Calculating the overall survival probability in patients with cervical cancer: a nomogram and decision curve analysis-based study

Xie, Gongnan; Wang, Ruiqi; Shang, Li; Qi, Cuifang; Yang, Lei; Huang, Liyan; Yang, Wenfang; Chung, Mei

doi:10.1186/s12885-020-07349-4

Cited by 28 publications

(36 citation statements)

References 33 publications

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“…The grade, tumor size and histological type of the tumor also significantly affected the prognosis of the patients [16,17]. In this study, the same results were supported by the C-index, concordance index; ROC, receiver operating characteristic; SEER, surveillance, epidemiology and end results; TNM, tumor-node-metastasis; EOCC, early-onset cervical cancer; CI, confidence intervals; OS, overall survival; CSS, cancer-specific survival.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a SEER-based prognostic nomogram for cervical cancer patients below the age of 45 years

Liu¹,

Li²,

Xie³

et al. 2020

Bosn J of Basic Med Sci

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This study aimed to establish a nomogram for the prognostic prediction of patients with early-onset cervical cancer (EOCC) in both overall survival (OS) and cancer-specific survival (CSS). The 10,079 patients diagnosed with EOCC between 2004 and 2015 were captured within the Surveillance, Epidemiology, and End Results (SEER) database and further were divided into training and validation sets randomly. The independent prognostic factors were identified in a retrospective study of 7,055 patients training sets randomly. Besides, the prognostic nomogram was developed using R software according to multivariable Cox regression analysis. Furthermore, the model was externally validated using the data of 3,024 patients diagnosed at different times enrolled in the SEER database. In training set, the C-indexes for OS and CSS prediction were 0.831 (95% confidence interval [CI]: 0.815-0.847) and 0.855(95%CI:0.839-0.871). The results of ROC indicated that nomograms possessed better predict performance compared with TNM-stage and SEER-stage. And the areas under the curve (AUC) of the nomogram for OS and CSS prediction in ROC analysis were 0.855(95%CI:0.847-0.864) and 0.782(95%CI:0.760-0.804), respectively. In addition, calibration curves presented perfect agreements between the nomogram-predicted and actual 1-, 3-, and 5-year in the validation cohort, in OS rate and CSS rate. This study established and validated a prognostic nomogram that provided an accurate prediction of 3-, 5-, and 10-year OS and CSS of EOCC patients, which contributed to clinicians to be useful for patients’ counseling and clinical trial designing.

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Section: Discussionmentioning

confidence: 99%

Development and validation of a SEER-based prognostic nomogram for cervical cancer patients below the age of 45 years

Liu¹,

Li²,

Xie³

et al. 2020

Bosn J of Basic Med Sci

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“…Predictive models was constructed based on tumor size, clinical grade, histological grade, age and other factors to predict 3-year and 5-year OS and CSS for endometrial cancer. Xie et al (18) developed and validated a nomogram of total cervical cancer survival to predict the survival of cervical cancer patients, FIGO staging, age, race, tumor size, pathological classification, and other important factors were used to predict 3-year and 5-year OS of cervical cancer. However, there is currently no nomogram to predict early death from gynecologic tumors.…”

Section: Discussionmentioning

confidence: 99%

A Novel Tool to Predict Early Death in Uterine Sarcoma Patients: A Surveillance, Epidemiology, and End Results-Based Study

et al. 2020

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BackgroundUterine sarcoma is a rare gynecologic tumor with a high degree of malignancy. There is a lack of effective prognostic tools to predict early death of uterine sarcoma.MethodsData on patients with uterine sarcoma registered between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) data. Important independent prognostic factors were identified by univariate and multivariate logistic regression analyses to construct a nomogram for total early deaths and cancer-specific early deaths.ResultsA total of 5,274 patients with uterine sarcoma were included in this study. Of which, 397 patients experienced early death (≤3 months), and 356 of whom died from cancer-specific causes. A nomogram for total early deaths and cancer-specific early deaths was created using data on age, race, tumor size, the International Federation of Gynecology and Obstetrics (FIGO) staging, histological classification, histological staging, treatment (surgery, radiotherapy, chemotherapy), and brain metastases. On comparing the C-index, area under the curve, and decision curve analysis, the created nomogram showed better predictive power and clinical practicality than one made exclusively with FIGO staging. Calibration of the nomogram by internal validation showed good consistency between the predicted and actual early death.ConclusionsNomograms that include clinical characteristics can provide a better prediction of the risk of early death for uterine sarcoma patients than nomograms only comprising the FIGO stage system. In doing so, this tool can help in identifying patients at high risk for early death because of uterine sarcoma.

