Influence of private practice setting and physician characteristics on the use of breast cancer adjuvant chemotherapy for elderly women


  • Dawn L. Hershman MD, MS,

    Corresponding author
    1. Department of Medicine and the Herbert Irving Comprehensive Cancer Center, College of Physicians and Surgeons, Columbia University, New York, New York
    2. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
    • Division of Medical Oncology, Herbert Irving Comprehensive Cancer Center, Columbia Presbyterian Hospital, 161 Fort Washington Avenue, Room 1068, New York, NY 10032===

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    • Fax: (212) 305-0178

  • Donna Buono MS,

    1. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
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  • Russell B. McBride MPH,

    1. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
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  • Wei Yann Tsai PhD,

    1. Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York
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  • Alfred I. Neugut MD, PhD

    1. Department of Medicine and the Herbert Irving Comprehensive Cancer Center, College of Physicians and Surgeons, Columbia University, New York, New York
    2. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
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  • This study used the linked Surveillance, Epidemiology, and End Results (SEER)-Medicare database. We acknowledge the efforts of the Applied Research Branch, Division of Cancer Prevention and Population Sciences, National Cancer Institute; the Office of Information Services and the Office of Strategic Planning, Health Care Financing Administration; Information Management Services, Inc; and the SEER Program tumor registries in the creation of the SEER-Medicare database.

  • This article is US Government work and, as such, is in the public domain in the United States of America.



Although >70% of younger women with nonmetastatic breast cancer (BC) received adjuvant chemotherapy, only approximately 15% to 20% of elderly women with BC received chemotherapy. The decision to treat may be associated with nonmedical factors, such as patient, physician, or practice characteristics. In the current study, the association between oncologist characteristics and the receipt of chemotherapy in elderly women with BC was evaluated.


Women aged >65 years who were diagnosed with American Joint Committee on Cancer stages I to III BC between 1991 and 2002 were identified in the Surveillance, Epidemiology, and End Results-Medicare database. The Physician Unique Identification Number was linked to the American Medical Association Masterfile to obtain information on oncologists. Investigated was the association between demographic, tumor, and oncologist-related factors and the receipt of chemotherapy, using Generalized Estimating Equations to control for clustering. Patients were defined as low risk (estrogen/progesterone receptor positive, stage I/II disease) and high risk (estrogen/progesterone receptor-negative, stage II/III disease).


Of 42,544 women identified, 8714 (20%) were treated with adjuvant chemotherapy. In a hierarchical analysis, women who underwent chemotherapy were more likely be treated by oncologists primarily employed in a private practice (odds ratio [OR], 1.40; 95% confidence interval [95% CI], 1.23-1.59) and who graduated after 1975 (OR, 1.12; 95% CI, 1.01-1.26) and were less likely to have an oncologist trained in the United States (OR, 0.83; 95% CI, 0.74-0.93). The association between a private practice setting and the receipt of chemotherapy was found to be similar for patients at high risk (OR, 1.55) and low risk (OR, 1.35) for cancer recurrence.


Elderly women with BC treated by oncologists who were employed in a private practice were more likely to receive chemotherapy. Efforts to determine whether these associations reflected experience, practice setting, insurance type, or other economic incentives are warranted. Cancer 2009. Published 2009 by the American Cancer Society.

One of the most important advances of medical oncology over the past 30 years has been the gradual refinement through large-scale randomized trials of the use of adjuvant systemic therapy for breast cancer. Professional guidelines dating back to the late 1990s recommended that chemotherapy be considered for all women with invasive breast cancer, especially those with positive lymph nodes or estrogen receptor (ER)-negative tumors.1-3 These guidelines for chemotherapy use are related to the risk of disease recurrence. Assessment of risk has traditionally been based on the patient's menopausal status, tumor stage, and tumor characteristics. The use of chemotherapy for small, hormone receptor-positive cancers is less clear-cut and involves choices by the patient and physician and shared decision making.

