Our study describes the incidence and risk factors for undiagnosed diabetes in elderly cancer patients. Using Surveillance, Epidemiology, and End Results-Medicare data, we followed patients with breast, colorectal, lung, or prostate cancer from 24 months before to 3 months after cancer diagnosis. Medicare claims were used to exclude patients with diabetes 24 to 4 months before cancer (look-back period), identify those with diabetes undiagnosed until cancer, and construct indicators of preventive services, physician contact, and comorbidity during the look-back period. Logistic regression analyses were performed to identify factors associated with undiagnosed diabetes. Overall, 2,678 patients had diabetes undiagnosed until cancer. Rates were the highest in patients with both advanced-stage cancer and low prior primary care/medical specialist contact (breast 8.2%, colorectal 5.9%, lung 4.4%). Nonwhite race/ethnicity, living in a census tract with a higher percent of the population in poverty and a lower percent college educated, lower prior preventive services use, and lack of primary care and/or medical specialist care prior to cancer all were associated with higher adjusted odds of undiagnosed diabetes. Undiagnosed diabetes is relatively common in selected subgroups of cancer patients, including those already at high risk of poor outcomes due to advanced cancer stage. 1. Introduction Diabetes and the metabolic derangements typical of diabetes are associated with poor prognosis in cancer [1–11]. In perhaps the most comprehensive study to date; Barone and colleagues [2] performed a systematic review and meta-analysis of the literature and found that preexisting diabetes was associated with statistically significant increases of 41% for all-cause mortality, across multiple tumor types, and 76%, 61%, and 32% in endometrial, breast, and colorectal cancer, respectively. Poor prognosis may be influenced through biological mechanisms related to hyperglycemia, hyperinsulinemia, and inflammation, which result in tumor cell proliferation and metastases [3–5, 12]. Other factors include less aggressive cancer treatment due to diabetes-related comorbidity [13], poorer response to cancer treatment [7, 11], presentation with later-stage cancer due to suboptimal cancer screening practices and other preventive health-seeking behavior [14], and that diagnosis of cancer may distract both the patient and the health care team from appropriate management of glycemia, blood pressure, and lipids [2]. Factors thought to play a role in observed associations between preexisting
References
[1]
E. Giovannucci, D. M. Harlan, M. C. Archer et al., “Diabetes and cancer: a consensus report,” Diabetes Care, vol. 33, no. 7, pp. 1674–1685, 2010.
[2]
B. B. Barone, H.-C. Yeh, C. F. Snyder et al., “Long-term all-cause mortality in cancer patients with preexisting diabetes mellitus: a systematic review and meta-analysis,” Journal of the American Medical Association, vol. 300, no. 23, pp. 2754–2764, 2008.
[3]
B. M. Wolpin, J. A. Meyerhardt, A. T. Chan et al., “Insulin, the insulin-like growth factor axis, and mortality in patients with nonmetastatic colorectal cancer,” Journal of Clinical Oncology, vol. 27, no. 2, pp. 176–185, 2009.
[4]
J. Ma, H. Li, E. Giovannucci et al., “Prediagnostic body-mass index, plasma C-peptide concentration, and prostate cancer-specific mortality in men with prostate cancer: a long-term survival analysis,” The Lancet Oncology, vol. 9, no. 11, pp. 1039–1047, 2008.
[5]
L. L. Lipscombe, P. J. Goodwin, B. Zinman, J. R. McLaughlin, and J. E. Hux, “The impact of diabetes on survival following breast cancer,” Breast Cancer Research and Treatment, vol. 109, no. 2, pp. 389–395, 2008.
[6]
L. C. Richardson and L. A. Pollack, “Therapy insight: influence of type 2 diabetes on the development, treatment and outcomes of cancer,” Nature Clinical Practice Oncology, vol. 2, no. 1, pp. 48–53, 2005.
[7]
M. A. Weiser, M. E. Cabanillas, M. Konopleva et al., “Relation between the duration of remission and hyperglycemia during induction chemotherapy for acute lymphocytic leukemia with a hyperfractionated cyclophosphamide, vincristine, doxorubicin, and dexamethasone/methotrexate-cytarabine regimen,” Cancer, vol. 100, no. 6, pp. 1179–1185, 2004.
[8]
S. S. Coughlin, E. E. Calle, L. R. Teras, J. Petrelli, and M. J. Thun, “Diabetes mellitus as a predictor of cancer mortality in a large cohort of US adults,” The American Journal of Epidemiology, vol. 159, no. 12, pp. 1160–1167, 2004.
[9]
S. H. Saydah, C. M. Loria, M. S. Eberhardt, and F. L. Brancati, “Abnormal glucose tolerance and the risk of cancer death in the United States,” The American Journal of Epidemiology, vol. 157, no. 12, pp. 1092–1100, 2003.
[10]
G. Verlato, G. Zoppini, E. Bonora, and M. Muggeo, “Mortality from site-specific malignancies in type 2 diabetic patients from Verona,” Diabetes Care, vol. 26, no. 4, pp. 1047–1051, 2003.
[11]
J. A. Meyerhardt, P. J. Catalano, D. G. Haller et al., “Impact of diabetes mellitus on outcomes in patients with colon cancer,” Journal of Clinical Oncology, vol. 21, no. 3, pp. 433–440, 2003.
[12]
I. Wolf, S. Sadetzki, R. Catane, A. Karasik, and B. Kaufman, “Diabetes mellitus and breast cancer,” The Lancet Oncology, vol. 6, no. 2, pp. 103–111, 2005.
