Disparities in survival after trimodality therapy for esophageal adenocarcinoma

Disparities in survival after trimodality therapy for esophageal adenocarcinoma Summary Trimodality therapy with neoadjuvant chemoradiation followed by surgery has emerged as the standard of care for the treatment of locally advanced esophageal cancer. Yet, there is considerable variation in survival within this population. We sought to analyze factors associated with survival after trimodality therapy in esophageal adenocarcinoma. We identified 4,679 patients from the National Cancer Database (NCDB) of the American College of Surgeons who received chemotherapy and radiation prior to surgery for esophageal adenocarcinoma from 2006 to 2013. We excluded patients with stage IV disease and unknown pathological nodal status. We performed regression analyses using a Cox proportional hazards model to identify independent predictors of overall survival. On multivariate analysis, pathologic characteristics associated with decreased overall survival included stage, lymphovascular invasion, and positive surgical margins. Insurance status, age, and comorbidity index were also associated with decreased survival. We found that pathologically node-positive patients who received additional adjuvant chemotherapy were associated with improved survival. Compared to private insurance, Medicaid (HR 1.45, CI 1.22–1.73, P < 0.0001), Medicare (HR 1.17, CI 1.04–1.31, P = 0.0082), or having no insurance (HR 1.50, CI 1.17–1.92, P = 0.0012) were all negative predictors of overall survival. In patients with esophageal adenocarcinoma who have undergone trimodality therapy, a number of different factors are associated with overall survival. In particular, socioeconomic factors relating to access to care are independent predictors of survival. Despite receiving the standard of care, treatment disparities persist in this population of patients. INTRODUCTION Each year, an estimated 15,690 deaths are expected from esophageal cancer, with only 19% of esophageal cancer patients surviving at five years.1 Trimodality therapy with neoadjuvant chemoradiation followed by surgery has been shown to improve survival compared to surgery alone for the treatment of locally advanced esophageal cancer.2 The findings of the CROSS trial have provided the basis for current National Comprehensive Cancer Network (NCCN) guidelines for the role of neoadjuvant therapy in the management of esophageal cancer; however, there is considerable variation in survival in this population.3 In addition, barriers to receiving neoadjuvant therapy are multifactorial, including age, comorbidities, and insurance status.4,5 As current NCCN guidelines recommend surveillance after trimodality therapy, identifying factors associated with survival after trimodality therapy remains an area of investigation. Recently, socioeconomic factors such as insurance status have been shown to be an independent predictor of survival in other forms of cancer.6,7 A retrospective study using the National Cancer Database (NCDB) demonstrated a survival benefit with adjuvant chemotherapy after trimodality therapy in pathologically node-positive esophageal adenocarcinoma patients.8 Yet, even in cancers where NCCN guidelines include adjuvant therapy, socioeconomic factors can serve as barriers to receive adjuvant treatment.9 In this study, we sought to analyze a variety of factors, including insurance status and adjuvant chemotherapy, to identify independent predictors of survival after trimodality therapy in esophageal adenocarcinoma. METHODS An Institutional Review Board approved retrospective analysis of the NCDB for patients who underwent esophagectomy for esophageal cancer from 2006 to 2013. The NCDB is a comprehensive clinical oncology database comprised of information from over 1500 Commission on Cancer (CoC)-accredited institutions, accounting for approximately 70% of newly diagnosed cancer cases across the United States. We performed stepwise inclusion and exclusion counts on an initial subset of patients identified to have a diagnosis of esophageal cancer as defined by the International Classification for Diseases, 3rd edn. Inclusion criteria included patients aged 18–90 years who underwent esophagectomy for esophageal adenocarcinoma, whom were treated with either neoadjuvant chemoradiotherapy only or neoadjuvant chemoradiotherapy and adjuvant chemotherapy. We excluded patients with stage IV disease, unknown pathological nodal status, a history of prior malignancy, and those with no followup information. TNM staging was assessed according to the American Joint Commission on Cancer 7th ed. staging definitions. Overall patient demographics and tumor characteristics were recorded and compared between groups. Hospital types were reported on the basis of cancer program categories as designated by the CoC.10 Insurance types reported included patients either with private insurance, not insured, or with Medicaid or Medicare. Medicaid is a government insurance program primarily for patients with limited income. Medicare is a government insurance program, which covers people age 65 or older, regardless of income. Wilcoxon-Mann-Whitney rank sum tests were performed for continuous variables and chi-squared tests for categorical data. A multivariate analysis was performed using a Cox proportional hazards model to identify potential independent predictors of overall survival such as age, gender, ethnicity, neoadjuvant/adjuvant therapy, socioeconomic status, insurance status, tumor characteristics, and surgical margin status. RESULTS A total of 4679 patients were identified from the NCDB who received neoadjuvant chemoradiotherapy followed by surgery for esophageal adenocarcinoma. Patient demographics are demonstrated in the Table 1. The median age was 62 years (interquartile range (IQR): 55–68), with 4217 (90%) patients being male. The vast majority of patients receiving trimodality therapy (4306; 92.0%) did not receive adjuvant chemotherapy. Table 1 Patient demographics, stage I–III esophageal adenocarcinoma after trimodality therapy, N = 4679. All N = 4679 N (%) Age Median (IQR+) 62 (55–68) Adjuvant chemotherapy No 4306 (92) Yes 373 (8) Distance to hospital <6 miles 969 (21) 6–15 miles 1107 (24) 15.1–44 miles 1356 (29) >44 miles 1247 (27) Sex Male 4217 (90) Female 462 (10) Hospital type Comprehensive 1479 (32) Academic/research 2583 (55) Community 254 (5) Integrated network 264 (6) Not given for age <40 89 (2) Other or unknown 10 (0) Primary insurance Private insurance 2551 (55) Medicaid 224 (5) Medicare 1742 (37) Not insured 110 (2) Insurance status unknown 52 (1) Reporting sources Single facility NCDB report 3149 (67) Multiple 1530 (33) Income quartiles <$30,000 429 (9) $30,000–$35,999 827 (18) $36,000–$45,999 1353 (29) $46,000+ 1899 (41) Not available 