Integrated Research Environment Research Articles

EXPLORATION OF THE THEMATIC CLUSTERING AND COLLABORATION OPPORTUNITIES IN KAZAKHSTANI RESEARCH

In today's academic environment, the rapid growth of research publications calls for advanced methods to organize and understand the extensive collections of academic work. This study aims to systematically categorize a substantial number of research paper abstracts from Kazakhstani institutions, focusing on identifying key themes and potential interdisciplinary collaboration opportunities. The dataset includes 13,356 abstracts from the Scopus database, covering a wide range of academic fields. The methodology of this research goes beyond traditional hand-done analysis by using advanced text analysis tools to organize the text data efficiently. This initial phase is crucial for summarizing each abstract's core content. The next steps of the analysis use this organized data to find and group similar thematic areas, considering the complex and multi-dimensional nature of academic research topics. The results reveal a diverse array of research themes, highlighting the dynamic academic contributions from Kazakhstan. Significant areas such as environmental science, technological advancements, linguistics, and cultural studies are among the prominent clusters identified. These insights not only provide an overview of current research directions but also highlight the potential for cross-disciplinary partnerships. Moreover, the findings have important implications for decision-makers, scholars, and educational institutions by illuminating key research areas and collaborative possibilities. This thematic overview acts as a guide for shaping research policies, fostering academic connections, and efficiently distributing resources within the scholarly community. Ultimately, this study adds to the academic conversation by offering a way to navigate and utilize the wealth of information in scientific literature, promoting a more collaborative and integrated research environment.

Trends in low-value cancer care during the COVID-19 pandemic.

To assess the association between the onset of the COVID-19 pandemic and change in low-value cancerservices. In this retrospective cohort study, we used administrative claims from the HealthCore Integrated Research Environment, a repository of medical and pharmacy data from US health plans representing more than 80 million members, between January 1, 2016, and March31, 2021. We used linear probability models to investigate the relation between the onset of the COVID-19 pandemic and 4 guideline-based metrics of low-value cancer care: (1) conventional fractionation radiotherapy instead of hypofractionated radiotherapy for early-stage breast cancer; (2) non-guideline-based antiemetic use for minimal-, low-, or moderate- to high-risk chemotherapies; (3) off-pathway systemic therapy; and (4) aggressive end-of-life care. We identified patients with new diagnoses of breast, colorectal, and/or lung cancer. We excluded members who did not have at least 6 months of continuous insurance coverage and members with prevalent cancers. Among 117,116 members (median [IQR] age, 60[53-69] years; 72.4% women), 59,729 (51.0%) had breast cancer, 25,751 (22.0%) had colorectal cancer, and 31,862(27.2%) had lung cancer. The payer mix was 18.7% Medicare Advantage or Medicare supplemental and 81.2% commercial non-Medicare. Rates of low-value cancer services exhibited minimal changes during the pandemic, as adjusted percentage-point differences were 3.93 (95%CI, 1.50-6.36) for conventional radiotherapy, 0.82 (95% CI, -0.62 to 2.25) for off-pathway systemic therapy, -3.62 (95% CI, -4.97 to -2.27) for non-guideline-based antiemetics, and 2.71(95% CI, -0.59 to 6.02) for aggressive end-of-life care. Low-value cancer care remained prevalent throughout the pandemic. Policy makers should consider changes to payment and incentive design to turn the tide against low-value cancer care.

The interactive Leipzig Corpus Miner: An extensible and adaptable text analysis tool for content analysis

We present the interactive Leipzig Corpus Miner (iLCM), which is the result of the development of an integrated research environment for the analysis of text data. The key features of iLCM compared to existing software tools for computer-assisted text analysis are its flexibility and scalability. The tool includes functions to offer commonly needed methods for automatic processing of text, such as preprocessing, standard text analysis, and visualization, which would be very time consuming without a ready-to-use software tool. To also provide more methodological flexibility, the iLCM is not tied to one specific class of research question, but can easily be extended to other applications. In this article, we will focus on the capabilities and the aspects of adaptability, extensibility, and data exchange with other tools from the field of empirical content analysis. We will present the features of the iLCM and showcase individual examples and a case study that demonstrates the practical use of the tool.

