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Abstract Peritoneal recurrence (PR) in gastric cancer after curative resection has poor prognosis. Therefore, we aimed to construct a nomogram to predict PR, and establish PR score for risk stratification to guide adjuvant chemotherapy. A total of 315 patients with gastric cancer after radical surgery were included, and randomly stratified into training group (n = 221) and validation group (n = 94). Univariate and multivariate analyses were used to determine predictive factors of PR. The nomogram was constructed to predict the risk of PR. We utilized the time-dependent area under the receiver operating characteristic (ROC) curves (AUCs), calibration curves, and decision curve analysis (DCA) to evaluate the performance of the nomogram. Multivariate analysis showed that tumor site, N stage, preoperative CEA, and postoperative CA199 were independent predictors of PR. A nomogram was constructed to predict PR based on these factors. The AUC value was 0.755 in the training group and 0.715 in the validation group. The calibration curves showed good agreement between prediction and observation in the training and validation groups. The decision curve analysis displayed a good net benefit of the nomogram. The novel PR score was developed and patients were stratified into the low-, medium-, and high -risk groups. For the high-risk group, postoperative adjuvant chemotherapy significantly improved patients' overall survival (OS) and disease-free survival (DFS). The establishment of nomogram facilitates the prediction of PR after radical gastrectomy, and a novel PR score may help guide adjuvant chemotherapy for gastric cancer.

ObjectiveThis study aimed to develop and validate a survival prediction model and nomogram to predict survival in patients with advanced gastric or gastroesophageal junction (G/GEJ) adenocarcinoma undergoing treatment with anti-programmed cell death 1 receptor (PD-1). This model incorporates immune-related adverse events (irAEs) alongside common clinical characteristics as predictive factors.MethodA dataset comprising 255 adult patients diagnosed with advanced G/GEJ adenocarcinoma was assembled. The irAEs affecting overall survival (OS) to a significant degree were identified and integrated as a candidate variable, together with 12 other candidate variables. These included gender, age, Eastern cooperative oncology group performance status (ECOG PS) score, tumor stage, human epidermal growth factor receptor 2 (HER2) expression status, presence of peritoneal and liver metastases, year and line of anti-PD-1 treatment, neutrophil-to-lymphocyte ratio (NLR), controlling nutritional status (CONUT) score, and Charlson comorbidity index (CCI). To mitigate timing bias related to irAEs, landmark analysis was employed. Variable selection was performed using the least absolute shrinkage and selection operator (LASSO) regression to pinpoint significant predictors, and the variance inflation factor was applied to address multicollinearity. Subsequently, a Cox regression analysis utilizing the forward likelihood ratio method was conducted to develop a survival prediction model, excluding variables that failed to satisfy the proportional hazards (PH) assumption. The model was developed using the entire dataset, then internally validated through bootstrap resampling and externally validated with a cohort from another Hospital. Furthermore, a nomogram was created to delineate the predictive model.ResultsAfter consolidating irAEs from the skin and endocrine systems into a single protective irAE category and applying landmark analysis, variable selection was conducted for the prognostic prediction model along with other candidate variables. The finalized model comprised seven variables: ECOG PS score, tumor stage, HER2 expression status in tumor tissue, first-line anti-PD-1 treatment, peritoneal metastasis, CONUT score, and protective irAE. The overall concordance index for the model was 0.66. Calibration analysis verified the model’s accuracy in aligning predicted outcomes with actual results. Clinical decision curve analysis indicated that utilizing this model for treatment decisions could enhance the net benefit regarding 1- and 2-year survival rates for patients.ConclusionThis study developed a prognostic prediction model by integrating common clinical characteristics of irAEs and G/GEJ adenocarcinoma. This model exhibits good clinical practicality and possesses accurate predictive ability for overall survival OS in patients with advanced G/GEJ adenocarcinoma.

BackgroudThe study aimed to analyze the efficacy and safety of PD-1 inhibitors plus chemotherapy with or without endostatin for stage IV lung squamous cell carcinoma (LUSC).MethodsA total of 219 patients with stage IV LUSC were included. 120 received PD-1 inhibitors plus chemotherapy with or without endostatin (IC ± A), of which 39 received endostatin (IC+A) and 81 did not receive endostatin (IC-A). 99 received chemotherapy with or without endostatin (C ± A). Endpoints included overall survival (OS), progression-free survival (PFS), adverse events (AEs), and immune-related adverse events (irAEs).ResultsThe median PFS in the IC ± A group versus the C ± A group was 8 and 4 months (P < 0.001), and the median OS was 17 and 9 months (P < 0.001). There was no significant difference in any grade AEs between the IC ± A and C ± A groups (P > 0.05). The median PFS in the IC+A group versus the IC-A group was 11 and 7 months (P = 0.024), and the median OS was 34 and 15 months (P = 0.01). There was no significant difference between the IC+A group and the IC-A group for all grade AEs and irAEs (P > 0.05). The subgroup analysis showed that patients with LIPI = 0 had significant OS and PFS benefits in IC+A group, while for patients with LIPI = 1–2, there was no significant difference in OS and PFS benefits between the IC+A group and IC-A group.ConclusionsPD-1 inhibitors plus chemotherapy with endostatin might be first-line treatment for patients with stage IV LUSC.

