Risk assessment model for overall survival in patients with locally advanced cervical cancer treated with definitive concurrent chemoradiotherapy

Exclusion of non-Involved uterus from the target volume (EXIT-trial): An individualized treatment for locally advanced cervical cancer using modern radiotherapy and imaging techniques followed by completion surgery

Background and purpose

Chemoradiotherapy followed by brachytherapy is the standard of care for locally advanced cervical cancer (LACC). In this study, we postulate that omitting an iconographical unaffected uterus (+12 mm distance from the tumour) from the treatment volume is safe and that no tumour will be found in the non-targeted uterus (NTU) leading to reduction of high-dose volumes of surrounding organs at risk (OARs).

Material and Methods

In this single-arm phase 2 study, two sets of target volumes were delineated: one standard-volume (whole uterus) and an EXIT-volume (exclusion of non-tumour-bearing parts of the uterus with a minimum 12 mm margin from the tumour). All patients underwent chemoradiotherapy targeting the EXIT-volume, followed by completion hysterectomy. In 15 patients, a plan comparison between two treatment plans (PTV vs PTV_EXIT) was performed. The primary endpoint was the pathological absence of tumour involvement in the non-targeted uterus (NTU). Secondary endpoints included dosimetric impact of target volume reduction on OARs, acute and chronic toxicity, overall survival (OS), locoregional recurrence-free survival (LRFS), and progression-free survival (PFS).

Results

In all 21 (FIGO stage I: 2; II: 14;III: 3; IV: 2) patients the NTU was pathologically negative. Ssignificant reductions in Dmean in bladder, sigmoid and rectum; V15Gy in sigmoid and rectum, V30Gy in bladder, sigmoid and rectum; V40Gy and V45Gy in bladder, bowel bag, sigmoid and rectum; V50Gy in rectum were achieved. Median follow-up was 54 months (range 7-79 months). Acute toxicity was mainly grade 2 and 5 % grade 3 urinary. The 3y- OS, PFS and LRFS were respectively 76,2%, 64,9% and 81 %.

Conclusion

MRI-based exclusion of the non-tumour-bearing parts of the uterus at a minimum distance of 12 mm from the tumour out of the target volume in LACC can be done without risk of residual disease in the NTU, leading to a significant reduction of the volume of surrounding OARS treated to high doses.

Development and validation of nomograms to recurrence and survival in patients with early-stage cervical adenocarcinoma

PURPOSE

Cervical adenocarcinoma is one of the most common types of cervical cancer and its incidence is increasing. The biological behavior and treatment outcomes of cervical adenocarcinoma (CA) differ from those of squamous cell carcinoma (SCC). We sought to develop a model to predict recurrence and cancer-specific survival (CSS) deaths in CA patients.

METHODS

131 patients were included in model development and internal validation, and patients from the SEER database (N = 1679) were used for external validation. Multivariable Cox proportional hazards regression analysis was used to select predictors of relapse-free survival (RFS) and CSS and to construct the model, which was presented as two nomograms. Internal validation of the nomograms was performed using the bootstrap resampling method.

RESULTS

Age, FIGO (International Federation of Gynecology and Obstetrics) stage, size of the tumor, lymph metastasis and depth of invasion were identified as independent prognostic factors for RFS, while age, FIGO stage, size of the tumor and number of positive LNs were identified as independent prognostic factors for CSS. The nomogram of the recurrence model predicted 2- and 5-year RFS, with optimism adjusted c-statistic of 75.41% and 74.49%. Another nomogram predicted the 2- and 5-year CSS with an optimism-adjusted c-statistic of 83.22% and 83.31% after internal validation; and 68.6% and 71.33% after external validation.

CONCLUSIONS

We developed and validated two effective nomograms based on static nomograms or online calculators that can help clinicians quantify the risk of relapse and death for patients with early-stage CA.

Rationality of FIGO 2018 IIIC restaging of cervical cancer according to local tumor size: A cohort study

INTRODUCTION

FIGO 2018 IIIC remains controversial for the heterogeneity of its prognoses. To ensure a better management of cervical cancer patients in Stage IIIC, a revision of the FIGO IIIC version classification is required according to local tumor size.

MATERIAL AND METHODS

We retrospectively enrolled cervical cancer patients of FIGO 2018 Stages I-IIIC who had undergone radical surgery or chemoradiotherapy. Based on the tumor factors from the Tumor Node Metastasis staging system, IIIC cases were divided into IIIC-T1, IIIC-T2a, IIIC-T2b, and IIIC-(T3a+T3b). Oncologcial outcomes of all stages were compared.

RESULTS

A total of 63 926 cervical cancer cases were identified, among which 9452 fulfilled the inclusion criteria and were included in this study. Kaplan-Meier pairwise analysis showed that: the oncology outcomes of I and IIA were significantly better than of IIB, IIIA+IIIB, and IIIC; the oncology outcome of IIIC-(T1-T2b) was significantly better than of IIIA+IIIB and IIIC-(T3a+T3b); no significant difference was noted between IIB and IIIC-(T1-T2b), or IIIC-(T3a+T3b) and IIIA+IIIB. Multivariate analysis indicated that, compared with IIIC-T1, Stages T2a, T2b, IIIA+IIIB and IIIC-(T3a+T3b) were associated with a higher risk of death and recurrence/death. There was no significant difference in the risk of death or recurrence/death between patients with IIIC-(T1-T2b) and IIB. Also, compared with IIB, IIIC-(T3a+T3b) was associated with a higher risk of death and recurrence/death. No significant differences in the risk of death and recurrence/death were noted between IIIC-(T3a+T3b) and IIIA+IIIB.

CONCLUSIONS

In terms of oncology outcomes of the study, FIGO 2018 Stage IIIC of cervical cancer is unreasonable. Stages IIIC-T1, T2a, and T2b may be integrated as IIC, and it might be unnecessary for T3a/T3b cases to be subdivided by lymph node status.

Development and validation of radiomic signature for predicting overall survival in advanced-stage cervical cancer

Background

The role of artificial intelligence and radiomics in prediction model development in cancer has been increasing every passing day. Cervical cancer is the 4th most common cancer in women worldwide, contributing to 6.5% of all cancer types. The treatment outcome of cervical cancer patients varies and individualized prediction of disease outcome is of paramount importance.

Purpose

The purpose of this study is to develop and validate the digital signature for 5-year overall survival prediction in cervical cancer using robust CT radiomic and clinical features.

Materials and Methods

Pretreatment clinical features and CT radiomic features of 68 patients, who were treated with chemoradiation therapy in our hospital, were used in this study. Radiomic features were extracted using an in-house developed python script and pyradiomic package. Clinical features were selected by the recursive feature elimination technique. Whereas radiomic feature selection was performed using a multi-step process i.e., step-1: only robust radiomic features were selected based on our previous study, step-2: a hierarchical clustering was performed to eliminate feature redundancy, and step-3: recursive feature elimination was performed to select the best features for prediction model development. Four machine algorithms i.e., Logistic regression (LR), Random Forest (RF), Support vector classifier (SVC), and Gradient boosting classifier (GBC), were used to develop 24 models (six models using each algorithm) using clinical, radiomic and combined features. Models were compared based on the prediction score in the internal validation.

Results

The average prediction accuracy was found to be 0.65 (95% CI: 0.60-0.70), 0.72 (95% CI: 0.63-0.81), and 0.77 (95% CI: 0.72-0.82) for clinical, radiomic, and combined models developed using four prediction algorithms respectively. The average prediction accuracy was found to be 0.69 (95% CI: 0.62-0.76), 0.79 (95% CI: 0.72-0.86), 0.71 (95% CI: 0.62-0.80), and 0.72 (95% CI: 0.66-0.78) for LR, RF, SVC and GBC models developed on three datasets respectively.

Conclusion

Our study shows the promising predictive performance of a robust radiomic signature to predict 5-year overall survival in cervical cancer patients.

