Nomogram Predicting Parametrial Involvement Based on the Radical Hysterectomy Specimens in the Early-Stage Cervical Cancer

基于早期宫颈癌根治性子宫切除标本的宫旁组织受累预测列线图

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Abstract

Objective: Radical hysterectomy (RH) is the surgical standard for the treatment of the early-stage cervical cancer (CC). However, this procedure is associated with a high rate of adverse impact on the quality of the life of the patient. Since the rate of parametrial involvement (PI) is low for the patients with the early-stage CC, some authors believe that the patients with the early-stage CC may benefit from the less radical surgery. This study aims to estimate the incidence of the PI in the patients with the early-stage CC and establish a simple nomogram to identify a cohort of the patients with low risk of the PI who may benefit from the less radical surgery. Methods: All the patients who underwent the RH and pelvic lymphadenectomy were included from 2013 to 2018. The significant independent predictors were identified through the Cox regression analysis and then incorporated into a nomogram to predicate the PI. The calibration plots and receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the nomogram. Results: A total of 4,533 patients met the inclusion criteria and 441 women (9.7%) had the PI. The positive PI rate in the ≤2 cm group (1.2%) was significantly lower compared to >2- ≤4 cm (6.2%) or >4 cm (22.4%) groups. The multivariate analyses revealed that tumor size (p = 0.002), lymphovascular space invasion (LVSI) (p = 0.001), vaginal involvement (VI) (p < 0.001), status of the pelvic lymph nodes (PLNs) (p = 0.001), and depth of stromal invasion (DSI) (p < 0.001) were the independent prognostic factors of the PI. Finally, the five variables were combined to construct the nomogram model. The concordance indexes (C-indexes) of the PI were 0.756 (95% CI 0.726-0.786) for the internal validation and 0.729 (95% CI 0.678-0.780) for the external validation. The calibration plots further showed good consistency between the nomogram prediction and the actual observation. Conclusion: This study confirmed that the patients with tumor size 2 cm or smaller were at very low risk for the PI. If other variables such as negative LVSI, DSI <50%, no VI, and negative PLN were limited, the risk would reduce significantly. Meanwhile, a simple nomogram based on the significant clinicopathological characteristics could be used as a tool for the clinicians to predict the PI among the patients with the early-stage CC, who might benefit from a less radical surgery.

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