This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a colleague Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Save to my personal folders Download to citation manager Rights & Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Earle, C. C. Articles by Weeks, J. C. Search for Related Content PubMed PubMed Citation Articles by Earle, C. C. Articles by Weeks, J. C. Social Bookmarking                            What's this?

Quality of Non–Breast Cancer Health Maintenance Among Elderly Breast Cancer Survivors

Craig C. Earle, Harold J. Burstein, Eric P. Winer, Jane C. Weeks

From the Division of Population Sciences, Center for Outcomes and Policy Research, Breast Oncology Center, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA.

Address reprint requests to Craig C. Earle, MD, Center for Outcomes and Policy Research, Dana-Farber Cancer Center, 44 Binney St., Boston, MA, 02115; email: craig_earle{at}dfci.harvard.edu.

	ABSTRACT

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

 
Purpose: To assess the quality of preventive health care, the role of health care participation, and the patient and provider characteristics associated with high-quality care for breast cancer survivors.

Methods: We analyzed the 1997 to 1998 Medicare data of elderly women who were diagnosed with nonmetastatic breast cancer in 1991 or 1992 while living in a Survival, Epidemiology, and End Results (SEER) tumor registry area and who survived to the end of 1998 without evidence of cancer recurrence. Controls were matched for age, race, and geographic location.

Results: The 5,965 breast cancer survivors received more preventive services (influenza vaccination, lipid testing, cervical and colon screening, and bone densitometry) than matched controls. Among both groups, those who were younger, non–African-American, of higher socioeconomic status, living in urban areas, and receiving care in a teaching center were most likely to receive high-quality health maintenance. Those survivors who continued to see oncology specialists were more likely to receive appropriate follow-up mammography for their cancer, but those who were monitored by primary care physicians were more likely to receive all other non–cancer-related preventive services. Those who saw both types of practitioners received more of both types of services. When the control group was restricted only to women actively undergoing mammographic screening before the study period, receipt of preventive services was similar.

Conclusion: Breast cancer survivors receive high-quality preventive services, but disparities on the basis of nonmedical factors still exist. Cancer follow-up may provide regular contact with the health system, maximizing the likelihood of receiving appropriate general medical care.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

 
BREAST CANCER is the most common cancer in women. With advances in both screening and treatment, the 5-year survival rate is now 85%,¹ and 61% of these women are still alive at 15 years.² As a result, there are an estimated 2 million women in the United States who are breast cancer survivors,^3,4 a number that is expected to continue to grow as the incidence of breast cancer increases, breast cancer mortality declines, and our population ages.

Previous studies have indicated that there are important competing risks for women with breast cancer.^5,6 In one study of breast cancer survivors identified through the Connecticut tumor registry, heart disease and gynecological cancers were identified as significant contributors to mortality.⁷ Analysis of public release data from the National Cancer Institute (NCI) Survival, Epidemiology, and End Results (SEER) program indicates that the major causes of non–breast cancer mortality among women with a history of breast cancer are heart disease and stroke; colorectal, lung, and gynecologic cancers; chronic lung disease; and complications of diabetes. These do not differ from the causes of death seen in matched controls drawn from the National Center for Vital Statistics.

The risk of several of these illnesses can potentially be lowered by appropriate preventive services such as screening for colon cancer or cardiovascular disease, immunization to prevent influenza, and recommendations for lifestyle interventions such as diet and smoking cessation. This observation led us to question whether there were differences in the non–breast cancer medical care breast cancer survivors receive compared with the general population and how sociodemographically vulnerable subgroups of survivors fare compared with others. One could hypothesize that survivors may receive less care because of an underlying sense that their cancer is their greatest threat to life or because cancer patients may rely on specialists for their primary care. Conversely, they may receive higher-quality care because they have already been engaged in the medical system or because their physicians may be more vigilant, having already identified a serious illness. If the latter were true, a prior diagnosis of breast cancer might mitigate the usually observed poorer quality of care received by certain subgroups of patients. To address these issues, we used population-based administrative data to assess and compare the use of standard preventive services among breast cancer survivors and matched controls.

