1
|
Duan X, Zhao F, Shang X, Yue J, Chen C, Ma Z, Chen Z, Zhang C, Pang Q, Zhang W, Abbas AE, Jiang H. Neoadjuvant chemoimmunotherapy was associated with better short-term survival of patients with locally advanced esophageal squamous cell carcinoma compared to neoadjuvant chemoradiotherapy. Cancer Med 2024; 13:e70113. [PMID: 39136674 PMCID: PMC11321237 DOI: 10.1002/cam4.70113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 07/29/2024] [Accepted: 08/06/2024] [Indexed: 08/15/2024] Open
Abstract
INTRODUCTION The chemotherapy and immunotherapy combination is currently the primary strategy to treat metastatic esophageal squamous cell carcinoma (ESCC). Neoadjuvant chemoimmunotherapy (NCIT) is being intensively investigated for treating locally advanced ESCC. OBJECTIVE We compared the efficacy and safety of NCIT and neoadjuvant chemoradiotherapy (NCRT) to treat locally advanced ESCC. METHODS We included 214 locally advanced ESCC patients who were administered neoadjuvant therapy from May 2014 to April 2022. The patients were grouped according to two neoadjuvant protocols (NCIT and NCRT) routinely used at our institution. Perioperative findings, pathological results, and survival data were compared between the two groups by conducting unmatched and 1:1 propensity score matching (PSM) analyses. RESULTS Following 1:1 PSM analysis of the confounders, 66 patients were allocated to each of the two groups. Time span between neoadjuvant therapy completion and esophagectomy was significantly longer after NCRT than that after NCIT (47.1 ± 13.2 days vs. 34.7 ± 8.8 days; p < 0.001). The NCIT group exhibited significantly greater number of harvested lymph nodes than the NCRT group (33.6 ± 12.7 vs. 21.7 ± 10.2; p < 0.001). The pathological complete response and major pathological response rates were similar between the two groups [NCIT group: 25.8% (17/66) and 62.1% (41/66), respectively; NCRT group: 27.3% (18/66) and 56.1% (37/66), respectively (p > 0.05)]. The overall incidence of pneumonia, anastomotic leakage, or postoperative complications did not differ significantly between the two groups. The 2-year cumulative overall survival rates and the 2-year disease-free survival rates of the NCIT and NCRT groups were 80.2% and 62.2%, respectively (p = 0.029) and 70.0% and 50.8%, respectively (p = 0.023). CONCLUSION In locally advanced ESCC patients, short-term survival after NCIT is superior to that after NCRT, with similar perioperative and pathological outcomes.
Collapse
Affiliation(s)
- Xiaofeng Duan
- Department of Minimally Invasive Esophageal SurgeryTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and TherapyTianjinChina
| | - Fangdong Zhao
- Department of Radiation OncologyTianjin Medical University Cancer Institute and HospitalTianjinChina
| | - Xiaobin Shang
- Department of Minimally Invasive Esophageal SurgeryTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and TherapyTianjinChina
| | - Jie Yue
- Department of Minimally Invasive Esophageal SurgeryTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and TherapyTianjinChina
| | - Chuangui Chen
- Department of Minimally Invasive Esophageal SurgeryTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and TherapyTianjinChina
| | - Zhao Ma
- Department of Minimally Invasive Esophageal SurgeryTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and TherapyTianjinChina
| | - Zuoyu Chen
- Department of Minimally Invasive Esophageal SurgeryTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and TherapyTianjinChina
| | - Chen Zhang
- Department of Minimally Invasive Esophageal SurgeryTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and TherapyTianjinChina
| | - Qingsong Pang
- Department of Radiation OncologyTianjin Medical University Cancer Institute and HospitalTianjinChina
| | - Wencheng Zhang
- Department of Radiation OncologyTianjin Medical University Cancer Institute and HospitalTianjinChina
| | - Abbas E. Abbas
- Department of Thoracic Oncology, Lifespan Health SystemWarren Alpert Medical School of Brown UniversityProvidenceRhode IslandUSA
| | - Hongjing Jiang
- Department of Minimally Invasive Esophageal SurgeryTianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and TherapyTianjinChina
| |
Collapse
|
2
|
Yang X, Yin H, Zhang S, Jiang T, Gu J, Jiao H, Wang H, Liang F, Xu S, Fan H, Ding J, Ge D, Wang Q, Yin J, Tan L. Perioperative outcomes and survival after neoadjuvant immunochemotherapy for locally advanced esophageal squamous cell carcinoma. J Thorac Cardiovasc Surg 2024:S0022-5223(24)00542-7. [PMID: 38944271 DOI: 10.1016/j.jtcvs.2024.06.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 04/22/2024] [Accepted: 06/10/2024] [Indexed: 07/01/2024]
Abstract