The elderly are generally under-represented in clinical trials. Because of the uncertain benefit of chemotherapy, elderly women are less likely to receive adjuvant chemotherapy compared with younger women.4-8 Studies that used the linked Surveillance, Epidemiology, and End Results (SEER)-Medicare database have demonstrated an improvement in survival for some women aged >65 years with early stage breast cancer who were treated with chemotherapy.7-9 Although there were slight differences, overall the studies found an approximate 25% survival benefit for women with lymph node-positive, hormone receptor-negative cancers, after controlling for multiple confounding variables. The use of chemotherapy decreased with increasing age, black race, and increased comorbidity, and use increased with year of diagnosis, tumor size, number of positive lymph nodes, and higher tumor grade. No benefits were observed for patients with lymph node-negative disease or for patients with hormone receptor-positive cancers.7, 8 Because it is also now known that elderly patients treated on cooperative group clinical trials experience reductions in breast cancer mortality and recurrence similar to younger patients, the identification of modifiable factors that influence the undertreatment of high-risk and the overtreatment of low-risk elderly women is necessary.10

Research on the determinants of receipt of cancer treatment has focused for the most part on patient-related factors, such as race/ethnicity, geographic location, age, and socioeconomic status (SES). To our knowledge, relatively less research has evaluated the role of the physician and practice setting in the receipt of cancer care. In this study, we used the SEER-Medicare database to investigate the association between oncologist characteristics such as gender, type of degree, year of graduation, and practice setting (private vs nonprivate) and the receipt of adjuvant chemotherapy for elderly patients with early stage breast cancer. We determined patterns of use both in patients at high risk and those at low risk for a breast cancer recurrence.


Study Database

We used the SEER-Medicare linked database, which was codeveloped by the US National Cancer Institute and the Center for Medicare and Medicaid Services. The SEER Program represented roughly 14% of the US population in 1991, and since 2000, has represented approximately 26%. Medicare covers hospital services, physician services, some drug therapy, and other medical services for >97% of persons aged >65 years. The linked SEER-Medicare database contains clinical, demographic, and medical claims data on patients aged >65 years and is a unique population-based resource for longitudinal epidemiologic and health outcomes studies. Its characteristics and validation have been comprehensively reported elsewhere.11, 12

To obtain information on the characteristics of the physicians who treated the SEER-Medicare patients, we used the Unique Physician Identification Number (UPIN) to link the Medicare claims with the American Medical Association (AMA) Masterfile, as described elsewhere.13 This file contains data collected from physician members of the AMA, including gender, age, medical degree (Doctor of Medicine [MD] or Doctor of Osteopathy [DO]), location of medical school (United States vs foreign), year of graduation, employment setting (private vs nonprivate), and specialty.13 Physicians records are continuously updated and verified by the AMA.14

Patient Selection

We initially identified all female Medicare participants aged >65 years who were diagnosed with American Joint Committee on Cancer [AJCC] stage I to III breast cancer from January 1, 1991, through December 31, 2002, who had undergone either a lumpectomy or mastectomy within 90 days of diagnosis (n = 61,867). We then selected patients who underwent consultation with an oncologist within 1 year after diagnosis (n = 42,544). We used Medicare claims to identify patients who had initiated chemotherapy within 6 months after surgery. Women who were not members of a health maintenance organization (HMO) and had Medicare Parts A and B during the 12 months before their diagnosis and until death/censoring, and women who had a prior breast cancer or other cancer, end-stage renal disease, or a breast cancer diagnosis without histologic confirmation were excluded.

A subset of the patients were categorized according to the National Comprehensive Cancer Network (NCCN) guidelines. Patients were classified as having a high risk of disease recurrence if they had tumors that were estrogen and progesterone receptor negative and had stage II or III cancer (n = 2947). Patients with a low risk of disease recurrence were defined as hormone receptor positive and having stage I or II disease (n = 28,859).

Oncologist Characteristics

Oncologist characteristics that were analyzed based on the variables in the AMA Masterfile included gender, year of graduation (<1975 or ≥1975; approximately 50% cutpoint), primary employment setting (private vs other), location of training (United States vs other), and type of degree (MD or DO). Private primary employment setting was defined as self-employed solo, 2-physician, or group practice (practice codes: 011, 013, 021, and 030). Other employment settings included medical school, nongovernment hospital, and governmental hospital or Veterans Administration hospital. In our sample, only 6% of physicians had missing data for this category. Physician age was categorized by decade of birth. Physicians' patient volumes (ie, total number of claims for breast cancer patients in the database for 1992-2002) were dichotomized as 1 to 40 versus >40 patients. We defined high patient volume as an oncologist who consulted on >40 patients in the sample. We chose this cutoff because it represented the top 10% of the oncologists with regard to numbers of patients from this cohort who underwent chemotherapy treatment based on the distribution of consultations.