	METHODS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

 
Data Sources
We primarily used two data sources: the NCI SEER and the Health Care Financing Administration (HCFA) Medicare database. The 11 tumor registries participating in the SEER program capture about 97% of their incident cases,⁸ covering a representative sample⁹ of approximately 14% of the United States population.¹⁰ Registries collect data on each patient’s age, sex, race and ethnicity, cancer site, stage, histology, date of diagnosis, and date and cause of death. They also record initial treatment data on surgery and radiation received in the first 4 months after diagnosis. However, SEER does not provide information on later treatments. To monitor these patients longitudinally, Medicare claims for patients older than age 65 years have been linked to the SEER registry data. The Medicare data set includes files through 1998 for inpatient and outpatient care, physician and laboratory billings, and bills for home health and hospice care. For patients age 65 years and older captured by the SEER registries, 94% have been linked to Medicare.¹¹ Census-level sociodemographic data have also been linked to these patient cases, allowing us to create socioeconomic quintiles on the basis of the race and age-adjusted income, wealth, and education in each patient’s census tract in the 1990 census. Combining SEER data with Medicare data provided us with information on initial diagnosis and later cancer treatment, as well as the downstream medical care for cancer survivors.

Cohort Selection
The study sample consisted of all women diagnosed with breast cancer in 1991 or 1992 while living in one of the SEER regions. We defined survivors as women that had local-regional, nonmetastatic disease at diagnosis; survived through the end of 1998; had not been diagnosed with subsequent cancers recorded in SEER; had not received chemotherapy or radiation in 1997 to 1998; had no diagnostic codes for metastatic cancer in any bills (International Classification of Disease, 9th revision [ICD-9] codes 196 to 199); and had not been enrolled in hospice.

Controls were obtained from a 5% random sample of Medicare patients with no history of cancer, as determined by having never appeared in a SEER tumor registry for any reason and having no claims for a cancer diagnosis, matched to each case on the basis of age, sex, race, and geographic location (living in the same SEER registry area). Patients were excluded if they were enrolled in a Health Maintenance Organization (HMO) at any time during the study period or if they were not eligible for both parts of Medicare, as they would not have complete treatment information.

We then compared the non–cancer-related preventive services received by survivors with those received by controls in the 2 years of 1997 and 1998. Analysis was restricted to these latter years to avoid assessing patients who may not have been considered survivors by all of their caregivers, which could potentially have biased comparisons of preventive health resource use.

Definitions of Preventive Services
Quality indicators were selected from the Health Plan Employer Data and Information Set, focusing on conditions identified in the literature as being important health threats for breast cancer survivors and those that could feasibly be assessed using administrative data. The final list to be examined between 1997 and 1998 consisted of influenza vaccination; lipid testing; cervical examination; colon examination, whether by endoscopy or fecal occult blood testing; and bone densitometry. We also looked at mammography use, but this was not considered in comparisons of preventive services because breast cancer patients would be expected to receive this as part of routine surveillance for recurrence.

Definitions of Explanatory Variables
We collapsed race and ethnicity into white, African-American, and other categories. Region-specific socioeconomic quintiles were developed on the basis of information availability, according to the following hierarchy: (1) race- and age-specific median household income by census tract (72.9% of patients); (2) unadjusted median household income by census tract (24.4%); and (3) median household wealth (2.7%).¹² For the control group, this information was only available at the county level. We identified comorbidities by looking for diagnostic billing codes for various conditions during the study period, using the Deyo implementation¹³ of the Charlson score,¹⁴ applied to both inpatient and outpatient claims as suggested by Klabunde.¹⁵ Use of chemotherapy and radiation was identified from billing claims, as we have done previously.¹⁶ We considered a woman to have received care in a teaching hospital if there was a bill for indirect medical education at one of her medical contacts during the study period.

