Treatment of Ductal Carcinoma In Situ Among Patients Cared for in Large Integrated Health Plans

May 11, 2010
Reina Haque, PhD

Ninah S. Achacoso, MS

Suzanne W. Fletcher, MD, MSc

Larissa Nekhlyudov, MD, MPH

Laura C. Collins, MBBS

Stuart J. Schnitt, MD

Charles P. Quesenberry Jr, PhD

Laurel A. Habel, PhD

Volume 16, Issue 5

Although we found no DCIS treatment disparities by race/ethnicity, use of adjuvant radiation therapy was less among older women and among residents of poorer neighborhoods.

Objective: To examine whether use of adjuvant therapy varies by race/ethnicity among patients with ductal carcinoma in situ (DCIS) at 3 integrated health plan delivery sites based in California and Massachusetts.

Study Design: Cross-sectional study nested within a cohort of women diagnosed as having DCIS between 1990 and 2001.

Methods: We reviewed medical records of 3000 non-Hispanic white (69%), black (10%), Hispanic (9%), and Asian or Pacific Islander (12%) women diagnosed as having DCIS between 1990 and 2001 and treated with breast-conserving therapy. X2 Test and multinomial logistic regression analysis were used to examine the association between race/ethnicity and use of adjuvant treatments after controlling for patient and clinical variables, including certain pathologic factors.

Results: We found no significant differences in DCIS adjuvant treatment among racial/ethnic groups in bivariate or multinomial analyses after adjusting for demographic characteristics, comorbidity, and clinical factors. Minority women were as likely to undergo adjuvant radiation therapy as non-Hispanic white women. However, women 70 years or older (odds ratio, 0.40; 95% confidence interval, 0.31-0.51) and women who lived in areas with low geocoded median family income (odds ratio, 0.65; 95% confidence interval, 0.48-0.89) were less likely to receive adjuvant radiation therapy. Tumor size and comedo histologic growth pattern were associated with increased likelihood of receiving radiation therapy.

Conclusion: Use of adjuvant therapy by minority women in these managed care plans is similar to that by non-Hispanic white women, although use was less among older women and among women who lived in poorer neighborhoods.

(Am J Manag Care. 2010;16(5):351-360)

The lack of differences in the treatment of ductal carcinoma in situ by race/ethnicity observed in these integrated healthcare delivery systems may be due to coordinated clinical guidelines and multidimensional approaches to reduce barriers in care by educating physician leaders, nurse practitioners, case managers, and disease management program managers in these organizations.

  • However, older women (>70 years) and women who lived in census tracts with low median family incomes were less likely to receive adjuvant radiation therapy.
  • Such groups of women may have different functionality, comorbidity burden, and treatment preferences, all of which need to be considered in the treatment decision-making process.

The diagnosis of ductal carcinoma in situ (DCIS) has increased markedly because of enhanced screening mammography efforts and constitutes more than 20% of newly diagnosed breast cancer cases in the United States.1 Despite improvements in detection, determining the most appropriate treatment strategy remains a challenge owing to the heterogeneity of DCIS lesions.2-4 While racial/ ethnic differences have been reported for the detection, diagnosis, evaluation, and treatment of invasive breast cancer, data are limited on whether there are similar disparities in the treatment of DCIS.5-7 Recent studies8-10 of women with invasive disease have found that racial/ ethnic minority women undergo breast-conserving surgery (BCS) more frequently than white women; however, black women are at twice the risk of white women for failing to receive postsurgery chemotherapy and hormonal therapy. This racial/ethnic disparity in the receipt of adjuvant therapy for invasive disease has been reported in many settings.5,8,10-17

In contrast, less information on treatment disparity exists for DCIS than for invasive disease.6,18 Because DCIS can progress to invasive disease, it is critical to determine whether modifiable and nonmodifiable factors are associated with receipt of therapy. While controversy exists regarding optimal treatment for DCIS, research indicates that women treated with BCS and subsequent radiation therapy have significantly reduced recurrence versus women treated with surgery alone.6,19 The risk of recurrence can be further reduced by combining radiation therapy with adjuvant tamoxifen citrate treatment.20,21 Breast-conserving surgery with adjuvant tamoxifen treatment alone is generally not a recommended option.In addition, neither cytotoxic chemotherapy nor any of the newer biologic agents are recommended for DCIS.