Measurement of Treatments and Outcomes

We identified and categorized patients with respect to the chemotherapy they received using the SEER-Medicare linked databases and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) procedure codes, Current Procedural Terminolgy-4 (CPT-4), Healthcare Common Procedure Coding System (HCPCS), and ICD-9-CM V codes. These codes have been found to capture virtually all breast cancer cases.15

We categorized patients as having had chemotherapy exposure in the Medicare files using codes for ICD-9-CM diagnosis, ICD-9-CM procedure code, CPT, HCPCS, and revenue center codes. We included codes v581, v662, v 672, E9331, E9307, 9925, Q0083, Q0084, Q0085, and CPT codes for the administration of chemotherapy 96,400 through 96,499 and 96,500 through 96,599 J9000 through J9999; diagnosis-related group code = 410 and revenue center codes = 0331, 0332, and 0335.

Socioeconomic Status of Patients

We generated an aggregate SES score based on education, poverty, and income data from the 2000 census track data, following the method adapted by Du et al.16 Patients were ranked on a scale of 1 to 5 scale, in which 1 was the lowest value, based on a formula incorporating these variables weighted equally. The 394 patients with missing data were assigned to the lowest SES category. The results did not change if they were assigned to a separate category. In the final analysis, the first and second rankings were combined.

Comorbid Disease

To assess the prevalence of comorbid disease in our cohort, we used the Klabunde adaptation of the Charlson comorbidity index.17, 18 Medicare inpatient and outpatient claims were searched for ICD-9-CM diagnostic codes. Each condition was weighted, and patients were assigned a score based on the Klabunde-Charlson index.18

Statistical Analysis

The chi-square test was used to compare oncologist-related, demographic, and clinical characteristics between patients who received chemotherapy and those who did not and between patients who consulted with an oncologist in private practice versus those who consulted with an oncologist in another practice setting. Univariate odds ratios (ORs) were calculated individually for each variable. All hypothesis tests were 2-sided.

The Generalized Estimating Equations (GEE) methodology was introduced by Zeger et al19 to deal with clustering in data that otherwise would be analyzed by means of a generalized linear model, and GEEs (PROC GENMOD in SAS statistical software [SAS Institute, Inc, Cary, NC]) have become an important strategy in the analysis of correlated data.19, 20 We used GEEs to account for the correlations of outcome measures among patients who had the same physician. The unit of analysis was the patient. For each patient, the physician's unique UPIN number was used as the clustering variable. The model assumptions were the data had a binomial distribution, the link function was logit, and the type of variance was exchangeable.

We evaluated the odds of chemotherapy for all the categories of each variable, controlling for all the other variables in the model. The model included the following: 1) oncologist characteristics (gender, type of degree, country of training, practice type, and patient volume); 2) patient demographic variables (age, race, place of residence, marital status, and SES); and 3) clinical variables (tumor grade, AJCC stage, hormone receptor status, and comorbidity score). We also performed separate analyses for the high-risk and low-risk recurrence groups. All statistical analyses were conducted using the SAS system for Windows (version 9.13).


We identified 42,544 women in the SEER-Medicare database who were diagnosed with stages I to IIII breast cancer during the study period and who met our eligibility criteria. A total of 2833 oncologists consulted on these patients. We defined 28,859 patients as being at low risk for recurrence, 4366 of whom (15%) received chemotherapy, whereas 2947 patients were defined as being of high risk, 1791 of whom (61%) received chemotherapy. Overall, 20% of women in the cohort received chemotherapy, with chemotherapy use increasing from 8% to 34% between 1992 and 2002. The oncologists who administered chemotherapy to these patients were predominantly male (80%), in private practice (72%), trained in the United States (72%), and holders of a medical degree (MD) (97%) as opposed to an osteopathic degree (DO). Only the number of female oncologists and the number of oncologists who graduated after 1975 was found to increase over time (Fig. 1).

Figure 1.

Change in oncologist characteristics between 1992 and 2002. Dr indicates doctor.

