Journal of the National Cancer Institute Advance Access published online on January 29, 2008
JNCI Journal of the National Cancer Institute, doi:10.1093/jnci/djm320
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
© The Author 2008. Published by Oxford University Press.
ARTICLES |
Surgeon Characteristics and Receipt of Adjuvant Radiotherapy in Women With Breast Cancer
Affiliations of authors: Departments of Medicine (DLH, VRG) and Surgery (KAJ) and the Herbert Irving Comprehensive Cancer Center (DLH, WYT, KAJ, VRG, JSJ), College of Physicians and Surgeons, and the Departments of Epidemiology (DLH, DB, RBM, VRG, JSJ) and Biostatistics (WYT), Mailman School of Public Health, Columbia University; New York Presbyterian Hospital, New York
Correspondence to: Dawn L. Hershman, MD, MS, Herbert Irving Comprehensive Cancer Center, Rm 1068, 161 Fort Washington, New York 10032 (e-mail: dlh23{at}columbia.edu).
 |
ABSTRACT |
|---|
 Top Abstract Context and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
|---|
Background: Adjuvant radiotherapy following breast conservation surgery (BCS) is considered to be an indicator of quality of care for the majority of women with breast cancer, but many women do not receive adjuvant radiotherapy. We investigated the association of surgeon-related factors with receipt of adjuvant radiotherapy after BCS.
Methods: We used the linked Surveillance, Epidemiology and End Results (SEER)–Medicare database to identify women aged 65 years or older with stage I/II breast cancer who were diagnosed between 1991 and 2002 and underwent BCS. We collected demographic and clinical data from SEER and treatment information from Medicare claims data. The American Medical Association Masterfile was used to obtain information on surgeons’ characteristics, including sex, medical school location (United States or elsewhere), and type of degree (MD or Doctorate in Osteopathic Medicine [DO]). The associations of patient (age, race, rural vs urban residence, comorbidities, marital status), tumor (hormone receptor status, grade, stage), and surgeon-related factors with receipt of adjuvant radiotherapy were analyzed using Generalized Estimating Equations to control for clustering. All statistical tests were two-sided.
Results: Of 29760 women in our sample, 22207 (75%) received radiotherapy. Patients who received adjuvant radiotherapy were younger, had fewer comorbidities, and were more likely to be white, married, from an urban area, and diagnosed in a later year compared with those who did not. They were also more likely to have a surgeon who was female (79% vs 73%), had an MD degree (75% vs 68%), or was US trained (75% vs 70%). The multivariable analysis confirmed the association of radiotherapy with having a surgeon who was female (odds ratio [OR] = 1.13; 95% confidence interval [CI] = 1.06 to 1.27), had an MD degree (OR = 1.55; 95% CI = 1.24 to 1.91), was US trained (OR = 1.12; 95% CI = 1.01 to 1.25), or had more than 15 patients (OR = 1.18; 95% CI = 1.10 to 1.28).
Conclusions: Surgeon characteristics were associated with patients’ receipt of adjuvant radiotherapy after BCS after controlling for patient and tumor characteristics, although the individual effect sizes were small for surgeon sex, location of training, and type of medical degree. More research is warranted to confirm the associations to determine whether they reflect surgeon behavior, patient response, or physician–patient interactions.
Prior knowledge The extent to which such surgeon characteristics as sex, location of medical education, and type of degree are associated with their patients’ receipt of adjuvant radiotherapy following breast conservation surgery was unknown. Study design Generalized Estimating Equations were used to analyze the association of patient and surgeon characteristics based on information from the American Medical Association Masterfile and the linked Surveillance, Epidemiology and End Results–Medicare database. Contribution After controlling for patient characteristics, this study found associations between surgeon characteristics and an indicator of the quality of breast cancer care, receipt of adjuvant therapy after breast conservation surgery. Implications More research is warranted to confirm the observed associations and to determine whether they are reflective of surgeon behavior, patient response, or physician–patient interaction. Limitations The database did not provide information on a number of potentially important surgeon- and patient-related variables and did not allow investigators to differentiate between lack of referral or patient refusal as the reason for not receiving radiotherapy.
|
Research on quality of care in oncology has focused on how patient factors, such as race/ethnicity, age, and socioeconomic status (SES), result in suboptimal care. However, little research has addressed how physician characteristics such as sex, training, practice volume, and type of practice may influence the quality of care patients receive.
