Cervical biopsy and excision procedure specimens lack sufficient predictive value for lymph-vascular space invasion seen at hysterectomy for cervical cancer

Predicting the status of lymphovascular space invasion using quantitative parameters from synthetic MRI in cervical squamous cell carcinoma without lymphatic metastasis

Purpose

To investigate the value of quantitative longitudinal relaxation time (T1), transverse relaxation time (T2), and proton density (PD) maps derived from synthetic magnetic resonance imaging (MRI) for evaluating the status of lymphovascular space invasion (LVSI) in cervical squamous cell carcinoma (CSCC) without lymph node metastasis (LNM).

Material and methods

Patients with suspected cervical cancer who visited our hospital from May 2020 to March 2023 were collected. All patients underwent preoperative MRI, including routine sequences and synthetic MRI. Patients with pathologically confirmed CSCC without lymphatic metastasis were included in this study. The subjects were divided into negative- and positive-LVSI groups based on the status of LVSI. Quantitative parameters of T1, T2, and PD values derived from synthetic MRI were compared between the two groups using independent samples t-test. Receiver operating characteristic curves were used to determine the diagnostic efficacy of the parameters.

Results

59 patients were enrolled in this study and were classified as positive (n = 32) and negative LVSI groups (n = 27). T1 and T2 values showed significant differences in differentiating negative-LVSI from positive-LVSI CSCC (1307.39 ± 122.02 vs. 1193.03 ± 107.86, P<0.0001; 88.42 ± 7.24 vs. 80.99 ± 5.50, P<0.0001, respectively). The area under the curve (AUC) for T1, T2 values and a combination of T1 and T2 values were 0.756, 0.799, 0.834 respectively, and there is no statistically significant difference in the diagnostic efficacy between individual and combined diagnosis of each parameter.

Conclusions

Quantitative parameters derived from synthetic MRI can be used to evaluate the LVSI status in patients with CSCC without LNM.

A federated approach to identify women with early-stage cervical cancer at low risk of lymph node metastases

OBJECTIVE

Lymph node metastases (pN+) in presumed early-stage cervical cancer negatively impact prognosis. Using federated learning, we aimed to develop a tool to identify a group of women at low risk of pN+, to guide the shared decision-making process concerning the extent of lymph node dissection.

METHODS

Women with cervical cancer between 2005 and 2020 were identified retrospectively from population-based registries: the Danish Gynaecological Cancer Database, Swedish Quality Registry for Gynaecologic Cancer and Netherlands Cancer Registry. Inclusion criteria were: squamous cell carcinoma, adenocarcinoma or adenosquamous carcinoma; The International Federation of Gynecology and Obstetrics 2009 IA2, IB1 and IIA1; treatment with radical hysterectomy and pelvic lymph node assessment. We applied privacy-preserving federated logistic regression to identify risk factors of pN+. Significant factors were used to stratify the risk of pN+.

RESULTS

We included 3606 women (pN+ 11%). The most important risk factors of pN+ were lymphovascular space invasion (LVSI) (odds ratio [OR] 5.16, 95% confidence interval [CI], 4.59-5.79), tumour size 21-40 mm (OR 2.14, 95% CI, 1.89-2.43) and depth of invasion>10 mm (OR 1.81, 95% CI, 1.59-2.08). A group of 1469 women (41%)-with tumours without LVSI, tumour size ≤20 mm, and depth of invasion ≤10 mm-had a very low risk of pN+ (2.4%, 95% CI, 1.7-3.3%).

CONCLUSION

Early-stage cervical cancer without LVSI, a tumour size ≤20 mm and depth of invasion ≤10 mm, confers a low risk of pN+. Based on an international privacy-preserving analysis, we developed a useful tool to guide the shared decision-making process regarding lymph node dissection.

Preliminary MRI Study of Extracellular Volume Fraction for Identification of Lymphovascular Space Invasion of Cervical Cancer

BACKGROUND

Lymphovascular space invasion (LVSI) is a risk factor for poor prognosis of cervical cancer. Preoperative identification of LVSI is very difficult.

PURPOSE

To evaluate the potential of extracellular volume (ECV) fraction based on T1 mapping in preoperative identification of LVSI in cervical cancer compared with dynamic contrast-enhanced MRI (DCE-MRI).

STUDY TYPE

Retrospective.

SUBJECTS

A total of 79 patients (median age 54 years) with cervical cancer were classified into LVSI group (n = 29) and without LVSI group (n = 50) according to postoperative pathology.

