ObjectiveTo analyze the risk factors influencing major postoperative complications (MPC) after minimally invasive radical gastrectomy for gastric cancer following neoadjuvant chemotherapy (NACT), and to construct a nomogram for accurately predicting MPC risk factors, and provide a reference for clinical decision-making. MethodsThe gastric cancer patients who underwent minimally invasive radical gastrectomy in the Department of General Surgery of the First Medical Center of the Chinese PLA General Hospital from February 2012 to December 2022 and met the inclusion criteria of this study were retrospectively collected. The univariate and multivariate logistic regression model were used to evaluate the risk factors influencing MPC and a nomogram model was constructed. The MPC were defined as Clavien-Dindo classification grade Ⅱ and beyond. The area under the receiver operating characteristic curve (AUC) and the calibration curve were used to evaluate the discrimination and accuracy of the nomogram model. ResultsA total of 362 patients were included in this study, among whom 65 cases (18.0%) experienced MPC. The multivariate logistic regression analysis showed that the age ≥58 years old, body mass index (BMI) ≥25 kg/m2, tumor long diameter ≥30 mm, operative time ≥300 min, and preoperative neutrophil-to-lymphocyte ratio (NLR) ≥3.7 were the risk factors influencing MPC. The nomogram model constructed using the above variables showed that the AUC (95%CI) was 0.731 (0.662, 0.801) in predicting the risk of MPC. The calibration curves showed that the prediction curve of the nomogram in predicting the MPC was agree well with the actual MPC (Hosmer-Lemeshow test: χ2=9.293, P=0.056). ConclusionFrom the results of this study, nomogram model constructed by combining age, BMI, tumor long diameter, operative time, and preoperative NLR can distinguish between patients with and without MPC after minimally invasive radical gastrectomy for gastric cancer following NACT, and has a better accuracy.
Objective
To summarize the progress of biological indexes which could predict the efficiency of neoadjuvant chemotherapy for breast cancer.
Methods
Various related researches were collected to make a review.
Results
Many indexes linked to the efficiency of neoadjuvant chemotherapy for breast cancer according to several studies. According to many studies, indexes such as human epidermal growth factor receptor-2 (HER-2) gene, estrogen receptor (ER), progesterone receptor (PR), Ki-67, P53 gene, neutrophil to lymphocyte ratio (NLR), platelet level, and mean platelet volume (MPV) may have association with the outcome of neoadjuvant chemotherapy in treatment of breast cancer, and these factors maybe individual biomarkers to predict the efficiency of the treatment, but no coincident conclusion has been reached for these indexes.
Conclusion
The value of these indexes that predict the efficiency of neoadjuvant chemotherapy is not sure, further study need to be done to solve this topic.
Objective To explore the value of multi-slice spiral CT (MSCT) 3D imaging in evaluating the efficacy of neoadjuvant chemotherapy for advanced gastric cancer. MethodsSixty-one patients with gastric cancer diagnosed by gastroscopy and pathological examination at the First Hospital of Lanzhou University from January 2019 to March 2022 were divided into chemotherapy effective group (n=39) and ineffective group (n=22) according to postoperative pathological regression grade (tumor regression grade, TRG) standards. MSCT was performed before neoadjuvant chemotherapy and before undergoing surgical treatment after neoadjuvant chemotherapy. The independent predictors related to the efficacy of chemotherapy were screened by binary logistics regression analysis of CT conventional observation indexes (including maximum tumor thickness, gastric wall motility, enhancement mode, lymph node metastasis, distant metastasis, peritoneal thickening or peritoneal nodules). Tumor volume and maximum tumor thickness were measured with the imaging histology software ITK-snap, and the diagnostic efficacy of tumor volume and CT conventional observation indexes was analyzed. Results In the evaluation of chemotherapy efficacy, tumor volume reduction rate and tumor maximum thickness reduction rate can evaluate the efficacy of chemotherapy to a certain extent (P< 0.01). The statistically significant indicators (tumor maximum thickness reduction rate, gastric wall motility, lesion intensification mode and peritoneal thickening and nodules) were analyzed by univariate analysis and binary logistic regression. The results showed that gastric wall motility [OR=0.294, 95%CI (0.093, 0.928), P=0.037] and maximum tumor thickness reduction rate [OR=0.282, 95%CI (0.083, 0.957), P=0.042] were independent predictors of the efficacy of neoadjuvant chemotherapy for progressive gastric cancer. Receiver operating characteristic (ROC) curve were plotted based on the predicted probability variable obtained from both and the results showed that the area under curve (AUC=0.900) , sensitivity (83.3%), and specificity (99.8%) of the tumor volume reduction rate were all higher than those of CT clinical index prediction probability variables (AUC=0.802, sensitivity was 58.3%, specificity was 85.7%). ConclusionThe measurement of tumor volume by MSCT combined with the imaging omics software ITK-snap provides an objective basis for the prediction of the efficacy of neoadjuvant chemotherapy, and its diagnostic efficacy is better.