In the 1980s, adjuvant radiation therapy after breast conservation surgery (BCS) (1) was found to reduce the risk of local recurrence for patients with breast cancer (2–4). Recent meta-analyses showed that, among 7300 patients treated with BCS, those who received adjuvant radiotherapy had a 5-year local recurrence risk of 7% and a 15-year breast cancer mortality risk of 30.5%. By comparison, those who received surgery alone had a 5-year local recurrence risk of 26% and 35.9% breast cancer mortality after 15 years (P < .001) (5,6). In response to these findings, a report published by the Agency for Healthcare Research and Quality recognized post-BCS radiotherapy as both an indicator and a measure of quality care (7).
Since the early 1990s, the use of radiotherapy following lumpectomy has increased, but it remains far from universal (8,9)––only 62%–94% of patients, depending on the population sampled, receive this treatment (10–14). BCS itself is more common among younger patients, those in urban areas, and those diagnosed in academic medical centers than among older patients, those in rural areas, and those diagnosed in community hospitals, respectively (15). Compared with white non-Hispanic women, Hispanic women were 38% less likely to receive radiotherapy following breast cancer surgery, and, for patients as a whole, the probability of receiving radiotherapy decreased by 3% for every 5 additional miles between the patient's residence and an radiotherapy facility (9). Thus, patient characteristics have been associated with the receipt of post-BCS radiotherapy and, therefore, with quality of care.
Little is known about the influence of physician characteristics on breast cancer care. In this study, we used a large population-based registry to investigate the association of physician-related factors with receipt of adjuvant radiotherapy following BCS.
|
Patients and Methods |
|---|
|
TopAbstractContext and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
|---|
Study Database
This study utilized the Surveillance, Epidemiology and End Results (SEER)–Medicare linked database, which was codeveloped by the US National Cancer Institute (NCI) and the Center for Medicare and Medicaid Services. The SEER Program represented roughly 14% of the United States population in 1991 and, since 2000, it represents approximately 26%. Medicare covers hospital services, physician services, some drug therapy, and other medical services for more than 97% of persons aged 65 or older. The linked SEER–Medicare database contains clinical, demographic, and medical claims data on patients aged 65 years or older and is a unique population-based resource for longitudinal epidemiologic and health outcomes studies. Its characteristics and validation have been described comprehensively elsewhere (16,17).
To obtain information on the characteristics of the SEER–Medicare patients’ physicians, we used the Unique Physician Identification Number (UPIN) to link the Medicare claims with the American Medical Association (AMA) Masterfile as described elsewhere (18). This file contains data collected from physician members of the AMA, including sex, age, medical degree (MD or Doctorate in Osteopathic Medicine [DO]), location of medical school (United States vs foreign), year of graduation, employment setting, and specialty (18).
Patient Selection
We initially identified all female Medicare participants aged 65 years or older who were diagnosed with stage I/II breast cancer from January 1, 1991, through December 31, 2002, who underwent BCS within 3 months (n = 45882) after their date of diagnosis and did not have a claim for mastectomy within 90 days after BCS (n = 31271). We used Medicare claims to identify patients who had received radiotherapy within 1 year of the date of diagnosis. Women who did not participate in Medicare Parts A and B during the 12 months before their diagnosis 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.
Also excluded were women whose physician did not have a UPIN number or a primary or secondary specialty listed in the AMA Masterfile (n = 1144). If a patient had two physicians, the physician who billed for the surgery was counted as her surgeon; if neither was listed as the operating physician, then the first physician listed was used. Among women with three or more physicians (n = 149), only those who had a surgical oncologist (n = 19) were included in the study.
Surgeon Characteristics
Surgeon characteristics that were analyzed based on the variables in the AMA Masterfile included sex, year of graduation, primary employment setting (private vs other), location of training (United States vs other), and type of degree (MD or DO). Physician age was characterized by decade of birth. Physicians’ patient volumes (ie, total number of claims for BCS in the database 1991–2002) were dichotomized as 1–15 vs 
15 procedures. We defined high surgeon volume as a surgeon who performed more than 15 of the surgeries in the sample. They represented the most active 15% of the surgeons who performed over 80% of the surgeries.
Measurement of Treatments and Outcomes
We identified and categorized patients with respect to the surgery, radiotherapy, and chemotherapy they received using the SEER–Medicare linked databases and International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) procedure, Current Procedural Terminology, Fourth Edition (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 (19).
We categorized patients as having had BCS if they had any of the following procedures: segmental mastectomy, lumpectomy, quadrantectomy, tylectomy, wedge resection, excisional biopsy, nipple resection, and partial mastectomy unspecified. We categorized patients as having had adjuvant radiotherapy if they had received beam radiation, radioactive implants, radioisotopes, or other radiation (20). We ascertained chemotherapy exposure in the Medicare files using codes for ICD-9-CM diagnosis, ICD-9-CM procedural, CPT, HCPCS, and revenue center codes (16,17).
