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Receipt of Appropriate Primary Breast Cancer Therapy and Adjuvant Therapy Are Not Associated With Obesity in Older Women With Access to Health Care

Diana S.M. Buist, Laura Ichikawa, Marianne N. Prout, Marianne Ulcickas Yood, Terry S. Field, Cynthia Owusu, Ann M. Geiger, Virginia P. Quinn, Feifei Wei, Rebecca A. Silliman

From the Group Health Center for Health Studies, Seattle, WA; Boston University School of Public Health and Boston University Medical Center, Boston; Meyers Primary Care Institute, University of Massachusetts Medical School, Fallon Community Health Plan, Fallon Foundation, Worcester, MA; Josephine Ford Cancer Center, Henry Ford Health System, Detroit, MI; Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT; Case Western Reserve University School of Medicine, Division of Hematology/Oncology, Cleveland, OH; Division of Public Health Sciences, Department of Social Sciences and Health Policy, Wake Forest University School of Medicine, Winston-Salem, NC; Kaiser Permanente Southern California, Pasadena, CA; and HealthPartners Research Foundation, Minneapolis, MN

Address reprint requests to Diana S.M. Buist, PhD, Group Health Center for Health Studies, 1730 Minor Ave, Suite 1600, Seattle, WA 98101; e-mail: buist.d{at}ghc.org.

	ABSTRACT

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Purpose: Many studies have reported body mass index (BMI) increases the risk of breast cancer recurrence and breast cancer–specific mortality. Few studies have reported or examined whether breast cancer treatment differs by BMI. The purpose of this study was to examine the association between BMI at breast cancer diagnosis and receipt of appropriate primary tumor therapy and adjuvant therapy.

Methods: We identified 897 women age 65 years diagnosed with stage I or II breast cancer from 1990 to 1999 at five health care organizations. We used medical records to confirm demographics, tumor characteristics, treatment, comorbid conditions, and to calculate BMI at diagnosis (< 25 kg/m², n = 328; 25 to < 30 kg/m², n = 305; 30 to < 35 kg/m², n = 188; 35 kg/m², n = 76). We defined primary therapy based on National Guidelines as receiving breast-conserving surgery with radiation therapy and axillary node dissection, simple mastectomy with axillary node dissection, or modified radical mastectomy (73% overall); adjuvant therapy was defined as receipt of hormonal therapy, chemotherapy, or both (60% overall).

Results: The median BMI was 26.7 kg/m² (range, 14.6 to 61.2). The proportion of women receiving primary therapy and adjuvant therapy was lowest for women less than 25 kg/m² (69% and 56%, respectively) and greatest for obese I (78% and 64%, respectively). There were no differences in receipt of primary or adjuvant treatment across BMI in univariate or multivariable models (after adjusting for age, stage, comorbidity, diagnosis year, and hormone receptor positivity).

Conclusion: Receipt of appropriate primary therapy and adjuvant therapy is not associated with BMI in older women with access to health care. Additional research in larger samples and more diverse settings is needed.

	INTRODUCTION

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There is a growing body of literature demonstrating that obesity worsens breast cancer prognosis^1-10 and is associated with breast cancer surgery–related complications.^11-14 Higher weight and body mass index (BMI) have been shown to be associated in some studies with increased breast cancer recurrence and mortality rates in pre- and postmenopausal women, with relative risk estimates for higher BMI ranging from 1.1 to 4.2.^1-10 Not all studies have found independent relationships between obesity and breast cancer prognosis.^15-19 Most studies examining weight or BMI as a breast cancer prognostic factor have adjusted for stage; however, there has been substantial variation in control of other covariates, including study population ages, weight adjusted for height, BMI cut points, self-reported versus clinically measured BMI, and primary and adjuvant therapy after diagnosis. Differential stage-appropriate therapy receipt by BMI could be an important factor driving associations between obesity and breast cancer prognosis.

As obesity prevalence increases,²⁰ it is important to determine whether there are any associations between BMI and receipt of primary and adjuvant breast cancer therapy. We undertook this analysis to examine whether BMI at breast cancer diagnosis was associated with receiving appropriate primary breast and adjuvant therapy in older women diagnosed with early-stage breast cancer and treated within integrated group practices.

