Predicting Positive Margins in Pancreatic Head Adenocarcinoma After Neoadjuvant Therapy: Investigating Disparities in Quality Care Using the National Cancer Database

Racial and Socioeconomic Differences and Surgical Outcomes in Pancreaticoduodenectomy Patients: A Systematic Review of High- Versus Low-Volume Hospitals in the United States

BACKGROUND

Pancreaticoduodenectomy (PD) is associated with better outcomes in high-volume hospitals. However, it is unknown whether and to what extent the improved performance of high-volume hospitals may be associated with racial and socioeconomic factors, which have been shown to impact operative and postoperative outcomes in major surgeries. This review aims to identify the differences in racial and socioeconomic characteristics of patients who underwent PD surgery in high- and low-volume hospitals.

METHODS

PubMed, Cochrane, and Web of Science were systematically searched between May 1, 2023 and May 7, 2023 without any time restriction on publication date. Studies that were conducted in the United States and had a direct comparison between high- and low-volume hospitals were included.

RESULTS

A total of 30 observational studies were included. When racial proportions were compared by hospital volume, thirteen studies reported that compared to high-volume hospitals, a higher percentage of racial minorities underwent PD in low-volume hospitals. Disparities in traveling distance, education levels, and median income at baseline between high- and low-volume hospitals were reported by four, three, and two studies, respectively.

CONCLUSION

A racial difference at baseline between high- and low-volume hospitals was observed. Socioeconomic factors were less frequently included in existing literature. Future studies are needed to understand the socioeconomic differences between patients receiving PD surgery in high- and low-volume hospitals.

Risk factors of positive resection margin differ in pancreaticoduodenectomy and distal pancreatosplenectomy for pancreatic ductal adenocarcinoma undergoing upfront surgery

OBJECTIVE

Positive resection margin indicates worse prognosis. The present study identified the independent risk factors of R1 resection in pancreaticoduodenectomy (PD) and distal pancreatosplenectomy (DP) for patients with pancreatic ductal adenocarcinoma (PDAC).

METHOD

Consecutive patients who were operated from 1st December 2017 to 30th December 2018 were analyzed retrospectively. A standardized pathological examination with digital whole-mount slide images (DWMSIs) was utilized for evaluation of resection margin status. R1 was defined as microscopic tumor infiltration within 1 mm to the resection margin. The potential risk factors of R1 resection for PD and DP were analyzed separately by univariate and multivariate logistic regression analyses.

RESULTS

For the 192 patients who underwent PD, and the 87 patients who underwent DP, the R1 resection rates were 31.8% and 35.6%, respectively. Univariate analysis on risk factors of R1 resection for PD were tumor location, lymphovascular invasion, N staging, and TNM staging; while those for DP were T staging and TNM staging. Multivariate logistic regression analysis showed the location of tumor in the neck and uncinate process, and N1/2 staging were independent risk factors of R1 resection for PD; while those for DP were T3 staging.

CONCLUSIONS

The clarification of the risk factors of R1 resection might clearly make surgeons take reasonable decisions on surgical strategies for different surgical procedures in patients with PDAC, so as to obtain the first attempt of R0 resection.

Feasibility of a CT-based lymph node radiomics nomogram in detecting lymph node metastasis in PDAC patients

Objectives

To investigate the potential value of a contrast enhanced computed tomography (CECT)-based radiological-radiomics nomogram combining a lymph node (LN) radiomics signature and LNs’ radiological features for preoperative detection of LN metastasis in patients with pancreatic ductal adenocarcinoma (PDAC).

Materials and methods

In this retrospective study, 196 LNs in 61 PDAC patients were enrolled and divided into the training (137 LNs) and validation (59 LNs) cohorts. Radiomic features were extracted from portal venous phase images of LNs. The least absolute shrinkage and selection operator (LASSO) regression algorithm with 10-fold cross-validation was used to select optimal features to determine the radiomics score (Rad-score). The radiological-radiomics nomogram was developed by using significant predictors of LN metastasis by multivariate logistic regression (LR) analysis in the training cohort and validated in the validation cohort independently. Its diagnostic performance was assessed by receiver operating characteristic curve (ROC), decision curve (DCA) and calibration curve analyses.

