No abstract

587 Background: Patient survival is impacted by several factors, one of which is stage at diagnosis. From 1976 to 2014, CRC death rate in the United States (US) declined by 51%. This retrospective study was conducted using US Surveillance, Epidemiology and End Results (SEER) data to evaluate 1- and 5-year relative survival for patients with CRC by American Joint Committee on Cancer (AJCC) stage, age and sex at diagnosis. Methods: The study included adults (age ≥20 years) in the SEER-18 registry diagnosed with CRC in 2004-2014. One- and 5-year relative survival rates were stratified by AJCC stage, age group (20-64 vs. ≥65 years) and sex. Results: One- and 5-year survival was calculated by age and stage at diagnosis (Table), and by sex (data not shown). Overall, 5-year survival rates declined compared to 1-year rates, with the biggest decline observed in stage IV patients. Survival was higher in the younger cohort than in patients ≥65 years of age regardless of stage. Both men and women diagnosed with stage IIB CRC had lower 1- and 5-year survival compared to stage IIIA and IIIB groups, consistent with previous findings. Patients with stage IV had the lowest survival irrespective of age or sex. Conclusions: Overall trends in 1- and 5-year relative survival for CRC varied by AJCC stage, age and sex. Since survival is lowest among CRC patients diagnosed at stage IV, particularly in elderly patients, it reinforces the need for early diagnosis and availability of innovative late stage therapies in this population. [Table: see text]

Background: Relapsing-remitting multiple sclerosis (RRMS) has a major impact on affected patients; therefore, improved understanding of RRMS is important, particularly in the context of real-world evidence. Objectives: To develop and validate algorithms for identifying patients with RRMS in both unstructured clinical notes found in electronic health records (EHRs) and structured/coded health care claims data. Methods: US Integrated Delivery Network data (2010 e2014) were queried for study inclusion criteria (possible multiple sclerosis [MS] base cohort): one or more MS diagnosis code, patients aged 18 years or older, 1 year or more baseline history, and no other demyelinating diseases. Sets of algorithms were developed to search narrative text of unstructured clinical notes (EHR clinical notesebased algorithms) and structured/coded data (claims-based algorithms) to identify adult patients with RRMS, excluding patients with evidence of progressive MS. Medical records were reviewed manually for algorithm validation. Positive predictive value was calculated for both EHR clinical notesebased and claims-based algorithms. Results: From a sample of 5308 patients with possible MS, 837 patients with RRMS were identified using only the EHR clinical notesebased algorithms and 2271 patients were identified using only the claims-based algorithms; 779 patients were identified using both algorithms. The positive predictive value was 99.1% (95% confidence interval [CI], 94.2% e100%) for the EHR clinical notesebased algorithms and 94.6% (95% CI, 89.1%e97.8%) to 94.9% (95% CI, 89.8%e97.9%) for the claims-based algorithms. Conclusions: The algorithms evaluated in this study identified a real-world cohort of patients with RRMS without evidence of progressive MS that can be studied in clinical research with confidence.

BackgroundVenous thromboembolic co-morbidities can have a significant impact on treatment response, treatment options, quality of life, and ultimately, survival from cancer. There is a dearth of published information on venous thromboembolic co-morbidity among older soft tissue sarcoma patients.MethodsSEER-Medicare linked data (1993–2005) was utilized for this retrospective cohort analysis (n = 3,480 soft tissue sarcoma patients). Non-cancer patients were frequency-matched by age to cancer patients at a ratio of 1:1; coverage and follow-up requirements were the same as for soft tissue sarcoma cases. Venous thromboembolic events were divided into three groups of interest: deep vein thrombosis, pulmonary embolism, and other thromboembolic events. Relative incidence rates of venous thromboembolic events in soft tissue sarcoma patients with a recent history of cardiovascular event or venous thromboembolic event (12 months before diagnosis) versus soft tissue sarcoma patients without such a recent history were calculated using the Cox proportional hazard models. The Cox proportional hazard model was used to build predictive models to identify important risk factors for each venous thromboembolic event of interest among soft tissue sarcoma patients. Relative incidence rate of VTEs in cancer patients (12 months after diagnosis) versus non-cancer cases (12 months after index date) was calculated using multivariable Cox proportional hazard models.ResultsWe observed that among older soft tissue sarcoma patients, 10.6% experienced a deep vein thrombosis, 3.0% experienced a pulmonary embolism, and 3.1% experienced other thromboembolic events in the 12 months after sarcoma diagnosis. On average, 60% of venous thromboembolic events occurred in the first 90 days after sarcoma diagnosis. The highest rates of deep vein thrombosis and pulmonary embolism after sarcoma diagnosis were seen in patients with sarcoma not otherwise specified (deep vein thrombosis: 204/1,000 p-y and pulmonary embolism: 50/1,000 p-y). Recent history of a venous thromboembolic event was the strongest predictor of a subsequent venous thromboembolic event after soft tissue sarcoma diagnosis.ConclusionVenous thromboembolic events are common and serious co-morbidities that should be closely monitored in older soft tissue sarcoma patients.