FIELD STRENGTH/SEQUENCE

A 3-T, noncontrast and contrast-enhanced T1 mapping performed with volume interpolated breath hold examination (VIBE) sequence, DCE-MRI applied with 3D T1-weighted VIBE sequence.

ASSESSMENT

Regions of interest along the medial edge of the lesion were drawn on slices depicting the maximum cross-section of the tumor. The noncontrast and contrast-enhanced T1 value of the tumor and arteries in the same slice were measured, and ECV was calculated from T1 values. The parametric maps (K^trans , k_ep , and v_e ) derived from DCE-MRI standard Toft's model were evaluated.

STATISTICAL TESTS

ECV, K^trans , k_ep , and v_e between groups with and without LVSI were compared using Student's t-test. The receiver operating characteristic (ROC) curve and DeLong test were used to evaluate and compare the diagnostic performance of ECV, K^trans , k_ep , and v_e for differentiating LVSI. P < 0.05 was considered statistically significant.

RESULTS

The ECV and K^trans of the LVSI group were significantly higher than that of non-LVSI group (52.86% vs. 36.77%, 0.239 vs. 0.176, respectively), and no significant differences in K_ep or v_e values were observed (P = 0.071 and P = 0.168, respectively). The ECV fraction showed significantly higher area under ROC curve than K^trans for differentiating LVSI (0.874 vs. 0.655, respectively).

DATA CONCLUSION

ECV measurements based on T1 mapping might improve the discrimination between patients with and without LVSI in cervical cancer, showing better performance for this purpose than DCE-MRI.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Prediction of Postoperative Pathologic Risk Factors in Cervical Cancer Patients Treated with Radical Hysterectomy by Machine Learning

Pretherapeutic serological parameters play a predictive role in pathologic risk factors (PRF), which correlate with treatment and prognosis in cervical cancer (CC). However, the method of pre-operative prediction to PRF is limited and the clinical availability of machine learning methods remains unknown in CC. Overall, 1260 early-stage CC patients treated with radical hysterectomy (RH) were randomly split into training and test cohorts. Six machine learning classifiers, including Gradient Boosting Machine, Support Vector Machine with Gaussian kernel, Random Forest, Conditional Random Forest, Naive Bayes, and Elastic Net, were used to derive diagnostic information from nine clinical factors and 75 parameters readily available from pretreatment peripheral blood tests. The best results were obtained by RF in deep stromal infiltration prediction with an accuracy of 70.8% and AUC of 0.767. The highest accuracy and AUC for predicting lymphatic metastasis with Cforest were 64.3% and 0.620, respectively. The highest accuracy of prediction for lymphavascular space invasion with EN was 59.7% and the AUC was 0.628. Blood markers, including D-dimer and uric acid, were associated with PRF. Machine learning methods can provide critical diagnostic prediction on PRF in CC before surgical intervention. The use of predictive algorithms may facilitate individualized treatment options through diagnostic stratification.

Multiparametric MRI radiomics nomogram for predicting lymph-vascular space invasion in early-stage cervical cancer

OBJECTIVE

To develop a radiomics nomogram based on multiparametric MRI (mpMRI) to pre-operatively predict lymph-vascular space invasion (LVSI) in patients with early-stage cervical cancer.

METHODS

This retrospective study included 233 consecutive patients with Stage IB-IIB cervical cancer. According to the ratio of 2:1, 154 patients and 79 patients were randomly assigned to the primary and validation cohorts, respectively. Features with intraclass and interclass correlation coefficient (ICCs) greater than 0.75 were selected for radiomics features. The significant features for predicting LVSI were selected using the least absolute shrinkage and selection operator (LASSO) algorithm based on the primary cohort. The rad-score for each patient was constructed via a linear combination of selected features that were weighted by their respective coefficients. The radiomics nomogram was developed using multivariable logistic regression analysis by incorporating the rad-score and clinical risk factors.

RESULTS

A total of 19 radiomics features and 3 clinical risk factors were selected. The rad-score exhibited a good performance in discriminating LVSI with a C-index of 0.76 and 0.81 in the primary and validation cohorts, respectively. The radiomics nomogram also exhibited a good discriminating performance in two cohorts (C-index of 0.78 and 0.82). The calibration curve of the radiomics nomogram demonstrated no significant differences was found between prediction and observation outcomes for the probability of LVSI in two cohorts (p = 0.86 and 0.98, respectively). The decision curve analysis indicated that clinician and patients could benefit from the use of radiomics nomogram and rad-score.

