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ORIGINAL ARTICLE
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Assessment of common risk factors and validation of the Gail model for breast cancer: A hospital-based study from Western India


1 Department of General Surgery, Rabindra Nath Tagore Medical College and Hospital, Udaipur, Rajasthan, India
2 Department of Physiology, All India Institute of Medical Sciences, New Delhi, India

Correspondence Address:
Naveen Kumar,
Department of General Surgery, Rabindra Nath Tagore Medical College and Hospital, Udaipur - 313 001, Rajasthan
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/tcmj.tcmj_171_19

Objective: Modified Gail Model is a noninvasive, easy to implement risk estimation tool for absolute breast cancer risk. It was developed with data collected from non African American females and further modified for African-American, the Hispanic, and Native American populations. The use of this model for population outside the US and European country is not yet validated. We evaluated the prevalent risk factors and the effectiveness of the Gail model for risk assessment in our local Indian population. Materials and Methods: A retrospective analysis of a prospectively maintained database was conducted on patients treated between 2008 and 2013. Six hundred and fifty patients were included in each group. Six questions were taken as per the breast cancer risk assessment tool calculator. A value of over 1.67% was taken as a high risk for breast cancer development. Results: The mean age of the participant was 50 ± 21.3 years in cases and 41 ± 16.4 years incontrols. Age and age at first childbirth >30 years were found to be significant and associated with increased risk of breast carcinoma, but the age at menarche, family history, previous breast biopsy, and atypical hyperplasia was no significant. The Gail model was assessed, and sensitivity was 10.30% and 96.30% specificity for our population. Positive and negative predictive values were 73.62% and 51.77%. Conclusion: Our study concluded that the Gail model is not an appropriate risk assessment tool for the population in its present form. For the future application of this model, we need to perform a bigger study with a higher sample size representing a maximum number of local variabilities in the Indian population.


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    -  Kumar N
    -  Singh V
    -  Mehta G
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