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Integrated approach to prediction of cervical intra‐epithelial neoplasia status through a case‐control study
Author(s) -
Sengupta Subrata,
Chaudhuri Salil K.,
Das Prasun,
Raichaudhuri Bulbul,
Pramanik Raghunath
Publication year - 1999
Publication title -
international journal of cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.475
H-Index - 234
eISSN - 1097-0215
pISSN - 0020-7136
DOI - 10.1002/(sici)1097-0215(19990219)84:1<69::aid-ijc13>3.0.co;2-j
Subject(s) - logistic regression , medicine , multivariate analysis , parity (physics) , papanicolaou stain , regression analysis , multivariate statistics , gynecology , cervical cancer , odds ratio , cervix , population , demography , statistics , obstetrics , cancer , mathematics , environmental health , physics , particle physics , sociology
A case‐control study on cervical intra‐epithelial neoplasia (CIN) was carried out on 398 subjects in the state of West Bengal, India. These samples were taken from mass screening programs organized by the authors, maintaining the uniformity of sampling to the extent possible. The cervical smears were tested by the Papanicolaou (PAP) method, following the Bethesda system for reporting of CIN status. Odds ratios and correlation coefficients among different variables, assumed to produce carcinoma of the cervix, show that 6 out of 11 variables, i.e., age, education, socio‐economic status, duration of marriage, age at marriage and body surface, are associated with CIN. Multivariate analysis of logistic regression was carried out using BMDP‐LR with dichotomized response variables considering CIN (0 and 1) in one group and CIN (2 and 3) in the other group. The outcome of the analysis indicated that age and educational level are 2 contributing factors for CIN. The percentage of correct classification in this analysis has improved to 74.5%, with a probability of 0.90. Polychotomous regression analysis was carried out using BMDP‐PR in the next step. This analysis showed that parity was a contributing factor, in addition to age and educational level. These 3 factors provide a predictive model for identifying the high‐risk group in a rational way. This approach would restrict screening to approximately 10% of the population. Subsequently, the model has been validated in a confirmatory trial among 85 new cases and was found to work satisfactorily. Int. J. Cancer (Pred. Oncol.) 84:69–73, 1999. © 1999 Wiley‐Liss, Inc.