Socioeconomic Status of Patients
An aggregate SES score was generated from a hierarchy of income data from the 2000 census according to the method adapted from Krieger et al. (21). Patients were ranked on a 1–5 scale, where 1 was the lowest value, based on a formula incorporating as many of the following as were available: median income in the census tract of residence, median income in the zip code of residence, census tract per capita income, and zip code per capita income. Patients for whom values for all variables were missing were assigned to the lowest SES category.
Comorbid Disease To assess the prevalence of comorbid disease in our cohort, we used the Klabunde adaptation of the Charlson comorbidity index (22–24). Medicare inpatient and outpatient claims were searched for ICD-9-CM diagnostic codes indicating a history of myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, chronic pulmonary disease, connective tissue disease, ulcer, liver disease, diabetes, hemiplegia, renal disease, or AIDS from 12 months before to 1 month after the diagnosis of cancer. Each condition was weighted, and patients were assigned a score based on the Klabunde–Charlson index (24).
Statistical Analysis
The chi-square test was used to compare surgeon-related, demographic, and clinical characteristics between patients who received radiotherapy and those who did not and between patients who were operated on by a female surgeon and those who were operated on by a male surgeon. Univariate odds ratios (ORs) were calculated individually for each variable. All hypothesis tests were two-sided.
The Generalized Estimating Equation (GEE) methodology was introduced by Zeger and Liang (25) to deal with clustering in data that otherwise would be analyzed by means of a generalized linear model, and GEEs (PROC GENMOD in SAS) have become an important strategy in the analysis of correlated data (25,26). 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 as follows: the data had a binomial distribution, the link function was logit, and the type of variance was exchangeable.
We evaluated the odds of radiotherapy for all the categories of each variable, controlling for all the other variables in the model. The model included 1) operating physician characteristics (sex, type of degree, country of training, practice type, surgical volume); 2) patient demographic variables (age, race, place of residence, marital status, SES); and 3) clinical variables (tumor grade, American Joint Committee on Cancer stage, hormone receptor status, comorbidity score). We also performed the same analysis for the odds of consultation with a radiation oncologist. To take into account the increases in both radiotherapy and in female physicians over time, we stratified the patients by year of diagnosis in two time frames: 1991–1998 and 1999–2002, representing an even distribution of the female physicians. All statistical analyses were conducted using the SAS system for Windows, Version 9.13.
|
Results |
|---|
|
TopAbstractContext and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
|---|
We identified 29760 women in the SEER–Medicare database who were diagnosed with stage I or II breast cancer during the study period and who met the eligibility criteria. A total of 4455 surgeons operated on these patients; 24346 patients (82%) saw a radiation oncologist, and 22207 (75%) underwent radiotherapy. In each year from 1991 through 1999, the proportions of newly diagnosed patients who saw a radiation oncologist and who received radiotherapy increased, and since then the proportions have stabilized (Fig. 1). The physicians who performed BCS on these patients were predominantly male (88%), in private practice (79%), trained in the United States (81%), and holders of MD (95%) as opposed to DO degrees.
|
Table 1 compares the distributions of patients who did and did not receive radiotherapy according to the demographic and clinical characteristics of the patient and the surgeon. As the unadjusted odds ratios show, radiotherapy use was associated with all of the clinical, demographic, and physician variables assessed in Table 1, except for the surgeon's type of practice (private or not). Patients who received radiotherapy were statistically significantly more likely than those who did not to have a surgeon who was female (79% vs 73%), had an MD degree (75% vs 68%), or was US trained (75% vs 70%). Female surgeons were more likely than male surgeons to have patients who resided in a metropolitan location, were married, received chemotherapy, and had no comorbid conditions (data not shown). Female surgeons were slightly more likely than male surgeons to have DO degrees and to be US trained; they also performed more BCS procedures and were less likely to practice in a private setting (Table 2). The proportion of female surgeons performing breast cancer surgery increased from 7% in 1991 to 24% in 2002 (Fig. 2).
