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Early stage breast cancer treatments for younger Medicare beneficiaries with different disabilities.

Government officials, including the U.S. Surgeon General, and patient advocates have called for including persons with disabilities in treatment disparity studies (U.S. Department of Health and Human Services 2000, 2005). Growing numbers of studies document underuse of routine screening and preventive services among some persons with disabilities, especially screening mammograms among disabled women (Nosek and Howland 1997; Chan et al. 1999; Iezzoni et al. 2000; Chevarley et al. 2006). Studies are also beginning to show important disparities in medical treatments (Caban et al. 2002; McCarthy et al. 2006; Iezzoni et al. 2008). Using data from the 11 Surveillance, Epidemiology, and End Results (SEER) cancer registries merged with Medicare claims, we recently showed that women under age 65 who have Medicare because of disability and who then develop breast cancer are much less likely than other women to receive recommended treatments and have shorter cancer survival (McCarthy et al. 2006). We did not show, however, that women with disabilities had later stage cancer diagnoses (McCarthy et al. 2007).

Although these findings are provocative, they leave important questions unanswered. Given clinical heterogeneity among disabled Medicare beneficiaries, one important question is whether treatment and survival disparities vary by underlying disability. Persons under age 65 become eligible for Medicare 24 months after first receiving cash benefits from Social Security Disability Insurance (SSDI). To explore whether breast cancer treatments and outcomes differ by disabling condition, we used SEER-Medicare data merged for the first time with information from the Social Security Administration (SSA) on causes of disability.

METHODS

Data Sources

Our methods for identifying women with and without disability (i.e., SSDI/ Medicare) are described elsewhere (McCarthy et al. 2006, 2007). Briefly, SEER data include 11 population-based tumor registries, representing 14 percent of the U.S. population (Warren et al. 2002). SEER registries identify cases primarily by reviewing hospital pathology reports and discharge diagnoses; they collect information on patient demographics and tumor characteristics at diagnosis, including primary tumor site, stage, size, histology, tumor grade, lymph node status, and, since 1990, hormone receptor status. SEER records initial treatment (within 4 months of diagnosis from 1973 to 1998, within 12 months of diagnosis after 1998) and generally captures all surgery and radiation therapy (Cooper et al. 2002; Virnig et al. 2002). Registries collect chemotherapy information but do not release it because of concerns about incomplete data. SEER tracks vital status annually, obtaining underlying cause of death from death certificates. The linked database contains Medicare enrollment and utilization information for Medicare beneficiaries diagnosed with cancer (Potosky et al. 1993).

SSA (2003) aggregate data indicate that neoplasms caused 9.8 percent of new SSDI disability determinations in 2002. As described elsewhere, we developed an algorithm allowing us to focus exclusively on individuals with Medicare when newly diagnosed with cancer, thus eliminating persons disabled by cancer (McCarthy et al. 2007). When individuals qualify for SSDI, SSA records their primary impairment (i.e., reason persons were "medically determined" disabled); SSA does not release impairment codes to nongovernmental investigators. For our study, officials at SSA, the Centers for Medicare and Medicaid Services (CMS), and the National Cancer Institute (NCI) had their data processing contractor merge SSA "impairment codes" and "diagnosis groups" with our final analytic file, which we provided to them (Iezzoni et al. 2008). To protect confidentiality, we did not have access to these merged files but instead worked with the government contractor to perform analyses using SSA information.

Study Sample

This retrospective cohort study included women ages 21-64 when diagnosed with their first primary breast cancer between January 1, 1988 and December 31, 1999 residing in SEER-11 coverage areas and diagnosed with stage I or II disease as classified by the American Joint Committee on Cancer. As described elsewhere, (McCarthy et al. 2006) we excluded: women with Paget's disease or inflammatory carcinoma; those whose tumor size was classified as widespread or unknown; and women who did not receive surgery (< 1 percent). For these analyses, we further excluded 77 women with SSDI/Medicare who did not match with SSA data and therefore were missing information on SSA disability determination. Our final study sample contains 90,243 women under age 65 with early stage breast cancer who received either mastectomy or breast conserving surgery; 2,582 (2.9 percent) had SSDI/Medicare.

