positive: HVF, 72.5%; MVF, 62.8%; and LVF, 55.6%). As in previous analyses, the thresholds held for the nonoropharyngeal HNSCC cohort (LVF vs MVF: HR, 1.10 [99% CI, 1.07-1.13] and HVF vs MVF: HR, 0.93 [99% CI, 0.90-0.97]) (Figure 4). However, after controlling for HPV status in the oropharyngeal HNSCC cohort, we found HPV to be the main driver for survival, not facility volume. Being HPV-positive carried a HR of 0.39 (99% CI, 0.36-0.43) compared with being HPV-negative. Whereas LVFs were associated with decreased survival compared with MVFs before Bonferroni correction, no difference was seen after correction (HR, 1.10; 99% CI, 0.99-1.23). The HVFs were also not associated with improved survival compared with MVFs (HR, 1.07; 99% CI, 0.94-1.22) (Figure 4).

Discussion

Multiple studies3-17 have reported the prognostic association of facility case volume on HNSCC outcomes and guideline adherence. To our knowledge, this is the first study to determine facility case volume thresholds for all HNSCCs. We identified 2 potential prognostic thresholds for outcomes at approximately 54 cases per year and approximately 165 cases per year. Multivariate analysis confirmed that our thresholds remained predictive after adjustment for many potentially confounding factors. This remained true in a subgroup of patients treated at only 1 CoC facility; thus, it may be used as a quality measure for hospital selection. Whereas the mean survival increase was modest (approximately 6 months mean survival difference between HVF and LVF), HNSCC affects more than 60 000 patients a year,1 and 6 months represents a substantial amount of time across all patients. Our findings were especially relevant given the increasing treatment of patients at MVFs and HVFs during the last decade and the current transition of the US health care system from fee-for-service to value-based reimbursement.24

The mechanism by which facility case volume is associated with improvements in patient survival has been the subject of review articles.25,26 It may be that high hospital volume translates to a higher volume per clinician, which may be especially important for oncologist,27,28 radiologist,29 surgeon,30-32 and radiation oncologist33-35 expertise in diagnosis and management of many cancers. In addition, such facilities may have more subspecialization, which has been shown with more accurate diagnoses of breast cancer by specialized breast pathologists.36 The HVFs may also have the resources to create clinical care pathways37 and effective multidisciplinary teams and tumor boards that may help in decision making38 and evidence-based guideline adherence.10,39 The HVFs may be better equipped with ancillary services such as dieticians and social services, which may independently improve outcomes and quality of life.40-42 Regardless of the specific factors, evidence suggests that facility volume is a useful quality marker. While exact volumes have proven previously elusive, this study helped define specific threshold cutoffs, which can be used to facilitate prognostication and to improve HNSCC care.

Our findings were consistent among a variety of subgroups performed to better characterize patients who were more likely to benefit from HVF referral. Subgroup analysis revealed that only the MVF vs LVF thresholds were associated with significant differences in outcomes among the patients with localized stage (I/II) cancer, whereas both thresholds were significant among the patients with advanced stage (III/IV) cancer. This outcome suggests that patients with more complex issues should be treated at highly experienced institutions, whereas patients with less complex issues may not need the same level of specialty care. While we found facility volume-based survival differences for patients with M0 cancer, none was identified for patients with M1 HNSCC. This may be indicative of the worse prognosis facing patients with metastases.43 Since these patients are often treated with palliative intent,43 our analysis suggested that this group need not travel long distances for treatment at HVFs. Granted, we were unable to assess quality-of-life outcomes in this analysis.

Whereas HSNCC facility volume thresholds may exist, we found no association with survival within an oropharyngeal HNSCC cohort. The HPV positivity was a main factor associated with improved survival, consistent with the literature.44,45 However, a previous Radiation Therapy Oncology Group randomized trial10 secondary analysis of 471 patients with known HPV-status (including 266 patients with oropharyngeal HNSCC) reported an overall survival benefit in HVFs, even when controlling for HPV status (LVF vs HVF: HR, 1.91; 95% CI, 1.37-2.65). Thus, our results may reflect inadequate power because of limited sample size, shorter follow-up compared with other subgroups (HPV data collection for NCDB began in 2010), and the missing association of patients with unknown HPV status. The HVFs were also more likely to treat HPV-positive patients within our analysis, though it is important to note that in a post hoc analysis of all oropharyngeal HNSCC cases from 2010 through 2014 (without excluding cases with unknown or low-risk HPV status), it was noted that unknown or low-risk HPV cases were more likely to be in the LVF group compared with the MVF and HVF groups (unknown or low risk HPV: HVF, 45.3%; MVF, 52.2%; and LVF, 63.0%), indicating that perhaps HPV reporting or HPV testing within LVFs may be lower compared with HVFs, not necessarily that they are less likely to see these patients. Differences in HPV testing and reporting may also have precluded us from observing a volume-based survival difference. Future analyses may, indeed, show a survival difference. However, the results of our study support regionalization of patients with HNSCC, especially those with advanced-stage, M0 disease.

