A Novel Tool to Predict Early Death in Uterine Sarcoma Patients: A Surveillance, Epidemiology, and End Results-Based Study

Survival nomograms for vulvar squamous cell carcinoma based on the SEER database and a Chinese external validation cohort

OBJECTIVE

The aim of study was to construct a nomogram to effectively predict the overall survival (OS) and cancer-specific survival (CSS) for patients with vulvar squamous cell carcinoma (VSCC).

METHODS

The training cohort consisted of 5405 patients with VSCC, extracted from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. Eighty-four patients with VSCC were selected from the disease database of the Shengjing Hospital of China Medical University from 2014 to 2020, and enrolled as the external validation cohort. Significant independent prognostic factors were identified using Cox regression analysis and used to develop nomograms to predict 1-, 3-, and 5-year OS and CSS in patients with VSCC.

RESULTS

The nomogram predicting OS was developed based on tumor size, histological grade, International Federation of Gynecology and Obstetrics (FIGO) stage, regional lymph node involvement, distant metastases, surgery, chemotherapy, age, and race. The nomogram for CSS was constructed using the similar factors, excluding race but including marital status. The nomogram for 1-, 3-, and 5-year OS demonstrated robust performance with receiver operating characteristic curves (AUCs) exceeding 80% (0.86, 0.84, and 0.82), outperforming the FIGO staging alone (0.77, 0.75, and 0.72). Similarly, for CSS, our nomograms achieved larger AUCs of 0.89, 0.88, and 0.86 compared with FIGO staging alone (0.81, 0.79, and 0.78).

CONCLUSION

The nomograms more accurately predict prognosis than simple FIGO staging. Moreover, the nomograms developed in this study provide a convenient, operable, and reliable tool for individual assessment and clinical decision-making for patients with VSCC.

Prognostic factors and predictive nomogram models for early death in elderly patients with hepatocellular carcinoma: a population-based study

Background: Owing to an aging society, there has been an observed increase in the average age of patients diagnosed with hepatocellular carcinoma (HCC). Consequently, this study is centered on identifying the prognostic factors linked with early death among this elderly demographic diagnosed with HCC. Additionally, our focus extends to developing nomograms capable of predicting such outcomes. Methods: The Surveillance, Epidemiology and End Results (SEER) database underpinned this study, showcasing participants aged 75 and above diagnosed with HCC within the timeframe from 2010 to 2015. These participants were divided randomly, at a 7:3 ratio, into training and validation cohorts. Univariable and multivariable logistic regressions were applied to the training cohort in the identification of prognostic indicators of early death, forming the basis for nomogram development. To measure the efficacy of these nomograms within both cohorts, we resorted to Receiver Operating Characteristic (ROC) curves, along with GiViTI calibration belt and Decision Curve Analysis (DCA). Results: The study involved 1,163 elderly individuals diagnosed with HCC, having reported instances of 397 all-cause early deaths and 356 HCC-specific early deaths. The sample group was divided into two cohorts: a training group consisting of 815 individuals, and a validation cohort, comprised of 348 individuals. Multifactorial analysis identified grade, T-stage, surgery, radiation, chemotherapy, bone and lung metastasis as significant predictors of mortality from all causes. Meanwhile, race, grade, T-stage, surgery, radiation, chemotherapy, and bone metastasis were revealed to be estimative factors for cancer-specific mortality. Subsequently, these factors were used to develop nomograms for prediction. GiViTI calibration belt corroborated the acceptable coherence of the nomograms, DCA confirmed their valuable clinical applicability, and ROC curves evidenced satisfactory discriminative capacity within both training and validation cohorts. Conclusion: The nomograms utilized in this study proved instrumental in detecting early death among elderly individuals afflicted with HCC. This tool could potentially assist physicians in formulating individualized treatment strategies.

Risk factors of early mortality in patients with small cell lung cancer: a retrospective study in the SEER database

BACKGROUND

Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine cancer with a high risk of early mortality (i.e., survival time less than 1 month). This study aimed to identify relevant risk factors and predict early mortality in SCLC patients.

METHODS

A total of 27,163 SCLC cases registered between 2010 and 2019 were extracted from the Surveillance, Epidemiology, and End Results (SEER) data. Significant independent risk factors were identified by univariate and multivariate logistic regression analyses. Nomograms for all-causes and cancer-specific early death were constructed and evaluated.

RESULTS

Age, sex, clinical stage, presence of metastasis (liver and lung), and absence of treatment (surgery, radiotherapy and chemotherapy) were identified for significant association with all-causes and cancer-specific early death. Nomograms based on these predictors exhibited high accuracy (area under ROC curve > 0.850) and potential clinical practicality in the prediction of early mortality.