Systematic review and meta-analysis of prediction models used in cervical cancer

BACKGROUND

Cervical cancer is one of the most common cancers in women with an incidence of around 6.5 % of all the cancer in women worldwide. Early detection and adequate treatment according to staging improve the patient's life expectancy. Outcome prediction models might aid treatment decisions, but a systematic review on prediction models for cervical cancer patients is not available.

DESIGN

We performed a systematic review for prediction models in cervical cancer following PRISMA guidelines. Key features that were used for model training and validation, the endpoints were extracted from the article and data were analyzed. Selected articles were grouped based on prediction endpoints i.e. Group1: Overall survival, Group2: progression-free survival; Group3: recurrence or distant metastasis; Group4: treatment response; Group5: toxicity or quality of life. We developed a scoring system to evaluate the manuscript. As per our criteria, studies were divided into four groups based on scores obtained in our scoring system, the Most significant study (Score > 60 %); Significant study (60 % > Score > 50 %); Moderately Significant study (50 % > Score > 40 %); least significant study (score < 40 %). A meta-analysis was performed for all the groups separately.

RESULTS

The first line of search selected 1358 articles and finally 39 articles were selected as eligible for inclusion in the review. As per our assessment criteria, 16, 13 and 10 studies were found to be the most significant, significant and moderately significant respectively. The intra-group pooled correlation coefficient for Group1, Group2, Group3, Group4, and Group5 were 0.76 [0.72, 0.79], 0.80 [0.73, 0.86], 0.87 [0.83, 0.90], 0.85 [0.77, 0.90], 0.88 [0.85, 0.90] respectively. All the models were found to be good (prediction accuracy [c-index/AUC/R²] >0.7) in endpoint prediction.

CONCLUSIONS

Prediction models of cervical cancer toxicity, local or distant recurrence and survival prediction show promising results with reasonable prediction accuracy [c-index/AUC/R² > 0.7]. These models should also be validated on external data and evaluated in prospective clinical studies.

Parametrial involvement and decreased survival of women with FIGO stage IIIC1 cervical cancer

OBJECTIVE

To evaluate the effect of parametrial status on FIGO stage IIIC1 cervical cancer.

METHODS

A retrospective study was conducted from June 1, 2009, to December 31, 2018.Patients with stage IIIC1 cervical cancer were included and stratified into two groups based on the status of parametrial involvement. Patients with IIIA or IIIB were selected as control. The primary outcomes are overall survival (OS) and progression-free survival (PFS).

RESULTS

Of 586 patients included, 377 patients were stage IIIC1 (group A) and 209 patients were stage IIIA/IIIB (group B). Compared control, stage IIIC1 was not associated with worse 5-year OS or PFS. Of the stage IIIC1 patients, 58.1% without parametrial involvement (group A1) and 41.9% with parametrial involvement (group A2). Patients of group A1 showed a better prognosis than group A2 both in 5-year rates of OS (79.09% vs. 59.43%, p<0.001) and PFS (73.27% vs. 56.95%, p=0.0002). However, patients of group A1 showed a better prognosis than group B both in OS and PFS. Also, patients of group A2 showed a comparable prognosis to group B both in OS and PFS.

CONCLUSION

Reclassification of stage IIIC1 cervical cancer without parametrial into a new stage is more appropriate and improves discriminatory ability.

Brachytherapy outcome modeling in cervical cancer patients: A predictive machine learning study on patient-specific clinical, physical and dosimetric parameters

PURPOSE

To predict clinical response in locally advanced cervical cancer (LACC) patients by a combination of measures, including clinical and brachytherapy parameters and several machine learning (ML) approaches.

METHODS

Brachytherapy features such as insertion approaches, source metrics, dosimetric, and clinical measures were used for modeling. Four different ML approaches, including LASSO, Ridge, support vector machine (SVM), and Random Forest (RF), were applied to extracted measures for model development alone or in combination. Model performance was evaluated using the area under the curve (AUC) of receiver operating characteristics curve, sensitivity, specificity, and accuracy. Our results were compared with a reference model developed by simple logistic regression applied to three distinct clinical features identified by previous papers.

RESULTS

One hundred eleven LACC patients were included. Nine data sets were obtained based on the features, and 36 predictive models were built. In terms of AUC, the model developed using RF applied to dosimetric, physical, and total BT sessions features were found as the most predictive [AUC; 0.82 (0.95 confidence interval (CI); 0.79 -0.93), sensitivity; 0.79, specificity; 0.76, and accuracy; 0.77]. The AUC (0.95 CI), sensitivity, specificity, and accuracy for the reference model were found as 0.56 (0.52 ...0.68), 0.51, 0.51, and 0.48, respectively. Most RF models had significantly better performance than the reference model (Bonferroni corrected p-value < 0.0014).

CONCLUSION

Brachytherapy response can be predicted using dosimetric and physical parameters extracted from treatment parameters. Machine learning algorithms, including Random Forest, could play a critical role in such predictive modeling.

Clavien-Dindo classification and risk prediction model of complications after robot-assisted radical hysterectomy for cervical cancer

Although significant progress has been made with surgical methods, the incidence of complications after minimally invasive surgery in patients with cervical cancer remains high. Established as a standardized system, Clavien-Dindo classification (CDC) has been applied in a variety of surgical fields. This study is designed to evaluate the complications after robot-assisted radical hysterectomy (RRH) for cervical cancer using CDC and further establish a prediction model. This is a study on the development of prediction model based on retrospective data. Patients with cervical cancer who received RRH treatment in our hospital from January 2016 to April 2019 were invited to participate in the study. The demographic data, laboratory and imaging examination results and postoperative complications were collected, and the logistic regression model was applied to analyze the risk factors possibly related to complications to establish a prediction model. 753 patients received RRH. The overall incidence of complications was 32.7%, most of which were grade I and grade II (accounting for 30.6%). The results of multivariate analysis showed that the preoperative neoadjuvant chemotherapy (OR = 1.693, 95%CI: 1.210-2.370, P = 0.002), preoperative ALT (OR = 1.028, 95%CI: 1.017-1.039, P < 0.001), preoperative urea nitrogen (OR = 0.868, 95%CI: 0.773-0.974, P = 0.016), preoperative total bilirubin (OR = 0.958, 95%CI: 0.925-0.993, P = 0.0.018), and preoperative albumin (OR = 0.937, 95%CI: 0.898-0.979, P = 0.003) were related to the occurrence of postoperative complications. The area under the curve (AUC) of receiver-operating characteristic (ROC) in the prediction model of RRH postoperative complications established based on these five factors was 0.827 with 95% CI of 0.794-0.860. In patients undergoing robot-assisted radical hysterectomy for cervical cancer, preoperative ALT level, urea nitrogen level, total bilirubin level, albumin level, and neoadjuvant chemotherapy were significantly related to the occurrence of postoperative complications. The regression prediction model established on this basis showed good prediction performance with certain clinical promotion and reference value.

Biotin-Targeted Au(I) Radiosensitizer for Cancer Synergistic Therapy by Intervening with Redox Homeostasis and Inducing Ferroptosis

The search for highly selective sensitizers with a novel mechanism for tumor targeting therapy is of considerable interest. In this work, we have developed a series of new biotin-targeted Au(I) complexes. Through systematic biological evaluation and comparison, biotinylated Au(I) complex 3a containing a triphenylphosphine ligand was screened, as it realized both prominent efficient inhibition and selective cytotoxicity to cancer cells, and the effect was better than that of popularly used auranofin. Meanwhile, complex 3a, as a potent radiosensitizer, enhances anticancer effects in vitro and in vivo and has sensitization selectivity. From the action mechanism study, we provide evidence that complex 3a could intervene in redox homeostasis through targeted binding and strong suppression of thioredoxin reductase (TrxR) and induce the ferroptosis death process, enabling it to sensitize tumor cells to radiotherapy. Thus, complex 3a has enormous potential as an efficient and specific radiosensitizing agent in cancer therapy.