Nonetheless, it may not be feasible to regionalize HNSCC cancer care to 130 MVFs and HVFs. As indicated in our study, LVFs tended to care for larger proportions of low-income patients with government insurance and increased age. Referral to HVFs, likely more centralized institutions, may result in further financial, transportation, and emotional hardships. Solely focusing on care regionalization may risk neglecting efforts aimed at improving care structures in LVFs. In addition, negative perception of LVF outcomes may discourage continuous reporting of case volume geared to the creation of cancer databases necessary for clinical outcome studies.46 Thus, concurrent processes and initiatives aimed at mitigating the survival gap between LVFs and HVFs is imperative. Initiatives, such as virtual tumor boards in small centers, to provide high-quality, multidisciplinary expertise at institutions lacking the necessary personnel for in-house implementation may help reduce such disparities.47,48

Strengths and Limitations

Our study had several strengths. We identified thresholds without a priori assumptions, allowing us to find 2 points of inflection in survival. Our high-volume threshold was set at approximately 165 cases per year; a value not only high, but which encompassed only 19 facilities in the database. Given the complexity of HNSCC, including multiple anatomic subsites and a myriad of surgical procedures and medical treatment variations, it was possible that HVF expertise was achieved only after treating substantially large cohorts of patients and may explain the high 165 cases per year threshold.

There were many study limitations. We included all subsites and stages with no consistent clinical guidelines, and we did not control for treatment modality in the multivariate model. In addition, our database was limited by the absence of certain important variables, such as patient smoking status, because of missing data or complete absence from the database. Furthermore, patients seen at multiple CoC facilities were arbitrarily assigned to a single facility within the database based on recency of patient contact or the most complete treatment records. Though we attempted to mitigate this limitation with a subgroup analysis of patients reportedly treated at only 1 CoC facility, this analysis was also limited since patients may have sought treatment at a non-CoC facility not captured by the NCDB. Identification of only 130 MVFs and HVFs suggested possible confounding bias; those seeking care at these centers may have a higher level of engagement and stronger support systems associated with better compliance and utilization of ancillary services.

Conclusions

We proposed novel prognostic thresholds for HNSCC facility case volume. Independent of multiple oncologic and system factors, patient survival appeared to be improved at centers that treated approximately 54 or more cases per year and further improved at centers that treated approximately 165 or more cases per year. Our thresholds appear to support regionalization of care to HVFs to improve patient outcomes.

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Article Information

Corresponding Author: Benjamin L. Judson, MD, Section of Otolaryngology, Department of Surgery, Yale University School of Medicine, 330 Cedar St, PO Box 208062, New Haven, CT 06520-8062 (benjamin.judson@yale.edu).

Published Online: June 13, 2019. doi:10.1001/jamaoto.2019.1187

Author Contributions: Mr Torabi and Dr Judson had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Torabi, Kuo Yu, Cheraghlou, Tate, Judson.

Acquisition, analysis, or interpretation of data: Torabi, Benchetrit, Savoca, Tate, Judson.

Drafting of the manuscript: Torabi, Benchetrit, Savoca.

Critical revision of the manuscript for important intellectual content: Benchetrit, Kuo Yu, Cheraghlou, Tate, Judson.

Statistical analysis: Torabi, Cheraghlou.

Obtained funding: Torabi.

Administrative, technical, or material support: Judson.

Supervision: Kuo Yu, Savoca, Tate, Judson.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by a grant T35HL007649 (Dr Torabi) from the National Heart, Lung, and Blood Institute.

Role of the Funder/Sponsor: The National Heart, Lung, and Blood Institute had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The data used in the study are derived from a deidentified NCDB file. The American College of Surgeons and the Commission on Cancer have not verified and are not responsible for the analytic or statistical methodology employed, or the conclusions drawn from these data by the investigator.

