Objective: To predict the risk factors of lymph node metastasis in cervical cancer by using large sample clinical data, and to construct and verify the nomogram for predicting lymph node metastasis. Methods: A total o...Objective: To predict the risk factors of lymph node metastasis in cervical cancer by using large sample clinical data, and to construct and verify the nomogram for predicting lymph node metastasis. Methods: A total of 5940 patients with cervical cancer from 2004 to 2015 in the National Cancer Institute Surveillance Epidemiology and End Results database were retrospectively screened and randomly assigned to training group (n = 4172) and validation group (n = 1768). Multivariate Logistic regression analysis was used, and the optimal model was selected according to AIC or BIC and likelihood ratio test, and a nomogram was drawn. The accuracy and robustness of the prediction model were evaluated in three aspects: discrimination, calibration and clinical net benefit. Results: The prediction model based on race, tumor tissue differentiation degree, tumor histopathological type, distant metastasis of tumor, tumor diameter and other risk factors was successfully established and a nomogram was constructed. The AUCs of training group and validation group were: 0.736 and 0.714, respectively. And the p-values of the Hosmer-Lemeshow test were 0.28 and 0.11, respectively. The calibration curve was in good agreement with the ideal curve. It had high accuracy and applicability after internal verification. Conclusion: A prediction model is constructed based on the risk factors of lymph node metastasis of cervical cancer. The nomogram has a good effective prediction and can provide a theoretical basis for clinicians to assess the disease quickly before surgery.展开更多
Background In general,sentinel lymph node (SLN) can reflect the whole state of the entire drainage area. The present study evaluated the clinical significance of sentinel lymph node identification in the treatment of ...Background In general,sentinel lymph node (SLN) can reflect the whole state of the entire drainage area. The present study evaluated the clinical significance of sentinel lymph node identification in the treatment of early stage cervical cancer.Methods Twenty-eight patients with early stage (Ia-IIa) cervical cancer undergoing radical hysterectomy and pelvic lymphadenectomy were included in this study. At two locations 8 hours before operation,0.4 ml 37 Mbq technicium-99 labeled dextran was injected intracervically. After that,preoperative lymphoscintigraphy was performed to detect SLNs. During the operation,lymph nodes were detected ex vivo by a γ-counter to identify SLNs. The samples of SLNs and non-SLNs were used for pathological examination separately and compared with the final results. Results SLNs were identified in 27 of 28 (96.4%) patients. A total of 123 SLNs were identified from 814 nodes. Six patients had altogether 11 positive lymph nodes,which were all SLNs. No patient had false-negative sentinel node. Conclusion SLNs can successfully predict the lymphatic metastasis in patients with cervical cancer. The clinical validity of this technique should be evaluated prospectively.展开更多
文摘Objective: To predict the risk factors of lymph node metastasis in cervical cancer by using large sample clinical data, and to construct and verify the nomogram for predicting lymph node metastasis. Methods: A total of 5940 patients with cervical cancer from 2004 to 2015 in the National Cancer Institute Surveillance Epidemiology and End Results database were retrospectively screened and randomly assigned to training group (n = 4172) and validation group (n = 1768). Multivariate Logistic regression analysis was used, and the optimal model was selected according to AIC or BIC and likelihood ratio test, and a nomogram was drawn. The accuracy and robustness of the prediction model were evaluated in three aspects: discrimination, calibration and clinical net benefit. Results: The prediction model based on race, tumor tissue differentiation degree, tumor histopathological type, distant metastasis of tumor, tumor diameter and other risk factors was successfully established and a nomogram was constructed. The AUCs of training group and validation group were: 0.736 and 0.714, respectively. And the p-values of the Hosmer-Lemeshow test were 0.28 and 0.11, respectively. The calibration curve was in good agreement with the ideal curve. It had high accuracy and applicability after internal verification. Conclusion: A prediction model is constructed based on the risk factors of lymph node metastasis of cervical cancer. The nomogram has a good effective prediction and can provide a theoretical basis for clinicians to assess the disease quickly before surgery.
文摘Background In general,sentinel lymph node (SLN) can reflect the whole state of the entire drainage area. The present study evaluated the clinical significance of sentinel lymph node identification in the treatment of early stage cervical cancer.Methods Twenty-eight patients with early stage (Ia-IIa) cervical cancer undergoing radical hysterectomy and pelvic lymphadenectomy were included in this study. At two locations 8 hours before operation,0.4 ml 37 Mbq technicium-99 labeled dextran was injected intracervically. After that,preoperative lymphoscintigraphy was performed to detect SLNs. During the operation,lymph nodes were detected ex vivo by a γ-counter to identify SLNs. The samples of SLNs and non-SLNs were used for pathological examination separately and compared with the final results. Results SLNs were identified in 27 of 28 (96.4%) patients. A total of 123 SLNs were identified from 814 nodes. Six patients had altogether 11 positive lymph nodes,which were all SLNs. No patient had false-negative sentinel node. Conclusion SLNs can successfully predict the lymphatic metastasis in patients with cervical cancer. The clinical validity of this technique should be evaluated prospectively.
