Design considerations for identifying breast cancer risk factors in a population-based study in Africa

Design considerations for identifying breast cancer risk factors in a population-based study in Africa

Abstract

OBJECTIVE

Although breast cancer is becoming more prevalent in Africa, few epidemiologic studies have been undertaken and appropriate methodologic approaches remain uncertain.

MATERIALS AND METHODS

We conducted a population-based case-control study in Accra and Kumasi, Ghana, enrolling 2,202 women with lesions suspicious for breast cancer and 2,161 population controls. Biopsy tissue for cases prior to neoadjuvant therapy (if given), blood, saliva and fecal samples were sought for study subjects. Response rates, risk factor prevalences and odds ratios for established breast cancer risk factors were calculated.

RESULTS

A total of 54.5% of the recruited cases were diagnosed with malignancies, 36.0% with benign conditions and 9.5% with indeterminate diagnoses. Response rates to interviews were 99.2% in cases and 91.9% in controls, with the vast majority of interviewed subjects providing saliva (97.9% in cases vs. 98.8% in controls) and blood (91.8% vs. 82.5%) samples; lower proportions (58.1% vs. 46.1%) provided fecal samples. While risk factor prevalences were unique as compared to women in other countries (e.g., less education, higher parity), cancer risk factors resembled patterns identified elsewhere (elevated risks associated with higher levels of education, familial histories of breast cancer, low parity and larger body sizes). Subjects with benign conditions were younger and exhibited higher socioeconomic profiles (e.g., higher education and lower parity) than those with malignancies, suggesting selective referral influences.

CONCLUSIONS

While further defining breast cancer risk factors in Africa, this study showed that successful population-based interdisciplinary studies of cancer in Africa are possible but require close attention to diagnostic referral biases and standardized and documented approaches for high-quality data collection, including biospecimens.

To read more, see the following article on the PubMed website: PMID: 28295287