171 (4) High school non-Graduate rate quartiles Q1 > = 29% 499 (11) Q2 20–28.9% 1089 (23) Q3 14–19.9% 1220 (26) Q4 < 14% 1700 (36) Not available 171 (4) Urban/rural Metro > 1 million 1932 (41) Metro 250,000–1 million 974 (21) Metro < 250,000 566 (12) Urban > 20,000 394 (8) Urban/rural < 20,000 646 (14) Unknown 167 (4) Age group 21–55 1239 (26) 56–62 1261 (27) 63–68 1158 (25) 69–89 1021 (22) Diagnosis time period 2006–2008 1601 (34) 2009–2011 2169 (46) 2012–2013 909 (19) Race/ethnicity White 4499 (96) Black 74 (2) Hispanic white 86 (2) Asian/Pacific islanders 20 (0) Charlson index group Low risk 3459 (74) Intermediate risk 1001 (21) High risk 219 (5) Surgical approach Open or unspecified 1370 (29) Minimally invasive 564 (12) Minimally invasive → open 71 (2) Unknown surgical approach 2674 (57) Grade Well differentiated 190 (4) Moderately differentiated 1608 (34) Poorly differentiated 2160 (46) Undifferentiated 74 (2) Unknown grade 647 (14) Tumor size <3 949 (20) 3–4.9 1030 (22) 5+ 1406 (30) Unknown size 1294 (28) Lymphovascular invasion Not present 1354 (29) Present 336 (7) Not applicable 38 (1) Unknown 2951 (63) T pathologic group T1 851 (18) T2 959 (20) T3 1887 (40) T4 56 (1) T0/Tis 694 (15) TX 232 (5) N pathologic group N− 2771 (59) N+ 1908 (41) Examined nodes 0–7 1271 (27) 8–12 1102 (24) 13–18 1066 (23) 19–83 1089 (23) Unknown # nodes 151 (3) Stage I 842 (18) II 2097 (45) III 1740 (37) Surgical margins Negative 4326 (92) Positive 279 (6) Margins unknown/not applicable 74 (2) All N = 4679 N (%) Age Median (IQR+) 62 (55–68) Adjuvant chemotherapy No 4306 (92) Yes 373 (8) Distance to hospital <6 miles 969 (21) 6–15 miles 1107 (24) 15.1–44 miles 1356 (29) >44 miles 1247 (27) Sex Male 4217 (90) Female 462 (10) Hospital type Comprehensive 1479 (32) Academic/research 2583 (55) Community 254 (5) Integrated network 264 (6) Not given for age <40 89 (2) Other or unknown 10 (0) Primary insurance Private insurance 2551 (55) Medicaid 224 (5) Medicare 1742 (37) Not insured 110 (2) Insurance status unknown 52 (1) Reporting sources Single facility NCDB report 3149 (67) Multiple 1530 (33) Income quartiles <$30,000 429 (9) $30,000–$35,999 827 (18) $36,000–$45,999 1353 (29) $46,000+ 1899 (41) Not available 171 (4) High school non-Graduate rate quartiles Q1 > = 29% 499 (11) Q2 20–28.9% 1089 (23) Q3 14–19.9% 1220 (26) Q4 < 14% 1700 (36) Not available 171 (4) Urban/rural Metro > 1 million 1932 (41) Metro 250,000–1 million 974 (21) Metro < 250,000 566 (12) Urban > 20,000 394 (8) Urban/rural < 20,000 646 (14) Unknown 167 (4) Age group 21–55 1239 (26) 56–62 1261 (27) 63–68 1158 (25) 69–89 1021 (22) Diagnosis time period 2006–2008 1601 (34) 2009–2011 2169 (46) 2012–2013 909 (19) Race/ethnicity White 4499 (96) Black 74 (2) Hispanic white 86 (2) Asian/Pacific islanders 20 (0) Charlson index group Low risk 3459 (74) Intermediate risk 1001 (21) High risk 219 (5) Surgical approach Open or unspecified 1370 (29) Minimally invasive 564 (12) Minimally invasive → open 71 (2) Unknown surgical approach 2674 (57) Grade Well differentiated 190 (4) Moderately differentiated 1608 (34) Poorly differentiated 2160 (46) Undifferentiated 74 (2) Unknown grade 647 (14) Tumor size <3 949 (20) 3–4.9 1030 (22) 5+ 1406 (30) Unknown size 1294 (28) Lymphovascular invasion Not present 1354 (29) Present 336 (7) Not applicable 38 (1) Unknown 2951 (63) T pathologic group T1 851 (18) T2 959 (20) T3 1887 (40) T4 56 (1) T0/Tis 694 (15) TX 232 (5) N pathologic group N− 2771 (59) N+ 1908 (41) Examined nodes 0–7 1271 (27) 8–12 1102 (24) 13–18 1066 (23) 19–83 1089 (23) Unknown # nodes 151 (3) Stage I 842 (18) II 2097 (45) III 1740 (37) Surgical margins Negative 4326 (92) Positive 279 (6) Margins unknown/not applicable 74 (2) IQR, interquartile range; NCDB, National Cancer Database. View Large Table 1 Patient demographics, stage I–III esophageal adenocarcinoma after trimodality therapy, N = 4679. All N = 4679 N (%) Age Median (IQR+) 62 (55–68) Adjuvant chemotherapy No 4306 (92) Yes 373 (8) Distance to hospital <6 miles 969 (21) 6–15 miles 1107 (24) 15.1–44 miles 1356 (29) >44 miles 1247 (27) Sex Male 4217 (90) Female 462 (10) Hospital type Comprehensive 1479 (32) Academic/research 2583 (55) Community 254 (5) Integrated network 264 (6) Not given for age <40 89 (2) Other or unknown 10 (0) Primary insurance Private insurance 2551 (55) Medicaid 224 (5) Medicare 1742 (37) Not insured 110 (2) Insurance status unknown 52 (1) Reporting sources Single facility NCDB report 3149 (67) Multiple 1530 (33) Income quartiles <$30,000 429 (9) $30,000–$35,999 827 (18) $36,000–$45,999 1353 (29) $46,000+ 1899 (41) Not available 171 (4) High school non-Graduate rate quartiles Q1 > = 29% 499 (11) Q2 20–28.9% 1089 (23) Q3 14–19.9% 1220 (26) Q4 < 14% 1700 (36) Not available 171 (4) Urban/rural Metro > 1 million 1932 (41) Metro 250,000–1 million 974 (21) Metro < 250,000 566 (12) Urban > 20,000 394 (8) Urban/rural < 20,000 646 (14) Unknown 167 (4) Age group 21–55 1239 (26) 56–62 1261 (27) 63–68 1158 (25) 69–89 1021 (22) Diagnosis time period 2006–2008 1601 (34) 2009–2011 2169 (46) 2012–2013 909 (19) Race/ethnicity White 4499 (96) Black 74 (2) Hispanic white 86 (2) Asian/Pacific islanders 20 (0) Charlson index group Low risk 3459 (74) Intermediate risk 1001 (21) High risk 219 (5) Surgical approach Open or unspecified 1370 (29) Minimally invasive 564 (12) Minimally invasive → open 71 (2) Unknown surgical approach 2674 (57) Grade Well differentiated 190 (4) Moderately differentiated 1608 (34) Poorly differentiated 2160 (46) Undifferentiated 74 (2) Unknown grade 647 (14) Tumor size <3 949 (20) 3–4.9 1030 (22) 5+ 1406 (30) Unknown size 1294 (28) Lymphovascular invasion Not present 1354 (29) Present 336 (7) Not applicable 38 (1) Unknown 2951 (63) T pathologic group T1 851 (18) T2 959 (20) T3 1887 (40) T4 56 (1) T0/Tis 694 (15) TX 232 (5) N pathologic group N− 2771 (59) N+ 1908 (41) Examined nodes 0–7 1271 (27) 8–12 1102 (24) 13–18 1066 (23) 19–83 1089 (23) Unknown # nodes 151 (3) Stage I 842 (18) II 2097 (45) III 1740 (37) Surgical margins Negative 4326 (92) Positive 279 (6) Margins unknown/not applicable 74 (2) All N = 4679 N (%) Age Median (IQR+) 62 (55–68) Adjuvant chemotherapy No 4306 (92) Yes 373 (8) Distance to hospital <6 miles 969 (21) 6–15 miles 1107 (24) 15.1–44 miles 1356 (29) >44 miles 1247 (27) Sex Male 4217 (90) Female 462 (10) Hospital type Comprehensive 1479 (32) Academic/research 2583 (55) Community 254 (5) Integrated network 264 (6) Not given for age <40 89 (2) Other or unknown 10 (0) Primary insurance Private insurance 2551 (55) Medicaid 224 (5) Medicare 1742 (37) Not insured 110 (2) Insurance status unknown 52 (1) Reporting sources Single facility NCDB report 3149 (67) Multiple 1530 (33) Income quartiles <$30,000 429 (9) $30,000–$35,999 827 (18) $36,000–$45,999 1353 (29) $46,000+ 1899 (41) Not available 