scholarly journals O4 Neural network image capture to predict response of oesophageal adenocarcinoma to neoadjuvant therapy

2021 ◽  
Vol 108 (Supplement_5) ◽  
Author(s):  
S Rahman ◽  
J Early ◽  
B Sharpe ◽  
M Lloyd ◽  
B Grace ◽  
...  
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Neoadjuvant Therapy ◽  
Locally Advanced ◽  
Neoadjuvant Treatment ◽  
Oesophageal Adenocarcinoma ◽  
Tumour Regression ◽  
Tumour Regression Grade ◽  
Pre Treatment ◽  
Diagnostic Biopsies

Abstract Introduction Locally advanced oesophageal adenocarcinoma is typically treated with neoadjuvant chemotherapy (NACT) or chemoradiotherapy (NACRT) followed by surgery. Significant benefit to neoadjuvant treatment however is confined to a minority of patients (<25%) and there are no reliable means of establishing prior to treatment in whom this benefit will occur. In this study, we assessed the utility of features extracted from high-resolution digital microscopy of pre-treatment biopsies in predicting response to neoadjuvant therapy in a machine-learning based modelling framework. Method A total of 102 cases were included in the study. Pre-treatment clinical information, including TNM staging, was obtained, along with diagnostic biopsies. Diagnostic biopsies were converted into high-resolution whole slide-images and features extracted using a pre-trained convolutional neural network (Xception). Elastic net regression models were then trained and validated with bootstrapping with 1000 resampled datasets. The response was considered according to Mandard tumour regression grade (TRG). Result There were 45 (44.1%) responders (TRG1-2) and 57 (57%) non-responders (TRG3-5) in the dataset. 34 patients (33.3%) received NACT and 68 (66.7%) received NACRT. A model trained with RNA-seq data achieved fair performance only in predicting response (AUC 0.598 95% CI 0.593–0.603), which was far exceeded by use of segmented diagnostic biopsy images (AUC 0.872 95% CI 0.869–0.875), which also produced well calibrated predictions of risk. Conclusion Despite using a small dataset, impressive performance in classifying response to neoadjuvant treatment can be achieved, particularly using automated image classification. Further study to refine the methodology is required before expansion to clinical settings. Take-home Message Response to neoadjuvant treatment for oesophageal cancer can be predicted from diagnostic biopsies

Efficacy and safety of camrelizumab combined with FLOT versus FLOT alone as neoadjuvant therapy in patients with resectable locally advanced gastric and gastroesophageal junction adenocarcinoma who received D2 radical gastrectomy.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16020-e16020
Author(s):  
Ning Liu ◽  
Zimin Liu ◽  
Yanbing Zhou ◽  
Zhaojian Niu ◽  
Haitao Jiang ◽  
...  
Keyword(s):  
Neoadjuvant Therapy ◽  
Intraoperative Complications ◽  
Gastroesophageal Junction ◽  
Locally Advanced ◽  
Neoadjuvant Treatment ◽  
Tumour Regression ◽  
R0 Resection ◽  
Resection Rate ◽  
Tumour Regression Grade ◽  
Ecog Ps