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“…Furthermore, previous studies demonstrated that these 10 variables were signi cantly associated with the prognosis of cervical cancer. For this reason, univariate and multivariate Cox proportional hazard regression were performed for all these 10 variables [15][16][17].…”

Section: Discussionmentioning

confidence: 99%

“…Our nomograms are well innovated and practical. Firstly, although nomograms for cervical cancer have been widely used [17,20], there is still no one for stage IIIC1 in cervical cancer. Secondly, contrast to FIGO stage, patient demographics (age, race), tumor characteristics (tumor size, histology, differentiation, extension range) and treatment (surgery, radiotherapy) which were independent prognosis factors for OS or CSS were included in our nomograms.…”

Section: Discussionmentioning

confidence: 99%

Nomograms Predicting Overall Survival and Cancer Special Survival for Cervical Cancer in stage IIIC1

Feng

Wang

Xie

et al. 2021

Preprint

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BackgroundThe purpose of this study is to explore the factors that affect the prognosis of overall survival (OS) and cancer special survival (CSS) in cervical cancer with stage IIIC1 and establish nomogram models to predict this prognosis.MethodsData from The Surveil-lance, Epidemiology, and End Results (SEER) Program meeting the inclusion criterions were classified into training group, and data of validation were obtained from the First Affiliated Hospital of Anhui Medical University from 2010 to 2019. The incidence, Kaplan‐Meier curves, OS and CSS of stage IIIC1 were evaluated according to the training group. Nomograms were established according to the results of univariate and multivariate Cox regression models. Harrell’s C-index and receiver operating characteristic curve (ROC) were calculated to measure the accuracy of the prediction models. Calibration plots show the relationship between the predicted probability and the actual outcome. Decision-curve analysis (DCA) was applied to evaluate the clinical applicability of the constructed nomogram.ResultsThe incidence of pelvic lymph node metastasis, a high-risk factor for prognosis in cervical cancer, decreased slightly over time. There are eight independent prognostic variables for OS, including age, race, histology, differentiation, extension range, tumor size, radiation recode and surgery, but seven for CSS with age excluded. Nomograms of OS and CSS were established based on the results. The C-index for the nomograms of OS and CSS were 0.692, 0.689 respectively when random sampling of SEER data sets, and 0.706, 0.737 respectively when random sampling of external data sets. AUCs for the nomogram of OS were 0.648, 0.644 respectively, and 0.683, 0.675 for the nomogram of CSS. Calibration plots for the nomograms were almost identical to the actual observations. The DCA also proved the value of the two models.ConclusionAge, race, histology, differentiation, extension range, tumor size, radiation recode and surgery were all independent prognosis factors for OS. Only age excepts in CSS. OS and CSS nomograms were established in our study based on the result of multivariate Cox proportional hazard regression, and both own good predictive and clinical application value after validation.

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Calculating the overall survival probability in patients with cervical cancer: a nomogram and decision curve analysis-based study

Cited by 28 publications

References 33 publications

Development and validation of a SEER-based prognostic nomogram for cervical cancer patients below the age of 45 years

Development and validation of a SEER-based prognostic nomogram for cervical cancer patients below the age of 45 years

A Novel Tool to Predict Early Death in Uterine Sarcoma Patients: A Surveillance, Epidemiology, and End Results-Based Study

Nomograms Predicting Overall Survival and Cancer Special Survival for Cervical Cancer in stage IIIC1

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