171 (4) High school non-Graduate rate quartiles Q1 > = 29% 499 (11) Q2 20–28.9% 1089 (23) Q3 14–19.9% 1220 (26) Q4 < 14% 1700 (36) Not available 171 (4) Urban/rural Metro > 1 million 1932 (41) Metro 250,000–1 million 974 (21) Metro < 250,000 566 (12) Urban > 20,000 394 (8) Urban/rural < 20,000 646 (14) Unknown 167 (4) Age group 21–55 1239 (26) 56–62 1261 (27) 63–68 1158 (25) 69–89 1021 (22) Diagnosis time period 2006–2008 1601 (34) 2009–2011 2169 (46) 2012–2013 909 (19) Race/ethnicity White 4499 (96) Black 74 (2) Hispanic white 86 (2) Asian/Pacific islanders 20 (0) Charlson index group Low risk 3459 (74) Intermediate risk 1001 (21) High risk 219 (5) Surgical approach Open or unspecified 1370 (29) Minimally invasive 564 (12) Minimally invasive → open 71 (2) Unknown surgical approach 2674 (57) Grade Well differentiated 190 (4) Moderately differentiated 1608 (34) Poorly differentiated 2160 (46) Undifferentiated 74 (2) Unknown grade 647 (14) Tumor size <3 949 (20) 3–4.9 1030 (22) 5+ 1406 (30) Unknown size 1294 (28) Lymphovascular invasion Not present 1354 (29) Present 336 (7) Not applicable 38 (1) Unknown 2951 (63) T pathologic group T1 851 (18) T2 959 (20) T3 1887 (40) T4 56 (1) T0/Tis 694 (15) TX 232 (5) N pathologic group N− 2771 (59) N+ 1908 (41) Examined nodes 0–7 1271 (27) 8–12 1102 (24) 13–18 1066 (23) 19–83 1089 (23) Unknown # nodes 151 (3) Stage I 842 (18) II 2097 (45) III 1740 (37) Surgical margins Negative 4326 (92) Positive 279 (6) Margins unknown/not applicable 74 (2) IQR, interquartile range; NCDB, National Cancer Database. View Large On multivariate analysis, pathologic characteristics associated with decreased overall survival included stage, lymphovascular invasion, and positive surgical margins (Fig. 1). Insurance status, age, and comorbidity index were also associated with decreased survival. We found that patients who received additional adjuvant chemotherapy had a trend toward improved overall survival (HR 0.87, CI 0.76–1.01, P = 0.0636). Treatment at an academic/research hospital, as well as greater lymph node yields, was associated with improved overall survival. Compared to private insurance, Medicare (HR 1.17, CI 1.04–1.31, P = 0.0082), Medicaid (HR 1.45, CI 1.22–1.73, P < 0.0001), or having no insurance (HR 1.50, CI 1.17–1.92, P = 0.0012) were all negative predictors of overall survival. Patients who received adjuvant chemotherapy were more likely to have private insurance (69 vs. 53%, P < 0.0001). Fig. 1 View largeDownload slide Multivariate hazard ratios and 95% confidence intervals, overall cohort. *Hospital type is not reported routinely in this national database for patients under the age of 40 in an effort to protect confidentiality. While this subgroup is not shown in this Figure, it was included in the analysis. Fig. 1 View largeDownload slide Multivariate hazard ratios and 95% confidence intervals, overall cohort. *Hospital type is not reported routinely in this national database for patients under the age of 40 in an effort to protect confidentiality. While this subgroup is not shown in this Figure, it was included in the analysis. On final pathology, 1908 (41%) patients had node-positive disease. In the node-positive subgroup, patients who underwent adjuvant chemotherapy had improved survival (HR 0.74, CI 0.63–0.88, P = 0.0005) (Fig. 2), whereas adjuvant chemotherapy was not associated with improved survival in the node-negative subgroup. Compared to private insurance, Medicaid (HR 1.40, CI 1.09–1.80, P = 0.0081) or having no insurance (HR 1.71, CI 1.24–2.35, P = 0.0011) were negative predictors of overall survival in node-positive patients. Median overall survival in patients with node-positive disease who received adjuvant chemotherapy was 30.9 months, in contrast to 23.1 months in patients who did not (log-rank p-value, 0.0001), shown in Figure 3. Fig. 2 View largeDownload slide Multivariate hazard ratios and 95% confidence intervals, Node-positive cohort. *Hospital type is not reported routinely in this national database for patients under the age of 40 in an effort to protect confidentiality. While this subgroup is not shown in this Figure, it was included in the analysis. Fig. 2 View largeDownload slide Multivariate hazard ratios and 95% confidence intervals, Node-positive cohort. *Hospital type is not reported routinely in this national database for patients under the age of 40 in an effort to protect confidentiality. While this subgroup is not shown in this Figure, it was included in the analysis. Fig. 3 View largeDownload slide Overall survival probability stratified by adjuvant chemotherapy, node-positive patients. Fig. 3 View largeDownload slide Overall survival probability stratified by adjuvant chemotherapy, node-positive patients. DISCUSSION Significant disparities in esophageal cancer outcomes are known.4,5 Previous research has found that much of the disparities in outcomes is attributable to differences in treatment, with non-White patients and lower socioeconomic status patients less likely to receive surgery.4 In this study, we found that certain socioeconomic factors such as insurance status and rural setting continued to be associated with survival even among patients who all received standard of care, trimodality therapy. These socioeconomic factors are often associated with comorbidities, but in our multivariate analysis, each was independently associated with survival. Many of the significant sociodemographic factors were related to access to tertiary care (insurance status, hospital type, location). In fact, insurance status was a stronger predictor of survival than many other factors, including the use of adjuvant chemotherapy. This leads us to wonder: Why do sociodemographic disparities persist? Why may outcomes be different when patients with different social determinants of health receive the same treatment? Perhaps these findings highlight the notion that medical care in patients with esophageal cancer or other malignancies does not simply end after receiving the indexed treatment, and that surveillance in itself is equally important in the care of these patients. For example, in other malignancies, adherence to posttreatment surveillance has been shown to be associated with improved overall survival.11 Currently, NCCN guidelines recommend the following as part of surveillance: history and physical examinations every 3–6 months for 1–2 years, every 6–12 months for 3–5 years, and annually thereafter, with laboratory testing and imaging as indicated and stratified by pathologic staging.12 Patients undergoing esophagectomy may also be a patient population with unique long-term needs. Studies have found that although overall long-term quality of life is similar to the general populations, certain symptoms, such as aspiration, persist after esophagectomy.13 There are also