Establishment and verification of the first prognostic nomograms in locally advanced thyroid cancer based on the analysis of clinical and follow-up information on 2396 patients

Background and objectives

The purpose of this research was to develop and validate the first prognostic nomograms for 3-, 5-, and 10-year cancer-specific survival (CSS) and overall survival (OS) in patients diagnosed with locally advanced thyroid cancer (LATC) by evaluating independent predictors of prognosis in a population of LATC patients.

Methods

Demographics, clinicopathologic characteristics, treatment, and follow-up of 2396 LATC patients in the surveillance, epidemiology, and end results database from 2004 to 2015 were retrospectively analyzed and compared with patients with LATC according to staging. We randomized all LATC patients into training and validation groups in a 7:3 ratio. Cox regression analyses helped us to derive independent prognostic factors for LATC patients. According to these results, we established and validated the first prognostic nomograms and risk stratification.

Results

In our research, the clinical information of LATC patients was compared and significant differences were found in the relevant variables including CSS and OS (P < 0.05), with CSS of 82.0 % and 49.0 %, and OS of 70.6 % and 40.0 %, respectively. Cox regression analyses showed that age at diagnosis, tumor diameter, presence of DM, extrathyroidal extension sites, histological type, thyroidectomy scope, radiotherapy status, and chronological sequence of radiotherapy and surgery were observably correlated with CSS in LATC patients, and in addition to the above factors, gender, marital status, and chemotherapy status were also observably correlated with OS in LATC patients. The prognostic predictive power of the above factors is visualized by the Kaplan-Meier survival curve. The concordance index of nomograms for CSS and OS were 0.933, 0.925, and 0.926 (CSS), 0.918, 0.909, and 0.906 (OS), respectively, and the time-dependent receiver operating characteristic curve, area under curve, calibration curve and decision curve analysis curve indicate that the nomograms have good discriminatory ability, accuracy and clinical applicability in both the training and validation groups.

Conclusions

In these findings, we drawed a conclusion that there were significant differences in clinical information between patients with T4a and T4b LATC, and we established and validated the first prognostic nomograms and risk stratification of CSS and OS for LATC patients at 3, 5, and 10 years, which will help clinicians to individualize their postoperative treatment and individualized follow-up.

The novel prognostic nomograms for predicting cancer-specific survival and overall survival in mixed medullary and follicular cell carcinoma: A SEER-based study

BACKGROUND

The aim of this study was to evaluate independent predictors of prognosis in patients with mixed medullary and follicular cell carcinoma (MMFCC) and to establish the novel prognostic nomograms in the academic community for 3-, 5-, and 10 year CSS and OS in patients with MMFCC.

METHODS

Demographic information, clinicopathological characteristics, treatment information, and survival status information of 200 patients with MMFCC and 6615 patients with medullary thyroid carcinoma (MTC) from 2000 to 2020 in the SEER database were retrospectively analyzed. Independent predictors of prognosis in MMFCC patients were derived using univariate and multivariate Cox regression analyses after relevant comparisons based on pathologic typing. On this basis, we developed and validated clinical prognostic nomograms and risk-stratified the patient population.

RESULTS

In this study, the clinical information of 200 patients with MMFCC was compared with that of 5947 patients with MTC (NOS) and 668 patients with MTC with amyloid stroma, and there was a significant difference in the relevant variables among the three, with the CSS being 88.5%, 87.5%, and 90.9%, and the OS being 76.5%, 75.4%, and 83.8%. Univariate and multivariate Cox regression analyses yielded that age at diagnosis, presence of distant metastases, thyroidectomy scope, and lymph node dissection status were significantly correlated with the prognosis of patients (P < 0.05), and were independent predictors of CSS and OS for patients with MMFCC, and the Kaplan-Meier survival curves plotted by these factors demonstrated their predictive power for the prognosis of patients with MMFCC. The concordance index of the prognostic nomograms of CSS and OS established on this basis was 0.838 and 0.794, respectively, and the time-dependent area under curve, calibration curve, and decision curve analysis curve showed that the model had good discriminative ability, accuracy, and clinical applicability.

CONCLUSIONS

In this study, we concluded that there are large differences between MMFCC and MTC in terms of demographic information, clinicopathological characteristics, treatment information, and survival status information, and we constructed the novel prognostic nomograms for 3-, 5-, and 10 year CSS and OS for patients with MMFCC with risk stratification, which will help clinicians to develop individualized protocols for their postoperative treatments and follow-ups.