CONCLUSION

We identified a set of factors associated with early mortality from SCLC and developed a clinically useful nomogram to predict high-risk patients. This nomogram could aid oncologists in the administration of individualized treatment regimens, potentially improving clinical outcomes of SCLC patients.

Fertility-Sparing Management May Be Considered in Young Women with Uterine Sarcoma

Uterine sarcomas occur very rarely in young women. Hysterectomy, which is a standard treatment, may not be acceptable for those patients, especially nulliparous women. Fertility-sparing management may be an alternative. The aim of the study was to assess fertility-sparing management in patients with uterine sarcoma. Eleven patients were eligible for the study. Histopathologic types of the tumor included: adenosarcoma (n = 3), low-grade endometrial stromal sarcoma (n = 3), low-grade myofibroblastic sarcoma (n = 1), leiomyosarcoma (n = 1), leiomyosarcoma myxoides (n = 1), rhabdomyosarcoma (n = 1), high grade endometrial stromal sarcoma (n = 1). The mean age of the patients at the time of diagnosis was 27.4 years (range: 17–35) and the average follow-up 61 months (range: 12–158). Six patients received adjuvant treatment: megestrol (n = 5) and chemotherapy (n = 1). Recurrence was diagnosed in five cases. Median time to recurrence was 35 months (range: 8–90). Three patients conceived spontaneously following treatment and gave at least one live birth. In total, five full-term pregnancies were recorded and five healthy children were born. Fertility-sparing management may be considered in some patients with uterine sarcoma; however, it may not be appropriate in high-grade endometrial stromal sarcoma. Patients with adenosarcoma may have a low chance of childbearing.

Risk factors and predictive nomograms for early death of patients with advanced hepatocellular carcinoma: a large retrospective study based on the SEER database

BACKGROUND

Hepatocellular carcinoma (HCC) is a kind of tumor with high invasiveness, and patients with advanced HCC have a higher risk of early death. The aim of the present study was to identify the risk factors of early death in patients with advanced HCC and establish predictive nomograms.

METHODS

Death that occurred within 3 months of initial diagnosis is defined as early death. Patients diagnosed with stage IV HCC between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results database for model establishment and verification. Univariable and multivariable logistic regression analyses were used to identify the risk factors. Predictive nomograms were constructed and an internal validation was performed. Decision curve analysis (DCA) was used to verify the true clinical application value of the models.

RESULTS

Of 6603 patients (57% age > 60, 81% male, 70% white, 46% married), 21% and 79% had stage IVA and IVB, respectively. On the multivariable analyses, risk factors for early deaths in patients with stage IVA were age, tumor size, histological grade, alpha-fetoprotein (AFP), fibrosis score, tumor stage (T stage), surgery, radiotherapy, and chemotherapy, and that in stage IVB were age, histological grade, AFP, T stage, node stage (N stage), bone metastasis, lung metastasis, surgery, radiotherapy, and chemotherapy. The areas under the curves (AUCs) were 0.830 (95% CI 0.809-0.851) and 0.789 (95% CI 0.768-0.810) in stage IVA and IVB, respectively. Nomograms comprising risk factors with the concordance indexes (C-indexes) were 0.820 (95% CI 0.799-0.841) in stage IVA and 0.785 (95% CI 0.764-0.0.806) in stage IVB for internal validation (Bootstrapping, 1000re-samplings). The calibration plots of the nomograms show that the predicted early death was consistent with the actual value. The results of the DCA analysis show that the nomograms had a good clinical application.

CONCLUSION

The nomograms can be beneficial for clinicians in identifying the risk factors for early death of patients with advanced HCC and predicting the probability of early death, so as to allow for individualized treatment plans to be accurately selected.

Nomogram for predicting postoperative cancer-specific early death in patients with epithelial ovarian cancer based on the SEER database: a large cohort study

Purpose

Ovarian cancer is a common gynecological malignant tumor. Poor prognosis is strongly associated with early death, but there is no effective tool to predict this. This study aimed to construct a nomogram for predicting cancer-specific early death in patients with ovarian cancer.

Methods

We used data from the Surveillance, Epidemiology, and End Results database of patients with ovarian cancer registered from 1988 to 2016. Important independent prognostic factors were determined by univariate and multivariate logistic regression and LASSO Cox regression. Several risk factors were considered in constructing the nomogram. Nomogram discrimination and calibration were evaluated using C-index, internal validation, and receiver operating characteristic (ROC) curves.

Results

A total of 4769 patients were included. Patients were assigned to the training set (n = 3340; 70%) and validation set (n = 1429; 30%). Based on the training set, eight variables were shown to be significant factors for early death and were incorporated in the nomogram: American Joint Committee on Cancer (AJCC) stage, residual lesion size, chemotherapy, serum CA125 level, tumor size, number of lymph nodes examined, surgery of primary site, and age. The concordance indices and ROC curves showed that the nomogram had better predictive ability than the AJCC staging system and good clinical practicability. Internal validation based on validation set showed good consistency between predicted and observed values for early death.