ObjectiveTo explore the expression of alpha B-crystallin (CRYAB) in human gastric cancer tissue and the influence of chemotherapeutics on expression of CRYAB mRNA.Methods① The gastric cancer tissues and corresponding adjacent tissues of 76 patients underwent radical resection from April 2018 to March 2020 in The First Affiliated Hospital of Southwest Medical University and the Sichuan Mianyang 404 Hospital were collected, the expression of CRYAB protein in the gastric cancer tissues and corresponding adjacent tissues of 76 patients with gastric cancer were detected by immunohistochemistry SP technique. The relation between the expression of CRYAB protein and clinicopathologic features was analyzed. ② Twenty-one gastric tissues of patients accepted neoadjuvant chemotherapy and 26 gastric tissues of patients with no neoadjuvant chemotherapy in the The First Affiliated Hospital of Southwest Medical University were collected from November 2018 to March 2020, the expression of CRYAB mRNA was detected by real time-PCR.ResultsThe expression of CRYAB protein in gastric cancer tissues was positive in 51 cases (67.1%) and in the corresponding adjacent tissues was positive in 32 cases (42.1%), the positive rate was higher in gastric cancer tissues (χ2=9.581, P=0.002). The over-expression of CRYAB protein in the gastric cancer tissues was correlated with the TNM stage, Borrmann typing, degree of differentiation, lymph node metastasis, depth of invasion of the patients, and Lauren classification (P<0.05), but not correlated with the age, gender, tumor sitation, and diameter (P>0.05). The expression of CRYAB mRNA in the gastric cancer tissues with neoadjuvant chemotherapy was significantly higher than that in the gastric cancer tissues without neoadjuvant chemotherapy (t=8.37, P<0.001).ConclusionsThe over-expression of CRYAB protein is closely related to the invasion and progression of gastric cancer, they may be involved in the progression of gastric cancer and play a crucial role. Moreover, the expression of CRYAB mRNA increases after chemotherapy, it suggests that chemotherapy drugs can activate the self-protection mechanism of tumor cells to some extent, and influence the effect of chemotherapy by increasing expression of CRYAB protein.
ObjectiveTo observe the accuracy of magnetic resonance imaging (MRI) for predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer, and to analyze the cause of the prediction error.MethodsData from 157 breast cancer patients who underwent NAC before surgery in Mianyang Central Hospital from January 2017 to January 2019 were analyzed. MRI parameters before and after NAC and pCR conditions were collected to analyze the parameters that produced false positives and false negatives.ResultsOf the 157 patients, 37 (23.6%) achieved pCR after NAC, and 33 (21.0%) achieved radiation complete remission (rCR) after NAC. The accuracy of MRI prediction was 70.7% (111/157), the sensitivity was 82.5% (99/120), and the specificity was 32.4% (12/37). A total of 25 cases did not achieve rCR, but postoperative evaluation achieved pCR (false positive), 21 cases achieved rCR, but postoperative evaluation did not achieve pCR (false negative). Diameter of tumor, peritumoral oedema, and background parenchymal enhancement were associated with MRI false positive prediction (P<0.05); gland density and tumor rim enhancement were associated with MRI false negative prediction (P<0.05).ConclusionMRI can be used as an important method to predict pCR after NAC in breast cancer patients, and its accuracy may be related to diameter of tumor, peritumoral oedema, background parenchymal enhancement, gland density, and tumor rim enhancement.