Table 1 reports the odds of the receipt of chemotherapy across individual demographic and clinical characteristics of the patients and the characteristics of the oncologists. Patients consulting with an oncologist who had primary employment in a private versus nonprivate practice, who was foreign trained as opposed to US trained, or who graduated after 1975 as opposed to before, were more likely to receive adjuvant chemotherapy. Oncologists in private practice were more likely to be male, have a larger patient panel, and have graduated before 1975 (Table 2).

Table 1. Unadjusted and Adjusted Associations Between Receipt of Chemotherapy Among Elderly Patients With Early Stage Breast Cancer, the Characteristics of Their Oncologists, and Their Own Demographic and Clinical Characteristics (N=42,544)*
CharacteristicsNo.%Odds Ratios (95% CI)Odds Ratios (95% CI)
  • 95% CI indicates 95% confidence interval; DO, Doctor of Osteopathy; MD, Doctor of Medicine; ER, estrogen receptor; +, positive; PR, progesterone receptor; −, negative.

  • *

    P < .001.

  • Odds ratios were based on univariate logistic regression.

Received chemotherapy871420.0  
Oncologist characteristics
  MD839020.41.01(0.90-1.15)0.87 (0.65-1.16)
  Yes660220.00.88 (0.83-0.93)*0.83 (0.74-0.93)*
 Date of graduation
  ≥1975499221.91.20 (1.15-1.26)*1.12 (1.01-1.26)*
 Type of practice
  Private735821.21.27 (1.19-1.36)*1.40 (1.23-1.60)*
 No. of patients in cohort
  >40403319.60.90 (0.86-0.94)*1.07 (0.93-1.23)
  Female150920.81.03 (0.96-1.09)0.99 (0.87-1.14)
Demographic characteristics
 Age at diagnosis, y
  70-74305224.20.61 (0.58-0.65)*0.53 (0.49-0.57)*
  75-79176216.20.37 (0.34-0.39)*0.27 (0.25-0.30)*
  ≥806396.70.14 (0.12-0.15)*0.07 (0.06-0.08)*
  Black56324.91.32 (1.19-1.45)*0.99 (0.86-1.15)
  Hispanic10922.11.13 (0.91-1.39)0.90 (0.69-1.18)
  Other34922.11.13 (0.99-1.27)1.01 (0.86-1.18)
  Metropolitan790320.50.99 (0.91-1.07)0.93 (0.82-1.06)
 Marital status
  Married458023.71.43 (1.36-1.50)*1.17 (1.10-1.24)*
 Socioeconomic status
  Lowest quartile259420.0ReferenceReference
  2nd quartile212020.41.03 (0.97-1.10)1.02 (0.93-1.12)
  3rd quartile187720.81.06 (0.99-1.13)1.07 (0.98-1.16)
  4th quartile206221.11.07 (1.01-1.16)*1.11 (1.01-1.22)*
Patient clinical characteristics
  II589934.26.96 (6.55-7.39)*8.43 (7.72-9.09)*
  III124946.311.57 (10.6-12.7)*17.68 (15.19-19.74)*
 Hormone receptor status
  ER+ and/or PR+508916.6ReferenceReference
  ER- and PR-238447.94.54 (4.26-4.83)*4.52 (4.13-4.93)*
  Well/moderately differentiated361515ReferenceReference
  Poorly differentiated411233.42.83 (2.69-2.99)*1.78 (1.67-1.90)*
  Unknown98715.81.06 (0.98-1.15)1.05 (0.94-1.16)
 Comorbidity score
  1213419.90.88 (0.84-0.94)*0.89 (0.83-0.95)*
  >195315.80.67 (0.62-0.72)*0.60 (0.55-0.66)*
Table 2. Characteristics of Oncologists in the Cohort Treating Women for Early Stage Breast Cancer in Private Practice, 1992 Through 2002 (N=2833)
Oncologist CharacteristicsNo.%No.%No.%P*
  • MD indicates Doctor of Medicine; DO, Doctor of Osteopathy.

  • *

    P value based on the chi-square test.