Risk factors and novel predictive model for metastatic cutaneous squamous cell carcinoma: a population-based analysis

Cutaneous squamous cell carcinoma (cSCC) is one of the most common skin malignancies. Patients with metastatic cSCC (mcSCC) tended to have unfavorable prognosis. However, there is no available models to evaluate the survival outcomes for these patients. This study retrospectively collected mcSCC cases identified from The Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2018. All patients were randomly divided into the training and validation cohorts. The independent factors which predicted the cancer-specific survival (CSS) were identified by Cox proportional hazard regression analysis, and were used to build nomogram. he discrimination ability of nomograms was evaluated using the concordance index (C-index). The receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) at 1, 3, and 5 years were calculated to estimate the predictive accuracy. The performance of this nomogram was evaluated by the calibration curves. The decision curve analyses (DCAs) were conducted to assess the clinical usefulness of the models. Based on the novel nomograms, all patients were classified into low- and high-risk groups. Kaplan-Meier curves were plotted to compare the survival outcomes of two groups. All analyses were conducted by R software (Version 4.1.3). A total of 916 patients were included. Age, marital status, location of the primary sites, number of metastases, T stage, N stage, surgical resection of the primary sites, radiotherapy of the primary sites, and chemotherapy were significantly associated with CSS. A nomogram predicting CSS was built based on these parameters. C-index and ROC curves of nomogram showed promising discriminating and predicting ability for CSS. Survival analysis showed that patients in the low-risk group had significant superior CSS time than those in the high-risk group (median CSS time: 15.0 vs. 5.0 months, p < 0.001). In conclusion, we developed and validated a novel nomogram predicting the CSS in metastatic cSCC patients. This nomogram could be used to assess the prognosis of metastatic cSCC patients, and help clinicians evaluating optimal treatment options for individual patient.

Clinical characteristics and survival prediction of surgical patients with invasive pancreatic cystic neoplasm: a large retrospective study over two decades

PURPOSES

Invasive pancreatic cystic neoplasms (iPCNs) are an uncommon and biologically heterogeneous group of malignant neoplasms. We aimed to investigate the clinicopathological characteristics of iPCN patients and to develop nomograms for individual survival prediction after radical surgery.

METHODS

Data of patients diagnosed with iPCN and pancreatic ductal adenocarcinoma (PDAC) between 2000 and 2018 from the SEER database were retrieved. The differences in clinical outcomes were evaluated using the Kaplan-Meier analysis. Nomograms were proposed based on the Cox regression model and internally validated by C-index, area under the curve (AUC) value, and calibration plot.

RESULTS

A total of 7777 iPCN patients and 154,336 PDAC patients were enrolled. Most neoplasms were advanced, with 63.1% at stage IV. The 3-year overall survival (OS) and cancer-specific survival (CSS) rates in surgical patients were as follows: 45.7% and 50.1% for invasive intraductal papillary mucinous neoplasm (IPMN), 54.8% and 59.3% for invasive mucinous cystic neoplasm (MCN), 97.8% and 98.2% for invasive solid pseudopapillary neoplasm (SPN), 88.9% and 88.9% for invasive serous cystic neoplasm (SCN), and 27.3% and 30.5% for PDAC. Subgroup analyses showed no clinical benefit from chemotherapy or radiotherapy in lymph node-negative iPCN patients who underwent surgery. The following variables associated with OS and CSS were identified: age, race, chemotherapy, radiotherapy, histologic type, pathological grade, regional nodes examined, and T, N, and M stage. The nomograms had good discrimination and calibration by internal validation, with an AUC value of 0.800 for 3-year OS and 0.814 for 3-year CSS.

CONCLUSION

Our study showed that the prognosis of iPCN patients was significantly better than PDAC patients. The proposed nomograms demonstrated substantially better discrimination and calibration.

Development and external validation of a novel nomogram for predicting cancer-specific survival in patients with ascending colon adenocarcinoma after surgery: a population-based study

Background

This study aimed to develop and validate a novel nomogram to predict the cancer-specific survival (CSS) of patients with ascending colon adenocarcinoma after surgery.

Methods

Patients with ascending colon adenocarcinoma were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database from 1973 to 2015 and randomly divided into a training set (5930) and a validation set (2540). The cut-off values for age, tumour size and lymph node ratio (LNR) were calculated via X-tile software. In the training set, independent prognostic factors were identified using univariate and multivariate Cox analyses, and a nomogram incorporating these factors was subsequently built. Data from the validation set were used to assess the reliability and accuracy of the nomogram and then compared with the 8th edition of the American Joint Committee on Cancer (AJCC) tumour-node-metastasis (TNM) staging system. Furthermore, external validation was performed from a single institution in China.

Results

A total of 8470 patients were enrolled from the SEER database, 5930 patients were allocated to the training set, 2540 were allocated to the internal validation set and a separate set of 473 patients was allocated to the external validation set. The optimal cut-off values of age, tumour size and lymph node ratio were 73 and 85, 33 and 75 and 4.9 and 32.8, respectively. Univariate and multivariate Cox multivariate regression revealed that age, AJCC 8th edition T, N and M stage, carcinoembryonic antigen (CEA), tumour differentiation, chemotherapy, perineural invasion and LNR were independent risk factors for patient CSS. The nomogram showed good predictive ability, as indicated by discriminative ability and calibration, with C statistics of 0.835 (95% CI, 0.823–0.847) and 0.848 (95% CI, 0.830–0.866) in the training and validation sets and 0.732 (95% CI, 0.664–0.799) in the external validation set. The nomogram showed favourable discrimination and calibration abilities and performed better than the AJCC TNM staging system.

Conclusions

A novel validated nomogram could effectively predict patients with ascending colon adenocarcinoma after surgery, and this predictive power may guide clinicians in accurate prognostic judgement.

