Dataset Information

A validated nomogram integrating hematological indicators to predict response to neoadjuvant therapy in esophageal squamous cell carcinoma patients.

ABSTRACT:

Background

The prognoses for advanced Esophageal squamous cell cancer (ESCC) was very poor. Neoadjuvant therapy was shown to improve overall survival of ESCC patients. However, there is still no effective indicator to predict the efficacy of neoadjuvant therapy. The present study intended to investigate the correlation between hematological parameters and the efficacy of neoadjuvant therapy so as to provide a reference for the prediction of cancer response to neoadjuvant therapy.

Methods

This study included 197 ESCC patients in our center from January 2010 to December 2018. Response evaluation criteria in solid tumors (RECIST) criteria were used for the treatment evaluation. The results of univariate and multivariate logistic regression analysis were used to select independent factors for construction of the prediction model. The concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve were used to evaluate the robustness of the model, while the bootstrap method was used for internal validation.

Results

Among the 197 included ESCC patients, 94 patients achieved partial remission, 80 patients were in stable condition, and 23 patients had disease progression, 123 of whom underwent surgery. The comparisons of the dynamic hematological test results before and after treatment show that pre-PLT, pre-MONO%, post-Hb, △WBC, and the option of undergoing neoadjuvant chemoradiation were the potential predictors for the effectiveness of neoadjuvant therapy. The model in which the C-index was 0.803 (95% confidence interval: 0.742-0.864) showed good prediction performance, and still reach a C-index of 0.764 when internally validated.

Conclusions

For the neoadjuvant treatment of ESCC, hematological indexes are closely related to the efficacy of neoadjuvant therapy. The nomogram can be used to easily predict the efficacy of neoadjuvant therapy in patients.

SUBMITTER: Wang S

PROVIDER: S-EPMC8106100 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A validated nomogram integrating hematological indicators to predict response to neoadjuvant therapy in esophageal squamous cell carcinoma patients.

Wang Sichao S Zhou Zihao Z Tian Dan D Huang Shujie S Wang Ce C Gao Zhen Z Ben Xiaosong X Tang Jiming J Xie Liang L Zhou Haiyu H Zhang Dongkun D Shi Ruiqing R Deng Cheng C Zhuang Weitao W Ding Yu Y Qiao Guibin G

Annals of translational medicine 20210401 8

<h4>Background</h4>The prognoses for advanced Esophageal squamous cell cancer (ESCC) was very poor. Neoadjuvant therapy was shown to improve overall survival of ESCC patients. However, there is still no effective indicator to predict the efficacy of neoadjuvant therapy. The present study intended to investigate the correlation between hematological parameters and the efficacy of neoadjuvant therapy so as to provide a reference for the prediction of cancer response to neoadjuvant therapy.<h4>Meth ...[more]

PMID: 33987401

Similar Datasets

Project description:PurposeThe degree of benefit from palliative chemotherapy differs widely among patients with metastatic esophageal squamous cell carcinoma (MESCC). The purpose of this study was to develop and validate a prognostic nomogram to predict survival and aid physicians and patients in the decision-making process regarding treatment options.Materials and methodsClinicopathologic variables and treatment outcomes of 239 patients who were diagnosed with MESCC and received either fluorouracil/cisplatin (FP) or capecitabine/cisplatin (XP) as first-line chemotherapy were reviewed. A nomogram was developed as a prognostic scoring system incorporating significant clinical and laboratory variables based on a multivariate Cox proportional hazards regression model. An independent series of 61 MESCC patients treated with FP served as an independent data set for nomogram validation.ResultsNo difference in response rate was observed between the FP group (44.8%) and the XP group (54.2%). Similarly, no significant differences in median progression-free survival and median overall survival were observed between regimen groups. Multivariate analysis showed that poor performance status (Eastern Cooperative Oncology Group [ECOG] status≥2), weight loss (10% of the weight loss for 3 months), low albumin level (≤3.5 g/dL), and absence of previous esophagectomy at the time of chemotherapy were significantly associated with low OS in both groups (p<0.05). Based on these findings, patients were classified into favorable (score, 0 to 90), intermediate (91-134), and poor (>135) prognostic groups. The median survival for those with a favorable ECOG was 13.8 months (95% confidence interval [CI], 10.8 to 18.6 months), for intermediate 11.2 months (95% CI, 8.7 to 11.9 months), and for poor, 7.0 months (95% CI, 3.6 to 10.0 months). External validation of the nomogram in a different patient cohort yielded significantly similar findings.ConclusionThe nomogram described here predicts survival in MESCC patients and could serve as a guide for the use of FP/XP chemotherapy in MESCC patients.

