|
Advertisement |
|
|
||
 |
|
|||||
|
|||||
|
 |
||||||
|
||||||
|
||||||
|
Journal of Clinical Oncology, Vol 24, No 1 (January 1), 2006: pp. 85-94 © 2006 American Society of Clinical Oncology. DOI: 10.1200/JCO.2005.02.4174 Factors Related to Underuse of Surveillance Mammography Among Breast Cancer SurvivorsFrom the Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital; Department of Health Care Policy, Harvard Medical School; and Department of Adult Oncology, Dana-Farber Cancer Institute, Boston, MA Address reprint requests to Nancy L. Keating, MD, MPH, Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115; e-mail: keating{at}hcp.med.harvard.edu
PURPOSE: Many older breast cancer survivors do not undergo annual mammography despite guideline recommendations. We identified factors associated with underuse of surveillance mammography and examined whether variation was explained by differences in follow-up care.
PATIENTS AND METHODS: We used Surveillance, Epidemiology, and End Results-Medicare data to identify a population-based sample of 44,511 women fee-for-service Medicare enrollees aged RESULTS: Only three quarters of women (77.6%) underwent mammography during months 7 to 18 after diagnosis, and only 56.7% had mammography yearly over 3 years. In multivariable analyses, women who were older, black, unmarried, and living in certain regions were less likely than other women to undergo surveillance mammography (all P < .05). Patients with more visits and patients who continued to see a medical oncologist, radiation oncologist, or surgeon were most likely to have mammograms (P < .001); however, adjusting for visits with providers did not explain the lower mammography rates based on age, race, marital status, and geographic region. CONCLUSION: Many elderly breast cancer survivors do not undergo annual surveillance mammography, particularly women who are older, black, and unmarried, and this underuse was not explained by access to follow-up care. New strategies are needed to increase use of surveillance mammography and decrease variations based on nonclinical factors that are likely unrelated to appropriateness of medical care.
National guidelines recommend strongly that all breast cancer survivors undergo annual mammography because they face an increased risk of new or recurrent breast cancer.1-4 Nevertheless, many breast cancer survivors do not receive routine surveillance mammograms,5-9 particularly women who are older,7,8 have more advanced tumors,7,9 and who received breast-conserving surgery without radiation rather than breast-conserving surgery with radiation.7-9 Studies of screening mammography in noncancer patients have found that nonclinical factors are important in understanding variation in receipt of this service. For example, women who are black,10-13 of lower socioeconomic status,10,12 less well insured,10,14 or residing in certain areas of the United States12 have lower rates of screening mammography. However, previous studies have not closely examined whether these nonclinical factors also influence receipt of surveillance mammography among breast cancer survivors. In addition, because providers’ recommendations are strong determinants of mammography for noncancer patients,6,15 the mix of providers that patients see after breast cancer treatment may influence their use of surveillance mammography. We examined surveillance mammography for a large, population-based cohort of breast cancer survivors diagnosed with invasive early-stage disease with two goals. First, we assessed whether patient sociodemographic and clinical factors that have been associated with screening mammography are associated with surveillance mammography. Second, we examined whether differences in follow-up care, including the types of providers seen and the number of visits to these providers, explained sociodemographic variation in surveillance mammography rates.