e16020 Background: Docetaxel-based neoadjuvant chemotherapy has been suggested to be beneficial in patients with locally advanced gastric and gastro-oesophageal junction cancer (GC/GEJC). And immunotherapy also show promising treatment efficacy for advanced GC/GEJC. Here we compared the safety and efficacy of camrelizumab combined with chemotherapy versus chemotherapy alone as the neoadjuvant therapy for patients with resectable locally advanced GC/GEJC. Methods: Eligible patients diagnosed as resectable locally advanced GC/GEJC were randomized to receive neoadjuvant treatment, in arm A, the patients received FLOT alone (docetaxel 50 mg/m²; oxaliplatin 85 mg/m²; leucovorin 200 mg/m²; 5-FU 2600 mg/m², every 2 weeks), in arm B, the patients received FLOT combined with camrelizumab(camrelizumab 200mg intravenously every 3 weeks). Eligible patients underwent gastrectomy with D2 lymph node dissection. The primary end point of this trial was pCR rate and R0 resection rate, and the secondary end points were ORR,PFS, OS and safety profile. Results: From January 15 2020 to January 15 2021, 24 patients were recruited (11 patients in arm A and 13 patients in arm B). 19 patients had completed planned neoadjuvant treatment for 4 cycles (9 pts in the arm A, 10 ptsin the arm B). Two patients in the arm A were waiting for gastrectomy. This analysis was based on the 17 pts. In the arm A, the median age was 61 years (47-72 years) and a total of 5 males and 4 females, ECOG PS 0 (n = 1), ECOG PS 1 (n = 8). In the arm B, the median age was 63 years (57-71 years) and a total of 9 males and 1 females, all patients with ECOG PS 1. The R0 resection rate was high in arm B compared with arm A (10/10,100% vs. 5/7, 71.4%). No pCR were observed in the two arms. Tumour regression grade were as follows:TRG1 [arm A 0% (0/7), arm B 10% (1/10)], TRG2 [arm A 43% (3/7), arm B 60% (6/10)], TRG3 [arm A 29% (2/7), arm B 30% (3/10)].There was a significantly higher proportion of patients achieved a postoperative ypN0 in the arm B than arm A(60% vs 0%), which had preoperative clinical stage cT3-4N+M0. Postoperative pathologic staging was as follows: ypT1 [arm A 14% (1/7); armB 30% (3/10)]. ypT2 [armA 0% (0/7); armB 30% (3/10)]. ypT3 [arm A 29% (2/7); arm B 20% (2/10)]. ypT4 [armA 29% (2/7); armB 20% (2/10)]. Neither serious intraoperative complications nor immune-related adverse events were observed during perioperation. Treatment-related AEs neutropenia and leukopenia were manageable and there was no treatment-related death. Conclusions: Camrelizumab combined with FLOT showed promising efficacy as neoadjuvant treatment for patients with locally advanced gastric or GEJ adenocarcinoma, with low complications and acceptable toxicity. Clinical trial information: ChiCTR2000030610.

scholarly journals O29: PREDICTING RESPONSE TO NEOADJUVANT THERAPY IN OESOPHAGEAL ADENOCARCINOMA PRE-TREATMENT BIOPSIES

2021 ◽  
Vol 108 (Supplement_1) ◽  
Author(s):  
M Lloyd ◽  
F Izadi ◽  
S Rahman ◽  
R Walker ◽  
A Hayden ◽  
...  
Keyword(s):  
Pilot Study ◽  
Neoadjuvant Therapy ◽  
Small Sample Size ◽  
Expression Profiles ◽  
Locally Advanced ◽  
Small Sample ◽  
Oesophageal Adenocarcinoma ◽  
Tumour Regression ◽  
Precision Therapy ◽  
Pre Treatment

Abstract Aims We currently cannot predict which patients with locally advanced oesophageal adenocarcinoma will be amongst the 15-20% to gain a clinically important response to neoadjuvant therapy (NAT). This pilot study aimed to identify differentially expressed genes from oesophageal adenocarcinoma pre-treatment biopsies between responders and non-responders to NAT and develop methodology for predicting response. Method Response to NAT was assessed pathologically using Tumour Regression Grading (TRG). Pre-treatment formalin-fixed paraffin embedded samples were analysed with two nuclease protection assays (EdgeSeq, HTG = Oncology Biomarker Panel (OBP) and Precision Immuno-Oncology Panel (PIP)). Sequencing was performed on the NextSeq500 (Illumina). Result Whilst there was no difference in pre-treatment characteristics, responders (TRG1-2, n=26) had significantly better post-treatment pathology and overall survival than non-responders (TRG4-5, n=30). Genes up-regulated in responders were involved in regulating cell cycling, whereas genes up-regulated in non-responders were involved in cytokine signalling and the immune response. Neuronal artificial network models could predict response to NAT with overall accuracy of 73% and 68% for the OBP and PIP, respectively, which is promising considering the small sample size. As no model will be 100% accurate, we developed a model that could take patient's views into consideration with an adjustable probability threshold for classification. Conclusion This pilot study informs a biologically sound hypothesis for the basis of response to NAT and suggests prediction from pre-treatment biopsies may be possible using EdgeSeq. We now aim to validate these results in a larger study to inform a bespoke classifier of response to enable delivery of precision therapy. Take-home message In oesophageal adenocarcinoma, responders and non-responders to neoadjuvant therapy have different expression profiles. Through using EdgeSeq in larger studies, we may be able to predict which patients will respond to treatment, allowing for delivery of precision therapy.

scholarly journals P-OGC57 Predicting survival and response to therapy using diagnostic biopsies: A machine learning approach to facilitate treatment decisions for oesophageal adenocarcinoma

2021 ◽  
Vol 108 (Supplement_9) ◽  
Author(s):  
Saqib Rahman ◽  
Joseph Early ◽  
Ben Sharpe ◽  
Megan Lloyd ◽  
Matt De Vries ◽  
...  
Keyword(s):  
Machine Learning ◽  
Overall Survival ◽  
High Resolution ◽  
Clinical Data ◽  
Neoadjuvant Treatment ◽  
Response To Therapy ◽  
Oesophageal Adenocarcinoma ◽  
Complex Data ◽  
Pre Treatment ◽  
Diagnostic Biopsies

Abstract Background Standard of care for locally advanced oesophageal adenocarcinoma is neoadjuvant chemotherapy or chemoradiotherapy followed by surgery. Only a minority of patients (<25%) derive significant survival benefit from neoadjuvant treatment and there are no reliable means of establishing prior to treatment in whom this benefit will occur. Moreover, accurate prediction of survival prior to treatment is also not possible. The availability of machine learning techniques provides the potential to use complex data sources to answer these problems. In this study, we assessed the utility of high-resolution digital microscopy of pre-treatment biopsies in predicting both response to neoadjuvant therapy and overall survival. Methods A total of 157 cases were included in the study. Pre-treatment clinical information, including neoadjuvant treatment, was obtained, along with diagnostic biopsies. Diagnostic biopsies were converted into high-resolution whole slide-images and features extracted using the pre-trained convolutional neural network Xception. Single representative images were converted into patches from which predictive models were trained. Elastic net regression classifiers were derived and validated with bootstrapping and 1000 resampled datasets. The response to treatment was considered according to Mandard tumour regression grade (TRG). Model performance was quantified using the C-index (for TRG) and time-dependent AUC (tAUC, fo Overall survival) along with calibration plots. Results Median survival was 78.9months (95%CI 35.9 months – not reached). Survival at 5-years was 52.1%. Neoadjuvant treatment was received by 123 patients (78.3%), with a significant response seen in 45 cases (36.6%). A response was more likely in those patients who received chemoradiotherapy than chemotherapy (53.3% vs 23.1% p < 0.001) and in older patients (median age 69.4 vs 66.0 years, p = 0.038), with other characteristics similar. A predictive model for response to neoadjuvant treatment derived from image features and clinical data achieved good discrimination (C-index 0.767, 95%CI 0.701-0.833) and calibration. Accuracy of prediction of overall survival was more modest (tAUC 0.640, 95%CI 0.518-0.762). Conclusions Using a small dataset, utility of a feature extraction pipeline in prediction of patient level outcomes has been demonstrated. This was more marked in prediction of response to neoadjuvant treatment than overall survival, which may reflect the importance of pre-treatment clinical data in determining the former outcome. Further study to refine the methodology and confirmation in larger datasets are required before expansion to clinical settings.

scholarly journals O-OGC06 Genomic analysis of response to neoadjuvant chemotherapy in oesophageal adenocarcinoma

2021 ◽  
Vol 108 (Supplement_9) ◽  
Author(s):  
Stella Breininger ◽  
Fereshteh Izadi ◽  
Benjamin Sharpe ◽  
Maria Secrier ◽  
Jane Gibson ◽  
...  
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Locally Advanced ◽  
Genomic Analysis ◽  
Standard Of Care ◽  
Response Prediction ◽  
Oesophageal Adenocarcinoma ◽  
Comparative Genomic ◽  
Tumour Regression ◽  
Tumour Regression Grade ◽  
Almost All

Abstract Background Oesophageal adenocarcinoma (OAC) is the ninth most common cancer worldwide, with an estimated mortality of over 500,000 deaths yearly. Neoadjuvant chemotherapy (NAC) followed by surgery is the standard of care (SOC) for locally advanced OAC. Although almost all patients receive chemotherapy as SOC, fewer than 20% obtain a clinically meaningful response and benefit before surgery. The OAC genome is complex and heterogeneous between patients, and it is not yet understood whether specific mutational patterns may result in chemotherapy sensitivity or resistance. Methods To identify associations between genomic events and response to NAC in OAC, a comparative genomic analysis was performed in 65 patients using whole-genome sequencing.  We defined response to NAC using Mandard Tumour Regression Grade (TRG), with responders classified as TRG1-2 (n = 27) and non-responders classified as TRG4-5 (n = 38). Results We report a higher non-synonymous mutation burden in responders (median 2.08/Mb vs 1.70/Mb, P = 0.036) and elevated copy number variation (CNV) in non-responders (282 vs 136/patient, P<0.001). We identified CNVs unique to each group, with cell cycle (CDKN2A, CCND1), c-Myc (MYC), RTK/PIK3 (KRAS, EGFR) and gastrointestinal differentiation (GATA6) pathway genes being specifically altered in non-responders. Of particular interest was the identification of the Neuron Navigator-3 (NAV3), a known tumour suppressor downstream of EGFR, which was mutated exclusively in non-responders with a frequency of 22%. Conclusions Our work characterises genetic features and mutations that are uniquely associated with response to NAC. We envision a treatment pipeline that incorporates driver mutation profiling in OAC, combining response prediction with targeted therapies to enhance response to NAC and improve survival outcomes.

scholarly journals P-OGC29 Pathological response profiles of FLOT and ECX neoadjuvant chemotherapy in oesophageal adenocarcinoma

2021 ◽  
Vol 108 (Supplement_9) ◽  
Author(s):  
William Knight ◽  
Arion Pepas ◽  
Melody Lee ◽  
Larysa Hlukha ◽  
Andrew Jackson ◽  
...  
Keyword(s):  
Neoadjuvant Chemotherapy ◽  
Primary Tumour ◽  
Neoadjuvant Treatment ◽  
Tumour Response ◽  
Oesophageal Adenocarcinoma ◽  
Tumour Regression ◽  
Tumour Regression Grade ◽  
Node Negative ◽  
Treatment Regimens ◽  
Nodal Upstaging

Abstract Background 70% of patients undergoing neo-adjuvant ECX chemotherapy for adenocarcinoma of the oesophagus, show little to know response in their primary tumour (Mandard 4,5). However, among these patients, those who have a complete nodal response (cN+ to ypN0) have equivalent survival to those with Mandard 1,2,3 tumours. FLOT chemotherapy has shown a survival advantage to ECX, however, rates of primary tumour response and nodal response are yet to be the focus of published study. Methods Retrospective cohort study comparing patients undergoing ECX and FLOT neoadjuvant chemotherapy between 2014 and 2021. Pathological outcomes were examined including, Mandard tumour regression grade (1-5), complete nodal response (cN+ to ypN0), clinically node negative nodal progression (cN0 to ypN+).   Results 226 patients had data available for analysis (193 ECX and 33 FLOT). 27% (52/193) of patients receiving ECX showed a response in the primary tumour (Mandard 1,2,3) compared to 63% (21/33) with patients undergoing FLOT (p < 0.001). Complete nodal response rates were 25% in ECX patients and 21% FLOT patients (p = 0.556). Clinically node negative nodal upstaging (cN0 to pN+) was higher among FLOT patients 30% (13/33) than ECX patients 12% (24/193) (p < 0.001). Conclusions FLOT chemotherapy confers improved primary tumour response. However, these findings were not echoed in locoregional nodal responses. Survival advantages with FLOT may result from improved responses in primary tumour and not improved systemic coverage. More data will be needed to explore this and over-come the confounding effect of staging inaccuracies. However, understanding systemic and loco-regional responses of different chemotherapy regimens will be needed to tailor future neoadjuvant treatment regimens.

scholarly journals Role of 18F-PET-CT to predict pathological response after neoadjuvant treatment of rectal cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Riccardo Caruso ◽  
Emilio Vicente ◽  
Yolanda Quijano ◽  
Hipolito Duran ◽  
Isabel Fabra ◽  
...  
Keyword(s):  
Rectal Cancer ◽  
Fdg Pet ◽  
Locally Advanced ◽  
Neoadjuvant Treatment ◽  
Standardized Uptake Value ◽  
Tumour Regression Grade ◽  
Pet Ct ◽  
Significant Difference ◽  
18F Fdg ◽  
Fdg Pet Ct