Nomograms Predicting Survival of Cervical Cancer Patients Treated With Concurrent Chemoradiotherapy Based on the 2018 FIGO Staging System

Background

In 2018, a revised staging system was released for cervical cancer, which defined pelvic and paraaortic lymph node metastasis as stages IIIC1 and IIIC2, respectively. In this study, we constructed and validated nomograms to predict the 3- and 5-year survival of patients with cervical cancer based on the revised International Federation of Gynecology and Obstetrics (FIGO) staging system.

Methods

We retrospectively examined patients with 2009 FIGO stage IB–IVA cervical cancer who were treated at our institute between 2011 and 2015. Patients were randomized into the model development and validation cohorts (2:1). Univariate and multivariate analyses were conducted for the model development cohort to identify prognostic factors. In the multivariate analysis, nomograms were built to predict overall survival (OS) and disease-free survival (DFS) using significant variables. The nomograms were assessed based on the discrimination and calibration in both cohorts. Discrimination was assessed using the concordance index. Calibration was performed by comparing the mean nomogram estimated survival and the mean observed survival.

Results

We included 1,192 patients, with 795 and 397 patients in the model development and validation cohorts, respectively. In the model development cohort, the median follow-up period was 49.2 months. After multivariate analysis, age, histology, 2018 FIGO stage, and pelvic lymph node number were independent factors for OS. Histology, 2018 FIGO stage, squamous cell carcinoma antigen, and pelvic lymph node number were significant predictors of DFS. The nomograms constructed to predict OS and DFS were based on these factors. In both model cohorts, the concordance index for the nomogram-predicted OS and DFS was 0.78 and 0.75 and 0.74 and 0.67, respectively. The calibration curve revealed good agreement between the nomogram predictions and actual values.

Conclusion

We constructed robust nomograms to predict the OS and DFS of patients with cervical cancer undergoing treatment with concurrent chemoradiotherapy based on the 2018 FIGO staging system.

Prognostic value of the 2018 FIGO staging system for cervical cancer

OBJECTIVE

To compare the prognostic performance of the FIGO 2009 and FIGO 2018 staging systems for cervical cancer (CC) in regards to risk stratification, survival and treatment outcome.

METHODS

A total of 4461 CC patients diagnosed in Denmark during 2005-2018 were identified through the Danish Gynaecological Cancer Database and restaged from the 2009 FIGO to the 2018 FIGO staging system. 5-year survival estimates were made for each group. Also, association between lymphovascular space invasion (LVSI) and lymph node metastasis (LNM) was assesed for tumors with a horizontal spread >7 mm and depth of invasion ≤5 mm.

RESULTS

Overall, stage migration was observed in 41.4% of our cases due to the introduction of stage IIIC (20.1%), refined tumor size criteria within stage I (76.2%), and use of radiological findings to define stage IV (3.7%). 5-year overall survival increased for all stages except IA2, IIA2, IIIA and IIIB. Restaging of 2009 IB1 to 2018 FIGO resulted in significant stage allocations. Furthermore, an association between LVSI and LNM was observed in squamous cell carcinomas with a depth of invasion of 3-5 mm and a horizontal spread >7 mm (p = 0.03).

CONCLUSION

The 2018 FIGO staging system provided improved discriminatory ability for stage I and IV. Grouping all patients with positive pelvic or paraortal lymph nodes to stage IIIC led to pronounced heterogenous survival rates within these stages. Lymph node assessment was proven imperative in FIGO 2018 IA2 squamous cell carcinomas with a depth of invasion of 3-5 mm, a horizontal spread >7 mm and LVSI.

Post-recurrence survival in patients with cervical cancer

BACKGROUND

Up to 26% of patients with early-stage cervical cancer experience relapse after primary surgery. However, little is known about which factors influence prognosis following disease recurrence. Therefore, our aims were to determine post-recurrence disease-specific survival (PR-DSS) and to identify respective prognostic factors for PR-DSS.

METHODS

Data from 528 patients with early-stage cervical cancer who relapsed after primary surgery performed between 2007 and 2016 were obtained from the SCANN study (Surveillance in Cervical CANcer). Factors related to the primary disease and recurrence were combined in a multivariable Cox proportional hazards model to predict PR-DSS.

RESULTS

The 5-year PR-DSS was 39.1% (95% confidence interval [CI] 22.7%-44.5%), median disease-free interval between primary surgery and recurrence (DFI1) was 1.5 years, and median survival after recurrence was 2.5 years. Six significant variables were identified in the multivariable analysis and were used to construct the prognostic model. Two were related to primary treatment (largest tumour size and lymphovascular space invasion) and four to recurrence (DFI1, age at recurrence, presence of symptoms, and recurrence type). The C-statistic after 10-fold cross-validation of prognostic model reached 0.701 (95% CI 0.675-0.727). Three risk-groups with significantly differing prognoses were identified, with 5-year PR-DSS rates of 81.8%, 44.6%, and 12.7%.

CONCLUSIONS

We developed the robust model of PR-DSS to stratify patients with relapsed cervical cancer according to risk profiles using six routinely recorded prognostic markers. The model can be utilised in clinical practice to aid decision-making on the strategy of recurrence management, and to better inform the patients.

Treatment Strategies and Prognostic Factors of 2018 FIGO Stage IIIC Cervical Cancer: A Review

Cervical cancer is the fourth most common malignant tumor globally in terms of morbidity and mortality. The presence of lymph node metastasis (LNM) is an independent prognostic factor for progression-free survival (PFS) and overall survival (OS) in cervical cancer patients. The International Federation of Gynecology and Obstetrics (FIGO) staging system was revised in 2018. An important revision designates patients with regional LNM as stage IIIC, pelvic LNM only as stage IIIC1, and para-aortic LNM as stage IIIC2. However, the current staging system is only based on the anatomical location of metastatic lymph nodes (LNs). It does not consider other LN status parameters, which may limit its prognostic significance to a certain extent and needs further exploration and confirmation in the future. The purpose of this review is to summarize the choice of treatment for stage IIIC cervical cancer and the effect of different LN status parameters on prognosis.

Nomogram Predicting Overall Survival in Patients With Locally Advanced Cervical Cancer Treated With Radiochemotherapy Including Image-Guided Brachytherapy: A Retro-EMBRACE Study

PURPOSE

To present a nomogram for prediction of overall survival (OS) in patients with locally advanced cervical cancer (LACC) undergoing definitive radiochemotherapy including image-guided adaptive brachytherapy (IGABT).

METHODS AND MATERIALS

Seven hundred twenty patients with LACC treated with radiochemotherapy including IGABT in 12 institutions (median follow-up 56 months) were analyzed; 248 deaths occurred. Thirteen candidate predictors for OS were a priori chosen on the basis of the literature and expert knowledge. Missing data (7.2%) were imputed using multiple imputation and predictive mean matching. Univariate analysis with a multivariable Cox regression model for OS stratified by center was performed. Stepwise selection of predictive factors with the Akaike Information Criterion was used to obtain a predictive model and construct a nomogram for OS predictions 60 months from diagnosis; this was internally validated by concordance probability as a measure of discrimination and a calibration plot.

RESULTS

Thirteen potential predictive factors were evaluated; 10 factors reached statistical significance in univariate analysis (age, Hemoglobin, FIGO Stage₂₀₀₉, tumor width, corpus involvement, lymph node involvement, concurrent chemotherapy, dose to 90% of the high-risk clinical target volume_, volume of CTV at the first brachytherapy [CTV_HRVolumeBT], overall treatment time [OTT]). Four factors were confirmed significant within the multivariable Cox regression model (FIGO Stage₂₀₀₉, lymph node involvement, concurrent chemotherapy, CTV_HRVolumeBT). The predictive model and corresponding nomogram were based on 7 Akaike Information Criterion-selected factors (age, corpus involvement, FIGO Stage₂₀₀₉, lymph node involvement, concurrent chemotherapy, CTV_HRVolumeBT, OTT) and showed promising calibration and discrimination (cross-validated concordance probability c = 0.73).