Data We used the Surveillance, Epidemiology, and End Results (SEER) –Medicare data for this analysis.16 The SEER program collects uniformly reported data from 11 population-based cancer registries covering approximately 14% of the US population.17 For each incident cancer, the SEER registries collect information on patients’ tumor characteristics, demographic characteristics, and month and year diagnosed. Since 1991, SEER data have been merged with Medicare administrative data by a matching algorithm that has successfully linked files for more than 94% of SEER registry patients diagnosed at age  65 years.16
Study Cohort We censored patients at the end of 2001 or sooner if they died, enrolled in an health maintenance organization (HMO), disenrolled from Medicare Part B, developed a second breast cancer or other cancer, or developed a recurrence based on claims for a new course of chemotherapy, radiation therapy, or surgery (lumpectomy, mastectomy, or excision of a chest wall tumor) beginning 13 months or more after diagnosis, with no treatments during months 7 through 12 after diagnosis. We used this relatively conservative definition of recurrence to ensure we had disease-free cohorts for evaluating surveillance mammography; preliminary analyses demonstrated substantial decreases in rates of these treatments after 6 months from diagnosis. Because mammography peaks at 12, 24, and 36 months after diagnosis,7,18 we examined care up to 42 months after diagnosis, defining the following three surveillance years: months 7 to 18, 19 to 30, and 31 to 42 after diagnosis. To be included in analyses of a surveillance year, patients had to be alive and not censored through the end of that surveillance year. Of the 44,511 women with early-stage breast cancer, 37,967 were alive and not censored through the end of surveillance year 1, 30,406 were observed through surveillance year 2, and 23,016 were observed through surveillance year 3. Of patients cumulatively censored before the end of surveillance year 3, 30% were censored for death, 12% were censored for enrolling in an HMO or disenrolling from Medicare Part B, 1% were censored for a new cancer diagnosis, 29% were censored for claims suggesting recurrence, and 28% were censored because we had no data after 2001.
Receipt of Mammography
Visits With Physicians
Patient Characteristics To measure comorbidity, we calculated Diagnostic Cost Groups (DCGs),26 a risk-adjustment tool for predicting future costs and disease burden for Medicare beneficiaries based on 184 clinical diagnostic categories from inpatient and ambulatory claims (compared with 18 for the Charlson score27). DCGs are highly predictive of mortality for Medicare beneficiaries with myocardial infarction28 and, because they capture so many conditions, may be particularly useful in differentiating among the majority of elderly breast cancer patients whose Charlson score is 0. We calculated DCGs (categorized in quintiles; excluding breast cancer codes) based on the 12 months from diagnosis to best characterize comorbidity when decisions about surveillance testing would be made.
Analyses
We used repeated-measures logistic regression with generalized estimating equations to assess the association of patients’ demographic and clinical characteristics with surveillance mammography.29 For each independent variable, we calculated the adjusted odds of surveillance mammography; this modeling strategy allowed inclusion of women in analyses for all surveillance years in which they had complete data. For example, a woman dying 35 months after diagnosis would contribute data about surveillance years 1 and 2. In a second model, we included providers seen and number of outpatient visits (categorized in quintiles) in each surveillance year to assess whether access to various types of providers and frequency of visits explained demographic and clinical differences in surveillance mammography. Types of physicians seen were categorized into the following exclusive categories for each surveillance year: (1) primary care provider but no cancer specialist (medical oncologist, radiation oncologist, or surgeon), (2) cancer specialist but no primary care provider, (3) both cancer specialist and primary care provider, and (4) neither cancer specialist nor primary care provider (omitted group).
In a sensitivity analysis, we replaced the DCG comorbidity quartiles with comorbidity categories based on the Deyo modification of the Charlson score,27,30 categorized as 0 (58% of sample), 1 (25%), 2 (9%), and
The mean age of the cohort at diagnosis was 76 years; 6% of women were black, 4% were Hispanic, and 56% were unmarried (Table 1). As seen in Table 1, unadjusted rates of surveillance mammography were lower for women who were older, black, Hispanic, unmarried, living in certain SEER regions, and living in areas with lower median incomes and fewer high school graduates (all P < .001). In addition, women with a history of a previous nonbreast cancer, with less well-differentiated cancers, stage II (v stage I) tumors, and larger tumors and women in the highest quartile of comorbidity were less likely than other women to undergo surveillance mammography. Surveillance mammography rates increased for women diagnosed more recently. Patterns of mammography use were similar for analyses of mammography in year 1 and for annual mammography during the 3 surveillance years. Visits with primary care physicians, medical oncologists, general surgeons, radiation oncologists, medical subspecialists, surgical subspecialists, and other specialists were all associated with greater use of surveillance mammography (Table 2). However, the effect was largest for women who saw cancer specialists (medical oncologists, general surgeons, and radiation oncologists) in follow-up. Women had a median of 11, eight, and three face-to-face office visits during surveillance years 1, 2, and 3, respectively, and the number of office visits increased with increasing comorbid illness (P < .001). During surveillance year 1, 69% of women in the lowest quintile of outpatient visits had a mammogram compared with 79%, 82%, 81%, and 75% of women in each successive quintile (P < .001).