Previous studies8,18,22-28 that have examined breast cancer treatment differences were based on claims data from fee-for-service settings; however, these sources offer a limited understanding of utilization. Tumor registries reliably capture information on surgery and race/ethnicity but less reliably capture adjuvant radiation therapy or hormonal treatment data.8 Such databases generally also lack data on socioeconomic status, which may contribute to treatment differences.8 Medical record review is resource intensive but enables more comprehensive insight into treatments used. The objective of this study was to use information abstracted from medical records to examine whether use of adjuvant therapy varied by race/ethnicity among a diverse cohort of 3000 women diagnosed as having DCIS between 1990 and 2001 and treated with BCS in 3 geographically diverse integrated healthcare delivery systems. A key advantage of this study is the additional information we captured on pathologic features and socioeconomic factors that vary by race/ethnicity and may influence treatment decisions.

METHODSDesign and Setting

This study was conducted at 3 sites participating in the Cancer Research Network, a consortium of research organizations affiliated with nonprofit integrated healthcare delivery systems and the National Cancer Institute. Study participantsincluded women enrolled at Kaiser Permanente Northern California, Kaiser Permanente Southern California, and Harvard Pilgrim Health Care. The sites care for more than 6 million members in California and Massachusetts. We examined patient and healthcare factors associated with utilization of adjuvant cancer treatment (radiation therapy and hormonal therapy). This study was part of a retrospective cohort study of women diagnosed as having DCIS between 1990 and 2001. The study was approved by the institutional review boards at all 3 study sites.

Study Participants

Women with DCIS were identified through the Kaiser Permanente health plans’ electronic cancer registries in California. These health plans report cancer cases in specific geographic regions to the SEER (Surveillance, Epidemiology and End Results) program. At Harvard Pilgrim Health Care, claims and electronic outpatient medical records were used to identify women with DCIS.

The cohort included women from Kaiser Permanente Northern California, Kaiser Permanente Southern California, and Harvard Pilgrim Health Care who were aged 20 to

84 years at diagnosis of DCIS, were diagnosed between 1990 and 2001, had unilateral disease, were treated with BCS, had no history of DCIS or invasive cancer (breast or other site), and remained enrolled within the health plans for at least 6 months after diagnosis.

Of 3668 patients identified as potentially eligible by our cancer registries or electronic medical records, 602 were deemed ineligible for 1 or more of the following reasons based on medical record review: unavailability of medical records (n = 82), miscoding of DCIS in the cancer registry (n = 63), prior breast or other cancer (n = 216), bilateral breast cancer at diagnosis (n = 29), mastectomy for the index DCIS (n = 96), age 85 years or older at diagnosis (n = 15), or lack of follow-up in the health plan for 6 consecutive months (n = 101). Of 3066 remaining patients, 29 women had unknown treatment and 37 women had missing race/ethnicity, leaving 3000 patients for this study.

Data Sources

We used standardized medical record abstraction forms to capture information on treatment (surgery, radiation therapy, chemotherapy, and hormonal therapy), history of breast cancer among first-degree relatives, year of diagnosis, and height, weight, and age at index DCIS diagnosis. Family history of breast cancer was history of the disease in a first-degree blood relative (including mother, sisters, half sisters, or daughters) of the study patient. We recorded information on family history if it appeared in the medical record within 6 months of the study patient’s DCIS diagnosis.

