A Nomogram Predicting Recurrence and Guiding Adjuvant Radiation for Thymic Carcinoma After Resection

Surgical, Radiation, and Systemic Treatments of Patients With Thymic Epithelial Tumors: A Systematic Review

INTRODUCTION

Thymic epithelial tumors are rare and are classified as thymoma, thymic carcinoma, and thymic neuroendocrine tumors. The objective of this systematic review was to evaluate the treatment options for patients with thymic epithelial tumors.

METHODS

This systematic review was developed by Ontario Health (Cancer Care Ontario)'s Program in Evidence-Based Care and by the Lung Cancer Disease Site Group. MEDLINE, EMBASE, and the Cochrane Library were searched for studies comparing surgical, radiotherapy, or systemic treatments against any combination of these treatments in patients with thymic epithelial tumors. Meta-analyses were conducted with clinically homogenous studies.

RESULTS

A total of 106 studies were included, mainly from observational studies. There was an overall survival benefit with postoperative radiotherapy for patients with thymic carcinoma (hazard ratio = 0.65, 95% confidence interval: 0.47-0.89) and for patients with thymoma (hazard ratio = 0.70, 95% confidence interval: 0.59-0.82), especially for those with a high risk for mortality. Patients with thymic carcinoma or thymoma had a response to chemotherapy. Selection bias affected the results for studies that evaluated neoadjuvant chemotherapy or minimally invasive surgical techniques. Furthermore, the overall survival benefit found for adjuvant chemotherapy may have been confounded by the administration of postoperative radiotherapy.

CONCLUSIONS

For patients with thymoma or thymic carcinoma, the literature is of low quality and subject to bias. There were overall survival benefits with postoperative radiotherapy. The results of this systematic review were used to inform treatment recommendations in a clinical practice guideline. Future large-scale prospective studies that control for confounders are needed.

Prognostic Value of Preoperative Nutritional Assessment and Neutrophil-to-Lymphocyte Ratio in Patients With Thymic Epithelial Tumors

Introduction

Systemic nutrition and immune inflammation are the key factors in cancer development and metastasis. This study aimed to compare and assess four nutritional status and immune indicators: prognostic nutritional index (PNI), nutritional risk index (NRI), neutrophil-to-lymphocyte ratio (NLR), and the systemic immune-inflammatory index (SII) as prognostic indicators for patients with thymic epithelial tumors.

Materials

We retrospectively reviewed 154 patients who underwent thymic epithelial tumor resection at our hospital between 2004 and 2015. The optimal cutoff value for each nutritional and immune index was obtained using the X-tile software. Kaplan-Meier curves and Cox proportional hazards models were used for survival analysis.

Results

Univariate analysis showed that PNI, NRI, NLR, SII, albumin (ALB), the albumin/globulin ratio (A/G), WHO stage, T stage, and drinking history were associated with the overall survival (OS) of patients (P < 0.05). The NRI, NLR, A/G, ALB, T stage, and WHO stage were significant independent prognostic factors of OS in multivariate analysis (P < 0.05). Finally, we constructed a coNRI-NLR model to predict OS and recurrence-free survival (RFS).

Conclusions

This study suggests that the preoperative NRI, NLR, and coNRI-NLR model may be important prognostic factors for patients with thymic epithelial tumors who undergo surgical resection.

The Prognostic Value of Preoperative Serum D-dimer Levels After Surgical Resection of Thymic Epithelial Tumors

Introduction

Thymic epithelial tumors are the most common mediastinal tumors. Despite the high survival rate after surgery, some patients still require postoperative adjuvant therapy and closer follow-up. Hematological indicators such as biochemical routines and coagulation indicators have been reported to be independently associated with the prognosis of various malignancies. Therefore, we included hematological indicators in the analysis.

Methods

The data of 105 patients with thymic epithelial tumors were retrospectively collected from Sun Yat-sen University Cancer Center, and the patients with missing preoperative hematological indicators were excluded. X-tile software was used to obtain the best cutoff value of each preoperative hematological indicator, and COX regression analysis and Kaplan-Meier survival curves were used to demonstrate statistically significant results.