In adjusted analyses that examined the association of patients’ demographic and clinical characteristics and use of mammography, women who were older, black (v white), and unmarried were less likely than other women to undergo surveillance mammography, as were women of Hispanic ethnicity, although this finding was of borderline statistical significance (P = .06; Table 3). Receipt of surveillance mammography also varied by region, with the highest adjusted rates in Iowa, Hawaii, Detroit, Connecticut, and Atlanta and the lowest adjusted rates in Utah, San Jose, Los Angeles, and New Mexico (Table 3). Rates of surveillance mammography increased for patients diagnosed more recently but decreased with each surveillance year after diagnosis (Table 3). Several clinical factors were also associated with lower rates of surveillance mammography, including having a history of a nonbreast cancer, larger tumor size, undergoing breast-conserving surgery without radiation, and being in the highest comorbidity quartile (Table 3).
In a second set of models that included types of providers seen in each surveillance year and number of outpatient visits, we found that, compared with patients who did not see a primary care provider or cancer specialist in a given year, patients who saw a primary care provider without a cancer specialist, a cancer specialist without a primary care provider, or both were more likely to undergo surveillance mammography, although the odds were highest for patients who saw a cancer specialist, with or without a primary care provider (Table 3). A greater number of visits was also associated with more surveillance mammograms compared with women with the fewest number of visits, although women in the highest quintile of visits were least likely to undergo mammography, likely because of competing comorbid illnesses. Most notably, accounting for differences in access to cancer specialists and number of visits did not explain the lower odds of screening mammography for women who were older, black, Hispanic, unmarried, or living in certain regions identified in our first model, although women living in Connecticut, Atlanta, and Hawaii no longer differed from women in San Francisco in the odds of surveillance mammography.
In this large, population-based study of early-stage breast cancer survivors, we found that many older women did not receive routine surveillance mammograms, and we observed substantial variation based on nonclinical factors such as race, ethnicity, marital status, and region. Although patients who continued to see cancer specialists had the highest rates of surveillance mammography, the types of providers seen and the number of visits did not explain the lower mammography rates among women who were older, black, Hispanic, unmarried, or living in certain regions. Other studies have demonstrated comparable differences in aspects of breast cancer diagnosis and treatment based on nonclinical factors. For example, black patients are less likely than white patients to receive screening mammograms,10-13 more likely to be diagnosed at advanced stage,31-33 less likely to receive definitive primary therapy,31,34-36 and more likely to have delays in diagnosis37,38 and initiation of treatment.37 Similar findings have been observed for patients of lower socioeconomic status or lacking health insurance, patients who are unmarried, and patients living in different regions.33,36,39-42 Although we found no differences based on area-level measures of socioeconomic status, such measures are only moderately reflective of individuals’ socioeconomic status.43,44 Prior studies have also found that diagnosis or treatment for cancer patients may vary based on the types of physicians seen,23,45-48 ambulatory care before diagnosis,49 and the number of generalist physicians in an area.50 Studies of screening mammography in patients without cancer have identified a physician’s recommendation as one of the strongest determinants of mammography use.6,15 Therefore, we expected that the number of visits and mix of providers seen after breast cancer treatment might also influence receipt of surveillance mammography, as suggested by another study.51 Moreover, because other studies have shown that access to cancer specialists may be influenced by patients’ age, employment, race, region, and type of primary therapy,8,23,47,48,52,53 we expected that access to cancer specialists might also explain sociodemographic variations in surveillance mammography. Although we found that patients who continued to see cancer specialists after their initial cancer treatment were more likely than other patients to undergo surveillance mammography, the types of providers seen and number of visits did not explain sociodemographic differences in care. Thus, simply increasing the number of patients observed by cancer specialists is unlikely to eliminate these disparities in use of surveillance mammography. Because many women who did not undergo surveillance mammography nevertheless had visits with physicians, better coordination of care with defined roles for physicians caring for cancer survivors may increase rates of surveillance mammography and decrease associated disparities. Similarly, patients may benefit from a care plan that specifies a mammography schedule, symptoms to watch for, and the clinicians they will see for routine visits. We