We also collected information on the presence of diabetes mellitus around the time of DCIS diagnosis as a surrogate measure of comorbidity because findings from studies29,30 suggest that patients with diabetes are treated less aggressively for cancer. The analysis presented herein examines the initial course of treatment documented in the medical records in the 6 months after DCIS diagnosis. Because detection methods can vary by race/ethnicity and influence treatment decisions, we abstracted information as to whether the breast lesion was identified through palpation or screening mammography. Because prevalence of pathologic features may vary by race/ethnicity and may influence treatment decisions, we conducted a subset analysis involving 1 study site (n = 986). At this study site, we abstracted key features from the pathology reports such as surgical margins, tumor size, comedo histologic growth pattern, necrosis, and nuclear grade. Because the health plan tumor registries in California did not uniformly capture pathologic variables during the study period, we assessed these factors based on review of the original pathology

report and specimens by a single study pathologist rather than through the SEER program. In this way, the pathologic variables were measured in a standard manner for all patients at this study site whether or not the patients lived in a geographic area covered by the SEER program during the study period (1990-2001).

Information on race/ethnicity was captured from the medical records or the electronic SEER-affiliated cancer registries (in California). The SEER data are based on medical records and administrative information. We grouped race/ethnicity as non-Hispanic white, black, Hispanic, or Asian or Pacific Islander. Because the health plans do not uniformly collect members’ income or educational attainment, information on these factors was obtained from geocoding files based on California’s 1990 census (which was closest to the DCIS diagnosis dates). In this approach, the women in the cohort were classified according to the socioeconomic characteristics of their census tract at the time of diagnosis.31,32 Geocoded educational attainment and median family income were based on the distribution of the women in our sample (the cohort’s census tract). Geocoded educational attainment was divided into 2 groups (high vs low). High geocoded educational attainment means that the percentage of women in the sample with at least some college education is greater than the percentage of women in the cohort with at most a high school diploma. Geocoded median family income was divided into quartiles. Analyses considering median family income and educational attainment were restricted to patients in California (93% of

the study cohort). Similar information was not feasible to ascertain for patients in Massachusetts.

Statistical Analysis

We first conducted stratified analyses and examined the distribution of patient characteristics by race/ethnicity and DCIS treatment regimens. Two-sided P values were based on χ2 test for heterogeneity. Unknown and missing values were excluded in the calculation of χ2 values. The levels of treatment examined included BCS alone (reference group), BCS with adjuvant radiation therapy, BCS with adjuvant tamoxifen therapy, and BCS with both adjuvant treatments. Finally, adjusted odds ratios (ORs) were estimated using multinomial logistic regression analysis, which is an extension of the binary logistic regression technique in which the dependent variable (DCIS treatment regimens) has unordered multiple levels.33 Variables examined in the models were race/ethnicity, age at diagnosis, year of diagnosis, study site, body mass index (BMI), family history of breast cancer, comorbidity (history of diabetes), geocoded educational attainment, and median family income. Cut points for BMI were based on categories of the National Heart, Lung, and Blood Institute.34 For the subset of patients for whom we had pathologic data, the model for receipt of adjuvant radiation therapy also included tumor characteristics. All analyses were conducted using commercially available statistical software (SAS, version 9.1; SAS Institute Inc, Cary, NC35).


Participants included 292 black (10%), 263 Hispanic (9%), 370 Asian or Pacific Islander (12%), and 2075 (69%) non-Hispanic white women. We identified only 1 woman as being non-white Hispanic (this patient was included in the black category). Asian or Pacific Islanders tended to be younger at the time of DCIS diagnosis, and 38% of those women were diagnosed before age 50 years (Table 1). Within each racial/ethnic group, the percentage of women diagnosed as having DCIS increased over time, with the sharpest rise occurring after 1997 among Asian or Pacific Islanders. Within this group, the rate of diagnosis increased from 14% in1996-1997 to 29% in 1998-1999. The percentage of women with a known family history (first-degree blood relative) of breast cancer was similar in black, Hispanic, and white women (19% in each group) and was lower in Asian or Pacific Islanders (11%).