emerging data regarding the impact of social determinants of health on life expectancy beyond just treatment disparities.14 Another interesting finding was the impact of adjuvant chemotherapy on survival. Although not part of NCCN guidelines, 8% of patients in this study received adjuvant chemotherapy. Similar to a recent publication by Burt et al., we found that adjuvant chemotherapy was associated with a lower risk of death in patients with residual nodal disease (ypTanyN+), but not among all patients.8 It is unclear why these patients were offered adjuvant therapy, but it does not appear to be random. Patients were much more likely to be given adjuvant chemotherapy if they had node-positive disease. As such, limitations of this study include its retrospective, observational design. Inherent to this is selection bias, as we do not have information on why or why not adjuvant chemotherapy was administered. Unfortunately, the NCDB does not have data on perioperative morbidity or details on chemotherapy and radiation regimens/techniques, both of which could potentially significantly impact decision-making. Not all data with regards to all variables were available, as indicated by some categories of ‘unknown’ or ‘absence of data.’ For example, hospital type is not recorded for patients under the age of 40 due to an effort to maintain confidentiality in accordance with national regulations. Finally, the NCDB does not incorporate data from all hospitals in the United States, and thus perhaps this patient population may not be truly representative of outcomes and practices nationwide. In conclusion, we found that in patients with esophageal adenocarcinoma who have undergone trimodality therapy, a number of different factors are associated with survival: biology of the disease, health of the patient, access to care, and adjuvant chemotherapy. Characteristics such as advanced pathologic stage, positive margins, octogenarians, and patients with comorbidities are, as expected, associated with decreased survival. However, sociodemographic factors relating to access to care are also important predictors of survival. Despite receiving the standard of care, treatment disparities persist in this population of patients. Notes Conflicts of Interest and Source of Funding: The authors have no conflicts of interest. No funding was obtained for this study. Dan J. Raz, MD, is a consultant for Cireca, LLC and has grant funding from Merck. The data used in the study are derived from a de-identified 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 investigators. The NCDB is a joint project of the Commission on Cancer of the American College of Surgeons and the American Cancer Society. This work was presented at the 2017 Gastrointestinal Cancers Symposium of the American Society of Clinical Oncology in San Francisco, CA. Specific author contributions: Conception/design: Oliver S. Eng, Rebecca A. Nelson, Jae Y. Kim; Data analysis/acquisition: Oliver S. Eng, Rebecca A. Nelson; Data interpretation: Oliver S. Eng, Rebecca A. Nelson, Ioannis Konstantinidis, Joseph Chao, Loretta Erhunmwunsee, Dan J. Raz, Jae Y. Kim; Drafting: Oliver S. Eng, Jae Y. Kim; Critical revision: Ioannis Konstantinidis, Joseph Chao, Loretta Erhunmwunsee, Dan J. Raz, Jae Y. Kim; Final approval for publication: Oliver S. Eng, Rebecca A. Nelson, Ioannis Konstantinidis, Joseph Chao, Loretta Erhunmwunsee, Dan J. Raz, Jae Y. Kim; Accountability agreement: Oliver S. Eng, Rebecca A. Nelson, Ioannis Konstantinidis, Joseph Chao, Loretta Erhunmwunsee, Dan J. Raz, Jae Y. Kim. References 1 Siegel R L , Miller K D , Jemal A . Cancer statistics, 2016 . CA Cancer J Clin 2016 ; 66 : 7 – 30 . Google Scholar Crossref Search ADS PubMed 2 Shapiro J , van Lanschot J J , Hulshof M C et al. Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): long-term results of a randomised controlled trial . Lancet Oncol 2015 ; 16 : 1090 – 8 . Google Scholar Crossref Search ADS PubMed 3 Ajani J A , D’Amico T A , Almhanna K et al. Esophageal and esophagogastric junction cancers, version 1.2015 . J Natl Compr Canc Netw 2015 ; 13 : 194 – 227 . Google Scholar Crossref Search ADS PubMed 4 Revels S L , Morris A M , Reddy R M , Akateh C , Wong S L . Racial disparities in esophageal cancer outcomes . Ann Surg Oncol 2013 : 20 ; 1136 – 41 . doi:10.1245/s10434-012-2807-3 . Google Scholar Crossref Search ADS PubMed 5 Merkow R P , Bilimoria K Y , McCarter M D , Chow W B , Ko C Y , Bentrem D J . Use of multimodality neoadjuvant therapy for esophageal cancer in the United States: assessment of 987 hospitals . Ann Surg Oncol 2012 ; 19 : 357 – 64 . Google Scholar Crossref Search ADS PubMed 6 Markt S C , Lago-Hernandez C A , Miller R E et al. Insurance status and disparities in disease presentation, treatment, and outcomes for men with germ cell tumors . Cancer 2016 ; 122 : 3127 – 35 . Google Scholar Crossref Search ADS PubMed 7 Rong X , Yang W , Garzon-Muvdi T et al. Influence of insurance status on survival of adults with glioblastoma multiforme: a population-based study . Cancer 2016 ; 122 : 3157 – 65 . Google Scholar Crossref Search ADS PubMed 8 Burt B M , Groth S S , Sada Y H et al. Utility of Adjuvant chemotherapy after neoadjuvant chemoradiation and esophagectomy for esophageal cancer . Ann Surg 2017 ; 266 : 297 – 304 . Google Scholar Crossref Search ADS PubMed 9 Lin C C , Bruinooge S S , Kirkwood M K et al. Association between geographic access to cancer care, insurance, and receipt of chemotherapy: geographic distribution of oncologists and travel distance . J Clin Oncol 2015 ; 33 : 3177 – 85 . Google Scholar Crossref Search ADS PubMed 10 Commission on Cancer: About Program Categories . https://www.facs.org/quality-programs/cancer/coc/apply/categories. Accessed August 1 , 2018 . 11 Deutschmann M W , Sykes K J , Harbison J , Cabrera-Muffly C , Shnayder Y . The impact of compliance in posttreatment surveillance in head and neck squamous cell carcinoma . JAMA Otolaryngol Head Neck Surg 2015 ; 141 : 519 – 25 . Google Scholar Crossref Search ADS PubMed 12 NCCN Guidelines® & Clinical Resources . https://www.nccn.org/professionals/physician_gls/default.aspx. Accessed August 1 , 2018 . 13 Derogar M , Lagergren P . Health-related quality of life among 5-year survivors of esophageal cancer surgery: a prospective population-based study . J Clin Oncol 2012 ; 30 : 413 – 8 . Google Scholar Crossref Search ADS PubMed 14 Djarv T , Lagergren P . Six-month postoperative quality of life predicts long-term survival after oesophageal cancer surgery . Eur J Cancer 2011 ; 47 : 530 – 5 . Google Scholar Crossref Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Diseases of the Esophagus Oxford University Press

Disparities in survival after trimodality therapy for esophageal adenocarcinoma

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus.