also found less surveillance mammography according to several clinical factors, including larger tumors and stage II cancers. Although patients with more advanced cancers are more likely to develop recurrence, our finding of greater use of mammography among patients with less advanced cancer may reflect a greater propensity for mammography screening before cancer diagnosis, which could translate into more surveillance mammograms after diagnosis. Alternatively, it may reflect physicians’ identifying these patients as having favorable prognosis and potentially likely to benefit more from surveillance mammograms. We also found that women who underwent breast-conserving surgery without radiation and women with the highest comorbidity levels received less surveillance mammography. These findings may reflect potentially appropriate decisions by patients or their physicians for less intensive care as a result of competing comorbid illness because elderly women with early-stage breast cancer are much more likely to die of other conditions than their breast cancer, particularly women with comorbid illness.54 Similarly, although rates of mammography initially increased with increasing number of visits, women with the most visits, who also had the greatest comorbidity, received fewer mammograms. Thus, more visits may provide more opportunities for ordering mammograms up to a point beyond which patients are so ill that surveillance mammography becomes a lower priority. Breast cancer patients are at an increased risk of developing second primary breast cancers and recurrence in the preserved breasts. Surveillance mammography leads to diagnosis of such cancers at earlier stages1,55-58 and may translate into improved survival. The life expectancy for the average 75-year-old women is currently 12.4 years,59 so substandard care for elderly breast cancer survivors could have substantial negative consequences. Although our study was not well suited to examine the relationship between surveillance mammography and long-term survival among older women, this is an important question for further study, particularly if such studies can identify subgroups of women who are more or less likely to benefit from surveillance mammography. Our study had several limitations. First, in administrative data, mammograms or visits may have been overlooked if services were not covered or bills were not submitted, such as in community mammography screening efforts. However, annual mammography for breast cancer patients was a Medicare-covered service throughout the study period.
Second, we studied older patients living in regions of the country with SEER registries, so the generalizability of our findings to younger women and women in other areas requires further study. However, patients aged Finally, our study’s cross-sectional nature allows us to identify associations, not causal relationships, and some associations we identified may reflect appropriate decisions for less aggressive care. Still, underuse of surveillance mammography based on race, ethnicity, marital status, and region is of substantial concern. Additional research is needed to understand the role of other factors in explaining this variation, such as patients’ preferences and physicians’ beliefs about the benefits of surveillance mammography, and to determine steps that can be taken to achieve more equitable care. Many elderly breast cancer survivors do not undergo annual surveillance mammography, particularly women who are older, black, Hispanic, unmarried, and living in certain geographic regions. These disparities are not explained by access to follow-up care. New strategies are needed to promote surveillance mammography and decrease variations based on nonclinical factors that are likely unrelated to appropriateness of medical care.
ICD-9 Procedure and CPT Codes for Various Procedures*
Abbreviations: ICD-9, International Classification of Diseases, ninth revision; CPT, Current Procedural Terminology. * The Medicare claims data used in this study include the Hospital Outpatient Standard Analytic file (outpatient facility services), the 100% Physician/Supplier file (physicians’ services and other medical services), and the Medicare Provider Analysis and Review file (inpatient claims).
Although all authors completed the disclosure declaration, the following author or immediate family members indicated a financial interest. No conflict exists for drugs or devices used in a study if they are not being evaluated as part of the investigation. For a detailed description of the disclosure categories, or for more information about ASCO’s conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.
Dollar Amount Codes (A) < $10,000 (B) $10,000-99,999 (C)
We thank Laurie Meneades, MS, for her expert programming assistance. We also thank the efforts of the Applied Research Program, National Cancer Institute; the Office of Research, Development and Information, Centers for Medicare and Medicaid Services; Information Management Services, Inc; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-Medicare database.
Supported by a Clinical Scientist Development Award from the Doris Duke Charitable Foundation (N.L.K.). This study used the linked Surveillance, Epidemiology, and End Results-Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors. Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.