Year of graduation       
No. of patients in the cohort       

Controlling for known demographic and clinical confounders, a lower likelihood of receiving chemotherapy was observed among patients with a US-trained versus a non–US-trained oncologist (OR, 0.83; 95% confidence interval [95% CI], 0.74-0.93 [P = .001]), but a greater likelihood of receiving chemotherapy with an oncologist in private versus nonprivate practice was noted (OR, 1.40; 95% CI, 1.23-1.60; [P < .0001]) (Table 1). Receipt of chemotherapy was also associated with younger age at diagnosis, higher SES, less favorable tumor characteristics, more recent year of diagnosis, fewer comorbid conditions, and being married.

To evaluate patterns of care in patients at low risk and high risk for disease recurrence, we conducted separate GEE analyses of the association between oncologist practice and the receipt of chemotherapy among patients stratified into 2 groups by risk of disease recurrence (high risk and low risk) (Table 3). The association between primary practice type and use of chemotherapy was found to be similar for patients with a high risk (OR, 1.55) and those with a low risk (OR, 1.35) of disease recurrence.

Table 3. Multivariable* Analysis of Associations Between the Receipt of Chemotherapy and Demographic, Tumor, and Oncologist Characteristics Among Elderly Patients With High-Risk and Low-Risk Breast Cancer (N=37,806)
 High Recurrence RiskLow Recurrence Risk
CharacteristicsOdds Ratio95% CIOdds Ratio95% CI
  • High recurrence risk indicates estrogen and progesterone receptor negative, stage II to III disease (N=2947); low recurrence risk, estrogen and progesterone receptor positive, stage I to II disease (N=28,859); 95% CI, 95% confidence interval; DO, Doctor of Osteopathy; MD, Doctor of Medicine.

  • *

    Each variable was corrected for the other listed characteristics and year of diagnosis.

  • P value <.01.

Surgeon characteristics
 Type of practice
 No. of patients in practice
 Year of graduation
Patient demographic characteristics   
 Age at diagnosis, y
 Marital status
 Socioeconomic status
  Lowest quartile1.00Referent1.00Referent
  2nd quartile1.261.02-1.551.161.03-1.31
  3rd quartile1.220.98-1.541.241.11-1.40
  Highest quartile1.371.06-1.751.321.17-1.49
Patient clinical characteristics
  Well/moderately differentiated1.00Referent1.00Referent
  Poorly differentiated1.361.12-1.661.591.46-1.73
 Comorbidity score


In this population-based study of elderly women with early stage breast cancer, we found that the number of elderly women treated with adjuvant chemotherapy increased from 8% to 34% between 1992 and 2002, with 61% of high-risk patients and 15% of low-risk patients undergoing chemotherapy. The results of the current study demonstrate that patients treated by physicians who have their primary employment in a private practice are more likely to receive adjuvant chemotherapy for early stage breast cancer. This correlation holds both for patients with high and low risks of disease recurrence. In addition, we confirmed that, after controlling for physician characteristics, the clinical and demographic characteristics known to influence treatment also influenced adjuvant chemotherapy use in our model.

Research on the determinants of receipt of cancer treatment has focused for the most part on patient factors such as race/ethnicity, geographic location, age, and SES. In the current study, we also found that younger age, being married, and high SES were all associated with a greater likelihood of receiving chemotherapy. Although we found that black women were more likely to receive chemotherapy in the unadjusted analysis, the association disappeared in the adjusted analysis. This finding is consistent with other studies in this patient population.7 Conversely, to our knowledge relatively little research has evaluated the role of oncologist characteristics in cancer treatment decisions. Investigators have reported the composite influence of the physician's characteristics on the receipt of androgen–deprivation therapy for patients with prostate cancer21 and radiation after breast conservation surgery,22 as well as on referral to an oncologist after a diagnosis of colon23 or lung cancer.24 It is increasingly apparent that patients with similar demographic and clinical characteristics may be treated differently depending on the physician they consult.25, 26 To the best of our knowledge, no prior studies have investigated the influence of physician and practice setting.