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1120-8694
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1442-2050
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Abstract

Summary Trimodality therapy with neoadjuvant chemoradiation followed by surgery has emerged as the standard of care for the treatment of locally advanced esophageal cancer. Yet, there is considerable variation in survival within this population. We sought to analyze factors associated with survival after trimodality therapy in esophageal adenocarcinoma. We identified 4,679 patients from the National Cancer Database (NCDB) of the American College of Surgeons who received chemotherapy and radiation prior to surgery for esophageal adenocarcinoma from 2006 to 2013. We excluded patients with stage IV disease and unknown pathological nodal status. We performed regression analyses using a Cox proportional hazards model to identify independent predictors of overall survival. On multivariate analysis, pathologic characteristics associated with decreased overall survival included stage, lymphovascular invasion, and positive surgical margins. Insurance status, age, and comorbidity index were also associated with decreased survival. We found that pathologically node-positive patients who received additional adjuvant chemotherapy were associated with improved survival. Compared to private insurance, Medicaid (HR 1.45, CI 1.22–1.73, P < 0.0001), Medicare (HR 1.17, CI 1.04–1.31, P = 0.0082), or having no insurance (HR 1.50, CI 1.17–1.92, P = 0.0012) were all negative predictors of overall survival. In patients with esophageal adenocarcinoma who have undergone trimodality therapy, a number of different factors are associated with overall survival. In particular, socioeconomic factors relating to access to care are independent predictors of survival. Despite receiving the standard of care, treatment disparities persist in this population of patients. INTRODUCTION Each year, an estimated 15,690 deaths are expected from esophageal cancer, with only 19% of esophageal cancer patients surviving at five years.1 Trimodality therapy with neoadjuvant chemoradiation followed by surgery has been shown to improve survival compared to surgery alone for the treatment of locally advanced esophageal cancer.2 The findings of the CROSS trial have provided the basis for current National Comprehensive Cancer Network (NCCN) guidelines for the role of neoadjuvant therapy in the management of esophageal cancer; however, there is considerable variation in survival in this population.3 In addition, barriers to receiving neoadjuvant therapy are multifactorial, including age, comorbidities, and insurance status.4,5 As current NCCN guidelines recommend surveillance after trimodality therapy, identifying factors associated with survival after trimodality therapy remains an area of investigation. Recently, socioeconomic factors such as insurance status have been shown to be an independent predictor of survival in other forms of cancer.6,7 A retrospective study using the National Cancer Database (NCDB) demonstrated a survival benefit with adjuvant chemotherapy after trimodality therapy in pathologically node-positive esophageal adenocarcinoma patients.8 Yet, even in cancers where NCCN guidelines include adjuvant therapy, socioeconomic factors can serve as barriers to receive adjuvant treatment.9 In this study, we sought to analyze a variety of factors, including insurance status and adjuvant chemotherapy, to identify independent predictors of survival after trimodality therapy in esophageal adenocarcinoma. METHODS An Institutional Review Board approved retrospective analysis of the NCDB for patients who underwent esophagectomy for esophageal cancer from 2006 to 2013. The NCDB is a comprehensive clinical oncology database comprised of information from over 1500 Commission on Cancer (CoC)-accredited institutions, accounting for approximately 70% of newly diagnosed cancer cases across the United States. We performed stepwise inclusion and exclusion counts on an initial subset of patients identified to have a diagnosis of esophageal cancer as defined by the International Classification for Diseases, 3rd edn. Inclusion criteria included patients aged 18–90 years who underwent esophagectomy for esophageal adenocarcinoma, whom were treated with either neoadjuvant chemoradiotherapy only or neoadjuvant chemoradiotherapy and adjuvant chemotherapy. We excluded patients with stage IV disease, unknown pathological nodal status, a history of prior malignancy, and those with no followup information. TNM staging was assessed according to the American Joint Commission on Cancer 7th ed. staging definitions. Overall patient demographics and tumor characteristics were recorded and compared between groups. Hospital types were reported on the basis of cancer program categories as designated by the CoC.10 Insurance types reported included patients either with private insurance, not insured, or with Medicaid or Medicare. Medicaid is a government insurance program primarily for patients with limited income. Medicare is a government insurance program, which covers people age 65 or older, regardless of income. Wilcoxon-Mann-Whitney rank sum tests were performed for continuous variables and chi-squared tests for categorical data. A multivariate analysis was performed using a Cox proportional hazards model to identify potential independent predictors of overall survival such as age, gender, ethnicity, neoadjuvant/adjuvant therapy, socioeconomic status, insurance status, tumor characteristics, and surgical margin status. RESULTS A total of 4679 patients were identified from the NCDB who received neoadjuvant chemoradiotherapy followed by surgery for esophageal adenocarcinoma. Patient demographics are demonstrated in the Table 1. The median age was 62 years (interquartile range (IQR): 55–68), with 4217 (90%) patients being male. The vast majority of patients receiving trimodality therapy (4306; 92.0%) did not receive adjuvant chemotherapy. Table 1 Patient demographics, stage I–III esophageal adenocarcinoma after trimodality therapy, N = 4679. All N = 4679 N (%) Age Median (IQR+) 62 (55–68) Adjuvant chemotherapy No 4306 (92) Yes 373 (8) Distance to hospital <6 miles 969 (21) 6–15 miles 1107 (24) 15.1–44 miles 1356 (29) >44 miles 1247 (27) Sex Male 4217 (90) Female 462 (10) Hospital type Comprehensive 1479 (32) Academic/research 2583 (55) Community 254 (5) Integrated network 264 (6) Not given for age <40 89 (2) Other or unknown 10 (0) Primary insurance Private insurance 2551 (55) Medicaid 224 (5) Medicare 1742 (37) Not insured 110 (2) Insurance status unknown 52 (1) Reporting sources Single facility NCDB report 3149 (67) Multiple 1530 (33) Income quartiles <$30,000 429 (9) $30,000–$35,999 827 (18) $36,000–$45,999 1353 (29) $46,000+ 1899 (41) Not available 171 (4) High