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.
Objective To investigate the clinicopathological characteristics of HER2 protein expression in different degrees in human epidermal growth factor receptor 2 (HER2) negative breast cancer and the factors related to the efficacy of neoadjuvant chemotherapy in breast cancer with low HER2 expression. Methods The clinicopathological data of 161 patients with HER2-negative breast cancer who received neoadjuvant chemotherapy in the Department of Breast Surgery, Affiliated Hospital of Southwest Medical University from March 2019 to March 2022 were retrospectively collected. The difference of clinical and pathological characteristics of patients with different levels of HER2 protein expression were analyzed, and the factors influencing the pathological complete remission (pCR) rate of breast cancer patients with low HER2 expression after neoadjuvant chemotherapy with unconditional logistic regression model were analyzed. Results Among 161 HER2 negative breast cancer patients, 108 cases were low HER2 expression, accounting for 67.1%. Compared with those with zero expression of HER2 [immunohistochemistry (IHC) 0], the patients with low HER2 expression had higher axillary lymph node metastasis rate (P=0.048), lower histological grade (P=0.006), and higher proportion of positive hormone receptor expression (P<0.001). There was no significant difference in pCR rate among the HER2 IHC 0, IHC 1+ and IHC 2+ / in situ hybridization (ISH)– (P=0.099) , and the pCR rate of low expression of HER2 was lower than that of zero expression of HER2 in the general population and Luminal subgroup, and the difference was statistically significant (P<0.05). There was no significant difference in triple negative breast cancer subgroup (P=0.814). The logistic regression analysis showed that age, histological grade and estrogen receptor expression status were independent influencing factors for pCR rate after neoadjuvant chemotherapy with low HER2 expression (P<0.05). Conclusions Different degrees of HER2 protein expressions in patients with HER2-negative breast cancer have unique clinicopathological characteristics. The pCR rate of neoadjuvant chemotherapy in patients with low HER2-expression breast cancer is lower than that in patients with zero HER2-expression breast cancer. Age, histological grade and estrogen receptor expression status are independent factors influencing the pCR rate of neoadjuvant chemotherapy in patients with low HER2-expression breast cancer.
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.
ObjectiveTo analyze the association between nutritional and immune-related laboratory indices and pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients and focused on constructing a combination of laboratory indices to serve as a clinical predictor of pCR after NAC in breast cancer. MethodsRetrospectively collected the pre-NAC laboratory indices [albumin (ALB), total cholesterol, triglyceride, high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol, apolipoprotein A- Ⅰ, apolipoprotein B, white blood cell, neutrophil, lymphocyte, monocyte (MON), and platelet ] and clinicopathologic data of 310 patients with invasive breast cancer who had received NAC in the Department of Breast Surgery, Affiliated Hospital of Southwest Medical University, from September 1, 2020 to October 31, 2022. Logistic regression analysis was conducted to determine the correlation between laboratory indices and post-NAC pCR. The combinations of laboratory indices were constructed by simple mathematical operation. The area under the receiver operating characteristic curve (AUC) was used to evaluate the efficacy of different combinations of laboratory indices in predicting pCR and to determine the optimal combination of liboratory indices. Multivariate logistic regression analysis was used to analysis the relevance between clinicopathologic features and post-NAC pCR in breast cancer patients and to determine the independent predictor of post-NAC pCR. ResultsAmong the 310 patients, 49.4% (153/310) of them achieved pCR after NAC. Logistic regression analysis revealed that ALB (Z=5.203, P<0.001) and HDL-C (Z=2.129, P=0.033) were positively correlated with post-NAC pCR, while MON (Z=–4.883, P<0.001) was negatively correlated with post-NAC pCR. The AUC analysis of 6 different combinations of laboratory indices showed that the ALB/MON combination (the optimal combination of liboratory indices) had the highest predictive performance (median AUC=0.708) and was determined to be the neoadjuvant therapy predictive index (NTPI). Multivariate logistic regression analysis showed that estrogen receptor (Z=–3.273, P=0.001), human epidermal growth factor 2 (Z=7.041, P<0.001), Ki-67 (Z=2.457, P=0.014), and NTPI (Z=4.661, P<0.001) were the independent predictors for post-NAC pCR. ConclusionNTPI could serve as a predictive index for post-NAC pCR in patients with breast cancer.
ObjectiveTo summarize the current research progress in the prediction of the efficacy of neoadjuvant therapy of breast cancer based on the application of artificial intelligence (AI) and radiomics. MethodThe researches on the application of AI and radiomics in neoadjuvant therapy of breast cancer in recent 5 years at home and abroad were searched in CNKI, Google Scholar, Wanfang database and PubMed database, and the related research progress was reviewed. ResultsAI had developed rapidly in the field of medical imaging, and molybdenum target, ultrasound and magnetic resonance imaging combined with AI had been deepened and expanded in different degrees in the application research of breast cancer diagnosis and treatment. In the research of molybdenum target combined with AI, the high sensitivity of molybdenum target to microcalcification was mostly used to improve the accuracy of early detection and diagnosis of breast cancer, so as to achieve the clinical purpose of early detection and diagnosis. However, in terms of prediction of neoadjuvant efficacy research of breast cancer, ultrasound and magnetic resonance imaging combined with AI were more prevalent, and their popularity remained unabated. ConclusionIn the monitoring of neoadjuvant therapy for breast cancer, the use of properly designed AI and radiomics models can give full play to its role in the predicting the curative effect of neoadjuvant therapy, and help to guide doctors in clinical diagnosis and treatment and evaluate the prognosis of breast cancer patients.
