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Journal of Clinical Oncology, Vol 25, No 17 (June 10), 2007: pp. 2389-2396 © 2007 American Society of Clinical Oncology. DOI: 10.1200/JCO.2006.09.7931 Referral Patterns, Treatment Choices, and Outcomes in Locoregional Esophageal Cancer: A Population-Based Analysis of Elderly Patients
From the Center for Medical Decision Making, Department of Public Health, Erasmus MC, Rotterdam, the Netherlands; and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA Address reprint requests to Ewout W. Steyerberg, PhD, Department of Public Health, Erasmus MC, PO Box 2040, 3000 CA Rotterdam, the Netherlands; e-mail: E.Steyerberg{at}ErasmusMC.nl
Purpose: To determine the impact of demographics and comorbidity on access to specialists' services, treatment, and outcome for patients with locoregional esophageal cancer. Patients and Methods: We performed a retrospective cohort study of 3,538 patients older than age 65 years who were diagnosed with locoregional esophageal cancer between 1991 and 1999 in one of 11 regions monitored by the Surveillance, Epidemiology, and End Results tumor program. We examined linked Medicare claims for assessment by a surgeon, radiation oncologist, or medical oncologist and subsequent treatment with surgery, radiation, or chemotherapy. Logistic regression analyses were performed for seeing a specialist and for undergoing treatment according to age, sex, race, socioeconomic status, geographic region, and presence of comorbidities. Cox proportional hazards analyses were performed to estimate hazard ratios (HRs) for survival with and without adjustment for treatment received. Results: Seeing a cancer specialist depended especially on age and region of diagnosis. These same factors were also related to subsequent treatment decisions, but associations were reversed in some regions, such that treatment depended less on region. Older patients had poorer survival (HR = 2.0 for 85+ v 65 to 69 years), which was partly explained by treatment received (HR decreased to 1.5 when adjusted for treatment). Conclusion: Older patients have less intensive treatment of esophageal cancer, which is explained by both a lower rate of seeing a cancer specialist and by less intensive treatment once seen. Referring physicians and treating specialists must ensure that elderly patients are not deprived of the opportunity to consider all of their treatment options.
Annually, approximately 400,000 people are diagnosed with esophageal cancer worldwide, and more than 350,000 people die of this malignancy. This makes esophageal cancer the eighth most common cancer and the sixth most common cause of cancer mortality.1 The prognosis of esophageal cancer is poor, with 5-year survival rates of less than 10%.2,3 Surgical resection is the treatment of choice when the aim is to cure locoregional disease.4 Additional treatments may improve the prognosis, especially the combination of chemotherapy and radiotherapy before surgery (neoadjuvant chemoradiotherapy).5-8 Disparities have been noted in many cancers with respect to the use of cancer-directed treatments. Patterns of care may differ by medically relevant characteristics, such as age and the presence of comorbidity, and also by nonmedical characteristics, such as geographic region, socioeconomic status (SES), sex, and race.9-16 These differences in treatment have been shown to account for differences in survival.17-21 The extent of variation in treatment and outcome is not well known for esophageal cancer patients, and the mechanisms underlying the selective use of cancer-directed treatment are still poorly understood. Additional insight may be obtained by studying receipt of treatment as a two-step process that involves referral to a specialist and treatment of referred patients.22 Therefore, we undertook a population-based study of locoregional esophageal cancer patients to evaluate disparities in the rates of referral to a specialist (surgeon, radiation oncologist, or medical oncologist) and undergoing treatment (surgery, radiotherapy, or chemotherapy). Furthermore, we evaluated the impact of these disparities on survival.