school non-Graduate rate quartiles Q1 > = 29% 499 (11) Q2 20–28.9% 1089 (23) Q3 14–19.9% 1220 (26) Q4 < 14% 1700 (36) Not available 171 (4) Urban/rural Metro > 1 million 1932 (41) Metro 250,000–1 million 974 (21) Metro < 250,000 566 (12) Urban > 20,000 394 (8) Urban/rural < 20,000 646 (14) Unknown 167 (4) Age group 21–55 1239 (26) 56–62 1261 (27) 63–68 1158 (25) 69–89 1021 (22) Diagnosis time period 2006–2008 1601 (34) 2009–2011 2169 (46) 2012–2013 909 (19) Race/ethnicity White 4499 (96) Black 74 (2) Hispanic white 86 (2) Asian/Pacific islanders 20 (0) Charlson index group Low risk 3459 (74) Intermediate risk 1001 (21) High risk 219 (5) Surgical approach Open or unspecified 1370 (29) Minimally invasive 564 (12) Minimally invasive → open 71 (2) Unknown surgical approach 2674 (57) Grade Well differentiated 190 (4) Moderately differentiated 1608 (34) Poorly differentiated 2160 (46) Undifferentiated 74 (2) Unknown grade 647 (14) Tumor size <3 949 (20) 3–4.9 1030 (22) 5+ 1406 (30) Unknown size 1294 (28) Lymphovascular invasion Not present 1354 (29) Present 336 (7) Not applicable 38 (1) Unknown 2951 (63) T pathologic group T1 851 (18) T2 959 (20) T3 1887 (40) T4 56 (1) T0/Tis 694 (15) TX 232 (5) N pathologic group N− 2771 (59) N+ 1908 (41) Examined nodes 0–7 1271 (27) 8–12 1102 (24) 13–18 1066 (23) 19–83 1089 (23) Unknown # nodes 151 (3) Stage I 842 (18) II 2097 (45) III 1740 (37) Surgical margins Negative 4326 (92) Positive 279 (6) Margins unknown/not applicable 74 (2) All N = 4679 N (%) Age Median (IQR+) 62 (55–68) Adjuvant chemotherapy No 4306 (92) Yes 373 (8) Distance to hospital <6 miles 969 (21) 6–15 miles 1107 (24) 15.1–44 miles 1356 (29) >44 miles 1247 (27) Sex Male 4217 (90) Female 462 (10) Hospital type Comprehensive 1479 (32) Academic/research 2583 (55) Community 254 (5) Integrated network 264 (6) Not given for age <40 89 (2) Other or unknown 10 (0) Primary insurance Private insurance 2551 (55) Medicaid 224 (5) Medicare 1742 (37) Not insured 110 (2) Insurance status unknown 52 (1) Reporting sources Single facility NCDB report 3149 (67) Multiple 1530 (33) Income quartiles <$30,000 429 (9) $30,000–$35,999 827 (18) $36,000–$45,999 1353 (29) $46,000+ 1899 (41) Not available 171 (4) High school non-Graduate rate quartiles Q1 > = 29% 499 (11) Q2 20–28.9% 1089 (23) Q3 14–19.9% 1220 (26) Q4 < 14% 1700 (36) Not available 171 (4) Urban/rural Metro > 1 million 1932 (41) Metro 250,000–1 million 974 (21) Metro < 250,000 566 (12) Urban > 20,000 394 (8) Urban/rural < 20,000 646 (14) Unknown 167 (4) Age group 21–55 1239 (26) 56–62 1261 (27) 63–68 1158 (25) 69–89 1021 (22) Diagnosis time period 2006–2008 1601 (34) 2009–2011 2169 (46) 2012–2013 909 (19) Race/ethnicity White 4499 (96) Black 74 (2) Hispanic white 86 (2) Asian/Pacific islanders 20 (0) Charlson index group Low risk 3459 (74) Intermediate risk 1001 (21) High risk 219 (5) Surgical approach Open or unspecified 1370 (29) Minimally invasive 564 (12) Minimally invasive → open 71 (2) Unknown surgical approach 2674 (57) Grade Well differentiated 190 (4) Moderately differentiated 1608 (34) Poorly differentiated 2160 (46) Undifferentiated 74 (2) Unknown grade 647 (14) Tumor size <3 949 (20) 3–4.9 1030 (22) 5+ 1406 (30) Unknown size 1294 (28) Lymphovascular invasion Not present 1354 (29) Present 336 (7) Not applicable 38 (1) Unknown 2951 (63) T pathologic group T1 851 (18) T2 959 (20) T3 1887 (40) T4 56 (1) T0/Tis 694 (15) TX 232 (5) N pathologic group N− 2771 (59) N+ 1908 (41) Examined nodes 0–7 1271 (27) 8–12 1102 (24) 13–18 1066 (23) 19–83 1089 (23) Unknown # nodes 151 (3) Stage I 842 (18) II 2097 (45) III 1740 (37) Surgical margins Negative 4326 (92) Positive 279 (6) Margins unknown/not applicable 74 (2) IQR, interquartile range; NCDB, National Cancer Database. View Large Table 1 Patient demographics, stage I–III esophageal adenocarcinoma after trimodality therapy, N = 4679. All N = 4679 N (%) Age Median (IQR+) 62 (55–68) Adjuvant chemotherapy No 4306 (92) Yes 373 (8) Distance to hospital <6 miles 969 (21) 6–15 miles 1107 (24) 15.1–44 miles 1356 (29) >44 miles 1247 (27) Sex Male 4217 (90) Female 462 (10) Hospital type Comprehensive 1479 (32) Academic/research 2583 (55) Community 254 (5) Integrated network 264 (6) Not given for age <40 89 (2) Other or unknown 10 (0) Primary insurance Private insurance 2551 (55) Medicaid 224 (5) Medicare 1742 (37) Not insured 110 (2) Insurance status unknown 52 (1) Reporting sources Single facility NCDB report 3149 (67) Multiple 1530 (33) Income quartiles <$30,000 429 (9) $30,000–$35,999 827 (18) $36,000–$45,999 1353 (29) $46,000+ 1899 (41) Not available 171 (4) High school non-Graduate rate quartiles Q1 > = 29% 499 (11) Q2 20–28.9% 1089 (23) Q3 14–19.9% 1220 (26) Q4 < 14% 1700 (36) Not available 171 (4) Urban/rural Metro > 1 million 1932 (41) Metro 250,000–1 million 974 (21) Metro < 250,000 566 (12) Urban > 20,000 394 (8) Urban/rural < 20,000 646 (14) Unknown 167 (4) Age group 21–55 1239 (26) 56–62 1261 (27) 63–68 1158 (25) 69–89 1021 (22) Diagnosis time period 2006–2008 1601 (34) 2009–2011 2169 (46) 2012–2013 909 (19) Race/ethnicity White 4499 (96) Black 74 (2) Hispanic white 86 (2) Asian/Pacific islanders 20 (0) Charlson index group Low risk 3459 (74) Intermediate risk 1001 (21) High risk 219 (5) Surgical approach Open or unspecified 1370 (29) Minimally invasive 564 (12) Minimally invasive → open 71 (2) Unknown surgical approach 2674 (57) Grade Well differentiated 190 (4) Moderately differentiated 1608 (34) Poorly differentiated 2160 (46) Undifferentiated 74 (2) Unknown grade 647 (14) Tumor size <3 949 (20) 3–4.9 1030 (22) 5+ 1406 (30) Unknown size 1294 (28) Lymphovascular invasion Not present 1354 (29) Present 336 (7) Not applicable 38 (1) Unknown 2951 (63) T pathologic group T1 851 (18) T2 959 (20) T3 1887 (40) T4 56 (1) T0/Tis 694 (15) TX 232 (5) N pathologic group N− 2771 (59) N+ 1908 (41) Examined nodes 0–7 1271 (27) 8–12 1102 (24) 13–18 1066 (23) 19–83 1089 (23) Unknown # nodes 151 (3) Stage I 842 (18) II 2097 (45) III 1740 (37) Surgical margins Negative 4326 (92) Positive 279 (6) Margins unknown/not applicable 74 (2) All N = 4679 N (%) Age Median (IQR+) 62 (55–68) Adjuvant chemotherapy No 4306 (92) Yes 373 (8) Distance to hospital <6 miles 969 (21) 6–15 miles 1107 (24) 15.1–44 miles 1356 (29) >44 miles 1247 (27) Sex Male 4217 (90) Female 462 (10) Hospital type Comprehensive 1479 (32) Academic/research 2583 (55) Community 254 (5) Integrated network 264 (6) Not given for age <40 89 (2) Other or unknown 10 (0) Primary insurance Private insurance 2551 (55) Medicaid 224 (5) Medicare 1742 (37) Not insured 110 (2) Insurance status unknown 52 (1) Reporting sources Single facility NCDB report 3149 (67) Multiple 1530 (33) Income quartiles <$30,000 429 (9) $30,000–$35,999 827 (18) $36,000–$45,999 1353 (29) $46,000+ 1899 (41) Not available 171 (4) High school non-Graduate rate quartiles Q1 > = 