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BackgroundColposcopy is recommended once human papillomavirus (HPV)16/18 infection is detected. However, not all HPV16/18-positive women will necessarily develop cervical lesions. Therefore, this study aimed to investigate the application of quantitative HPV16 E7 oncoprotein detection as a cervical cancer screening method for more efficient screening while minimizing unnecessary colposcopy.MethodsE7 oncoprotein (HPV16) was quantitatively detected in cervical exfoliated cells of HPV16-positive women. The levels of HPV16 E7 oncoprotein in different degrees of cervical lesions were compared, and the optimal cut-off value for identifying HSIL+ was determined by receiver operating characteristic (ROC) curve analysis. With a pathological diagnosis as the gold standard, the sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and Kappa value were calculated to verify the diagnostic value of the method. Women diagnosed with low-grade squamous intraepithelial lesions (LSIL) and normal women were followed up for 5 years to evaluate the predictive value of HPV16 E7 protein for disease progression/persistent infection.ResultsThe expression level of HPV16 E7 oncoprotein was positively correlated with the degree of the cervical lesion (r = 0.589, P < 0.01). The area under the ROC curve (AUC) was 0.817 (confidence interval: 0.729–0.904). The cut-off value of E7 oncoprotein for identifying HSIL+ was 8.68 ng/ml. The SEN, SPE, PPV, NPV, and Kappa values of HPV16 E7 oncoprotein for the identification of HSIL+ were 87.1%,70.0%, 87.1%, 70.0%, and 0.571, respectively, which were higher than those of ThinPrep cytology test (TCT). The SEN, SPE, PPV, and NPV of HPV16 E7 oncoprotein in predicting disease progression/persistent infection were 93.75%, 91.30%, 88.24%, and 95.45%, respectively.ConclusionThe quantitative detection of HPV 16 E7 oncoprotein can not only accurately screen cervical lesions but also achieve efficient colposcopy referral. Additionally, HPV16 E7 oncoprotein can accurately predict the progression of cervical lesions and persistent HPV infection.