The prognostic role of in-hospital transfusion of fresh frozen plasma in patients with cholangiocarcinoma undergoing curative-intent liver surgery

INTRODUCTION

Major hepatectomy for perihilar and intrahepatic cholangiocarcinoma (CCA) is often associated with a significant intraoperative blood loss and the requirement for perioperative transfusion of blood products. The aim of this study was to investigate the oncological impact of fresh frozen plasma (FFP) transfusion during hospitalization in patients undergoing hepatectomy for CCA as adverse effects have been described in other malignancies.

MATERIAL AND METHODS

Patients undergoing hepatectomy for CCA from 2010 to 2019 at a single institution were eligible for this study. Survival analysis was carried out according to Kaplan-Meier and the associations of cancer-specific (CSS) and recurrence-free survival (RFS) with in-hospital application of FFP and other clinico-pathological characteristics were assessed using Cox regression models. Perioperatively deceased patients were excluded from the analysis.

RESULTS

A total of 219 CCA patients were included in this survival analysis of which 53.0% (116/219) received FFP during hospitalization. Patients receiving in-hospital FFP showed a median CCS of 33 months (3-year-CSS = 46%, 5-year-CSS = 29%) compared to 83 months (3-year-CSS = 55%, 5-year-CSS = 53%) in patients who did not receive in-hospital FFP (p = 0.006 log rank). Further, in-hospital FFP was identified as an independent predictor of oncological outcome in multivariable analysis (CSS: HR = 1.71, p = 0.016; RFS: HR = 1.89, p = 0.003).

CONCLUSION

In a large European cohort of patients, in-hospital transfusion of FFP was identified as a novel independent prognostic marker in CCA patients undergoing curative-intent liver surgery. A restrictive transfusion policy is therefore recommended to improve long-term outcome in these patients.

Prognostic nomogram for hepatocellular carcinoma with radiofrequency ablation: a retrospective cohort study

Background

Radiofrequency ablation (RFA) is an effective treatment option for hepatocellular carcinoma (HCC). This study aimed to analyze the prognostic factors of HCC patients treated with RFA and to develop nomograms for outcome prediction.

Methods

A total of 3142 HCC patients treated with RFA were recruited, and their data were collected from the Surveillance, Epidemiology, and End Results database. Univariate and multifactor Cox analyses were performed to identify independent prognostic factors. These factors were integrated into a nomogram to predict 3- and 5-year cancer-specific survival (CSS) and overall survival (OS). Consistency indices and calibration plots were used to assess the accuracy of the nomograms in both the internal and external cohorts.

Results

The median follow-up periods for HCC patients treated with RFA were 27 and 29 months for OS and CSS, respectively. Marital status, age, race, histological grade of differentiation, tumor size, T stage, and serum alpha-fetoprotein levels at the time of diagnosis were identified as prognostic factors for OS and CSS. Additionally, M stage was identified as risk factors for OS. These risk factors are included in the nomogram. The calibration plots of the OS and CSS nomograms showed excellent consistency between actual survival and nomogram predictions. The bootstrap-corrected concordance indices of the OS and CSS nomograms were 0.637 (95% CI, 0.628–0.646) and 0.670 (95% 0.661–0.679), respectively. Importantly, our nomogram performed better discriminatory compared with 8th edition tumor-node-metastasis (TNM) stage system for predicting OS and CSS.

Conclusions

We identified prognostic factors for HCC patients treated with RFA and provided an accurate and personalized survival prediction scheme.

Nomogram for predicting the survival rate of primary pulmonary mucoepidermoid carcinoma patients: a retrospective study based on SEER database

Background

Primary pulmonary mucoepidermoid carcinoma (PMEC) is a rare malignant tumor, and the clinical manifestations lack specificity. The study evaluates the prognostic factors and constructs a practicable nomogram to estimate the individualized survival status for PMEC patients.

Methods

Surveillance, Epidemiology, and End Results (SEER) database was used to selected eligible patients between 1975 and 2016. The baseline characteristics including age, sex, race, marital status, tumor stage, differentiated degree, tumor laterality, primary tumor site, tumor size, lymph node metastases status, distant metastases status, surgery, chemotherapy, and radiation. We identified independent variables to build 3-, 5-, 10-year overall survival (OS) and cancer-specific survival (CSS) nomograms by univariate and multivariate analyses.

Results

A total of 438 PMEC patients met our selection criteria. In multivariate analysis, age, tumor stage, differentiated grade, tumor size, lymph node metastases status, distant metastases status, surgery and radiation were involved in the nomogram. The C-index (0.887 (95% CI: 0.863-0.911), calibrate plots and ROC curves (AUC =0.941, 0.951, 0.935 for 3-, 5-, 10-year OS, respectively) indicated the satisfied accuracy and practicability of our nomograms. Compared to TNM system, our model also showed a superior prediction (IDI =0.167, 0.171, 0.172, P<0.001).

Conclusions

We built OS (CSS) nomograms that can accurately estimate individualized survival time and identify the risk classification of PMEC.