29% 499 (11) Q2 20–28.9% 1089 (23) Q3 14–19.9% 1220 (26) Q4 < 14% 1700 (36) Not available 171 (4) Urban/rural Metro > 1 million 1932 (41) Metro 250,000–1 million 974 (21) Metro < 250,000 566 (12) Urban > 20,000 394 (8) Urban/rural < 20,000 646 (14) Unknown 167 (4) Age group 21–55 1239 (26) 56–62 1261 (27) 63–68 1158 (25) 69–89 1021 (22) Diagnosis time period 2006–2008 1601 (34) 2009–2011 2169 (46) 2012–2013 909 (19) Race/ethnicity White 4499 (96) Black 74 (2) Hispanic white 86 (2) Asian/Pacific islanders 20 (0) Charlson index group Low risk 3459 (74) Intermediate risk 1001 (21) High risk 219 (5) Surgical approach Open or unspecified 1370 (29) Minimally invasive 564 (12) Minimally invasive → open 71 (2) Unknown surgical approach 2674 (57) Grade Well differentiated 190 (4) Moderately differentiated 1608 (34) Poorly differentiated 2160 (46) Undifferentiated 74 (2) Unknown grade 647 (14) Tumor size <3 949 (20) 3–4.9 1030 (22) 5+ 1406 (30) Unknown size 1294 (28) Lymphovascular invasion Not present 1354 (29) Present 336 (7) Not applicable 38 (1) Unknown 2951 (63) T pathologic group T1 851 (18) T2 959 (20) T3 1887 (40) T4 56 (1) T0/Tis 694 (15) TX 232 (5) N pathologic group N− 2771 (59) N+ 1908 (41) Examined nodes 0–7 1271 (27) 8–12 1102 (24) 13–18 1066 (23) 19–83 1089 (23) Unknown # nodes 151 (3) Stage I 842 (18) II 2097 (45) III 1740 (37) Surgical margins Negative 4326 (92) Positive 279 (6) Margins unknown/not applicable 74 (2) IQR, interquartile range; NCDB, National Cancer Database. View Large On multivariate analysis, pathologic characteristics associated with decreased overall survival included stage, lymphovascular invasion, and positive surgical margins (Fig. 1). Insurance status, age, and comorbidity index were also associated with decreased survival. We found that patients who received additional adjuvant chemotherapy had a trend toward improved overall survival (HR 0.87, CI 0.76–1.01, P = 0.0636). Treatment at an academic/research hospital, as well as greater lymph node yields, was associated with improved overall survival. Compared to private insurance, Medicare (HR 1.17, CI 1.04–1.31, P = 0.0082), Medicaid (HR 1.45, CI 1.22–1.73, P < 0.0001), or having no insurance (HR 1.50, CI 1.17–1.92, P = 0.0012) were all negative predictors of overall survival. Patients who received adjuvant chemotherapy were more likely to have private insurance (69 vs. 53%, P < 0.0001). Fig. 1 View largeDownload slide Multivariate hazard ratios and 95% confidence intervals, overall cohort. *Hospital type is not reported routinely in this national database for patients under the age of 40 in an effort to protect confidentiality. While this subgroup is not shown in this Figure, it was included in the analysis. Fig. 1 View largeDownload slide Multivariate hazard ratios and 95% confidence intervals, overall cohort. *Hospital type is not reported routinely in this national database for patients under the age of 40 in an effort to protect confidentiality. While this subgroup is not shown in this Figure, it was included in the analysis. On final pathology, 1908 (41%) patients had node-positive disease. In the node-positive subgroup, patients who underwent adjuvant chemotherapy had improved survival (HR 0.74, CI 0.63–0.88, P = 0.0005) (Fig. 2), whereas adjuvant chemotherapy was not associated with improved survival in the node-negative subgroup. Compared to private insurance, Medicaid (HR 1.40, CI 1.09–1.80, P = 0.0081) or having no insurance (HR 1.71, CI 1.24–2.35, P = 0.0011) were negative predictors of overall survival in node-positive patients. Median overall survival in patients with node-positive disease who received adjuvant chemotherapy was 30.9 months, in contrast to 23.1 months in patients who did not (log-rank p-value, 0.0001), shown in Figure 3. Fig. 2 View largeDownload slide Multivariate hazard ratios and 95% confidence intervals, Node-positive cohort. *Hospital type is not reported routinely in this national database for patients under the age of 40 in an effort to protect confidentiality. While this subgroup is not shown in this Figure, it was included in the analysis. Fig. 2 View largeDownload slide Multivariate hazard ratios and 95% confidence intervals, Node-positive cohort. *Hospital type is not reported routinely in this national database for patients under the age of 40 in an effort to protect confidentiality. While this subgroup is not shown in this Figure, it was included in the analysis. Fig. 3 View largeDownload slide Overall survival probability stratified by adjuvant chemotherapy, node-positive patients. Fig. 3 View largeDownload slide Overall survival probability stratified by adjuvant chemotherapy, node-positive patients. DISCUSSION Significant disparities in esophageal cancer outcomes are known.4,5 Previous research has found that much of the disparities in outcomes is attributable to differences in treatment, with non-White patients and lower socioeconomic status patients less likely to receive surgery.4 In this study, we found that certain socioeconomic factors such as insurance status and rural setting continued to be associated with survival even among patients who all received standard of care, trimodality therapy. These socioeconomic factors are often associated with comorbidities, but in our multivariate analysis, each was independently associated with survival. Many of the significant sociodemographic factors were related to access to tertiary care (insurance status, hospital type, location). In fact, insurance status was a stronger predictor of survival than many other factors, including the use of adjuvant chemotherapy. This leads us to wonder: Why do sociodemographic disparities persist? Why may outcomes be different when patients with different social determinants of health receive the same treatment? Perhaps these findings highlight the notion that medical care in patients with esophageal cancer or other malignancies does not simply end after receiving the indexed treatment, and that surveillance in itself is equally important in the care of these patients. For example, in other malignancies, adherence to posttreatment surveillance has been shown to be associated with improved overall survival.11 Currently, NCCN guidelines recommend the following as part of surveillance: history and physical examinations every 3–6 months for 1–2 years, every 6–12 months for 3–5 years, and annually thereafter, with laboratory testing and imaging as indicated and stratified by pathologic staging.12 Patients undergoing esophagectomy may also be a patient population with unique long-term needs. Studies have found that although overall long-term quality of life is similar to the general populations, certain symptoms, such as aspiration, persist after esophagectomy.13 There are also emerging data regarding the impact of social determinants of health on life expectancy beyond