To investigate the effect of access and participation in the health care system on receipt of services, as opposed to differential treatment of cancer survivors by doctors, we repeated the analyses restricting the control group to those women who had had a mammogram in 1991 and 1992, the same 2-year period when the survivors were diagnosed with their breast cancer. In this way, both groups consisted only of patients who were actively participating in the health care system 5 years previously. To assess the type of physicians patients were seeing, we categorized physicians on the basis of their specialty identification in Medicare. Oncology specialists were defined as subspecialists in medical oncology or hematology-oncology (HCFA specialty codes 83 or 90, respectively), radiation oncologists (code 92), or surgeons (code 02, general surgery; code 91, surgical oncology). The analyses were also carried out with surgeons not classified as oncologists; these results were similar and are not reported. Primary care physicians were identified with the following provider codes: 01, general practice; 11, internal medicine; 08, family practice; 16, obstetrics/gynecology; 38, geriatric medicine; and 70, multispecialty group practices.

Analytic Considerations
Univariate analyses comparing the receipt of services between 1997 and 1998 by survivors with that of matched controls were carried out using t-tests for continuous variables and ² analyses for categorical variables. To explore the effect of age and presenting stage, analyses were repeated restricting the cohort to women age 75 and younger and to survivors who did not have in situ disease. On the basis of the univariate results, we constructed multivariate models to determine which characteristics predict receiving each intervention. We also assessed an empirically chosen composite end point consisting of receipt of two of the preventive services as the dependent variable (mammography was not included); this roughly split the sample in half. We explored several other end point definitions as well, but none altered the results, and they are not reported. Significant explanatory variables were identified through stepwise elimination. Interaction terms between the significant explanatory variables were further investigated if they had a ² P < .10. All statistical analyses were performed with Statistical Analysis Software (SAS; version 8.01 for Windows, SAS Institute Inc, Cary, NC, 1999).

	RESULTS

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

 
A total of 6,365 nonmetastatic breast cancer patients met the eligibility criteria of surviving and continuously participating in both parts of Medicare through to the end of 1998 and were matched with controls. After we excluded those in each group with evidence of chemotherapy or radiation use, receiving hospice services, or with cancer diagnoses in their bills during the study period, there were 5,965 survivors and 6,062 controls. When this small excess of controls was eliminated, results for all analyses were similar and are not reported.

Patient Characteristics
Among breast cancer survivors, 71% had node-negative disease at the time of their original diagnosis (Table 1). The population was quite elderly, with an average age of more than 78 years. Age and race were matching criteria and, consequently, were not different. Rates of care in teaching institutions and living in urban settings were similar in the two groups. There was slightly more comorbidity documented in the survivors than in controls (45% v 42%, respectively; P = .0003). Although there was a weak trend toward myocardial infarction being a little less frequent in the controls, heart failure was more common in breast cancer survivors (P = .01). Diabetes is the only other condition that was different between the two groups; it was more common in survivors than controls (P < .0001).

Relationship Between Patient Characteristics and Use of Preventive Services
Multivariate analyses on a number of composite end points indicate that increasing age, African-American race, lower socioeconomic scale, living in a rural area, and receiving care entirely in a nonteaching center all were associated with less receipt of preventive services. Table 3 shows the effects of these variables on the odds of having received two or more preventive services. Survivors had an adjusted odds ratio (OR) of 1.42 (95% confidence interval [CI], 1.32 to 1.53) of receiving two or more services. The OR for each year of age was 0.93 (95% CI, 0.93 to 0.94). African-American patients were significantly less likely to receive preventive interventions, with an OR of 0.59 (95% CI, 0.49 to 0.71). Patients in each quintile of higher socioeconomic status received more care (OR, 1.08; 95% CI, 1.04 to 1.12). Each increase in the Charlson comorbidity score was associated with an increase in odds of receiving preventive services (OR, 1.03; 95% CI, 1.00 to 1.07). Also receiving more services were patients in urban areas (OR, 1.39, 95% CI, 1.14 to 1.41) and those who received care in a teaching hospital (OR, 1.27, 95% CI, 1.14 to 1.41). There were no important interactions. The results of multivariate analyses were similar when the control group was restricted to women undergoing mammographic screening, except that comorbidity score no longer reached statistical significance as a predictor (although it was significant in univariate analysis).

