Predictive models for personalized precision medical intervention in spontaneous regression stages of cervical precancerous lesions.
J Transl Med
; 22(1): 686, 2024 Jul 26.
Article
em En
| MEDLINE
| ID: mdl-39061062
ABSTRACT
BACKGROUND:
During the prolonged period from Human Papillomavirus (HPV) infection to cervical cancer development, Low-Grade Squamous Intraepithelial Lesion (LSIL) stage provides a critical opportunity for cervical cancer prevention, giving the high potential for reversal in this stage. However, there is few research and a lack of clear guidelines on appropriate intervention strategies at this stage, underscoring the need for real-time prognostic predictions and personalized treatments to promote lesion reversal.METHODS:
We have established a prospective cohort. Since 2018, we have been collecting clinical data and pathological images of HPV-infected patients, followed by tracking the progression of their cervical lesions. In constructing our predictive models, we applied logistic regression and six machine learning models, evaluating each model's predictive performance using metrics such as the Area Under the Curve (AUC). We also employed the SHAP method for interpretative analysis of the prediction results. Additionally, the model identifies key factors influencing the progression of the lesions.RESULTS:
Model comparisons highlighted the superior performance of Random Forests (RF) and Support Vector Machines (SVM), both in clinical parameter and pathological image-based predictions. Notably, the RF model, which integrates pathological images and clinical multi-parameters, achieved the highest AUC of 0.866. Another significant finding was the substantial impact of sleep quality on the spontaneous clearance of HPV and regression of LSIL.CONCLUSIONS:
In contrast to current cervical cancer prediction models, our model's prognostic capabilities extend to the spontaneous regression stage of cervical cancer. This model aids clinicians in real-time monitoring of lesions and in developing personalized treatment or follow-up plans by assessing individual risk factors, thus fostering lesion spontaneous reversal and aiding in cervical cancer prevention and reduction.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Lesões Pré-Cancerosas
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Neoplasias do Colo do Útero
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Medicina de Precisão
Limite:
Adult
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Female
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Humans
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Middle aged
Idioma:
En
Revista:
J Transl Med
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China