Prognostic Model for Predicting Overall and Cancer-Specific Survival Among Patients With Cervical Squamous Cell Carcinoma: A SEER Based Study

Li, Zhuolin; Lin, Yao; Cheng, Bizhen; Zhang, Qiaoxin; Cai, Yingmu

doi:10.3389/fonc.2021.651975

Cited by 20 publications

(26 citation statements)

References 85 publications

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“…Finally, nomograms were developed to calculate the probabilities of 1-, 3-, and 5-year OS (based on 13 independent prognostic factors) and CSS (based on 11 independent prognostic factors) in patients with CC. Our nomograms indicated that FIGO stage made the largest contribution to the predicted probability between 1-, 3-, and 5-year OS and CSS, which was consistent with a large body of previous research ( 6 , 9 , 25 ).…”

Section: Discussionsupporting

confidence: 91%

“…At the end of April 2022, there were two main clinical staging schemes: the American Joint Committee on Cancer (AJCC) Staging Seventh Edition and the International Federation of Obstetrics and Gynecology (FIGO) 2009 Guidelines. FIGO staging is mainly based on clinical characteristics, but few studies have considered the impact of non-clinical parameters on its clinical utility and net benefit in patients with CC (6)(7)(8)(9). Clinical staging is mainly based on cervical tumor size or extent of pelvic disease, with less weight given to other important prognostic factors such as age, race, and treatment modality.…”

Section: Introductionmentioning

confidence: 99%

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Nomogram models for the prognosis of cervical cancer: A SEER-based study

Jiang

et al. 2022

Front. Oncol.

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BackgroundCervical cancer (CC) is one of the most common cancers in women. This study aimed to investigate the clinical and non-clinical features that may affect the prognosis of patients with CC and to develop accurate prognostic models with respect to overall survival (OS) and cancer-specific survival (CSS).MethodsWe identified 11,148 patients with CC from the SEER (Surveillance, Epidemiology, and End Results) database from 2010 to 2016. Univariate and multivariate Cox regression models were used to identify potential predictors of patients’ survival outcomes (OS and CSS). We selected meaningful independent parameters and developed nomogram models for 1-, 3-, and 5-year OS and CSS via R tools. Model performance was evaluated by C-index and receiver operating characteristic curve. Furthermore, calibration curves were plotted to compare the predictions of nomograms with observed outcomes, and decision curve analysis (DCA) and clinical impact curves (CICs) were used to evaluate the clinical effectiveness of the nomograms.ResultsAll eligible patients (n=11148) were randomized at a 7:3 ratio into training (n=7803) and validation (n=3345) groups. Ten variables were identified as common independent predictors of OS and CSS: insurance status, grade, histology, chemotherapy, metastasis number, tumor size, regional nodes examined, International Federation of Obstetrics and Gynecology stage, lymph vascular space invasion (LVSI), and radiation. The C-index values for OS (0.831 and 0.824) and CSS (0.844 and 0.841) in the training cohorts and validation cohorts, respectively, indicated excellent discrimination performance of the nomograms. The internal and external calibration plots indicated excellent agreement between nomogram prediction and actual survival, and the DCA and CICs reflected favorable potential clinical effects.ConclusionsWe constructed nomograms that could predict 1-, 3-, and 5-year OS and CSS in patients with CC. These tools showed near-perfect accuracy and clinical utility; thus, they could lead to better patient counseling and personalized and tailored treatment to improve clinical prognosis.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Nomogram models for the prognosis of cervical cancer: A SEER-based study

Jiang

et al. 2022

Front. Oncol.