Disability Diagnosis Groups

After merging SSA data with our analytic file, the government contractor produced frequency distributions for each "impairment code" (SSA's most granular listing of conditions) and "diagnosis groups" (SSA's groupings of impairment codes). Very few cases fell into individual impairment codes; many diagnosis groups also had too few cases for separate analysis. Of the 2,582 women with SSDI/Medicare, 658 (25.5 percent) had codes indicating "miscellaneous" (n = 186) and "unknown" (n = 472) conditions. To bolster sample sizes, we combined some diagnosis groups and present data for four broad conditions with sufficient numbers for analysis (see Table 1 footnotes). Readers may obtain lists of diagnosis groups included in our four conditions upon request.

Breast Cancer Treatment

We used SEER data to identify breast cancer treatments. Our primary outcome of interest was initial surgical treatment for early stage breast cancer, comparing breast conserving surgery with mastectomy. SEER registries recorded initial surgical treatment within 4 months of diagnosis from 1973 to 1998 and within 12 months of diagnosis after 1998. As described elsewhere (McCarthy et al. 2006), we defined breast conserving surgery as segmental mastectomy, lumpectomy, quadrantectomy, tylectomy, wedge resection, nipple resection, excisional biopsy, or partial mastectomy that was not otherwise specified (n = 46,297). We defined mastectomy as subcutaneous, total (simple), modified radical, radical, extended radical mastectomy, or mastectomy that was not otherwise specified (n = 43,946).

For the subset of women receiving breast conserving surgery, we studied two additional recommended interventions (NIH Consensus Conference 1991): axillary lymph node dissection; and radiation therapy, which is recommended for women who undergo breast conserving surgery to reduce the risk of local recurrence. SEER collects information on whether persons have contraindications to surgery or refuse radiotherapy. Only 250 (0.5 percent) women with breast conserving surgery refused radiation therapy, and of these, 10 had SSDI/Medicare; we assigned these women to the "no radiotherapy" group.

Survival

We examined survival (all-cause and breast cancer-specific) following diagnosis. We measured survival time as number of days from diagnosis until death or December 31, 2001, whichever came first. Because SEER indicates only the month of diagnoses, we set all diagnosis dates as the first of the month; this might introduce some small error in calculating survival times, but these errors are unlikely to differ systematically between women with and without disabilities. For all-cause mortality, we censored observations of women alive when follow-up ended (n = 77,048). We also studied breast cancer-specific deaths, censoring observations of women alive at the end of follow-up or who died from causes other than breast cancer or cancers of common metastatic sites (liver, lung, bone, or brain) (n = 81,201).

Analysis

All statistical analyses used SAS version 9.1 (SAS Institute, Cary, NC). Because our analyses used SEER-Medicare linked with SSA data to examine whether breast cancer treatment and outcomes varied across disability groups, we supplied SAS code to the government contractor, who performed the analyses for us. After internal quality assurance audits, they returned aggregated results (i.e., we did not receive information on individual cases).

Using bivariable analyses, we compared demographic and tumor characteristics at diagnosis by SSDI/Medicare (disability) status. We conducted multivariable logistic regression to examine adjusted associations between disability status and each treatment (surgery, lymph node dissection, radiotherapy) after adjusting for: age at diagnosis (continuous); race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, Asian American/Pacific Islander, other); marital status at diagnosis (married, widowed, never married, other); SEER tumor registry; year of diagnosis; tumor size (continuous, in cm); grade (well differentiated, moderately differentiated, poorly/undifferentiated); histology (ductal, lobular, mixed ductal/lobular); estrogen receptor status (positive, negative, unknown); and progesterone receptor status (positive, negative, unknown). In analyses examining all women combined, we also adjusted for stage at diagnosis. In addition, we conducted analyses stratifying women by stage at diagnosis, speculating that associations might differ for women with stage I versus stage IIB disease. In each model, we compared women with and without SSDI/Medicare. We converted odds ratios to relative risks (RR) with 95 percent confidence intervals (Flanders and Rhodes 1987).

