Abstract:Background: Breast cancer is the most commonly diagnosed cancer among the female population of Assam, India. Chewing of betel quid with or without tobacco is common practice among female population of this region. Moreoverthe method of preparing the betel quid is different from other parts of the country.So matched case control study is conducted to analyse whetherbetel quid chewing plays a significant role in the high incidence of breast cancer occurrences in Assam. Methods and Material: Here, controls are matched to the cases by age at diagnosis (±5 years), family income and place of residence with matching ratio 1:1. Conditional logistic regression models and odd ratios (OR) was used to draw conclusions. Results: It is observed that cases are more habituated to chewing habits than the controls.Further the conditional logistic regression analysis reveals that betel quid chewer faces 2.353 times more risk having breast cancer than the non-chewer with p value 0.0003 (95% CI 1.334-4.150). Conclusion:Though the female population in Assam usually does not smoke, the addictive habits typical to this region have equal effect on the occurrence of breast cancer.
Background:Awareness is the primary means to control breast cancer occurrence. The purpose of the present work is to study the risk of breast cancer occurrence in different age group, for the study area, Assam, India, by means of survival analysis techniques.Methods:Survival and hazard functions are key concepts in survival analysis for describing the distribution of event times. In the present research a new individialized model has been proposed for cumulative hazard function, taking gamma probability distribution as probability distribution of breast cancer occurrences. Kaplan Meier Survival method has been applied to find out the probability of diseases occurrence in the early menarche and late menarche group. The data used for implementation were collected from the Record Department of a prime local cancer institute, for the period 2010-2012. The information for the risk factor age at menarche were collected from the patients registered during August 2011 to February 2012.Results:The study reveals that in the study area, cumulative hazard of the women belonging to 35 to 50 years is higher than the early and late aged women. The cumulative hazard plot with shape parameter 0.5, 1 and 10 shows that cumulative risk for early aged women are greater than the late age women but when this values is increased from 10, the opposite trend is observed. Further, the median age of disease occurrence among early menarche group is 52 years and for late menarche it is 54 years.Conclusion:The model developed could successfully point out the age group for women lying at higher risk of breast cancer occurrence. Additionally the important risk factor, age at menarche, was effectively applied to supplement to this calculation. It is hoped that practical use of this method would enhance not only awareness but also early detection of the said disease.
Context:Cytological changes in terms of shape and size of nuclei are some of the common morphometric features to study breast cancer, which can be observed by careful screening of fine needle aspiration cytology (FNAC) images.Aims:This study attempts to categorize a collection of FNAC microscopic images into benign and malignant classes based on family of probability distribution using some morphometric features of cell nuclei.Materials and Methods:For this study, features namely area, perimeter, eccentricity, compactness, and circularity of cell nuclei were extracted from FNAC images of both benign and malignant samples using an image processing technique. All experiments were performed on a generated FNAC image database containing 564 malignant (cancerous) and 693 benign (noncancerous) cell level images. The five-set extracted features were reduced to three-set (area, perimeter, and circularity) based on the mean statistic. Finally, the data were fitted to the generalized Pearsonian system of frequency curve, so that the resulting distribution can be used as a statistical model. Pearsonian system is a family of distributions where kappa (κ) is the selection criteria computed as functions of the first four central moments.Results and Conclusions:For the benign group, kappa (κ) corresponding to area, perimeter, and circularity was −0.00004, 0.0000, and 0.04155 and for malignant group it was 1016942, 0.01464, and −0.3213, respectively. Thus, the family of distribution related to these features for the benign and malignant group were different, and therefore, characterization of their probability curve will also be different.
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