scholarly journals Association between Paclitaxel Clearance and Tumor Response in Patients with Esophageal Cancer

Cancers ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 173
Author(s):  
Eelke L.A. Toxopeus ◽  
Femke M. de Man ◽  
Nanda Krak ◽  
Katharina Biermann ◽  
Annemieke J.M. Nieuweboer ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Treatment Response ◽  
Tumor Regression ◽  
Geometric Mean ◽  
Neoadjuvant Chemoradiotherapy ◽  
Systemic Exposure ◽  
Tumor Regression Grade ◽  
P Value ◽  
Response To Chemotherapy ◽  
Regression Grade

Inter-individual variability in paclitaxel pharmacokinetics may play a role in the response to chemotherapy. Therefore, we studied the association between paclitaxel clearance and treatment response in patients with esophageal cancer. All patients who received paclitaxel (plus carboplatin) treatment for esophageal cancer between 2007 and 2013 were included. The treatment was given as neoadjuvant chemoradiotherapy (nCRT), induction chemotherapy (iCT), or palliative chemotherapy (pCT). The treatment response was assessed by the tumor regression grade (TRG) or by the RECIST1.1 criteria, respectively. The unbound paclitaxel clearance (CL) was estimated with NONMEM. The log-transformed clearance was related to response with ANOVA and independent sample t-tests. A total of 166 patients were included, of whom 113 received nCRT, 23 iCT and 30 pCT. In patients receiving nCRT, paclitaxel clearance was not associated with tumor regression grade (p-value = 0.25), nor with pathologically complete response (geometric mean 561.6 L/h) and residual disease (geometric mean 566.1 L/h, p-value = 0.90). In patients who underwent iCT or pCT, also no association between paclitaxel clearance and RECIST outcome was identified (iCT: p-value = 0.08 and pCT: p-value = 0.81, respectively). In conclusion, systemic paclitaxel exposure was not associated with response to common paclitaxel-based treatment regimens for esophageal cancer. Future studies should focus on tumor exposure in relation to systemic exposure and treatment outcome.

Correlation between standardized uptake value in pre- and post-neoadjuvant chemoradiotherapy and tumor regression grade in patients with locally advanced esophageal cancer.

2014 ◽  
Vol 32 (3_suppl) ◽  
pp. 150-150
Author(s):  
Kathryn Baksh ◽  
Khaldoun Almhanna
Keyword(s):  
Esophageal Cancer ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Neoadjuvant Chemoradiotherapy ◽  
Tumor Regression Grade ◽  
P Value ◽  
Advanced Esophageal Cancer ◽  
Pet Scans ◽  
Regression Grade ◽  
Locally Advanced Esophageal Cancer

150 Background: A multimodality approach with neoadjuvant chemotherapy and radiation is the standard of care in the United States in the treatment of patients with locally advanced esophageal cancer. It is well established that neoadjuvant chemoradiotherapy (CRT) in these patients can facilitate downstaging, correlating with pathologic response, and improving overall survival. Our clinical practice involves the use of positron emission tomography (PET) to assist with staging in patients prior to undergoing neoadjuvant CRT and surgery. While there has been evidence showing correlation between tumor regression grade (TRG) and increased overall survival in these patients, the relationship between standardized uptake values on PET scans and TRG has not been discerned. The purpose of this study was to determine whether pre and post-chemoradiotherapy SUV on PET scans correlate with TRG in esophageal cancer patients receiving neoadjuvant chemoradiotherapy. Methods: A retrospective review of 56 patients with stage II-III esophageal cancer treated with neo-adjuvant CRT followed by surgery was performed. Pre- and post- treatment PET scans were reviewed. Maximum SUV at the site of the primary tumor was recorded. Upon completion of surgery, tumor regression grade was determined by a specialized pathologist. Spearman correlation was used to compare pre, post, and change in max SUV, to the 4 level TRG variables. Results: The median follow-up was 24 months. No significant correlation was found between pre-treatment or post treatment SUV and TRG with p value of 0.73 and 0.94 respectively. There was no significant correlation between decreased FDG uptake following CRT and TRG with p value of 0.82. Consistent with previous data, TRG predicted the therapeutic efficacy and prognosis for patients with locally advanced esophageal carcinoma treated by neoadjuvant chemotherapy. Conclusions: Our results are preliminary and retrospective in nature. A larger sample is needed to confirm these findings. Decreased FDG uptake in sequential PET scans strongly correlates with tumor response, but is not accurate enough to predict pathological response.

Rectal cancer – current treatment strategy and the tumor regression grade evaluation after neoadjuvant therapy in patients who underwent surgery at the I. Department of Surgery, General University Hospital in Prague between 2012 and 2016

2021 ◽  
Vol 100 (2) ◽  
Keyword(s):  
Rectal Cancer ◽  
Neoadjuvant Therapy ◽  
Tumor Regression ◽  
Neoadjuvant Treatment ◽  
Neoadjuvant Chemoradiotherapy ◽  
Current Treatment ◽  
University Hospital ◽  
Tumor Regression Grade ◽  
Oncological Treatment ◽  
Regression Grade

Introduction: The article contains a summary of the issues of staging and therapy with an emphasis on the neoadjuvant treatment and associated tumor regression grade with the analysis of our own group of patients. Methods: Retrospective analysis of patients with rectal cancer who underwent a surgery at the 1st Department of Surgery – Thoratic, Abdominal and Injury Surgery; First Faculty of Medicine, Charles University in Prague and General University Hospital in Prague, Czech Republic, focusing on those who underwent neoadjuvant chemoradiotherapy and their pathologists evaluated tumor regression grade after the resection. Results: The group consists of 161 patients operated on between 2012 and 2016. 47 patients underwent neoadjuvant oncological treatment with further evaluation of the tumor regression grade by a pathologist, a scoring system according to Ryan was used. A complete pathological response was elicited in 10.4% of patients, no response in 35.4% of patients, and partial tumor regression in 54.2%. Conclusion: Although there is a difference in our results compared to foreign publications, the proportion of patients remains comparable. Studies evaluating the advantages versus disadvantages of neoadjuvant therapy will certainly follow, and the question of the suitability of surgical treatment as the only curative solution is partially raised.