CONCLUSIONS

This is the first nomogram to predict OS in patients with LACC treated with IGABT. In addition to previously reported factors (age, FIGO₂₀₀₉ stage, corpus involvement, chemotherapy delivery, OTT, lymph node involvement), status of primary tumor at the time of brachytherapy seems to be an essential outcome predictor. These results can facilitate individualized tailoring of treatment and patient counseling during the treatment.

A prognostic value of CD45RA+, CD45RO+, CCL20+ and CCR6+ expressing cells as 'immunoscore' to predict cervical cancer induced by HPV

The interplay between cervical cancer (CC) and immune cells, mainly intratumoral lymphocytes, has a pivotal role in carcinogenesis. In this context, we evaluated the distribution of CD45RA⁺ and CD45RO⁺ cells as well as CCR6⁺ and CCL20⁺ cells in intraepithelial (IE) and marginal stroma (MS) areas from cervical intraepithelial neoplasia (CIN) I-III, and CC as 'immunoscore' for HPV-induced CC outcome. We observed increased CD45RA⁺ and CD45RO⁺ cells distribution in IE and MS areas in the CC group compared to CIN groups and healthy volunteers. Interestingly, there is a remarkable reduction of CCL20⁺ expressing cells distribution according to lesion severity. The CC group had a significant decrease in CCL20⁺ and CCR6⁺-expressing cells distribution in both IE and MS areas compared to all groups. Using the 'immunoscore' model, we observed an increased number of women presenting high CD45RA⁺/CD45RO⁺ and low CCL20⁺/CCR6⁺ 'immunoscore' in the CC group. Our results suggested a pattern in cervical inflammatory process with increasing CD45RA⁺/CD45RO⁺, and decreasing CCL20⁺/CCR6⁺ expression in accordance with CIN severity. Taken together, these markers could be evaluated as 'immunoscore' predictors to CC response. A more comprehensive analysis of longitudinal studies should be conducted to associate CD45RA⁺/CD45RO⁺ and CCL20⁺/CCR6⁺ 'immunoscore' to CC progression and validate its value as a prognosis method.

Development and validation of a novel nomogram to predict cancer-specific survival in patients with uterine cervical adenocarcinoma

BACKGROUND

The treatment strategies and prognostic factors for uterine cervical adenocarcinoma (UAC) primarily refer to that for squamous cell carcinoma (SCC). However, the biological behavior, treatment outcomes of UAC differ from that of SCC. This study aimed to develop and validate a prognostic nomogram for predicting the probability of 3- and 5-year cancer-specific survival (CSS) in patients with UAC.

METHODS

A total of 8,991 UAC patients from the Surveillance, Epidemiology, and End Results (SEER) database were included in this study. Patients diagnosed between 1988 and 2010 (n=5,655) were enrolled for model development and internal validation, and those diagnosed between 2011 and 2016 (n=3,336) were used for temporal validation. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to select predictors of CSS. Cox hazard regression analysis was used to construct the model, which was presented as a static nomogram and web-based dynamic nomogram. The nomogram was internally validated using the bootstrap resampling method and underwent temporal validation.

RESULTS

Tumor grade, stage T, stage N, stage M, tumor size, and surgery of the primary site were identified as independent prognostic factors for CSS and subsequently incorporated into construction of the nomogram. The nomogram could accurately predict 3- and 5-year CSS with an optimism adjusted c-statistic of 0.90 [95% confidence intervals (CI): 0.89-0.91] and 0.89 (95% CI: 0.88-0.91) after internal validation, respectively; while, after temporal validation, the statistics were 0.89 (95% CI: 0.87-0.91) and 0.88 (95% CI: 0.83-0.94), respectively. The internal and temporal calibration plots demonstrated good consistency between the predicted and observed values of CSS. Based on the model, the cases were stratified into high- and low-risk groups. The Kaplan-Meier plot showed that high-risk patients exhibited significantly poorer survival than those at low risk (P<0.0001). The prediction model exhibited a good discriminative ability and an optimal accuracy.

CONCLUSIONS

In the form of a static nomogram or an online calculator, an effective and convenient nomogram was developed and validated to help clinicians quantify the risk of mortality, make personalized survival assessments, and create optimal treatment plans for UAC patients.

Prognostic Nomograms Predicting Survival in Patients With Locally Advanced Cervical Squamous Cell Carcinoma: The First Nomogram Compared With Revised FIGO 2018 Staging System

Objectives

To develop nomograms to assess prognostic factors for 5-year overall survival (OS) and 5-year progression-free survival (PFS) in locally advanced cervical squamous cell carcinoma (LACSC).

Methods

Overall, 618 patients with LACSC were included in this retrospective analysis. Nomograms for 5-year OS and PFS were developed based on Cox proportional hazards regression models. Concordance index (C-index) and calibration curves were used to define the predictive and discriminatory capacity of the nomogram. A comparison between the nomogram and the International Federation of Gynecology and Obstetrics (FIGO) staging system was conducted using time-dependent receiver operating characteristic (tROC) and area under the curve (tAUC).

Results

Multivariate analysis identified several prognostic factors for OS including squamous cell carcinoma antigen (SCC-Ag), body mass index (BMI), tumor size, pelvic wall involvement, and para-aortic lymph node metastasis (PALNM). Prognostic factors for PFS included BMI, hemoglobin (HGB), tumor size, pelvic wall involvement, pelvic lymph node metastasis (PLNM) and PALNM. Following bootstrap correction, the C-index of OS and PFS was 0.713 and 0.686, respectively. These nomograms showed superior performance compared with the FIGO 2009 and 2018 staging schema.

Conclusions

Nomograms were developed to identify prognostic factors for 5-year OS and PFS in patients with LACSC. These nomograms showed good prognostication and are more comprehensive in predicting survival outcomes than existing staging criteria.

Pretreatment Lymph Node Metastasis as a Prognostic Significance in Cervical Cancer: Comparison between Disease Status

PURPOSE

Lymph node metastasis (LNM) is the most significant prognostic factor in cervical cancer that was recently incorporated into the International Federation of Gynecology and Obstetrics (FIGO) staging system. This study was performed to evaluate whether the prognostic significance of LNM differs according to disease status.

MATERIALS AND METHODS

Patients with FIGO stage IB or higher cervical cancer who had pretreatment computed tomography and/or magnetic resonance imaging studies as well as long-term follow-up were enrolled in this retrospective study. The hazard ratio (HR) of Cox regression was used to determine the prognostic significance of LNM. The HRs were compared between the different tumor groups (based on stage, histology, tumor size, primary treatment, age, parametrium involvement, and lymphovascular space invasion).

RESULTS

A total of 970 patients treated between January 1999 and December 2007 were included. The pretreatment LNM had prognostic significance in patients with stage IB1/IIA (HR for progression-free survival 2.10, p=0.001; HR for overall survival 1.99, p=0.005). However, the significance gradually decreased or disappeared with advancing stages. Similarly, the prognostic significance of the pretreatment LNM decreased with advancing disease status, including old age, parametrial involvement or lymphovascular space involvement. In contrast, the tumor size was associated with the prognostic significance of LNM with advancing status. The significance of the clinical LNM did not reflect the significance of the clinical stage. In contrast, the tumor size, parametrial involvement, and significance of the pathologic LNM reflected the clinical stage.

CONCLUSION

In patients with cervical cancer, pretreatment LNM on imaging has different clinical significance depending on the tumor status.

Combinative evaluation of primary tumor and lymph nodes to predict pelvic lymphatic metastasis in cervical cancer: an integrated PET-IVIM MRI study

Background

The aim of this study was to evaluate the value of combining pelvic lymph node and tumor characteristics on positron emission tomography-intravoxel incoherent motion magnetic resonance (PET-IVIM MR) imaging for predicting lymph node metastasis in patients with cervical cancer, especially in those with negative lymph nodes on PET.

