Developing and validating a novel nomogram used a competing-risks model for predicting the prognosis of primary fallopian tube carcinoma: a retrospective study based on the SEER database

Rare non-serous fallopian tube cancers: institutional experience and literature review

INTRODUCTION

We reviewed 63 reports from the literature on rare non-serous tumors of the fallopian tubes and carried out a comparative analysis of clinical manifestations and diagnostic methods. We also report our observations from patients with these tumors.

MATERIALS AND METHODS

Of 157 patients with primary fallopian tube cancer (FTC) treated in our regional oncological hospital between 1970 and 2020, there were nine (6%) cases of rare non-serous cancers, including one case each of choriocarcinoma, carcinosarcoma, and neuroendocrine tumor, and two cases each of non-keratinizing squamous cell carcinoma, mucinous adenocarcinoma, and clear cell adenocarcinoma.

RESULTS

For carcinosarcoma and squamous cell, clear cell, and transitional cell carcinomas, clinical history, patient age, and clinical manifestations were similar to the main group of FTCs. Choriocarcinoma differed significantly from other cancers of the fallopian tubes in terms of patient age and clinical course. Mucinous adenocarcinoma, mesothelioma, and borderline tumors, with rare exceptions, were almost always asymptomatic and were found only incidentally during surgery. Choriocarcinoma and carcinosarcoma had an aggressive course, while squamous cell, transitional cell, clear cell, and mucinous carcinomas were less aggressive. Since most rare non-serous tumors have a similar disease course to typical FTCs and there is a lack of appropriate treatment protocols for rare tumors, treatment options developed for ovarian tumors and FTC are justified for these tumors.

CONCLUSION

Rare non-serous malignant fallopian tube tumors are very similar to serous and endometrioid FTC in terms of clinical manifestations and diagnosis.

Construction and validation of a prognostic nomogram for predicting cancer-specific survival in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy

BACKGROUND

Existing predictive models often focus solely on overall survival (OS), neglecting the bias that other causes of death might introduce into survival rate predictions. To date, there is no strict predictive model established for cancer-specific survival (CSS) in patients with intermediate and advanced colon cancer after receiving surgery and chemotherapy.

METHODS

We extracted the data from the Surveillance, Epidemiology, and End Results (SEER) database on patients with stage-III and -IV colon cancer treated with surgery and chemotherapy between 2010 and 2015. The cancer-specific survival (CSS) was assessed using a competitive risk model, and the associated risk factors were identified via univariate and multivariate analyses. A nomogram predicting 1-, 3-, and 5-year CSS was constructed. The c-index, area under the curve (AUC), and calibration curve were adopted to assess the predictive performance of the model. Additionally, the model was externally validated.

RESULTS

A total of 18 risk factors were identified by univariate and multivariate analyses for constructing the nomogram. The AUC values of the nomogram for the 1-, 3-, and 5-year CSS prediction were 0.831, 0.842, and 0.848 in the training set; 0.842, 0.853, and 0.849 in the internal validation set; and 0.815, 0.823, and 0.839 in the external validation set. The C-index were 0.826 (se: 0.001), 0.836 (se: 0.002) and 0.763 (se: 0.013), respectively. Moreover, the calibration curve showed great calibration.

CONCLUSION

The model we have constructed is of great accuracy and reliability, and can help physicians develop treatment and follow-up strategies that are beneficial to the survival of the patients.

Prognostic analysis of cutaneous Kaposi sarcoma based on a competing risk model

The data regarding the prognosis of cutaneous Kaposi sarcoma (KS) was limited. The current study aimed to explore the risk factors and develop a predictive model for the prognosis of cutaneous KS patients. Data were extracted from Surveillance, Epidemiology, and End Results database from 2000 to 2018 and randomly divided into training and validation cohort. The Kaplan-Meier analysis, cumulative incidence function based on the competing risk model and Fine-Gray multivariable regression model was used to identify the prognostic factors and then construct a 5-, 10-, and 15-year KS-specific death (KSSD) nomogram for patients. The concordance index (C-index), area under the curve (AUC) of operating characteristics and calibration plots were used to evaluate the performance of the model. The clinical utility of the model was measured by decision curve analysis (DCA). In 2257 cutaneous KS patients identified from database, the overall median survival time was about 13 years. Radiotherapy (p = 0.013) and surgery (p < 0.001) could lower the KSSD, while chemotherapy (p = 0.042) and surgery (p < 0.001) could increase the overall survival (OS) of patients with metastatic and localized lesions, respectively. Race, number of lesions, surgery, extent of disease, year of diagnosis and age were identified as risk factors associated with cutaneous KS-specific survival. Performance of the nomogram was validated by calibration and discrimination, with C-index values of 0.709 and AUC for 5-, 10-, and 15-year-KSSD of 0.739, 0.728 and 0.725 respectively. DCA indicated that the nomogram had good net benefits in clinical scenarios. Using a competing-risk model, this study firstly identified the prognostic factors, and constructed a validated nomogram to provide individualized assessment and reliable prognostic prediction for cutaneous KS patients.

