Linear endoscopic ultrasonography (EUS) allows the visualization, identification, and characterization of the extent of lesions of the gastrointestinal (GI) tract and adjacent structures. EUS-guided fine-needle aspiration (EUS-FNA) facilitates a more accurate diagnosis of mediastinal, intra-abdominal, and pancreatic lesions through the collection of the cytological material under direct visualization. Recent reports suggest that histological samples can be obtained by EUS-FNA with a reverse, bevel-tipped needle (the ProCore needle) to collect the core samples (fine needle biopsy, FNB), thereby adding a new dimension to the diagnostic usefulness of this technique. Certain neoplasms, such as lymphoma and stromal tumors, can be assessed by EUS-FNB to confirm the diagnosis. Here, we aimed to carry out a prospective, multicenter, single-blind, randomized, controlled trial to compare EUS-FNB and EUS-FNA. A total of 408 patients will be enrolled from five endoscopic centers. Patients will be divided into two groups: (1) group A, which is the EUS regular needle group (EUS-FNA) and (2) group B, which is the EUS ProCore needle group (EUS-FNB). Patients in group A will be examined with a 22G EchoTip Ultra needle, and patients in group B, with a 22G EchoTip ProCore needle. For all included patients, four EUS-guided passes will be made in each lesion. In the first and second pass, a slow-pull suction method of the stylet will be done. The third and fourth pass will use manual suction of 5 cc. The primary objective is to compare the diagnostic yield of malignancy by EUS-FNA versus EUS-FNB. The trial will compare samples obtained by EUS-FNA versus EUS-FNB for the diagnostic yield of solid lesions. The efficacy of these two sampling methods will be assessed on various lesions, which may provide insights into developing practice guidelines for their future indications. Clinical Trials.gov, NCT02327065 .

INTRODUCTION: The ability of carbohydrate antigen 19-9 (CA19-9) to differentiate pancreatic cancer from other benign pancreatic lesions is unsatisfactory. This study explored the diagnostic value of KRAS gene mutations and plasma circulating tumor DNA (ctDNA) in patients with pancreatic cancer. METHODS: The prospective cohort study comprised 149 consecutive patients with solid pancreatic lesions who underwent endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA). KRAS subtype mutations were analyzed by digital droplet PCR (ddPCR) in EUS-FNA histopathology tissue samples, and blood samples were sent for plasma ctDNA analysis. The final diagnosis was based on surgical resection pathology or follow-up for at least 2 years. RESULTS: Adding KRAS mutation ddPCR increased the sensitivity and accuracy of EUS-FNA from 71.4% to 91.6% (P < 0.001) and 75.8% to 88.6% (P < 0.001), respectively. By comparison, the sensitivities of circulating biomarkers ctDNA and CA19-9 were only 35.2% and 71.2%. The area under the curve of the receiver operating characteristic curve (AUC) of EUS-FNA and KRAS ddPCR combination was >0.90 for distinguishing pancreatic cancer from benign lesions, whereas the AUC of EUS-FNA and CA19-9 combination was 0.83. The median survival time was significantly shorter in patients with G12D KRAS mutations than that in patients with other mutations (180 vs 240 days, P < 0.001). DISCUSSION: FNA tissue sample KRAS mutation analysis in tissues significantly improves the diagnostic accuracy of cyto/histopathological evaluation in EUS-FNA samples. The combination of EUS-FNA and tissue sample KRAS ddPCR provided a more accurate method for pancreatic cancer diagnosis, superior to the combination of EUS-FNA and CA19-9/ctDNA. G12D KRAS mutations in pancreatic cancer were independently associated with poor overall survival.

Several suction techniques have been developed recently to enhance tissue acquisition when sampling solid lesions using endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA). The aim of this study is to determine whether a new modified wet suction technique (MWST) compared with the conventional dry suction technique (DRST) shall present better outcomes with respect to diagnostic yield and specimen quality of solid lesions in the intra-abdomen and mediastinum. This is a single-blind, randomized, controlled, superiority trial conducted at four large tertiary care centers in China. Two hundred and ninety-six patients with solid lesions referred for EUS-FNA will be randomly assigned to group A, using DRST for the first pass, or group B, using MWST for the first pass in a ratio of 1:1. Following a 2 × 2 cross-over design, the pass sequence for group A is DRST, MWST, DRST, MWST. For group B, the pass sequence is MWST, DRST, MWST, DRST. All procedures will be performed by experienced echoendoscopists, and the patients and assessors (cytologists and pathologists) will be blinded during the entire study. The primary outcome measure is the diagnosis yield. Secondary outcome measures are specimen quality, including assessment of quantity of cell, tissue integrity, and blood contamination. To our knowledge, this is the first large-scale randomized controlled trial to compare MWST with DRST when sampling solid lesions in the intra-abdomen and mediastinum. The results may contribute to future multicenter clinical trials in standardizing suction techniques during EUS-FNA. Clinical Trials.gov, NCT02789371 . Retrospectively registered on 6 June 2016.