Methods

The medical records of 95 patients with cervical cancer who underwent surgical resection with pelvic lymph node dissection were evaluated. The patients were divided into negative and positive groups according to postoperative pathologic lymph node diagnosis, and comparisons of the PET and IVIM-derived parameters between the two groups were performed. Univariate and multivariate analyses were performed to construct a predictive model of lymph node metastasis.

Results

For all patients, tumor SUV_max, TLG, D_min, PET and MRI for lymph node diagnosis showed significant differences between patients with and without confirmed lymph node metastasis. Univariate and multivariate logistic analysis showed that the combination of tumor TLG, D_min and PET for lymph node diagnosis had the strongest predictive value (AUC 0.913, p < 0.001). For patients with PET-negative lymph nodes, SUV_max, SUV_mean, MTV, TLG, and D_min showed significant between-group differences, and univariate and multivariate logistic analysis showed that TLG had the strongest predictive value.

Conclusions

The combination of tumorTLG, D_min and PET for lymph node diagnosis is a powerful prognostic factor for all patients. TLG has the best predictive performance in patients with PET negative lymph nodes.

Prognostic Performance of the 2018 International Federation of Gynecology and Obstetrics Cervical Cancer Staging Guidelines

OBJECTIVE

To examine the prognostic performance of the revised 2018 International Federation of Gynecology and Obstetrics (FIGO) cervical cancer staging schema.

METHODS

We used the National Cancer Database to identify women with cervical cancer diagnosed from 2004 to 2015. Using clinical and pathologic data, each patient's stage was classified using three staging schemas: American Joint Committee on Cancer 7th edition, FIGO 2009 and FIGO 2018. The FIGO 2018 revised staging classifies stage IB tumors into three substages based on tumor size (IB1-IB3) and classifies patients with positive lymph nodes (pathologically or clinically detected) as stage IIIC1 (positive pelvic nodes) or IIIC2 (positive para-aortic nodes). Five-year survival rates were estimated for each stage grouping. We sought to determine whether the 2018 FIGO staging system was able to offer improved 5-year survival rate differentiation compared with older staging schemas.

RESULTS

A total of 62,212 women were identified. The classification of stage IB tumors into three substages improved discriminatory ability. Five-year survival in the FIGO 2018 schema was 91.6% (95% CI 90.4-92.6%) for stage IB1 tumors, 83.3% (95% CI 81.8-84.8%) for stage IB2 neoplasms, and 76.1% (95% CI 74.3-77.8%) for IB3 lesions. In contrast, for women with stage III tumors, higher FIGO staging was not consistently associated with worse 5-year survival rates: stage IIIA (40.7%, 95 CI 37.1-44.3%), stage IIIB (41.4%; 95% CI 39.9-42.9%), stage IIIC1 (positive pelvic nodes) was 60.8% (95% CI 58.7-62.8%) and stage IIIC2 37.5% (95% CI 33.3-41.7%).

CONCLUSION

The FIGO 2018 staging schema provides improved discriminatory ability for women with stage IB tumors; however, classification of all women with positive lymph nodes into a single stage results in a very heterogeneous group of patients with highly variable survival rates.

Prognosis-Predicting Model Based on [18F]fluorodeoxyglucose PET Metabolic Parameters in Locally Advanced Cervical Cancer Patients Treated with Concurrent Chemoradiotherapy: Multi-Center Retrospective Study

This study aimed to develop a prognosis-predicting model based on [¹⁸F]fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) and clinicopathologic factors in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT). The medical records of 270 locally advanced cervical cancer patients who were treated with CCRT were collected from three institutions and reviewed retrospectively. A nomogram was used for predicting 2-year disease-free survival (DFS) and 5-year overall survival (OS) based on Cox proportional hazards regression. Predictor variables included nodal maximum standardized uptake value (SUVmax), primary tumor SUVmax, age, tumor size, stage, serum squamous cell carcinoma antigen level, and human papillomavirus status. Internal nomogram validation was performed. A nomogram for predicting the 2-year DFS and 5-year OS was constructed using six and seven parameters, respectively. With a focus on 2-year DFS, our model found nodal SUVmax to be the highest weighted negative prognostic factor. With a focus on 5-year OS, young age was the highest weighted negative prognostic factor. The concordance index was 0.75 and 0.78 for the 2-year DFS and 5-year OS, respectively. This nomogram is a predictive tool that can be used to counsel patients for predicting survival outcomes. Moreover, our prognosis-predicting model may make it possible to personalize treatment.

Nomograms for predicting the survival rate for cervical cancer patients who undergo radiation therapy: a SEER analysis

Aim: To integrate multiple independent risk factors to establish prognostic nomograms for better predicting overall survival and disease-specific survival in patients with cervical cancer receiving radiation therapy. Materials & methods: Cox analysis used to construct nomograms. The C-index, time-dependent receiver operating characteristic and calibration plots were used to evaluate the performance. The discrimination abilities were compared using the decision curve analysis, net reclassification improvement and integrated discrimination improvement. Results: After randomization, 2869 and 1230 cervical cancer patients were included in the training and validation sets, respectively. Nomograms that incorporated all of the significant independent factors for predicting the 3- and 5-year overall survival and disease-specific survival in the training cohort were established. Conclusion: Compared with the International Federation of Gynecology and Obstetrics staging system, the proposed nomograms exhibit superior prognostic discrimination and survival prediction.

Prophylactic Extended-Field Irradiation for Patients With Cervical Cancer Treated With Concurrent Chemoradiotherapy: A Propensity-Score Matching Analysis

Supplemental digital content is available in the text.

Objective

The aim of the study was to evaluate the efficacy and toxicity of prophylactic extended-field radiation therapy (RT) for cervical cancer patients treated with concurrent chemoradiotherapy (CCRT).

Methods

Records of patients with cervical cancer without para-aortic metastatic lymph nodes who were treated with definitive RT or CCRT between January 2011 and December 2014 were reviewed. Patients were classified into the pelvic RT and extended-field RT groups. An additional dose of 50.4 Gy in 28 fractions was delivered to para-aortic lymph node regions for patients in the extended-field RT group. Cox regression and propensity-score matching (1:1) were used to compare the overall survival (OS), disease-free survival (DFS), distant failure, and para-aortic lymph node failure (PALNF) between the pelvic RT and extended-field RT groups.

Results

A total of 778 patients were analyzed. Of them, 624 patients were treated with pelvic RT and 154 patients received extended-field RT. The median follow-up period was 37.5 months. In multivariate analysis, extended-field RT was an independent prognostic factor of distant failure (hazard ratio [HR] = 0.49, 95% confidence interval [CI] = 0.26–0.90, P = 0.023) and PALNF (HR = 0.012, 95% CI = 0.00–0.49, P = 0.019). However, it was not significant in predicting OS (P = 0.546) and DFS (P = 0.187). With propensity-score matching, 108 pairs of patients were selected. The 3-year OS, DFS, local control, distant failure, and PALNF rates in the pelvic RT and extended-field RT groups were 87.1% and 85.7% (P = 0.681), 71.0% and 80.6% (P = 0.199), 86.6% and 85.0% (P = 0.695), 21.7% and 7.0% (P = 0.016), and 6.6% and 0% (P = 0.014), respectively. The incidences of grade 3 or greater chronic toxicities were 3.5% and 6.5% in the pelvic RT and extended-field RT groups, respectively (P = 0.097).

Conclusions

Prophylactic extended-field RT was associated with decreased distant failure and PALNF and showed a trend in improving DFS in patients with cervical cancer treated with CCRT.

Nomograms predicting survival and patterns of failure in patients with cervical cancer treated with concurrent chemoradiotherapy: A special focus on lymph nodes metastases

Objective

To construct nomograms predicting survival and patterns of failure in patients with cervical cancer treated with concurrent chemoradiotherapy (CCRT).

