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Competing risk nomogram predicting cancer-specific mortality for endometrial cancer patients treated with hysterectomy.

ABSTRACT:

Background

The incidence of endometrial cancer has tended to increase in recent years. However, competing risk nomogram combining comprehensive factors for endometrial cancer patients treated with hysterectomy is still scarce. Therefore, we aimed to build a competing risk nomogram predicting cancer-specific mortality for endometrial cancer patients treated with hysterectomy.

Methods

Patients diagnosed with endometrial cancer between 2010 and 2012 were abstracted from the Surveillance, Epidemiology, and End Results (SEER) database. Competing risk model was performed to select prognostic variables to build the competing risk nomogram to predict the cumulative 3- and 5-year incidences of endometrial cancer-specific mortality. Harrell's C-index, receiver operating characteristic (ROC) curve, and calibration plot were used in the internal validation. And decision curve analysis was applied to evaluate clinical utility.

Results

A total of 10,447 patients were selected for analysis. The competing risk nomogram identified eight prognostic variables, including age at diagnosis, race, marital status at diagnosis, grade, histology, tumor size, FIGO stage, and number of regional nodes positive. The C-index of the competing risk nomogram was 0.857 (95% confidence interval [CI]: 0.854-0.859), and the calibration plots were adequately fitted. When the threshold probabilities were between 1% and 57% for 3-year prediction and between 2% and 67% for 5-year prediction, the competing risk nomogram was of good clinical utility.

Conclusions

A competing risk nomogram for endometrial cancer patients treated with hysterectomy was successfully built and internally validated. It was an accurately predicted and clinical useful tool, which could play an important role in consulting and health care management of endometrial cancer patients.

SUBMITTER: Xie G

PROVIDER: S-EPMC8124128 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundComprehensive investigations of the prognosis factors and treatment strategies with adjustment of competing causes of death for patients with malignant meningioma (MM) is still lacking.Patient and methodThe surveillance, Epidemiology, and End Results (SEER) database were used to include adult patients with this rare disease between 2004 and 2018. The probability of MM-caused mortality (MMCM) and non-MM-caused mortality (non-MMCM) were presented by cumulative incidence function curves. Then, the association between variates with non-MMCM was evaluated by the cox proportional hazard model, and the prognostic factors of MMCM were identified by Fine-Gray competing risk regression model. Furthermore, a nomogram was developed to predict the 1-year, 2-year, and 5-year MMCM and the performance was tested by a time-dependent area under the receiver operating characteristic (ROC) curve and calibration.Result577 patients were included, with a median age of 62 (18-100) years old and a median overall survival time of 36 (0-176) months. The percentage of non-MMCM was 15.4% (n = 89) in the entire population and 21.7% (n = 54) in elderly patients. The multivariable Cox proportional hazard regression model revealed that older age and other tumor(s) before or after MM had an independently significant association with higher non-MMCM. After adjustment of competing causes of death, the multivariable Fine-gray regression model identified age group ≥ 65 year, tumor size > 5.3 cm, recurrent MM, and histologic type 9530/3 (Meningioma, malignant) had an independently significant association with higher MMCM. Compared with gross total (GTR) of tumor, subtotal resection of tumor (HR 1.66, 95%CI 1.08-2.56, P = 0.02), partial resection of lobe (HR 2.26, 95%CI 1.32-3.87, P = 0.003), and gross total resection of lobe (HR 1.69, 95%CI 1.12-2.51, P = 0.01) had an independently significant association with higher MMCM.ConclusionThe competing risk nomogram including age group, tumor size, initial status, histologic type, and extent of resection is discriminative and clinically useful. This study emphasized the importance of the GTR of tumor in the treatment of MM patients, which had a significantly lower incidence of MMCM compared with biopsy, STR of tumor, partial resection of lobe, and GTR of lobe.