just treatment disparities.14 Another interesting finding was the impact of adjuvant chemotherapy on survival. Although not part of NCCN guidelines, 8% of patients in this study received adjuvant chemotherapy. Similar to a recent publication by Burt et al., we found that adjuvant chemotherapy was associated with a lower risk of death in patients with residual nodal disease (ypTanyN+), but not among all patients.8 It is unclear why these patients were offered adjuvant therapy, but it does not appear to be random. Patients were much more likely to be given adjuvant chemotherapy if they had node-positive disease. As such, limitations of this study include its retrospective, observational design. Inherent to this is selection bias, as we do not have information on why or why not adjuvant chemotherapy was administered. Unfortunately, the NCDB does not have data on perioperative morbidity or details on chemotherapy and radiation regimens/techniques, both of which could potentially significantly impact decision-making. Not all data with regards to all variables were available, as indicated by some categories of ‘unknown’ or ‘absence of data.’ For example, hospital type is not recorded for patients under the age of 40 due to an effort to maintain confidentiality in accordance with national regulations. Finally, the NCDB does not incorporate data from all hospitals in the United States, and thus perhaps this patient population may not be truly representative of outcomes and practices nationwide. In conclusion, we found that in patients with esophageal adenocarcinoma who have undergone trimodality therapy, a number of different factors are associated with survival: biology of the disease, health of the patient, access to care, and adjuvant chemotherapy. Characteristics such as advanced pathologic stage, positive margins, octogenarians, and patients with comorbidities are, as expected, associated with decreased survival. However, sociodemographic factors relating to access to care are also important predictors of survival. Despite receiving the standard of care, treatment disparities persist in this population of patients. Notes Conflicts of Interest and Source of Funding: The authors have no conflicts of interest. No funding was obtained for this study. Dan J. Raz, MD, is a consultant for Cireca, LLC and has grant funding from Merck. The data used in the study are derived from a de-identified 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 investigators. The NCDB is a joint project of the Commission on Cancer of the American College of Surgeons and the American Cancer Society. This work was presented at the 2017 Gastrointestinal Cancers Symposium of the American Society of Clinical Oncology in San Francisco, CA. Specific author contributions: Conception/design: Oliver S. Eng, Rebecca A. Nelson, Jae Y. Kim; Data analysis/acquisition: Oliver S. Eng, Rebecca A. Nelson; Data interpretation: Oliver S. Eng, Rebecca A. Nelson, Ioannis Konstantinidis, Joseph Chao, Loretta Erhunmwunsee, Dan J. Raz, Jae Y. Kim; Drafting: Oliver S. Eng, Jae Y. Kim; Critical revision: Ioannis Konstantinidis, Joseph Chao, Loretta Erhunmwunsee, Dan J. Raz, Jae Y. Kim; Final approval for publication: Oliver S. Eng, Rebecca A. Nelson, Ioannis Konstantinidis, Joseph Chao, Loretta Erhunmwunsee, Dan J. Raz, Jae Y. Kim; Accountability agreement: Oliver S. Eng, Rebecca A. Nelson, Ioannis Konstantinidis, Joseph Chao, Loretta Erhunmwunsee, Dan J. Raz, Jae Y. Kim. References 1 Siegel R L , Miller K D , Jemal A . Cancer statistics, 2016 . CA Cancer J Clin 2016 ; 66 : 7 – 30 . Google Scholar Crossref Search ADS PubMed 2 Shapiro J , van Lanschot J J , Hulshof M C et al. Neoadjuvant chemoradiotherapy plus surgery versus surgery alone for oesophageal or junctional cancer (CROSS): long-term results of a randomised controlled trial . Lancet Oncol 2015 ; 16 : 1090 – 8 . Google Scholar Crossref Search ADS PubMed 3 Ajani J A , D’Amico T A , Almhanna K et al. Esophageal and esophagogastric junction cancers, version 1.2015 . J Natl Compr Canc Netw 2015 ; 13 : 194 – 227 . Google Scholar Crossref Search ADS PubMed 4 Revels S L , Morris A M , Reddy R M , Akateh C , Wong S L . Racial disparities in esophageal cancer outcomes . Ann Surg Oncol 2013 : 20 ; 1136 – 41 . doi:10.1245/s10434-012-2807-3 . Google Scholar Crossref Search ADS PubMed 5 Merkow R P , Bilimoria K Y , McCarter M D , Chow W B , Ko C Y , Bentrem D J . Use of multimodality neoadjuvant therapy for esophageal cancer in the United States: assessment of 987 hospitals . Ann Surg Oncol 2012 ; 19 : 357 – 64 . Google Scholar Crossref Search ADS PubMed 6 Markt S C , Lago-Hernandez C A , Miller R E et al. Insurance status and disparities in disease presentation, treatment, and outcomes for men with germ cell tumors . Cancer 2016 ; 122 : 3127 – 35 . Google Scholar Crossref Search ADS PubMed 7 Rong X , Yang W , Garzon-Muvdi T et al. Influence of insurance status on survival of adults with glioblastoma multiforme: a population-based study . Cancer 2016 ; 122 : 3157 – 65 . Google Scholar Crossref Search ADS PubMed 8 Burt B M , Groth S S , Sada Y H et al. Utility of Adjuvant chemotherapy after neoadjuvant chemoradiation and esophagectomy for esophageal cancer . Ann Surg 2017 ; 266 : 297 – 304 . Google Scholar Crossref Search ADS PubMed 9 Lin C C , Bruinooge S S , Kirkwood M K et al. Association between geographic access to cancer care, insurance, and receipt of chemotherapy: geographic distribution of oncologists and travel distance . J Clin Oncol 2015 ; 33 : 3177 – 85 . Google Scholar Crossref Search ADS PubMed 10 Commission on Cancer: About Program Categories . https://www.facs.org/quality-programs/cancer/coc/apply/categories. Accessed August 1 , 2018 . 11 Deutschmann M W , Sykes K J , Harbison J , Cabrera-Muffly C , Shnayder Y . The impact of compliance in posttreatment surveillance in head and neck squamous cell carcinoma . JAMA Otolaryngol Head Neck Surg 2015 ; 141 : 519 – 25 . Google Scholar Crossref Search ADS PubMed 12 NCCN Guidelines® & Clinical Resources . https://www.nccn.org/professionals/physician_gls/default.aspx. Accessed August 1 , 2018 . 13 Derogar M , Lagergren P . Health-related quality of life among 5-year survivors of esophageal cancer surgery: a prospective population-based study . J Clin Oncol 2012 ; 30 : 413 – 8 . Google Scholar Crossref Search ADS PubMed 14 Djarv T , Lagergren P . Six-month postoperative quality of life predicts long-term survival after oesophageal cancer surgery . Eur J Cancer 2011 ; 47 : 530 – 5 . Google Scholar Crossref Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press on behalf of International Society for Diseases of the Esophagus. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Journal

Diseases of the EsophagusOxford University Press

Published: Sep 1, 2018

References

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