For participants with known addresses, 77% lived in census tracts where the geocoded educational attainment included some college. Geocoded educational attainment varied by race/ethnicity, with Asian or Pacific Islander women and white women representing the highest proportions of women who lived in census tracts with higher educational attainment (P <.001). Similarly, geocoded median family income varied by race/ethnicity, with higher percentages of black and Hispanic women living in census tracts with lower median family income (P <.001). Among participants with known weight, 58% of Asian or Pacific Islanders were of normal weight. A considerable percentage of white women were of normal weight (41%), although 57% were in the overweight and obese categories.

Detection method of DCIS was associated with race/ ethnicity (P = .02) and varied by age, with more younger women having palpable lesions (P <.001). Although most lesions (83%) were detected by screening mammography, 17% were detected by palpation. Among Asian or Pacific Islanders, almost one-fourth of the lesions were detected by palpation, whereas among white women 16% were detected by palpation.

Table 2 gives adjusted ORs from the multinomial logistic regression models for the association of patient and tumor factors with DCIS treatment regimens. The reference group for each treatment regimen (the dependent variable) comprised women who underwent BCS alone. The reference group for race/ethnicity (the main independent variable) was white women. Of 3000 women, 43% (n = 1284) underwent BCS alone, whereas 57% (n = 1716) underwent adjuvant radiation therapy or tamoxifen treatment. As expected, none of the women in our cohort were treated with chemotherapy. Radiation therapy alone was the most common adjuvant regimen. About 4% (n = 129) of women underwent adjuvant tamoxifen treatment only, while 11% (n = 337) underwent a combination of adjuvant radiation therapy and tamoxifen treatment.

Race/ethnicity was not strongly associated with use of adjuvant treatments; variation differed little by these subgroups of women, as the confidence intervals (CIs) were wide and included the null. Treatment regimens also did not vary by family history of breast cancer, geocoded educational attainment, BMI, or history of diabetes. Year of diagnosis was the strongest correlate of adjuvant radiation therapy use. For example, compared with women who underwent BCS alone, the oddsof adjuvant radiation therapy receipt increased over the years; adjusted ORs varied from 2.55 (95% CI, 1.75-3.71) in 1992- 1993 to 4.08 (95% CI, 2.86-5.83) in 2000-2001. Women who lived in census tracts with a low geocoded median family income were significantly less likely to receive adjuvant radiation therapy (OR, 0.65; 95% CI, 0.48-0.89). Older women (>70 years) were 2.5 times more likely to receive adjuvant tamoxifen therapy (without radiation therapy) than younger women (<50 years) (OR, 2.52; 95% CI, 1.29-4.90). However, older women were dramatically less likely to receive adjuvant radiation therapy (OR, 0.40; 95% CI, 0.31-0.51). The ORs for all treatment regimens increased over the years, with the sharpest rise occurring for combined radiation therapy and tamoxifen treatment.

Of the subset of women with pathologic data (n = 986), patients with large tumors (OR, 2.45; 95% CI, 1.23-4.88) and comedo histologic growth pattern (OR, 1.89; 95% CI, 1.35-2.64) were more likely to receive adjuvant radiation therapy than BCS alone. We did not have a large enough sample size to examine the association of pathologic factors and other treatment combinations (ie, BCS with tamoxifen treatment or BCS with radiation therapy and tamoxifen treatment). During the study period (1990-2001), estrogen receptor testing was not routinely performed. Therefore, this information was not captured in relation to tamoxifen use.


Our findings suggest that receipt of adjuvant radiation therapy (with or without tamoxifen treatment) was not related to race/ethnicity in these managed care plans. However, we found that older women (>70 years) and women who lived in census tracts with low median family incomes were substantially less likely to receive adjuvant radiation therapy, despite potential equal access to care.