|
|
|
Controlling for known potential demographic and clinical confounders, patients who received radiotherapy were more likely than patients who did not to have their BCS performed by a surgeon who had an MD rather than a DO degree (OR = 1.55; 95% CI = 1.24 to 1.91, P < .001), was US trained (OR = 1.12, 95% CI = 1.01 to 1.25, P = .03), had performed procedures on more than 15 patients in this cohort (OR = 1.18, 95% CI = 1.10 to 1.28, P < .001), and was female (OR = 1.13, 95% CI = 1.06 to 1.27, P = .04) (Table 3). In addition, patients who received radiotherapy were more likely than those who did not to be young, to be married, to have stage I rather than stage II disease, to have no comorbid conditions, to reside in a metropolitan area, to be above the lowest category of SES, and to receive adjuvant chemotherapy and were less likely to be of black race/ethnicity.
|
To control for the interaction between year of diagnosis and surgeon sex, we conducted separate GEE analyses of the association between surgeon sex and receipt of radiotherapy among patients stratified into two groups by year of diagnosis (1991–1998 and 1999–2002) (Table 4). Surgeon sex was not associated with receipt of radiotherapy among patients diagnosed during 1991–1998 (P = .44). However, patients diagnosed between 1999 and 2002 were more likely to receive adjuvant radiotherapy if they had a female surgeon than if they had a male surgeon (OR = 1.17, 95% CI = 1.01 to 1.36, P = .04).
|
|
Discussion |
|---|
|
TopAbstractContext and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
|---|
In our sample population of women older than 65 in the linked SEER–Medicare database, in 1991–2002, 25% of women did not receive radiotherapy following BCS, although the proportions of patients who received radiotherapy increased among patients diagnosed in each succeeding year during the 1990s (Fig. 1). Patients characterized by increased age, black race, residence in a nonmetropolitan location, or unmarried status were less likely than others to receive adjuvant radiotherapy after BCS. After adjustment for patient and tumor characteristics, receipt of post-BCS radiotherapy was also associated with surgeon characteristics including sex, location of training (United States vs foreign), type of degree, and number of patients operated on in the cohort.
Surgeon characteristics have been found to play an important role in the receipt of other types of postsurgical care besides radiotherapy. Cyran et al. (27) found that patients with early-stage breast cancer who were seen by female surgeons were more likely to receive BCS, as opposed to mastectomy, than patients seen by male surgeons. Using SEER–Medicare data, other investigators observed associations between physician characteristics and receipt of androgen deprivation therapy for prostate cancer (28) as well as referral to an oncologist after a diagnosis of stage III colon cancer (29) or lung cancer (30). The probability of a patient's being referred to subspecialists has also been associated with the primary care physician's sex, number of years in practice, practice patient volume, and patient population characteristics (31–33). Patients with breast cancer are more likely to have BCS if their surgeon is female or has a large case volume than if their surgeon is male or performs relatively few procedures (27,34). Thus, patients who are similar in demographic and clinical characteristics may get different treatments depending on their surgeons.
We found that the number of female breast cancer patients registered in the SEER–Medicare database whose BCS was performed by a female surgeon has increased steadily since 1991. Patients who received radiotherapy were more likely to have had a female surgeon than those who did not. Furthermore, patients who received radiotherapy were more likely to have a surgeon who performed BCS on more than 15 other patients in the SEER–Medicare database than those who did not.
We also found that patients of physicians with more patients with claims for BCS in the dataset were more likely than other patients to receive adjuvant radiotherapy. Others have also found that surgical volume influences quality of care and outcomes (35,36).
Considering that medical graduates who were not trained in the United States represent approximately 25% of the US physician supply (37), surprisingly few studies have compared the performance of these medical graduates with that of US-trained graduates. Elderly women patients of medical school graduates trained outside the United States appear to have lower mammography referral rates than comparable patients of US-trained physicians, but this may reflect a difference in clinical decision making rather than patient preference (38). A study in Canada based on a large database found that the survival of patients with acute myocardial infarction treated by graduates of medical schools outside of Canada was similar to that of patients treated by Canadian-trained physicians (39). We found no studies that investigated the quality of care of surgeons who were medical graduates of institutions outside the United States. Nonetheless, Moore and Rhodenbaugh (40) found that surgical residency programs discriminated against international medical graduates in their admissions. Virtually no research has compared allopathic and osteopathic physicians, although one small study found that osteopathic physicians were less likely to recommend cancer screening for their patients (41).
In our study, controlling for patient, tumor, and surgeon characteristics, black women were still less likely than white women to receive post-BCS radiotherapy (Table 3). Differences according to race have also been observed in the frequency of breast cancer screening practices (42,43), the length of intervals between onset of symptoms and treatment for breast cancer (44,45), and the stage at diagnosis (46,47). In addition, the use of BCS vs mastectomy has been found to vary by geographic region, SES, and race/ethnicity in the United States (48–50). In a recent analysis of SEER data, Joslyn et al. (51) reported that black women with early-stage breast cancer were less likely than white women to receive adjuvant radiotherapy.
