Role of stereotactic body radiation in the enhancement of the quality of life in locally advanced pancreatic adenocarcinoma: a systematic review

Introduction Up to 30% of pancreatic cancer patients initially present locally advanced (LAPC). Stereotactic body radiation therapy (SBRT) may be an additional palliative treatment option when curative resection is no longer achievable. Our systematic review aimed to assess the effect of SBRT on the quality of life in LAPC. Methods We searched five databases until June 29th, 2021, for original articles that reported on SBRT for histologically proven LAPC in adults. Data were extracted on study characteristics, SBRT and additional therapy regimen, pain, biliary complications, nutrition, quality of life and other patient-reported outcomes. Statistical analyses were performed for population and survival data. Results 11 case series studies comprising 292 patients with a median age of 66 (range 34–89) years were included in the final analysis. The weighted average BED2;10 (radiation biologically effective dose, equivalent dose in 2 Gy fractions) was 54 Gy, delivered in 3 to 6 fractions. The individual studies used different scales and endpoints, not allowing a meta-analysis. Pain generally appeared to be improved by SBRT. SBRT significantly reduced jaundice. Local control was achieved in 71.7% of patients. Weight loss and nausea also tended to improve after SBRT. Conclusion SBRT of locally advanced irresectable pancreatic cancer is a promising approach for achieving local control and improving the quality of life. However, randomized controlled trials with larger cohorts are needed to assess the value of SBRT in pancreatic cancer therapy

Evidence for diagnosis of early chronic pancreatitis after three episodes of acute pancreatitis : a cross-sectional multicentre international study with experimental animal model

Chronic pancreatitis (CP) is an end-stage disease with no specific therapy; therefore, an early diagnosis is of crucial importance. In this study, data from 1315 and 318 patients were analysed from acute pancreatitis (AP) and CP registries, respectively. The population from the AP registry was divided into AP (n=983), recurrent AP (RAP, n=270) and CP (n=62) groups. The prevalence of CP in combination with AP, RAP2, RAP3, RAP4 and RAP5+was 0%, 1%, 16%, 50% and 47%, respectively, suggesting that three or more episodes of AP is a strong risk factor for CP. Laboratory, imaging and clinical biomarkers highlighted that patients with RAP3+do not show a significant difference between RAPs and CP. Data from CP registries showed 98% of patients had at least one AP and the average number of episodes was four. We mimicked the human RAPs in a mouse model and found that three or more episodes of AP cause early chronic-like morphological changes in the pancreas. We concluded that three or more attacks of AP with no morphological changes to the pancreas could be considered as early CP (ECP).The new diagnostic criteria for ECP allow the majority of CP patients to be diagnosed earlier. They can be used in hospitals with no additional costs in healthcare.Peer reviewe

Pancreatic family history does not predict disease progression but connotes alcohol consumption in adolescents and young adults with acute pancreatitis : analysis of an international cohort of 2,335 patients

BACKGROUND: In pediatric acute pancreatitis (AP), a family history of pancreatic diseases is prognostic for earlier onset of recurrent AP (ARP) and chronic pancreatitis (CP). No evidence supports the same association in adult-onset pancreatitis. Age-specific reasons for familial aggregation are also unclear. We aimed to examine the prognostic role of pancreatic family history for ARP/CP and observe possible underlying mechanisms. METHODS: We conducted a secondary analysis of the Hungarian Pancreatic Study Group’s (HPSG) multicenter, international, prospective registry of patients with AP, both children and adults. We compared the positive family history and the negative family history of pancreatic diseases, in different age groups, and analyzed trends of accompanying factors. Chi-square and Fisher exact tests were used. RESULTS: We found a higher rate of ARP/CP in the positive pancreatic family history group (33.7 vs. 25.9%, p = 0.018), peaking at 6–17 years. Idiopathic AP peaked in childhood in the positive family history group (75% 0–5 years) and was consistently 20–35% in the negative group. A higher rate of alcohol consumption/smoking was found in the positive groups at 12–17 years (62.5 vs. 15.8%, p = 0.013) and 18–29 years (90.9 vs. 58.1%, p = 0.049). The prevalence of diabetes and hyperlipidemia steadily rose with age in both groups. CONCLUSION: Positive family history most likely signifies genetic background in early childhood. During adolescence and early adulthood, alcohol consumption and smoking emerge—clinicians should be aware and turn to intervention in such cases. Contrary to current viewpoints, positive pancreatic family history is not a prognostic factor for ARP and CP in adults, so it should not be regarded that way

EASY-APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis

BACKGROUND: Acute pancreatitis (AP) is a potentially severe or even fatal inflammation of the pancreas. Early identification of patients at high risk for developing a severe course of the disease is crucial for preventing organ failure and death. Most of the former predictive scores require many parameters or at least 24 h to predict the severity; therefore, the early therapeutic window is often missed. METHODS: The early achievable severity index (EASY) is a multicentre, multinational, prospective and observational study (ISRCTN10525246). The predictions were made using machine learning models. We used the scikit‐learn, xgboost and catboost Python packages for modelling. We evaluated our models using fourfold cross‐validation, and the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and accuracy metrics were calculated on the union of the test sets of the cross‐validation. The most critical factors and their contribution to the prediction were identified using a modern tool of explainable artificial intelligence called SHapley Additive exPlanations (SHAP). RESULTS: The prediction model was based on an international cohort of 1184 patients and a validation cohort of 3543 patients. The best performing model was an XGBoost classifier with an average AUC score of 0.81 ± 0.033 and an accuracy of 89.1%, and the model improved with experience. The six most influential features were the respiratory rate, body temperature, abdominal muscular reflex, gender, age and glucose level. Using the XGBoost machine learning algorithm for prediction, the SHAP values for the explanation and the bootstrapping method to estimate confidence, we developed a free and easy‐to‐use web application in the Streamlit Python‐based framework (http://easy‐app.org/). CONCLUSIONS: The EASY prediction score is a practical tool for identifying patients at high risk for severe AP within hours of hospital admission. The web application is available for clinicians and contributes to the improvement of the model