Integration of Library, Museum and Archive Resources: Together or Independently?

The article deals with modern problems of integration of digital resources of libraries, archives and museums. The author identifies and describes changes in the goal-setting system of activities within the framework of joint projects, caused by the digitalization of the internal activities of cultural institutions. The vector of change in the goals is directed from general goals to more practical ones, which include: the formation of an integrated research environment of a humanitarian profile; the development of digital collections as a new information product of libraries; the usage of integrated resources as a means of training and educating various groups of patrons; the creation of a joint virtual platform of historical memory institutions for professional communication and project implementation. Creating a new information product — digital collections — will require significant efforts, primarily a scientific and methodological study of the issues of their organization, taking into account the specifics of information products and their future place in the information consumption market. The creation of such products can be carried out not only by the efforts of the keepers of cultural and historical heritage, but also with the involvement of organizations engaged in artificial intelligence and semantic networks. Among the trends, there is a consistent leveling of the degree of digitalisation of libraries, archives and museums, their self-sufficiency and the desire to develop along their own information trajectories. The article provides examples of the most successful projects in the field of creating digital resources of historical memory institutions. There are identified the basic problems: departmental disunity, the lack of a publicly accessible reliable software and technology environment for interaction, as well as the lack of a system of scientific and methodical procedures and information support for resource integration activities. It is necessary to organize interdisciplinary vocational training centers for personnel to work in an integrated environment.

Venous thromboembolism incidence and risk factors associated with immune checkpoint inhibitors among patients with advanced non-small cell lung cancer

BackgroundVenous thromboembolism (VTE) is a significant cause of morbidity and mortality in patients with lung cancer. Systemic therapies, such as chemotherapy (chemo), are associated with increased risk of VTE. Immune...

Trends in low-value oncology care during the COVID-19 pandemic.

6594 Background: Low-value services, which provide minimal patient benefit while entailing costs and risks, are prevalent in cancer care. Shifts in cancer care delivery during the COVID-19 pandemic to minimize exposure provided opportunities for health systems and clinicians to prioritize higher-value over low-value oncology services. Methods: In this retrospective cohort study, we investigated the association between the COVID-19 pandemic period and low-value cancer care practices using administrative claims from the HealthCore Integrated Research Environment, consisting of ̃65 million members managed by 14 health plans across the US. We identified commercial or Medicare Advantage members diagnosed with breast, colorectal, or lung cancer between January 2015 and March 2021. Low-value cancer care practices were identified from peer-reviewed medical literature, including ASCO and ASTRO Choosing Wisely campaigns and evidence-based pathways. Five low-value practices were studied: (1) conventional fractionation instead of hypofractionation for early-stage breast cancer; (2) off-pathway systemic therapy; (3) non-guideline-based antiemetic use for minimal-, low-, or moderate-to-high-risk chemotherapies; (4) Positron Emission Tomography/Computed Tomography (PET/CT) instead of conventional CT for staging; and (5) aggressive end-of-life care (chemotherapy ≤14 days, multiple emergency department visits ≤30 days, ICU utilization ≤30 days, hospice initiation ≤3 days, and/or no hospice before death). We used linear probability models to evaluate the association between the COVID-19 period (March to December 2020) and the 5 outcomes, adjusting for patient, facility, geographic and temporal characteristics. Results: Among 204,581 members (mean age 63.1, 139,488 [68.1%] female), 83,593 (40.8%) had breast cancer, 56,373 (27.5%) had colon cancer, and 64,615 (31.5%) had lung cancer. Rates of low-value care were similar in pre-COVID vs. COVID periods: conventional radiotherapy: 22.1% vs. 9.4%; off-pathway systemic therapy: 36.7% vs. 43.2%; non-guideline-based antiemetics: 61.2% vs. 58.1%; PET/CT imaging: 39.9% vs. 41.3%; aggressive end-of-life care: 75.8% vs. 73.3%. In adjusted analyses, the COVID-19 period was associated with no changes in off-pathway therapy (adjusted percentage point difference [aPPD] 0.82, SD 0.08, p = 0.33), PET/CT imaging (aPPD 0.10, SD 0.005, p = 0.83), and aggressive end-of-life care (aPPD 2.71, SD 0.02, p = 0.16). Small changes in conventional radiotherapy (aPPD 3.93, SD 0.01, p < 0.01) and non-guideline-based antiemetics (aPPD -3.62, SD 0.006, p < 0.01), were noted. Conclusions: The shock of the COVID-19 pandemic did not meaningfully change several metrics of low-value cancer care. Broader changes to payment and incentive design should be considered to turn the tide toward higher-value cancer care.