References
1.
Siegel  RL, Miller  KD, Jemal  A.  Cancer statistics, 2018.  CA Cancer J Clin. 2018;68(1):7-30. doi:10.3322/caac.21442PubMedGoogle ScholarCrossref
2.
National Comprehensive Cancer Network (NCCN). NCCN Clinical Practice Guidelines in Oncology. Head and Neck Cancers, version 2. 2018. National Comprehensive Cancer Network. http://oncolife.com.ua/doc/nccn/Head_and_Neck_Cancers.pdf Accessed May 12, 2019.
3.
David  JM, Ho  AS, Luu  M,  et al.  Treatment at high-volume facilities and academic centers is independently associated with improved survival in patients with locally advanced head and neck cancer.  Cancer. 2017;123(20):3933-3942. doi:10.1002/cncr.30843PubMedGoogle ScholarCrossref
4.
Gourin  CG, Stewart  CM, Frick  KD,  et al.  Association of hospital volume with laryngectomy outcomes in patients with larynx cancer.  JAMA Otolaryngol Head Neck Surg. 2019;145(1):62-70. doi:10.1001/jamaoto.2018.2986PubMedGoogle Scholar
5.
Gourin  CG, Dy  SM, Herbert  RJ,  et al.  Treatment, survival, and costs of laryngeal cancer care in the elderly.  Laryngoscope. 2014;124(8):1827-1835. doi:10.1002/lary.24574PubMedGoogle ScholarCrossref
6.
Cheraghlou  S, Kuo  P, Judson  BL.  Treatment delay and facility case volume are associated with survival in early-stage glottic cancer.  Laryngoscope. 2017;127(3):616-622. doi:10.1002/lary.26259PubMedGoogle ScholarCrossref
7.
Chen  AY, Pavluck  A, Halpern  M, Ward  E.  Impact of treating facilities’ volume on survival for early-stage laryngeal cancer.  Head Neck. 2009;31(9):1137-1143. doi:10.1002/hed.21072PubMedGoogle ScholarCrossref
8.
Mulvey  CL, Pronovost  PJ, Gourin  CG.  Hospital volume and failure to rescue after head and neck cancer surgery.  Otolaryngol Head Neck Surg. 2015;152(5):783-789. doi:10.1177/0194599815570026PubMedGoogle ScholarCrossref
9.
Nieman  CL, Stewart  CM, Eisele  DW, Pronovost  PJ, Gourin  CG.  Frailty, hospital volume, and failure to rescue after head and neck cancer surgery.  Laryngoscope. 2018;128(6):1365-1370. doi:10.1002/lary.26952PubMedGoogle ScholarCrossref
10.
Wuthrick  EJ, Zhang  Q, Machtay  M,  et al.  Institutional clinical trial accrual volume and survival of patients with head and neck cancer.  J Clin Oncol. 2015;33(2):156-164. doi:10.1200/JCO.2014.56.5218PubMedGoogle ScholarCrossref
11.
Gourin  CG, Frick  KD, Blackford  AL,  et al.  Quality indicators of laryngeal cancer care in the elderly.  Laryngoscope. 2014;124(9):2049-2056. doi:10.1002/lary.24593PubMedGoogle ScholarCrossref
12.
Morse  E, Fujiwara  RJT, Judson  B, Mehra  S.  Treatment delays in laryngeal squamous cell carcinoma: a national cancer database analysis.  Laryngoscope. 2018;128(12):2751-2758. doi:10.1002/lary.27247PubMedGoogle ScholarCrossref
13.
Morse  E, Berson  E, Fujiwara  R, Judson  B, Mehra  S.  Hypopharyngeal cancer treatment delays: benchmarks and survival association.  Otolaryngol Head Neck Surg. 2019;160(2):267-276. doi:10.1177/0194599818797605PubMedGoogle Scholar
14.
Morse  E, Judson  B, Husain  Z,  et al.  National treatment times in oropharyngeal cancer treated with primary radiation or chemoradiation.  Oral Oncol. 2018;82:122-130. doi:10.1016/j.oraloncology.2018.02.010PubMedGoogle ScholarCrossref
15.
Morse  E, Fujiwara  RJT, Judson  B, Prasad  ML, Mehra  S.  Positive surgical margins in parotid malignancies: institutional variation and survival association.  Laryngoscope. 2019; 129(1):129-137. doi:10.1002/lary.27221PubMedGoogle Scholar
16.
Luryi  AL, Chen  MM, Mehra  S, Roman  SA, Sosa  JA, Judson  BL.  Positive surgical margins in early stage oral cavity cancer: an analysis of 20,602 cases.  Otolaryngol Head Neck Surg. 2014;151(6):984-990. doi:10.1177/0194599814551718PubMedGoogle ScholarCrossref
17.