Methods

A total of 833 patients with cervical cancer treated with definitive radiotherapy or CCRT in our institute from January 2011 to December 2014 were included. Cox proportional hazard regression models were used in univariate and multivariate analysis. The following variables were included in the univariate analysis: histology, FIGO stage, lymph node metastases (para-aortic, pelvic, common iliac, binary pelvic, and binary common iliac LNMs), the number of pelvic metastatic lymph nodes (MLNs), and the diameter of pelvic MLNs. Nomograms predicting the 3- and 5-year overall survival (OS), disease-free survival (DFS), local control (LC) and distant metastasis-free (DMF) were constructed. The nomograms were internally validated with respect to discrimination and calibration.

Results

The median follow-up period was 36.4 months (range,1.0 to 76.2 months). After univariate and multivariate analysis, histology, FIGO stage, para-aortic LNM, pelvic LNM, number of MLNs and diameter of pelvic MLNs significantly predicted OS, DFS, LC or DMF. Nomograms predicting the 3- and 5-year OS, DFS, LC and DMF were constructed incorporating these significant variables. These nomograms showed good discrimination and calibration, with a concordance index of 0.73 for predicting OS, 0.71 for DFS, 0.73 for LC and 0.67 for DMF.

Conclusion

We constructed nomograms predicting survival and patterns of failure with a special focus on regional LNM in patients with cervical cancer treated with concurrent chemoradiotherapy.

Combinative evaluation of primary tumor and lymph nodes in predicting pelvic lymphatic metastasis in early-stage cervical cancer: A multiparametric PET-CT study

PURPOSE

The purpose of this study is to investigate the value of combining tumor and pelvic lymph node (PLN) characteristics on PET-CT in predicting PLN metastasis of patients with early-stage cervical cancer, specifically to further reduce the false-negative cases of diagnosis.

METHODS

The [18F] FDG PET-CT imaging data of 394 patients who were newly diagnosed with cervical cancer (FIGO stage, Ia-IIa) were retrospectively studied. We measured size, total lesion glycolysis (TLG) of tumor, metabolic tumor volume (MTV), maximum and mean standardized uptake value (SUVmax, SUVmean) of tumor and lymph node (LN). Diagnostic efficiency was evaluated using receiver operator characteristic (ROC) curve. We also investigated additional CT diagnosis information in PET-negative cases.

RESULTS

Our results indicated both lymph node and tumor parameters were independent risk factors for lymphatic metastasis in early-stage cervical cancer. The diagnosis based on above meaningful parameters, we name it 'combination diagnosis', offered significantly higher predictive value than that based on SUV measurement alone, which the values of AUC were 0.842 and 0.784 respectively (P < 0.05). In PET-negative cases, we also found that tumor TLG, suspicious LN in lymphatic drainage pathway, long/short axis of LN ≤ 2, heterogeneity of LN significantly associated with PLN metastasis. ROC analysis showed combination diagnosis of all these parameters above produced an AUC value of 0.859 (P < 0.05, 95% CI, 0.811-0.899), which was significantly higher than either using tumor TLG alone (AUC = 0.622, Z = 3.919, P < 0.05) or indices derived from CT alone (AUC = 0.727, 0.668, 0.695. Z = 3.620, 5.356, 3.696, P < 0.05).

CONCLUSIONS

We proposed a combination diagnosis method that can better predict PLN metastasis for patients with early-stage cervical cancer. In PET-negative cases, combination diagnosis of TLG of tumor and CT indicators also produced improved prediction by reducing false-negative cases of diagnosis. This combination diagnosis approach has significant implications in cervical cancer patient management and treatment planning.

Correlation Between Squamous Cell Carcinoma Antigen Level and the Clinicopathological Features of Early-Stage Cervical Squamous Cell Carcinoma and the Predictive Value of Squamous Cell Carcinoma Antigen Combined With Computed Tomography Scan for Lymph Node Metastasis

OBJECTIVE

The aim of this study was to analyze the relationship between serum squamous cell carcinoma antigen (SCC-Ag) and the clinicopathological features of cervical squamous cell carcinoma. The value of SCC-Ag and computed tomography (CT) for predicting lymph node metastasis (LNM) was evaluated.

METHODS

A total of 197 patients with International Federation of Gynecology and Obstetrics stages IB to IIA cervical squamous cell carcinoma who underwent radical surgery were enrolled in this study. The SCC-Ag was measured, and CT scans were used for the preoperative assessment of lymph node status.

RESULTS

Increased preoperative SCC-Ag levels were associated with International Federation of Gynecology and Obstetrics stage (P = 0.001), tumor diameter of greater than 4 cm (P < 0.001), lymphovascular invasion (P = 0.001), LNM (P < 0.001), and greater than one half stromal infiltration (P < 0.001). Multivariate analysis identified LNM (P < 0.001, odds ratio [OR] = 4.399), tumor diameter of greater than >4 cm (P = 0.001, OR = 4.019), and greater than one half stromal infiltration (P = 0.002, OR = 3.680) as independent factors affecting SCC-Ag greater than or equal to 2.35 ng/mL. In the analysis of LNM, SCC-Ag greater than or equal to 2.35 ng/mL (P < 0.001, OR = 4.825) was an independent factor for LNM. The area under the receiver operator characteristic curve (AUC) of SCC-Ag was 0.763 for all patients, and 0.805 and 0.530 for IB1 + IIA1 and IB2 + IIA2 patients, respectively; 2.35 ng/mL was the optimum cutoff for predicting LNM. The combination of CT and SCC-Ag showed a sensitivity and specificity of 82.9% and 66% in parallel tests, and 29.8% and 93.3% in serial tests, respectively.

CONCLUSIONS

The increase of SCC-Ag level in the preoperative phase means that there may be a pathological risk factor for postoperative outcomes. The SCC-Ag (≥2.35 ng/mL) may be a useful marker for predicting LNM of cervical cancer, especially in stages IB1 and IIA1, and the combination of SCC-Ag and CT may help identify patients with LNM to provide them with the most appropriate therapeutic approach.

The Prognosis and Risk Stratification Based on Pelvic Lymph Node Characteristics in Patients With Locally Advanced Cervical Squamous Cell Carcinoma Treated With Concurrent Chemoradiotherapy

BACKGROUND

The purpose of this study is to determine the prognostic significance of pelvic lymph node (PLN) characteristics and perform risk stratification in patients undergoing concurrent chemoradiotherapy for locally advanced cervical squamous cell carcinoma.

METHODS

We retrospectively reviewed the records of 609 patients with Federation Internationale de Gynecologie et d'Obstetrique (FIGO) stage II to IVa who underwent concurrent chemoradiotherapy, compared overall survival (OS), distant metastasis-free survival (DMFS), and pelvic recurrence-free survival between patients with or without PLN involvement. We further analyzed prognostic factors for OS and DMFS including FIGO stage, tumor volume, and lymph node (LN) characteristics in 300 patients with PLN involvement.

RESULTS

The 3-year OS rate was 81.7% versus 92.8% (P = 0.002) and the 3-year DMFS rate was 79.3% versus 92.7% (P = 0.006) in patients with or without PLN involvement, respectively. With univariable analysis, FIGO stage, LN-volume, LN-number, LN-diameter, and matted/necrotic LN affected both OS and DMFS. Based on multivariable analysis, we created a risk stratification model. For OS, the independent risk factors were FIGO stage III or IVa, LN-volume of 3 cm or more, LN-diameter of 1.5 cm or more, and matted/necrotic LN. The low-risk group (no risk factors), mid-risk group (1 or 2 risk factors), and high-risk group (3 or 4 risk factors) had a 3-year OS of 96.6%, 84.9%, and 64.7%, respectively (P = 0.005). For DMFS, LN-diameter of 1.5 cm or more, LN-number of 3 or more, and matted/necrotic LN were the independent risk factors. The subgroups for DMFS were the low-risk group (no risk factors), the mid-risk group (1 risk factor), and the high-risk group (2 or 3 risk factors), and the 3-year DMFS was 92.4%, 76.2%, and 64.6%, respectively (P = 0.001).