	METHODS

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Study Populations
This report incorporates data on 897 women from two studies; both had institutional review board approval at all participating sites. The first is the Breast Cancer Treatment Effectiveness in Older Women (BOW) study²¹ conducted within the National Cancer Institute–funded Cancer Research Network.²² The parent BOW study included 1,859 women age 65 years diagnosed with incident early-stage breast cancer (I to IIB)²³ between January 1, 1990 and January 31, 1994, within six health care organizations: Group Health, Seattle, WA; Fallon Community Health Plan, Fallon Foundation, Worcester, MA; Henry Ford Health System, Detroit, MI; HealthPartners Research Foundation, Minneapolis, MN; Kaiser Permanente Southern California, Pasadena, CA; and Lovelace Clinic Foundation, Albuquerque, NM. We added BMI abstraction after BOW started. As a result, BMI information was only available for 480 women, representing a sample of women from all sites except Lovelace. Charts were not selected for abstraction in any way that could have biased our inclusion of women with different BMI or distributions of therapy.

This report also includes women diagnosed with incident early-stage breast cancer from the American Cancer Society–funded BOW-sister study (ACS) conducted exclusively at Group Health. We applied the same study entry criteria to a more contemporary cohort of 911 women age 18 years diagnosed with breast cancer between January 1, 1996 and December 31, 1999, using the BOW abstraction instrument. Our analysis includes 417 women age 65 at diagnosis and a subanalysis of the 467 women younger than 65 years. Details about our study methodology have been published,²¹ but are summarized briefly in the following paragraphs.

Data Elements
Trained medical records abstractors completed standardized abstractions and entered information directly into a computerized data collection system that included a variety of preloaded automated data from cancer registries, and administrative and clinical databases. Women were ineligible if they had another clinically active malignancy, except nonmelanoma skin cancer, diagnosed 5 years before or 30 days after their breast cancer diagnosis; had bilateral breast cancer; or were enrolled in their health system for less than 12 months before or after diagnosis, unless they died less than 12 months after diagnosis.

Abstractors recorded measured height and weight for each woman anchored by her date of diagnosis. We calculated BMI as weight in kilograms divided by height in square meters and limited these analyses to BMI measured 6 months before diagnosis. We characterized women as underweight (less than 18.5 kg/m²), normal weight (18.5 to < 25 kg/m²), overweight (25 to < 30 kg/m²), obese I (30 to < 35 kg/m²), obese II (35 to < 40 kg/m²), and obese III ( 40 kg/m²).²⁴ We modeled the underweight and normal weight women together and obesity categories II/III together after we examined the data and found no substantive treatment differences between the groups.

We collected primary and adjuvant treatment from medical records: surgery performed (breast-conserving therapy [BCS] or mastectomy), axillary or sentinel node biopsy, number of radiation and chemotherapy sessions, and specific hormonal and chemotherapeutic agents. We were able to identify whether patients were referred to oncologists and captured information about whether treatment was received, refused, or not recommended. We used national clinical guidelines²⁵ to define primary tumor therapy as BCS with radiation therapy and axillary node evaluation, simple mastectomy with axillary node dissection, or modified radical mastectomy. Adjuvant therapy was defined as receipt of any hormonal therapy, chemotherapy, or both. We also examined receipt of any adjuvant hormonal therapy, and limited our analyses to women with hormone receptor–positive tumors (n = 718).

We examined a number of potential confounding variables including date of diagnosis and stage at diagnosis, tumor size, lymph node evaluation, estrogen and progesterone receptor protein positivity (estrogen receptor [ER] positive or progesterone receptor [PR] positive; ER negative/PR negative; other [not done, ordered but no results, unknown]), histology and grade, stage (I, IIA, or IIB²³), age at diagnosis, and race or ethnicity (non-Hispanic white, Hispanic, African American, Asian/Pacific Islander, or other). Medical records were used to collect information on comorbid conditions in the year before diagnosis to calculate the Charlson comorbidity index.²⁶ We examined separately whether the presence of congestive heart failure, cerebrovascular event, myocardial infarction, chronic obstructive pulmonary disease, hypertension (not included in the Charlson comorbidity index), or diabetes mellitus influenced the relationship between BMI and therapy; comorbid conditions were not mutually exclusive.

