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Impact of Perineural Invasion and Preexisting Type 2 Diabetes on Patients with Esophageal Squamous Cell Carcinoma Receiving Neoadjuvant Chemoradiotherapy.

ABSTRACT: Neoadjuvant chemoradiotherapy (neoCRT) followed by surgery is the cornerstone treatment strategy in locally advanced esophageal squamous cell carcinoma (ESCC). Despite this high- intensity multimodality therapy, most patients still experience recurrences and metastases, especially those who do not achieve a pathological complete response (pCR) after neoCRT. Here, we focused on identifying poor prognostic factors. In this retrospective cohort study; we enrolled 140 patients who completed neoCRT plus surgery treatment sequence with no interval metastasis. Overall, 45 of 140 patients (32.1%) achieved a pCR. The overall survival, disease-free survival (DFS), and metastasis-free survival was significantly better in patients with a pCR than in patients with a non-pCR. In the non-pCR subgroup, the presence of perineural invasion (PNI) and preexisting type 2 diabetes (T2DM) were two factors adversely affecting DFS. After adjusting for other factors, multivariate analysis showed that the hazard ratio (HR) was 2.354 (95% confidence interval [CI] 1.240-4.467, p = 0.009) for the presence of PNI and 2.368 (95% CI 1.351-4.150, p = 0.003) for preexisting T2DM. Patients with a combination of both factors had the worst survival. In conclusion, PNI and preexisting T2DM may adversely affect the prognosis of patients with ESCC receiving neoadjuvant chemoradiotherapy.

SUBMITTER: Su NW

PROVIDER: S-EPMC9954405 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Impact of Perineural Invasion and Preexisting Type 2 Diabetes on Patients with Esophageal Squamous Cell Carcinoma Receiving Neoadjuvant Chemoradiotherapy.

Su Nai-Wen NW Mok Lai-Man LM Chan Mei-Lin ML Liu Hung-Chang HC Chang Wei-Chin WC Yun Chun-Ho CH Shieh Tze-Yu TY Wu Ming-Che MC Lin Huan-Chau HC Huang Wen-Chien WC Chen Yu-Jen YJ

Cancers 20230209 4

Neoadjuvant chemoradiotherapy (neoCRT) followed by surgery is the cornerstone treatment strategy in locally advanced esophageal squamous cell carcinoma (ESCC). Despite this high- intensity multimodality therapy, most patients still experience recurrences and metastases, especially those who do not achieve a pathological complete response (pCR) after neoCRT. Here, we focused on identifying poor prognostic factors. In this retrospective cohort study; we enrolled 140 patients who completed neoCRT p ...[more]

PMID: 36831461

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Project description:ImportanceThe association of neoadjuvant chemoimmunotherapy (NCIT) vs chemoradiotherapy (NCRT) with tumor downstaging and survival in locally advanced esophageal squamous cell carcinoma (ESCC) remains unclear because of limited evidence.ObjectiveTo compare the associations of NCIT and NCRT with tumor regression and long-term survival in patients with locally advanced ESCC.Design, setting, and participantsIn this comparative effectiveness research study, from January 2016 to March 2023, patients with locally advanced ESCC who underwent esophagectomy following NCRT or NCIT were identified from a prospective database of 8 high-volume esophageal surgery centers in China. Follow-up began on the date of surgery and continued until the last recorded contact or March 2024, whichever occurred first. Data were analyzed between April and September 2024.Main outcomes and measuresThe primary end points were 2-year overall survival (OS) and disease-free survival (DFS). Secondary end points included major pathologic response (MPR) and pathologic complete response (pCR). Cox proportional hazard regression analysis was used to investigate the risk factors for OS and DFS.ResultsThe study included 1428 patients (median [IQR] age, 63 [57-68] years; 1184 men [82.9%]), with 704 patients in the NCRT group and 724 patients in the NCIT group. After propensity score matching, there were 532 patients in each group. The 2-year OS (81.3% vs 71.3%; hazard ratio, 1.57; 95% CI, 1.26-1.96; P < .001) and DFS (73.9% vs 63.4%; hazard ratio, 1.37; 95% CI, 1.11-1.69; P < .001) rates were significantly higher in NCIT group than in the NCRT group. The NCRT group had a higher MPR rate than that of the NCIT group (71.8% vs 61.5%), whereas the pCR rates were similar (25.9% vs 22.9%). Multivariable Cox analysis demonstrated that NCIT and MPR were independently associated with both OS and DFS. The NCIT group exhibited a lower overall recurrence rate (126 patients [23.7%] vs 190 patients [35.7%]) and distant metastasis rate (72 patients [13.5%] vs 133 patients [25.0%]), although locoregional metastasis rates were similar (98 patients [18.4%] vs 111 patients [20.9%]). Better OS and DFS were obtained for the NCIT group than for the NCRT group, regardless of whether adjuvant immunotherapy was given.Conclusions and relevanceCompared with NCRT, patients with locally advanced ESCC receiving NCIT had better 2-year OS and DFS. The decrease in distant metastasis may be the main reason, but further prospective randomized clinical trials are needed to verify this finding.

Project description:ObjectivesThis study aimed to develop and validate a deep-learning radiomics model using CT, T2, and DWI images for predicting pathological complete response (pCR) in patients with esophageal squamous cell carcinoma (ESCC) undergoing neoadjuvant chemoradiotherapy (nCRT).Materials and methodsPatients with ESCC undergoing nCRT followed by surgery were retrospectively enrolled from three institutions and divided into training and testing cohorts. Both traditional and deep-learning radiomics features were extracted from pre-treatment CT, T2, and DWI. Multiple radiomics models were developed, both single modality and integrated, using machine learning algorithms. The models' performance was assessed using receiver operating characteristic curve analysis, with the area under the curve (AUC) as a primary metric, alongside sensitivity and specificity from the cut-off analysis.ResultsThe study involved 151 patients, among whom 63 achieved pCR. The training cohort consisted of 89 patients from Institution 1 (median age 62, 73 males) and the testing cohort included 52 patients from Institution 2 (median age 62, 41 males), and 10 in a clinical trial from Institution 3 (median age 69, 9 males). The integrated model, combining traditional and deep learning radiomics features from CT, T2, and DWI, demonstrated the best performance with an AUC of 0.868 (95% CI: 0.766-0.959), sensitivity of 88% (95% CI: 73.9-100), and specificity of 78.4% (95% CI: 63.6-90.2) in the testing cohort. This model outperformed single-modality models and the clinical model.ConclusionA multimodality deep learning radiomics model, utilizing CT, T2, and DWI images, was developed and validated for accurately predicting pCR of ESCC following nCRT.Critical relevance statementOur research demonstrates the satisfactory predictive value of multimodality deep learning radiomics for the response of nCRT in ESCC and provides a potentially helpful tool for personalized treatment including organ preservation strategy.Key pointsAfter neoadjuvant chemoradiotherapy, patients with ESCC have pCR rates of about 40%. The multimodality deep learning radiomics model, could predict pCR after nCRT with high accuracy. The multimodality radiomics can be helpful in personalized treatment of esophageal cancer.

Dataset Information

Impact of Perineural Invasion and Preexisting Type 2 Diabetes on Patients with Esophageal Squamous Cell Carcinoma Receiving Neoadjuvant Chemoradiotherapy.

Publications

Impact of Perineural Invasion and Preexisting Type 2 Diabetes on Patients with Esophageal Squamous Cell Carcinoma Receiving Neoadjuvant Chemoradiotherapy.

Similar Datasets

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