	DISCUSSION

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

The baseline characteristics of the survivor and control groups in this study were well matched. The population was quite elderly, largely because of the 5-year survival requirement, but restriction to a younger cohort did not change the results. Rates of care in teaching institutions were likely underestimated because this could only be established for patients admitted to the hospital. Interestingly, congestive heart failure was more common among survivors, possibly related to prior receipt of anthracyclines or chest irradiation. Myocardial infarction, a severe, acute event likely to be less affected by patterns of health care seeking, was actually more common among controls. This suggests that comorbidities were being captured well in both groups, not simply that survivors had more comorbid conditions documented by virtue of having more medical contacts (detection bias). The higher rate of diabetes observed in the survivor population might be explained because obesity in postmenopausal women is a risk factor for both breast cancer and diabetes.

In absolute terms, the rates of use of preventive services presented in this article likely represent conservative estimates of the true rates in both groups. It is possible, for example, that some women received influenza vaccination or mammography through free programs not captured by Medicare. It is not expected that this would occur differentially between the two groups, however, making comparison of rates internally valid. The finding of mammography in 85% of breast cancer survivors younger than age 75 years 5 years after their cancer diagnosis appears consistent with expectations. The rates could also be low because of lack of consensus about the use of several of these preventive health measures in older patients. However, the results of our analyses were similar when patients were restricted to those younger than age 75 years.

Having established that rates of preventive service use were different, we next attempted to determine whether this was because women diagnosed with breast cancer were regular participants in the health care system or because they were being treated differently by physicians. When we controlled for health care participation by limiting the control group to only those women who had previously undergone mammographic screening, all differences between the groups were removed. This finding reinforces existing evidence that health care participation is likely an important determinant of the quality of care patients receive.¹⁷ It is impossible to know whether it was the patients who were proactive in seeking preventive health behaviors or whether they had physicians who were attuned to providing preventive care.

Although Grunfeld et al^18,19 were unable to show that specialist follow-up in the United Kingdom improves outcomes such as survival or quality of life, here we present data indicating that it may improve some processes of cancer care—in this case, surveillance mammography. These seemingly conflicting results may be related to the different roles of the consulting specialist in the health care systems of the United States and United Kingdom. Although it is unknown whether the observed patterns of care are mostly driven by patient health-seeking behaviors or physician diligence, those survivors that continued to see oncology specialists were more likely to receive appropriate follow-up care for their cancer, whereas those that were observed by primary care physicians were more likely to receive standard non–breast cancer-related preventive services. Patients that continued to see both types of physicians received the best preventive care overall. Interestingly, those followed only by oncologists were less likely to receive cervical or colon cancer screening, indicating that the oncologists may be too focused on the follow-up of the previously diagnosed cancer to pay attention to other cancer-related issues.

There are a number of limitations to our analysis. It is unknown whether the relationships we observed determine the likelihood of receiving preventive services or whether patients with these characteristics are more likely to seek preventive services. Because we examined processes of care in patients who had to be alive to be eligible, by design our study could not assess the outcomes of such care. We can only apply these results to elderly women in a fee-for-service environment. The analysis relies on the accuracy of billing data. It is impossible to know whether all of the survivors were truly free of disease, and some procedures may have been carried out for diagnostic reasons, not as part of routine care (eg, screening colonoscopy only became covered by Medicare in the last year of the study; however, a systematic difference between the two groups would not be expected). Last, defining oncologists on the basis of their designation in Medicare may overlook physicians who are not board-certified, but who nonetheless specialize in cancer care.²⁰ The strengths of this study are that these are national-level population-based data, with a large sample size, consisting of patients with uniform insurance so financial incentives should not affect practice.

Improvements in screening and treatment for breast cancer have decreased the 5-year mortality rate for this disease and increased the number of breast cancer survivors. These women are at risk from other, non–breast cancer-related illness, however. Because many breast cancer survivors are regular participants in the health care system, physicians caring for them have a ready opportunity not only to diagnose and manage disorders unrelated to breast cancer but to prevent many of them. The implications of this study are that being engaged in medical care for one reason may have beneficial effects in other areas. Health care participation is obviously not the whole story, however. Even for patients actively engaged in specialty health care, nonmedical factors such as race, socioeconomic status, geography, and teaching status of hospitals were associated with disparities in preventive medicine. Still, although follow-up after definitive cancer treatment has not been shown to improve cancer-specific survival^19,21 it may serve the purpose of keeping patients in regular contact with a variety of health care providers. Whether these procedures translate into better health outcomes requires further study but could suggest a role for observation of these patients by both specialist and generalist.²²

	NOTES

 
Supported by grants from the Massachusetts Department of Public Health (MDPH 34080066068) and the Friends of the Dana-Farber Cancer Institute.

Presented at the thirty-seventh annual meeting of the American Society of Clinical Oncology, May 12–15, 2001, San Francisco, CA.

	REFERENCES

TOP ABSTRACT INTRODUCTION METHODS RESULTS DISCUSSION REFERENCES

 
1. Greenlee RT, Murry T, Bolden S, et al: Cancer Statistics, 2000. CA Cancer J Clin 50:7–33, 2000[Abstract]

2. Wingo PA, Ries LAG, Parker SL, et al: Long-term cancer patient survival in the United States. Cancer Epidemiol Biomarkers Prev 7:271–282, 1998[Abstract]

3. Hewitt M, Breen N, Devesa S: Cancer prevalence and survivorship issues: Analyses of the 1992 National Health Interview Survey. J Natl Cancer Inst 91:1480–1486, 1999[Abstract/Free Full Text]

4. SEER. Persons living with major cancers in the United States, 1998. J Natl Cancer Inst 90:565, 1998

5. Rutqvist LE: Intercurrent mortality of breast carcinoma patients. Acta Radiol Oncol 23:337–343, 1984[Medline]

6. Brown BW, Braunder C, Minnotte MC: Noncancer deaths in white adult cancer patients. J Natl Cancer Inst 85:979–987, 1993[Abstract/Free Full Text]

7. Ederer F, Cutler SJ, Goldenberg IS, et al: Causes of death among long-term survivors from breast cancer in Connecticut. J Natl Cancer Inst 30:933–947, 1963

8. Zippin C, Lum D, Hankey BF: Completeness of hospital cancer case reporting from the SEER program of the National Cancer Institute. Cancer 76:2343–2350, 1995[CrossRef][Medline]

9. 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]

10. Ries LAG, Kosary CL, Hankey BF, et al: SEER Cancer Statistics Review, 1973–1994. Bethesda, MD, National Cancer Institute, NIH publication 97-2789, 1997

11. 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]

12. Krieger N: Overcoming the absence of socioeconomic data in medical records: Validation and application of a census-based methodology. Am J Public Health 92:703–710, 1992

13. 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]

14. 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, 1986

15. Klabunde CN: Development of a comorbidity index using physician claims data. J Clin Epidemiol 53:1258–1267, 2000[CrossRef][Medline]

16. Earle CC, Tsai JS, Gelber RD, et al: Effectiveness of palliative chemotherapy for advanced lung cancer: Instrumental variable and propensity analysis. J Clin Oncol 19:1064–1070, 2001[Abstract/Free Full Text]

17. Kahn KL, Goldberg RJ, DeCosimo D, et al: Health maintenance activities of physicians and nonphysicians. Arch Intern Med 148:2433–2436, 1988[Abstract/Free Full Text]

18. Grunfeld E, Mant D, Vessey MP, et al: Evaluating primary care follow-up of breast cancer: Methods and preliminary results of three studies. Ann Oncol 6:S47–S52, 1995[Abstract]

19. Grunfeld E, Mant D, Yudkin P, et al: Routine follow-up of breast cancer in primary care: Randomised trial. Br Med J 313:665–669, 1996[Abstract/Free Full Text]

20. Earle CC, Neumann PJ, Gelber RD, et al: Impact of referral patterns on the use of chemotherapy for lung cancer. J Clin Oncol 20:1786–92, 2002[Abstract/Free Full Text]

21. Tomiak E, Piccart M: Routine follow-up of patients after primary therapy for early breast cancer: Changing concepts and challenges for the future. Ann Oncol 4:199–204, 1993[Abstract/Free Full Text]

22. Burstein HJ, Winer EP: Primary care for survivors of breast cancer. N Engl J Med 343:1086–1094, 2000[Free Full Text]

Submitted March 12, 2002; accepted January 13, 2003.

CiteULike    Complore    Connotea    Del.icio.us    Digg    Facebook    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				L. A. Jacobs, S. C. Palmer, L. A. Schwartz, A. DeMichele, J. J. Mao, J. Carver, C. Gracia, C. E. Hill-Kayser, J. M. Metz, M. K. Hampshire, et al. Adult Cancer Survivorship: Evolution, Research, and Planning Care CA Cancer J Clin, November 1, 2009; 59(6): 391 - 410. [Abstract] [Full Text] [PDF]

				L. Nekhlyudov, L. A. Habel, N. S. Achacoso, I. Jung, R. Haque, L. C. Collins, S. J. Schnitt, C. P. Quesenberry Jr, and S. W. Fletcher Adherence to Long-Term Surveillance Mammography Among Women With Ductal Carcinoma In Situ Treated With Breast-Conserving Surgery J. Clin. Oncol., July 1, 2009; 27(19): 3211 - 3216. [Abstract] [Full Text] [PDF]

				W. Y. Cheung, B. A. Neville, D. B. Cameron, E. F. Cook, and C. C. Earle Comparisons of Patient and Physician Expectations for Cancer Survivorship Care J. Clin. Oncol., May 20, 2009; 27(15): 2489 - 2495. [Abstract] [Full Text] [PDF]

				L. Nekhlyudov "Doc, Should I See You or My Oncologist?" A Primary Care Perspective on Opportunities and Challenges in Providing Comprehensive Care for Cancer Survivors J. Clin. Oncol., May 20, 2009; 27(15): 2424 - 2426. [Full Text] [PDF]

				L. N. Shulman, L. A. Jacobs, S. Greenfield, B. Jones, M. S. McCabe, K. Syrjala, L. Diller, C. L. Shapiro, A. C. Marcus, M. Campbell, et al. Cancer Care and Cancer Survivorship Care in the United States: Will We Be Able to Care for These Patients in the Future? J. Oncol. Pract, May 1, 2009; 5(3): 119 - 123. [Abstract] [Full Text] [PDF]

				C. F. Snyder, K. D. Frick, M. E. Kantsiper, K. S. Peairs, R. J. Herbert, A. L. Blackford, A. C. Wolff, and C. C. Earle Prevention, Screening, and Surveillance Care for Breast Cancer Survivors Compared With Controls: Changes from 1998 to 2002 J. Clin. Oncol., March 1, 2009; 27(7): 1054 - 1061. [Abstract] [Full Text] [PDF]

				M. Schootman, D. B. Jeffe, M. Lian, W. E. Gillanders, and R. Aft The Role of Poverty Rate and Racial Distribution in the Geographic Clustering of Breast Cancer Survival Among Older Women: A Geographic and Multilevel Analysis Am. J. Epidemiol., March 1, 2009; 169(5): 554 - 561. [Abstract] [Full Text] [PDF]

				J. J. Mao, M. A. Bowman, C. T. Stricker, A. DeMichele, L. Jacobs, D. Chan, and K. Armstrong Delivery of Survivorship Care by Primary Care Physicians: The Perspective of Breast Cancer Patients J. Clin. Oncol., February 20, 2009; 27(6): 933 - 938. [Abstract] [Full Text] [PDF]

				ASCO Policy Statement Highlights Oncologist's Role in Providing Cancer Prevention Services J. Oncol. Pract, January 1, 2009; 5(1): 10 - 12. [Full Text] [PDF]

				M. Lustberg and C. L. Shapiro Physical Challenges of Adult Cancer Survivors ASCO Educational Book, January 1, 2009; 2009(1): 564 - 569. [Abstract] [Full Text] [PDF]

				C. F. Snyder, C. C. Earle, R. J. Herbert, B. A. Neville, A. L. Blackford, and K. D. Frick Preventive Care for Colorectal Cancer Survivors: A 5-Year Longitudinal Study J. Clin. Oncol., March 1, 2008; 26(7): 1073 - 1079. [Abstract] [Full Text] [PDF]