Abstract Objectives Neoadjuvant chemoradiation (nCRT) is universally considered to be a valid treatment to achieve downstaging, to improve local disease control and to obtain better resectability in locally advanced rectal cancer (LARC). The aim of this study is to correlate the change in the tumour 18F-FDG PET-CT standardized uptake value (SUV) before and after nCRT, in order to obtain an early prediction of the pathologic response (pR) achieved in patients with LARC. Data description We performed a retrospective analysis of patients with LARC diagnosis who underwent curative resection. All patients underwent a baseline 18F-FDG PET-CT scan within the week prior to the initiation of the treatment (PET-CT SUV1) and a second scan (PET-CT SUV2) within 6 weeks of the completion of nCRT. We evaluated the prognostic value of 18F-FDG PET-CT in terms of disease-free survival (DFS) and overall survival (OS) in patients with LARC.A total of 133 patients with LARC were included in the study. Patients were divided in two groups according to the TRG (tumour regression grade): 107 (80%) as the responders group (TRG0-TRG1) and 26 (25%) as the no-responders group (TRG2-TRG3). We obtained a significant difference in Δ%SUV between the two different groups; responders versus no-responders (p < 0.012). The results of this analysis show that 18F-FDG PET-CT may be an indicator to evaluate the pR to nCRT in patients with LARC. The decrease in 18F-FDG PET-CT uptake in the primary tumour may offer important information in order for an early identification of those patients more likely to obtain a pCR to nCRT and to predict those who are unlikely to significantly regress.

scholarly journals MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrea Delli Pizzi ◽  
Antonio Maria Chiarelli ◽  
Piero Chiacchiaretta ◽  
Martina d’Annibale ◽  
Pierpaolo Croce ◽  
...  
Keyword(s):  
Machine Learning ◽  
Rectal Cancer ◽  
Treatment Response ◽  
Randomized Clinical Trials ◽  
Locally Advanced ◽  
Neoadjuvant Treatment ◽  
Learning Model ◽  
Partial Least Square ◽  
Machine Learning Model ◽  
Pre Treatment

AbstractNeoadjuvant chemo-radiotherapy (CRT) followed by total mesorectal excision (TME) represents the standard treatment for patients with locally advanced (≥ T3 or N+) rectal cancer (LARC). Approximately 15% of patients with LARC shows a complete response after CRT. The use of pre-treatment MRI as predictive biomarker could help to increase the chance of organ preservation by tailoring the neoadjuvant treatment. We present a novel machine learning model combining pre-treatment MRI-based clinical and radiomic features for the early prediction of treatment response in LARC patients. MRI scans (3.0 T, T2-weighted) of 72 patients with LARC were included. Two readers independently segmented each tumor. Radiomic features were extracted from both the “tumor core” (TC) and the “tumor border” (TB). Partial least square (PLS) regression was used as the multivariate, machine learning, algorithm of choice and leave-one-out nested cross-validation was used to optimize hyperparameters of the PLS. The MRI-Based “clinical-radiomic” machine learning model properly predicted the treatment response (AUC = 0.793, p = 5.6 × 10–5). Importantly, the prediction improved when combining MRI-based clinical features and radiomic features, the latter extracted from both TC and TB. Prospective validation studies in randomized clinical trials are warranted to better define the role of radiomics in the development of rectal cancer precision medicine.

Phase-II study of toripalimab combined with neoadjuvant chemotherapy for the treatment of resectable esophageal squamous cell carcinoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16029-e16029
Author(s):  
Delin Liu ◽  
Qin Zhang ◽  
Jinghua Zhu ◽  
Ting Qian ◽  
Rong Yin ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Neoadjuvant Therapy ◽  
Squamous Cell ◽  
Phase Ii Study ◽  
Locally Advanced ◽  
Neoadjuvant Treatment ◽  
Neoadjuvant Radiochemotherapy ◽  
Grade 3