OBJECTIVE This study aimed to compare the difference in perioperative outcomes and prognosis between neoadjuvant immunochemotherapy and neoadjuvant chemoradiotherapy for locally advanced esophageal squamous cell carcinoma. METHODS The patients with locally advanced esophageal squamous cell carcinoma receiving neoadjuvant immunochemotherapy or neoadjuvant chemoradiotherapy were identified from a prospectively maintained database at Zhongshan Hospital of Fudan University between January 2018 and March 2022. Propensity score matching was performed to balance the 2 groups. RESULTS A total of 124 patient pairs were enrolled in the final analysis. The complete pathological response rate (20.2% vs 29.0%, P = .140) was similar in the 2 groups, whereas the lower major pathological response rate (44.4% vs 61.3%, P = .011) was observed in the neoadjuvant immunochemotherapy group. Neoadjuvant immunochemotherapy was associated with a lower rate of adverse events (42.7% vs 55.6%, P = .047) without additional postoperative complications (38.7% vs 35.5%, P = .693). The neoadjuvant immunochemotherapy group had lower distant metastasis (6.5% vs 16.1%, P = .027) and overall recurrence (11.3% vs 23.4%, P = .019) in the postoperative 1 year. Also, neoadjuvant immunochemotherapy was associated with better progression-free survival (hazard ratio, 0.50; 95% CI, 0.32-0.77; P = .002). Cox proportional hazard analysis showed that neoadjuvant immunochemotherapy (univariable: hazard ratio, 0.55; 95% CI, 0.37-0.82; P = .003; multivariable: hazard ratio, 0.44; 95% CI, 0.29-0.65; P < .001) was one of the independent prognostic factors for progression-free survival. The 2 groups had similar overall survival (hazard ratio, 0.62; 95% CI, 0.36-1.09; P = .094) at the latest follow-up. CONCLUSIONS This retrospective study showed that neoadjuvant immunochemotherapy was safe and effective for patients with locally advanced esophageal squamous cell carcinoma. Further verification is needed in randomized controlled trials.
Collapse
Affiliation(s)
- Xinyu Yang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Yin
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shaoyuan Zhang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Tian Jiang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jianmin Gu
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Heng Jiao
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Hao Wang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Fei Liang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Clinical Statistics Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Songtao Xu
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Thoracic Surgery, Shanghai Geriatric Medical Center, Shanghai, China
| | - Hong Fan
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Thoracic Surgery, Xiamen Branch, Zhongshan Hospital, Fudan University, Fujian, China
| | - Jianyong Ding
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Di Ge
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Qun Wang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jun Yin
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lijie Tan
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China; Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China.
| |
Collapse
|
3
|
Cao Y, Huang B, Tang H, Dong D, Shen T, Chen X, Feng X, Zhang J, Shi L, Li C, Jiao H, Tan L, Zhang J, Li H, Zhang Y. Online tools to predict individualised survival for primary oesophageal cancer patients with and without pathological complete response after neoadjuvant therapy followed by oesophagectomy: development and external validation of two independent nomograms. BMJ Open Gastroenterol 2024; 11:e001253. [PMID: 38538088 PMCID: PMC10982901 DOI: 10.1136/bmjgast-2023-001253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 01/01/2024] [Indexed: 04/04/2024] Open
Abstract
OBJECTIVE This study aimed to develop and validate robust predictive models for patients with oesophageal cancer who achieved a pathological complete response (pCR) and those who did not (non-pCR) after neoadjuvant therapy and oesophagectomy. DESIGN Clinicopathological data of 6517 primary oesophageal cancer patients who underwent neoadjuvant therapy and oesophagectomy were obtained from the National Cancer Database for the training cohort. An independent cohort of 444 Chinese patients served as the validation set. Two distinct multivariable Cox models of overall survival (OS) were constructed for pCR and non-pCR patients, respectively, and were presented using web-based dynamic nomograms (graphical representation of predicted OS based on the clinical characteristics that a patient could input into the website). The calibration plot, concordance index and decision curve analysis were employed to assess calibration, discrimination and clinical usefulness of the predictive models. RESULTS In total, 13 and 15 variables were used to predict OS for pCR and non-pCR patients undergoing neoadjuvant therapy followed by oesophagectomy, respectively. Key predictors included demographic characteristics, pretreatment clinical stage, surgical approach, pathological information and postoperative treatments. The predictive models for pCR and non-pCR patients demonstrated good calibration and clinical utility, with acceptable discrimination that surpassed that of the current tumour, node, metastases staging system. CONCLUSIONS The web-based dynamic nomograms for pCR (https://predict-survival.shinyapps.io/pCR-eso/) and non-pCR patients (https://predict-survival.shinyapps.io/non-pCR-eso/) developed in this study can facilitate the calculation of OS probability for individual patients undergoing neoadjuvant therapy and radical oesophagectomy, aiding clinicians and patients in making personalised treatment decisions.