				T. L. Lash, M. P. Fox, D. S.M. Buist, F. Wei, T. S. Field, F. J. Frost, A. M. Geiger, V. P. Quinn, M. U. Yood, and R. A. Silliman Mammography Surveillance and Mortality in Older Breast Cancer Survivors J. Clin. Oncol., July 20, 2007; 25(21): 3001 - 3006. [Abstract] [Full Text] [PDF]

				S. A. Sabatino, R. J. Coates, R. J. Uhler, L. A. Pollack, L. G. Alley, and L. J. Zauderer Provider Counseling About Health Behaviors Among Cancer Survivors in the United States J. Clin. Oncol., May 20, 2007; 25(15): 2100 - 2106. [Abstract] [Full Text] [PDF]

				N. L. Keating, M. B. Landrum, E. Guadagnoli, E. P. Winer, and J. Z. Ayanian Surveillance Testing Among Survivors of Early-Stage Breast Cancer J. Clin. Oncol., March 20, 2007; 25(9): 1074 - 1081. [Abstract] [Full Text] [PDF]

				P. A. Ganz Monitoring the Physical Health of Cancer Survivors: A Survivorship-Focused Medical History J. Clin. Oncol., November 10, 2006; 24(32): 5105 - 5111. [Abstract] [Full Text] [PDF]

				C. C. Earle Failing to Plan Is Planning to Fail: Improving the Quality of Care With Survivorship Care Plans J. Clin. Oncol., November 10, 2006; 24(32): 5112 - 5116. [Abstract] [Full Text] [PDF]

				P. A. Ganz, L. Kwan, M. R. Somerfield, D. Alberts, J. E. Garber, K. Offit, and S. M. Lippman The Role of Prevention in Oncology Practice: Results From a 2004 Survey of American Society of Clinical Oncology Members J. Clin. Oncol., June 20, 2006; 24(18): 2948 - 2957. [Abstract] [Full Text] [PDF]

				E. Grunfeld, M. N. Levine, J. A. Julian, D. Coyle, B. Szechtman, D. Mirsky, S. Verma, S. Dent, C. Sawka, K. I. Pritchard, et al. Randomized Trial of Long-Term Follow-Up for Early-Stage Breast Cancer: A Comparison of Family Physician Versus Specialist Care J. Clin. Oncol., February 20, 2006; 24(6): 848 - 855. [Abstract] [Full Text] [PDF]

				K. McNiff The Quality Oncology Practice Initiative: Assessing and Improving Care Within the Medical Oncology Practice J. Oncol. Pract, January 1, 2006; 2(1): 26 - 30. [Full Text] [PDF]

				N. L. Keating, M. B. Landrum, E. Guadagnoli, E. P. Winer, and J. Z. Ayanian Factors Related to Underuse of Surveillance Mammography Among Breast Cancer Survivors J. Clin. Oncol., January 1, 2006; 24(1): 85 - 94. [Abstract] [Full Text] [PDF]

				M. N. Neuss, C. E. Desch, K. K. McNiff, P. D. Eisenberg, D. H. Gesme, J. O. Jacobson, M. Jahanzeb, J. J. Padberg, J. M. Rainey, J. J. Guo, et al. A Process for Measuring the Quality of Cancer Care: The Quality Oncology Practice Initiative J. Clin. Oncol., September 1, 2005; 23(25): 6233 - 6239. [Abstract] [Full Text] [PDF]

				W. Demark-Wahnefried, N. M. Aziz, J. H. Rowland, and B. M. Pinto Riding the Crest of the Teachable Moment: Promoting Long-Term Health After the Diagnosis of Cancer J. Clin. Oncol., August 20, 2005; 23(24): 5814 - 5830. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a colleague Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Save to my personal folders Download to citation manager Rights & Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Earle, C. C. Articles by Weeks, J. C. Search for Related Content PubMed PubMed Citation Articles by Earle, C. C. Articles by Weeks, J. C. Social Bookmarking                            What's this?