CONCLUSION

The nomogram and rad-score could be used conveniently and individually to predict LVSI in patients with early-stage cervical cancer and facilitate the treatment decision for clinician and patients.

ADVANCES IN KNOWLEDGE

The nomogram could pre-operatively predict LVSI in early-stage cervical cancer.

Prediction of lymphovascular space invasion in cervical carcinoma using diffusion kurtosis imaging

BACKGROUND

This study aimed to investigate the potential relationship between diffusion kurtosis imaging (DKI)- derived parameters and lymphovascular space invasion (LVSI) in patients with cervical carcinoma.

PATIENTS AND METHODS

This prospective study included 30 patients with cervical carcinoma. The patients underwent MRI, diffusion-weighted imaging (DWI), and DKI prior to surgery. The surgical pathology results were accepted as the reference standard for determining the LVSI status. The DKI-derived parameters, including mean diffusivity (MD) and mean kurtosis (MK), were measured. The apparent diffusion coefficient (ADC) value was also assessed.

RESULTS

The MD value of LVSI positive cervical carcinomas was significantly lower than LVSI negative carcinomas (p-value = 0.01). MK value was significantly higher in LVSI positive tumors (p-value = 0.01). However, the ADC value did not show a significant difference between LVSI positive and LVSI negative tumors (p-value = 0.2). MD and MK parameters showed similar diagnostic accuracy in identifying the LVSI status, with the area under the curve of 0.77 and 0.78, respectively.

CONCLUSION

In this study, DKI-derived parameters were associated with the LVSI status in cervical carcinomas. Further studies with larger sample size are required to confirm these results.

The diagnostic value of core needle biopsy in cervical cancer: A retrospective analysis

Cervical carcinoma is a major cause of morbidity and mortality among women worldwide. Histological subtype, lymphovascular space invasion and tumor grade could have a prognostic and predictive value for patients’ outcome and the knowledge of these histologic characteristics may influence clinical decision making. However, studies evaluating the diagnostic value of various biopsy techniques regarding these parameters of cervical cancer are scarce. We reviewed 318 cases of cervical carcinoma with available pathology reports from preoperative core needle biopsy (CNB) assessment and from final postoperative evaluation of the hysterectomy specimen. Setting the postoperative comprehensive pathological evaluation as reference, we analysed CNB assessment of histological tumor characteristics. In addition, we performed multivariable logistic regression to identify factors influencing the accuracy in identifying LVSI and tumor grade. CNB was highly accurate in discriminating histological subtype. Sensitivity and specificity were 98.8% and 89% for squamous cell carcinoma, 92.9% and 96.6% for adenocarcinoma, 33.3% and 100% in adenosquamous carcinoma respectively. Neuroendocrine carcinoma was always recognized correctly. The accuracy of the prediction of LVSI was 61.9% and was positively influenced by tumor size in preoperative magnetic resonance imaging and negatively influenced by strong peritumoral inflammation. High tumor grade (G3) was diagnosed accurately in 73.9% of cases and was influenced by histological tumor type. In conclusion, CNB is an accurate sampling technique for histological classification of cervical cancer and represents a reasonable alternative to other biopsy techniques.

Can Conization Specimens Predict Sentinel Lymph Node Status in Early-Stage Cervical Cancer? A SENTICOL Group Study

Simple Summary

Lymph node involvement is one of the major prognosis factors for early-stage cervical cancer. Improvement in preoperative identification of node-positive patients may lead to a more accurate triage to primary chemoradiation for these patients instead of radical surgery followed by adjuvant radiotherapy, given the increased morbidity of combined treatment. Several studies have well established risk factors for node involvement, but they are based on final pathologic examination of radical hysterectomy specimens and are usually extrapolated for preoperative risk assessment. Among these risk factors, tumor size, lymphovascular space invasion (LVSI) and depth of stromal invasion might be assessed in conization specimens. Our findings suggest that patients with depth of stromal invasion lower than 10 mm and no LVSI in conization specimens had lower risk of micro- and macrometastatic SLN. In this subpopulation, full node dissection may be questionable in case of SLN unilateral detection.