Real-World Effectiveness of Once-Weekly Semaglutide From a US Commercially Insured and Medicare Advantage Population

PurposePatients managing type 2 diabetes mellitus (T2DM) often require combination therapy to meet their blood glucose control targets. With limited real-world evidence focused on the use of glucagon-like peptide 1 receptor agonist (GLP-1RA) therapies, the objective of this study was to describe the association between semaglutide once weekly (OW) initiation and changes in hemoglobin A1c (A1c) levels. MethodsThis retrospective, descriptive cohort study used the HealthCore Integrated Research Environment (HIRE) to examine commercially insured and Medicare Advantage patients who had T2DM while taking semaglutide OW from December 1, 2017, to April 30, 2019. The first semaglutide OW prescription fill was defined as the study index date. Changes in mean A1c levels and A1c target attainment were evaluated among an intention-to-treat (ITT) population (overall group). Furthermore, a persistent population (PP) analysis on the same outcomes was performed that was limited to ITT patients who were observed to continue to use semaglutide OW at the time of the postindex A1c measurement. In addition, these outcomes were explored in patients stratified based on prior use of GLP-1RA therapy (experienced vs naive) and baseline A1c values >9% (75 mmol/mol). FindingsA total of 1888 patients were identified in the overall ITT group. The mean change in the overall ITT group between preindex and postindex A1c values was −0.9% percentage points (−9.8 mmol/mol) (mean preindex A1c, 8.2% [66.1 mmol/mol]) and −1.1 percentage points (−12.0 mmol/mol) (mean preindex A1c, 8.2% [66.1 mmol/mol]) in the PP subgroup (all P < 0.001). Among the subgroup of patients with a baseline A1c value >9% (75 mmol/mol), percentage point changes in A1c were −2.2 (−24.0 mmol/mol) and −2.4 (−26.2 mmol/mol) (all P < 0.001). When accounting for prior GLP-1RA use, the GLP-1RA–naive stratum had double the mean reduction in A1c compared with the GLP-1RA–experienced stratum (−1.2 [−13.1 mmol/mol] vs −0.6 [−6.6 mmol/mol] percentage points). ImplicationsSemaglutide OW is associated with clinically and statistically significant A1C reduction and increases in reaching A1 targets using real-world data, even in GLP-1RA–experienced patients, despite more frequent use of insulin or sodium glucose transport protein 2 inhibitors in this group. Target A1c attainment significantly increased overall and within all subgroups and strata, with approximately half of all patients attaining an A1c value <7% (53 mmol/mol) and three-quarters attaining an A1c value <8% (64 mmol/mol).