We conducted multivariable Cox proportional hazards regression to estimate adjusted relative hazard ratios for each mortality outcome (all-cause, cancer-specific). We fit three separate proportional hazards models for each mortality outcome. Model 1 estimated the unadjusted relative hazard ratio comparing women with and without SSDI/Medicare. Model 2 adjusted this relative hazard ratio for age at diagnosis (continuous), race/ethnicity, marital status, tumor registry, year of diagnosis, stage at diagnosis (overall model only), tumor size (continuous), tumor grade, histology, and hormone receptor status. Model 3 further adjusted the relative hazard ratio for treatment (breast-conserving surgery only, mastectomy only, breast-conserving surgery plus radiotherapy, and mastectomy plus radiotherapy). With large sample sizes such as those in our study, the test for the proportional hazards assumption almost always yields a significant p-value, which implies that the assumption of the proportionality of hazards is invalid. Therefore, we examined the assumption of proportionality by graphically comparing women with and without disabilities (Lee 1992). Specifically, we plotted the log(- log(S(t))) versus time and found the distance between these two curves remained relatively constant throughout the study period; this suggests that the assumption of proportional hazards was reasonable for our models. We present adjusted relative hazard ratios (aHR) and 95 percent CI: aHR> 1.00 indicates shorter survival times for disabled compared with nondisabled women.

RESULTS

Women with disabilities (SSDI/Medicare) differed importantly from nondisabled women (Table 1): they were older and more likely to be non-Hispanic black and not married at the time of diagnosis. Distributions across race and ethnicity, marital status, and tumor characteristics sometimes differed by disability group. For example, women with neurological conditions were most likely to be white and married. Among women with musculoskeletal conditions, 57.8 percent had stage I disease, compared with 49.9 percent of women with mental disorders.

Treatments

Table 2 shows the percent of women receiving breast conserving surgery (BCS), as well as the adjusted relative risks of receiving BCS for women by disability group compared with nondisabled women. While women with circulatory/respiratory conditions and musculoskeletal conditions obtained BCS at similar rates as nondisabled women, those with mental disorders and neurological conditions were much less likely to have BCS when diagnosed with stage I or IIA disease.

For women receiving BCS, Table 3 shows the percent and relative risks of receiving axillary node dissections and radiotherapy. Only women with circulatory/respiratory conditions had much lower adjusted relative risks of receiving axillary node dissections than nondisabled women. In contrast, adjusted relative risks for radiation therapy fell significantly below 1.00 for women with mental disorders, neurological conditions, and circulatory/respiratory disabilities.

Survival

Women with mental disorders and circulatory/respiratory conditions had much higher cancer-specific mortality rates than nondisabled women, although statistically significant differences disappeared for women with mental disorders following adjustment (Table 4). All-cause mortality rates, however, remained significantly higher for women within all four disability groups, even after adjusting for demographic and tumor characteristics and treatment differences (Table 4).

DISCUSSION

Not surprisingly, as suggested by their much higher all-cause mortality rates, women with SSDI/Medicare who develop breast cancer likely carry a much heavier burden of underlying health problems than do other women. However, breast cancer experiences--treatment and outcomes--among women with versus without disabilities varied among the four disabling conditions. For stages I and IIA disease, women with mental health problems and mental retardation, along with women with neurological conditions, were significantly less likely than nondisabled women to receive breast conserving surgery, as well as the radiotherapy required to prevent local recurrence of their tumors. Women with circulatory and respiratory disabilities were significantly less likely than women without disabilities to receive axillary node dissection and radiotherapy following BCS, which might reflect a variety of possibilities including patient preferences and substandard quality of care.