Nocon  CC, Ajmani  GS, Bhayani  MK.  Association of facility volume with positive margin rate in the surgical treatment of head and neck cancer.  JAMA Otolaryngol Head Neck Surg. 2018;144(12):1090-1097. doi:10.1001/jamaoto.2018.2421PubMedGoogle Scholar
18.
Bilimoria  KY, Stewart  AK, Winchester  DP, Ko  CY.  The National Cancer Data Base: a powerful initiative to improve cancer care in the United States.  Ann Surg Oncol. 2008;15(3):683-690. doi:10.1245/s10434-007-9747-3PubMedGoogle ScholarCrossref
19.
Cheraghlou  S, Kuo  P, Mehra  S, Yarbrough  WG, Judson  BL.  Untreated oral cavity cancer: long-term survival and factors associated with treatment refusal.  Laryngoscope. 2018;128(3):664-669. doi:10.1002/lary.26809PubMedGoogle ScholarCrossref
20.
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(32):3892-3897. doi:10.1200/JCO.2016.67.3863PubMedGoogle ScholarCrossref
21.
Cheraghlou  S, Torabi  SJ, Husain  ZA,  et al.  HPV status in unknown primary head and neck cancer: prognosis and treatment outcomes.  Laryngoscope. 2019;129(3):684-691. doi:10.1002/lary.27475PubMedGoogle Scholar
22.
Torabi  SJ, Cheraghlou  S, Kasle  DA, Savoca  EL, Judson  BL.  Nonsquamous cell laryngeal cancers: incidence, demographics, care patterns, and effect of surgery  [published online January 10, 2019].  Laryngoscope. PubMedGoogle Scholar
23.
US Census Bureau. American Community Survey Data. https://www.census.gov/programs-surveys/acs/data.html Accessed May 12, 2019.
24.
Lidor  A, Telem  D, Bower  C, Sinha  P, Orlando  R  III, Romanelli  J.  SAGES quality initiative: an introduction.  Surg Endosc. 2017;31(8):3072-3077. doi:10.1007/s00464-017-5627-5PubMedGoogle ScholarCrossref
25.
Mesman  R, Westert  GP, Berden  BJMM, Faber  MJ.  Why do high-volume hospitals achieve better outcomes? A systematic review about intermediate factors in volume-outcome relationships.  Health Policy. 2015;119(8):1055-1067. doi:10.1016/j.healthpol.2015.04.005PubMedGoogle ScholarCrossref
26.
Finlayson  SR.  The volume-outcome debate revisited.  Am Surg. 2006;72(11):1038-1042.PubMedGoogle Scholar
27.
Abrams  TA, Meyer  G, Meyerhardt  JA, Wolpin  BM, Schrag  D, Fuchs  CS.  Patterns of chemotherapy use in a US-based cohort of patients with metastatic pancreatic cancer.  Oncologist. 2017;22(8):925-933. doi:10.1634/theoncologist.2016-0447PubMedGoogle ScholarCrossref
28.
Huntington  SF, Hoag  JR, Zhu  W,  et al.  Oncologist volume and outcomes in older adults diagnosed with diffuse large B cell lymphoma.  Cancer. 2018;124(21):4211-4220. doi:10.1002/cncr.31688PubMedGoogle ScholarCrossref
29.
Buist  DSM, Anderson  ML, Haneuse  SJPA,  et al.  Influence of annual interpretive volume on screening mammography performance in the United States.  Radiology. 2011;259(1):72-84. doi:10.1148/radiol.10101698PubMedGoogle ScholarCrossref
30.
Chowdhury  MM, Dagash  H, Pierro  A.  A systematic review of the impact of volume of surgery and specialization on patient outcome.  Br J Surg. 2007;94(2):145-161. doi:10.1002/bjs.5714PubMedGoogle ScholarCrossref
31.
Hodgson  DC, Fuchs  CS, Ayanian  JZ.  Impact of patient and provider characteristics on the treatment and outcomes of colorectal cancer.  J Natl Cancer Inst. 2001;93(7):501-515. doi:10.1093/jnci/93.7.501PubMedGoogle ScholarCrossref
32.
Enestvedt  CK, Perry  KA, Kim  C,  et al.  Trends in the management of esophageal carcinoma based on provider volume: treatment practices of 618 esophageal surgeons.  Dis Esophagus. 2010;23(2):136-144. doi:10.1111/j.1442-2050.2009.00985.xPubMedGoogle ScholarCrossref
33.
Chen  AB, D’Amico  AV, Neville  BA, Steyerberg  EW, Earle  CC.  Provider case volume and outcomes following prostate brachytherapy.  J Urol. 2009;181(1):113-118. doi:10.1016/j.juro.2008.09.034PubMedGoogle ScholarCrossref
34.
