A multi-variable predictive warning model for cervical cancer using clinical and SNPs data
Xiangqin Li,
Ruoqi Ning,
Bing Xiao
et al.
Abstract:IntroductionCervical cancer is the fourth most common cancer among female worldwide. Early detection and intervention are essential. This study aims to construct an early predictive warning model for cervical cancer and precancerous lesions utilizing clinical data and simple nucleotide polymorphisms (SNPs).MethodsClinical data and germline SNPs were collected from 472 participants. Univariate logistic regression, least absolute shrinkage selection operator (LASSO), and stepwise regression were performed to scr… Show more
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