Evaluation of Clinical and Pathologic Risk Factors May Reduce the Rate of Multimodality Treatment of Early Cervical Cancer

Preoperative prediction of recurrence risk factors in operable cervical cancer based on clinical-radiomics features

Objective

To investigate the value of preoperative prediction of risk factors for recurrence of operable cervical cancer based on the radiomics features of biparametric magnetic resonance imaging (bp-MRI) combined with clinical features.

Method

A retrospective collection of cervical cancer cases undergoing radical hysterectomy + pelvic and/or para-aortic lymph node dissection at the Affiliated Hospital of North Sichuan Medical College was conducted. Region of interest (ROI) was outlined using the 3D Slicer software, and radiomics after feature extraction and feature screening was performed using the least absolute shrinkage and selection operator (LASSO) algorithm. Logistic regression algorithms were used to construct a fusion clinical-radiomics model to visualize nomograms. Receiver operating characteristic (ROC), DeLong test, calibration curve (CC), and decision curve (DC) were used to evaluate the predictive performance and clinical benefit of the model.

Result

A total of 99 patients with cervical cancer were included in this study, with 79 and 20 cases in the training and test groups, respectively. Seventeen key features were selected for radiomics model construction. Three clinical features were screened to construct a clinical model. A fusion model of the radiomics model combined with the clinical model was constructed. The area under the curve (AUC) values in the training group were 0.710 (95% CI 0.602-0.819), 0.892 (95% CI 0.826-0.958), and 0.906 (95% CI 0.842-0.970), for the comparative clinical model, radiomics model, and fusion model, respectively, and the AUC values in the testing group were 0.620 (95% CI 0.366-0.874), 0.860 (95% CI 0.677-1.000), and 0.880 (95% CI 0.690-1.000), respectively. The DeLong test showed a statistically significant difference between the AUC values of the fusion model and the clinical model (p < 0.05). Decision curve analysis (DCA) showed that the fusion model had the greatest net benefit when the threshold probability was approximately 0.5.

Conclusion

The fusion model constructed based on bp-MRI radiomics features combined with clinical features provides an important reference for predicting the risk status of recurrence in operable cervical cancer. The findings of this study are preliminary exploratory results, and further large-scale, multicenter studies are needed to validate these findings.

Systematic Review-Role of MRI in Cervical Cancer Staging

A systematic review of the diagnostic accuracy of MRI in the staging of cervical cancer was conducted based on the literature from the last 5 years. A literature search was performed in the Cochrane Library, EMBASE, MEDLINE and PubMed databases using the MeSH terms "cervical cancer", "MRI" and "neoplasm staging". A total of 110 studies were identified, of which 8 fit the inclusion criteria. MRI showed adequate accuracy (74-95%) and high sensitivity (92-100%) in assessing stromal invasion. The data for MRI in terms of assessing vaginal and pelvic side wall involvement were wide ranging and inconclusive. In assessing lymph node metastasis, MRI showed an adequate accuracy (73-90%), specificity (75-91%) and NPV (71-96%) but poor sensitivity (52-75%) and PPV (52-75%). MRI showed high accuracy (95%), sensitivity (78-96%), specificity (87-94%), and NPV (98-100%) but poor PPV (27-42%) in detecting bladder involvement. There was a paucity of data on the use of MRI in assessing rectal involvement in cervical cancer. Overall, the literature was heterogenous in the definitions and language used, which reduced the comparability between articles. More research is required into the diagnostic accuracy of MRI in the staging of cervical cancer and there must be increased consistency in the definitions and language used in the literature.

Conditional survival analysis and real-time prognosis prediction for cervical cancer patients below the age of 65 years

Background

Survival prediction for cervical cancer is usually based on its stage at diagnosis or a multivariate nomogram. However, few studies cared whether long-term survival improved after they survived for several years. Meanwhile, traditional survival analysis could not calculate this dynamic outcome. We aimed to assess the improvement of survival over time using conditional survival (CS) analysis and developed a novel conditional survival nomogram (CS-nomogram) to provide individualized and real-time prognostic information.