Understanding the causes of these differences between women with and without disabilities, as well as across disabilities, will require further study. Different types of disabilities might affect women's treatment options, preferences, and choices. For instance, women who rely on their arms for mobility by self-propelling manual wheelchairs or using walkers or crutches may worry that mastectomy could compromise arm function. Extensive axillary lymph node procedures can produce lymphedema and other complications that compromise upper extremity function. Even if women prefer breast conserving surgery, physical impairments could prevent the radiotherapy required to prevent local recurrences. Being unable to lie flat, remain still, and/or adequately abduct the arm pose contraindications to radiation therapy (Caban et al. 2002).

Compared with other disability groups, women with musculoskeletal disabilities--probably primarily arthritis and back problems--appear to have treatments and outcomes most similar to nondisabled women. Women with musculoskeletal disorders do differ substantially demographically from nondisabled women, with the highest percentage of Hispanic and large numbers of non-Hispanic black women compared with the other subpopulations. But they also have the highest percentage with stage I disease, 6.4 and 7.9 percentage points higher than for nondisabled women and women with mental disabilities, respectively. One possible explanation is that women with musculoskeletal disabilities have Medicare coverage and therefore can afford physician visits, while some unknown fraction of nondisabled women lack health insurance and do not receive routine care. Perhaps discussing musculoskeletal conditions requires less time than other disabling conditions, leaving physicians and patients more time to perform preventive services, like breast exams, and discuss screening tests, like mammograms. Clearly, this speculation requires further investigation.

Although mastectomy and breast conserving surgery are equivalent with respect to survival (NIH Consensus Conference 1991), the relatively low rates of breast conserving surgery observed among women with mental health/mental retardation disorders raise interesting questions. A small body of literature has explored various issues relating to breast cancer in this population. Women with psychiatric disabilities might possibly have higher rates of breast cancer, perhaps related to medications or hormonal causes, although evidence is contradictory (Halbreich, Shen, and Panaro 1996; Lokugamage et al. 2006). Research also seems inconclusive but suggests that women with mental health problems might receive mammograms less often than other women (Owen, Jessie, and De Vries Robbe 2002; Lasser et al. 2003; Sullivan et al. 2003; Friedman et al. 2005; Kahn et al. 2005). Lower rates of mammography could result from a variety of causes, but might raise concerns about whether these women would adhere to demanding radiotherapy schedules or receive adequate follow-up care if BCS were performed. Little information is available specifically about breast cancer treatment decisions for this population. It is possible that certain mental health and cognitive developmental conditions might affect women's decision-making capacity or their abilities to weigh different treatment options. Investigations of decision-making for breast cancer treatment in general note that women's concerns about their appearance play a role, although follow-up studies have produced contradictory findings about associations between surgery choices and women's long-term body image, quality of life, sexual functioning, and other psychosocial outcomes (Ganz et al. 1992; Moyer 1997; Curran et al. 1998; Nold et al. 2000; Arora et al. 2001; Nissen et al. 2001; Henson 2002; Figueiredo et al. 2004). Physical appearance may prove particularly complex for women with mental health problems or mental retardation. Some clinicians may have stigmatizing views regarding sexuality of these women, which could potentially affect their treatment recommendations. Studies highlight the crucial role of patient-clinician communication, including the extent of interaction and shared decision making, in treatment choices for women with breast cancer (Katz et al. 2005; Lantz et al. 2005; Katz and Hawley 2007), but this issue has been little explored for women with disabilities. The forced sterilization of disabled women, especially those with developmental disabilities and mental retardation, provides a troubling historical backdrop to these attitudes (Asch and Fine 1988).

Our database did not contain clinical information about women with and without SSDI/Medicare that might independently affect treatment choices and predict poor prognosis (e.g., pulmonary function, smoking history, comorbid illness). The data also did not indicate patients' preferences or clinicians' treatment recommendations; we also lacked information on adjuvant chemotherapy, which certainly can affect survival. Although the SSA data provide useful insight into underlying disabling conditions, small numbers of cases and frequent missing or clinically imprecise data limited this effort. Our findings may not generalize to women with disabilities who do not apply or qualify for SSDI and Medicare, for whatever reason. In particular, the data do not identify women receiving only Supplemental Security Income (SSI), the income support program for persons with disabilities who are poor or have not paid sufficient payroll taxes; nationwide estimates suggest that < 2.5 percent of working-age persons get SSI (McCarthy et al. 2007). Individuals with SSI immediately receive Medicaid coverage. Impoverished SSI recipients and low income or uninsured persons with disabilities who have not yet applied for disability benefits face financial barriers to accessing health care.

Despite these limitations, this study raises questions about the care of specific groups of disabled Medicare beneficiaries under age 65 who develop early stage breast cancer. Disparities in treatments between women with and without disabilities appear to vary across disabling conditions. Many factors could account for these differences, including clinical considerations and patients' preferences. Given that women with mental health conditions and mental retardation appear especially disadvantaged, questions arise about whether stigmatized attitudes among providers and other caregivers might affect their access to good quality care, particularly around adjuvant radiation following breast conserving surgery. Additional research must investigate sources of these treatment disparities to ensure that women with disabilities receive care that respects their preferences and maximizes their quality of life.

ACKNOWLEDGMENTS

This study used the linked SEER-Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of several groups responsible for the creation and dissemination of the Linked Database, including the Applied Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute (NCI); the Office of Information Services, and the Office of Research, Development, and Information, Centers for Medicare and Medicaid Services (CMS); Information Management Services, Inc.; and the Surveillance, Epidemiology, and End Results Program Tumor Registries.

This research involved creation of a new database, when Social Security Administration (SSA) disability determination data were linked to the SEER-Medicare files. We are grateful to Joan Warren from NCI, Gerald F. Riley from CMS, and Joel Packman from SSA for supporting this effort. We also thank staff at CHD Research Associates and Fu Associates, particularly LeAnn Weaver and Celia Hsu Dahlman for their meticulous assistance in data analysis.

Funding Source: The National Cancer Institute funded this research (R01 CA100029).

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SUPPLEMENTARY MATERIAL

The following material is available for this article online: Appendix SA1: Author Matrix.

This material is available as part of the online article from: This material is available as part of the online article from: http://www.blackwellsynergy.com/doi/abs/10.1111/j.1475-6773.2008.00853.x (this link will take you to the article abstract).

Please note: Blackwell Publishing is not responsible for the content or functionality of any supplementary materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.

Address correspondence to Lisa I. Iezzoni, M.D., M.Sc., Institute for Health Policy, Division of Medicine, Massachusetts General Hospital and Harvard Medical School, 50 Staniford St., Rm 901C, Boston, MA 02114; e-mail: liezzoni@partners.org. Long H. Ngo, Ph.D., is with the Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA. Donglin Li, M.D., M.P.H., is with the Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, Boston, MA. Richard G. Roetzheim, M.D., M.P.S.H., is with the Department of Family Medicine, University of South Florida, Tampa, FL. Reed E. Drews, M.D., is with the Division of Hematology and Oncology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA. Ellen P. McCarthy, Ph.D., M.P.H., is with the Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA.
Table 1: Demographic and Tumor Characteristics by SSDI Status and
Disability Group

 Disability Group *

Demographic, Registry, Diagnosis Not Mental
Year, and Tumor Characteristics SSDI Disorders