[13]
L. V. van de Poll-Franse, S. Houterman, M. L. G. Janssen-Heijnen, M. W. Dercksen, J. W. W. Coebergh, and H. R. Haak, “Less aggressive treatment and worse overall survival in cancer patients with diabetes: a large population based analysis,” International Journal of Cancer, vol. 120, no. 9, pp. 1986–1992, 2007.
[14]
A. M. McBean and X. Yu, “The underuse of screening services among elderly women with diabetes,” Diabetes Care, vol. 30, no. 6, pp. 1466–1472, 2007.
[15]
M. D. Danese, C. O’Malley, K. Lindquist, M. Gleeson, and R. I. Griffiths, “An observational study of the prevalence and incidence of comorbid conditions in older women with breast cancer,” Annals of Oncology, vol. 23, no. 7, pp. 1756–1765, 2012.
[16]
N. L. Keating, M. B. Landrum, J. Z. Ayanian, E. P. Winer, and E. Guadagnoli, “The association of ambulatory care with breast cancer stage at diagnosis among medicare beneficiaries,” Journal of General Internal Medicine, vol. 20, no. 1, pp. 38–44, 2005.
[17]
M. E. Gornick, P. W. Eggers, and G. F. Riley, “Associations of race, education, and patterns of preventive service use with stage of cancer at time of diagnosis,” Health Services Research, vol. 39, no. 5, pp. 1403–1427, 2004.
[18]
S. T. Fleming, H. G. Pursley, B. Newman, D. Pavlov, and K. Chen, “Comorbidity as a predictor of stage of illness for patients with breast cancer,” Medical Care, vol. 43, no. 2, pp. 132–140, 2005.
[19]
L. X. Clegg, M. E. Reichman, B. A. Miller et al., “Impact of socioeconomic status on cancer incidence and stage at diagnosis: selected findings from the surveillance, epidemiology, and end results: National Longitudinal Mortality Study,” Cancer Causes and Control, vol. 20, no. 4, pp. 417–435, 2009.
[20]
J. L. Warren, C. N. Klabunde, D. Schrag, P. B. Bach, and G. F. Riley, “Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population,” Medical Care, vol. 40, no. 8, pp. 3–18, 2002.
[21]
National Cancer Institute, “Overview of the SEER Program,” National Cancer Institute, Bethesda, Md, USA, 2011, http://seer.cancer.gov/about/overview.html.
[22]
National Cancer Institute, “Overview of the SEER Program,” National Cancer Institute, Bethesda, Md, USA, 2011, http://healthservices.cancer.gov/seermedicare/overview/linked.html.
[23]
The American Cancer Society Cancer Action Network, “Cancer and Medicare: a chartbook,” The American Cancer Society, Washington, DC, USA, 2012, http://action.acscan.org/site/DocServer/medicare-chartbook.pdf?docID=12061.
[24]
P. L. Hebert, L. S. Geiss, E. F. Tierney, M. M. Engelgau, B. P. Yawn, and A. M. McBean, “Identifying persons with diabetes using medicare claims data,” The American Journal of Medical Quality, vol. 14, no. 6, pp. 270–277, 1999.
[25]
A. Fritz and L. Ries, Eds., SEER Program Code Manual, Cancer Statistics Branch, Surveillance Program, Division of Cancer Control and Pop Sciences, National Cancer Institute, National Institutes of Health, Public Health Service, U.S. Dept of Health and Human Services, Bethesda, Md, USA, 3rd edition, 1998, http://seer.cancer.gov/manuals/codeman.pdf.
[26]
C. N. Klabunde, A. L. Potosky, J. M. Legler, and J. L. Warren, “Development of a comorbidity index using physician claims data,” Journal of Clinical Epidemiology, vol. 53, no. 12, pp. 1258–1267, 2000.
[27]
C. N. Klabunde, J. M. Legler, J. L. Warren, L.-M. Baldwin, and D. Schrag, “A refined comorbidity measurement algorithm for claims-based studies of breast, prostate, colorectal, and lung cancer patients,” Annals of Epidemiology, vol. 17, no. 8, pp. 584–590, 2007.
[28]
National Cancer Institute, “Overview of the SEER Program,” National Cancer Institute, Bethesda, Md, USA, 2010, http://healthservices.cancer.gov/seermedicare/program/remove.ruleout.dxcodes.macro.txt.
[29]
National Cancer Institute, “of the SEER Program,” National Cancer Institute, Bethesda, Md, USA, 2010, http://healthservices.cancer.gov/seermedicare/program/charlson.comorbidity.macro.txt.
[30]
M. E. Charlson, P. Pompei, K. A. Ales, and C. R. MacKenzie, “A new method of classifying prognostic comorbidity in longitudinal studies: development and validation,” Journal of Chronic Diseases, vol. 40, no. 5, pp. 373–383, 1987.
[31]
R. A. Deyo, D. C. Cherkin, and M. A. Ciol, “Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases,” Journal of Clinical Epidemiology, vol. 45, no. 6, pp. 613–619, 1992.
[32]
P. S. Romano, L. L. Roos, H. S. Luft, J. G. Jollis, and K. Doliszny, “A comparison of administrative versus clinical data: coronary artery bypass surgery as an example,” Journal of Clinical Epidemiology, vol. 47, no. 3, pp. 249–260, 1994.
[33]
R. Ashkenazy and M. J. Abrahamson, “Medicare coverage for patients with diabetes: a national plan with individual consequences,” Journal of General Internal Medicine, vol. 21, no. 4, pp. 386–392, 2006.