Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery

The molecular characteristics could supplement the staging system of pT2/T3N0M0 esophageal squamous cell carcinoma: a translational study based on a cohort with over 20 years of follow-up

OBJECTIVE

This study aimed to construct a model based on 23 enrolled molecules to evaluate prognoses of pT2/3N0M0 esophageal squamous cell carcinoma (ESCC) patients with up to 20 years of follow-up.

METHODS

The lasso-Cox model was used to identify the candidate molecule. A nomogram was conducted to develop the survival model (molecular score, MS) based on the molecular features. Cox regression and Kaplan-Meier analysis were used in this study. The concordance index (C-index) was measured to compare the predicted ability between different models. The primary endpoint was overall survival (OS).

RESULTS

A total of 226 patients and 23 proteins were enrolled in this study. Patients were classified into high-risk (MS-H) and low-risk (MS-L) groups based on the MS score of 227. The survival curves showed that the MS-L cohort had better 5-year and 10-year survival rates than the MS-H group (5-year OS: 51.0% vs. 8.0%; 10-year OS: 45.0% vs. 5.0%, all p < 0.001). Furthermore, multivariable analysis confirmed MS as an independent prognostic factor after eliminating the confounding factors (Hazard ratio 3.220, p < 0.001). The pT classification was confirmed to differentiate ESCC patients' prognosis (Log-rank: p = 0.029). However, the combination of pT and MS could classify survival curves evidently (overall p < 0.001), which showed that the prognostic prediction efficiency was improved significantly by the combination of the pT and MS than by the classical pT classification (C-index: 0.656 vs. 0.539, p < 0.001).

CONCLUSIONS

Our study suggested an MS for significant clinical stratification of T2/3N0M0 ESCC patients to screen out subgroups with poor prognoses. Besides, the combination of pT staging and MS could predict survival more accurately for this cohort than the pT staging system alone.

Diagnostic performance of radiomics model for preoperative risk categorization in thymic epithelial tumors: a systematic review and meta-analysis

BACKGROUND

Incidental thymus region masses during thoracic examinations are not uncommon. The clinician's decision-making for treatment largely depends on imaging findings. Due to the lack of specific indicators, it may be of great value to explore the role of radiomics in risk categorization of the thymic epithelial tumors (TETs).

METHODS

Four databases (PubMed, Web of Science, EMBASE and the Cochrane Library) were screened to identify eligible articles reporting radiomics models of diagnostic performance for risk categorization in TETs patients. The quality assessment of diagnostic accuracy studies 2 (QUADAS-2) and radiomics quality score (RQS) were used for methodological quality assessment. The pooled area under the receiver operating characteristic curve (AUC), sensitivity and specificity with their 95% confidence intervals were calculated.

RESULTS

A total of 2134 patients in 13 studies were included in this meta-analysis. The pooled AUC of 11 studies reporting high/low-risk histologic subtypes was 0.855 (95% CI, 0.817-0.893), while the pooled AUC of 4 studies differentiating stage classification was 0.826 (95% CI, 0.817-0.893). Meta-regression revealed no source of significant heterogeneity. Subgroup analysis demonstrated that the best diagnostic imaging was contrast enhanced computer tomography (CECT) with largest pooled AUC (0.873, 95% CI 0.832-0.914). Publication bias was found to be no significance by Deeks' funnel plot.

CONCLUSIONS

This present study shows promise for preoperative selection of high-risk TETs patients based on radiomics signatures with current available evidence. However, methodological quality in further studies still needs to be improved for feasibility confirmation and clinical application of radiomics-based models in predicting risk categorization of the thymic epithelial tumors.

Prognostic value of preoperative C-reactive protein to albumin ratio in patients with thymic epithelial tumors: a retrospective study

Background

The C-reactive protein to albumin ratio (CAR) is associated with poor prognosis in various cancers. However, its value in thymic epithelial tumors remains to be elucidated, we aimed to evaluate the prognostic significance of preoperative CAR in patients with surgically resected thymic epithelial tumors (TETs).

Methods

We retrospectively collected data from 125 patients with TETs who underwent thymoma resection at our center. The best cutoff values ​​for the continuous variable, CAR, were obtained using X-tile software. Univariate and multivariate Cox regression analyses were used to evaluate CAR as an independent predictor of overall survival (OS) and recurrence-free survival (RFS). Kaplan–Meier analysis and log-rank tests were used to present risk stratification of patients based on CAR and the Glasgow-prognostic-score (GPS). The prognostic effect of CAR was assessed using a receiver operating characteristic curve.

Results

Patients were categorized into high (≥ 0.17) and low (< 0.17) CAR groups according to the optimal cutoff value of 0.17. Univariate and multivariate analyses showed that CAR was an independent predictor of prognosis. World health organization stage, CAR level, GPS score, and drinking history were important independent prognostic factors for OS (p < 0.05). T stage, CAR level, and drinking history were important independent prognostic factors for RFS (p < 0.05). The area under the curve value of CAR to predict prognosis was 0.734 for OS and 0.680 for RFS.

Conclusions

Elevated preoperative CAR was independently associated with poor OS and RFS after thymectomy. Therefore, CAR may be a valuable biomarker for the postoperative prognosis of TETs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10234-x.

The Construction and Validation of Nomogram to Predict the Prognosis with Small-Cell Lung Cancer Followed Surgery

This study constructed and validated a prognostic model to evaluate the survival of small-cell lung cancer (SCLC) patients following surgery, and shed light on the strategy of postoperative radiotherapy. A total of 882 patients from Shanghai Pulmonary Hospital and the Surveillance, Epidemiology and End Results database after lung resection were selected. Multivariable Cox analysis was used to identify the indicators affecting long-term survival in patients. A nomogram was constructed to predict the prognosis of eligible patients. Indices of concordance (C-index) was used to access the predictive ability of cancer-specific survival (CSS) for the prognostic model. CSS discrimination in the prognostic model was comparable in the training and validation cohorts (C-index = 0.637[NORAD-T], 0.660[NORAD-V], 0.656[RAD] and 0.627[our hospital], respectively. Stratification based on the cutoff value of the nomogram yielded low- and high-risk subgroups in four cohorts. For patients in the high-risk group, postoperative radiotherapy was considered a survival-promoting strategy (unadjusted HR 0.641, 95% CI 0.469-0.876, p = 0.0046). In the low-risk group, however, the implementation of radiotherapy barely had an influence on CSS. In conclusion, the nomogram we constructed and validated could predict the prognosis of SCLC patients followed surgery and identify high-risk patients who were likely to benefit from postoperative radiotherapy.

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.