We were surprised to observe the strong and consistent correlation between practice setting and chemotherapy use independent of physician characteristics, and were even more surprised to find that this association was similar both for patients with a clear indication due to high recurrence risk, as well as for those who were likely to have only minimal benefit. What might explain this association? One possibility may relate to patient volume, because the oncologists in private practice generally had a higher patient volume, which may then translate into a greater comfort level treating elderly patients. However, the association between panel size and chemotherapy use was weak and did not modify the association with practice setting. Another possibility is that it is related to patient selection factors. Patients may choose to see physicians for chemotherapy in private settings due to convenience, and patients with more complicated medical conditions may be treated at university hospitals and clinics in which they are less likely to receive chemotherapy; therefore, these results may be a product of selection bias. However, many of these biases are controlled for in the multivariate analysis. Another possibility is that it is related to patients' insurance status. Patients seen in a private practice setting are, in general, more likely to have private insurance and to be of higher SES. Although all of the patients in the current study cohort had Medicare coverage and were not covered under an HMO, physician practice patterns may be influenced by the type of patients in the overall practice. Research has shown that payment mechanisms influence physicians' clinical decision making,27 that physicians are more likely to recommend services for insured than for uninsured patients,28 and that salaried versus fee-for-service reimbursement influences physician behavior.29 In a survey of medical oncologists, the majority of physicians reported that out-of-pocket costs could influence chemotherapy decisions; however, only 30% reported that costs had actually influenced their treatment decisions.30 In another survey, only 16% of oncologists acknowledged omitting treatment options on the basis of their perceptions of a patient's ability to afford treatment.31

A less honorable possibility is that recommendations for chemotherapy are influenced by financial reimbursement and personal compensation that ensues from chemotherapy administration. An issue that has plagued oncology is the conflict of interest that ensues from the administration of chemotherapy drugs. Many practices buy chemotherapy drugs at discounted prices, and then administer these drugs in the office. Profit is generated from the difference between what is paid for the drug and what is charged to insurers and government programs. Some estimates indicate that oncologists in private practice make the bulk of their practice revenue from chemotherapy concessions.32 Although the majority of oncologists are motivated by patient desires, the potential for a conflict of interest in the system has raised concerns, and has resulted in proposals to regulate the reimbursement system.32

Patients also play a large role in the ultimate decision to undergo treatment with adjuvant chemotherapy. Acceptance of adjuvant chemotherapy by a woman with breast cancer occurs often after an assessment of risk and benefit, a process referred to as shared decision making. Although there are some patients with a low recurrence risk who are willing to accept a very small benefit despite the risk of treatment–related complications, there are others who clearly benefit due to the higher risk of disease recurrence and the NCCN guidelines recommend chemotherapy. A recent study found that only 45% of 4395 women with early stage breast cancer received treatment that was consistent with NCCN guidelines. The authors concluded that the reasons for low adherence to guidelines were multifactorial and included insufficient health system supports to clinicians, inadequate organization and delivery systems, and ineffective continuing medical education.33 Similarly, a recent study of 275 women with early stage breast cancer found that 16% of patients who should have received adjuvant chemotherapy did not.34 Studies have shown that chemotherapy use in the elderly decreases with increasing age, number of comorbid conditions, and favorable tumor characteristics.5

The current study has some weaknesses. The SEER-Medicare dataset that we used for these analyses does not include data regarding several variables that might have also been associated with the receipt of adjuvant chemotherapy, such as psychologic outlook, communication with the physician, or health behaviors, and specific contraindications, such as performance status. However, given the very large size of our sample, these unmeasured variables are often correlated with the variables used in the analysis and are unlikely to have a significant influence on the point estimates. It is also possible that there was some misclassification of the private practice variable. In addition, incomplete billing in medical centers or government hospitals could also result in biased results.

The results of the current study have demonstrated a small but independent association between both the oncologist's primary practice setting and location of medical training and the use of adjuvant chemotherapy in women with localized breast cancer, regardless of the risk for breast cancer recurrence. We believe this study adds significantly to the limited investigation of the influence of practice setting and physician characteristics on treatment. To improve the quality of cancer care, efforts to determine whether these associations reflect experience, education, practice setting, insurance type, or other economic incentives are warranted.

Conflict of Interest Disclosures

Dr. Hershman is the recipient of an American Society of Clinical Oncology Advanced Clinical Research Award.

Drs. Hershman and Neugut are the recipients of grants from the American Cancer Society (RSGT-08-009-01-CPHPS and RSGT-01-02,404-CPHPS).

Mr. McBride is the recipient of an R25 fellowship from the National Cancer Institute (CA09461).