Project description:BackgroundThere are various treatment options for esophageal squamous cell cancer. including surgery, peri-operative chemotherapy, and radiation. More recently, neoadjuvant immunotherapy has also been shown improve outcomes. In this study, we addressed the question, "Can we predict which patients with esophageal squamous cell cancer will benefit from neoadjuvant immunotherapy?".MethodsAll patients with thoracic esophageal squamous-cell carcinoma (T2N+M0-T3-4N0/+M0) (according to the eighth edition of the National Comprehensive Cancer Network guidelines) who underwent immune neoadjuvant immunochemotherapy with programmed cell death protein 1 (PD-1) combined with paclitaxel plus cisplatin or nedaplatin in the Affiliated Cancer Hospital of Zhengzhou University, China, between November 2019 and August 2021 were included in this study. All patients underwent surgical resection. We developed a response [tumor regression grade (TRG)] prediction model using the least absolute shrinkage and selection operator (LASSO) regression incorporating factors associated with response. The accuracy of the prediction model was then validated.ResultsWe included 79 patients who underwent neoadjuvant immunotherapy combined with chemotherapy, aged 48-78 years (62.05±6.67), including 21 males and 58 females. There were five cases of immune-related pneumonia, of which three cases were diagnosed as immune-related pneumonia during the perioperative period, and one case of immune-related thyroid dysfunction changes. After LASSO regression, the factors that were independently associated with TRG were clinical T stage before neoadjuvant therapy, clinical N stage before neoadjuvant therapy, albumin level difference from before to after neoadjuvant therapy, white blood cell (WBC) count before neoadjuvant therapy, and T stage before surgery. We constructed a prediction model, plotted the nomogram, and verified its accuracy. Its Brier score was 0.13, its calibration slope was 0.98, and its C-index was 0.90 (95% CI: 0.82-0.97).ConclusionsOur prediction model can predict the likelihood of TRG in patients with esophageal squamous cell cancer after immunotherapy combined with neoadjuvant chemotherapy. Using this prediction model, we plan to conduct a subsequent neoadjuvant radiotherapy in patients with of TRG 2-3 patients with neoadjuvant radiotherapy.

Project description:The lymphovascular invasion (LVI) status facilitates the determination of the optimal therapeutic strategy for superficial esophageal squamous cell carcinoma (SESCC), but in clinical practice, LVI must be confirmed by postoperative pathology. However, studies of the risk factors for LVI in SESCC are limited. Consequently, this study aimed to identify the risk factors for LVI and use these factors to establish a prediction model. The data of 516 patients who underwent radical esophagectomy between January 2007 and September 2019 were retrospectively collected (training set, n=361, January 2007 to May 2015; validation set, n=155, June 2015 to September 2019). In the training set, least absolute shrinkage and selection operator (LASSO) regression and multivariate analyses were utilized to identify predictive factors for LVI in patients with SESCC. A nomogram was then developed using these predictors. The area under the curve (AUC), calibration curve, and decision curve were used to evaluate the efficiency, accuracy, and clinical utility of the model. LASSO regression indicated that the tumor size, depth of invasion, tumor differentiation, lymph node metastasis (LNM), sex, circumferential extension, the presence of multiple lesions, and the resection margin were correlated with LVI. However, multivariate analysis revealed that only the tumor size, depth of invasion, tumor differentiation, and LNM were independent risk factors for LVI. Incorporating these four variables, model 1 achieved an AUC of 0.817 in predicting LVI. Adding circumferential extension to model 1 did not appreciably change the AUC and integrated discrimination improvement, but led to a significant increase in the net reclassification improvement (p=0.011). A final nomogram was constructed by incorporating tumor size, depth of invasion, tumor differentiation, LNM, and circumferential extension and showed good discrimination (training set, AUC=0.833; validation set, AUC=0.819) and good calibration in the training and validation sets. Decision curve analysis demonstrated that the nomogram was clinically useful in both sets. Thus, it is possible to predict the status of LVI using this nomogram scoring system, which can aid the selection of an appropriate treatment plan.

Dataset Information

A validated nomogram integrating hematological indicators to predict response to neoadjuvant therapy in esophageal squamous cell carcinoma patients.

Background

Methods

Results

Conclusions

Publications

A validated nomogram integrating hematological indicators to predict response to neoadjuvant therapy in esophageal squamous cell carcinoma patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets