The standard treatment for locally advanced rectal cancer is neoadjuvant chemoradiotherapy combined with surgery, but patients after the same treatment regimen show a large difference in outcomes. For patients with good response to neoadjuvant therapy, the waiting & observation scheme can be selected to avoid surgery and other complications. Therefore, accurate assessment of the response of patients with locally advanced rectal cancer after neoadjuvant therapy can better develop personalized treatment strategies. Current studies have found that blood sample detection, endoscopy, imaging examination and artificial intelligence have their own advantages and disadvantages in evaluating the response of neoadjuvant therapy. Therefore, this article reviews the application of different clinical tools in evaluating and predicting the response of neoadjuvant therapy for locally advanced rectal cancer, and looks forward to the future development direction.
China is a country with a high incidence of esophageal cancer. Most patients are already in the locally advanced stage when first diagnosed. Preoperative neoadjuvant therapy followed by surgery has become the standard treatment mode for them. Closely related to prognosis, the evaluation of tumor response is essential. Response evaluation criteria in solid tumors is the gold standard to evaluate tumor response, but the lesions must meet the measurement standards. Tumor regression grading (TRG) systems are designed to classify regressive changes after neoadjuvant treatment based on histopathological results to reveal prognostic information. Concentrating on pathologic assessment of esophageal cancer following neoadjuvant therapy, this article reviews histopathological changes, commonly used TRG systems and current debate.
ObjectiveTo investigate the influencing factors of total pathological complete response (tpCR) in newly treated human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients after neoadjuvant targeted chemotherapy, so as to provide more reference for the formulation of surgical plan and prognosis assessment. MethodsNinety-five newly treated HER2-positive breast cancer patients after neoadjuvant targeted chemotherapy were retrospectively chosen in the period from January 2021 to January 2023 in our hospital and all patients were divided into tpCR group (51 cases) and non-tpCR group (44 cases) according to whether tpCR was achieved after neoadjuvant targeted chemotherapy or not. Univariate and multivariate methods were used to evaluate the independent influencing factors of tpCR after neoadjuvant targeted chemotherapy in newly treated HER2-positive breast cancer patients. The prediction model based on the above independent influencing factors was constructed and the potential predictive efficacy of this model for tpCR after neoadjuvant targeted chemotherapy was evaluated. ResultsAmong 95 patients, 51 patients achieved tpCR after neoadjuvant targeted chemotherapy and 44 patients did not achieve tpCR. The results of the multivariate logistic regression model analysis showed that the patients with HER2 3+(OR=6.102, P=0.014), HER2+/hormone receptor– (HER2+/hormone receptor+ OR=0.129, P=0.006), and trastuzumab+pantomizumab treatment (OR=6.582, P=0.014) had higher tpCR rate, estrogen receptor 3+ (OR=0.122, P=0.0.033), progesterone receptor 3+ (OR=0.179, P=0.020), Ki-67 index of 15%–30% (OR=0.088, P=0.030) and 31%–60% (OR=0.066, P=0.017) had lower tpCR rate. The predicted area under the curve of this model was 0.881 [95%CI (0.815, 0.947)]. ConclusionsThe achievement of tpCR after new adjuvant treatment in newly diagnosed HER2 positive breast cancer patients is related to the expression level of HER2 in immunohistochemistry, molecular typing and new adjuvant targeted treatment scheme. At the same time, the prediction model based on these influencing factors can predict the effect of tpCR after new adjuvant treatment in patients to a certain extent.