Methods

Cervical cancer patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The Kaplan-Meier method estimated cancer-specific survival (CSS) and calculated the conditional CSS (C-CSS) at year y+x after giving x years of survival based on the formula C-CSS(y|x) =CSS(y+x)/CSS(x). y indicated the number of years of further survival under the condition that the patient was determined to have survived for x years. The study identified predictors by the least absolute shrinkage and selection operator (LASSO) regression and used multivariate Cox regression to demonstrate these predictors' effect on CSS and to develop a nomogram. Finally, the CSS possibilities predicted by the nomogram were brought into the C-CSS formula to create the CS-nomogram.

Results

A total of 18,511 patients aged <65 years with cervical cancer from 2004 to 2019 were included in this study. CS analysis revealed that the 15-year CSS increased year by year from the initial 72.6% to 77.8%, 84.5%, 88.8%, 91.5%, 93.5%, 94.8%, 95.7%, 96.4%, 97.3%, 98.0%, 98.5%, 99.1%, and 99.4% (after surviving for 1-13 years, respectively), and found that when survival exceeded 5-6 years, the risk of death from cervical cancer would be less than 5% in 10-15 years. The CS-nomogram constructed using tumor size, lymph node status, distant metastasis status, and histological grade showed strong predictive performance with a concordance index (C-index) of 0.805 and a stable area under the curve (AUC) between 0.795 and 0.816 over 15 years.

Conclusions

CS analysis in this study revealed the gradual improvement of CSS over time in long-term survived cervical cancer patients. We applied CS to the nomogram and developed a CS-nomogram successfully predicting individualized and real-time prognosis.

Predicting the rate of adjuvant postoperative chemo/radiation in cervical cancer with tumor size ≥2 cm and <4 cm: An Israeli Gynecologic Oncology Group study

OBJECTIVE

Women with cervical cancer who undergo radical hysterectomy are often treated postoperatively with chemoradiation. Patient selection that minimizes adjuvant treatment is valuable. We compared two methods for predicting postoperative adjuvant treatment of women with tumor size ≥2 cm and <4 cm.

STUDY DESIGN

This multicenter retrospective study included 272 women with tumor size ≥2 cm and <4 cm. A receiver operating characteristic curve (ROC) analysis was used to determine the optimal tumor cutoff size to predict adjuvant treatment. A second analysis compared the rate of adjuvant treatment between women with and without lymph vascular space involvement (LVSI).

RESULTS

According to the ROC, the optimal cutoff value of tumor size for predicting adjuvant treatment was 2.95 cm (sensitivity 0.70, specificity 0.67). Tumors were ≥3.0 cm in 166 (61.0%) women. The rate of adjuvant treatment was higher in women with larger tumor diameter (73.8% vs. 47.9%, p < 0.0001). Of the 241 women with a LVSI record, LVSI was present in 81 (34%) women. Among women with LVSI, rates were higher of positive lymph nodes (41.0% vs 14.5%, p < 0.0001) and postoperative adjuvant treatment (83.3% vs. 53.7%, p < 0.001). Among women with tumor size ≥3.0 cm and LVSI, the rate of adjuvant treatment was 90.0%. In the multivariate analysis, both tumor size ≥3.0 cm and the presence of LVSI were independently associated with adjuvant treatment (OR 3.9, 95% CI 2.1-7.1; p < 0.0001 and OR 4.9, 95% CI 2.4-10.0; p < 0.0001, respectively).

CONCLUSION

In women with cervical cancer who underwent radical hysterectomy, tumors ≥3 cm were associated with a >70% rate of adjuvant treatment, and LVSI was associated with a >80% rate. These data should be weighed in multidisciplinary consultation with radiation oncologists when deciding treatment strategy.

Is the pathologic tumor size associated with survival in early cervical cancer treated with radical hysterectomy and adjuvant radiotherapy?

OBJECTIVE

In 2018 International Federation of Gynecology and Obstetrics (FIGO) staging system of uterine cervix cancer, size criteria of primary tumor has been revised. This study aimed to evaluate the validity of this new size criteria (<2, 2-4, and ≧4 cm) in patients who underwent radical hysterectomy and adjuvant radiation therapy (RT) for early cervical cancer.

MATERIALS AND METHODS

We retrospectively examined 312 patients who underwent radical hysterectomy and adjuvant RT for early cervical cancer (IB-IIA) from 2001 to 2014. The effects of clinical and pathological factors on disease-free survival (DFS) and overall survival (OS) were evaluated in univariate and multivariate analyses.