MPN-067: Ruxolitinib Retreatment in Patients with Myelofibrosis: Real-World Evidence on Patient Characteristics and Outcomes

Context: Ruxolitinib is a Janus kinase (JAK)-1/JAK2 inhibitor FDA-approved for treatment of intermediate/high-risk myelofibrosis (MF). In the COMFORT studies, ruxolitinib reduced spleen volume in patients with MF (primary endpoint), with median time to response of 3 months. Case reports and clinical studies have shown some patients' symptoms and/or splenomegaly improve upon ruxolitinib reinitiation after interruption. For novel JAK inhibitors (JAKi), dose optimization and identifying indicators for treatment changes remain major challenges. Objective: To describe treatment patterns and clinical outcomes of patients with MF with ruxolitinib interruption and retreatment in clinical practices. Design, Setting, and Patients: Two independent patient care data sources were queried (not directly compared): (1) Cardinal Health Oncology Provider Extended Network (OPEN), (2) HealthCore Integrated Research Environment (HIRE®); retrospective review of medical charts was conducted. Entry criteria for analysis included: age ≥18 years; primary, post-polycythemia vera, or post-essential thrombocythemia MF diagnosis between 1/1/2012–12/31/2016 (OPEN) or 1/2013–11/2017 (HIRE®); use of RUX for MF; and documented physician-directed RUX interruption. Main Outcomes and Measures: MF-related symptoms, splenomegaly, and treatment dose and patterns. Results: 26 patients met entry criteria (n=12, OPEN; n=14, HIRE). Median (IQR) age at interruption was 69 (60–72, OPEN) and 73 (69–76, HIRE) years. Pre-interruption median (IQR) ruxolitinib treatment duration was 123 (57–391, OPEN) and 110 (37–148, HIRE) days; 50% had interruption within 3 months. Most interruptions were for adverse events (AEs; 50%, OPEN; 71%, HIRE), followed by (in OPEN) alternative treatment (17%), disease progression (8%), no response (8%), or loss of response (8%). Dose interruptions from AEs were primarily due to thrombocytopenia (17%, OPEN; 50%, HIRE) and anemia (8%, OPEN; 36%, HIRE). After restarting ruxolitinib, median (IQR) retreatment duration was 196 (54–553) and 166 (108–262) days, respectively. Symptoms improved in 45% and 43% of evaluable patients, respectively, and spleen size improved in 40% and 33%. Conclusions: MF symptoms and spleen size improved with ruxolitinib retreatment in some patients. One reason for clinical improvements upon reinitiation may be that initial treatment was discontinued before deriving full JAKi benefit. Future studies investigating JAKi treatment sequencing and reinitiation are warranted.

Ruxolitinib (RUX) retreatment in patients (Pts) with myelofibrosis (MF): Real-world evidence on pt characteristics and outcomes.

e19535 Background: RUX is a JAK1/JAK2 inhibitor FDA-approved for treatment (tx) of int/high risk MF. In the COMFORT studies, RUX reduced spleen volume in pts with MF (primary endpoint), with a median time to response of 3 mo. Case reports and clinical studies have shown some pts’ symptoms and/or splenomegaly improve upon RUX reinitiation after interruption. In the era of novel JAK inhibitors (JAKi), dose optimization and identifying indicators for tx changes remain major challenges. This study describes tx patterns and clinical outcomes of pts with MF with RUX interruption and retreatment in community-based clinical practices. Methods: Two independent patient care data sources were queried (not directly compared): (1) Cardinal Health Oncology Provider Extended Network (OPEN), (2) HealthCore Integrated Research Environment (HIRE); retrospective review of medical charts was conducted. Rigorous entry criteria for this analysis included: age ≥18 y; primary MF (PMF), post-polycythemia vera (PV) MF, or post-essential thrombocythemia (ET) MF diagnosis between 1/1/2012–12/31/2016 (OPEN) or 1/2013–11/2017 (HIRE); use of RUX for MF; and documented physician-directed RUX interruption. MF-related symptoms, splenomegaly, and tx dose and patterns were analyzed. Results: 26 pts met entry criteria (Table). Pre-interruption median (IQR) RUX tx duration was 123 (57–391, OPEN) and 110 (37–148, HIRE) days; 50% had tx interruption within 3 mo. Most interruptions were for adverse events (AEs; 50% and 71%, respectively), followed by (in OPEN) alternative tx (17%), disease progression (8%), no response (8%), or loss of response (8%). After restarting RUX, median (IQR) retreatment duration was 196 (54–553) and 166 (108–262) days, respectively. Symptoms improved in 45% and 43% of evaluable pts, respectively, and spleen size improved in 40% and 33%. Conclusions: Consistent with previous reports, MF symptoms and spleen size improved with RUX retreatment in some pts. While RUX was discontinued for various reasons, one reason for clinical improvements upon reinitiation may be that tx was discontinued before deriving full JAKi benefit. Future studies are warranted investigating JAKi tx sequencing and reinitiation. [Table: see text]

