The efficacy and safety of neoadjuvant chemotherapy in the treatment of locally advanced cervical cancer: A randomized multicenter study

Yang, Zhijun; Chen, Dandan; Zhang, Jieqing; Yao, Desheng; Gao, Kun; Wang, He; Liu, Cui; Yu, Jiang; Li, Li

doi:10.1016/j.ygyno.2015.06.027

Cited by 51 publications

(61 citation statements)

References 18 publications

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“…The short-term response was evaluated by change in tumor size according to Response Evaluation Criteria In Solid Tumors (RECIST v. 1.1) as follows: complete response (CR) was defined as eradication of cervical lesion; partial response (PR) (a ≥30% decrease in the longest tumor diameter); progressive disease (PD) (a ≥20% increase in the longest diameter (LD) of tumor) and stable disease (SD) as the decrease or increase of LD of the cervical lesion was less than PR or PD (25). Many studies proposed two cycles of NACT were adequate for LACC patients to obtain optimal efficacy with relatively low adverse reactions (9,26). Based on various treatment courses in the study, we set up new response evaluation criteria especially for upcoming radiomic analysis as following: For patients with CR or PR by RECIST (v.1.1) within two cycles of treatment are recognized as "responder" (chemo-sensitive).…”

Section: Assessment Of Responsementioning

confidence: 99%

Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis

et al. 2020

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Objective: To investigate whether pre-treatment CT-derived radiomic features could be applied for prediction of clinical response to neoadjuvant chemotherapy (NACT) in locally advanced cervical cancer (LACC).Patients and Methods: Two hundred and seventy-seven LACC patients treated with NACT followed by surgery/radiotherapy were included in this multi-institution retrospective study. One thousand and ninety-four radiomic features were extracted from venous contrast enhanced and non-enhanced CT imaging for each patient. Five combined methods of feature selection were used to reduce dimension of features. Radiomics signature was constructed by Random Forest (RF) method in a primary cohort of 221 patients. A combined model incorporating radiomics signature with clinical factors was developed using multivariable logistic regression. Prediction performance was then tested in a validation cohort of 56 patients.Results: Radiomics signature containing pre-and post-contrast imaging features can adequately distinguish chemotherapeutic responders from non-responders in both primary and validation cohorts [AUCs: 0.773 (95% CI, 0.701-0.845) and 0.816 (95% CI, 0.690-0.942), respectively] and remain relatively stable across centers. The combined model has a better predictive performance with an AUC of 0.803 (95% CI, 0.734-0.872) in the primary set and an AUC of 0.821 (95% CI, 0.697-0.946) in the validation set, compared to radiomics signature alone. Both models showed good discrimination, calibration.Conclusion: Newly developed radiomic model provided an easy-to-use predictor of chemotherapeutic response with improved predictive ability, which might facilitate optimal treatment strategies tailored for individual LACC patients.

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Section: Assessment Of Responsementioning

confidence: 99%

Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis

et al. 2020

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“…LVSI and vaginal surgical margin were reported to be independent prognostic factors132627, and these risk factors were statistically significant in univariate Cox regression for DFS during risk model training. Although these two margins were ultimately excluded from the multivariate Cox model, our study did validate previous findings17.…”

Section: Discussionmentioning

confidence: 90%

Prognostic risk model development and prospective validation among patients with cervical cancer stage IB2 to IIB submitted to neoadjuvant chemotherapy

Huang

Sun

Xiong

et al. 2016

Sci Rep

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This study was designed to develop a risk model for disease recurrence among cervical cancer patients who underwent neoadjuvant chemotherapy and radical surgery. Data for 853 patients were obtained from a retrospective study and used to train the model, and then data for 447 patients from a prospective cohort study were employed to validate the model. The Cox regression model was used for calculating the coefficients of the risk factors. According to risk scores, patients were classified into high-, intermediate-, and low-risk groups. There were 49 (49/144, 34%) recurrences observed in the high-risk group (with a risk score ≥ 2.65), compared with 3 (3/142, 2%) recurrences in the low-risk group (with a risk score < 0.90). Disease-free survival (DFS) was significantly different (log-rank p < 0.001) among the three risk groups; the risk model also revealed a significant increase in the accuracy of predicting 5-year DFS with the area under the ROC curve (AUC = 0.754 for risk model vs 0.679 for FIGO stage system); the risk model was also validated with data from the prospective study (log-rank p < 0.001, AUC = 0.766). Both high-risk and intermediate-risk patients can be more effectively identified by this risk model.

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“…Neoadjuvant chemotherapy (NACT) was proven to be an effective treatment for cervical cancer23. However, approximately 20% of patients do not respond to NACT.…”

mentioning

confidence: 99%

“…In previous studies, no clinical factors have shown a strong correlation with the response to NACT23. Additionally, there has been no bio-marker proven to effectively predict the response to NACT.…”

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confidence: 99%

Genome-wide association study identifies four SNPs associated with response to platinum-based neoadjuvant chemotherapy for cervical cancer

Huang

Zhang

et al. 2017

Sci Rep

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To identify genomic markers associated with the response to neoadjuvant chemotherapy (NACT) in patients with cervical cancer, we performed a three-stage genome-wide association study (GWAS) in the Han Chinese population. A total of 596 patients with stage IA2-IIIB cervical cancer were enrolled in this study. One single nucleotide polymorphism (SNP) (rs6812281, per allele OR = 2.37, P = 9.0 × 10−9) located at 4q34.3 reached GWAS significance (P < 5.0 × 10−8). Another three SNPs, rs4590782 (10q26.2, P = 1.59 × 10−5, per allele OR = 0.48), rs1742101 (14q32.11, P = 7.11 × 10−6, per allele OR = 0.52), and rs1364121 (16q23.3, P = 3.15 × 10−6, per allele OR = 1.98), exhibited strong evidence of associations with response to neoadjuvant chemotherapy. Patients with a C allele (CT + CC) of rs4590782 had better 5-year overall survival rates (82.9% vs. 75.8%, P = 0.083) and 5-year disease-free survival rate (80.8% vs. 72.7%, P = 0.021) than those without a C allele. Our findings help to characterize the genetic etiology of the response to neoadjuvant chemotherapy in patients with cervical cancer.

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The efficacy and safety of neoadjuvant chemotherapy in the treatment of locally advanced cervical cancer: A randomized multicenter study

Cited by 51 publications

References 18 publications

Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis

Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis

Prognostic risk model development and prospective validation among patients with cervical cancer stage IB2 to IIB submitted to neoadjuvant chemotherapy

Genome-wide association study identifies four SNPs associated with response to platinum-based neoadjuvant chemotherapy for cervical cancer

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