Number of women 87,661 767
Demographic characteristics
Age in years: mean (SD) 50.4 52.5 (7.7)
 ([dagger]) (8.7)
Race/ethnicity (%) ([dagger])
 Non-Hispanic white 75.7 66.4
 Non-Hispanic black 8.0 20..5
 Hispanic 7.0 8.3
 Other 9.3 4.8
Marital status (%) ([dagger])
 Never married 12.6 35.5
 Married 68.9 24.1
 Widowed 4.7 10.2
 Other 13.8 30.3
Tumor registry (%)
 ([double dagger])
 Connecticut 11.4 13.3
 Hawaii 3.9 3.7
 Iowa 8.7 8.3
 New Mexico 4.3 4.2
 Utah 4.1 4.6
 Atlanta 7.7 6.7
 Detroit 12.5 16.7
 Los Angeles 16.7 17.5
 San Francisco/Oakland 13.6 11.3
 San Jose/Monterey 5.0 4.0
 Seattle/Puget Sound 12.1 9.8
Year of diagnosis (%) ([dagger])
 1988-1991 22.3 15.4
 1992-1995 34.7 34.0
 1996-1999 43.0 50.6
Breast tumor characteristics (%)
Stage ([double dagger])
 I 51.4 49.9
 IIA 31.7 30.1
 IIB 17.0 20.0
Lymph nodes ([dagger])
 Negative 63.2 58.8
 Positive 30.2 32.2
 Unknown 6.6 9.0
Grade ([dagger])
 Well-differentiated 11.9 15.4
 Moderately differentiated 31.8 33.5
 Poorly differentiated 31.7 28.8
Histology
 Ductal 79.0 75.8
 Lobular 6.2 6.5
 Mixed ductal/lobular 5.8 6.4
Estrogen receptor status
 ([dagger]), ([section])
 Positive 53.2 5.8
 Negative 20.3 21.4
Progesterone receptor status
 ([dagger]), ([section])
 Positive 47.0 51.1
 Negative 24.2 23.9

 Disability Group *

Demographic, Registry, Diagnosis Neurological Circulatory/
Year, and Tumor Characteristics Conditions Respiratory

Number of women 184 306
Demographic characteristics
Age in years: mean (SD) 53.3 (7.4) 58.1 (5.6)
 ([dagger])
Race/ethnicity (%) ([dagger])
 Non-Hispanic white 79.9 68.0
 Non-Hispanic black 13.0 21.6
 Hispanic 3.8 5.6
 Other 3.3 4.9
Marital status (%) ([dagger])
 Never married 20.7 11.8
 Married 53.8 46.4
 Widowed 7.1 16.7
 Other 18.5 25.2
Tumor registry (%)
 ([double dagger])
 Connecticut 7.1 11.8
 Hawaii 2.2 2.9
 Iowa 13.0 8.2
 New Mexico 3.8 3.6
 Utah 4.4 2.9
 Atlanta 6.0 7.8
 Detroit 13.6 19.3
 Los Angeles 17.4 17.3
 San Francisco/Oakland 12.5 11.8
 San Jose/Monterey 6.5 3.4
 Seattle/Puget Sound 13.6 10.8
Year of diagnosis (%) ([dagger])
 1988-1991 13.0 21.2
 1992-1995 29.4 33.7
 1996-1999 57.6 45.1
Breast tumor characteristics (%)
Stage ([double dagger])
 I 51.1 55.2
 IIA 29.4 29.7
 IIB 19.6 15.0
Lymph nodes ([dagger])
 Negative 61.4 60.1
 Positive 27.7 25.5
 Unknown 10.9 14.4
Grade ([dagger])
 Well-differentiated 13.6 12.1
 Moderately differentiated 34.2 36.6
 Poorly differentiated 31.0 28.8
Histology
 Ductal 75.0 81.1
 Lobular 6.0 5.9
 Mixed ductal/lobular 8.2 3.9
Estrogen receptor status
 ([dagger]), ([section])
 Positive 60.3 57.8
 Negative 21.2 18.0
Progesterone receptor status
 ([dagger]), ([section])
 Positive 50.0 50.7
 Negative 30.4 22.9

 Disability Group *

Demographic, Registry, Diagnosis Musculo-
Year, and Tumor Characteristics skeletal