CONCLUSIONS

The prognosis was significantly poorer for patients with high-risk lymph node characteristics. Using this risk stratification, we should select the most appropriate and individualized treatment modality to improve outcomes in those patients with a poorer prognosis.

Prognostic models for locally advanced cervical cancer: external validation of the published models

OBJECTIVE

To externally validate the prognostic models for predicting the time-dependent outcome in patients with locally advanced cervical cancer (LACC) who were treated with concurrent chemoradiotherapy in an independent cohort.

METHODS

A historical cohort of 297 women with LACC who were treated with radical concurrent chemoradiotherapy from 1999 to 2014 at the 12 de Octubre University Hospital (H12O), Madrid, Spain. The external validity of prognostic models was quantified regarding discrimination, calibration, measures of overall performance, and decision curve analyses.

RESULTS

The review identified 8 studies containing 13 prognostic models. Different (International Federation of Gynecology and Obstetrics [FIGO] stages, parametrium involvement, hydronephrosis, location of positive nodes, and race) but related cohorts with validation cohort (5-year overall survival [OS]=70%; 5-year disease-free survival [DFS]=64%; average age of 50; and over 79% squamous cell) were evaluated. The following models exhibited good external validity in terms of discrimination and calibration but limited clinical utility: the OS model at 3 year from Kidd et al.'s study (area under the receiver operating characteristic curve [AUROC]=0.69; threshold of clinical utility [TCU] between 36% and 50%), the models of DFS at 1 year from Kidd et al.'s study (AUROC=0.64; TCU between 24% and 32%) and 2 years from Rose et al.'s study (AUROC=0.70; TCU between 19% and 58%) and the distant recurrence model at 5 years from Kang et al.'s study (AUROC=0.67; TCU between 12% and 36%).

CONCLUSION

The external validation revealed the statistical and clinical usefulness of 4 prognostic models published in the literature.

Validation of Nomograms for Survival and Metastases after Hysterectomy and Adjuvant Therapy in Uterine Cervical Cancer with Risk Factors

Background. Three nomogram models for early stage uterine cervical cancer have been developed (KROG 13-03 for overall survival [OS], SNUH/AMC for disease-free survival [DFS], and KROG 12-08 for distant metastases-free survival [DMFS]) after radical hysterectomy (RH) and pelvic lymph node dissection (PLND). This study aimed to validate these models using our cohort with adjuvant radiotherapy. Methods. According to the eligibility criteria of nomogram studies, patients were enrolled in Group A (N = 109) for the two KROG models (RH with PLND and whole pelvic irradiation) and Group B (N = 101) for the SNUH/AMC model (RH with PLND and squamous histology). Using Cox-regression hazard models, the prognostic factors of our cohorts were evaluated. The risk probabilities induced from published nomogram scores were calculated and the concordance indices were evaluated. Results. Group A had 88.1% 5-year OS and 86.0% 5-year DMFS. Group B had 83.0% 5-year DFS. In multivariate analyses, large tumor size for OS (HR 8.62, P < 0.001) and DMFS (HR 5.13, P = 0.003), young age (≤40 versus 41-64 years) for OS (HR 4.63, P = 0.097) and DFS (HR 3.44, P = 0.051), and multiple lymph node metastases (0 versus ≥3) for DMFS (HR 4.03, P = 0.031) and DFS (HR 3.90, P = 0.038) were significantly correlated. The concordance indices for OS, DMFS, and DFS were 0.612 (P = 0.002), 0.597 (P = 0.014), and 0.587 (P = 0.020), respectively. Conclusion. The developed nomogram models after RH and PLND are clinically useful in predicting various types of survival with significance.

Treatment Compliance and Outcomes for Women With Locoregionally Advanced Cervical Cancer Treated in a Safety Net Health System

OBJECTIVE

This study aims to assess treatment compliance among women undergoing definitive chemoradiation with weekly cisplatin for cervical cancer within a safety net health system and to quantify the impact of chemotherapy compliance on outcomes.

MATERIALS AND METHODS

All women who were treated for International Federation of Gynecology and Obstetrics stage IB2 to stage IVA cervical cancer between April 2008 and May 2014 were identified. Treatment delays were attributed to toxicity, comorbid conditions, or system issues, or categorized as patient-initiated. Disease-free survival and overall survival of women who received fewer than 6 versus 6 or more doses of weekly cisplatin 40 mg/m were compared using Kaplan-Meier analyses.

RESULTS

One hundred nineteen women (mean [SD] age, 48.5 [11.8] years) were identified. Most women (n = 112; 94.1%) completed definitive radiotherapy, requiring a mean (SD) of 56.5 (20.1) days. Sixty-four women (57.1%) completed definitive radiotherapy in 56 days or less. Only 44 women (36.4%) received 6 or more cycles of cisplatin. Of 122 delayed cycles, reasons for delay were as follows: grade 2 or higher toxicity (n = 70; 57.4%), medical comorbidity (n = 12; 9.8%), system issues (n = 9; 7.4%), and patient-initiated (n = 14; 11.5%). Multiple issues complicated treatment for 3 doses (2.5%). Reasons for delay were not documented in 14 doses (11.5%). Among patients who received 6 or more cycles, disease-free survival improved by 17.4 months (mean [SD], 61.1 [3.7] vs 43.7 [4.3] months, P = 0.002) and overall survival improved by 8.6 months (mean [SD], 68.7 [2.3] vs 60.1 [3.7] months, P = 0.011).

CONCLUSIONS

Higher rates of toxicity and psychosocial barriers to chemotherapy compliance adversely impact survival among women who seek care in low-resource settings. In our population, administration of all 6 cycles of cisplatin was necessary for optimal survival benefit. Future efforts to improve cervical cancer outcomes should address preventable reasons for treatment delays among underinsured or uninsured individuals.

Complementary Prognostic Value of Pelvic Magnetic Resonance Imaging and Whole-Body Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography in the Pretreatment Assessment of Patients With Cervical Cancer

OBJECTIVE

The aim of this study was to evaluate the incremental prognostic value of pelvic magnetic resonance imaging (MRI) and whole-body F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) findings compared with clinical-histopathologic factors in patients with newly diagnosed cervical cancer.

METHODS

The institutional review board approved this retrospective study of 114 patients (median age, 40.6 years) with International Federation of Gynecology and Obstetrics (FIGO) stage I-IVB cervical cancer who underwent pretreatment MRI and PET/CT. All scans were reviewed for locoregional tumor extent, pelvic or/and para-aortic lymphadenopathy, and distant metastases. Univariate Cox proportional hazard regression was performed to evaluate associations between clinical-histopathologic factors, imaging findings, and progression-free survival (PFS). Multivariate models were built using independent predictors for PFS. Harrell C was used to measure concordance (C index).

RESULTS

Forty patients progressed within a median time of 10.4 months (range, 0.4-40.3 months). At univariate analysis, age, FIGO stage, tumor histology, tumor grade, and all MRI and PET/CT features were significantly associated with PFS (P < 0.0001 to P = 0.0474). A multivariate model including clinical and imaging parameters (parametrial invasion on MRI and para-aortic lymphadenopathy/distant metastases on PET/CT) had significantly higher concordance for predicting PFS than a model including clinical parameters only (C index: 0.81 [95% confidence interval, 0.75-0.87] vs 0.68 [95% confidence interval, 0.59-0.78]; P < 0.001). The comparison of C indices for the combined clinical and imaging model approached significance when compared with a FIGO stage model (C index: 0.81 [95% confidence interval, 0.75-0.87] vs 0.75 [95% confidence interval, 0.69-0.82]; P = 0.058).

CONCLUSIONS

In patients with newly diagnosed cervical cancer, a prognostic model including combined MRI and PET/CT findings provides information that complements clinical and histopathologic factors.