The prognostic value of a modified tumor regression grade after neoadjuvant chemoradiotherapy and resection of esophageal carcinoma.

2015 ◽  
Vol 33 (15_suppl) ◽  
pp. 4066-4066
Author(s):  
Maarten CJ Anderegg ◽  
Sjoerd M Lagarde ◽  
Wernard A Borstlap ◽  
Suzanne S Gisbertz ◽  
Sybren L. Meijer ◽  
...  
Keyword(s):  
Esophageal Carcinoma ◽  
Prognostic Value ◽  
Tumor Regression ◽  
Neoadjuvant Chemoradiotherapy ◽  
Tumor Regression Grade ◽  
Regression Grade

scholarly journals Predicting Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Mucinous Adenocarcinoma Using an MRI-Based Radiomics Nomogram

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhihui Li ◽  
Shuai Li ◽  
Shuqin Zang ◽  
Xiaolu Ma ◽  
Fangying Chen ◽  
...  
Keyword(s):  
Treatment Response ◽  
Mucinous Adenocarcinoma ◽  
Tumor Regression ◽  
Neoadjuvant Chemoradiotherapy ◽  
Roc Curves ◽  
Quantitative Mri ◽  
Tumor Regression Grade ◽  
Patient Variables ◽  
Validation Set ◽  
Radiomics Signature

ObjectiveTo build and validate an MRI-based radiomics nomogram to predict the therapeutic response to neoadjuvant chemoradiotherapy (nCRT) in rectal mucinous adenocarcinoma (RMAC).MethodsTotally, 92 individuals with pathologically confirmed RMAC administered surgical resection upon nCRT in two different centers were assessed retrospectively (training set, n = 52, validation set, n = 40). Rectal MRI was performed pre-nCRT. Radiomics parameters were obtained from high-resolution T2-weighted images and selected to construct a radiomics signature. Then, radiomics nomogram construction integrated patient variables and the radiomics signature. The resulting radiomics nomogram was utilized to assess the tumor regression grade (TRG). Diagnostic performance was determined by generating receiver operating characteristic (ROC) curves and decision curve analysis (DCA).ResultsSix optimal features related to TRG were obtained to construct a radiomics signature. The nomogram combining the radiomics signature with age and mucin deposit outperformed the radiomics signature alone in the training (AUC, 0.950 vs 0.843, p < 0.05) and validation (AUC, 0.868 vs 0.719, p < 0.05) cohorts. DCA demonstrated a clinical utility for the radiomics nomogram model.ConclusionsThe established quantitative MRI-based radiomics nomogram is effective in predicting treatment response to neoadjuvant therapy in patients with RMAC.

scholarly journals Pathological tumor regression grade of metastatic tumors in lymph node predicts prognosis in esophageal cancer patients

2018 ◽  
Vol 109 (6) ◽  
pp. 2046-2055 ◽  
Author(s):  
Tomohiro Kadota ◽  
Ken Hatogai ◽  
Tomonori Yano ◽  
Takeo Fujita ◽  
Takashi Kojima ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Lymph Node ◽  
Cancer Patients ◽  
Tumor Regression ◽  
Tumor Regression Grade ◽  
Metastatic Tumors ◽  
Regression Grade

scholarly journals Evaluating treatment response to neoadjuvant chemoradiotherapy in rectal cancer using various MRI-based radiomics models

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhihui Li ◽  
Xiaolu Ma ◽  
Fu Shen ◽  
Haidi Lu ◽  
Yuwei Xia ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Treatment Response ◽  
Nearest Neighbor ◽  
Tumor Regression ◽  
Locally Advanced ◽  
Pathologic Complete Response ◽  
Neoadjuvant Chemoradiotherapy ◽  
Principal Component ◽  
Tumor Regression Grade ◽  
K Nearest Neighbor

Abstract Background To validate and compare various MRI-based radiomics models to evaluate treatment response to neoadjuvant chemoradiotherapy (nCRT) of rectal cancer. Methods A total of 80 patients with locally advanced rectal cancer (LARC) who underwent surgical resection after nCRT were enrolled retrospectively. Rectal MR images were scanned pre- and post-nCRT. The radiomics features were extracted from T2-weighted images, then reduced separately by least absolute shrinkage and selection operator (LASSO) and principal component analysis (PCA). Four classifiers of Logistic Regression, Random Forest (RF), Decision Tree and K-nearest neighbor (KNN) models were constructed to assess the tumor regression grade (TRG) and pathologic complete response (pCR), respectively. The diagnostic performances of models were determined with leave-one-out cross-validation by generating receiver operating characteristic curves and decision curve analysis. Results Three features related to the TRG and 11 features related to the pCR were obtained by LASSO. Top five principal components representing a cumulative contribution of 80% to overall features were selected by PCA. For TRG, the area under the curve (AUC) of RF model was 0.943 for LASSO and 0.930 for PCA, higher than other models (P < 0.05 for both). As for pCR, the AUCs of KNN for LASSO and PCA were 0.945 and 0.712, higher than other models (P < 0.05 for both). The DCA showed that LASSO algorithm was clinically superior to PCA. Conclusion MRI-based radiomics models demonstrated good performance for evaluating the treatment response of LARC after nCRT and LASSO algorithm yielded more clinical benefit.

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