ObjectiveTo evaluate the predictive value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) combined with multislice computed tomography (MSCT) in the evaluation of neoadjuvant chemotherapy (NACT) for breast cancer. MethodsThe clinical, imaging, and pathological data of breast cancer patients who received NACT in the Affiliated Hospital of Southwest Medical University from February 2019 to August 2021 were retrospectively collected. Based on the results of postoperative pathological examination, the patients were assigned into significant remission (Miller-Payne grade Ⅰ–Ⅲ) and non-significant remission (Miller-Payne grade Ⅳ–Ⅴ). The variables with statistical significance by univariate analysis or factors with clinical significance judged based on professional knowledge were included to conduct the logistic regression multivariate analysis to screen the risk factors affecting the degree of pathological remission after NACT. Then, the screened risk factors were used to establish a prediction model for the degree of pathological remission of breast cancer after NACT, and the efficacy of this model was evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve. ResultsAccording to the inclusion and exclusion criteria, a total of 211 breast cancer patients who received NACT were collected, including 116 patients with significant remission and 95 patients with non-significant remission. Logistic regression multivariate analysis results showed that the human epidermal growth factor receptor 2 positive, lower early enhancement rate after NACT, lower arterial stage net increment after NACT, and lower CT value of arterial phase of lesions would increase the probability of significant remission in patients with breast cancer after NACT (P<0.05). The area under the ROC curve of the model for predicting the degree of pathological remission of breast cancer after NACT was 0.984, the specificity was 93.7%, and the sensitivity was 95.7%. The calibration curve showed that the model result fit well with the actual result, and the DCA result showed that it had a high clinical net benefit value. ConclusionFrom the results of this study, DCE-MRI combined with MSCT enhanced scanning has a good predictive value for pathological remission degree after NACT for breast cancer, which can provide clinical guidance for further treatment.
ObjectiveTo investigate the effect and predictive value of systemic inflammatory markers on pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) for locally advanced breast cancer (LABC). MethodsThe clinicopathologic data of female patients with LABC who received NACT and radical surgical resection in the Department of Breast Surgery, Affiliated Hospital of Southwest Medical University from February 2019 to February 2022 were retrospectively analyzed. The factors affecting pCR after NACT were analyzed by the multivariate logistic regression and the prediction model was established. The efficiency of the prediction model was evaluated by receiver operating characteristic (ROC) curve and area under the ROC curve (AUC). ResultsA total of 98 patients were gathered, of which 29 obtained pCR, with a pCR rate of 29.6%. The multivariate analysis of binary logistic regression showed that the patients with non-menopausal status, negative estrogen receptor (ER), chemotherapy+targeted therapy, and systemic immune-inflammation index (SII) <532.70 (optimal critical value) were more likely to obtain pCR after NACT (P<0.05). The prediction model was established according to logistic regression analysis: Logit (P)=0.697–2.974×(menopausal status)–1.932×(ER status)+3.277×(chemotherapy regimen)–2.652×(SII). The AUC (95%CI) of the prediction model was 0.914 (0.840, 0.961), P<0.001. ConclusionsIt is not found that other inflammatory indicators such as neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio are associated with pCR after NACT. But SII is an important predictor of pCR after NACT for LABC and has a good predictive efficiency.