ObjectiveTo analyze the details and efficacy of neoadjuvant therapy of colorectal cancer in the current version of Database from Colorectal Cancer (DACCA).MethodsThe DACCA version selected for this data analysis was the updated version on July 28th, 2020. The data items included “planned strategy of neoadjuvant therapy” “compliance of neoadjuvant therapy”, and “cycles of neoadjuvant therapy”. Item of “planned strategy of neoadjuvant therapy” included “accuracy of neoadjuvant therapy” and “once included in researches”. Item of “the intensity of neoadjuvant therapy” included “chemotherapy” “cycles of neoadjuvant therapy” “targeted drugs”, and “neoadjuvant radiotherapy”. Item of “effect of neoadjuvant therapy” included CEA value of “pre-neoadjuvant therapy” and “post-neoadjuvant therapy”“variation of tumor markers” “variation of symptom” “variation of gross” “variation of radiography”, and tumor regression grade (TRG). The selected data items were statistically analyzed.ResultsThe total number of medical records (data rows) that met the criteria was 7 513, including 2 539 (33.8%) valid data on the “accuracy of neoadjuvant therapy”, 498 (6.6%) valid data on “once included in researches”, 637 (8.5%) valid data on the “compliance of neoadjuvant therapy”, 2 077 (27.6%) valid data on “neoadjuvant chemotherapy”, 614 (8.2%) valid data on “cycles of neoadjuvant therapy”, 455 (6.1%) valid data on “targeted drugs”, 135 (1.8%) valid data on “neoadjuvant radiotherapy”, 5 022 (66.8%) valid data on “pre-neoadjuvant therapy CEA value”, 818 (10.9%) valid data on “post-neoadjuvant therapy CEA value ”, 614 (8.2%) valid data on “variation of tumor marker”, 464 (6.2%) valid data on “variation of symptom”, 478 (6.4%) valid data on “variation of gross”, 492 (6.5%) valid data on “variation of radiography”, and 459 (6.1%) valid data on TRG. During the correlation analysis, it appeared that “variation of tumor marker” and “variation of gross” (χ2=6.26, P=0.02), “variation of symptom” and “variation of gross”, “radiography” and TRG (χ2=53.71, P<0.01; χ2=38.41, P<0.01; χ2=8.68, P<0.01), “variation of gross” and “variation of radiography”, and TRG (χ2=44.41, P<0.01; χ2=100.37, P<0.01), “variation of radiography” and TRG (χ2=31.52, P<0.01) were related with each other.ConclusionsThe protocol choosing of neoadjuvant therapy has a room for further research and DACCA can provide data support for those who is willing to perform neoadjuvant therapy. The efficacy indicators of neoadjuvant therapy have association with each other, the better understand of it will provide more valuable information for the establishment of therapeutic prediction model.
Objective To investigate the perioperative differences between video-assisted thoracoscopic surgery (VATS) and thoracotomy after neoadjuvant therapy in patients with non-small cell lung cancer (NSCLC). Methods Clinical data of NSCLC patients who underwent VATS or thoracotomy after neoadjuvant therapy at Shanghai Pulmonary Hospital from June 2020 to May 2022 were retrospectively collected. Perioperative outcomes were compared between the two groups. Results A total of 260 patients were enrolled, 184 (70.8%) patients underwent VATS and 76 (29.2%) patients underwent thoracotomy. After propensity matching, there were 113 (62.4%) patients in the VATS group and 68 (37.6%) patients in the thoracotomy group. VATS had similar lymph node dissection ability and postoperative complication rate with thoracotomy (P>0.05), with the advantage of having shorter operative time (146.00 min vs. 165.00 min, P=0.006), less intraoperative blood loss (50.00 mL vs. 100.00 mL, P<0.001), lower intraoperative blood transfusion rate (0.0% vs. 7.4%, P=0.003), less 3-day postoperative drainage (250.00 mL vs. 350.00 mL, P=0.011; 180.00 mL vs. 250.00 mL, P=0.002; 150.00 mL vs. 235.00 mL, P<0.001), and shorter postoperative drainage time (9.34 d vs. 13.84 d, P<0.001) and postoperative hospitalization time (6.19 d vs. 7.94 d, P=0.006). Conclusion VATS after neoadjuvant therapy for NSCLC is safer than thoracotomy and results in better postoperative recovery.
ObjectiveTo analyze the impact of neoadjuvant regimens on prognosis in patients with rectal cancer in the current version of the Database from Colorectal Cancer (DACCA) database. MethodsPatient information was extracted from the updated version of DACCA on November 24, 2022 according to the established screening criteria, and the following items were analyzed: gender, age, body mass index (BMI), marriage, economic conditions, degree of differentiation, neoadjuvant treatment regimen, and pTNM staging. According to the neoadjuvant treatment regimen, the patients were divided into three groups: chemotherapy group, chemotherapy combined radiotherapy group, and chemotherapy combined targeted therapy group, and the overall survival (OS) and disease-specific survival (DSS) of patients in the three groups were analyzed, and the influencing factors of OS and DSS were analyzed by univariate and multivariate Cox proportional hazard regression models. ResultsAccording to the screening criteria, 1 716 valid data were obtained from the DACCA database, of which 954 (55.6%) were in the chemotherapy group, 332 (19.3%) in the chemotherapy combined radiotherapy group, and 430 (25.1%) in the chemotherapy combined targeted therapy group. The differences in the Kaplan-Merier survival curves of patients with different neoadjuvant regimens for OS and DSS in the three groups were statistically significant (χ2=142.142, P＜0.001; χ2=129.528, P＜0.001). There were significant differences in OS rate and DSS rate between the three groups in 3 years and 5 years (P<0.001). Further comparison of different neoadjuvant therapy groups showed that the OS of the chemotherapy combined targeted therapy group was slightly better than that of the chemotherapy group in 3 years, however, OS and DSS in 5 years were slightly worse than those the chemotherapy group, but the difference were not statistically significant (P>0.05). The OS and DSS of the chemotherapy group and the chemotherapy combined targeted therapy group were better than those of the chemotherapy combined radiotherapy group in 3 years and 5 years, and the differences were statistically significant (P<0.01). The results of multivariate analysis showed that patients’ age, economic conditions, degree of tumor differentiation, new auxiliary scheme and pTNM staging were the influencing factors of OS and DSS. ConclusionNeoadjuvant treatment regimen will affect the long-term survival prognosis of rectal cancer patients.
ObjectiveTo analyze the relation between educational level of patients with colorectal cancer (CRC) and decision-making and curative effect of neoadjuvant therapy (NAT) in the current version of the Database from Colorectal Cancer (DACCA). MethodsThe eligible CRC patients were collected from June 29, 2022 updated DACCA according to the screening criteria and were assigned into 4 groups according to their educational level, namely, uneducated, primary educated, secondary educated, and tertiary educated. The differences in NAT decision-making, cancer marker change, symptomatic change, gross change, imaging change, and tumor regression grade (TRG) among the CRC patients with different educational levels were compared. ResultsA total of 2 816 data that met the screening criteria were collected, 138 of whom were uneducated, 777 of whom were primary educated, 1 414 of whom were secondary educated, and 487 of whom were tertiary educated. The analysis results revealed that the difference in the composition ratio of patients choosing NAT regimens by educational level was statistically significant (χ2=30.937, P<0.001), which was reflected that the composition ratio of choosing a simple chemotherapy regimen in the uneducated CRC patients was highest, while which of choosing combined targeted therapy regimen in the tertiary educated CRC patients was highest. In terms of treatment outcomes, the composition ratios of changes in cancer markers (H=4.795, P=0.187), symptoms (H=1.722, P=0.632), gross (H=2.524, P=0.471), imaging (H=2.843, P=0.416), and TRG (H=2.346, P=0.504) had no statistical differences. ConclusionsThrough data analysis in DACCA, it is found that the educational level of patients with CRC can affect the choice of NAT scheme. However, it is not found that the educational level is related to the changes in the curative effect of patients with CRC before and after NAT, and further analysis is needed to determine the reasons for this.
ObjectiveTo analyze the relation between the place of residence of patients with colorectal cancer (CRC) and patient compliance or regimen decision-making or outcomes for neoadjuvant therapy (NAT) in the current version of the Database from Colorectal Cancer (DACCA). MethodsThe version of DACCA selected for this analysis was updated on June 29, 2022. The patients were enrolled according to the established screening criteria and then assigned into inside and outside of Sichuan Province groups as well as inside and outside of Chengdu City groups. The differences in the patient compliance or regimen decision-making or outcomes (changes of symptom and imaging, and cancer marker carcinoembryonic antigen) for NAT were analyzed. ResultsA total of 3 574 data that met the screened criteria were enrolled, 3 142 (87.91%) and 432 (12.09%) were inside of Sichuan Province group and outside of Sichuan Province group, respectively; 1 340 (42.65%) and 1 802 (57.35%) were inside