4.3 Article

Population risk factors for late-stage presentation of cervical cancer in sub-Saharan Africa

Journal

CANCER EPIDEMIOLOGY
Volume 53, Issue -, Pages 81-92

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.canep.2018.01.014

Keywords

Uterine cervical neoplasms; Africa south of the Sahara; Incidence; Prevalence; Risk factors; Condoms; Rural population; HIV infections; Socioeconomic factors

Funding

  1. South African MRC
  2. South African National Department of Health
  3. GSK (RD)
  4. MRC UK
  5. MRC [MC_PC_16098] Funding Source: UKRI
  6. Medical Research Council [MC_PC_16098] Funding Source: researchfish

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Background: Cervical cancer is the most prevalent malignancy in sub-Saharan Africa (SSA) with many women only seeking professional help when they are experiencing symptoms, implying late-stage malignancy and higher mortality rates. This ecological study assesses population-level exposures of SSA women to the numerous risk factors for HPV infection and cervical cancer, against late-stage presentation of cervical cancer. Materials and method: A literature review revealed the relevant risk factors in SSA. Open-access databases were mined for variables closely representing each risk factor. A proxy for late-stage presentation was used (ratio of incidence-to-mortality, IMR), and gathered from IARC's GLOBOCAN 2012 database. Variables showing significant correlation to the IMR were used in stepwise multiple regression to quantify their effect on the IMR. Results: Countries with high cervical cancer mortality rates relative to their incidence have an IMR nearer one, suggesting a larger proportion of late-stage presentation. Western Africa had the lowest median IMR (1.463), followed by Eastern Africa (IMR= 1.595) and Central Africa (IMR= 1.675), whereas Southern Africa had the highest median IMR (1.761). Variables selected for the final model explain 65.2% of changes seen in the IMR. Significant predictors of IMR were GDP (coefficient= 2.189x10(-6), p= 0.064), HIV infection (-1.936x10(-3), p= 0.095), not using a condom (-1.347x10(-3), p= 0.013), high parity (-1.744x10(-2), p= 0.008), and no formal education (-1.311x10(-3), p < 0.001). Conclusion: Using an IMR enables identification of factors predicting late-stage cervical cancer in SSA including: GDP, HIV infection, not using a condom, high parity and no formal education.

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