Number of women 526
Demographic characteristics
Age in years: mean (SD) 57.1
 ([dagger]) (6.4)
Race/ethnicity (%) ([dagger])
 Non-Hispanic white 65.6
 Non-Hispanic black 19.0
 Hispanic 11.2
 Other 4.2
Marital status (%) ([dagger])
 Never married 13.1
 Married 48.7
 Widowed 16.4
 Other 21.8
Tumor registry (%)
 ([double dagger])
 Connecticut 10.8
 Hawaii 2.1
 Iowa 8.8
 New Mexico 5.7
 Utah 4.0
 Atlanta 4.9
 Detroit 14.5
 Los Angeles 16.5
 San Francisco/Oakland 13.3
 San Jose/Monterey 6.5
 Seattle/Puget Sound 12.9
Year of diagnosis (%) ([dagger])
 1988-1991 15.2
 1992-1995 34.2
 1996-1999 50.6
Breast tumor characteristics (%)
Stage ([double dagger])
 I 57.8
 IIA 31.2
 IIB 11.0
Lymph nodes ([dagger])
 Negative 67.1
 Positive 24.1
 Unknown 8.8
Grade ([dagger])
 Well-differentiated 15.8
 Moderately differentiated 31.9
 Poorly differentiated 29.1
Histology
 Ductal 78.5
 Lobular 5.9
 Mixed ductal/lobular 4.9
Estrogen receptor status
 ([dagger]), ([section])
 Positive 52.7
 Negative 23.8
Progesterone receptor status
 ([dagger]), ([section])
 Positive 45.3
 Negative 28.3

* Mental disorders = mental disorders and mental retardation;
neurological = nervous system disorders; circulatory/respiratory =
circulatory conditions and respiratory conditions; musculoskeletal
= musculoskeletal and connective tissue disorders.

([dagger]) p-value <.0001 for comparison across all groups.

([double dagger]) p-value = .002 for comparison across all groups.

([section]) Receptor status collected starting in 1990.

Table 2: Receipt of Breast Conserving Surgery by SSDI
Status and Disability Group

 Disability Group *

Population by Not Mental
Tumor Stage SSDI Disorders

Percent with breast conserving surgery ([dagger])

All women 51.5 43.8
Stage I 62.2 54.3
Stage IIA 46.0 35.9
Stage IIB 29.5 29.4

Adjusted relative risk (95% CI) ([double dagger])

All women 1.00 0.80 (0.74, 0.87)
Stage I 1.00 0.80 (0.73, 0.88)
Stage IIA 1.00 0.75 (0.63, 0.89)
Stage IIB 1.00 0.91 (0.71, 1.17)

 Disability Group *

Population by Neurological Circulatory/
Tumor Stage Conditions Respiratory

Percent with breast conserving surgery ([dagger])

All women 41.9 46.4
Stage I .53.2 55.6
Stage IIA 33.3 39.6
Stage IIB 25.0 26.1

Adjusted relative risk (95% CI) ([double dagger])

All women 0.77 (0.66, 0.91) 0.87 (0.77, 0.98)
Stage I 0.81 (0.66, 0.98) 0.88 (0.77, 1.00)
Stage IIA 0.68 (0.47, 0.99) 0.83 (0.64, 1.06)
Stage IIB 0.83 (0.47, 1.45) 0.95 (0.61, 1.50)

 Disability Group *

Population by
Tumor Stage Musculoskeletal

Percent with breast conserving surgery ([dagger])

All women 53.0
Stage I 63.5
Stage IIA 42.1
Stage IIB 29.3

Adjusted relative risk (95% CI) ([double dagger])

All women 0.95 (0.88, 1.03)
Stage I 0.96 (0.88, 1.05)
Stage IIA 0.93 (0.78, 1.10)
Stage IIB 0.96 (0.65, 1.42)

* See Table 1 for definition of disability groups.

([dagger]) Other women received mastectomy.

([double dagger]) Adjusted for: age at diagnosis (continuous),
race/ethnicity, marital status, tumor registry, year of diagnosis,
stage at diagnosis (only the model of all women combined), tumor
size (continuous), histology, grade, estrogen receptor status,
and progesterone receptor status.