of Chengdu City group and outside of Chengdu City group in Sichuan Province, respectively. ① The constituent ratios of the patient compliance for NAT had no statistical differences between the inside and outside of Sichuan Province groups (χ2=0.299, P=0.585) as well as between the inside and outside of Chengdu City groups (χ2=3.109, P=0.078). ② In terms of the impact of the place of residence on the decision-making of NAT: For the patients with targeted therapy or not, there was a statistical difference between the inside and outside of Sichuan Province groups (χ2=5.047, P=0.025), but which had no statistical difference between the inside and outside of Chengdu City groups (χ2=0.091, P=0.762); For the patients with radiotherapy or not, there were no statistical differences in the constituent ratios of patients between the inside and outside of Sichuan Province groups as well as between the inside and outside of Chengdu City groups (χ2=2.215, P=0.137; χ2=2.964, P=0.085); For the neoadjuvant intensity, there was a statistical difference between the inside and outside of Sichuan Province groups (χ2=12.472, P=0.002), but which had no statistical difference between the inside and outside of Chengdu City groups (χ2=2.488, P=0.288). ③ The outcomes for NAT: The changes of carcinoembryonic antigen had no statistical differences between the inside and outside of Sichuan Province groups as well as between the inside and outside of Chengdu City groups (H=1.762, P=0.184; H=3.531, P=0.060); In the symptom changes, there was a statistical difference between the inside and outside of Sichuan Province groups (χ2=3.896, P=0.048), which had no statistical difference between the inside and outside of Chengdu City groups (χ2=0.016, P=0.900); In the image changes, the difference was statistically significant between the inside and outside of Chengdu City groups (χ2=7.975, P=0.005), but which had no statistical difference between the inside and outside of Sichuan Province groups (χ2=0.063, P=0.802). ConclusionsThrough data analysis in DACCA in this study, it is found that there are no statistical differences in compliance and carcinoembryonic antigen changes. However, decision-making of NAT for patients of inside and outside of Sichuan Province has different choices on whether to assist targeted therapy and chemotherapy intensity for NAT; Symptom changes of NAT in patients of inside of Sichuan Province has a better effect than in patients of outside of Sichuan Province; Imaging change of NAT in patients of inside of Chengdu City has a better effect than in patients of outside of Chengdu City.
ObjectiveTo evaluate the efficacy and safety of programmed cell death receptor 1 (PD-1) inhibitor combined with chemotherapy in the preoperative neoadjuvant treatment of stage Ⅲ non-small cell lung cancer (NSCLC).MethodsThe clinical data of 68 patients with stage Ⅲ NSCLC who underwent preoperative neoadjuvant treatment in our hospital from June 2019 to October 2020 were analyzed and divided into two groups according to a random number table. There were 34 patients in the control group including 19 males and 15 females with an average age of 59.41±4.77 years. In the observation group, there were 34 patients including 21 males and 13 females with an average age of 61.15±6.24 years. The patients in the control group were treated with albumin-bound paclitaxel and cisplatin for injection, and the patients in the observation group were treated with carrelizumab on the basis of the control group, and both groups received 2 cycles of preoperative neoadjuvant therapy. We compared the clinical efficacy of imaging, T lymphocyte subsets, drug side effects, surgical resection rate, major pathological remission (MPR), complete pathological remission (pCR) and postoperative complications of the two groups of patients, and analyzed the influencing factors for MPR.ResultsThe objective response rate (ORR) of imaging in the observation group (70.6%) was higher than that in the control group (38.2%, P<0.05). The positive rate of CD3+ cells, the positive rate of CD4+ cells, the positive rate of CD8+ cells and the ratio of CD4+/CD8+ cells in the observation group after treatment were higher than those in the control group (P<0.05). The drug toxicity of the observation group was higher than that of the control group in the reactive cutaneouscapillary endothelial proliferation (RCCEP)/rash, abnormal thyroid function, and abnormal myocardial enzymes (P<0.05). The MPR (66.7%) and pCR (51.9%) of the surgical observation group were higher than those of the surgical control group (MPR: 19.2%, pCR: 7.7%, P<0.05). There was no statistical difference in surgical resection rate and postoperative complications between the two groups (P>0.05). Univariate analysis showed that ECOG score, pathological type, neoadjuvant treatment plan and surgical resection were related to MPR (P<0.05). The results of binary logistic regression analysis showed that Eastern Cooperative Oncology Group (ECOG) score and neoadjuvant treatment plan were independent risk factors for MPR (P<0.05).ConclusionThe clinical efficacy of PD-1 inhibitor combined with chemotherapy in the preoperative neoadjuvant treatment of stage Ⅲ NSCLC patients is definite, and it can significantly improve the patients' MPR, pCR and cellular immune function, but the side effects caused by immunotherapy drugs need to be concerned.