ObjectiveTo summarize advances of neoadjuvant chemotherapy (NACT) in treatment for locally advanced gastric cancer (AGC) in recent years, in order to providing reference for development of NACT and application of clinical research.MethodThe domestic and foreign literatures about the NACT for the AGC were reviewed.ResultsThe efficacy and safety of NACT had been affirmed, but there were still many questions in the clinical practice, such as the selection of NACT regimen, indications, number of chemotherapy cycles, whether to combine targeted therapy, the selection of treatment and restaging after the NACT, and relevant researches were still underway.ConclusionsTherapy methods of AGC are varied and NACT has an obvious effect, which has become one of the most important treatments for AGC. However, there are still many problems in clinical practice, further research is needed.
ObjectiveTo explore the clinical application of oncoplastic surgery in breast-conserving surgery after neoadjuvant chemotherapy.MethodsFrom May 2016 to May 2018, 32 breast cancer patients (cT2–3N0–3M0) who were scheduled for neoadjuvant chemotherapy (NAC) and agreed to accept breast-conserving surgery after NAC in the Henan Tumor Hospital were enrolled into the retrospective study. These patients were originally unable to perform traditional breast conserving surgery because of the size or location of the tumor. We observed the success rate, safety and cosmetic effects of breast-conserving therapy, which were applicated of tumor down-staging after neoadjuvant chemotherapy combined with oncoplastic surgery.ResultsIn this study, after neoadjuvant chemotherapy, 31 patients achieved CR or PR, and 1 patient had SD. All 32 patients underwent breast-conserving surgery successfully, 3 patients underwent breast-conserving combined with volume replacement, and 29 patients underwent breast-conserving combined with volume displacement. One patient was not satisfied with the cosmetic effects, the other patients were satisfied or basically satisfied with the cosmetic effects. The median follow-up was 18 months (5–24 months), and no local recurrence or distant metastasis was found in 32 patients.ConclusionsBy tumor down-staging after neoadjuvant chemotherapy combined with oncoplastic surgery, we can make some patients who are originally not suitable for breast conserving due to tumor size and tumor location succeed in breast-conserving therapy, and the safety and cosmetic effect are basically satisfied.
Objective To investigate the effect of radiotherapy after neoadjuvant chemotherapy and modified radical surgery on breast cancer specific survival (BCSS) of patients with stage cT1–2N1M0 breast cancer. Methods A total of 917 cT1–2N1M0 stage breast cancer patients treated with neoadjuvant chemotherapy and modified radical surgery from 2010 to 2017 were extracted from the The Surveillance, Epidemiology, and End Results (SEER) database. Of them 720 matched patients were divided into radiotherapy group (n=360) and non-radiotherapy group (n=360) by using propensity score matching (PSM). Cox proportional hazard regression model was used to explore the factors affecting BCSS. Results Patients were all interviewed for a median follow-up of 65 months, and the 5-year BCSS was 91.9% in the radiotherapy group and 93.2% in the non-radiotherapy group, there was no significant difference between the 2 groups (χ2=0.292, P=0.589). The results were the same in patients with no axillary lymph node metastasis, one axillary lymphnode metastasis, two axillary lymph node metastasis and 3 axillary lymph node metastasis group (χ2=0.139, P=0.709; χ2=0.578, P=0.447; χ2=2.617, P=0.106; χ2=0.062, P=0.803). The result of Cox proportional hazard regression analysis showed that, after controlling for Grade grade, time from diagnosis to treatment, efficacy of neoadjuvant chemotherapy, number of positive axillary lymph nodes, molecular typing, and tumor diameter at first diagnosis, radiotherapy had no statistically significant effect on BCSS [HR=1.048, 95%CI (0.704, 1.561), P=0.817]. Conclusions The effect of radiotherapy on the BCSS of patients with stage cT1–2N1M0 breast cancer who have received neoadjuvant chemotherapy and modified radical surgery with 0 to 3 axillary lymph nodes metastases is limited, but whether to undergo radiotherapy should still be determined according to the comprehensive risk of individual tumor patients.