Our finding that minority women received adjuvant therapy as often as non-Hispanic white women in these managed care plans may be due to equal access to care. In their synthesis of research on racial/ethnic disparities in cancertreatment,36-40 Shavers and Brown5 similarly noted fewer differences among women receiving cancer treatment by race/ ethnicity in single institutions and equal-access systems. Inaddition to race/ethnicity, other research indicates that treatment of invasive breast cancer differs by age at diagnosis,9,25 tumor characteristics,8,41 and radiation therapy initiation,26 but few corresponding data exist for DCIS.27,28 Patients with DCIS 70 years or older in our cohort were less likely to receive adjuvant radiation therapy. Enger and colleagues42 similarly noted that treatment variations for invasive breast cancer may be related to age, with older women (>75 years) receiving nonstandard care compared with women aged 65 to 74 years among those treated at health maintenance organizations. A reanalysis of that study showed that almost 20% of older women (>65 years) at high risk of recurrence received chemotherapy; however, no variation was found by race/ethnicity. 43 Although the presence of comorbidities (diabetes or high BMI) differed by race/ethnicity in the present study, they were unrelated to DCIS treatment (Table 2).

This study has several strengths. Data for this investigation came from one of the largest medical record review—based studies of women diagnosed as having DCIS and included 3000 women. The study group also included a population for whom breast cancer screening is a covered benefit. Our study was able to overcome several limitations of previous studies. Out-of-pocket expense is an important known barrier to cancer treatment; however, our study group included a large insured population in which the effects of such barriers are minimized. Participants for this study were drawn from integrated healthcare delivery organizations, and their care may reflect the general cancer treatment that patients receive in other delivery systems in the United States. However, our results may not be generalizable to other settings, especially those for which there is no equal access to healthcare. In addition, although our sites somewhat underrepresent the very poor and the very wealthy, the memberships include the entire socioeconomic spectrum, including some who are Medicaid recipients. The study sites, particularly those in California, have racially/ethnically diverse memberships that represent the communities they serve.

This study has certain limitations. We ascertained race/ ethnicity information from medical records, which may be inaccurately documented. However, a study44 that compared self-reported race/ethnicity with that documented in medical records demonstrated that the overall accuracy of medical records for race/ethnicity is high, although substantial inaccuracy may exist in the recording of Hispanic race/ethnicity. Underrecording of Hispanic race/ethnicity might have partially contributed to the lack of treatment disparity observed in this study. Furthermore, a limitation of geocoded median family income and educational attainment data is that they may not reflect the actual educational and household income of the individual. However, previous studies27,45 demonstrated the usefulness of both of these geocoded variables. This study also did not examine the patient—provider interactions that influence use of adjuvant treatments. Findings from previous studies14,46-48 demonstrate that patient-reported barriers to cancer treatment include anxiety, cultural differences, lack of physician recommendation, and transportation problems. Other than diabetes, we could not adjust for notable comorbidities that affect breast cancer treatment decisions such as history of strokes and blood clots; however, results of studies25,26 suggest that diabetes is on the rise and that patients with this condition are less likely to be treated aggressively for their breast cancer. It is possible that history of stroke and blood clots may have also influenced treatment choices.

Although we observed that women with larger tumor size and comedo histologic growth pattern were more likely to undergo adjuvant radiation therapy, we were unable to examine the effect of pathologic factors on receipt of other adjuvant treatments. Because use of tamoxifen was not approved for DCIS until 2000, its use was consequently low in this cohort.20 Among women who received tamoxifen, we could not ascertain estrogen receptor status because this testing was rarely performed before 1999, when results of the first randomized clinical trial (National Surgical Adjuvant Breast and Bowel Project B-24) on the use of tamoxifen in the treatment of intraductal breast cancer were reported.20 Data linkages with the SEER-affiliated tumor registries at 2 California study sites (Los Angeles and San Francisco Bay area) showed that information on estrogen receptor testing was missing or unknown for more than 90% of women. Therefore, our analysis included all women who underwent BCS with tamoxifen treatment regardless of estrogen receptor status.