ObjectiveTo summarize the complete response (CR, which referred to the imaging level) achieved by conversion therapy for hepatocellular carcinoma (HCC) in the current researches, and explore the further therapy strategies and outcomes for patients acquired CR. MethodThe domestic and foreign literature on the research of CR achieved by conversion therapy for HCC was reviewed and summarized. ResultsWith the great progress of conversion therapy such as local therapy, systemic therapy, and local therapy in combination with systemic therapy for HCC, the proportion of the CR was increasing after conversion therapy. For the patients who achieved CR after conversion therapy, the surgical resection, liver transplantation, follow-up observation, etc. could be selected and showed a survival benefit. Conclusions From the opinion summarized in this review, with the development of targeted therapy and immunotherapy, as well as the new anti-tumor drugs, a growing number of conversion therapeutic schedules could be provided, CR rate was increasing. At present, for patients who have achieved CR after conversion therapy, surgical or non-surgical treatment can be chosen. However, there is no authoritative conclusion on which therapy method can benefit patients more. The current strategy is to perform personalized treatment plan based on the individual situation of patient, in order to achieve better survival benefit for patient.
ObjectiveTo explore the value of a decision tree (DT) model based on CT for predicting pathological complete response (pCR) after neoadjuvant chemotherapy therapy (NACT) in patients with locally advanced rectal cancer (LARC).MethodsThe clinical data and DICOM images of CT examination of 244 patients who underwent radical surgery after the NACT from October 2016 to March 2019 in the Database from Colorectal Cancer (DACCA) in the West China Hospital were retrospectively analyzed. The ITK-SNAP software was used to select the largest level of tumor and sketch the region of interest. By using a random allocation software, 200 patients were allocated into the training set and 44 patients were allocated into the test set. The MATLAB software was used to read the CT images in DICOM format and extract and select radiomics features. Then these reduced-dimensions features were used to construct the prediction model. Finally, the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), sensitivity, and specificity values were used to evaluate the prediction model.ResultsAccording to the postoperative pathological tumor regression grade (TRG) classification, there were 28 cases in the pCR group (TRG0) and 216 cases in the non-pCR group (TRG1–TRG3). The outcomes of patients with LARC after NACT were highly correlated with 13 radiomics features based on CT (6 grayscale features: mean, variance, deviation, skewness, kurtosis, energy; 3 texture features: contrast, correlation, homogeneity; 4 shape features: perimeter, diameter, area, shape). The AUC value of DT model based on CT was 0.772 [95% CI (0.656, 0.888)] for predicting pCR after the NACT in the patients with LARC. The accuracy of prediction was higher for the non-PCR patients (97.2%), but lower for the pCR patients (57.1%).ConclusionsIn this preliminary study, the DT model based on CT shows a lower prediction efficiency in judging pCR patient with LARC before operation as compared with homogeneity researches, so a more accurate prediction model of pCR patient will be optimized through advancing algorithm, expanding data set, and digging up more radiomics features.
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.
Objective To observe the short-term efficacy and safety of neoadjuvant sintilimab combined with chemotherapy in the treatment of patients with locally advanced resectable esophageal squamous cell carcinoma (ESCC). MethodsClinical data were collected from patients with locally advanced resectable ESCC who received neoadjuvant immunotherapy combined with chemotherapy followed by surgical treatment at the Department of Thoracic Surgery of Jining First People's Hospital from April 2020 to April 2022. The endpoints included major pathological response (MPR), pathological complete response (pCR), R0 resection rate, safety, and postoperative survival. Results A total of 43 patients with ESCC who received at least one cycle of neoadjuvant immunotherapy before surgery were included. Among them, there were 31 males and 12 females, aged from 46 to 77 years, with a median age of 65 years. All patients successfully completed the surgery without any surgical delays. The pCR rate was 14.0% (6/43), the MPR rate was 58.1% (25/43), and the R0 resection rate was 97.7% (42/43). Patients exhibited reliable safety during neoadjuvant therapy and postoperatively. The 2-year overall survival and disease-free survival rates were 90.7% and 81.4%, respectively. Kaplan-Meier survival analysis and log-rank test revealed lower recurrence rates and better survival in the MPR group compared to the non-MPR group. Conclusion The combination of neoadjuvant sintilimab and chemotherapy in the treatment of patients with locally advanced resectable ESCC has demonstrated significant clinical efficacy, while also being safe and reliable.
Organ preservation after neoadjuvant therapy for esophageal cancer has gained significant attention. While the CROSS trial established neoadjuvant chemoradiotherapy (nCRT) followed by surgery as standard care, approximately 30% of patients achieve pathological complete response (pCR), prompting exploration of active surveillance (AS). The landmark SANO phase Ⅲ trial (2025) demonstrated non-inferior 2-year overall survival (74% AS vs. 71% surgery), with 31% of patients avoiding surgery. Multimodal assessment (endoscopic deep biopsy+EUS+PET-CT) reduced residual disease misdiagnosis to 10%. The Asian-led NEEDS trial is evaluating definitive chemoradiotherapy with salvage surgery. Although immunotherapy boosts pCR rates to 40%-55%, challenges persist, including 8%-12% false-negative cCR assessments, limited long-term data, and East-West histological disparities. The 2024 NCCN guidelines conditionally recommend AS (Category 2B, prioritized for squamous cell carcinoma), emphasizing centralized implementation. Future directions involve ctDNA and radiomics for risk stratification to advance precision organ-preserving strategies.