Analysis of Prognostic Variables, Development of Predictive Models, and Stratification of Risk Groups in Surgically Treated FIGO Early-Stage (IA–IIA) Carcinoma Cervix

Abstract

In this study, age 70 years or older and positive LVSI were found to be statistically significant prognostic factors for both OS and RFS. Positive lymph nodes status showed only a trend toward lower OS. Positive LVSI status had significant adverse prognostic effects on RFS and OS in tumors with increasing depth of invasion. Additive prognostic model helps identify predictors and stratify patients into low-, medium-, and high-risk groups for survival. Many of these factors can be identified preoperatively and may assist in decision to offer primary surgery or alternative therapies in patients with potentially operable cervix cancer. Prognostic model can be used as a tool to design clinical trials and select the group of patients who are the appropriate target for a trial.

Surgical Treatment of Early-Stage Cervical Cancer: A Multi-Institution Experience in 2124 Cases in The Netherlands Over a 30-Year Period

“…This is not a surprise because many other smaller studies showed the same results for most of these variables. 25,26 Nonsquamous histology, especially adenosquamous histology, was an independent poor prognostic factor in this large group of early cervix cancers. This is an interesting finding because it can be identified preoperatively.…”

Establishing a Nomogram for Stage IA-IIB Cervical Cancer Patients after Complete Resection

“…Although clinicopathologic factors have been suggested to guide postoperative adjuvant therapy selection, controversy surrounding the independence of these factors for prognosis of cervical cancer patients still exists (Chang et al, 2009;Small et al, 2012). These different results may be due to the heterogeneity of the population enrolled in different studies (Kamura et al, 1992;Yuan et al, 1998;Ho et al, 2004;Singh et al, 2012). For example, the Yuan model enrolled stage IB-IIA squamous cell carcinoma patients, while other models chose patients of different stages and histology.…”

“…In China, nearly 130,000 cervical cancer cases are newly diagnosed each year, and approximately 30,000 women die of cervical cancer every year (Nguyen et al, 2011 Radical hysterectomy and pelvic lymph node dissection remain the primary therapeutic choices following the FIGO clinical staging system (Landoni et al, 1997;Waggoner, 2003). However, clinicopathologic factors other than FIGO stage, such as lymph node metastasis (LNM) and lymph-vascular space invasion (LVSI), have proven to be relevant to the prognosis of cervical cancer patients (Ho et al, 2004;Pecorelli et al, 2009;Singh et al, 2012). Although NCCN (Grochola et al, 2008)guidelines have suggested that adjuvant therapy should be applied to certain patients with intermediate or high risk factors after surgery, these factors remain controversial in many studies (Kamura et al, 1992;Yuan et al, 1998;Creasman and Kohler, 2004;Ho et al, 2004;Chang et al, 2009;Singh et al, 2012;Williams et al, 2015).…”

“…Until now, most of the prognostic models for cervical cancer were based on the risk stratification method, which grouped together patients with similar prognoses (Kamura et al, 1992;Yuan et al, 1998;Ho et al, 2004;Singh et al, 2012). However, this method may ignore certain surgicalpathological factors.…”

“…However, clinicopathologic factors other than FIGO stage, such as lymph node metastasis (LNM) and lymph-vascular space invasion (LVSI), have proven to be relevant to the prognosis of cervical cancer patients (Ho et al, 2004;Pecorelli et al, 2009;Singh et al, 2012). Although NCCN (Grochola et al, 2008)guidelines have suggested that adjuvant therapy should be applied to certain patients with intermediate or high risk factors after surgery, these factors remain controversial in many studies (Kamura et al, 1992;Yuan et al, 1998;Creasman and Kohler, 2004;Ho et al, 2004;Chang et al, 2009;Singh et al, 2012;Williams et al, 2015). Therefore, different opinions on the impact of prognostic factors between studies may lead to various selection criteria for adjuvant therapy, as suggested by researchers (Chang et al, 2009;Small et al, 2012).…”