Development of predictive models to identify advanced-stage cancer patients in a US healthcare claims database

BackgroundAlthough healthcare databases are a valuable source for real-world oncology data, cancer stage is often lacking. We developed predictive models using claims data to identify metastatic/advanced-stage patients with ovarian cancer, urothelial carcinoma, gastric adenocarcinoma, Merkel cell carcinoma (MCC), and non-small cell lung cancer (NSCLC). MethodsPatients with ≥1 diagnosis of a cancer of interest were identified in the HealthCore Integrated Research Database (HIRD), a United States (US) healthcare database (2010–2016). Data were linked to three US state cancer registries and the HealthCore Integrated Research Environment Oncology database to identify cancer stage. Predictive models were constructed to estimate the probability of metastatic/advanced stage. Predictors available in the HIRD were identified and coefficients estimated by Least Absolute Shrinkage and Selection Operator (LASSO) regression with cross-validation to control overfitting. Classification error rates and receiver operating characteristic curves were used to select probability thresholds for classifying patients as cases of metastatic/advanced cancer. ResultsWe used 2723 ovarian cancer, 6522 urothelial carcinoma, 1441 gastric adenocarcinoma, 109 MCC, and 12,373 NSCLC cases of early and metastatic/advanced cancer to develop predictive models. All models had high discrimination (C > 0.85). At thresholds selected for each model, PPVs were all >0.75: ovarian cancer = 0.95 (95% confidence interval [95% CI]: 0.94–0.96), urothelial carcinoma = 0.78 (95% CI: 0.70–0.86), gastric adenocarcinoma = 0.86 (95% CI: 0.83–0.88), MCC = 0.77 (95% CI 0.68–0.89), and NSCLC = 0.91 (95% CI 0.90 – 0.92). ConclusionPredictive modeling was used to identify five types of metastatic/advanced cancer in a healthcare claims database with greater accuracy than previous methods.

Using claims data to attribute patients with breast, lung, or colorectal cancer to prescribing oncologists.

BackgroundAlternative payment models frequently require attribution of patients to individual physicians to assign cost and quality outcomes. Our objective was to examine the performance of three methods for attributing a patient with cancer to the likeliest physician prescriber of anticancer drugs for that patient using administrative claims data.MethodsWe used the HealthCore Integrated Research Environment to identify patients who had claims for anticancer medication along with diagnosis codes for breast, lung, or colorectal lung cancer between July 2013 and September 2017. The index date was the first date with a record for anticancer medication and cancer diagnosis code. Included patients had continuous medical coverage from 6 months before index to at least 7 days after index. Patients who received anticancer drugs during the 6 months prior to index were excluded. The three methods attributed each patient to the physician with whom the patient had the most evaluation and management (E&M) visits within a 90-day window around the index date (Method 1); the most E&M visits with no time window (Method 2); or the E&M visit nearest in time to the index date (Method 3). We assessed the performance of the methods using the percentage of the study cohort successfully attributed to a physician, and the positive predictive value (PPV) relative to available physician-reported data on patient(s) they treat.ResultsIn total, 70,641 patients were available for attribution to physicians. Percentages of the study cohort attributed to a physician were: Method 1, 92.6%; Method 2, 96.9%; and Method 3, 96.9%. PPVs for each method were 84.4%, 80.6%, and 75.8%, respectively.ConclusionWe found that a claims-based algorithm – specifically, a plurality method with a 90-day time window – correctly attributed nearly 85% of patients to a prescribing physician. Claims data can reliably identify prescribing physicians in oncology.