RESULTS

After a median follow-up of 71.5 months, the 5-year DFS and OS rates were 89.5% and 94.7%, respectively. The primary tumor size was not a significant factor for DFS (p = 0.382) or OS (p = 0.725) in all patients.

CONCLUSION

Primary tumor size was not a significant factor for survival in patients who received hysterectomy and adjuvant RT for early cervical cancer. Adequacy of new tumor size criteria (<2, 2-4, and ≧4 cm) in new 2018 FIGO stage needs to be validated in further studies.

MRI-derived radiomics analysis improves the noninvasive pretreatment identification of multimodality therapy candidates with early-stage cervical cancer

OBJECTIVES

To develop and validate a clinical-radiomics model that incorporates radiomics signatures and pretreatment clinicopathological parameters to identify multimodality therapy candidates among patients with early-stage cervical cancer.

METHODS

Between January 2017 and February 2021, 235 patients with IB1-IIA1 cervical cancer who underwent radical hysterectomy were enrolled and divided into training (n = 194, training:validation = 8:2) and testing (n = 41) sets according to surgical time. The radiomics features of each patient were extracted from preoperative sagittal T2-weighted images. Significance testing, Pearson correlation analysis, and Least Absolute Shrinkage and Selection Operator were used to select radiomic features associated with multimodality therapy administration. A clinical-radiomics model incorporating radiomics signature, age, 2018 Federation International of Gynecology and Obstetrics (FIGO) stage, menopausal status, and preoperative biopsy histological type was developed to identify multimodality therapy candidates. A clinical model and a clinical-conventional radiological model were also constructed. A nomogram and decision curve analysis were developed to facilitate clinical application.

RESULTS

The clinical-radiomics model showed good predictive performance, with an area under the curve, sensitivity, and specificity in the testing set of 0.885 (95% confidence interval: 0.781-0.989), 78.9%, and 81.8%, respectively. The AUC, sensitivity, and specificity of the clinical model and clinical-conventional radiological model were 0.751 (0.603-0.900), 63.2%, and 63.6%, 0.801 (0.661-0.942), 73.7%, and 68.2%, respectively. A decision curve analysis demonstrated that when the threshold probability was > 20%, the clinical-radiomics model or nomogram may be more advantageous than the treat all or treat-none strategy.

CONCLUSIONS

The clinical-radiomics model and nomogram can potentially identify multimodality therapy candidates in patients with early-stage cervical cancer.

KEY POINTS

• Pretreatment identification of multimodality therapy candidates among patients with early-stage cervical cancer helped to select the optimal primary treatment and reduce severe complication risk and costs. • The clinical-radiomics model achieved a better prediction performance compared with the clinical model and the clinical-conventional radiological model. • An easy-to-use nomogram exhibited good performance for individual preoperative prediction.

Cancer of the cervix uteri: 2021 update

Since the publication of the 2018 FIGO Cancer Report, giant strides have been made in the global effort to reduce the burden of cervical cancer, with the World Health Organization (WHO) rolling out a global strategy for cervical cancer elimination, aiming for implementation by 2030. In over 130 countries, including low- and middle-income countries, HPV vaccination is now included in the national program. Screening has seen major advances with wider implementation of HPV testing. These interventions will take a few years to show their impact. Meanwhile, over half a million new cases are added each year. FIGO's revised staging of cervical cancer (2018) has been widely implemented and retrospective analyses of data based on the new staging have been published. Minimally invasive surgery has been shown to be disadvantageous in women with cervical cancer. This chapter discusses the management of cervical cancer based on the stage of disease, including attention to palliation and quality of life issues.

Adjuvant treatment in cervical, vaginal and vulvar cancer

Primary surgical management is successful as the sole therapeutic modality in the majority of women with early-stage cervical, vaginal and vulvar cancer, but the presence of certain risk factors in the surgico-pathological specimen indicates a poorer prognosis. Adjuvant treatment can improve overall survival in such cases. Important risk factors in cervical cancer include intermediate-risk factors (large tumor size, deep cervical stromal invasion, lymph-vascular space invasion) and high-risk factors (positive or close margins, lymph nodes, or parametrial involvement). In vulvar cancer, positive margins and lymph nodes are the two most important factors for adjuvant therapy. Radiation therapy has been the mainstay of adjuvant therapy in these cancers, supplemented by chemotherapy. Recent advances have witnessed the inclusion of newer therapeutic modalities such as immunotherapy. This review addresses the current status of various adjuvant therapeutic modalities for these gynecological cancers.

