Clinical Nomograms for Predicting the Overall Survival and Cancer-specific Survival of patients with Ovarian Carcinosarcoma patients after Primary Surgery

Ren, Fang; Wang, Shengtan; Li, Feifei; Gao, Jian; Xu, Haoya; Li, Xianli; Zhu, Liping

doi:10.7150/jca.63224

Cited by 3 publications

(5 citation statements)

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“…The rapid decline in mortality among men may be due in part to reduction in smoking ( 29 ). Thus, while medical advances have slowed the trend of rising mortality, targeted cancer control treatments remain urgent ( 11 , 25 , 27 , 28 , 30 ). Consistent with the overall rising incidence and slowing death trend, the prevalence of carcinosarcoma has increased year-by-year, mainly in women, elderly, blacks, and localized stage.…”

Section: Discussionmentioning

confidence: 99%

“…The total score was calculated using the quantitative score of each factor, and the 1-, 3-, and 5-year survival rate were scientifically and accurately predicted. Due to the inclusion of the primary tumor site, the predictive model is applicable to a wider population of patients and has a better predictive probability than other single-site predictive models ( 11 , 30 ). In summary, this simple but effective model could be used to individualize prognostic assessment of carcinosarcoma and will facilitate clinical decision-making.…”

Section: Discussionmentioning

confidence: 99%

“…Most studies on carcinosarcoma focused on gynecological carcinosarcoma and suggested that the incidence of carcinosarcoma gradually increased in recent years ( 5 , 10 ). The vast majority of studies are case reports or small population-based studies for a single disease site ( 11 – 14 ). Previous researches on single pathological types indicated that primary tumor site could affect prognosis ( 15 – 17 ).…”

Section: Introductionmentioning

confidence: 99%

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Epidemiology and prediction model of patients with carcinosarcoma in the United States

Chen

Yang³

et al. 2022

Front. Public Health

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BackgroundCarcinosarcoma is a rare biphasic tumor composed of both carcinoma and sarcoma elements, which occurs at various sites. Most studies are case reports or small population-based studies for a single disease site, so comprehensive evaluations of epidemiology and prognostic factors for carcinosarcoma are needed.MethodsSurveillance, Epidemiology, and End Results (SEER)-8 (1975–2019) provided data for the epidemiological analysis. SEER-17 (2000–2019) provided data on the primary tumor sites, initial treatment, construction, and validation of the nomogram.ResultsThe age-adjusted incidence per 100,000 persons of carcinosarcoma increased significantly from 0.46 to 0.91 [1975–2019; average annual percent change (AAPC): 1.3%, P = 0.006], with localized stage increasing from 0.14 to 0.26 [2005–2015; annual percent change (APC): 4.2%]. The 20-year limited-duration prevalence per 100,000 increased from 0.47 to 3.36 (1999–2018). The mortality per 100,000 increased significantly from 0.16 to 0.51 (1975–2019; AAPC: 1.9%, P < 0.001). The 5-year relative survival was 32.8%. The greatest number of carcinosarcomas were from the uterus (68.7%), ovary (17.8%), lung and bronchus (2.3%). The main treatment is comprehensive treatment based on surgery; however, surgery alone is preferred in older patients. In multivariate analysis (N = 11,424), age, sex, race, year of diagnosis, disease stage, tumor site, and treatment were associated with survival. A nomogram was established to predict 1-, 3-, and 5-year survival, and the C-indexes were 0.732 and 0.748 for the training and testing sets, respectively. The receiver operating characteristic curve demonstrated that the nomogram provided a comprehensive and accurate prediction [1-year area under the curve (AUC): 0.782 vs. 0.796; 3-year AUC: 0.771 vs. 0.798; 5-year AUC: 0.777 vs. 0.810].ConclusionsIn this study, the incidence, prevalence, and mortality of carcinosarcoma have increased over the past decades. There was a rapid rise in the incidence of localized stage in recent years, which reflected improved early detection. The prognosis of carcinosarcoma remains poor, signifying the urgency of exploring targeted cancer control treatments. Explicating distribution and gender disparities of carcinosarcoma may facilitate disease screening and medical surveillance. The nomogram demonstrated good predictive capacity and facilitated clinical decision-making.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Epidemiology and prediction model of patients with carcinosarcoma in the United States