Results

COX univariate regression analysis of all patients showed that Masaoka stage, T stage, WHO histologic types, D-dimer, albumin-fibrinogen ratio (AFR), Fibrinogen (Fbg) were associated with postoperative overall survival ( P < .05). T stage, WHO histologic types, D-dimer, and AFR were associated with postoperative recurrence-free survival ( P < .05). Finally, multivariate regression analysis showed that T stage, D-dimer levels were independently associated with postoperative overall survival (OS) and recurrence-free survival (RFS) in patients with thymic epithelial tumors.

Conclusions

For thymic epithelial tumors, higher preoperative D-dimer levels predict poorer survival and shorter recurrence-free survival. This may help guide postoperative adjuvant therapy and follow-up patterns in patients with thymic epithelial tumors.

Diagnostic and prognostic values of 2-[18F]FDG PET/CT in resectable thymic epithelial tumour

OBJECTIVES

We aimed to evaluate the diagnostic ability for the prediction of histologic grades and prognostic values on recurrence and death of pretreatment 2-[¹⁸F]FDG PET/CT in patients with resectable thymic epithelial tumours (TETs).

METHODS

One hundred and fourteen patients with TETs who underwent pretreatment 2-[¹⁸F]FDG PET/CT between 2012 and 2018 were retrospectively evaluated. TETs were classified into three histologic subtypes: low-risk thymoma (LRT, WHO classification A/AB/B1), high-risk thymoma (HRT, B2/B3), and thymic carcinoma (TC). Area under the receiver operating characteristics curve (AUC) was used to assess the diagnostic performance of PET/CT variables (maximum standardised uptake value [SUVmax], metabolic tumour volume [MTV], total lesion glycolysis [TLG], maximum diameter). Cox proportional hazards models were built using PET/CT and clinical variables.

RESULTS

The tumours included 52 LRT, 33 HRT, and 29 TC. SUVmax showed good diagnostic ability for differentiating HRT/TC from LRT (AUC 0.84, 95% confidence interval [CI] 0.76 - 0.92) and excellent ability for differentiating TC from LRT/HRT (AUC 0.94, 95% CI 0.90 - 0.98), with significantly higher values than MTV, TLG, and maximum diameter. With an optimal cut-off value of 6.4, the sensitivity, specificity, and accuracy for differentiating TC from LRT/HRT were 69%, 96%, and 89%, respectively. In the multivariable Cox proportional hazards analyses for freedom-from-recurrence, SUVmax was an independent prognostic factor (p < 0.001), whereas MTV and TLG were not. SUVmax was a significant predictor for overall survival in conjunction with clinical stage and resection margin.

CONCLUSION

SUVmax showed excellent diagnostic performance for prediction of TC and significant prognostic value in terms of recurrence and survival.

KEY POINTS

• Maximum standardised uptake value (SUVmax) shows excellent performance in the differentiation of thymic carcinoma from low- and high-risk thymoma. • SUVmax is an independent prognostic factor for freedom-from-recurrence in the multivariable Cox proportional hazard model and a significant predictor for overall survival. • 2-[¹⁸F]FDG PET/CT can provide a useful diagnostic and prognostic imaging biomarker in conjunction with histologic classification and stage and help choose appropriate management for thymic epithelial tumours.

LOXL1‑AS1 promotes thymoma and thymic carcinoma progression by regulating miR‑525‑5p‑HSPA9

Due to the lack of specific symptoms in early thymic epithelial tumours (TETs), patients are mostly in the advanced stage at the time of presentation. The aim of the present study was to explore the mechanism by which the long noncoding RNA (lncRNA) LOXL1‑AS1 affects thymoma and thymic carcinoma progression by targeting the miR‑525‑5p‑HSPA9 axis. Bioinformatics was used to analyse the process of LOXL1‑AS1 targeting miR‑525‑5p‑HSPA9 and its expression characteristics in TET. The relationships between LOXL1‑AS1, miR‑525‑5p, HSPA9 and prognosis were analysed. The dual luciferase reporter assay was applied to verify targeting. The gene was knocked down or overexpressed by plasmid transfection. Cell counting kit 8 (CCK‑8) assay, flow cytometry and Transwell assay were used to detect cell viability, apoptosis and invasion ability, respectively. Proteins and RNAs were examined by western blot analysis and qPCR, respectively. A tumour‑burdened assay was used to perform in vivo verification. LOXL1‑AS1 and HSPA9 were overexpressed in thymoma and thymic carcinoma; high levels of LOXL1‑AS1 and HSPA9 were associated with poor prognosis, and there was a significant positive correlation between their levels. Downregulation of miR‑525‑5p expression was also associated with poor prognosis of patients. Clinical trials also demonstrated the same trends. miR‑525‑5p inhibited the expression of HSPA9 protein by targeting the 3'‑untranslated region (UTR) of HSPA9 mRNA. LOXL1‑AS1 promoted the expression of HSPA9 as a sponge targeting miR‑525‑5p. Animal experiment results also showed that knockdown of miR‑525‑5p promoted cancer by promoting the expression of HSPA9. In conclusion, LOXL1‑AS1 and HSPA9 are highly expressed in thymoma and thymic carcinoma; miR‑525‑5p is expressed at low levels in thymoma and thymic carcinoma; and downregulation of miR‑525‑5p is associated with poor prognosis. In summary, this study demonstrates that LOXL1‑AS1 acts as a sponge that targets miR‑525‑5p to promote HSPA9 expression, thereby promoting the growth and invasion and inhibiting apoptosis of thymoma and thymic carcinoma cells.