Although few investigations of DCIS have examined treatment disparity, our study corroborates previous findings that racial/ethnic differences in cancer therapies are modest in integrated healthcare systems with equal access to care.5 The lack of differences in treatment of DCIS by race/ethnicity observed in these integrated healthcare delivery systems may be due to coordinated clinical guidelines and multidimensional approaches to reduce barriers in care by educating physician leaders, nurse practitioners, case managers, and disease management program managers in these organizations. Older women and women who lived in census tracts with low median family incomes were less likely to receive adjuvant radiation therapy. Such groups of women may have different functionality, comorbidity burden, reduced access to transportation, less flexibility in work schedules, and other treatment preferences, all of which need to be considered in the treatment decision-making process.


We thank Ann Geiger, PhD, Chantal Avila, MA, Luana Acton, BS, Richard Contreras, MPH, and Gerri Salazar, CTR, for their contributions to the overall study and project management.

Author Affiliations: From the Division of Research and Evaluation (RH), Kaiser Permanente Southern California, Pasadena, CA; Division of Research (NSA, CPQ, LAH), Kaiser Permanente Northern California, Oakland, CA; Department of Ambulatory Care and Prevention (SWF, LN), Harvard Pilgrim Health Care, Boston, MA; Department of Pathology (LCC, SJS), Beth Israel Deaconess Medical Center, Boston, MA; and Department of Ambulatory Care and Prevention (SWF, LN, SJS), Harvard Medical School, Boston, MA.

Funding Source: The study was supported by grant U19 CA 79689 (Increasing Effectiveness of Cancer Control Interventions) from the National Cancer Institute to the Cancer Research Network and by grant R01 CA81302 from the Public Health Service.

Author Disclosures: The authors (RH, NSA, SWF, LN, LCC, SJS, CPQ, LAH) report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

Authorship Information: Concept and design (RH, SWF, LN, LCC, SJS); acquisition of data (NSA, LN, LCC, SJS, LAH); analysis and interpretation of data (RH, NSA, SWF, LN, LCC, SJS, CPQ, LAH); drafting of the manuscript (NSA, LN, SJS); critical revision of the manuscript for important intellectual content (RH, NSA, SWF, LN, LCC, SJS, CPQ, LAH); statistical analysis (RH, NSA, LN, LCC, CPQ); provision of study materials or patients (LAH); obtaining funding (LAH); administrative, technical, or logistic support (RH, NSA, LN, LCC, LAH); and supervision (LAH).

Address correspondence to: Reina Haque, PhD, Division of Research and Evaluation, Kaiser Permanente Southern California, 100 S Los Robles Ave, 2nd Fl, Pasadena, CA 91101. E-mail:

1. American Cancer Society. SR2: Cancer Facts and Figures 2005. Atlanta, GA: American Cancer Society Inc; 2005.

2. Mokbel K, Cutuli B. Heterogeneity of ductal carcinoma in situ and its effects on management. Lancet Oncol. 2006;7(9):756-765.

3. Li CI, Daling JR, Malone KE. Age-specific incidence rates of in situ breast carcinomas by histologic type, 1980 to 2001. Cancer Epidemiol Biomarkers Prev. 2005;14(4):1008-1011.

4. Li CI, Malone KE, Saltzman BS, Daling JR. Risk of invasive breast carcinoma among women diagnosed with ductal carcinoma in situ and lobular carcinoma in situ, 1988-2001. Cancer. 2006;106(10):2104-2112.

5. Shavers VL, Brown ML. Racial and ethnic disparities in the receipt of cancer treatment. J Natl Cancer Inst. 2002;94(5):334-357.

6. Joslyn SA. Ductal carcinoma in situ: trends in geographic, temporal, and demographic patterns of care and survival. Breast J. 2006;12(1):20-27.

7. Leonard GD, Swain SM. Ductal carcinoma in situ, complexities and challenges. J Natl Cancer Inst. 2004;96(12):906-920.

8. Bickell NA, Wang JJ, Oluwole S, et al. Missed opportunities: racial disparities in adjuvant breast cancer treatment. J Clin Oncol. 2006;24(9):1357-1362.

