Background: Malignant peritoneal mesothelioma (MPM) is a rare disease with a historically poor prognosis. Given the emergence of effective therapies, a contemporary analysis of MPM incidence and survival is warranted. Methods: The SEER-18 registry dataset was analyzed (2000–2018). Age-adjusted annual incidence was stratified by sex and histology. Joinpoint regression was used to estimate annual percent change (APC) in incidence. Multivariable cox proportional hazards models were used to investigate survival trends. Results: Of 1689 MPM cases, most were male (55.4%), >50 years (80.0%), and white (75.2%). Age-adjusted incidence of MPM remained stable over time, with an average annual incidence of 1.02 cases/million. Epithelioid histology increased by 240% (APC 2.6; 95% CI: 0.7, 4.5), while incidence of undefined histology decreased significantly (APC −2.1; 95% CI: −3.1, −1.1). Cases treated with cancer-directed surgery increased from 27% to 43%. Overall median age-standardized survival was 11.6 months. Median age-standardized survival was 16.6 months for epithelioid histology but 2.0 months for sarcomatoid histology. Diagnosis in recent years (2015–2018 HR 0.51; 95% CI: 0.38, 0.67) and receipt of cancer-directed surgery (HR 0.84; 95% CI: 0.72, 0.98) were associated with improved survival. Conclusions: Although the overall incidence of MPM remained stable, recognition of epithelioid histology increased. Concurrent with an increase in cancer-directed surgery, MPM survival has improved.

Limited contemporary data has compared similarities and differences between total laparoscopic (LDP), hand-assisted (HALDP), and open distal pancreatectomy (ODP). This study aimed to examine similarities and differences in outcomes between these three approaches in a contemporary cohort. Methods: Patients undergoing elective LDP, HALDP, and ODP in the NSQIP dataset (2014–2019) were included. Descriptive statistics and multivariate regression analyses were employed to compare postoperative outcomes. Results: Among 5636 patients, 33.9% underwent LDP, 13.1% HALDP, and 52.9% ODP. Compared with the LDP approach, surgical site infections were more frequent in HALDP and ODP approaches (1.2% vs. 2.6% vs. 2.8%, respectively, p < 0.01). After adjustment, the LDP approach was associated with a significantly lower likelihood of surgical site infection (OR 0.25, p = 0.03) when compared to ODP. There was no difference in the likelihood of surgical site infection when HALDP was compared to ODP (OR 0.59, p = 0.40). Unadjusted operative times were similar between approaches (LDP = 192 min, HALDP = 193 min, ODP = 191 min, p = 0.59). After adjustment, the LDP approach had a longer operative time (+10.3 min, p = 0.04) compared to ODP. There was no difference in the adjusted operative time between HALDP and ODP approaches (+5.4 min, p = 0.80). Conclusions: Compared to ODP, LDP was associated with improved surgical site infection rates and slightly longer operative times. There was no difference in surgical site infection rates between ODP and HALDP. Surgeon comfort and experience should decide the operative approach, but it is important to discuss the differences between these approaches with patients.

Pancreatoblastoma is perceived to be aggressive in adults; however, data are limited due to the rarity of the disease. We benchmarked clinico-pathologic characteristics, outcomes, and survival of adult patients with pancreatoblastoma to a comparable PDAC cohort using the National Cancer Database (NCDB). This study included 301,204 patients: 35 with pancreatoblastoma and 301,169 PDAC patients. Pancreatoblastoma patients were younger than PDAC patients (56 vs. 69 years, p < 0.001). More pancreatoblastoma patients were managed at academic institutions (63.0% vs. 40.7%, p = 0.047). The most frequent primary site was the head and the neck of the pancreas. There were no differences in tumor size (4.2 cm vs. 3.7 cm, p = 0.828), lymph node positivity (14.3% vs. 26.4%, p = 0.103), or metastasis at time of diagnosis (31.4% vs. 46.1%, p = 0.081). The majority of pancreatoblastoma patients underwent resection compared to a minority of PDAC patients (69.7% vs. 15.5%, p < 0.001). Time from diagnosis to surgery was longer for pancreatoblastoma patients (33 vs. 14 days, p = 0.030). Pancreaticoduodenectomy was the most common type of resection in the pancreatoblastoma and PDAC groups (47.8% vs. 67.7%, p = 0.124). Among resected patients, pancreatoblastoma patients were less likely to receive radiation (4.8% vs. 37.0%, p = 0.002), but the use of chemotherapy was similar to PDAC patients (60.9% vs. 70.7%). After matching, median overall survival was longer for pancreatoblastoma than PDAC (59.8 months vs. 15.2 months, p = 0.014).