Boero  IJ, Paravati  AJ, Xu  B,  et al.  Importance of radiation oncologist experience among patients with head-and-neck cancer treated with intensity-modulated radiation therapy.  J Clin Oncol. 2016;34(7):684-690. doi:10.1200/JCO.2015.63.9898PubMedGoogle ScholarCrossref
35.
Jeldres  C, Suardi  N, Saad  F,  et al.  High provider volume is associated with lower rate of secondary therapies after definitive radiotherapy for localized prostate cancer.  Eur Urol. 2008;54(1):97-105. doi:10.1016/j.eururo.2007.10.070PubMedGoogle ScholarCrossref
36.
Soofi  Y, Khoury  T.  Inter-institutional pathology consultation: the importance of breast pathology subspecialization in a setting of tertiary cancer center.  Breast J. 2015;21(4):337-344. doi:10.1111/tbj.12420PubMedGoogle ScholarCrossref
37.
Morse  E, Henderson  C, Carafeno  T,  et al.  A clinical care pathway to reduce ICU usage in head and neck microvascular reconstruction.  Otolaryngol Head Neck Surg. 2018:194599818782404.PubMedGoogle Scholar
38.
Newman  EA, Guest  AB, Helvie  MA,  et al.  Changes in surgical management resulting from case review at a breast cancer multidisciplinary tumor board.  Cancer. 2006;107(10):2346-2351. doi:10.1002/cncr.22266PubMedGoogle ScholarCrossref
39.
Sher  DJ, Rusthoven  CG, Khan  SA, Fidler  MJ, Zhu  H, Koshy  M.  National patterns of care and predictors of neoadjuvant and concurrent chemotherapy use with definitive radiotherapy in the treatment of patients with oropharyngeal squamous cell carcinoma.  Cancer. 2017;123(2):273-282. doi:10.1002/cncr.30255PubMedGoogle ScholarCrossref
40.
Isenring  EA, Capra  S, Bauer  JD.  Nutrition intervention is beneficial in oncology outpatients receiving radiotherapy to the gastrointestinal or head and neck area.  Br J Cancer. 2004;91(3):447-452. doi:10.1038/sj.bjc.6601962PubMedGoogle ScholarCrossref
41.
Moffatt  S, Noble  E, White  M.  Addressing the financial consequences of cancer: qualitative evaluation of a welfare rights advice service.  PLoS One. 2012;7(8):e42979. doi:10.1371/journal.pone.0042979PubMedGoogle ScholarCrossref
42.
Roland  KB, Milliken  EL, Rohan  EA,  et al.  Use of community health workers and patient navigators to improve cancer outcomes among patients served by federally qualified health centers: a systematic literature review.  Health Equity. 2017;1(1):61-76. doi:10.1089/heq.2017.0001PubMedGoogle ScholarCrossref
43.
Price  KA, Cohen  EE.  Current treatment options for metastatic head and neck cancer.  Curr Treat Options Oncol. 2012;13(1):35-46. doi:10.1007/s11864-011-0176-yPubMedGoogle ScholarCrossref
44.
Li  H, Torabi  SJ, Yarbrough  WG, Mehra  S, Osborn  HA, Judson  B.  Association of human papillomavirus status at head and neck carcinoma subsites with overall survival.  JAMA Otolaryngol Head Neck Surg. 2018;144(6):519-525. doi:10.1001/jamaoto.2018.0395PubMedGoogle ScholarCrossref
45.
Amini  A, Jasem  J, Jones  BL,  et al.  Predictors of overall survival in human papillomavirus-associated oropharyngeal cancer using the National Cancer Data Base.  Oral Oncol. 2016;56:1-7. doi:10.1016/j.oraloncology.2016.02.011PubMedGoogle ScholarCrossref
46.
Greene  FL.  Is volume the most important predictor of outcome in cancer management?  J Surg Oncol. 2008;97(2):97-98. doi:10.1002/jso.20833PubMedGoogle ScholarCrossref
47.
Marshall  CL, Petersen  NJ, Naik  AD,  et al.  Implementation of a regional virtual tumor board: a prospective study evaluating feasibility and provider acceptance.  Telemed J E Health. 2014;20(8):705-711. doi:10.1089/tmj.2013.0320PubMedGoogle ScholarCrossref
48.
Salami  AC, Barden  GM, Castillo  DL,  et al.  Establishment of a regional virtual tumor board program to improve the process of care for patients With hepatocellular carcinoma.  J Oncol Pract. 2015;11(1):e66-e74. doi:10.1200/JOP.2014.000679PubMedGoogle ScholarCrossref
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