e16029 Background: Compared with neoadjuvant chemotherapy alone，Neoadjuvant radiochemotherapy can significantly increase pCR rate in esophageal squamous cell carcinoma and improve patient overall survival. However, the addition of radiotherapy increases the risk of adverse reactions and surgery. Neoadjuvant radiochemotherapy is currently used in < 5% of Chinese patients.The purpose of this phase II study is to assess the efficacy and safety of toripalimab combined with paclitaxel and cisplatin as neoadjuvant treatment for resectable locally advanced esophageal squamous cell carcinoma(clinical trial registration number: ChiCTR1900025318). Methods: Patients 18–75 years old with esophageal squamous cell carcinoma confirmed by endoscopic biopsy, assessed to be locally advanced esophageal squamous cell carcinoma (cT1–cT2, N+; cT3–cT4 a, any N), and expected to be resectable were given toripalimab (240 mg d1 + PTX 175 mg/m2 + PDD 75 mg/m2 q3w) before surgery for two treatment cycles, followed by efficacy assessment. A consultation meeting with thoracic surgeons was held to assess radical surgery for patients with resectable lesions 4–6 weeks after neoadjuvant therapy was completed. pCR and postoperative-stage statistical analysis were conducted based on postoperative pathology test results. These results were used to determine the efficacy and safety of PD-1 monoclonal antibody combined with chemotherapy as neoadjuvant therapy for locally advanced esophageal cancer. Results: By December 2020, 23 subjects were enrolled. Of the subjects, five withdrew without undergoing surgery (three subjects refused surgery and switched to radical radiochemotherapy, one subject progressed to PD after two cycles of neoadjuvant therapy and switched to palliative treatment, and one subject could not undergo surgery after neoadjuvant treatment and gave up the treatment) and 18 evaluable patients underwent surgery. The R0 resection rate was 100%, and T0–Tis 33.3% (6/18) achieved pCR. Among these patients, 61.1% (11/18) achieved T0–T1 after surgery, and 72.2% (13/18) achieved N0. Moreover, stage reduction effects were significant compared with preoperative TN staging. Common side-effects include nausea, vomiting, neutropenia, thrombocytopenia, rash, asthenia, constipation, and muscle soreness. Most adverse events were grades 1–2, and grades 3/4 adverse events include one case of grade 3 neutropenia and one case of grade 3 diarrhea (suspected immune-related colitis), which improved after symptomatic treatment. Conclusions: Toripalimab combined with the TP scheme showed preliminary efficacy and controllable safety in the treatment of resectable locally advanced esophageal squamous cell carcinoma and is worthy of further exploration. Clinical trial information: ChiCTR1900025318.

Camrelizumab combined with paclitaxel and nedaplatin as neoadjuvant therapy for locally advanced esophageal squamous cell carcinoma (ESPRIT): A phase Ⅱ, single-arm, exploratory research.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16033-e16033
Author(s):  
Jianqun Ma ◽  
Jinfeng Zhang ◽  
Yingnan Yang ◽  
Dayong Zheng ◽  
Xiaoyuan Wang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Neoadjuvant Therapy ◽  
Squamous Cell ◽  
Radical Surgery ◽  
Objective Response ◽  
Locally Advanced ◽  
Neoadjuvant Treatment ◽  
Therapeutic Effects

e16033 Background: Camrelizumab has been approved as a standard therapy in the second-line treatment of esophageal squamous cell carcinoma (ESCC). This study aimed to explore the efficacy and safety of camrelizumab combined with commonly used neoadjuvant chemotherapy (paclitaxel and platinum) in neoadjuvant treatment of ESCC. Methods: In this single-arm, phase Ⅱ study, patients with advanced ESCC who were expected to receive neoadjuvant therapy followed by radical surgery were recruited. The patients received 2-4 cycles of camrelizumab (200mg, iv, q3w) in combination with paclitaxel (155mg/m2, iv, q3w) and nedaplatin (80mg/m2, iv, q3w) as neoadjuvant therapy, and the therapeutic effects were determined every 2 cycles. The radical surgery was performed on patients whose tumors were evaluated as resectable. The primary endpoint was pCR, and the secondary endpoints were objective response rate (ORR) and disease control rate (DCR). Results: From May 2020 to January 2021, 24 patients with a median age of 60.5 years (50-73) were enrolled. Among them, 21 patients were available for efficacy analysis, of which 1 achieved complete response (CR), 7 achieved partial response (PR), and 13 had stable disease (SD). The ORR was 38.1% and DCR was 100%. The tumor in 10 patients shrank significantly after neoadjuvant therapy and these patients preferred radiotherapy instead of surgery as the radical therapeutic method. 2 patients abandoned surgery because of personal reasons. 2 patients were in the process of neoadjuvant therapy and had not undergone surgery yet. The remaining 7 patients underwent radical surgery and 4 patients (57.14%) achieved pCR (pT0N0M0). The main treatment-related grade 3/4 adverse event (AE) was neutropenia (1/21). All the AEs were manageable. The average intraoperative blood loss was 221mL and the average hospitalization time after operation was 12.7 days (range 8-19 days). No anastomotic leakage and treatment-related death occurred. Conclusions: Camrelizumab in combination with paclitaxel and platinum as a neoadjuvant therapy was well tolerated. The pCR rate of 57.14% was higher than the expected 40%. This encouraging result promoted us to continue this phase Ⅱ study. Clinical trial information: ChiCTR2000033761.

Sign in / Sign up

Export Citation Format

Share Document