Another factor that may contribute to medical decision making is the gender and racial concordance between the physician and patient. Patients who are seen by a physician of their own race have reported more participatory decision making and more satisfaction than patients seen by a physician of a different race (52,53). Women seen by a female physician have been observed to be more likely to undergo screening with Pap smears and mammograms than those seen by a male physician, particularly if the physician is an internist or family practitioner (54). Similarly, cancer-screening activity was higher among patients seen by medical doctors than those seen by doctors of osteopathic medicine (41). Female physicians were more likely than male physicians to ask new patients about components of prevention, to believe in the effectiveness of mammography, to feel personal responsibility for ensuring that their patients received screening, and to report comfort in performing Pap smears and breast examinations (55). Thus, it is clear that decision making involves a complex interaction between the physician and patient and their individual characteristics.
Our study had a number of limitations. The SEER–Medicare dataset that we used is population based, but it does not include data on variables that might also have been associated with receipt of radiotherapy, such as physical condition or performance status, psychological outlook, communication by the patient with her physician, or health behaviors. It also did not enable us to differentiate between lack of referral and patient refusal. In addition, the AMA Masterfile that we used did not provide information on the race/ethnicity or board certification status of the surgeons.
In addition, our study was limited to patients over the age of 65 and may not be generalizable to younger populations. Recent data suggest that while the local recurrence rates are reduced, the survival benefits of adjuvant radiation may be attenuated in patients over the age of 70 with hormone receptor positive cancer treated with tamoxifen (56,57). These data were not known during the time period of our analysis, although some investigators may have anticipated that these were going to be the findings and acted accordingly.
Because post-BCS radiation has been shown to reduce local recurrence as well as to improve both disease-free and overall survival in women with localized breast cancer (5,58), it is recognized as an indicator of quality of care (7). Our finding of associations between this procedure and referring physician characteristics may therefore support other evidence that certain subgroups of breast surgeons have deficiencies in training or continued education and practice (59,60). Moreover, breast cancer is not unique in this regard. In a survey of 30 health conditions ranging from osteoarthritis to breast cancer, McGlynn et al. (61) estimated that, on average, Americans received about half (54.9%) of the recommended medical care processes for basic care.
Another limitation of our study was the use of odds ratios to characterize the relationship between surgeon characteristics and receipt of radiotherapy, controlling for other factors and correcting for clustering. The odds ratio is a good approximation of the relative risk when the outcome is rare but can be an overestimate when the outcome is common. Methods of calculating multivariable relative risks have been developed for studies of common outcomes (62,63). No such method has been developed for use in hierarchical logistic models, where clustering has a substantial effect on the estimate. Bias occurs because these formulas proposed in other contexts fail to take into consideration the complex relationship between the outcome and exposure for each covariate pattern (64). In addition, the calculation does not consider the covariance between the estimated incidence and estimated odds ratio, and, therefore, the precision of the confidence intervals can be affected (64). It should be noted that it is likely that the true relative risks are slightly lower than the odds ratio we have reported, but they are unlikely to be dramatically different given the small overall effect sizes that we found (Table 3).
Our study is one of the first to demonstrate associations between certain surgeon characteristics and quality of breast cancer care, although the individual effect sizes were small for surgeon sex, location of training, and type of medical degree. Further research is essential to confirm these associations. If confirmed, more research is needed on whether they reflect surgeon behavior, patient response, or physician–patient interactions.
|
Funding |
|---|
|
TopAbstractContext and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
|---|
American Society of Clinical Oncology Advanced Clinical Research Award (to D. L. H.); American Cancer Society (RSGT08-009-01-CPHPS to D. L. H., RSGHP PBP105710 to V. R. G.); Department of Defense Breast Cancer Center of Excellence Award (BC043120 [GenBank] ).
|
NOTES |
|---|
|
TopAbstractContext and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
|---|
This study used the linked SEER–Medicare database. The analysis, interpretation and reporting of the data, writing of the manuscript, and decision to publish were the sole responsibility of the authors. The authors acknowledge the efforts of the Applied Research Branch, Division of Cancer Prevention and Population Science, NCI; the Office of Information Services, and the Office of Strategic Planning, HCFA; Information Management Services, Inc; and the SEER Program tumor registries in the creation of the SEER–Medicare database.
|
REFERENCES |
|---|
|
TopAbstractContext and CaveatsPatients and MethodsResultsDiscussionFundingReferencesNotes |
|---|
1. Chia S, Bryce C, Gelmon K. The 2000 EBCTCG overview: a widening gap. Lancet (2005) 365(9472):1665–1666.[CrossRef][Web of Science][Medline]
2. Lee T, Brugge D, Francis C, Fisher O. Asthma prevalence among inner-city Asian American schoolchildren. Public Health Rep (2003) 118(3):215–220.