We conducted multiple intra- and inter-rater reliability exercises for BOW and ACS and found all intrarater reliability measures 93% and inter-rater reliability 88%.²¹ Treatment outcomes were included in the reliability exercises, but BMI measures were not.

Analysis
We compared characteristics of women and distributions of outcomes across the BOW and ACS study populations. We used a ² test and Monte Carlo estimates for the exact test to examine differences before combining the cohorts in our analyses. The only differences were that the ACS cohort had a larger proportion of women without axillary node dissection (31% v 20% BOW), a larger proportion of women with ER-positive and PR-positive tumors (71% v 60% BOW), and a smaller proportion of women with missing information on grade (10% v 21% BOW). The ACS cohort also had a great proportion of the older study population ( 80 years; 22% v 11% BOW). We adjusted all models for year of diagnosis to account for differences between study populations and any differences in treatment patterns that may have occurred over time.

We fit univariate and multivariable logistic regression models to calculate the odds ratios (OR) and 95% CIs to estimate the effect between BMI and receipt of primary and adjuvant breast cancer treatment. We included any covariate significantly associated (P < .05) with BMI or receipt of primary, adjuvant, or hormonal therapy in our final multivariable models, with the exception of tumor size (component of stage), grade (highly correlated with stage), and race/ethnicity (small numbers in subcategories). We included the same covariates in each multivariable model so BMI estimates would be adjusted comparably across models. All multivariable models included age, stage, Charlson comorbidity index (0, 1, or 2+), hypertension, and diagnosis year. Primary and adjuvant therapy models also adjusted for hormone receptor positivity.

Subanalyses
We conducted several subanalyses to examine if there were differences in whether treatment was received, refused by the patient, not recommended by the physician, or whether there were no data available for hormone therapy, chemotherapy, and radiation therapy. We limited subanalyses to women with hormone receptor–positive tumors (hormone therapy), positive lymph nodes (chemotherapy), and BCS (radiation therapy). We also examined nodal status as positive versus negative to remove any effect on number of positive nodes.

We also completed multivariable analyses limited to 467 women younger than 65 years from the ACS cohort to examine whether results between BMI and treatment differed among younger women.

	RESULTS

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Two thirds of women were age 65 to 69 years (35%) and 70 to 74 years (33%; Table 1). Most women had stage I cancer (72%) and tumors 2 cm (81%). One fourth of women did not have lymph nodes evaluated; 88% of these women had stage IA and 12% of these women had stage IIA. Only 6% of women did not have their hormone receptors evaluated (2%) or had unknown values (4%). The most prevalent comorbid condition in the year before diagnosis was hypertension (46%), followed by chronic obstructive pulmonary disease (11%), diabetes (10%), cerebrovascular disease (6%), myocardial infarction (5%), and congestive heart failure (3%).

Therapy
The majority of women (73%) received primary therapy in accordance with guidelines, with receipt associated with younger age, later stage, larger tumors, hormone receptor–negative tumors, and fewer comorbidities in the year before diagnosis (Table 2).

Treatment by BMI
There was no significant univariate difference in receipt of primary therapy, adjuvant therapy, or surgical procedure by BMI (Table 3). Nearly every woman who received radiation therapy completed a full course (95%; data not shown). Completion of chemotherapy, among women who received any, ranged from a low of 83% (obese I) to 100% (obese II/III; data not shown).

View this table: [in this window] [in a new window]   Table 4. Multivariable Adjusted Odds of Receiving Primary Therapy, Adjuvant Therapy, and Hormonal Therapy by BMI at Time of Diagnosis Among Women Age 65 Years at Diagnosis of Incident, Invasive, Early-Stage Breast Cancer

	DISCUSSION

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These analyses were designed to examine whether breast cancer treatment was received differentially across BMI in older women with early-stage breast cancer who had access to health care. We hypothesized that underweight women and the most obese women ( 35 kg/m²) would be less likely to receive primary therapy and adjuvant therapy. However, we demonstrated that receipt of appropriate primary and adjuvant breast cancer therapy was not associated with BMI in older women, and found comparable results in our subanalysis among younger women. Our study was conducted within integrated health organizations, which limits the external generalizability, but increases the internal validity of our findings, given that integrated organizations have fewer treatment variations due to health care access and lower provider variation in treatment delivery.