Background: Staging laparoscopy (SL) is an essential procedure for peritoneal metastasis (PM) detection. Although surgeons are expected to differentiate between benign and malignant lesions intraoperatively, this task remains difficult and error-prone. The aim of this study was to develop a novel multimodal machine learning (MML) model to differentiate PM from benign lesions by integrating morphologic characteristics with intraoperative SL images. Materials and Methods: Deep learning (DL) models were trained to classify peritoneal lesions in video frames of patients undergoing SL for suspected PM. Two expert surgeons blinded to the pathology results performed an objective morphologic evaluation of these lesions. Traditional machine learning (ML) models were trained to predict tumors based on their morphology. A combined MML model was developed by integrating the best-performing morphology- and image-based models. The MML model was evaluated using an independent test set, and its predictions were compared with those of 13 oncologic surgeons. Results: The cohort included videos of 67 patients, with 453 consecutive biopsied lesions (benign: n = 197; malignant: n = 256). The MML model achieved an area under the curve (AUC) of 0.88 [95% confidence interval (CI), 0.77–0.96], outperforming the best image-based DL model [AUC = 0.72 (95% CI, 0.54–0.87)], the best morphology-based ML [AUC = 0.86 (95% CI, 0.71–0.95)], and the surgeons’ predictions [AUC = 0.78 (95% CI, 0.53–1.00)]. Conclusions: A novel MML model combining the visual and morphologic characteristics of peritoneal lesions was developed and internally validated, demonstrating good discriminative power for classifying PM during SL. This model shows promise as an intraoperative decision-support tool for surgeons, enhancing PM recognition and potentially reducing unnecessary biopsies.

(1) Background: Comprehensive evaluation of guideline-concordant care (GCC) across all PDAC stages has yet to be thoroughly conducted. This study aimed to characterize treatment patterns and assess factors associated with receiving GCC among patients with pancreatic ductal adenocarcinoma (PDAC) in California. (2) Methods: Data on adult patients with PDAC were extracted from the California Cancer Registry (2004–2020). GCC is defined according to the recommendations provided by the National Comprehensive Cancer Network. We used multivariable logistic regression to identify factors associated with receiving GCC. A Cox model was used to examine the association of GCC with overall survival. (3) Results: A total of 50,346 PDAC patients were included (stage 1: 10%; stage 2: 25%; stage 3: 11%; stage 4: 54%). Only 46.7% of all patients received GCC (stage 1: 20%; stage 2: 40%; stage 3: 69%; stage 4: 50%). Only 31% of stage 1 patients underwent surgery. Factors inversely associated with receiving GCC were Hispanic ethnicity (OR 0.78; p < 0.001), Black race (OR 0.74; p < 0.001), having no insurance (OR 0.40; p < 0.001]), and a Charlson–Deyo score of ≥2 (OR 0.68; p < 0.001). Adherence to GCC was associated with improved survival (Hazard Ratio 0.39; p < 0.001). Notably, patients with stage 1 PDAC who received GCC had a median survival of 47 months vs. 8 months for those who did not. (4) Conclusions: Although stage 1 PDAC patients have the greatest potential for survival with GCC, only 20% of patients received such treatment. Thus, it is crucial to identify and address the modifiable factors contributing to these suboptimal care patterns.