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

ABSTRACT: 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.

SUBMITTER: Wang W

PROVIDER: S-EPMC6464190 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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

Wang Weiping W Liu Xiaoliang X Meng Qingyu Q Zhang Fuquan F Hu Ke K

PloS one 20190415 4

<h4>Objective</h4>To construct nomograms predicting survival and patterns of failure in patients with cervical cancer treated with concurrent chemoradiotherapy (CCRT).<h4>Methods</h4>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: h ...[more]

PMID: 30986236

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Project description:BackgroundIn 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.MethodsWe 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.ResultsWe 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.ConclusionWe 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.

Project description:BackgroundGlioblastoma (GBM) is the most common malignant brain tumor in adults. The prognosis of GBM patients is poor. Even with active standard treatment, the median overall survival is only 14.6 months. It is therefore critical to ascertain recurrence and search for factors that influence the prognosis of GBM. This study aimed to screen the variables related to the progression-free survival (PFS) and overall survival (OS) of GBM patients undergoing surgery and concurrent chemoradiotherapy, as well as propose a nomogram for individual risk prediction based on preoperative imaging parameters and clinicopathological variables readily available in clinical practice.MethodsWe retrospectively analyzed 114 consecutive patients with GBM who underwent surgery and concurrent chemoradiotherapy at the Second Affiliated Hospital, Zhejiang University School of Medicine from January 1st, 2015, to June 1st, 2018. Twenty-four preoperative magnetic resonance imaging (MRI) parameters were extracted manually from the Picture Archiving and Communication System (PACS). Clinicopathological factors were extracted from the electronic medical record system (EMRS). Least absolute shrinkage and selection operator (LASSO) regression and Cox regression were used for feature selection and model prediction, respectively. The models were presented using nomograms, which were applied to identify the risk of recurrence and survival according to the score. The performance of the nomograms to predict PFS and OS was tested with C-statistics, calibration plots, and Kaplan-Meier curves.ResultsThe results revealed that sex, Karnofsky performance score (KPS), O6-methylglucamine-DNA methyltransferase (MGMT) protein expression, number of adjuvant chemotherapy cycles with temozolomide (TMZ), and the MRI signature effectively predicted PFS; and sex, KPS, extent of surgery, number of TMZ cycles, and MRI signature effectively predicted OS. The nomogram revealed good discriminative ability (C-statistics: 0.81 for PFS and 0.79 for OS). In the nomogram of PFS, patients with a score greater than 122 were considered to have a high risk of recurrence. In the nomogram of OS, the cutoff score were 115 and 145, and then patients were classified as low, medium, and high risk.ConclusionsIn conclusion, our nomograms can effectively predict the risk of recurrence and survival of GBM patients and thus can be a good guide for clinical practice.

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

Publications

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

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