Competing risk nomogram for predicting prognosis of patients with spinal and pelvic chordoma: A SEER-based retrospective study

PURPOSE

Recently, competing risk nomograms were widely applied to predict prognosis in numerous tumors other than chordoma. Here, we aimed to construct and validate a competing-risk-based prognostic nomogram to predict 3- and 5-year cancer-specific death (CSD) in patients with spinal and pelvic chordoma.

METHODS

All chordoma patient data were abstracted from the Surveillance, Epidemiology, and End Results (SEER) resource, and a total of 485 chordoma patients were eventually included in this study. Multivariate competing risk model and multivariate Cox model were used to determine independent prognostic factors, respectively, and the results of the two models were compared. Nomogram was employed to visualize the competing risk model. The discrimination, calibration, and clinical utility of this model were evaluated by Harrell concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Ten-fold cross-validation was further utilized to validate the prognostic nomogram.

RESULTS

Significant prognostic factors affecting CSD were age (P = 0.016), localized involvement (P < 0.0001), and radical resection (P < 0.001) in the multivariate competing risk model. C-indexes were 0.799 and 0.76, and AUC were 0.812 and 0.778 for 3- and 5-year CSD. Calibration plots demonstrated the nomogram was well-fitted, and DCA indicated good clinical utility. The nomogram showed good performance in the 10-fold cross-validation.

CONCLUSION

We successfully built the first competing-risk-based nomogram to predict clinical outcomes in patients with spinal and pelvic chordoma. This well-established nomogram hopes to help clinicians with precise prognostic assessment and thus improve clinical outcomes.

Cause-specific mortality rate of ovarian cancer in the presence of competing risks of death: a nationwide population-based cohort study

Objective

This nationwide cohort study aimed to evaluate the cause-specific mortality (probability of death by ovarian cancer, probability of death by other causes) under the competing risks of death in women with ovarian cancer.

Methods

The Korea Central Cancer Registry was searched to identify women with primary ovarian cancer diagnosed between 2006 and 2016. Epithelial ovarian cancer cases were identified using the International Classification of Diseases for Oncology 3rd edition. We estimated the cause-specific mortality according to age (<65 years, ≥65 years), stage (local, regional, and distant), and histology (serous, mucinous, endometrioid, clear cell, and others) under the competing risks framework; moreover, cumulative incidences were estimated.

Results

We included 21,446 cases. Cause-specific mortality continuously increased throughout 10 year follow-up. Compared with women aged <65 years, ovarian cancer-specific mortality (5-year, 28.9% vs. 61.9%; 10-year, 39.0% vs. 68.6%, p<0.001) and other cause mortality (5-year, 1.7% vs. 4.8%; 10-year, 2.8% vs. 8.2%, p<0.001) increased in women aged ≥65 years. This trend was consistent across all the stages and histological types. There was a substantial increase in competing risks from 1.1% in women aged <65 years to 8.0% in women aged ≥65 years in patients with early-stage (p<0.001) non-serous ovarian cancer (p<0.001).

Conclusion

Older age at diagnosis is associated with increasing ovarian cancer-specific mortality and competing risks. Given the substantial effect of competing risks on elderly patients, there is a need for assessment tools to balance the beneficial and harmful effects to provide optimal treatment.

This nationwide cohort study analyzed 21,446 women with primary ovarian cancer to evaluate survival and cause-specific competing mortality. Older age was associated with increasing both ovarian cancer-specific mortality and competing risks. Increased awareness of competing mortality is required for the optimal treatment decisions in the elderly.