9. Joslyn SA, West MM. Racial differences in breast carcinoma survival. Cancer. 2000;88(1):114-123.

10. Griggs JJ, Sorbero ME, Stark AT, Heininger SE, Dick AW. Racial disparity in the dose and dose intensity of breast cancer adjuvant chemotherapy. Breast Cancer Res Treat. 2003;81(1):21-31.

11. Moormeier J. Breast cancer in black women. Ann Intern Med. 1996;124(10):897-905.

12. Joslyn SA. Racial differences in treatment and survival from early-stage breast carcinoma. Cancer. 2002;95(8):1759-1766.

13. Li CI, Malone KE, Daling JR. Differences in breast cancer stage, treatment, and survival by race and ethnicity. Arch Intern Med. 2003;163(1):49-56.

14. Mandelblatt JS, Kerner JF, Hadley J, et al; OPTIONS (Outcomes and Preferences for Treatment in Older Women Nationwide Study). Variations in breast carcinoma treatment in older Medicare beneficiaries: is it black or white? Cancer. 2002;95:1401-1414.

15. Farrow DC, Hunt WC, Samet JM. Geographic variation in the treatment of localized breast cancer. N Engl J Med. 1992;326(17):1097-1101.

16. Ballard-Barbash R, Potosky AL, Harlan LC, Nayfield SG, Kessler LG. Factors associated with surgical and radiation therapy for early stage breast cancer in older women. J Natl Cancer Inst. 1996;88(11):716-726.

17. Riley GF, Potosky AL, Klabunde CN, Warren JL, Ballard-Barbash R. Stage at diagnosis and treatment patterns among older women with breast cancer: an HMO and fee-for-service comparison. JAMA. 1999;281(8):720-726.

18. Innos K, Horn-Ross PL. Recent trends and racial/ethnic differences in the incidence and treatment of ductal carcinoma in situ of the breast in California women. Cancer. 2003;97(4):1099-1106.

19. Mokbel K. Contemporary treatment of ductal carcinoma in situ of the breast. Med Sci Monit. 2005;11(3):RA86-RA93.

20. Fisher B, Dignam J, Wolmark N, et al. Tamoxifen in treatment of intraductal breast cancer: National Surgical Adjuvant Breast and Bowel Project B-24 randomised controlled trial. Lancet. 1999;353(9169):1993-2000.

21. Bijker N, Peterse JL, Fentiman IS, et al. Effects of patient selection on the applicability of results from a randomised clinical trial (EORTC 10853) investigating breast-conserving therapy for DCIS. Br J Cancer. 2002;87(6):615-620.

22. Du XL, Key CR, Osborne C. Community-based assessment of adjuvant hormone therapy in women with breast cancer, 1991-1997. Breast J. 2004;10(5):433-439.

23. Malin JL, Schuster MA, Kahn KA, Brook RH. Quality of breast cancer care: what do we know? J Clin Oncol. 2002;20(21):4381-4393.

24. Elmore JG, Nakano CY, Linden HM, Reisch LM, Ayanian JZ, Larson EB. Racial inequities in the timing of breast cancer detection, diagnosis, and initiation of treatment. Med Care. 2005;43(2):141-148.

25. 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.

26. Gold HT, Thwin SS, Buist DS, et al. Delayed radiotherapy for breast cancer patients in integrated delivery systems. Am J Manag Care. 2009;15(11):785-789.

27. Baxter NN, Virnig BA, Durham SB, Tuttle TM. Trends in the treatment of ductal carcinoma in situ of the breast. J Natl Cancer Inst. 2004;96(6):443-448.

28. Gold HT, Dick AW. Variations in treatment for ductal carcinoma in situ in elderly women. Med Care. 2004;42(3):267-275.

29. van de Poll-Franse LV, Houterman S, Janssen-Heijnen ML, Dercksen MW, Coebergh JW, Haak HR. Less aggressive treatment and worse overall survival in cancer patients with diabetes: a large population based analysis. Int J Cancer. 2007;120(9):1986-1992.