We are unaware of other published data focused on primary and adjuvant breast cancer treatment in relation to BMI. Some studies have examined whether obesity is associated with treatment effectiveness, with four studies examining the impact of BMI on tamoxifen efficacy.^16,27-29 One small study demonstrated reduced tamoxifen metabolism among obese women,²⁷ whereas two others did not.^28,29 The largest analysis to date on obesity and tamoxifen efficacy found that obesity did not influence the efficacy of tamoxifen in preventing recurrence or death, but did decrease the efficacy of tamoxifen in preventing new primary breast tumors and in reducing non–breast cancer deaths.¹⁶ There is also a growing body of literature demonstrating chemotherapy underdosing in obese patients.^30-33 We were unable to examine whether there were differences in relative chemotherapy dose-intensity across BMI because we did not have that information. Given that there is no evidence of increased chemotherapy toxicity among obese women who receive chemotherapy on the basis of full body surface area^30,34,35 and there has been evidence demonstrating worse long-term outcomes (eg, greater recurrence) among obese women,^30,33,34 it will be important for other studies to evaluate relative dose-intensity.

Screening before diagnosis leads to small and less extensive tumors at diagnosis. Wee et al³⁶ and Fontaine et al³⁷ previously reported reduced mammography rates in obese and very lean women. We did not have information on mode of detection or mammography screening history before diagnosis. However, in contrast to other studies, obesity was not associated with tumor size³⁸ or number of positive nodes^38-40 in our population. The lack of relationship among obesity, tumor size, and nodal status is unusual because there was a significant association between increasing BMI and stage in our population—a finding supported by other studies.^27,41,42 However, there were several small tumors with positive lymph node extension and several larger tumors without nodal extension. When we examined nodal status as positive versus negative to remove any effect of number of positive nodes, we still observed no difference by BMI. Differences in staging by BMI could reflect faster growing tumors, more aggressive smaller tumors, or delays in detection due to differential mammography screening adherence or accuracy.⁴³

The biologic mechanisms by which obesity is believed to affect breast cancer progression are well documented. Obesity increases circulating endogenous peptide and steroid hormones and their binding factors through aromatization of estrogens in the fat tissue and increasing insulin levels,⁴⁴ which has been hypothesized as one mechanism for higher rates of hormone receptor–positive tumors in more obese women. Unlike several other studies,^4,45,46 we did not observe any difference in the distribution of hormone receptor positivity across BMI. It is important to determine whether obesity is truly associated with early-stage hormone receptor–positive tumors in other settings.

Many factors are associated with whether women receive complete adjuvant therapy, such as access to care, age, comorbidities, life expectancy, provider variation in recommendation, and treatment complications such as tolerance. Importantly, we found no differences in rates of refusal or recommendation for therapy by BMI in the older or younger women. Among women for whom therapy was indicated, a small proportion of women were not referred to a medical oncologist for chemotherapy (2%) or a radiation oncologist for radiation therapy (6%), with no patterns by BMI. We observed substantial variation in the proportion of women not recommended by type of therapy (17% to 23% for hormone, 29% to 39% for chemotherapy, and 1% to 3% for radiation therapy), with no patterns across BMI.

There may be other treatment factors that differ by BMI that could influence breast cancer outcomes. For example, wound infections, lymphedema, and radiation and sentinel node biopsy complications have all been shown to be associated with increased BMI.^47-52 There is strong evidence demonstrating increased thromboembolic events in tamoxifen users⁵³ and in obese women,⁵⁴ which might influence physicians' willingness to recommend tamoxifen use among obese women, yet we found no difference in rates of adjuvant hormonal therapy, comorbidity, or composite Charlson comorbidity index by BMI. A higher index of suspicion for thromboembolic disease may be warranted in obese women. Aromatase inhibitors will need to be evaluated across BMI to understand whether there are differences in risks (higher fracture rates) and benefits (decreased thromboembolic events) by BMI.