Chen

Yang³

et al. 2022

Front. Public Health

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“…Factors associated with an increased risk of EC include mainly age, obesity, family history and tumor stage [6]. More previous studies have suggested that age is an important factor associated with overall survival, but the importance of age in assessing the prognosis of patients with EC remains controversial [7]. It has been suggested that EC patients under 45 years of age tend to have a lower incidence of advanced disease, a higher degree of tumor differentiation and a better prognosis [8].…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a nomogram for predicting overall survival in patients with early-onset endometrial cancer

Zhang

et al. 2023

Preprint

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Background The aim of this study was to investigate the differences in the clinicopathological characteristics of younger and older endometrial cancer (EC)patients, and further assess the prognosis of early-onset EC in terms of overall survival by developing a nomogram. Methods Patients with EC diagnosed from surveillance, epidemiology and end results (SEER) between 2004 and 2015 were selected. Clinicopathological characteristics were compared between younger and older patients, and survival analysis was performed in both groups. Prognostic factors affecting overall survival in young EC patients were identified by Cox regression, a nomogram was created and internal validation was performed by consistency index, decision curve analysis, receiver operating characteristic curves and calibration curves. Data from 70 early-onset EC patients for external validation. Finally, Kaplan-Meier curves were plotted to compare survival outcomes across risk subgroups. Results A total of 5037 young patients and 60612 older patients were included in this study. Younger patients were divided into a training cohort (3526) and a validation cohort (1511) in a 7:3 ratio. Cox analysis yielded age, marital status, race, SEER stage and T stage as independent risk factors for overall survival, and a nomogram was constructed based on these factors. Internal and external validation demonstrated the good predictive power of the nomogram. In particular, the C-index for the overall survival nomogram was 0.839 [95% confidence interval (0.814–0.864)] in the training cohort and 0.826 (0.785–0.867) in the internal validation cohort. The differences in Kaplan-Meier curves between the different risk subgroups were statistically significant. Conclusions In this study, the nomogram predicting overall survival of early-onset endometrial cancer patients based on the SEER database was developed to help assess the prognosis of patients and guide clinical treatment.

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“…Factors associated with an increased risk of EC include age, obesity, family history, and tumor stage [ 6 ]. Previous studies have suggested age as an important factor associated with overall survival, the importance of age in assessing the prognosis of patients with EC remains controversial [ 7 ]. It has been suggested that patients with EC under 45 years of age tend to have a lower incidence of advanced disease, a higher degree of tumor differentiation, and better prognosis [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Development and validation of a nomogram for predicting overall survival in patients with early-onset endometrial cancer

Zhang,

Li,

Zhang

et al. 2023

BMC Cancer

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Background This study aimed to investigate the differences in the clinicopathological characteristics of younger and older patients with endometrial cancer (EC) and develop a nomogram to assess the prognosis of early onset EC in terms of overall survival. Methods Patients diagnosed with EC from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015 were selected. Clinicopathological characteristics were compared between younger and older patients, and survival analysis was performed for both groups. Prognostic factors affecting overall survival in young patients with EC were identified using Cox regression. A nomogram was created and internal validation was performed using the consistency index, decision curve analysis, receiver operating characteristic curves, and calibration curves. External validation used data from 70 patients with early onset EC. Finally, Kaplan-Meier curves were plotted to compare survival outcomes across the risk subgroups. Results A total of 1042 young patients and 12,991 older patients were included in this study. Younger patients were divided into training (732) and validation (310) cohorts in a 7:3 ratio. Cox regression analysis identified age, tumorsize, grade, FIGO stage(International Federation of Gynecology and Obstetrics) and surgery as independent risk factors for overall survival, and a nomogram was constructed based on these factors. Internal and external validations demonstrated the good predictive power of the nomogram. In particular, the C-index for the overall survival nomogram was 0.832 [95% confidence interval (0.797–0.844)] in the training cohort and 0.839 (0.810–0.868) in the internal validation cohort. The differences in the Kaplan-Meier curves between the different risk subgroups were statistically significant. Conclusions In this study, a nomogram for predicting overall survival of patients with early onset endometrial cancer based on the SEER database was developed to help assess the prognosis of patients and guide clinical treatment.

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Clinical Nomograms for Predicting the Overall Survival and Cancer-specific Survival of patients with Ovarian Carcinosarcoma patients after Primary Surgery

Cited by 3 publications

References 24 publications

Epidemiology and prediction model of patients with carcinosarcoma in the United States

Epidemiology and prediction model of patients with carcinosarcoma in the United States

Development and validation of a nomogram for predicting overall survival in patients with early-onset endometrial cancer

Development and validation of a nomogram for predicting overall survival in patients with early-onset endometrial cancer

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