3. Veronesi U, Luini A, Del Vecchio M, et al. Radiotherapy after breast-preserving surgery in women with localized cancer of the breast. N Engl J Med (1993) 328(22):1587–1591.
4. Fisher B, Anderson S, Bryant J, et al. Twenty-year follow-up of a randomized trial comparing total mastectomy, lumpectomy, and lumpectomy plus irradiation for the treatment of invasive breast cancer. N Engl J Med (2002) 347(16):1233–1241.
5. Whelan TJ, Julian J, Wright J, Jadad AR, Levine ML. Does locoregional radiation therapy improve survival in breast cancer? A meta-analysis. J Clin Oncol (2000) 18(6):1220–1229.
6. Clarke M, Collins R, Darby S, et al. Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local recurrence and 15-year survival: an overview of the randomised trials. Lancet (2005) 366(9503):2087–2106.[Web of Science][Medline]
7. Moher D, Mamaladze V, Lewin G, et al. Measuring the Quality of Breast Cancer Care in Women. Rockville, MD: Agency for Healthcare Research and Quality; September 2004. Summary, Evidence Report/Technology Assessment 105. AHRQ Publication No. 04-E030-1.
8. Voti L, Richardson LC, Reis I, Fleming LE, Mackinnon J, Coebergh JW. The effect of race/ethnicity and insurance in the administration of standard therapy for local breast cancer in Florida. Breast Cancer Res Treat (2006) 95(1):89–95.[CrossRef][Web of Science][Medline]
9. Voti L, Richardson LC, Reis IM, Fleming LE, Mackinnon J, Coebergh JW. Treatment of local breast carcinoma in Florida: the role of the distance to radiation therapy facilities. Cancer (2006) 106(1):201–207.[CrossRef][Web of Science][Medline]
10. Farrow DC, Hunt WC, Samet JM. Geographic variation in the treatment of localized breast cancer. N Engl J Med (1992) 326(17):1097–1101.[Abstract]
11. Nattinger AB, Goodwin JS. Geographic and hospital variation in the management of older women with breast cancer. Cancer Control (1994) 1(4):334–338.[Medline]
12. Buchholz TA, Theriault RL, Niland JC, et al. The use of radiation as a component of breast conservation therapy in National Comprehensive Cancer Network Centers. J Clin Oncol (2006) 24(3):361–369.
13. Malin JL, Asch SM, Kerr EA, McGlynn EA. Evaluating the quality of cancer care: development of cancer quality indicators for a global quality assessment tool. Cancer (2000) 88(3):701–707.[CrossRef][Web of Science][Medline]
14. Morrow M, White J, Moughan J, et al. Factors predicting the use of breast-conserving therapy in stage I and II breast carcinoma. J Clin Oncol (2001) 19(8):2254–2262.
15. Gilligan MA, Neuner J, Sparapani R, Laud PW, Nattinger AB. Surgeon characteristics and variations in treatment for early-stage breast cancer. Arch Surg (2007) 142(1):17–22.
16. Warren JL, Harlan LC, Fahey A, et al. Utility of the SEER-Medicare data to identify chemotherapy use. Med Care (2002) 40((8 suppl)). IV-55-61.
17. Warren JL, Klabunde CN, Schrag D, Bach PB, Riley GF. Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. Med Care (2002) 40((8 suppl)). IV-3-18.
18. Baldwin LM, Adamache W, Klabunde CN, Kenward K, Dahlman C, Warren LJ. Linking physician characteristics and medicare claims data: issues in data availability, quality, and measurement. Med Care (2002) 40((8 suppl)). IV-82-95.
19. Du XL, Osborne C, Goodwin JS. Population-based assessment of hospitalizations for toxicity from chemotherapy in older women with breast cancer. J Clin Oncol (2002) 20(24):4636–4642.
