Search Results

Background: A prediction model for overall survival (OS) in metastatic pancreatic ductal adenocarcinoma (PDAC) including patient and treatment characteristics is currently not available, but it could be valuable for supporting clinicians in patient communication about expectations and prognosis. We aimed to develop a prediction model for OS in metastatic PDAC, called SOURCE-PANC, based on nationwide population-based data. Materials and Methods: Data on patients diagnosed with synchronous metastatic PDAC in 2015 through 2018 were retrieved from the Netherlands Cancer Registry. A multivariate Cox regression model was created to predict OS for various treatment strategies. Available patient, tumor, and treatment characteristics were used to compose the model. Treatment strategies were categorized as systemic treatment (subdivided into FOLFIRINOX, gemcitabine/nab-paclitaxel, and gemcitabine monotherapy), biliary drainage, and best supportive care only. Validation was performed according to a temporal internal–external cross-validation scheme. The predictive quality was assessed with the C-index and calibration. Results: Data for 4,739 patients were included in the model. Sixteen predictors were included: age, sex, performance status, laboratory values (albumin, bilirubin, CA19-9, lactate dehydrogenase), clinical tumor and nodal stage, tumor sublocation, presence of distant lymph node metastases, liver or peritoneal metastases, number of metastatic sites, and treatment strategy. The model demonstrated a C-index of 0.72 in the internal–external cross-validation and showed good calibration, with the intercept and slope 95% confidence intervals including the ideal values of 0 and 1, respectively. Conclusions: A population-based prediction model for OS was developed for patients with metastatic PDAC and showed good performance. The predictors that were included in the model comprised both baseline patient and tumor characteristics and type of treatment. SOURCE-PANC will be incorporated in an electronic decision support tool to support shared decision-making in clinical practice.

Background: Cachexia is common in patients with esophagogastric cancer and is associated with increased mortality. Nutritional screening and dietetic interventions can be helpful in preventing evolvement of cachexia. Our aim was to study the real-world prevalence and prognostic value of pretreatment cachexia on overall survival (OS) using patient-reported weight loss, and to explore dietetic interventions in esophagogastric cancer. Materials and Methods: Patients with esophagogastric cancer (2015–2018), regardless of disease stage, who participated in the Prospective Observational Cohort Study of Esophageal-Gastric Cancer Patients (POCOP) and completed patient-reported outcome measures were included. Data on weight loss and dietetic interventions were retrieved from questionnaires before start of treatment (baseline) and 3 months thereafter. Additional patient data were obtained from the Netherlands Cancer Registry. Cachexia was defined as self-reported >5% half-year body weight loss at baseline or >2% in patients with a body mass index (BMI) <20 kg/m² according to the Fearon criteria. The association between cachexia and OS was analyzed using multivariable Cox proportional hazard analyses adjusted for sex, age, performance status, comorbidities, primary tumor location, disease stage, histology, and treatment strategy. Results: Of 406 included patients, 48% had pretreatment cachexia, of whom 65% were referred for dietetic consultation at baseline. The proportion of patients with cachexia was the highest among those who received palliative chemotherapy (59%) or best supportive care (67%). Cachexia was associated with decreased OS (hazard ratio, 1.52; 95% CI, 1.11–2.09). Median weight loss after 3-month follow-up was lower in patients with cachexia who were referred to a dietician at baseline compared with those who were not (0% vs 2%; P=.047). Conclusions: Nearly half of patients with esophagogastric cancer have pretreatment cachexia. Dietetic consultation at baseline was not reported in more than one-third of the patients with cachexia. Because cachexia was independently associated with decreased survival, improving nutritional screening and referral for dietetic consultation are warranted to prevent further deterioration of malnutrition and mortality.

Background: Personalized prediction of treatment outcomes can aid patients with cancer when deciding on treatment options. Existing prediction models for esophageal and gastric cancer, however, have mostly been developed for survival prediction after surgery (ie, when treatment has already been completed). Furthermore, prediction models for patients with metastatic cancer are scarce. The aim of this study was to develop prediction models of overall survival at diagnosis for patients with potentially curable and metastatic esophageal and gastric cancer (the SOURCE study). Methods: Data from 13,080 patients with esophageal or gastric cancer diagnosed in 2015 through 2018 were retrieved from the prospective Netherlands Cancer Registry. Four Cox proportional hazards regression models were created for patients with potentially curable and metastatic esophageal or gastric cancer. Predictors, including treatment type, were selected using the Akaike information criterion. The models were validated with temporal cross-validation on their C-index and calibration. Results: The validated model’s C-index was 0.78 for potentially curable gastric cancer and 0.80 for potentially curable esophageal cancer. For the metastatic models, the c-indices were 0.72 and 0.73 for esophageal and gastric cancer, respectively. The 95% confidence interval of the calibration intercepts and slopes contain the values 0 and 1, respectively. Conclusions: The SOURCE prediction models show fair to good c-indices and an overall good calibration. The models are the first in esophageal and gastric cancer to predict survival at diagnosis for a variety of treatments. Future research is needed to demonstrate their value for shared decision-making in clinical practice.