1. American Society of Clinical Oncology: Recommended breast cancer surveillance guidelines. J Clin Oncol 15:2149-2156, 1997 2. Smith TJ, Davidson NE, Schapira DV, et al: American Society of Clinical Oncology 1998 update of recommended breast cancer surveillance guidelines. J Clin Oncol 17:1080-1082, 1999 3. National Comprehensive Cancer Network: Update of the NCCN guidelines for treatment of breast cancer. Oncology (Williston Park) 11:199-220, 1997[Medline] 4. National Comprehensive Cancer Network: NCCN Practice Guidelines in Oncology, v. 1.2005. http://www.nccn.org/professionals/physician_gls/PDF/breast.pdf 5. Hillner BE, McDonald MK, Penberthy L, et al: Measuring standards of care for early breast cancer in an insured population. J Clin Oncol 15:1401-1408, 1997[Abstract] 6. Andersen MR, Urban N: The use of mammography by survivors of breast cancer. Am J Public Health 88:1713-1714, 1998 7. Schapira MM, McAuliffe TL, Nattinger AB: Underutilization of mammography in older breast cancer survivors. Med Care 38:281-289, 2000[CrossRef][Medline] 8. Lash TL, Silliman RA: Medical surveillance after breast cancer diagnosis. Med Care 39:945-955, 2001[CrossRef][Medline] 9. Geller BM, Kerlikowske K, Carney PA, et al: Mammography surveillance following breast cancer. Breast Cancer Res Treat 81:107-115, 2003[Medline] 10. Blustein J: Medicare coverage, supplemental insurance, and the use of mammography by older women. N Engl J Med 332:1138-1143, 1995 11. Burns RB, McCarthy EP, Freund KM, et al: Black women receive less mammography even with similar use of primary care. Ann Intern Med 125:173-182, 1996 12. Burns RB, McCarthy EP, Freund KM, et al: Variability in mammography use among older women. J Am Geriatr Soc 44:922-926, 1996[Medline] 13. Blackman DK, Bennett EM, Miller DS: Trends in self-reported use of mammograms (1989-1997) and Papanicolaou tests (1991-1997)–Behavioral Risk Factor Surveillance System. MMWR CDC Surveill Summ 48:1-22, 1999[Medline] 14. Ayanian JZ, Weissman JS, Schneider EC, et al: Unmet health needs of uninsured adults in the United States. JAMA 284:2061-2069, 2000 15. NCI Breast Cancer Screening Consortium: Screening mammography: A missed clinical opportunity? Results of the NCI Breast Cancer Screening Consortium and National Health Interview Survey Studies. JAMA 264:54-58, 1990[Abstract] 16. Potosky AL, Riley GF, Lubitz JD, et al: Potential for cancer related health services research using a linked Medicare-tumor registry database. Med Care 31:732-748, 1993[Medline] 17. Ries LA, Wingo PA, Miller DS, et al: The annual report to the nation on the status of cancer, 1973-1997, with a special section on colorectal cancer. Cancer 88:2398-2424, 2000[CrossRef][Medline] 18. Keating NL, Landrum MB, Meara E, et al: Do increases in managed care market share of managed are influence quality of cancer care in the fee-for-service sector? J Natl Cancer Inst 97:257-264, 2005 19. Edelman MJ, Meyers FJ, Siegel D: The utility of follow-up testing after curative cancer therapy: A critical review and economic analysis. J Gen Intern Med 12:318-331, 1997[CrossRef][Medline] 20. Baldwin LM, Adamache W, Klabunde C, et al: Linking physician characteristics and Medicare claims data: Issues in data availability, quality, and measurement. Med Care 40:IV-82-IV-95, 2002 21. Bach PB, Guadagnoli E, Schrag D, et al: Patient demographic and socioeconomic characteristics in the SEER-Medicare database applications and limitations. Med Care 40:IV-19-IV-25, 2002 22. American Joint Committee on Cancer: AJCC Cancer Staging Manual (ed 5). New York, NY, Springer Verlag, 1997 23. Keating NL, Landrum MB, Ayanian JZ, et al: Consultation with a medical oncologist before surgery and type of surgery among elderly women with early-stage breast cancer. J Clin Oncol 21:4532-4539, 2003 24. Cooper GS, Virnig B, Klabunde CN, et al: Use of SEER-Medicare data for measuring cancer