30. Kuijpens JL, Janssen-Heijnen ML, Lemmens VE, Haak HR, Heijckmann AC, Coebergh JW. Comorbidity in newly diagnosed thyroid cancer patients: a population-based study on prevalence and the impact on treatment and survival. Clin Endocrinol. 2006;64(4):450-455.

31. Krieger N, Waterman P, Lemieux K, Zierler S, Hogan JW. On the wrong side of the tracts? evaluating the accuracy of geocoding in public health research. Am J Public Health. 2001;91(7):1114-1116.

32. Oliver MN, Matthews KA, Siadaty M, Hauck FR, Pickle LW. Geographic bias related to geocoding in epidemiologic studies. Int J Health Geogr. 2005;4:e29.

33. Hosmer DW, Lemeshow S. Applied Logistic Regression. 2nd ed. Toronto, ON: John Wiley & Son Inc; 2000.

34. National Heart, Lung, and Blood Institute. Calculate your body mass index. Accessed January 6, 2010.

35. SAS [computer program]. Version 9.1. Cary, NC: SAS Institute Inc; 2001.

36. Heimann R, Ferguson D, Powers C, Suri D, Weichselbaum RR, Hellman S. Race and clinical outcome in breast cancer in a series with long-term follow-up evaluation. J Clin Oncol. 1997;15(6):2329-2337.

37. Velanovich V, Yood MU, Bawle U, et al. Racial differences in the presentation and surgical management of breast cancer. Surgery. 1999;125(4):375-379.

38. Han I, Orton C, Shamsa F, Hart K, et al. Combined low-dose-rate brachytherapy and external beam radiation for cervical cancer: experience over ten years. Radiat Oncol Investig. 1999;7(5):289-296.

39. Franzini L, Williams AF, Franklin J, Singletary SE, Theriault RL. Effects of race and socioeconomic status on survival of 1,332 black, Hispanic, and white women with breast cancer. Ann Surg Oncol. 1997;4(2):111-118.

40. Logsdon MD, Eifel PJ. FIGO IIIB squamous cell carcinoma of the cervix: an analysis of prognostic factors emphasizing the balance between external beam and intracavitary radiation therapy. Int J Radiat Oncol Biol Phys. 1999;43(4):763-775.

41. Chlebowski RT, Chen Z, Anderson GL, et al. Ethnicity and breast cancer: factors influencing differences in incidence and outcome. J Natl Cancer Inst. 2005;97(6):439-448.

42. Enger SM, Thwin SS, Buist DS, et al. Breast cancer treatment of older women in integrated health care settings. J Clin Oncol. 2006;24(27):4377-4383.

43. Buist DS, Chubak J, Prout M, et al. Referral, receipt, and completion of chemotherapy in patients with early-stage breast cancer older than 65 years and at high risk of breast cancer recurrence. J Clin Oncol. 2009;27(27):4508-4514.

44. West CN, Geiger AM, Greene SM, et al. Race and ethnicity: comparing medical records to self-reports. J Natl Cancer Inst Monogr. 2005;35:72-74.

45. Chen FM, Breiman RF, Farley M, Plikaytis B, Deaver K, Cetron MS. Geocoding and linking data from population-based surveillance and the US Census to evaluate the impact of median household income on the epidemiology of invasive Streptococcus pneumoniae infections. Am J Epidemiol. 1998;148(12):1212-1218.

46. Vernon SW. Participation in colorectal cancer screening: a review. J Natl Cancer Inst. 1997;89(19):1406-1422.

47. Brenes GA, Paskett ED. Predictors and stage of adoption for colorectal cancer screening. Prev Med. 2000;31(4):410-416.

48. Partridge A, Adloff K, Blood E, et al. Risk perceptions and psychosocial outcomes of women with ductal carcinoma in situ: longitudinal results from a cohort study. J Natl Cancer Inst. 2008;100(4):243-251.