Abstract

Background: The prognosis of patients with cervical cancer is significantly worsened in case of lymph node involvement. The goal of this study was to determine whether pathologic features in conization specimens can predict the sentinel lymph node (SLN) status in early-stage cervical cancer. Methods: An ancillary analysis of two prospective multicentric database on SLN biopsy for cervical cancer (SENTICOL I and II) was carried out. Patients with IA to IB2 2018 FIGO stage, who underwent preoperative conization before SLN biopsy were included. Results: Between January 2005 and July 2012, 161 patients from 25 French centers fulfilled the inclusion criteria. Macrometastases, micrometastases and Isolated tumor cells (ITCs) were found in 4 (2.5%), 6 (3.7%) and 5 (3.1%) patients respectively. Compared to negative SLN patients, patients with micrometastatic and macrometastatic SLN were more likely to have lymphovascular space invasion (LVSI) (60% vs. 29.5%, p = 0.04) and deep stromal invasion (DSI) ≥ 10 mm (50% vs. 17.8%, p = 0.04). Among the 93 patients with DSI < 10 mm and absence of LVSI on conization specimens, three patients (3.2%) had ITCs and only one (1.1%) had micrometastases. Conclusions: Patients with DSI < 10 mm and no LVSI in conization specimens had lower risk of micro- and macrometastatic SLN. In this subpopulation, full node dissection may be questionable in case of SLN unilateral detection.

The clinical and prognostic implication of deep stromal invasion in cervical cancer patients undergoing radical hysterectomy

Background: To evaluate the patterns of recurrence and survival related to deep stromal invasion (DSI) in cervical cancer patients who underwent the radical surgery.

Methods: Patients with International Federation of Gynaecology and Obstetrics (FIGO) 2009 stage IB and IIA and definite pathology-confirmed deep stromal invasion between 03/2006 and 06/2014 were collected. A subcategorization of deep stromal invasion (inner full-thickness, full-thickness and outer full-thickness) were performed. Disease-free survival (DFS) and overall survival (OS) were compared by Kaplan-Meier analysis and independent predictors were identified using Cox regression analysis.

Results: A total of 3,298 cervical cancer patients were included. The proportion of patients with outer 1/3 to full-thickness invasion, full-thickness invasion and outer-full-thickness invasion were 60.6%, 33.5% and 5.9%, respectively. Deep stromal invasion strongly correlated with patients' age, stage, menopause status, tumor diameter, lymphovascular space invasion (LVSI), nodal metastasis, parametrial and vaginal involvement, as well as the site of recurrence. However, no connection was found between the DSI and tumor histologic type. Upon further analysis, patients with full- and outer-full-thickness invasion exhibited significantly higher recurrence rates compared to inner full-thickness group. Both DFS and OS was independently associated with the depth of deep stromal invasion. By subgroup analysis, multivariate analysis revealed that only adjuvant radiotherapy was independent risk factors for both DFS and OS in isolated full-thickness invasion patients.

Conclusions: This study indicated that the depth of deep stromal invasion is an important prognostic factor in patients with cervical cancer. Patients with full-thickness invasion should receive customized adjuvant treatment.

Pre-operative surgical algorithm: sentinel lymph node biopsy as predictor of parametrial involvement in early-stage cervical cancer

Introduction

Radical hysterectomy is the gold standard in the management of early-stage cervical cancer. Parametrectomy aims to remove occult disease but is associated with significant surgical morbidity. Avoiding unnecessary parametrectomy in a subset of patients at low risk of parametrial involvement may decrease the incidence of such morbidity. The purpose of this study was to identify patients at low risk of parametrial involvement in early-stage cervical cancer potentially eligible for less radical surgery based on pre-operative criteria and sentinel lymph node (SLN) status.

Methods

We performed an ancillary analysis of data from two prospective trials on sentinel node biopsy for cervical cancer (SENTICOL I and II). Patients with International Federation of Gynecology and Obstetrics (FIGO) IA–IIA cervical cancer who underwent primary radical surgery and bilateral SLN mapping were identified between 2005 and 2012 from 25 French oncologic centers. Patients who underwent pre-operative brachytherapy or did not undergo radical surgery (simple trachelectomy, simple hysterectomy, or lymph node staging only) were excluded.

Results

Of 174 patients who fullfiled the inclusion criteria, 9 patients (5.2%) had parametrial involvement and 24 patients (13.8%) had positive SLN. Most patients had 2018 FIGO stage IB1 disease (86.1%) and squamous cell carcinomas (68.9%). Parametrial involvement was significantly associated with tumor size ≥20 mm on pelvic magnetic resonance imaging (MRI) (adjusted odds ratio (ORa) 9.30, 95% CI 1.71 to 50.57, p=0.01) and micrometastic or macrometastatic SLN (ORa 8.98, 95% CI 1.59 to 50.84, p=0.01). Of 114 patients with tumors <20 mm on pre-operative MRI and negative SLN after ultrastaging, only one patient had parametrial involvement (0.9%). By triaging patients with both of these criteria in a two-step surgical procedure, unjustified and contra-indicated radical hysterectomy would have been avoided in 65.5% and 8.6% of cases, respectively.

