Geographic Variations of Colorectal and Breast Cancer Late-Stage Diagnosis and the Effects of Neighborhood-Level Factors

Abstract 27 Background: Although Kazakhstan (KZ) has made significant investments to improve population health, high cancer rates persist, with breast cancer as the most prevalent. We assessed factors that contribute to delays in treatment and late staging for patients with breast cancer. Methods: A retrospective follow-up study design was used. By using 2014 registry data, we identified 4,248 patients with breast cancer who were treated at cancer centers in the 16 KZ regions. Patients with delays in treatment as a result of medical errors and other reasons were identified. We used logistic regression to estimate associations of delays with patient demographics, occupation, and cancer center region; and associations of late-stage (III and IV) cancer diagnosis with delays in treatment while controlling for patient demographics, occupation, and cancer center region. Results: Approximately 9% (n = 378) of patients experienced delayed treatment. Older and Russian patients as well as those treated in regions further away from Almaty City had significantly higher adjusted risk of delayed treatment. However, risk of late-stage diagnosis was greater for patients who were treated in Almaty City and for those who were Russian, unemployed, or who had delayed treatment. Conclusion: The main driver of delayed treatment was cancer center region. Patients who were treated in Almaty City, where the national cancer research and treatment center is located, had fewer delays in treatment but a higher likelihood of late-stage diagnosis, likely as a result of referrals of sicker patients from neighboring regions. These findings suggest that referrals to new tertiary care centers being developed in KZ may reduce treatment delays but affect facility case mix. Future research will examine the role played by distance to cancer centers in access to specialty care and whether tertiary care is associated with improved outcomes conditional on case mix. AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST No COIs from the authors.

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Modeling Geospatial Patterns of Late-Stage Diagnosis of Breast Cancer in the US

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph14050484 ◽

2017 ◽

Vol 14 (5) ◽

pp. 484 ◽

Cited By ~ 9

Author(s):

Lee Mobley ◽

Tzy-Mey Kuo ◽

Lia Scott ◽

Yamisha Rutherford ◽

Srimoyee Bose

Keyword(s):

Breast Cancer ◽

Late Stage ◽

The Us ◽

Late Stage Diagnosis

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Frequency of late-stage breast cancer diagnoses despite high mammography screening rates in an HMO

Journal of Clinical Oncology ◽

10.1200/jco.2009.27.15_suppl.1526 ◽

2009 ◽

Vol 27 (15_suppl) ◽

pp. 1526-1526

Author(s):

R. Haque ◽

J. E. Schottinger ◽

M. H. Kanter ◽

C. C. Avila ◽

R. Contreras ◽

...

Keyword(s):

Breast Cancer ◽

Late Stage ◽

Mammography Screening ◽

Early Stage ◽

Advanced Tumor Stage ◽

Early Stage Disease ◽

Advanced Tumor ◽

Stage Disease ◽

Late Stage Diagnosis ◽

The Impact

1526 Background: Kaiser Permanente Southern California (KPSC) led the nation in screening women for breast cancer (BCa) with a mammography rate of nearly 90% in 2007 according to 2008 Healthcare Effectiveness Data and Information Set (HEDIS) measures. Despite successes in improving screening rates in this health plan that serves 3+ million diverse members, the percentage of women diagnosed with late stage BCa (stage III, IV) remained stable, varying from 12.9% (N∼323) in 2003 to 10.8% (N∼270) in 2007. To identify patient and health care factors associated with late stage diagnosis and the impact of its enhanced screening implementation guidelines, KPSC undertook this study. Methods: This cross-sectional study included a cohort of 10,580 BCa patients from 2003–2007. We compared women diagnosed with late stage disease versus those with early stage disease (stages I, II). P values (2-sided) were based on the chi-square distribution. Adjusted odds ratios and 95% confidence intervals were estimated using unconditional logistic regression. Results: Factors that were positively associated with late stage diagnosis in the univariate analyses included age, lack of recent mammography screening, worse tumor features, 80+ years of age, minority race, lower geocoded household income, increased healthcare visits, and use of Pap testing (P < 0.01 for all variables). Factors significantly associated with late stage diagnosis in the multivariate model included only lack of recent mammography screening (OR = 1.35, 95% CI: 1.14–1.58) and worse tumor features including high grade (grade 3, OR = 2.58, 95% CI: 1.96–3.40), positive lymph nodes (OR = 53.49, 95% CI: 39.90–71.72), and HER-2+ tumors (OR = 1.40, 95% CI: 1.13–1.72). Conclusions: Targeting older women, those with lower utilization, and women who did not have a recent mammogram may help further lower the prevalence of late stage diagnoses. However, given the extent of the health plan's previous efforts to enhance BCa screening rates, a ceiling effect may limit additional benefit. Additional efforts to decrease the rate of advanced tumor stage at diagnosis may include improving interpretation of mammograms or earlier detection of aggressive tumors by enhanced BRCA genetic testing. No significant financial relationships to disclose.

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