PGx testing provides significant 'real world' cost savings, while simultaneously improving adherence in a difficult to treat psychiatric population. Limitations of this study include the lack of therapeutic efficacy follow-up data and possible confounding due to matching only on demographic and psychiatric variables.

BackgroundPatients with COPD often experience severe exacerbations involving hospitalization, which accelerate lung function decline and reduce quality of life. This study aimed to develop and validate a predictive model to identify patients at risk of developing severe COPD exacerbations using administrative claims data, to facilitate appropriate disease management programs.MethodsA predictive model was developed using a retrospective cohort of COPD patients aged 55–89 years identified between July 1, 2010 and June 30, 2013 using Humana’s claims data. The baseline period was 12 months postdiagnosis, and the prediction period covered months 12–24. Patients with and without severe exacerbations in the prediction period were compared to identify characteristics associated with severe COPD exacerbations. Models were developed using stepwise logistic regression, and a final model was chosen to optimize sensitivity, specificity, positive predictive value (PPV), and negative PV (NPV).ResultsOf 45,722 patients, 5,317 had severe exacerbations in the prediction period. Patients with severe exacerbations had significantly higher comorbidity burden, use of respiratory medications, and tobacco-cessation counseling compared to those without severe exacerbations in the baseline period. The predictive model included 29 variables that were significantly associated with severe exacerbations. The strongest predictors were prior severe exacerbations and higher Deyo–Charlson comorbidity score (OR 1.50 and 1.47, respectively). The best-performing predictive model had an area under the curve of 0.77. A receiver operating characteristic cutoff of 0.4 was chosen to optimize PPV, and the model had sensitivity of 17%, specificity of 98%, PPV of 48%, and NPV of 90%.ConclusionThis study found that of every two patients identified by the predictive model to be at risk of severe exacerbation, one patient may have a severe exacerbation. Once at-risk patients are identified, appropriate maintenance medication, implementation of disease-management programs, and education may prevent future exacerbations.

Objective: To use novel statistical methods for analyzing the effect of lesion set on (long-standing) persistent atrial fibrillation (AF) in the Cardiothoracic Surgical Trials Network trial of surgical ablation during mitral valve surgery (MVS). Methods: Two hundred sixty such patients were randomized to MVS + surgical ablation or MVS alone. Ablation was randomized between pulmonary vein isolation and biatrial maze. During 12 months postsurgery, 228 patients (88%) submitted 7949 transtelephonic monitoring (TTM) recordings, analyzed for AF, atrial flutter (AFL), or atrial tachycardia (AT). As previously reported, more ablation than MVS-alone patients were free of AF or AF/AFL at 6 and 12 months (63% vs 29%; P < .001) by 72-hour Holter monitoring, without evident difference between lesion sets (for which the trial was underpowered). Results: Estimated freedom from AF/AFL/ATon any transmission trended higher after biatrial maze than pulmonary vein isolation (odds ratio, 2.31; 95% confidence interval, 0.95–5.65; P = .07) 3 to 12 months postsurgery; estimated AF/AFL/AT load (ie, proportion of TTM strips recording AF/AFL/AT) was similar (odds ratio, 0.90; 95% confidence interval, 0.57–1.43; P .6). Within 12 months, estimated prevalence of AF/AFL/AT by TTM was 58% after MVS alone, and 36% versus 23% after pulmonary vein isolation versus biatrial maze (P<.02). Conclusions: Statistical modeling using TTM recordings after MVS in patients with (long-standing) persistent AF suggests that a biatrial maze is associated with lower AF/AFL/AT prevalence, but not a lower load, compared with pulmonary vein isolation. The discrepancy between AF/AFL/AT prevalence assessed at 2 time points by Holter monitoring versus weekly TTM suggests the need for a confirmatory trial, reassessment of definitions for failure after ablation, and validation of statistical methods for assessing atrial rhythms longitudinally.

Secondary SSI after CABG continues to be an important source of morbidity. This serious complication often occurs after discharge and is associated with open SVG harvesting, larger body mass, and blood transfusions. Patients with a secondary SSI have longer lengths of stay and are readmitted more frequently.

1585 Background: While aNSCLC is a leading cause of US cancer deaths, targeted therapies and immune checkpoint inhibitors (ICPi) have emerged as important new treatment options for these pts NCCN guidelines recommend testing of eight genes in aNSCLC patients at diagnosis. Targetable alterations (TA) in four genes, EGFR, ALK, ROS1, and BRAF, are associated with FDA-approved therapies. The labels for ICPis indicate that pts with TAs in EGFR and ALK are not candidates for first line treatment with ICPi. Methods: The Integra Connect database, which includes electronic medical record (EMR) and claims data on approximately 600,000 cancer patients, was queried across five community oncology practices (289 oncologists) to identify aNSCLC patients (stage 3B or 4) treated since January 2017. Manual review of charts was done to abstract tumor type/stage, drug regimens, and evidence of somatic genetic testing. A Wilcoxon rank sum test was used to test difference in time to results (TTR) for blood- vs tissue-based tests. Results: A total of 1,203 aNSCLC patients were identified. Testing rates varied from 54% for EGFR to 22% for all 4 genes (table). 163 patients had a TA in EGFR, ALK, ROS1 or BRAF, and 55% of these pts did not receive targeted therapy. 84 pts with TA’s in EGFR or ALK had no evidence of progression on targeted therapy, yet 31 (37%) received an ICPi; 24% had the TA test result prior to ICPi use and 13% received the TA result after starting ICPi. Median TTR for blood-based somatic tests was shorter than tissue-based tests (4 vs 14 days, p-value= 3.5-e07). Conclusions: Our analysis in the community oncology setting for aNSCLC pts finds evidence of underutilization of genomic testing, underutilization of targeted therapies, and ICPi use outside of label. Further research is needed to identify strategies to increase testing in aNSCLC pts to provide physicians with the information needed to make optimal treatment decisions. [Table: see text]