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“…There were also studies revealed that preoperative elevated serum CEA level was a risk factor for worse survival 8, 25 . Meanwhile, the present study found the prognosis was strongly associated with age, which was con rmed by other studies in patients with C-MAC who underwent surgical treatment 7,26,5,27 . The potential explanation was that elderly patients were often accompanied by dysfunction, malnutrition, and comorbidity, which limited them to receive aggressive treatment.…”

Section: Discussionsupporting

confidence: 89%

Development and validation of a prognostic nomogram for patients with stage II colon mucinous adenocarcinoma

Huang

Zhang

Zhou

et al. 2022

Int J Colorectal Dis

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Mucinous histology is generally considered as a risk factor of prognosis in stage II colon cancer, but there is no appropriate model for prognostic evaluation and treatment decision in patients with stage II colon mucinous adenocarcinoma (C-MAC). MethodsPatients with stage II C-MAC who underwent surgical treatment in the Surveillance, Epidemiology, and End Results Program were enrolled and randomly divided into training cohort (70%) and internal validation cohort (30%). Prognostic predictors which were determined by univariate and multivariate analysis in the training cohort were included in the nomogram. The calibration curves, decision curve analysis, X-tile analysis, and Kaplan-Meier curve of the nomogram were validated in the internal validation cohort. Results 3762 patients of stage II C-MAC were enrolled. The age, pathological T (pT) stage, tumor number, serum carcinoembryonic antigen (CEA), and perineural invasion (PNI) were independent predictors of overall survival (OS), which were used to establish a nomogram. Calibration curves of the nomogram indicated good consistency between nomogram prediction and actual survival for 1-, 3-and 5-year OS. Besides, patients with stage II C-MAC could be divided into high-, middle-and low-risk subgroups by the nomogram. Further subgroup analysis indicated that patients in the high-risk group could have a survival bene t from chemotherapy after surgical treatment. ConclusionsWe established the rst nomogram to accurately predict the survival of stage II C-MAC patients who underwent surgical treatment. In addition, the nomogram identi ed low-, middle-and high-risk subgroups of patients and found chemotherapy might improve survival in the high-risk subgroup of stage II C-MAC patients.

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“…The small sample size (n = 43) could have resulted in a type-II error. For example, known poor prognostic factors for cervical cancer, such as older age and locoregional progression (cT), were not significantly correlated with prognosis in the current study [23]. This may be due to the the small sample size of this study as well as the possibility that the prognostic significance of age and locoregional progression in stage IVB is unclear.…”

Section: Plos Onecontrasting

confidence: 63%

Hypoalbuminemia for the prediction of survival in patients with stage IVB cervical cancer

et al. 2022

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We evaluated the prognostic significance of malnutrition in patients with metastatic cervical cancer. In this study, we retrospectively analyzed the cases of 43 patients with stage IVB (FIGO2018) cervical cancer treated at our institute from December 2004 to December 2017. We determined the correlation between clinicopathological characteristics and survival by performing univariate and multivariate analyses. The serum albumin value at diagnosis was used as an index of malnutrition. The median follow-up period was 16.4 months (range, 0.9–91.4 months). On Kaplan-Meier analysis, the 1- and 2-year overall survival (OS) rates for all patients were 61.6% and 48.6%, respectively. The optimal serum albumin for predicting 1-year survival was 3.3 g/dL, as determined by the receiver operating characteristic curve to maximize the area under the curve. The OS of the patients with albumin >3.3 g/dL (n = 28) was significantly better than that of the patients with albumin ≤3.3 g/dL (n = 15) (p = 0.004). The univariate and multivariate analyses revealed that pretreatment serum albumin and mode of primary treatment were significantly associated with survival in patients with stage IVB cervical cancer. Hypoalbuminemia was an unfavorable prognostic factor for patients with metastatic cervical cancer.

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Prognostic Model for Predicting Overall and Cancer-Specific Survival Among Patients With Cervical Squamous Cell Carcinoma: A SEER Based Study

Cited by 20 publications

References 85 publications

Nomogram models for the prognosis of cervical cancer: A SEER-based study

Nomogram models for the prognosis of cervical cancer: A SEER-based study

Development and validation of a prognostic nomogram for patients with stage II colon mucinous adenocarcinoma

Hypoalbuminemia for the prediction of survival in patients with stage IVB cervical cancer

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