Development and Validation of Novel Nomograms to Predict the Overall Survival and Cancer-Specific Survival of Cervical Cancer Patients With Lymph Node Metastasis

Yi, Jianying; Liu, Zhili; Wang, Lu; Zhang, Xingxin; Pi, Lili; Zhou, Chunlei; Mu, Hong

doi:10.3389/fonc.2022.857375

Cited by 5 publications

(4 citation statements)

References 37 publications

(35 reference statements)

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“…Nomograms, a statistic-based tool, can assess the risk of clinicopathological features by quantifying the biological and clinical variables of patients with cancer (6). To date, nomograms have been widely applied in the personalized prediction of cancer, such lung, cervical, prostate, and hepatocellular carcinomas (7)(8)(9)(10)(11). To the best of our knowledge, several studies have reported risk factors associated with breast cancer (12)(13)(14)(15)(16)(17).…”

Section: Introductionmentioning

confidence: 99%

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

Wang¹,

Xing²,

X³

et al. 2022

Gland Surg

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Background: Nomograms can assess the risk of clinicopathological features by quantifying the biological and clinical variables of cancer patients. However, the nomogram based on significant factors that influence the survival of breast cancer in a large population has been rarely explored. This study was to investigate the predictive effectiveness of a nomogram for the survival of patients with breast cancer. Methods: Demographic and clinical data of 275,812 breast cancer patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. All patients aged ≥20 years in this retrospective cohort study were classified as two groups in a random manner, namely the training set (n=193,069) and validation set (n=82,743). The outcomes of our study were the 3-and 5-year survival of breast cancer. The potential predictors of cancer mortality were screened by univariate and multivariable Cox regression analyses. The nomogram was conducted based on the predictors. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curve was utilized to evaluate the performance of the nomogram.Results: The age at diagnosis, race, marital status, tumor size, first malignant primary indicator, American Joint Committee on Cancer (AJCC) T stage, M stage, tumor grade, and number of malignant tumors were independent predictors for the death of patients with breast cancer. The C-indexes of the training set and the validation set were 0.782 and 0.778, respectively. The area under the curve (AUC) values of the nomogram for predicting the 3-and 5-year survival of breast cancer were 0.770 and 0.756, respectively. Furthermore, the C-index values of our nomogram were 0.816, 0.775, 0.773, 0.734, and 0.750 for predicting survival in Asian, White, Hispanic, American Indian, and Black populations, respectively. Conclusions:The nomogram may have predictive performance for predicting the 3-and 5-year survival of breast cancer patients, and future studies need to validate our findings.

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Section: Introductionmentioning

confidence: 99%

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

Wang¹,

Xing²,

X³

et al. 2022

Gland Surg

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“…All variables can be analyzed simultaneously to avoid overfitting and to reduce the impact of collinearity. The article of Yi et al (25) only focused on the prognosis of cervical cancer patients with lymph node metastases. We had not only established and verified a nomogram for (OR: 1.073-4.286 (29).…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a nomogram for predicting pelvic lymph node metastasis and prognosis in patients with cervical cancer

Wang

Yang

et al. 2022

Front. Oncol.

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ObjectiveCervical cancer (CC) is one of the main causes of death among gynecological malignancies. Patients with CC with lymph node metastasis (LNM) have poor prognoses. We investigated the risk factors and prognosis of LNM in patients with CC patients using data from the SEER database.MethodsWe collected the information of cervical cancer patients registered in SEER database from 2010 to 2015. The dataset was divided into a training set and a validation set at a 7:3 ratio. LASSO regression analysis was used to evaluate risk factors for LNM in patients with CC. Using the results, we established a nomogram prediction model. C-index, ROC curves, calibration curves, decision curve analysis, and clinical impact curves were used to evaluate the prediction performance of the model.ResultsWe included 14,356 patients with CC in the analysis. Among these, 3997 patients were diagnosed with LNM. A training set (10,050 cases) and a validation set (4306 cases) were used for the following analysis. We established nomogram LNM prediction models for the patients with T1-2-stage CC. The C-indices for the internal and external validations of the prediction models were 0.758 and 0.744, respectively. In addition, we established a prognostic nomogram for all CC patients with LNM, and the internal and external validation C-indices were 0.763 and 0.737.ConclusionWe constructed a quantitative and visual predictive nomogram that predicted prognosis of patients with LNM in CC to provide clinicians with a reference for diagnosis and treatment.

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“…The association between multiple socioeconomic factors and survival in patients with cervical cancer requires further assessment. The American Joint Council on Cancer (AJCC) staging system is currently used for routine prognostic assessment of patients with cervical cancer 19. Nevertheless, the AJCC staging system is not comprehensive enough without taking into account other important factors such as age, race, tumour location, cancer grade and clinical treatments.…”

Section: Introductionmentioning

confidence: 99%

“…The American Joint Council on Cancer (AJCC) staging system is currently used for routine prognostic assessment of patients with cervical cancer. 19 Nevertheless, the AJCC staging system is not comprehensive enough without taking into account other important factors such as age, race, tumour location, cancer grade and clinical treatments. Prediction models for cervical cancer prognosis are therefore still urgently needed.…”

Section: Introductionmentioning

confidence: 99%

Establishment of prediction models to predict survival among patients with cervical cancer based on socioeconomic factors: a retrospective cohort study based on the SEER Database

Jia,

Zhou,

et al. 2023

BMJ Open

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ObjectiveTo construct and validate predictive models based on socioeconomic factors for predicting overall survival (OS) in cervical cancer and compare them with the American Joint Council on Cancer (AJCC) staging system.DesignRetrospective cohort study.Setting and participantsWe extracted data from 5954 patients who were diagnosed with cervical cancer between 2007 and 2011 from the Surveillance, Epidemiology, and End Results Database. This database holds data related to cancer incidence from 18 population-based cancer registries in the USA.Outcome measures1-year and 5-year OS.ResultsOf the total 5954 patients, 5820 patients had 1-year mortality and 5460 patients had 5-year mortality. Lower local education level [Hazard ratios (HR): 1.15, 95% confidence interval (CI): 1.04 to 1.27, p= 0.005] and being widowed (HR 1.28, 95% CI 1.06 to 1.55, p=0.009) were associated with a worse OS for patients with cervical cancer. Having insurance (HR 0.75, 95% CI 0.62 to 0.90, p=0.002), earning a local median annual income of ≥US$56 270 (HR 0.83, 95% CI 0.75 to 0.92, p<0.001) and being married (HR 0.79, 95% CI 0.69 to 0.89, p<0.001) were related to better OS in patients with cervical cancer. The predictive models based on socioeconomic factors and the AJCC staging system had a favourable performance for predicting OS in cervical cancer compared with the AJCC staging system alone.ConclusionOur proposed predictive models exhibit superior predictive performance, which may highlight the potential clinical application of incorporating socioeconomic factors in predicting OS in cervical cancer.

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Development and Validation of Novel Nomograms to Predict the Overall Survival and Cancer-Specific Survival of Cervical Cancer Patients With Lymph Node Metastasis

Cited by 5 publications

References 37 publications

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

A nomogram for survival prediction in 275,812 U.S. patients with breast cancer: a population-based cohort study based on the SEER database

Development and validation of a nomogram for predicting pelvic lymph node metastasis and prognosis in patients with cervical cancer

Establishment of prediction models to predict survival among patients with cervical cancer based on socioeconomic factors: a retrospective cohort study based on the SEER Database

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