Validation of cost-effective model for breast self-examination

Abstract

Introduction: The incidence of breast cancer is increasing in India; it predominantly affects women in their 30s and 40s. The disease burden is very high given the high incidence of triple-negative disease in a large portion of the population. Early detection can save lives and aid in breast conservation surgery. Breast self-examination (BSE) is a valid tool for early breast cancer detection. If performed with the help of a simulation model that resembles a given culture and tradition, it can result in good outcomes from screening programs. We designed and validated an Indian model for BSE and reported the feasibility of this model. Materials and methods: We designed an Indian model for the BSE based on the cultural mindset of Indian women. The design was finalized, and the model was constructed. It was then compared with preexisting international models and validated by in-depth interviews with validation experts from various fields involved in breast cancer management. Minor design revisions were made, followed by testing and re-testing. Finally, it was ready for public use. Results: The in-depth interview was conducted using a validated modified animation multimedia questionnaire. The majority of the validation experts had used stimulation models before, and all stated that it could help teach women about BSE, and it was comparable with other preexisting internationally validated models (91.33±4.98%). Conclusion: Using a breast model, women can learn to detect breast cancer as early as possible, and this can lead to good outcomes. We designed the model using easily available, cheap, and safe materials to keep it as realistic and useful as possible. The Indian BSE model can be used by Indian women to learn to detect breast lumps early. It is easily reproducible and cost-effective.