Collapse
Affiliation(s)
- Yuqin Cao
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Binhao Huang
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai, Shanghai, China
- Department of Gastric Surgery, Fudan University Shanghai Cancer Center, Shanghai, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Cardiothoracic Surgery, University of Pittsburgh Medical Center Health System, Pittsburgh, Pennsylvania, USA
| | - Han Tang
- Department of Thoracic Surgery, Zhongshan Hospital Fudan University, Shanghai, Shanghai, China
| | - Dong Dong
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Tianzheng Shen
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Xiang Chen
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Xijia Feng
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Jiahao Zhang
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Liqiang Shi
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Chengqiang Li
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Heng Jiao
- Department of Thoracic Surgery, Zhongshan Hospital Fudan University, Shanghai, Shanghai, China
| | - Lijie Tan
- Department of Thoracic Surgery, Zhongshan Hospital Fudan University, Shanghai, Shanghai, China
| | - Jie Zhang
- Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai, Shanghai, China
- Department of Cardiothoracic Surgery, University of Pittsburgh Medical Center Health System, Pittsburgh, Pennsylvania, USA
| | - Hecheng Li
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| | - Yajie Zhang
- Department of Thoracic Surgery, Shanghai Jiao Tong University Medical School Affiliated Ruijin Hospital, Shanghai, Shanghai, China
| |
Collapse
|
4
|
Qi WX, Li S, Xiao J, Li H, Chen J, Zhao S. A machine learning approach using 18F-FDG PET and enhanced CT scan-based radiomics combined with clinical model to predict pathological complete response in ESCC patients after neoadjuvant chemoradiotherapy and anti-PD-1 inhibitors. Front Immunol 2024; 15:1351750. [PMID: 38352868 PMCID: PMC10863474 DOI: 10.3389/fimmu.2024.1351750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 01/12/2024] [Indexed: 02/16/2024] Open
Abstract
Background We aim to evaluate the value of an integrated multimodal radiomics with machine learning model to predict the pathological complete response (pCR) of primary tumor in a prospective cohort of esophageal squamous cell carcinoma (ESCC) treated with neoadjuvant chemoradiotherapy (nCRT) and anti-PD-1 inhibitors. Materials and methods Clinical information of 126 ESCC patients were included for analysis. Radiomics features were extracted from 18F-FDG PET and enhanced plan CT images. Four machine learning algorithms, including SVM (Support Vector Machine), Random Forest (RF), and eXtreme Gradient Boosting (XGB) and logistic regression (LR), were applied using k-fold cross-validation to predict pCR after nCRT. The predictive ability of the models was assessed using receiver operating characteristics (ROC) curve analysis. Results A total of 842 features were extracted. Among the four machine learning algorithms, SVM achieved the most promising performance on the test set for PET(AUC:0.775), CT (AUC:0.710) and clinical model (AUC:0.722). For all combinations of various modalities-based models, the combination model of 18 F-FDG PET, CT and clinical features with SVM machine learning had the highest AUC of 0.852 in the test set when compared to single-modality models in various algorithms. The other combined models had AUC ranged 0.716 to 0.775. Conclusion Machine learning models utilizing radiomics features from 18F-FDG PET and enhanced plan CT exhibit promising performance in predicting pCR in ESCC after nCRT and anti-PD-1 inhibitors. The fusion of features from multiple modalities radiomics and clinical features enhances the better predictive performance compared to using a single modality alone.
Collapse
Affiliation(s)
- Wei-Xiang Qi
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shuyan Li
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jifeng Xiao
- Real Time Lab, Shenzhen United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China
| | - Huan Li
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jiayi Chen
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Shengguang Zhao
- Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| |
Collapse
|
5
|
Su F, Yang X, Yin J, Shen Y, Tan L. ASO Author Reflections: The Validity of Using Pathological Response as a Surrogate for Overall Survival in Neoadjuvant Studies for Esophageal Cancer: A Systematic Review and Meta-analysis. Ann Surg Oncol 2023; 30:7507-7508. [PMID: 37349616 DOI: 10.1245/s10434-023-13788-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 06/12/2023] [Indexed: 06/24/2023]
Affiliation(s)
- Feng Su
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xinyu Yang
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jun Yin
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yaxing Shen
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Lijie Tan
- Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China
| |
Collapse
|