This study has several strengths that deserve mention. The study population had no entry criteria associated with BMI. All women in the study had access to health care and some medical insurance, reducing treatment variations due to socioeconomic status or other factors potentially associated with medical care. Collecting measured BMI from medical records with information on treatment outcomes that do not rely on recall eliminates systematic selection bias in this study, which is often present in population-based studies requiring patient recruitment. In contrast, our observed effect sizes limited our power to 29%, 32%, and 50% for adjuvant, hormonal, and primary therapy, respectively, translating into 80% power for a 0.11 global effect size.

The long-term effects of receiving inadequate care include increased risk of recurrence⁵⁵ and death from breast cancer⁵⁶; both of which have been shown to be higher in obese women in many studies.^1-10 Differential receipt of primary or adjuvant therapy by BMI could lead to apparent relationships among obesity, disease recurrence, and breast cancer mortality. It will be important to examine whether there are BMI treatment differences in other health care settings. The ability to disentangle treatment from biologic factors is critical to understanding how BMI influences breast cancer outcomes.

Our findings demonstrate that older women in integrated health organizations are not receiving differential breast cancer treatment by BMI. Given that obesity is highly correlated with the presence of comorbidities, and having comorbidities is often an exclusion criterion for randomized trials, obese women may be excluded differentially from trials. We found overweight and obese women are not excluded from receiving therapy that trials have demonstrated to be most effective in women with early-stage breast cancer. Our results emphasize the importance of additional research to identify what factors are accounting for differential breast cancer outcomes in women by BMI. Additional research in larger samples and more diverse settings is needed.

	AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

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The author(s) indicated no potential conflicts of interest.

	AUTHOR CONTRIBUTIONS

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Conception and design: Diana S.M. Buist, Laura Ichikawa, Terry S. Field, Virginia P. Quinn, Feifei Wei, Rebecca A. Silliman

Financial support: Diana S.M. Buist, Rebecca A. Silliman

Administrative support: Diana S.M. Buist, Virginia P. Quinn, Rebecca A. Silliman

Provision of study materials or patients: Diana S.M. Buist, Marianne Ulcickas Yood, Terry S. Field, Virginia P. Quinn, Feifei Wei, Rebecca A. Silliman

Collection and assembly of data: Diana S.M. Buist, Marianne Ulcickas Yood, Terry S. Field, Ann M. Geiger, Feifei Wei, Rebecca A. Silliman

Data analysis and interpretation: Diana S.M. Buist, Laura Ichikawa, Marianne N. Prout, Virginia P. Quinn, Feifei Wei, Rebecca A. Silliman

Manuscript writing: Diana S.M. Buist, Laura Ichikawa, Marianne N. Prout, Marianne Ulcickas Yood, Terry S. Field, Cynthia Owusu, Virginia P. Quinn, Rebecca A. Silliman

Final approval of manuscript: Diana S.M. Buist, Laura Ichikawa, Marianne N. Prout, Marianne Ulcickas Yood, Terry S. Field, Cynthia Owusu, Ann M. Geiger, Virginia P. Quinn, Feifei Wei, Rebecca A. Silliman

	ACKNOWLEDGMENTS

 
We thank the following site project managers, programmers, and medical record abstractors: Group Health—Linda Shultz, Kristin Delaney, Margaret Farrell-Ross, Mary Sunderland, Millie Magner, Beth Kirlin, and Jessica Chubak; Meyers Primary Care Institute and Fallon Community Health Plan—Jackie Fuller, Doris Hoyer, and Janet Guilbert; Henry Ford Health System—Sharon Hensley Alford, Karen Wells, Patricia Baker, and Rita Montague; HealthPartners—Maribet McCarty and Alex Kravchik; Kaiser Permanente Southern California—Julie Stern, Janis Yao, Michelle McGuire, and Erica Hnatek-Mitchell; and Lovelace Health Plan—Judith Hurley, Hans Petersen, and Melissa Roberts. We also thank Soe Soe Thwin, PhD, for managing and processing the BOW data.

	NOTES

 
Supported by the American Cancer Society (Grant No. CRTG-03-024-01-CCE; D.B.) and the National Cancer Institute (Grant No. R01 CA093772; R.S.).

Presented in part at the International Epidemiology Congress Meeting, June 21-24, 2006, Seattle, WA.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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Submitted February 28, 2007; accepted June 4, 2007.

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