The Level of Squamous Cell Carcinoma Antigen and Lymph Node Metastasis in Locally Advanced Cervical Cancer

BACKGROUND

This study aimed to determine the utility and a cut-off level of serum squamous cell carcinoma antigen (SCC-Ag) to predict lymph node metastasis in locally advanced cervical cancer cases. We also investigated the correlation between SCC-Ag level and lymph node status.

MATERIALS AND METHODS

From June 2009 to June 2014, 232 patients with cervical cancer stage IB2-IVA, who were treated at Ramathibodi Hospital, were recruited. Receiver operating characteristic (ROC) curves were used to identify the best cut-off point of SCC-Ag level to predict lymph node metastasis. Quantile regression was performed to evaluate the correlation between SCC-Ag levels and pelvic lymph node metastasis, paraaortic lymph node metastasis, and parametrial involvement as well as tumor size.

RESULTS

Pelvic lymph node metastasis and paraaortic lymph node metastasis were diagnosed in 46.6% and 20.1% of the patients, respectively. The median SCC-Ag level was 6 ng/mL (range, 0.5 to 464.6 ng/ mL). The areas under ROC curves between SCC-Ag level and pelvic lymph node metastasis, paraaotic lymph node metastasis, parametrial involvements were low. SCC-Ag level was significantly correlated with paraaortic lymph node status (p=0.045) but not with pelvic lymph node status and parametrial involvement. SCC-Ag level was also related to the tumor diameter (p<0.05).

CONCLUSIONS

SCC-Ag level is not a good predictor for pelvic and paraaortic lymph node metastasis. However, it is still beneficial to assess the tumor burden of squamous cell carcinoma of the cervix.

Efficacy and safety of nedaplatin-based concurrent chemoradiotherapy for FIGO Stage IB2-IVA cervical cancer and its clinical prognostic factors

Cisplatin-based concurrent chemoradiotherapy (CCRT) is a standard treatment for cervical cancer, but nedaplatin-based CCRT is not routinely administered. We evaluated the efficacy and safety of nedaplatin-based CCRT (35 mg/m(2) weekly) and analyzed prognostic factors for survival among 52 patients with International Federation of Gynecology and Obstetrics (FIGO) Stage IB2-IVA cervical cancer treated from 1999 to 2009. Patients were treated with a combination of external beam radiotherapy of 40-56 Gy (in 20-28 fractions) and 13.6-28.8 Gy (in 2-4 fractions) of high-dose-rate (HDR) intracavitary brachytherapy or 18 Gy (in 3 fractions) of HDR interstitial brachytherapy. Overall survival (OS), progression-free survival (PFS), and local control (LC) were estimated using the Kaplan-Meier method. The Cox proportional hazard model was used for multivariate analysis. Acute and late toxicities were evaluated using the Common Terminology Criteria for Adverse Events version 4.0. The median follow-up period was 52 months. The median patient age was 63 years. The 5-year OS, PFS and LC rates were 78%, 57% and 73%, respectively. Multivariate analysis showed that histologic type, maximum tumor diameter, and pretreatment hemoglobin level were independent risk factors for PFS. Regarding adverse effects, 24 patients (46%) had acute Grade 3-4 leukopenia and 5 (10%) had late Grade 3 gastrointestinal toxicities. No patient experienced renal toxicity. Nedaplatin-based CCRT for FIGO Stage IB2-IVA cervical cancer was efficacious and safe, with no renal toxicity. Histologic type, maximum tumor diameter, and pretreatment hemoglobin level were statistically significant prognostic factors for PFS.

Distant metastasis in patients with cervical cancer after primary radiotherapy with or without chemotherapy and image guided adaptive brachytherapy

OBJECTIVE

The aim of this study is to investigate patterns of distant relapse after primary radiochemotherapy in cervical cancer patients.

METHODS

All patients with cervical cancer treated in curative intent with external beam radiotherapy +/- chemotherapy and image-guided adaptive brachytherapy between January 1998 and June 2009 at the Medical University of Vienna were included in this retrospective analysis. Patients with locoregional recurrences were excluded from this study. Presence, site of and time to distant metastases were recorded. For identifying prognostic factors, uni- and multivariate analyses using Cox regression analysis were performed. Based on the result from the multivariate analysis, patients were stratified into a high and a low risk group. The Kaplan-Meier method was used to estimate distant-metastasis-free-survival in the overall cohort, in the risk groups and for analysing the impact of chemotherapy within the risk groups.

RESULTS

A total number of 189 patients were included in this study. After a median follow-up of 54 months, 49 patients developed distant metastases. Overall, distant-metastasis-free-survival 5 years after treatment was 73%. FIGO stage, lymph node status and the extent of tumour regression during treatment were significant predictors for distant metastasis. Distant-metastasis-free-survival 5 years after treatment was 91% and 60% in the low and high risk groups, respectively. The number of the cycles of chemotherapy had a significant impact on the occurrence of distant metastasis in high risk patients, but not in low risk patients.

CONCLUSION

Patients with high risk factors have a 40% probability of developing distant metastasis within 5 years. In these patients, decreasing the number of cycles of cisplatin may increase their probability of developing distant metastasis.

Individualized prediction of overall survival after postoperative radiation therapy in patients with early-stage cervical cancer: a Korean Radiation Oncology Group study (KROG 13-03)

PURPOSE

A nomogram is a predictive statistical model that generates the continuous probability of a clinical event such as death or recurrence. The aim of the study was to construct a nomogram to predict 5-year overall survival after postoperative radiation therapy for stage IB to IIA cervical cancer.

METHODS AND MATERIALS

The clinical data from 1702 patients with early-stage cervical cancer, treated at 10 participating hospitals from 1990 to 2011, were reviewed to develop a prediction nomogram based on the Cox proportional hazards model. Demographic, clinical, and pathologic variables were included and analyzed to formulate the nomogram. The discrimination and calibration power of the model was measured using a concordance index (c-index) and calibration curve.

RESULTS

The median follow-up period for surviving patients was 75.6 months, and the 5-year overall survival probability was 87.1%. The final model was constructed using the following variables: age, number of positive pelvic lymph nodes, parametrial invasion, lymphovascular invasion, and the use of concurrent chemotherapy. The nomogram predicted the 5-year overall survival with a c-index of 0.69, which was superior to the predictive power of the International Federation of Gynecology and Obstetrics (FIGO) staging system (c-index of 0.54).

CONCLUSIONS

A survival-predicting nomogram that offers an accurate level of prediction and discrimination was developed based on a large multi-center study. The model may be more useful than the FIGO staging system for counseling individual patients regarding prognosis.

Preoperative nomogram for the identification of lymph node metastasis in early cervical cancer

Background:

The objective of this study is to construct a preoperative nomogram predicting lymph node metastasis (LNM) in early-cervical cancer patients.

Methods:

Between 2009 and 2012, 493 early-cervical cancer patients received hysterectomy and pelvic/para-aortic lymphadenectomy. Patients who were diagnosed during 2009–2010 were assigned to a model-development cohort (n=304) and the others were assigned to a validation cohort (n=189). A multivariate logistic model was created from preoperative clinicopathologic data, from which a nomogram was developed and validated. A predicted probability of LNM<5% was defined as low risk.

Results:

Age, tumour size assessed by magnetic resonance imaging, and LNM assessed by positron emission tomography/computed tomography were independent predictors of nodal metastasis. The nomogram incorporating these three predictors demonstrated good discrimination and calibration (concordance index=0.878; 95% confidence interval (CI), 0.833−0.917). In the validation cohort, the discrimination accuracy was 0.825 (95% CI, 0.736−0.895). In the model-development cohort, 34% of them were classified as low risk and negative predictive value (NPV) was 99.0%. In the validation cohort, 38% were identified as low risk and NPV was 95.8%. Integrating the model-development and validation cohorts, negative likelihood ratio was 0.094 (95% CI, 0.036−0.248).

Conclusion:

A robust nomogram predicting LNM in early cervical cancer was developed. This model may improve clinical trial design and help physicians to decide whether lymphadenectomy should be performed.