Conclusions

Less radical surgery may be an option for patients with bilateral negative SLN after ultrastaging and tumors <20 mm. SLN status should be integrated into the decision-making process for tailored surgery in early-stage cervical cancer.

Nomogram Predicting the Likelihood of Parametrial Involvement in Early-Stage Cervical Cancer: Avoiding Unjustified Radical Hysterectomies

BACKGROUND

We aimed to establish a tool predicting parametrial involvement (PI) in patients with early-stage cervical cancer and select a sub-group of patients who would most benefit from a less radical surgery.

METHODS

We retrospectively reviewed patients from two prospective multicentric databases-SENTICOL I and II-from 2005 to 2012. Patients with early-stage cervical cancer (FIGO 2018 IA with lympho-vascular involvement to IIA1), undergoing radical surgery (hysterectomy or trachelectomy) with bilateral sentinel lymph node (SLN) mapping with no metastatic node or PI on pre-operative imaging, were included.

RESULTS

In total, 5.2% patients (11/211) presented a histologic PI. After univariate analysis, SLN status, lympho-vascular space invasion, deep stromal invasion and tumor size were significantly associated with PI and were included in our nomogram. Our predictive model had an AUC of 0.92 (IC95% = 0.86-0.98) and presented a good calibration. A low risk group, defined according to the optimal sensitivity and specificity, presented a predicted probability of PI of 2%.

CONCLUSION

Patients could benefit from a two-step approach. Final surgery (i.e. radical surgery and/or lymphadenectomy) would depend on the SLN status and the probability PI calculated after an initial conization with bilateral SLN mapping.

Prognostic factors for and pattern of lymph-node involvement in patients with operable cervical cancer

PURPOSE

Lymph node metastases significantly worsen the prognosis in cervical carcinoma. Risk factors-pathological and patient related-could select patients at high risk for lymph node involvement.

METHODS

This retrospective analysis was performed by analyzing data from patients with cervical carcinoma treated between 2000 and 2017 at the Department of Obstetrics and Gynecology of the University Hospital Ulm.

RESULTS

In total, 261 patients with cervical carcinoma (International Federation of Gynecology and Obstetrics (FIGO) stage IA-IIB) and lymphadenectomy with at least 10 removed lymph nodes were available for analysis. Overall, 86 (33.0%) patients had lymph node metastases; 73 patients had pelvic lymph node metastases only and 13 patients had both pelvic and paraaortic lymph node metastases. Lymph node metastases were found most often in the region of the external iliac artery and obturator fossa, with 57.0% and 54.7% of all 86 node-positive patients, respectively. Univariable analyses showed that presence of lymph node metastases was significantly associated with both preoperative FIGO stage (p = 0.001) and final pathological tumor stage (p < 0.001), status of resection margin (p = 0.002), lymphovascular space invasion (LVSI), (p < 0.001) and vascular space invasion, (p < 0.001). In a multivariable logistic regression model with presence of lymph node metastases (yes/no) as binary response variable, only LVSI (p < 0.001) and body mass index (BMI), (p = 0.035) remained as significant independent predictors of lymph node involvement. Subgroup analyses showed that LVSI was a significant predictive factor for lymph node involvement in patients with a preoperatively assessed FIGO stage < IIB (p < 0.001), but not for patients with a preoperatively assessed FIGO stage ≥ IIB (p = 0.122).

CONCLUSIONS

The risk factor LVSI should play an important role in deciding whether an individualized therapy concept is based on escalating or deescalating treatment. In future, the sentinel concept could reduce morbidity and at the same time provide an important prognostic assessment for a subset of cervical cancer patients.

Incidence of Lymph Node Metastases in Women With Low-Risk Early Cervical Cancer (<2 cm) Without Lymph-Vascular Invasion

Objective

To determine the incidence of lymph node metastasis in women with low-risk cervical cancer stage IA2 or IB1 (<2 cm) without lymph-vascular space invasion.

Methods

A multicenter retrospective study was performed in patients who underwent radical or simple hysterectomy, conization, or trachelectomy plus pelvic lymphadenectomy for cervical cancer between January 2000 and June 2016.