Patients We studied patients included in the linked Surveillance, Epidemiology, and End Results (SEER)–Medicare database diagnosed between January 1, 1991 and December 31, 1999.23 The SEER registry covers approximately 14% of the US population24 and has been linked to the Centers for Medicare and Medicaid Services Medicare claims through the end of 2001, as well as to census tract level SES information. We identified patients diagnosed with pathologically confirmed locoregional esophageal cancer, as described previously.25,26 We excluded patients for whom the date of death differed by more than 3 months between the SEER and Medicare databases, patients who were diagnosed from death certificate or autopsy, and patients for whom the month of diagnosis was not available. We also excluded patients who were only eligible for Medicare on the basis of end-stage renal failure or disability; therefore, all patients were 65 years or older. We considered combinations of surgery, radiation, and chemotherapy. Surgery was identified from the Medicare database only, using the International Classification of Diseases, ninth revision (codes 42.0 to 43.99).27 Information on radiation use was based on SEER records and Medicare data.28 Information on chemotherapy was based on Medicare data only.29 Treatment was classified as supportive care only (ie, no cancer-directed treatment within 8 months after diagnosis), radiotherapy, chemotherapy, or chemoradiotherapy (sequential or concurrent receipt of chemotherapy and radiotherapy). Patients who underwent surgery were further subclassified as having had surgery (including patients who received surgery alone, surgery and any adjuvant treatment, or surgery and neoadjuvant radiotherapy) or surgery and neoadjuvant chemotherapy or chemoradiotherapy (including patients who underwent surgery and received preoperative chemotherapy or sequential or concurrent chemoradiotherapy).5-7,30 Comorbidity was determined based on Medicare claims between 13 months and 1 month before diagnosis.31 Missing values were assigned to patients without Medicare data from this time window if no comorbidity was registered. Missing values were statistically imputed to allow for analysis of the available information from other predictors.25,32 Exclusion of these patients in a sensitivity analysis did not affect results (data not shown). International Classification of Diseases, ninth revision codes of both inpatient and outpatient bills were analyzed.33,34 Comorbidities were combined in the Charlson score33,35 and grouped as cardiovascular (previous myocardial infarction, heart failure, peripheral arterial disease, or cerebrovascular disease), diabetes (with or without complications), or pulmonary comorbidity (chronic obstructive pulmonary disease).36-38 Renal and hepatic comorbidities were too rare to perform analyses. Demographic characteristics included age at diagnosis, sex, race (white, black, or other), census region (West, Midwest, Northeast, or South), and SES. SES was determined using the median income in the patient's census tract of residence using year 2000 data. If this information was missing, we used the zip code median income; if this was missing, we used the census tract per capita income; if that was missing, then we used the zip code per capita income. If all of this information was missing, the patient was classified in the lowest SES quintile.39 Cancer characteristics included histology (adenocarcinoma or squamous, mixed, or other carcinoma) and stage of disease (categorized as local v regional according to SEER classification). Stage migration could have occurred for patients undergoing surgery. To minimize this bias, we considered all surgical patients as having, at most, regional disease.40
Statistical Analysis Survival curves were constructed using the Kaplan-Meier method. We used Cox proportional hazards regression to study the effects of patient characteristics on survival, expressed as hazard ratios (HRs). Multivariable analyses first included the characteristics listed earlier and were then extended with a variable for treatment received. Hence, we studied the extent to which differences in survival might be explained by treatment received. We used statistical interaction terms to study whether the association between patient characteristics and survival differed by type of treatment. We used Nagelkerke's R2 to compare the impact of the different patient characteristics. This measure is analogous to the explained variation for linear models. It is calculated at the log likelihood scale both for logistic and Cox models.41 We compared the R2 of multivariable models with and without the characteristic to calculate partial R2 statistics. These partial R2 statistics reflect the additional impact of a characteristic to a model that already contained the other characteristics. We provide the total R2 values of models including all characteristics to place the partial R2 values in perspective. Analyses were performed with SAS version 8 (SAS Institute, Cary, NC), SPSS version 11 (SPSS Inc, Chicago, IL), and S-Plus version 6 (Insightful Inc, Seattle, WA). We present 95% CIs for unadjusted and adjusted ORs and HRs, which do not include the value 1 if statistically significant.
Patient Characteristics We studied 3,538 patients with locoregional esophageal cancer (Table 1). Patients were, on average, 75 years of age and predominantly of white race (83%), male (70%), and of lower SES. Comorbidity was present in 29% of patients (Charlson score > 0), including predominantly cardiovascular disease, pulmonary disease, and diabetes. The tumor histology was squamous cell carcinoma in 52% of patients.
Correlations between characteristics were generally low (correlation coefficients, r < 0.3). Males were 2 years younger than females (74.3 v 76.6 years; r = 0.16) and had a slightly higher SES (average, 3.0 v 2.8; r = 0.23). A lower SES was found among blacks compared with other races (mean, 1.7 v 3.0; r = 0.28). Males and white patients were more likely to have adenocarcinoma (r = 0.25 and r = 0.30, respectively). Comorbidity was only weakly associated with increasing age (r = 0.03).
