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High Level of miR-18a Promote Radiotherapy Progress in Non-Small Cell Lung Cancer
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Palliative radiotherapy has become an important treatment way for local control of advanced Non-Small Cell Lung Cancer (NSCLC). Current investigation aims to clarify miR-18a as a predictor of radiotherapy sensitivity, its cutoff value for predicting response. 70 patients with NSCLC were enrolled for radiotherapy during the period of 2018-2020. The level of miR-18a in blood were detected by using Quantitative PCR. Another seven variances including age, sex, smoking history, pathologic stage, radiation therapy days, radiation dosage and radiation type were enrolled to predict radiation therapy response. The level of hasmiR- 18a showed higher in patients with poor effects after radiation therapy (P<0.001). The optimal cut-off value of 18.287 for miR-18a alone with AUC of 0.879 (95% confidence interval, 0.8-0.958) can predict the radiation therapy effectiveness. Hsa-mir-18a is significantly positive (β1=-0.2845, P=0.0001) in logistical regression model AUC of 0.89 (95% confidence interval, 0.811-0.97). Hsa-mir-18a is the most important factors in random forest model with an AUC of 0.69 (95% confidence interval, 0.6-0.82) for predicting the radiation therapy effectiveness. High expressed hsa-mir-18a positively correlated with radiation therapy progress in patients with advanced NSCLC.
Title: High Level of miR-18a Promote Radiotherapy Progress in Non-Small Cell Lung Cancer
Description:
Palliative radiotherapy has become an important treatment way for local control of advanced Non-Small Cell Lung Cancer (NSCLC).
Current investigation aims to clarify miR-18a as a predictor of radiotherapy sensitivity, its cutoff value for predicting response.
70 patients with NSCLC were enrolled for radiotherapy during the period of 2018-2020.
The level of miR-18a in blood were detected by using Quantitative PCR.
Another seven variances including age, sex, smoking history, pathologic stage, radiation therapy days, radiation dosage and radiation type were enrolled to predict radiation therapy response.
The level of hasmiR- 18a showed higher in patients with poor effects after radiation therapy (P<0.
001).
The optimal cut-off value of 18.
287 for miR-18a alone with AUC of 0.
879 (95% confidence interval, 0.
8-0.
958) can predict the radiation therapy effectiveness.
Hsa-mir-18a is significantly positive (β1=-0.
2845, P=0.
0001) in logistical regression model AUC of 0.
89 (95% confidence interval, 0.
811-0.
97).
Hsa-mir-18a is the most important factors in random forest model with an AUC of 0.
69 (95% confidence interval, 0.
6-0.
82) for predicting the radiation therapy effectiveness.
High expressed hsa-mir-18a positively correlated with radiation therapy progress in patients with advanced NSCLC.
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