Table 3: For Women with Breast Conserving Surgery, Receipt
of Axillary Node Dissection and Radiation Therapy by SSDI
Status and Disability Group

 Disability Group *

 Not Mental Neurological
Receipt of Service SSDI Disorders Conditions

Axillary node
 dissection
Percent receiving 89.9 84.8 83.1
 axillary
 dissection (%)
Unadjusted relative 1.00 0.94 (0.90, 0.99) 0.92 (0.83, 1.02)
 risk (95% CI)
Adjusted relative 1.00 0.97 (0.93, 1.01) 0.93 (0.84, 1.02)
 risk (95% CI)
 ([dagger])
Radiation therapy
Percent receiving 81.6 70.9 70.3
 radiation
 therapy (%)
Unadjusted relative 1.00 0.87 (0.81, 0.93) 0.87 (0.75, 1.00)
 risk (95% CI)
Adjusted relative 1.00 0.93 (0.88, 0.98) 0.85 (0.73, 0.98)
 risk (95% CI)

 Disability Group *

 Circulatory/
Receipt of Service Respiratory Musculoskeletal

Axillary node
 dissection
Percent receiving 72.5 88.5
 axillary
 dissection (%)
Unadjusted relative 0.80 (0.73, 0.89) 0.98 (0.94, 1.03)
 risk (95% CI)
Adjusted relative 0.87 (0.80, 0.94) 1.00 (0.97, 1.04)
 risk (95% CI)
 ([dagger])
Radiation therapy
Percent receiving 70.8 81.2
 radiation
 therapy (%)
Unadjusted relative 0.87 (0.78, 0.97) 0.99 (0.94, 1.05)
 risk (95% CI)
Adjusted relative 0.88 (0.79, 0.97) 0.98 (0.93, 1.04)
 risk (95% CI)

* See Table 1 for definition of disability groups.

([dagger]) Adjusted for: age at diagnosis (continuous), race/
ethnicity, marital status, tumor registry, year of diagnosis,
stage at diagnosis, tumor size (continuous), histology, grade,
estrogen receptor status, and progesterone receptor status.

Table 4: Cancer-Specific and All Cause Mortality for Selected
Disability Categories

 Disability Group *

 Not Mental Neurological
Predictive Model SSD Disorders Conditions

Hazards ratios, adjusted as indicated (9.5% CI)

Cancer-specific
 mortality ([dagger])
 Unadjusted 1.0 1.28 (1.04, 1.57) 1.35 (0.89, 2.05)
 Adjusted for 1.0 1.20 (0.98, 1.47) 1.33 (0.87, 2.02)
 demographic
 and tumor
 characteristics
 Adjusted further for 1.0 1.17 (0.95, 1.43) 1.31 (0.86, 2.00)
 axillary node
 dissection,
 radiotherapy
 Unadjusted 1.0 1.88 (1.63, 2.17) 2.90 (2.26, 3.72)
 Adjusted for 1.0 1.63 (1.41, 1.88) 2.61 (2.04, 3.35)
 demographic
 and tumor
 characteristics
 Adjusted further for 1.0 1.58 (1.37, 1.83) 2.57 (2.00, 3.29)
 axillary node
 dissection,
 radiotherapy

 Disability Group *

 Circulatory/
Predictive Model Respiratory Musculoskeletal

Hazards ratios, adjusted as indicated (9.5% CI)

Cancer-specific
 mortality ([dagger])
 Unadjusted 1.69 (1.24, 2.31) 1.05 (0.78, 1.40)
 Adjusted for 1.49 (1.09, 2.04) 0.98 (0.73, 1.32)
 demographic
 and tumor
 characteristics
 Adjusted further for 1.49 (1.09, 2.04) 1.00 (0.74, 1.34)
 axillary node
 dissection,
 radiotherapy
 Unadjusted 4.32 (3.67, 5.09) 2.03 (1.70, 2.42)
 Adjusted for 3.29 (2.78, 3.88) 1.65 (1.38, 1.97)
 demographic
 and tumor
 characteristics
 Adjusted further for 3.27 (2.77, 3.86) 1.66 (1.39, 1.98)
 axillary node
 dissection,
 radiotherapy

* See footnotes to Table 1 for details.

([dagger]) Includes deaths from breast cancer and cancers in
common metastatic sites: liver, lung, bone, brain.
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Title Annotation:Research Briefs
Author:Iezzoni, Lisa I.; Ngo, Long H.; Li, Donglin; Roetzheim, Richard G.; Drews, Reed E.; McCarthy, Ellen
Publication:Health Services Research
Article Type:Report
Date:Oct 1, 2008
Words:6306
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