A Prognostic Nomogram for Cervical Cancer after Surgery from SEER Database

Wang, Ce; Yang, Chunyan; Wang, Wenjie; Xia, Bairong; Li, Kang; Sun, Fengyu; Hou, Yan

doi:10.7150/jca.26220

Cited by 74 publications

(82 citation statements)

References 25 publications

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“…However, other studies have reported inconsistent results. Wu et al [ 22 ] and Wang et al [ 23 ] reported an equivalent survival for patients with ADC and patients with SCC. In a retrospective competing-risks regression analysis of 2,108 patients with cervical cancer, Intaraphet et al [ 12 ] observed an association of ADC with poorer survival compared with SCC in advanced stages, while no difference was observed at early stages.…”

Section: Discussionmentioning

confidence: 99%

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

et al. 2020

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Objective To compare survival outcomes between cervical adenocarcinoma (ADC) and squamous cell carcinoma (SCC) using a propensity score matching (PSM) analysis based on the Surveillance, Epidemiology, and End Results (SEER) Program. Methods Patients diagnosed with cervical cancer between 1998 and 2016 were identified from the SEER database. The Kaplan-Meier method and Cox regression analysis were used to analyze survival. A subgroup analysis of overall survival (OS) between patients with ADC and SCC was performed after the 1:1 PSM analysis. Results Of the 33,148 patients, 24,591 (79.19%) had SCC and 8,557 (25.81%) had ADC. In the unmatched cohort, after adjustment in multivariate analysis, patients with ADC had a worse prognosis than patients with SCC (hazard ratio [HR]=1.12; 95% confidence interval [CI]=1.07–1.18; p<0.001). In the propensity matched cohort, Kaplan-Meier analysis and subgroup analysis showed that ADC was associated with a worse prognosis than SCC (p=0.001). An analysis stratified by SEER stage revealed a worse prognosis for patients with ADC patients presenting with a regional disease than patients with SCC (HR=1.24; 95% CI=1.14–1.36 p<0.001), but no statistically significant differences were observed between the localized disease (HR=0.97; 95% CI=0.86–1.10; p=0.664) and distant disease (HR=1.09; 95% CI=0.97–1.22; p=0.162) subgroups. Conclusion The significant differences in survival outcomes between patients with cervical ADC and SCC were only observed in the regional disease subgroup, but not in the localized disease and distant disease subgroups.

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Section: Discussionmentioning

confidence: 99%

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

et al. 2020

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“…For a more accurate prognostic prediction, nomograms have been developed, and these nomograms show better performance than conventional staging systems in some cancers [51, 52]. In this study, we identified ARL3 as a prognostic marker for glioma, and constructed a nomogram and risk classification system.…”

Section: Discussionmentioning

confidence: 99%

ARL3 is downregulated and acts as a prognostic biomarker in glioma

et al. 2019

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Background Glioma is the most common primary malignant brain tumor in adults with a poor prognosis. ARL3 is a member of the ARF family, and plays a key role in ciliary function and lipid-modified protein trafficking. ARL3 has been reported to be involved in ciliary diseases, in which it affects kidney and photoreceptor development. However, the functional role of ARL3 in cancer remains unknown. In this study, we aimed to explore ARL3 expression and its roles in glioma prognosis. Methods RT-PCR and immunohistochemistry were performed to examine the expression level of ARL3 in glioma samples. Data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and Repository for Molecular Brain Neoplasia Data (REMBRANDT) databases were employed to investigate ARL3 expression and its roles in glioma prognosis. A nomogram for predicting 3- or 5-year survival was established using Cox proportional hazards regression. Finally, gene ontology (GO) analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were performed to explore the biological function. Results ARL3 expression was downregulated in glioma, and associated with poor prognosis in glioma patients. The C-indexes, areas under the ROC curve and calibration plots of the nomogram indicated an effective predictive performance for glioma patients. In addition, GO and pathway analyses suggested the involvement of ARL3 in angiogenesis and immune cell infiltration in the microenvironment. Conclusions Low ARL3 expression predicted poor prognosis and contributed to antiangiogenesis and the proportion of infiltrating immune cells in the GBM microenvironment. Thus, ARL3 may be a prognostic marker and therapeutic target for glioma. Electronic supplementary material The online version of this article (10.1186/s12967-019-1914-3) contains supplementary material, which is available to authorized users.

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“…a total of 4432 small-cell lung cancer patients were included in the study. We randomly divided these patient data into a training cohort of 1776 (40.07%) and a validation group of 2656 (59.93%) [6][7][8] with the createDataPartition function in R caret package.…”

Section: Data Sourcesmentioning

confidence: 99%

A nomogram model assessing prognostic factors in patients with chemo/radiotherapy of small-cell lung cancer

Tan¹,

Huang²,

Kong³

et al. 2020

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Background: Small-cell lung cancer (SCLC) is difficult to cure. In this study, the SEER database was used to construct a nomogram model and explore the potential prognostic factors of SCLC patients who treated with chemo/radiotherapy. Methods: The data were sorted out and randomly divided into training cohort and verification cohort. Univariate and multivariate Cox regression were used in the training cohort to analyze the independent prognostic factors, then they be incorporated into the Nomogram model. Using the C-index, calibration algorithm and ROC in conjunction with the risk scores, the model was verified with the verification cohort. Finally, the overall survivals of those factors were evaluated in the total cases.Results: In the training cohort, we found that age, race, sex, total stage and extension were independent factors which were included in the nomogram model. C-index(s) that obtained from the training and verification cohorts showed that the model has predictive power. Moreover, the calibration curves and AUC results proved that the model is of great consistency not only in the training cohort but also in the verification cohort. Finally, significant differences in survival were observed among the above-mentioned factors and the overall survivals decreased over time.Conclusions: Age, race, sex, total stage and extension degree are independent factors for overall survival of patients. The nomogram model can better predict the 1-year, 3-year and 5-year survival probabilities, providing accurate reference for clinical individualized treatment.

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A Prognostic Nomogram for Cervical Cancer after Surgery from SEER Database

Cited by 74 publications

References 25 publications

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

Does adenocarcinoma have a worse prognosis than squamous cell carcinoma in patients with cervical cancer? A real-world study with a propensity score matching analysis

ARL3 is downregulated and acts as a prognostic biomarker in glioma

A nomogram model assessing prognostic factors in patients with chemo/radiotherapy of small-cell lung cancer

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