surgery. Med Care 40:IV-43-IV-48, 2002 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. J Clin Epidemiol 52:463-470, 1999[CrossRef][Medline] 26. Ellis RP, Pope GC, Iezzoni LI, et al: Diagnosis-based risk adjustment for Medicare capitation payments. Health Care Financ Rev 17:101-128, 1996[Medline] 27. Charlson ME, Pompei P, Ales KL, et al: A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 40:373-383, 1987[CrossRef][Medline] 28. Ash AS, Posner MA, Speckman J, et al: Using claims data to examine mortality trends following hospitalization for heart attack in Medicare. Health Serv Res 38:1253-1262, 2003[CrossRef][Medline] 29. Zeger SL, Liang K: Longitudinal data analysis for discrete and continuous outcomes. Biometrics 42:121-130, 1986[CrossRef][Medline] 30. Deyo RA, Cherkin DC, Ciol MA: Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45:613-619, 1992[CrossRef][Medline] 31. Li CI, Malone KE, Daling JR: Differences in breast cancer stage, treatment, and survival by race and ethnicity. Arch Intern Med 163:49-56, 2003 32. Eley JW, Hill HA, Chen VW, et al: Racial differences in survival from breast cancer: Results of the National Cancer Institute Black/White Cancer Survival Study. JAMA 272:947-954, 1994[Abstract] 33. Roetzheim RG, Pal N, Tennant C, et al: Effects of health insurance and race on early detection of cancer. J Natl Cancer Inst 91:1409-1415, 1999 34. Mandelblatt JS, Kerner JF, Hadley J, et al: Variations in breast carcinoma treatment in older Medicare beneficiaries: Is it black or white. Cancer 95:1401-1414, 2002[CrossRef][Medline] 35. McWhorter WP, Mayer WJ: Black/white differences in type of initial breast cancer treatment and implications for survival. Am J Public Health 77:1515-1517, 1987 36. Bradley CJ, Given CW, Roberts C: Race, socioeconomic status, and breast cancer treatment and survival. J Natl Cancer Inst 94:490-496, 2002 37. Elmore JG, Nakano CY, Linden HM, et al: Racial inequities in the timing of breast cancer detection, diagnosis, and initiation of treatment. Med Care 43:141-148, 2005[CrossRef][Medline] 38. Gwyn K, Bondy ML, Cohen DS, et al: Racial differences in diagnosis, treatment, and clinical delays in a population-based study of patients with newly diagnosed breast carcinoma. Cancer 100:1595-1604, 2004[CrossRef][Medline] 39. Ayanian JZ, Kohler BA, Abe T, et al: The relation between health insurance coverage and clinical outcomes among women with breast cancer. N Engl J Med 329:326-331, 1993 40. Ayanian JZ, Guadagnoli E: Variations in breast cancer treatment by patient and provider characteristics. Breast Cancer Res Treat 40:65-74, 1996[CrossRef][Medline] 41. Cross CK, Harris J, Recht A: Race, socioeconomic status, and breast carcinoma in the U.S: What have we learned from clinical studies. Cancer 95:1988-1999, 2002[CrossRef][Medline] 42. Roetzheim RG, Gonzalez EC, Ferrante JM, et al: Effects of health insurance and race on breast carcinoma treatments and outcomes. Cancer 89:2202-2213, 2000[CrossRef][Medline] 43. Krieger N: Overcoming the absence of socioeconomic data in medical records: Validation and application of a census-based methodology. Am J Public Health 82:703-710, 1992 44. Geronimus A, Bound J, Wagner E: On the validity of using census geocode data to proxy individual socioeconomic characteristics. J Am Stat Assoc 91:529-537, 1996[CrossRef] 45. Liberati A, Patterson WB, Biener L, et al: Determinants of physicians' preferences for alternative treatments in women with early breast cancer. Tumori 73:601-609, 1987[Medline] 46. Deber RB, Thompson GG: Who still prefers aggressive surgery for breast cancer? Implications for the clinical applications of clinical trials. Arch Intern Med 147:1543-1547, 1987[Abstract] 47. Keating NL, Weeks JC, Landrum MB, et al: Discussion of treatment options for early-stage breast cancer: Effect of provider specialty on type of surgery and satisfaction. Med Care 39:681-691, 