PURPOSE Delays across the entire cancer care continuum are not uncommon. This cross-sectional study explored the health care trajectories of Surinamese women with breast cancer and identified predictors of timely diagnosis and treatment initiation. METHODS One hundred women age 30 years or older who were newly diagnosed with breast cancer in 2017 to 2018 were recruited from all 4 hospitals in Paramaribo. Data on their demographics, lifestyle, reproductive and medical history, health status, and family history of breast cancer and other malignancies were collected using a validated semistructured questionnaire. Using Anderson’s Model of Pathways to Treatment, we defined a patient interval (from detection to first consultation), diagnostic interval (from consultation to histopathologic diagnosis), and treatment interval (from diagnosis to first treatment). Log-transformed data were analyzed using linear regression, and variables with P ≤ .05 were considered statistically significant predictors of intervals. RESULTS All participants had health insurance and access to health care. Eighty-five percent of patients presented with early-stage disease. Ninety percent of patients had self-detected their disease, with 70% finding a lump. Average age was 55.6 years (± 11.8 years). Median durations of patient, diagnostic, and treatment intervals were 13 days (interquartile, range, 4-63 days), 40 days (IQR, 21-57 days), and 18 days (IQR, 8-38 days), respectively. Median duration of the entire interval was 95 days (IQR, 59-272 days). Patient-related factors associated with the intervals were religion (β = −530; P = .003), being employed (β = 149.4; P = .007), and age 50 years and older (β = −195.8; P = .037). Disease-related factors were lump as first symptom (β = −175.6; P = .038) and late-stage disease at diagnosis (β = 213.5; P = .004). CONCLUSION Given the limited-resource setting, delays in Suriname’s health care can be minimized by programs aimed at increasing breast cancer awareness and education; however, delays may have been underestimated as a result of the over-representation of early-stage disease and recall bias regarding the first symptom detected.
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