Construction and validation of the prognostic model for patients with neuroendocrine cervical carcinoma: a competing risk nomogram analysis

Causes of death analysis and the prognostic model construction in neuroendocrine carcinoma of the cervix: A SEER-based study

PURPOSE

Neuroendocrine carcinoma of the cervix (NECC) is rare but results in poor prognosis. The causes of death (CODs) in NECC patients are rarely reported. Our study aimed to explore the distributions of death causes of NECC patients compared with squamous cell carcinoma (SCC) and adenocarcinoma (ADC) and to develop a validated survival prediction model.

METHODS

Patients diagnosed with NECC, SCC, or ADC were identified from the Surveillance, Epidemiology, and End Results Program database from 1975 to 2019. We analyzed the standardized mortality ratio (SMR) to determine each cause of death for each survival time category. The Kaplan-Meier method was used for survival analysis. Univariate and multivariate Cox regression analyses were used to establish a nomogram model.

RESULTS

A total of 358 NECC patients were included in this study, and 270 (75.4%) died during the follow-up period. Patients with NECC had 5.55 times (95% CI, 4.53-6.79, p < 0.0001) higher risk of death compared with patients with SCC and 10.38 times (95% CI, 8.28-13.01, p < 0.0001) higher compared with ADC. Cervical cancer is the main cause of death in NECC. As the diagnosis time increased, the risk of death from all causes and cervix cancer gradually decreased. While after at least 10 years of follow-up time, the highest and most dramatical SMR values were observed for metastasis (SMR, 138.81; 95% CI, 37.82-355.40; p < 0.05) and other cancers as the reason for death has an over 7-fold higher SMR (SMR: 7.07; 95% CI: 2.60-15.40, p < 0.05) more than 5 years after the cancer diagnosis. Race, FIGO stage, and surgery were independent risk factors for the overall survival (OS) of NECC patients. For the predictive nomogram, the C-index was 0.711 (95% CI: 0.697-0.725) and was corrected to 0.709 (95% CI: 0.680, 0.737) by bootstrap 1000 resampling validation.

CONCLUSION

Compared with SCC and ADC, NECC patients have an elevated risk of mortality due to cervical cancer and metastasis. We successfully constructed a prognostic nomogram for patients with NECC. Based on refractoriness and high mortality of NECC, targeted treatment strategies and follow-up plans should be further developed according to the risk of death and distribution characteristics of CODs.

Competing risk nomogram and risk classification system for evaluating overall and cancer-specific survival in neuroendocrine carcinoma of the cervix: a population-based retrospective study

OBJECTIVE

Neuroendocrine carcinoma of the cervix (NECC) is a rare malignancy with poor clinical prognosis due to limited therapeutic options. This study aimed to establish a risk-stratification score and nomogram models to predict prognosis in NECC patients.

METHODS

Data on individuals diagnosed with NECC between 2000 and 2019 were retrieved from the Surveillance Epidemiology and End Results (SEER) database and then randomly classified into training and validation cohorts (7:3). Univariate and multivariate Cox regression analyses evaluated independent indicators of prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis further assisted in confirming candidate variables. Based on these factors, cancer-specific survival (CSS) and overall survival (OS) nomograms that predict survival over 1, 3, and 5 years were constructed. The receiver operating characteristic (ROC) curve, the concordance index (C-index), and the calibration curve estimated the precision and discriminability of the competing risk nomogram for both cohorts. Finally, we assessed the clinical value of the nomograms using decision curve analysis (DCA).

RESULTS

Data from 2348 patients were obtained from the SEER database. Age, tumor stage, T stage, N stage, chemotherapy, radiotherapy, and surgery predicted OS. Additionally, histological type was another standalone indicator of CSS prognosis. For predicting CSS, the C-index was 0.751 (95% CI 0.731 ~ 0.770) and 0.740 (95% CI 0.710 ~ 0.770) for the training and validation cohorts, respectively. Furthermore, the C-index in OS prediction was 0.757 (95% CI 0.738 ~ 0.776) and 0.747 (95% CI 0.718 ~ 0.776) for both cohorts. The proposed model had an excellent discriminative ability. Good accuracy and discriminability were also demonstrated using the AUC and calibration curves. Additionally, DCA demonstrated the high clinical potential of the nomograms for CSS and OS prediction. We constructed a corresponding risk classification system using nomogram scores. For the whole cohort, the median CSS times for the low-, moderate-, and high-risk groups were 59.3, 19.5, and 7.4 months, respectively.

CONCLUSION

New competing risk nomograms and a risk classification system were successfully developed to predict the 1-, 3-, and 5-year CSS and OS of NECC patients. The models are internally accurate and reliable and may guide clinicians toward better clinical decisions and the development of personalized treatment plans.

The risk and latency evaluation of secondary primary malignancies of cervical cancer patients who received radiotherapy: A study based on the SEER database

Objectives

To study the risk factors for the onset of secondary primary malignancies (SPM) and the latency between SPM and cervical cancer after radiotherapy.

Methods

We selected patients with cervical cancer who underwent radiotherapy between 2000 and 2019 from the Surveillance, Epidemiology, and End Results (SEER) database. And the data of patients with cervical cancer who underwent radiotherapy in Guangxi Medical University Cancer Hospital during January 1,1997 to December 31,2016 were collected and analyzed. The factors associated with SPM onset and latency were then estimated by nomograms based on logistic regression and a complete risk model. Dynamic risk plots were performed by Poisson regression.

Results

A total of 32,313 cases of cervical cancer who underwent radiotherapy were downloaded from the SEER database; of these, 19,439 cases had a complete dataset and were included in the final analysis. In total, 561 cases suffered from SPM; the remaining 18,878 did not. And a total of 1486 cases of cervical cancer who underwent radiotherapy from Guangxi Medical University Cancer Hospital were analyzed, 27 cases caught SPM and the rest of 1459 cases did not. Patients with SPM were older than those without SPM(p=0.000); significant associations were also identified between SPM and white race(p=0.000), localized stage (p=0.000), squamous carcinoma (SCC)(p=0.003), surgery(p=0.000), and combination radiotherapy (p=0.026). A logistic regression nomogram showed that older age (HR:1.015, 95%CI:1.009-1.021, p=0.000), localized stage (HR:4.056, 95%CI: 2.625-6.269, p=0.000) and regional stage (HR: 3.181, 95%CI:2.094-4.834, p=0.000), white (HR: 1.722, 95%CI:1.145-2.590, p=0.000) and black race (HR: 1.889, 95%CI:1.327-2.689, p=0.000), and the receipt of surgery (HR: 1.381, 95%CI:1.151-1.657, p=0.000) were all independent risk factors for the onset of SPM. The largest proportion of cases involved SPM in the female reproductive system. A dynamic risk plot showed that age, race, stage, and surgery had impacts on the latency of SPM onset. A competing risk regression analysis nomogram showed that age (HR: 1.564, 95%CI: 1.272-1.920, p=0.000), surgery (HR: 1.415, 95%CI: 1.140-1.760, p=0.002), localized stage (HR: 8.035, 95%CI: 4.502-14.340, p=0.000) and regional stage (HR: 4.904, 95%CI: 2.790-8.620, p=0.000), and black race (HR: 1.786, 95%CI: 1.161-2.750, p=0.008) all had significant impacts on the cumulative incidence and latency of SPM.

Conclusions

Advanced age, the receipt of surgery, earlier stages, and white and black race were identified as risk factors for SPM onset and influenced latency in patients with cervical cancer after radiotherapy.