AbstractBackground This study aimed to compare the efficacy and safety of different treatment modalities for previously untreated advanced EGFR-mutated non-squamous non-small-cell lung cancer (NSCLC).Methods This retrospective study included 196 advanced EGFR-mutated non-squamous NSCLC. 107 received EGFR-tyrosine kinase inhibitor (EGFR-TKI) monotherapy (T), 53 received EGFR-TKI + bevacizumab (T + A), and 36 received EGFR-TKI + bevacizumab + chemotherapy (T + A + C). The endpoints included progression-free survival (PFS), overall survival (OS), objective response rate (ORR) and adverse events (AEs).Results The median PFS was 27 months in the T + A + C group, 17 months in the T + A group, and 10 months in the T group. The multivariate analysis showed lower disease progression in the T + A + C group (HR, 0.377; 95% CI, 0.224–0.634; p

BackgroundThis study aimed to develop and validate a novel nomogram to predict survival in advanced non-small cell lung cancer (NSCLC) receiving programmed cell death 1 (PD-1) inhibitor plus chemotherapy with or without antiangiogenic therapy.MethodsA total of 271 patients with advanced NSCLC who received anti-PD-1 plus chemotherapy with or without antiangiogenic therapy were enrolled in our center and randomized into the training cohort (n = 133) and the internal validation cohort (n = 138). Forty-five patients from another center were included as an independent external validation cohort. The nomogram was created based on the multivariate Cox regression analysis to predict overall survival (OS) and progression-free survival (PFS). The performance of the nomogram was assessed using the concordance index (C-index), the time-dependent area under the receiver operating (ROC) curves (AUCs), calibration curves, and decision curve analysis (DCA).ResultsFour factors significantly associated with OS were utilized to create a nomogram to predict OS: Eastern Cooperative Oncology Group performance status (ECOG PS), programmed cell death-ligand 1 (PD-L1) expression, chemotherapy cycle, and pretreatment lactate dehydrogenase–albumin ratio (LAR). Six variables significantly associated with PFS were incorporated into the development of a nomogram for predicting PFS: ECOG PS, histology, PD-L1 expression, chemotherapy cycle, pretreatment platelet to lymphocyte (PLR), and pretreatment LAR. The C-indexes of the nomogram for predicting OS and PFS were 0.750 and 0.747, respectively. The AUCs for predicting the 6-month, 12-month, and 18-month OS and PFS were 0.847, 0.791, and 0.776 and 0.810, 0.787, and 0.861, respectively. The calibration curves demonstrated a good agreement between predictions and actual observations. The DCA curves indicated that the nomograms had good net benefits. Furthermore, the nomogram model was well-validated in the internal and external cohorts.ConclusionThe novel nomogram for predicting the prognosis of advanced NSCLC receiving anti-PD-1 plus chemotherapy with or without antiangiogenic therapy may help guide clinical treatment decisions.

Background: Previous researches have reported that donor lymphocyte infusion (DLI) provides a new approach for the treatment of hematological malignancies and some solid tumors. The present study was designed to discuss the antitumor effect on mice with melanoma and possible involvement of the mechanism of haploidentical DLI in CB6F1 mice→CC3HF1 mice (F1→F1) mouse model. Methods: An F1→F1 haploidentical infusion model was established. CB6F1 mice (H-2b/d) bearing melanoma were used as recipients. CC3HF1 mice (H-2d/k) were used as donors. Changes in tumor volume and mice survival, host-derived lymphocytes proliferation, cytotoxicity, donor cell survival in vivo, histopathological examination of important organs, and the secretion Th1/Th2 cytokines were analyzed. Results: Irradiated haploidentical DLI combined with low-dose cyclophosphamide (Cy) chemotherapy induced an antitumor effect on mice with melanoma using the F1→F1 infusion model. Graft-versus-host disease (GvHD) was not obvious in any DLI-treated groups. Donor lymphocytes disappeared within 5 days after infusion, while the antitumor effect continued to be observed. Moreover, the DLI-treated groups showed a significant increase in the secretion of Th1 cytokines, including IFN-γ and IL-2, and an enhanced proliferation of CD8+ T lymphocytes and NK cells. Conclusions: Irradiated haploidentical DLI without bone marrow transplantation offers a safe, feasible, and effective approach in the treatment of melanoma.