PNI might be an effective predictive indicator for the prognosis of cancer, especially digestive system carcinomas. Further studies are required to verify the significance of PNI in clinical practice.

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BackgroundProgrammed cell death 1 (PD-1) blockade induces tumor regression in patients with advanced esophageal squamous cell carcinoma (ESCC); however, little is known about the efficacy of PD-1 blockade as neoadjuvant therapy in resectable ESCC. We aim to assess the safety and feasibility of using the combination of neoadjuvant PD-1 blockade with chemotherapy in patients with ESCC.MethodsPatients with previously untreated, resectable (stage II or III) ESCC were enrolled. Each patient received two 21-day cycles of neoadjuvant treatment with camrelizumab, nab-paclitaxel, and carboplatin before undergoing surgical resection approximately 6–9 weeks after the first cycle.ResultsBetween January 2020 and September 2020, 37 patients were screened, of whom 23 were enrolled. The neoadjuvant therapeutic regimen had an acceptable side effect profile, and no delays in surgery were observed. Severe (grade 3–4) treatment-related adverse events included neutropenia (9 of 23, 39.1%) and leukopenia (2 of 23, 8.7%). The objective response and disease control rates were 90.5% and 100%, respectively. Twenty patients received surgery, and R0 resection was achieved in all cases. Five (25%) patients had a pathological complete response (PCR) and 10 (50%) patients had a major pathological response. The proportion of patients with a high tumor mutation burden and a high expression of programmed death-ligand 1 (PD-L1) in primary tumor was significantly higher in the PCR group than in the non-PCR group (p=0.044). The number of infiltrating PD-L1+ CD163+ cells was significantly lower in the PCR group than in the non-PCR group after treatment (p=0.017).ConclusionsNeoadjuvant camrelizumab plus carboplatin and nab-paclitaxel had manageable treatment-related adverse effects and induced an objective response in 90.5% of patients, demonstrating its antitumor efficacy in resectable ESCC.Trial registration numberChiCTR2000028900.

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Objective To construct a prediction model based on peritumoral radiomics signatures from CT images and investigate its efficiency in predicting early recurrence (ER) of hepatocellular carcinoma (HCC) after curative treatment. Materials and methods In total, 156 patients with primary HCC were randomly divided into the training cohort (109 patients) and the validation cohort (47 patients). From the pretreatment CT images, we extracted 3-phase two-dimensional images from the largest cross-sectional area of the tumor. A region of interest (ROI) was manually delineated around the lesion for tumoral radiomics (T-RO) feature extraction, and another ROI was outlined with an additional 2 cm peritumoral area for peritumoral radiomics (PT-RO) feature extraction. The least absolute shrinkage and selection operator (LASSO) logistic regression model was applied for feature selection and model construction. The T-RO and PT-RO models were constructed. In the validation cohort, the prediction efficiencies of the two models and peritumoral enhancement (PT-E) were evaluated qualitatively by receiver operating characteristic (ROC) curves, calibration curves and decision curves and quantitatively by area under the curve (AUC), the category-free net reclassification index (cfNRI) and integrated discrimination improvement values (IDI). Results By comparing AUC values, the prediction accuracy in the validation cohort was good for the PT-RO model (0.80 vs. 0.79, P = 0.47) but poor for the T-RO model (0.82 vs. 0.62, P < 0.01), which was significantly overfitted. In the validation cohort, the ROC curves, calibration curves and decision curves indicated that the PT-RO model had better calibration efficiency and provided greater clinical benefits. CfNRI indicated that the PT-RO model correctly reclassified 47% of ER patients and 32% of non-ER patients compared to the T-RO model (P < 0.01); additionally, the PT-RO model correctly reclassified 24% of ER patients and 41% of non-ER patients compared to PT-E ( P = 0.02). IDI indicated that the PT-RO model could improve prediction accuracy by 0.22 (P < 0.01) compared to the T-RO model and by 0.20 ( P = 0.01) compared to PT-E. Conclusion The CT-based PT-RO model can effectively predict the ER of HCC and is more efficient than the T-RO model and the conventional imaging feature PT-E. Electronic supplementary material The online version of this article (10.1186/s40644-019-0197-5) contains supplementary material, which is available to authorized users.

An antenatal emotional self-management training that may lower the risk of developing postnatal depression among Chinese women is recommended.

AIM:To assess the prognostic significance of immunological and nutritional-based indices, including the prognostic nutritional index (PNI), neutrophillymphocyte ratio (NLR), and platelet-lymphocyte ratio in gastric cancer. METHODS:We retrospectively reviewed 632 gastric cancer patients who underwent gastrectomy between 1998 and 2008. Areas under the receiver operating characteristic curve were calculated to compare the predictive ability of the indices, together with estimating the sensitivity, specificity and agreement rate. Univariate and multivariate analyses were performed to identify risk factors for overall survival (OS). Propensity score analysis was performed to adjust variables to control for selection bias. RESULTS:Each index could predict OS in gastric cancer patients in univariate analysis, but only PNI had independent prognostic significance in multivariate analysis before and after adjustment with propensity scoring (hazard ratio, 1.668; 95% confidence interval: 1.368-2.035). In subgroup analysis, a low PNI predicted a significantly shorter OS in patients with stage Ⅱ- Retrospective Study ORIGINAL ARTICLEⅢ disease (P = 0.019, P < 0.001), T3-T4 tumors (P < 0.001), or lymph node metastasis (P < 0.001). Canton score, a combination of PNI, NLR, and platelet, was a better indicator for OS than PNI, with the largest area under the curve for 12-, 36-, 60-mo OS and overall OS (P = 0.022, P = 0.030, P < 0.001, and P = 0.024, respectively). The maximum sensitivity, specificity, and agreement rate of Canton score for predicting prognosis were 84.6%, 34.9%, and 70.1%, respectively. CONCLUSION:PNI is an independent prognostic factor for OS in gastric cancer. Canton score can be a novel preoperative prognostic index in gastric cancer. Core tip: This is the first study to compare the prognostic significance of different immuno-nutritional indices including prognostic nutritional index (PNI), neutrophil-lymphocyte ratio (NLR) and plateletlymphocyte ratio (PLR) in gastric cancer. We found that PNI was an independent prognostic factor for overall survival in gastric cancer before and after the propensity score analysis, especially in patients with advanced disease, deep tumors, or lymph node metastasis. We also proposed that a new index-Canton score (a combination of PNI, NLR and PLT) is a superior prognostic factor compared to PNI, NLR, or PLR alone, as it better represents the relative contribution of each of these indices.Sun KY, Xu JB, Chen SL, Yuan YJ, Wu H, Peng JJ, Chen CQ, Guo P, Hao YT, He YL. Novel immunological and nutritionalbased prognostic index for gastric cancer.