Home Insurance Status and the Severity of Breast Cancer at the Time of Diagnosis
Post
Cancel

Insurance Status and the Severity of Breast Cancer at the Time of Diagnosis

Rationale and Objectives

To evaluate how the insurance status of women diagnosed with breast cancer correlates with size and stage at the time of diagnosis.

Methods and Materials

The age-adjusted incidence of early- and late-stage breast cancer as determined by the tumor node metastasis classification system of stages in situ, local, regional, or distant was calculated for insured and uninsured women from our institution’s database between 2002 and 2004. Late-stage breast cancer was defined as present when patients had either regional or distant disease. Statistical analysis was conducted using generalized linear models and χ 2 tests.

Results

There were a total of 617 patients in our retrospective study. Of these, 564 (91.4%) had insurance and 53 (8.6%) were uninsured. Four hundred forty-seven (72.4%) patients were Caucasian and 170 (27.6%) patients were non-Caucasian. Of the 463 patients with early-stage breast cancer (0, I, or II), 433 (93.5%) had insurance and 30 (6.5%) were uninsured. Of the 154 patients with late-stage breast cancer (III or IV), 131 (85.1%) had insurance and 23 (14.9%) patients were uninsured. Analysis demonstrated that there was a significant effect in the insurance status on cancer stage ( P = .006) and tumor size ( P = .010). Compared to insured patients, uninsured patients had a 66% higher likelihood of presenting with a late-stage cancer and larger tumor. The analysis from the χ 2 test also supports the above with a significant association between patients’ cancer stage and insurance status ( P = .001) and also between tumor size and insurance status ( P = .001). Patients’ ages and geographic locations were not significant correlated with size and stage, but non-Caucasians had a significantly higher risk of larger tumors and more advanced stage than Caucasians ( P < .005).

Conclusions

Uninsured, non-Caucasian patients have a higher probability of presenting with a more advanced stage of breast cancer and larger tumor size than patients with insurance in a large university multidisciplinary breast cancer population.

Health care is a subject of substantial concern in the United States. More than 45 million Americans lack health insurance and many more are underinsured ( ). Studies have shown that individuals without health insurance are less likely to receive cancer screening and other preventive services because of cost and access to health care ( ).

Recent studies have demonstrated that there is a link between insurance coverage and health outcomes ( ). Because insurance coverage is associated with differences in outcome, it is most evident for diseases that can be diagnosed and treated early ( ). Such an example is breast cancer. Breast cancer may take years to develop and often there are no symptoms of the disease in the early stages.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Materials and methods

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Results

Get Radiology Tree app to read full this article<

Table 1

Characteristics of Insurance Type

Insurance Type Number of Patients Percent Managed Care 344 55.75 Medicare 66 10.70 Medicare with supplement 55 8.91 Medicaid 49 7.94 Private insurance 37 6.00 Military 13 2.11 Not insured 53 8.59

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Table 2

Distribution of the Breast Cancer Tumor Sizes Among Insured Patients versus Uninsured Patients

Insurance Status Tumor T1 Tumor T2 Tumor T3 Insured patients: 564 (91.4%) 406 (71.9%) 147 (26.1%) 11 (2%) Uninsured patients: 53 (8.6%) 21 (39.6%) 10 (18.9%) 22 (41.5%)

Table 3

Distribution of the Cancer Stages Among Insured Patients versus Uninsured Patients

Insurance Status Cancer Stages 0, I, II Cancer Stages III, IV Insured patients: 564 (91.4%) 433 (76.8%) 131 (23.2%) Uninsured patients: 53 (8.6%) 30 (56.6%) 23 (43.3%)

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Discussion

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

References

  • 1. Halpern M.T., Bian J., Ward E.M., et. al.: Insurance status and stage of cancer at diagnosis among women with breast cancer. Cancer 2007; 100: pp. 403-411.

  • 2. Roetzheim R.G., Gonzalez E.C., Ferrante J.M., et. al.: Effects of health insurance and race on breast carcinoma treatments and outcomes. Cancer 2000; 89: pp. 2202-2213.

  • 3. National Cancer Institute Breast Cancer Screening Consortium: Screening mammography: a missed clinical opportunity. JAMA 1990; 264: pp. 54-58.

  • 4. Haywood R., Shapiro M., Freeman H., et. al.: Who gets screened for cervical and breast cancer?. Arch Intern Med 1998; 148: pp. 1177-1181.

  • 5. Ayanian J.Z., Kohler B.A., Abe T., et. al.: The relationship between health insurance coverage and clinical outcomes among women with breast cancer. N Engl J Med 1993; 329: pp. 326-331.

  • 6. Hadley J., Steinberg E.P., Feder J.: Comparison of uninsured and privately insured hospital patients: condition on admission, resource use, and outcome. JAMA 1991; 265: pp. 374-379.

  • 7. Lurie N., Ward N.B., Shapiro M.F., et. al.: Termination from Medi-Cal benefits—does it affect health?. N Engl J Med 1984; 311: pp. 480-484.

  • 8. Lurie N., Ward N.B., Shapiro M.F., et. al.: Termination from Medi-Cal benefits: a follow-up study one year later. N Engl J Med 1986; 314: pp. 1266-1268.

  • 9. Gorey K.M., Kliewer E., Holowaty E.J., et. al.: An international comparison of cancer survival: metropolitan Toronto, Ontario, and Honolulu, Hawaii. Am J Public Health 2000; 90: pp. 866-1871.

  • 10. American Cancer Society: Mammograms and other breast imaging procedures. http://www.cancer.org/docroot/PED/content/PED_2_3X_Mammography_and_Other_Breast_Imaging_Procedures.asp? Accessed May 1, 2008

  • 11. American Medical Association: AMA policies on breast cancer: H-55.993 Early detection of breast cancer. http://www.ama-assn.org/ama/pub/category/9060.html Accessed May 1, 2008

  • 12. Chaverly F., White E.: Recent trends in breast cancer mortality among white and black US women. Am J Public Health 1997; 87: pp. 775-781.

  • 13. National Cancer Institute: Cellular classification of breast cancer. http://www.cancer.gov/cancertopics/pdq/treatment/breast/HealthProfessional/page3#Section_30 Accessed May 1, 2008

  • 14. Cancer facts and figures 2004: American Cancer Society. Cancer facts and figures: 9–10 http://www.cancer.org/downloads/STT/CAFF2004PWSecured.pdf Accessed May 1, 2008

  • 15. Short P.F., Graefe D.: Battery-powered health insurance?. Health Affairs 2003; 22: pp. 244-255.

  • 16. Chu K.C., Tarone R.E., Brawley O.W.: Breast cancer trends of black women compared with white women. Arch Family Med 1999; 8: pp. 521-528.

  • 17. Lyman G.H., Kuderer N.M., Lyman S.L., et. al.: Importance of race on breast cancer survival. Ann Surg Oncol 1997; 4: pp. 80-87.

  • 18. Ely J.W., Hill H., Chen V.W., et. al.: Racial differences in survival from breast cancer. JAMA 1994; 272: pp. 947-954.

  • 19. Carey L.A., Perou C.M., Livasy C., et. al.: Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 2006; 295: pp. 2492-2502.

This post is licensed under CC BY 4.0 by the author.