Results

A total of 271 patients were included in the study. Median age and body mass index were 46 years (range, 23–77 years) and 24 kg/m2 (range, 18–48 kg/m2), respectively. Twenty-two patients had stage IA2 (8.1%), and 249 (91.9%) had stage IB1. The median tumor size was 14 mm (range, 5–20 mm). Tumor grades were 1 (n = 63 [23.2%]), 2 (n = 120 [44.3%]), 3 (n = 63 [23.2%]), and unknown (25 [9.2%]). Median depth stromal invasion was 6 mm (range, 3–20 mm). Histologic subtypes included squamous (n = 171 [63.1%]), adenocarcinoma (n = 92 [33.9%]), and adenosquamous (n = 8 [3.0%]). Overall incidence of lymph node metastasis was 2.9% (n = 8). The incidence of lymph node involvement in G1, G2, and G3 was 0% (0/63), 5% (6/120), and 3.1% (2/63), respectively. No patient with stage IA2 (regardless of grade or histology) or G1 cervical cancer less than 2 cm (stage IB1) had lymph node metastasis.

Conclusions

Patients with stage IA2 or IB1 (G1) with tumor size of less than 2 cm and no lymph-vascular space invasion may not need lymph node evaluation. On the other hand, 95% and 98% of patients with grade 2 or 3 tumors, respectively, could potentially undergo an unnecessary lymphadenectomy. Further studies with bigger sample size are required to confirm these results.

Occult invasive cervical cancer after simple hysterectomy: a multi-center retrospective study of 89 cases

Background

Occult invasive cervical cancer (OICC) is sometimes incidentally found in surgical specimens after a simple hysterectomy (SH). This study was aimed at identifying a subset of patients with OICC who have a favorable prognosis. This patient group may not require adjuvant radiotherapy and other procedures.

Methods

The medical records of women in whom OICC was detected after an inadvertent SH were retrospectively reviewed. The relevant data, including clinicopathological characteristics, treatment and clinical outcome were evaluated. The primary and secondary endpoints were overall survival (OS) and relapse-free survival (RFS), respectively.

Results

Eighty-nine patients who met the inclusion criteria were included for analysis, and the risk of OICC was found to be 1.9 %. Finding an invasive cancer in a hysterectomy specimen after a conization procedure that shows positive margins was the most common reason (41.6 %) for the performance of inadvertent SH. In the univariate analysis, a tumor width > 20 mm, deep stromal invasion, and lymph node metastasis (LNM) were adversely associated with relapse (P < 0.001, < 0.001, and = 0.001, respectively) and survival (P = 0.003, 0.004, and 0.027, respectively), although these parameters were not independently associated with patient prognoses in the multivariate analysis. In patients with a tumor width ≤ 20 mm and superficial stromal invasion in the observation subgroup, the 5-year RFS and 5-year OS were both 100 %, whereas they were 57.1 % and 66.7 %, respectively, in patients with a tumor size > 20 mm and deep stromal invasion in the radiotherapy or chemotherapy subgroup (P < 0.001, and = 0.008, respectively).

Conclusions

Simple observation after a lymphadenectomy procedure may be feasible in OICC patients with a tumor width ≤ 20 mm, superficial stromal invasion, a negative section margin in hysterectomy specimens, and no LNM.

Accuracy of conization procedure for predicting pathological parameters of radical hysterectomy in stage Ia2-Ib1 (≤2 cm) cervical cancer

The accuracy of conization for the prediction of radical hysterectomy (RH) pathological variables in patients with stage Ia2 to Ib1 (≤2 cm) cervical cancer was retrospectively evaluated in the present study. Endocervical or deep resection margin (RM) involvement in the conization specimens was found to be independently associated with residual disease in the hysterectomy specimens (P < 0.001, = 0.003, respectively). When a tumor width of >20 mm in the final RH pathology analysis was predicted by a tumor width of >2 mm or involvement of endocervical or deep RMs in the conization specimens, the sensitivity and negative predictive value (NPV) of conization were 98.2% and 95.2%, respectively. In addition, when deep stromal invasion in the final RH pathology analysis was predicted by deep stromal invasion or involvement of the endocervical or deep RMs in the conization specimens, the sensitivity and NPV of conization were 98.4% and 95.8%, respectively. The sensitivity and NPV of this prediction model for identifying LVSI in the final RH pathology analysis were both 100%. These findings suggest that conization variables and endocervical and deep resection margin statuses can be analyzed to effectively predict RH pathological parameters.