20. Du X, Freeman JL, Goodwin JS. Information on radiation treatment in patients with breast cancer: the advantages of the linked medicare and SEER data. Surveillance, Epidemiology and End Results. J Clin Epidemiol (1999) 52(5):463–470.[CrossRef][Web of Science][Medline]
21. Krieger N. Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am J Public Health (1992) 82(5):703–710.
22. Charlson ME, Sax FL, MacKenzie CR, Fields SD, Braham RL, Douglas RG Jr. Assessing illness severity: does clinical judgment work? J Chronic Dis (1986) 39(6):439–452.[CrossRef][Web of Science][Medline]
23. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol (1992) 45(6):613–619.[CrossRef][Web of Science][Medline]
24. Klabunde CN, Potosky AL, Legler JM, Warren JL. Development of a comorbidity index using physician claims data. J Clin Epidemiol (2000) 53(12):1258–1267.[CrossRef][Web of Science][Medline]
25. Zeger SL, Liang KY, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics (1988) 44(4):1049–1060.[CrossRef][Web of Science][Medline]
26. Panageas KS, Schrag D, Russell Localio A, Venkatraman ES, Begg CB. Properties of analysis methods that account for clustering in volume-outcome studies when the primary predictor is cluster size. Stat Med (2006) 26(9):2017–2035.[CrossRef][Web of Science]
27. Cyran EM, Crane LA, Palmer L. Physician sex and other factors associated with type of breast cancer surgery in older women. Arch Surg (2001) 136(2):185–191.
28. Shahinian VB, Kuo YF, Freeman JL, Goodwin JS. Determinants of androgen deprivation therapy use for prostate cancer: role of the urologist. J Natl Cancer Inst (2006) 98(12):839–845.
29. Luo R, Giordano SH, Zhang DD, Freeman J, Goodwin JS. The role of the surgeon in whether patients with lymph node-positive colon cancer see a medical oncologist. Cancer (2007) 109(5):975–982.[CrossRef][Medline]
30. Earle CC, Neumann PJ, Gelber RD, Weinstein MC, Weeks JC. Impact of referral patterns on the use of chemotherapy for lung cancer. J Clin Oncol (2002) 20(7):1786–1792.
31. Franks P, Clancy CM. Referrals of adult patients from primary care: demographic disparities and their relationship to HMO insurance. J Fam Pract (1997) 45(1):47–53.[Web of Science][Medline]
32. Franks P, Williams GC, Zwanziger J, Mooney C, Sorbero M. Why do physicians vary so widely in their referral rates? J Gen Intern Med (2000) 15(3):163–168.[CrossRef][Web of Science][Medline]
33. Freiman MP. The rate of adoption of new procedures among physicians. The impact of specialty and practice characteristics. Med Care (1985) 23(8):939–945.[CrossRef][Web of Science][Medline]
34. Hawley ST, Hofer TP, Janz NK, et al. Correlates of between-surgeon variation in breast cancer treatments. Med Care (2006) 44(7):609–616.[CrossRef][Web of Science][Medline]
35. Bach PB, Cramer LD, Schrag D, Downey RJ, Gelfand SE, Begg CB. The influence of hospital volume on survival after resection for lung cancer. N Engl J Med (2001) 345(3):181–188.
36. Begg CB, Riedel ER, Bach PB, et al. Variations in morbidity after radical prostatectomy. N Engl J Med (2002) 346(15):1138–1144.
37. Mullan F, Politzer RM, Davis CH. Medical migration and the physician workforce. International medical graduates and American medicine. JAMA (1995) 273(19):1521–1527.
38. Grady KE, Lemkau JP, McVay JM, et al. Clinical decision-making and mammography referral. Prev Med (1996) 25(3):327–338.[CrossRef][Web of Science][Medline]
39. Ko DT, Austin PC, Chan BT, Tu JV. Quality of care of international and Canadian medical graduates in acute myocardial infarction. Arch Intern Med (2005) 165(4):458–463.
40. Moore RA, Rhodenbaugh EJ. The unkindest cut of all: are international medical school graduates subjected to discrimination by general surgery residency programs? Curr Surg (2002) 59(2):228–236.[CrossRef][Medline]
41. Brownson RC, Davis JR, Simms SG, Kern TG, Harmon RG. Cancer control knowledge and priorities among primary care physicians. J Cancer Educ (1993) 8(1):35–41.[Medline]
42. Caplan LS, Wells BL, Haynes S. Breast cancer screening among older racial/ethnic minorities and whites: barriers to early detection. J Gerontol (1992) 47. Spec No:101–110.