Results

The radiological model, including LN size, and margin and enhancement pattern (three significant predictors), exhibited areas under the curves (AUCs) of 0.831 and 0.756 in the training and validation cohorts, respectively. Nine radiomic features were used to construct a radiomics model, which showed AUCs of 0.879 and 0.804 in the training and validation cohorts, respectively. The radiological-radiomics nomogram, which incorporated the LN Rad-score and the three LNs’ radiological features, performed better than the Rad-score and radiological models individually, with AUCs of 0.937 and 0.851 in the training and validation cohorts, respectively. Calibration curve analysis and DCA revealed that the radiological-radiomics nomogram showed satisfactory consistency and the highest net benefit for preoperative diagnosis of LN metastasis.

Conclusions

The CT-based LN radiological-radiomics nomogram may serve as a valid and convenient computer-aided tool for personalized risk assessment of LN metastasis and help clinicians make appropriate clinical decisions for PADC patients.

Concepts and Outcomes of Perioperative Therapy in Stage IA-III Pancreatic Cancer-A Cross-Validation of the National Cancer Database (NCDB) and the German Cancer Registry Group of the Society of German Tumor Centers (GCRG/ADT)

(1) Background: The aim of this study is to assess perioperative therapy in stage IA-III pancreatic cancer cross-validating the German Cancer Registry Group of the Society of German Tumor Centers-Network for Care, Quality, and Research in Oncology, Berlin (GCRG/ADT) and the National Cancer Database (NCDB). (2) Methods: Patients with clinical stage IA-III PDAC undergoing surgery alone (OP), neoadjuvant therapy (TX) + surgery (neo + OP), surgery+adjuvantTX (OP + adj) and neoadjuvantTX + surgery + adjuvantTX (neo + OP + adj) were identified. Baseline characteristics, histopathological parameters, and overall survival (OS) were evaluated. (3) Results: 1392 patients from the GCRG/ADT and 29,081 patients from the NCDB were included. Patient selection and strategies of perioperative therapy remained consistent across the registries for stage IA-III pancreatic cancer. Combined neo + OP + adj was associated with prolonged OS as compared to neo + OP alone (17.8 m vs. 21.3 m, p = 0.012) across all stages in the GCRG/ADT registry. Similarly, OS with neo + OP + adj was improved as compared to neo + OP in the NCDB registry (26.4 m vs. 35.4 m, p < 0.001). (4) Conclusion: The cross-validation study demonstrated similar concepts and patient selection criteria of perioperative therapy across clinical stages of PDAC. Neoadjuvant therapy combined with adjuvant therapy is associated with improved overall survival as compared to either therapy alone.

A radiomics model that predicts lymph node status in pancreatic cancer to guide clinical decision making: A retrospective study

Purpose: To construct a radiomics-based model for predicting lymph node (LN) metastasis status in pancreatic ductal adenocarcinoma (PDAC) before therapy and to evaluate its prognostic clinical value. Materials and Methods: We retrospectively collected preoperative CT scans of 130 PDAC patients who underwent original tumor resection and LN dissection in the entire cohort between January 2014 and December 2017. Radiomics features were systematically extracted and analyzed from CT scans of 89 patients in the primary cohort. To construct a radiomics signature, the least absolute shrinkage and selection operator methods were employed with LN metastasis status as classification labels. Pathological analysis of LN status which were assessed by experienced pathologists was used as the evaluation label. We subjected the clinical nomogram to multivariable logistic regression analysis and conducted performance evaluation based on its discrimination, calibration, and clinical value. The model was tested and validated in 41 patients with PDAC in a separate validation cohort. Results: Four radiomics features closely associated with LN metastasis were selected in the primary and validation cohorts (P < 0.01). Following the integration of CT-reported results and radiomics signatures into the radiomics nomogram, we reported better performance in the primary (area under the curve, 0.80) and validation (area under the curve, 0.78) cohorts. Conclusion: The noninvasive tool constructed from the portal venous phase CT based on radiomics showed better performance for LN metastasis prediction than traditional approaches in pancreatic cancer. It may assist surgeons in crafting detailed procedures before treatment, this subsequently improves tumor staging and resection of patients.