Region-specific Risk Factors for Pelvic Lymph Node Metastasis in Patients with Stage IB1 Cervical Cancer

Objectives: We aimed to identify the risk factors associated with pelvic lymph node metastasis (LNM) at each anatomic location in patients with stage IB1 cervical cancer.

Methods: A primary cohort of 728 patients with stage IB1 cervical cancer who underwent radical hysterectomy and systematic pelvic lymphadenectomy were retrospectively studied. All removed pelvic nodes (N=20,134) were pathologically examined. The risk factors for LNM in different anatomic regions (obturator, internal iliac, external iliac, and common iliac) were evaluated by multivariate logistic regression analyses. Nomograms were generated from the primary cohort and validated in another external cohort (N=242). The performance of the nomogram was assessed by its calibration and discrimination. Overall survival and progression-free survival in patients with different LNM patterns were compared.

Results: LNM was found in 266 (1.3%) removed nodes and 106 (14.6%) patients. The incidences of LNM at the obturator, internal iliac, external iliac, common iliac, and parametrial regions were 8.5%, 5.4%, 4.7%, 1.9% and 1.8%, respectively. Among others, tumour size and lymph-vascular space invasion (LVSI), which are preoperatively assessable, were identified as independent risk factors of LNM in the common iliac region and the lower pelvis, respectively, and age was an additional independent risk factor of obturator LNM. The negative predictive values of tumour size <2 cm for common iliac LNM and negative LVSI combined with older age (> 50 years) for obturator LNM were 100% and 98.7%, respectively. A nomogram of these two factors showed good calibration and discrimination (concordance index, 0.761 in the primary cohort and 0.830 in validation cohort). The patients with common iliac LNM had poorer survival than those with LNM confined to the lower pelvis, while the differences in survival between patients with LNM confined to one node, one region or single side and those with more widely spreading LNM were not statistically significant.

Conclusions: Tumour size, LVSI and age are region-specific risk factors for pelvic LNM in IB1 cervical cancer, which could be used to allocate the appropriate extent of pelvic lymphadenectomy.

Prognostic value of lymphovascular space invasion in patients with early stage cervical cancer in Jilin, China: A retrospective study

The metastasis of cervical carcinoma is associated with the lymphovascular spread. The primary objective of the present study was to determine the prognostic value of lymphovascular space invasion (LVSI) in patients with early-stage cervical cancer in Jilin, China.In this retrospective cohort study, patients with early-stage cervical cancer (stage IB-IIA) at the Second Hospital of Jilin University from February 2014 to December 2016 were included in the analysis. All included participants underwent radical hysterectomy with pelvic lymphadenectomy. LVSI was identified by hematoxylin and eosin (H&E) staining. The primary outcomes are overall survival (OS) and progression-free survival (PFS). Kaplan-Meier curves were used to calculate the patient's survival. Survival was compared using the log-rank test, while risk factors for the prognosis were assessed by Cox regression analysis.The incidence of LVSI was positively associated with the depth of stromal invasion (P = .009) and lymph node metastasis (LNM, P < .001). LVSI is an independent factor that affects OS (P = .009) and PFS (P = .006) in patients with early stage cervical cancer. LNM status is an independent factor that affects postoperative OS (P = .005).The incidence of lymphatic vessel infiltration is positively associated with the depth of stromal invasion and LNM. LVSI is an independent risk factor for the prognosis of early cervical cancer. The results suggest that further large-scale studies are needed to improve the treatment for patients with LVSI.

Cancer of the cervix uteri

Since the publication of the last FIGO Cancer Report there have been giant strides in the global effort to reduce the burden of cervical cancer, with WHO announcing a call for elimination. In over 80 countries, including LMICs, HPV vaccination is now included in the national program. Screening has also seen major advances with implementation of HPV testing on a larger scale. However, these interventions will take a few years to show their impact. Meanwhile, over half a million new cases are added each year. Recent developments in imaging and increased use of minimally invasive surgery have changed the paradigm for management of these cases. The FIGO Gynecologic Oncology Committee has revised the staging system based on these advances. This chapter discusses the management of cervical cancer based on the stage of disease, including attention to palliation and quality of life issues.