Referral and Treatment Younger patients were far more likely to undergo surgery, with rates of 55% for patients between 65 and 70 years old compared with only 23% for patients older than 85 years of age. This treatment pattern was partly attributable to a lower rate of being seen by a surgeon, which declined from approximately 80% for patients between 65 and 75 years old to 61% for patients older than 85 years of age (Table 2). Moreover, elderly patients had a lower rate of surgery among those seen by a surgeon compared with younger patients (rates declined from 67% to 38%, respectively). In multivariable analyses, a 10-year younger age was associated with a 2.1-fold higher likelihood of undergoing surgery, a 1.8-fold higher likelihood of being seen by a surgeon, and a two-fold higher likelihood of undergoing surgery once seen (Table 3). Age had no association with seeing a radiation oncologist or undergoing radiotherapy. However, younger patients were much more likely to receive chemotherapy (45% of patients between 65 and 75 years v 20% of patients older than 85 years; Table 2). The multivariable OR was 1.67 per 10 years younger (Table 3). This pattern was explained both by a greater likelihood of being seen by a medical oncologist (OR = 1.47) and by more subsequent treatment among younger patients seen by a medical oncologist (OR = 1.59, Table 3). Figure 1 illustrates these relationships.
Males underwent surgery more often than females (47% v 35%, respectively), but this association was largely attributable to other characteristics, such as the younger age of males (adjusted OR close to 1, Table 3). Sex was not associated with receiving radiotherapy or chemotherapy. Substantial racial disparities were found for surgery rates (black patients, 25%; white patients, 46%) but not for radiotherapy or chemotherapy rates. Multivariable analyses showed statistically significant disparities for all three treatments considered. For surgery and chemotherapy, disparities occurred both in seeing the relevant provider and for subsequently receiving treatment (OR of approximately 0.6 for black v white patients). For radiotherapy, the main disparities appeared at the step of seeing a radiation oncologist. A lower SES was associated with lower rates of surgery (Table 2). However, this effect disappeared in multivariable analyses because of the correlation with race (ORs close to 1, Table 3). Remarkable regional differences were noted, especially in being seen by a surgeon (Fig 1). Patients in the Midwest or Northeast were more often seen by a surgeon (86% and 82%, respectively) than patients in the West or the South (both 70%, Table 2). These differences remained important in multivariable analyses (Table 3). However, relatively few of the patients seen by a surgeon underwent surgery in the Midwest (OR = 0.70, Table 3). Therefore, patients in the Midwest were overall only slightly more likely to undergo surgery (OR = 1.10, Table 3). However, patients in the Midwest were more likely to receive radiotherapy and/or chemotherapy (OR = 1.35 and 1.51, respectively; Table 3). Patients in the Northeast were more likely to undergo surgery (OR = 1.76, Table 3). Patients in the Northeast were more likely to see a surgeon (OR = 2.03) and had slightly higher rates of surgery among those seen (OR = 1.35, Table 3). Patients in the West and South were rather similar in treatment patterns. Although they were actually more likely to be seen by a surgeon, patients with comorbidity were less likely to subsequently have surgery. Patients with comorbidity were more likely to receive radiotherapy and chemotherapy (Tables 2 and 3).
Survival The relative importance of most factors decreased when we adjusted for treatment received (Fig 2). For age, the estimated median survival time was 310 days for patients between 65 and 69 years of age and 200 days for patients aged 85 years and older when adjusted for treatment (Appendix Fig A2, online only). The HR for age 85+ versus 65 to 69 years decreased from 2.0 to 1.5 (95% CI, 1.3 to 1.7). Less intensive treatment (surgery, radiotherapy, or chemotherapy) explained a substantial part, but not all, of the age differences in survival. In our analyses, we assumed a similar effect of treatments across age groups. This was supported by a nonsignificant interaction between age and treatment.
A small sex disparity was noted in multivariable analyses, with worse survival for males. This disparity remained when analyses were adjusted for treatment received (Table 4). In contrast, racial disparities in survival could largely be attributed to differences in treatment received. SES and region were not relevant for survival. Patients with a Charlson comorbidity score of  2 had a poorer survival (Appendix Fig A1), which was not explained by correlations with other characteristics or treatment (adjusted HR > 1, Table 4).