2001[CrossRef][Medline] 48. Earle CC, Neumann PJ, Gelber RD, et al: Impact of referral patterns on the use of chemotherapy for lung cancer. J Clin Oncol 20:1786-1792, 2002 49. Keating NL, Landrum MB, Ayanian JZ, et al: The association of ambulatory care with breast cancer stage at diagnosis among Medicare beneficiaries. J Gen Intern Med 20:38-44, 2005[CrossRef][Medline] 50. Roetzheim RG, Pal N, Gonzalez EC, et al: The effects of physician supply on the early detection of colorectal cancer. J Fam Pract 48:850-858, 1999[Medline] 51. Earle CC, Burstein HJ, Winer EP, et al: Quality of non-breast cancer health maintenance among elderly breast cancer survivors. J Clin Oncol 21:1447-1451, 2003 52. Siminoff LA, Zhang A, Saunders Sturm CM, et al: Referral of breast cancer patients to medical oncologists after initial surgical management. Med Care 38:696-704, 2000[CrossRef][Medline] 53. Worster A, Wood ML, McWhinney IR, et al: Who provides follow-up care for patients with early breast cancer? Can Fam Physician 41:1314-1320, 1995[Medline] 54. Satariano WA, Ragland DR: The effect of comorbidity on 3-year survival of women with primary breast cancer. Ann Intern Med 120:104-110, 1994 55. Senofsky GM, Wanebo HJ, Wilhelm MC, et al: Has monitoring of the contralateral breast improved the prognosis in patients treated for primary breast cancer? Cancer 57:597-602, 1986[CrossRef][Medline] 56. Mellink WA, Holland R, Hendriks JH, et al: The contribution of routine follow-up mammography to an early detection of asynchronous contralateral breast cancer. Cancer 67:1844-1848, 1991[CrossRef][Medline] 57. Orel SG, Fowble BL, Solin LJ, et al: Breast cancer recurrence after lumpectomy and radiation therapy for early-stage disease: Prognostic significance of detection method. Radiology 188:189-194, 1993 58. Muttarak M, Pojchamarnwiputh S, Padungchaichote W, et al: Evaluation of the contralateral breast in patients with ipsilateral breast carcinoma: The role of mammography. Singapore Med J 43:229-233, 2002[Medline] 59. National Center for Health Statistics: Health, United States, 2004, with Chartbook on Trends in the Health of Americans. Hyattsville, MD, National Center for Health Statistics, 2004 60. Ries LAG, Eisner MP, Kosary CL, et al: SEER Cancer Statistics Review, 1973-1999. http://seer.cancer.gov/csr/1973_1999/ 61. Warren JL, Klabunde CN, Schrag D, et al: Overview of the SEER-Medicare data: Content, research applications, and generalizability to the United States elderly population. Med Care 40:IV-3-IV-18, 2002 62. Nattinger AB, McAuliffe TL, Schapira MM: Generalizability of the surveillance, epidemiology, and end results registry population: Factors relevant to epidemiologic and health care research. J Clin Epidemiol 50:939-945, 1997[CrossRef][Medline] 63. Silliman RA, Guadagnoli E, Weitberg AB, et al: Age as a predictor of diagnostic and initial treatment intensity in newly diagnosed breast cancer patients. J Gerontol 44:M46-M50, 1989[Medline] 64. Silliman RA, Troyan SL, Guadagnoli E, et al: The impact of age, marital status, and physician-patient interactions on the care of older women with breast carcinoma. Cancer 80:1326-1334, 1997[CrossRef][Medline] Submitted April 18, 2005; accepted October 11, 2005. This article has been cited by other articles:
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|
|||||||||||
|
|||||||||||
|
|
Copyright © 2006 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
|
TOP
ABSTRACT
INTRODUCTION
2 tests. Similarly, we assessed whether the providers seen in a surveillance year were associated with mammography during surveillance year 1 and annual mammography during surveillance years 1 through 3. We also examined whether the number of outpatient visits (categorized in quintiles) was associated with mammography in each surveillance year, and we assessed the association between visit quintile and comorbidity quartile. 