Conclusion

Compared with predictions made based on AJCC stage or residual lesion size, the nomogram could provide more robust predictions for early death in patients with ovarian cancer.

The incidence, risk factors and predictive nomograms for early death of lung cancer with synchronous brain metastasis: a retrospective study in the SEER database

BACKGROUND

The prognosis of lung cancer with synchronous brain metastasis (LCBM) is very poor, and patients often die within a short time. However, little is known about the early mortality and related factors in patients with LCBM.

METHODS

Patients diagnosed with LCBM between 2010 and 2016 were enrolled from the Surveillance, Epidemiology, and End Result (SEER) database. Univariate and multivariate logistic regression analysis were used to identify significant independent prognostic factors, which were used to construct nomograms of overall and cancer-specific early death. Then, the prediction ability of the model was verified by receiver operating characteristic (ROC) curve. At last, the clinical application value of the model was tested through decision curve analysis (DCA).

RESULTS

A total of 29,902 patients with LCBM were enrolled in this study. Among them, 13,275 (44.4%) patients had early death, and 11,425 (38.2%) cases died of lung cancer. The significant independent risk factors for overall and cancer-specific early death included age, race, gender, Gleason grade, histological type, T stage, N stage, bone metastasis, liver metastasis and marital status, which were used to construct the nomogram. The ROC curve demonstrated good predictive ability and clinical application value. The areas under the curve (AUC) of the training group was 0.793 (95% CI: 0.788-0.799) and 0.794 (95% CI: 0.788-0.799), in the model of overall and cancer-specific early death respectively. And the AUC of the validation group were 0.803 (95% CI: 0.788-0.818) and 0.806 (95% CI: 0.791-0.821), respectively. The calibration plots of the model showed that the predicted early death is consistent with the actual value. The DCA analysis indicated a good clinical application value of this model.

CONCLUSIONS

We established a comprehensive nomogram to predict early death in lung cancer patients with synchronous brain metastases. Nomograms may help oncologists develop better treatment strategies, such as clinical trials and hospice care.

Gynecological sarcomas: literature review of 2020

PURPOSE OF REVIEW

This article, focus on recently published data of the last 18 months on the management of gynecologic sarcomas.

RECENT FINDINGS

Different tools have been studied to identify the differences between benign from malignant uterine conjonctive tumor.Molecular biology impact more and more on the diagnosis of uterine sarcoma with new definitions of very specific groups. This will make it possible to better define the last group of endometrial sarcoma which has been defined as undifferentiated.In several articles, surgical approaches and fertility-sparing surgery were described including the role of surgery for recurrences.Some other articles have evaluated the potential benefice of adjuvant therapy for uterine sarcoma with early stages.Several new targeted therapies are in development. Notably deoxyribonucleic acid repair machinery in uterine leiomyosarcoma and also immune therapies, transforming growth factor beta pathway, mechanistic target of rapamycin inhibitor, anti angiogenics, etc.

SUMMARY

This last year the potential interest for uterine sarcoma increased, demonstrated by the increasing number of publications in the literature compared to previous years. Despite this greater interest over time, the standard of care for uterine sarcoma does not change and we are always waiting for new innovative therapies able to change routine practice and survival of patients. Currently, the result of different clinical trials, which include new options as targeted molecular approach or immune checkpoint inhibitors are closed to be reported.

A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer

Background: Ovarian cancer is a common gynecological malignancy, most of which is epithelial ovarian cancer (EOC). Advanced EOC is linked with a higher incidence of premature death. To date, no effective prognostic tools are available to evaluate the possibility of early death in patients with advanced EOC.

Methods: Advanced (FIGO stage III and IV) EOC patients who were enrolled in the Surveillance, Epidemiology, and End Results database between 2004 and 2015 were regarded as subjects and studied. We aimed to construct a nomogram that can deliver early death prognosis in patients with advanced EOC by identifying crucial independent factors using univariate and multivariate logistic regression analyses to help deliver accurate prognoses.

Results: In total, 13,403 patients with advanced EOC were included in this study. Three hundred ninety-seven out of a total of 9,379 FIGO stage III patients died early. There were 4,024 patients with FIGO stage IV, 414 of whom died early. Nomograms based on independent prognostic factors have the satisfactory predictive capability and clinical pragmatism. The internal validation feature of the nomogram demonstrated a high level of accuracy of the predicted death.

Conclusions: By analyzing data from a large cohort, a clinically convenient nomogram was established to predict premature death in advanced EOC. This tool can aid clinicians in screening patients who are at higher risk for tailoring treatment plans.