Development and validation of a nomogram for prediction of lymph node metastasis in early-stage breast cancer

Background

Lymph node status is an important factor in determining the prognosis of early-stage breast cancer. We endeavored to build and validate a simple nomogram to predict lymph node metastasis (LNM) in patients with early-stage breast cancer.

Methods

Patients with T1-2 and non-metastasis (M0) breast cancer registered in the Surveillance, Epidemiology, and End Results (SEER) database were enrolled. All patients were divided into primary cohort and validation cohort in a 2:1 ratio. In order to assess risk factors for LNM, we performed univariate and multivariate binary logistic regression, and based on results of multivariable analysis, we built the predictive nomogram model. The C-index, receiver operating characteristic (ROC) and calibration plots were applied to assess LNM model performance. Moreover, the nomogram efficiency was further validated through the validation cohort, part of which was from the First Affiliated Hospital of Nanjing Medical University database.

Results

Totally, 184,531 female breast cancer with T1-2 tumor size from SEER database and 1,222 patients from the Chinese institutional data were included. There were 123,019 patients in the primary cohort and 62,734 patients in validation cohort. The LNM nomogram was composed of seven features including age at diagnosis, race, primary site, histologic type, grade, tumor size and subtype. The model showed good discrimination, with a C-index of 0.720 [95% confidence interval (CI): 0.717-0.723] and good calibration. Similar C-index was 0.718 (95% CI: 0.713-0.723) in validation cohort. Consistently, ROC curves presented good discrimination in the primary cohort [area under the curve (AUC) =0.720] and the validation set (AUC =0.718) for the LNM nomogram. Calibration curve of the nomogram demonstrated good agreement.

Conclusions

With the prediction of novel validated nomogram for women with early-stage breast cancer, doctors may distinguish patients with high possibility of LNM and devise individualize treatments.

Development and validation of a nomogram prognostic model for patients with neuroendocrine tumors of the thymus

Background

The purpose of this study was to analyze the clinical characteristics and prognostic survival of patients with neuroendocrine tumors of the thymus (NETTs), and to develop and validate a nomogram model for predicting the prognosis of patients.

Methods

We conducted a retrospective analysis of patients with neuroendocrine tumors of the thymus in the Surveillance, Epidemiology, and End Results (SEER) database in the United States between 1988 and 2016. Cox scale risk regression analysis, the Kaplan‐Meier method and log‐rank test were used to carry out the significance test to determine the independent prognostic factors, from which a nomogram for NETTs was established. C‐index and calibration curve were used to evaluate the prediction accuracy of the model. External validation of the nomogram was performed using data from our center.

Results

A total of 254 patients with NETTs were collected in the SEER database. In the multivariable analysis, T stage, tumor grade, surgery, and chemotherapy were found to be independent factors affecting the prognosis of patients (all P < 0.05). A nomogram model was constructed based on these variables, and its c‐index was 0.707 (0.661–0.752). The c‐index results showed that the nomogram model had better authentication capability than the eighth edition of the tumor, node, metastasis (TNM) staging system and Masaoka‐Koga (MK) staging system. The calibration curve showed that the model could accurately predict patient prognosis.

Conclusions

The study established a nomogram model that predicted the overall survival rate of one‐, three‐ and five‐years, and used the survival prediction model to optimize individualized therapy and prognostic follow‐up through risk stratification.