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Factors associated with delays in time to treatment initiation in Colombian women with cervical cancer: A cross-sectional analysis. | LitMetric

AI Article Synopsis

  • Cervical cancer is a major health issue in Colombia, particularly affecting women, and treatment delays are linked to worse outcomes.
  • * A study analyzed 1,249 newly diagnosed cases of cervical cancer in 2018, finding a median time to treatment initiation of 71 days, with only a small percentage starting treatment within 30 days.
  • * Factors like age, type of health insurance, and region significantly influenced delays, highlighting systemic healthcare access issues among various demographics.

Article Abstract

Cervical cancer (CC) is one of the leading causes of morbidity in upper-middle income countries such as Colombia. Several studies have reported poor prognosis when treatment is delayed. We aimed to describe the factors associated with delays in time to treatment initiation (TTI) in Colombian women with CC. Cross-sectional analysis including newly diagnosed cases of CC during 2018 and reported to the National Administrative Cancer Registry. TTI was defined as days from diagnosis to the first treatment (chemotherapy, radiation, or surgery). Linear and multinomial logistic regression models were estimated to analyze the association of interest. 1,249 new cases of CC were analyzed (26.98% and 40.11% locally advanced). The median age was 46 years (IQR: 36-58). Median TTI was 71 days (IQR: 42-105), varying from 70 days (IQR: 43-106) among the surgery group to 76 days (IQR: 41-118) in women under chemotherapy. Only 12.41% were treated within 30 days from diagnosis. TTI was significantly longer in women with state insurance (β = 18.95 days, 95% CI: 11.77-26.13) compared with those insured by the third payer. Women from the Pacific and Eastern regions also had a significantly longer TTI than those living in the capital of Colombia. Age, health insurance, region of residence, and stage at diagnosis were associated with TTI longer than 45 days in the multinomial model. We concluded that demographic variables (age, region of residence, and health insurance) which are proxies of social disparities and poor access to quality health care services, were associated with delays in TTI.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822946PMC
http://dx.doi.org/10.1016/j.gore.2021.100697DOI Listing

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