Please use this identifier to cite or link to this item: http://localhost:80/xmlui/handle/123456789/13369
Title: Statistical Evaluation of Accuracy of Mammography in Early Breast Cancer Detection
Authors: SAIF, SAIMA QAYYUM
ISHTIAQ, MUHAMMAD TAYYAB
SADIQ, RAFSHAN
SHAHID, ATTIQUE KHAN
MARYAM, AROOMA
ASLAM, SIDRA
ASLAM, TEHZEEB
ASLAM, SADIA
TUSLEEM, KISHVER
QAMAR, MUHAMMAD TAHIR UL
Keywords: Mammography
Sensitivity
Specificity
Predictive probability
Issue Date: Dec-2017
Publisher: Pakistan Journal of Medical and Health Sciences
Citation: MARYAM, A., SAIF, S., ASLAM, T., ASLAM, S., TUSLEEM, K., & QAMAR, M. T. U. (2017). Statistical Evaluation of Accuracy of Mammography in Early Breast Cancer Detection. Pakistan J Med Health Sci, 11(4), 1430-5.
Abstract: Aim: To assess the clinical significance of mammography in early stage breast lump detection which could assist health practitioners in taking appropriate prognostic measures for lowering breast cancer burden in Faisalabad region. Methods: Cross sectional comparative study was designed to collect the data of symptoms associated to breast cancer from 250 women enrolled in breast cancer section of Punjab Institute of Nuclear Medicine (PINUM). Afterwards mammography screening of 60 highly suspicious cases was done. Diagnostic reports based on mammograms were analyzed to study the compliance of mammography reports and symptoms reported by patients. True positive (TP), false positive (FP), true negative (TN) and false negative (FN) outcomes were elucidated to evaluate the predictive accuracy of mammography in early breast lump detection by calculation specificity, sensitivity, positive likelihood ratio and negative likelihood ratio. Specificity and sensitivity results were further used to calculate the predictive probability through Pearson chi square test at < 0.05 significance level through SPSS v10.0. Results: Sensitivity, specificity, positive likelihood ratio and negative likelihood ratio of early breast cancer detection through mammography screening in our study sample of mammography was 83.33% [95%CI= 67.19% to 93.63%], 91.67% [95%CI= 73.00% to 98.97%], 10.00 at [95%CI= 2.63 to 38.00] and 0.18 [95%CI= 0.09 to 0.38]respectively which clearly demonstrate that system is well versed to identify true positive and true negative cases and give least prediction of false negative results. Moreover, Predicative probability (p-value <0.00001) calculated by Pearson Chi-square ( 2 ) test at 0.05 significance level indicate a highly significant correlation between mammography performance and clinical symptoms of breast cancer. Conclusion: Our findings suggest that mammography is highly efficient and promising imaging technique. Looking at its high accuracy in early breast cancer detection, breast cancer screening through mammography should be encouraged and worth being practiced.
URI: http://142.54.178.187:9060/xmlui/handle/123456789/13369
ISSN: 1996-7195
Appears in Collections:Oct-Dec,2017,Issue(4)

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