43. Caplan LS, Helzlsouer KJ, Shapiro S, Wesley MN, Edwards BK. Reasons for delay in breast cancer diagnosis. Prev Med (1996) 25(2):218–224.[CrossRef][Web of Science][Medline]
44. Richards MA, Westcombe AM, Love SB, Littlejohns P, Ramirez AJ. Influence of delay on survival in patients with breast cancer: a systematic review. Lancet (1999) 353(9159):1119–1126.[CrossRef][Web of Science][Medline]
45. Gwyn K, Bondy ML, Cohen DS, et al. Racial differences in diagnosis, treatment, and clinical delays in a population-based study of patients with newly diagnosed breast carcinoma. Cancer (2004) 100(8):1595–1604.[CrossRef][Web of Science][Medline]
46. Shavers VL, Harlan LC, Stevens JL. Racial/ethnic variation in clinical presentation, treatment, and survival among breast cancer patients under age 35. Cancer (2003) 97(1):134–147.[CrossRef][Web of Science][Medline]
47. Ghafoor A, Jemal A, Ward E, Cokkinides V, Smith R, Thun M. Trends in breast cancer by race and ethnicity. CA Cancer J Clin (2003) 53(6):342–355.
48. Nattinger AB, Gottlieb MS, Veum J, Yahnke D, Goodwin JS. Geographic variation in the use of breast-conserving treatment for breast cancer. N Engl J Med (1992) 326(17):1102–1107.[Abstract]
49. Morris CR, Cohen R, Schlag R, Wright WE. Increasing trends in the use of breast-conserving surgery in California. Am J Public Health (2000) 90(2):281–284.
50. Lantz PV, Zemencuk JK, Katz SJ. Is mastectomy overused? A call for an expanded research agenda. Health Serv Res. (2002) 37(2):417–431.[CrossRef][Web of Science][Medline]
51. Joslyn SA. Racial differences in treatment and survival from early-stage breast carcinoma. Cancer (2002) 95(8):1759–1766.[CrossRef][Web of Science][Medline]
52. Cooper-Patrick L, Gallo JJ, Gonzales JJ, et al. Race, gender, and partnership in the patient-physician relationship. JAMA (1999) 282(6):583–589.
53. Cooper LA, Roter DL, Johnson RL, Ford DE, Steinwachs DM, Powe NR. Patient-centered communication, ratings of care, and concordance of patient and physician race. Ann Intern Med (2003) 139(11):907–915.
54. Lurie N, Slater J, McGovern P, Ekstrum J, Quam L, Margolis K. Preventive care for women. Does the sex of the physician matter? N Engl J Med (1993) 329(7):478–482.
55. Lurie N, Margolis KL, McGovern PG, Mink PJ, Slater JS. Why do patients of female physicians have higher rates of breast and cervical cancer screening? J Gen Intern Med (1997) 12(1):34–43.[CrossRef][Web of Science][Medline]
56. Hughes KS, Schnaper LA, Berry D, et al. Lumpectomy plus tamoxifen with or without irradiation in women 70 years of age or older with early breast cancer. N Engl J Med (2004) 351(10):971–977.
57. Fyles AW, McCready DR, Manchul LA, et al. Tamoxifen with or without breast irradiation in women 50 years of age or older with early breast cancer. N Engl J Med (2004) 351(10):963–970.
58. Favourable and unfavourable effects on long-term survival of radiotherapy for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists’ Collaborative Group. Lancet (2000) 355(9217):1757–1770.[CrossRef][Web of Science][Medline]
59. Committee on the Quality of Health Care in America, Institute of Medicine. In: Crossing the Quality Chasm: A New Health System for the 21st Century (2001) Washington, DC: National Academy Press.
60. McGlynn EA, Cassel CK, Leatherman ST, DeCristofaro A, Smits HL. Establishing national goals for quality improvement. Med Care (2003) 41(1 suppl):I16–I29.[Web of Science][Medline]
61. McGlynn EA, Asch SM, Adams J, et al. The quality of health care delivered to adults in the United States. N Engl J Med (2003) 348(26):2635–2645.
62. Spiegelman D, Hertzmark E. Easy SAS calculations for risk or prevalence ratios and differences. Am J Epidemiol (2005) 162(3):199–200.
63. Zhang J, Yu KF. What's the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. JAMA (1998) 280(19):1690–1691.
64. McNutt LA, Wu C, Xue X, Hafner JP. Estimating the relative risk in cohort studies and clinical trials of common outcomes. Am J Epidemiol (2003) 157(10):940–943.
Manuscript received June 18, 2007; revised December 7, 2007; accepted December 17, 2007.
Related Articles in JNCI
CiteULike 
Connotea 
Del.icio.us What's this?
J Natl Cancer Inst 2008 100: 157.
J Natl Cancer Inst 2008 100: 157.
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||