Anlotinib is a small-molecule RTK inhibitor that has achieved certain results in further-line treatment, but many patients do not respond to this drug and lack effective methods for identification. Although radiomics has been widely used in lung cancer, very few studies have been conducted in the field of antiangiogenic drugs. This study aims to develop a new model to predict the efficacy of patients receiving anlotinib by combining pretreatment computed tomography (CT) radiomic characters with clinical characters, in order to assist precision medicine of pulmonary cancer. 254 patients from seven institutions were involved in the study. Lesions were selected according to the RECIST 1.1 criteria, and the corresponding radiomic features were obtained. We constructed prediction models based on clinical, NCE-CT, and CE-CT radiomic features, respectively, and evaluated the prediction performance of the models for training sets, internal validation sets, and external validation sets. In the RAD score only model, the area under curve(AUC) of the NCE-CT cohort was 0.740 (95% CI: 0.622, 0.857) for the training set, 0.711 (95% CI: 0.480, 0.942) for the internal validation set, and 0.633(95% CI: 0.479, 0.787) for the external validation set, while that of the CE-CT cohort was 0.815 (95% CI: 0.705, 0.926) for the training set, 0.771 (95% CI: 0.539, 1.000) for the internal validation set, and 0.701 (95% CI: 0.489, 0.913) for the external validation set. In the RAD score-combined model, the AUC of the NCE-CT cohort was 0.796 (95% CI: 0.691, 0.901) for the training set, 0.579 (95% CI: 0.309, 0.848) for the internal validation set, and 0.590 (95% CI: 0.427, 0.753) for the external validation set, while that of the CE-CT cohort was 0.902 (95% CI: 0.828, 0.977) for the training set, 0.865 (95% CI: 0.696, 1.000) for the internal validation set, and 0.837 (95% CI: 0.682, 0.992) for the external validation set. In conclusion, radiomics has accurate predictions for the efficacy of anlotinib. CE-CT-based radiomic models have the best predictive potential in predicting the efficacy of anlotinib, and model predictions become better when they are combined with clinical characteristics.

Background: Anlotinib has shown remarkable efficacy in later‐line treatment of advanced non‐small cell lung cancer (NSCLC). This prospective real‐world study evaluated its efficacy and safety in routine clinical practice. Methods: Patients from 13 centers in China received anlotinib (8–12 mg) once daily on days 1–14 of a 21‐day cycle until disease progression, death, or unacceptable toxicity. Primary endpoint was progression‐free survival (PFS). Secondary endpoints included overall survival (OS), objective response rate (ORR), disease control rate (DCR), and safety. Results: From July 2019 to October 2021, 352 of 373 enrolled patients received ≥ 2 cycles of anlotinib. Median follow‐up was 35.5 months. Median PFS and OS were 5.8 months (95% CI, 5.0–6.4) and 11.3 months (95% CI, 9.9–13.1), respectively. ORR and DCR were 19.3% and 84.4%. Multivariable analysis indicated that age ≥ 70 years was independently associated with poorer OS, though a clinically meaningful benefit remained (PFS, 5.9 months; OS, 9.6 months). Efficacy appeared generally similar regardless of baseline brain metastases. Median PFS and OS were 6.3 and 12.7 months in the second‐line setting, and 5.5 and 11.3 months in the≥ third‐line setting. Treatment‐related adverse events occurred in 10.5%, with grade ≥ 3 events in 1.4%; no treatment‐related deaths were observed. Conclusion: In this real‐world cohort, anlotinib demonstrated effectiveness and acceptable tolerability in advanced NSCLC. Given the observational design, exploratory analyses—including age, treatment line, and baseline brain metastases—should be interpreted with caution. These findings complement limited existing real‐world data and may inform future clinical research and decision‐making. Trial Registration: ClinicalTrials.gov identifier: NCT04871997