Radiomics-Based Outcome Prediction for Pancreatic Cancer Following Stereotactic Body Radiotherapy

(1) Background: Radiomics use high-throughput mining of medical imaging data to extract unique information and predict tumor behavior. Currently available clinical prediction models poorly predict treatment outcomes in pancreatic adenocarcinoma. Therefore, we used radiomic features of primary pancreatic tumors to develop outcome prediction models and compared them to traditional clinical models. (2) Methods: We extracted and analyzed radiomic data from pre-radiation contrast-enhanced CTs of 74 pancreatic cancer patients undergoing stereotactic body radiotherapy. A panel of over 800 radiomic features was screened to create overall survival and local-regional recurrence prediction models, which were compared to clinical prediction models and models combining radiomic and clinical information. (3) Results: A 6-feature radiomic signature was identified that achieved better overall survival prediction performance than the clinical model (mean concordance index: 0.66 vs. 0.54 on resampled cross-validation test sets), and the combined model improved the performance slightly further to 0.68. Similarly, a 7-feature radiomic signature better predicted recurrence than the clinical model (mean AUC of 0.78 vs. 0.66). (4) Conclusion: Overall survival and recurrence can be better predicted with models based on radiomic features than with those based on clinical features for pancreatic cancer

Safety of overlapping inpatient orthopaedic surgery: A multicenter study

BackgroundAlthough overlapping surgery is used to maximize efficiency, more empirical data are needed to guide patient safety. We conducted a retrospective cohort study to evaluate the safety of overlapping inpatient orthopaedic surgery, as judged by the occurrence of perioperative complications.MethodsAll inpatient orthopaedic surgical procedures performed at 5 academic institutions from January 1, 2015, to December 31, 2015, were included. Overlapping surgery was defined as 2 skin incisions open simultaneously for 1 surgeon. In comparing patients who underwent overlapping surgery with those who underwent non-overlapping surgery, the primary outcome was the occurrence of a perioperative complication within 30 days of the surgical procedure, and secondary outcomes included all-cause 30-day readmission, length of stay, and mortality. To determine if there was an association between overlapping surgery and a perioperative complication, we tested for non-inferiority of overlapping surgery, assuming a null hypothesis of an increased risk of 50%. We used an inverse probability of treatment weighted regression model adjusted for institution, procedure type, demographic characteristics (age, sex, race, comorbidities), admission type, admission severity of illness, and clustering by surgeon.ResultsAmong 14,135 cases, the frequency of overlapping surgery was 40%. The frequencies of perioperative complications were 1% in the overlapping surgery group and 2% in the non-overlapping surgery group. The overlapping surgery group was non-inferior to the non-overlapping surgery group (odds ratio [OR], 0.61 [90% confidence interval (CI), 0.45 to 0.83]; p < 0.001), with reduced odds of perioperative complications (OR, 0.61 [95% CI, 0.43 to 0.88]; p = 0.009). For secondary outcomes, there was a significantly lower chance of all-cause 30-day readmission in the overlapping surgery group (OR, 0.67 [95% CI, 0.52 to 0.87]; p = 0.003) and shorter length of stay (e, 0.94 [95% CI, 0.89 to 0.99]; p = 0.012). There was no difference in mortality.ConclusionsOur results suggest that overlapping inpatient orthopaedic surgery does not introduce additional perioperative risk for the complications that we evaluated. The suitability of this practice should be determined by individual surgeons on a case-by-case basis with appropriate informed consent.Level of evidenceTherapeutic Level III. See Instructions for Authors for a complete description of levels of evidence

Neoadjuvant anti-PD-1 immunotherapy promotes a survival benefit with intratumoral and systemic immune responses in recurrent glioblastoma.

Glioblastoma is the most common primary malignant brain tumor in adults and is associated with poor survival. The Ivy Foundation Early Phase Clinical Trials Consortium conducted a randomized, multi-institution clinical trial to evaluate immune responses and survival following neoadjuvant and/or adjuvant therapy with pembrolizumab in 35 patients with recurrent, surgically resectable glioblastoma. Patients who were randomized to receive neoadjuvant pembrolizumab, with continued adjuvant therapy following surgery, had significantly extended overall survival compared to patients that were randomized to receive adjuvant, post-surgical programmed cell death protein 1 (PD-1) blockade alone. Neoadjuvant PD-1 blockade was associated with upregulation of T cell- and interferon-γ-related gene expression, but downregulation of cell-cycle-related gene expression within the tumor, which was not seen in patients that received adjuvant therapy alone. Focal induction of programmed death-ligand 1 in the tumor microenvironment, enhanced clonal expansion of T cells, decreased PD-1 expression on peripheral blood T cells and a decreasing monocytic population was observed more frequently in the neoadjuvant group than in patients treated only in the adjuvant setting. These findings suggest that the neoadjuvant administration of PD-1 blockade enhances both the local and systemic antitumor immune response and may represent a more efficacious approach to the treatment of this uniformly lethal brain tumor

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 total subjects or 38.5% of sample), and whether pre-ECT and longitudinal changes (pre/post-ECT) in regional brain network biomarkers are associated with treatment-related changes in depression ratings. Results show the networks with the best predictive performance of ECT response were negative (anti-correlated) FC networks, which predict the post-ECT depression severity (continuous measure) with a 76.23% accuracy for remission prediction. FC networks with the greatest predictive power were concentrated in the prefrontal and temporal cortices and subcortical nuclei, and include the inferior frontal (IFG), superior frontal (SFG), superior temporal (STG), inferior temporal gyri (ITG), basal ganglia (BG), and thalamus (Tha). Several of these brain regions were also identified as nodes in the FC networks that show significant change pre-/post-ECT, but these networks were not related to treatment response. This study design has limitations regarding the longitudinal design and the absence of a control group that limit the causal inference regarding mechanism of post-treatment status. Though predictive biomarkers remained below the threshold of those recommended for potential translation, the analysis methods and results demonstrate the promise and generalizability of biomarkers for advancing personalized treatment strategies

Risk-Adjusted Capitation Payments: How Well Do Principal Inpatient Diagnosis-Based Models Work in the German Situation? Results From a Large Data Set

The Risk Adjustment Reform Act of 2001 mandates that a health-status-based risk adjustment mechanism has to be implemented in Germany's Statutory Health Insurance system by January 1, 2007. German parliament decided this as with the existing demographic risk adjustment model, that means there is cream skimming and sickness funds hesitate to engage in managing care for the chronical ill. Four approaches were used to test the feasibility of incorporating use of diagnosis as a proxy measure for health status in a German risk adjustment formula. The first two models used standard demographic and socio-demographic variables. The other two models are separately incorporating a simple binary indicator for hospitilization and Hierarchical Coexisting Conditions (HCCs: DxCG® Risk Adjustment Software Release 6.1) using inpatient diagnosis. Age and gender grouping accounted for 3.2% of the variation in total expenditures for concurrent as well as prospective models. The current German risk adjusters age, sex, and invalidity status account for 5.1% and 4.5% of the variance in the concurrent and prospective models respectively. There are substantial increases in explanatory power, however, when HCCs are added. Age, gender, invalidity status and HCC covariates explain about 37% of the variations of the total expenditures in a concurrent model and roughly 12% of the variations of total expenditures in a prospective model. For high-risk (cost) groups, substantial underprediction remains; conversely, for the low-risk group, represented by enrolees who did not show any health care expense in the base year, all of the models over-predict expenditure. --Risk Adjustment,HCCs,Germany