We found several striking differences in treatment and survival according to various characteristics of patients with locoregional esophageal cancer. Differences in treatment patterns were especially noted for age, race, geographical region, and comorbidity. Survival depended on age and, to a lesser extent, on sex and comorbidity. Older patients were less likely to be seen by a surgeon or medical oncologist, and if seen, they were less likely to undergo surgery or chemotherapy, respectively. For example, only 23% of patients older than 85 years underwent surgery compared with 55% of patients less than 70 years old. Neither medically relevant factors, such as comorbidity or tumor histology, nor nonmedical factors, such as ecologic SES or geographic region, could explain these differences. Survival was worse for older patients, which was, for a substantial part, explained by treatment received. The remaining impact of age, independent of treatment, may reflect biologic frailty. Sex disparities in treatment were relatively small. Males had a slightly poorer survival than females after adjustment for other patient characteristics, with or without treatment received, in line with previous studies.42,43 Important disparities in treatment were noted for race. Black patients were less likely to be seen by a surgeon or medical oncologist, and if seen, they were less likely to undergo surgery or chemotherapy, respectively. However, the impact of race on treatment pattern was much smaller than for age. An important finding was that the racial disparity in survival was largely explained by treatment received. Hence, race was not a determinant of survival per se, and a similar survival should be expected if similar treatment is received. Indeed, we have previously reported that, among patients undergoing surgery for esophageal cancer, race had no effect on survival (black v white patients: HR = 1.05; 95% CI, 0.82 to 1.35).25 Another pattern of treatment disparities was found according to region of diagnosis, which is in line with studies of other diseases, such as prostate cancer.44 In some regions (eg, the Midwest), patients were more likely to be seen by a surgeon or medical oncologist, but this liberal referral was partly compensated by less treatment once seen. Hence, regional differences in treatment were smaller than expected from referral patterns (Fig 1). The referral disparities may reflect differences in access to care across the SEER regions, possibly related to organizational aspects. The patient characteristics in our study could not explain the disparities, which remained relevant in multivariable analyses. Regional differences in survival were small and largely explained by treatment received. Some referral patterns and treatment choices may well be justified from a medical perspective.45 For example, it is well known that 30-day mortality increases with age for many surgical procedures46 and with presence of comorbidity.26 Similarly, complications of chemotherapy may be more frequent in older patients and in those with comorbidity.47 Comorbidity was also associated with more referral but less intensive treatment once seen (especially more radiotherapy). Comorbidity and age had small effects on survival, independent of treatment received. Our analyses have some limitations. We only considered patients older than age 65 years because we required Medicare claims to determine treatment and the presence of comorbidities. An advantage of this selection is that all patients had Medicare coverage, so there should not have been insurance-related barriers to accessing care. Also, the impact of age would likely have been even larger if a wider range would have been studied. The observational nature of the data precludes firm conclusions about the impact of patient characteristics on treatment and outcome. The data do not capture all medical factors relevant to deciding, for example, whether a patient is a surgical candidate, such as performance status. SES was measured at the census tract level instead of at the individual level. Hence, the observed age and racial differences may still partly reflect socioeconomic differences, even after adjustment for ecologic SES. Similarly, we were only able to capture comorbidities serious enough to result in the use of medical services before diagnosis, which likely underestimates the true presence of coexistent illnesses.37 Regional differences were studied at an aggregated level, possibly obscuring differences between smaller regions. Referral patterns and treatment choices may also simply reflect patient preferences. Finally, we relied on statistical modeling to adjust for various confounding factors and for treatment received, but these models can only approximate underlying patterns. In conclusion, treatment of patients with locoregional esophageal cancer depends on several patient characteristics, especially age, race, geographical region, and comorbidity. Some determinants, such as region and comorbidity, have differential effects on referral and treatment decisions once seen by a specialist. Although age-related treatment disparities explained a large part of age-related survival differences, age had a small independent impact on survival. Other characteristics, such as race, were only associated with survival through treatment received. Referring physicians and treating specialists must ensure that biases and barriers to care do not deprive certain patient groups, such as the elderly and black patients, of the opportunity to consider all of their treatment options.
The author(s) indicated no potential conflicts of interest.
Conception and design: Ewout W. Steyerberg, Jane C. Weeks, Craig C. Earle Financial support: Jane C. Weeks Collection and assembly of data: Bridget Neville, Craig C. Earle Data analysis and interpretation: Bridget Neville, Jane C. Weeks, Craig C. Earle Manuscript writing: Ewout W. Steyerberg, Bridget Neville, Craig C. Earle Final approval of manuscript: Ewout W. Steyerberg, Bridget Neville, Jane C. Weeks, Craig C. Earle
We thank Valery E.P.P. Lemmens, epidemiologist in Rotterdam and Eindhoven, and an anonymous reviewer for helpful and valuable comments to improve this article.
Supported by a Marx Family Fellowship from Dana-Farber/Harvard Cancer Center (E.W.S.). Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
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Copyright © 2007 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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ABSTRACT
INTRODUCTION