Opioid utilization patterns among patients with cancer and non-cancer pain.

Opioid pain medication continues to be an important treatment option for patients with moderate to severe cancer and non-cancer pain; however, limited evidence is available regarding differences in opioid use between these two populations. The objective of this analysis was to compare real-world opioid use patterns over time in these two populations. Retrospective analysis of administrative claims data. HealthCore Integrated Research Environment database. Adults with ≥1 opioid pharmacy claim (and a confirmed cancer diagnosis for the cancer pain cohort). Opioid doses and dose changes following the initial prescribed (index) dose were determined. In the cancer pain (n = 9,209) and non-cancer pain (n = 409,703) cohorts, median index opioid doses were 51.7 and 45.0 morphine-equivalent units (MEU), respectively, and median post-index opioid doses were 55.8 and 45.1 MEU for the cancer pain and non-cancer pain cohorts, respectively. The most common dose escalation in both groups was up to a dose doubling (cancer pain, 31.8 percent; non-cancer pain, 28.3 percent). The proportions of patients with dose increases exceeding two times the index dose were low and clinically comparable between cohorts (cancer pain, 9.9 percent; non-cancer pain, 7.4 percent). Opioid use was consistent between patients with cancer pain and non-cancer pain, including clinically comparable total daily opioid doses and consistent rates of dose escalations and chronic utilization. Opioid medications are an important element of cancer and non-cancer pain management; thus, access to appropriate therapies, use patterns, and risk assessment and management are important for both patient populations.

Variation in Outpatient Antibiotic Dispensing for Respiratory Infections in Children by Clinician Specialty and Treatment Setting.

Antibiotics are commonly prescribed for children with acute respiratory infections (ARIs). This study describes the distribution of ARI diagnoses and specifically quantifies antibiotic dispensing for bronchitis and upper respiratory infection (URI) by treatment setting and specialty. This retrospective, observational cross-sectional study used data from the HealthCore Integrated Research Environment containing claims from 14 commercial health plans for 2012 to 2014. Children (2-17 years) with first-episode ARI were identified by diagnosis of acute otitis media (AOM), sinusitis, pharyngitis, bronchitis or URI with no competing infections or chronic illnesses. Treatment setting was where diagnoses were made: primary care offices, urgent care centers (UCC), retail health clinics (RHCs) or emergency departments. Primary outcome measure was antibiotic prescription fills from pharmacies within 2 days of start of ARI episode. For URI, the highest proportions in antibiotic dispensing were ordered by office-based or UCC family physicians (28% and 30%, respectively) and office-based or UCC nurse practitioners/physician assistants (30% and 29%, respectively). Across all settings and specialties, there was high proportion of antibiotic dispensing for bronchitis (75%). Overall, 48% of 544,531 children diagnosed with ARI filled antibiotics. Nurse practitioners/physician assistants in RHC made the most diagnoses of AOM (24%) and streptococcal pharyngitis (22%). Outreach efforts to decrease antibiotic dispensing for URI can be focused on office-based and UCC family physicians and nurse practitioners/physician assistants. All specialties need widespread interventions to reduce antibiotic dispensing for bronchitis. RHC nurse practitioners/physician assistants can be targeted to reduce high proportion of AOM and streptococcal pharyngitis diagnoses.

Impact of opioid-induced constipation on healthcare resource utilization and costs for cancer pain patients receiving continuous opioid therapy.

Opioid therapy is often associated with adverse effects, including opioid-induced constipation (OIC), in patients receiving opioids for cancer pain. This retrospective observational cohort study evaluated healthcare utilization and costs during the first year after initiating opioid therapy among cancer patients with (cohort 1) and without (cohort 2) constipation. This study used administrative claims data from the HealthCore Integrated Research Environment between January 1, 2006, and April 30, 2014. Eligible patients included adults ≥ 18years with a diagnosis of cancer who initiated continuous opioid therapy (≥ 30days). Propensity scores were used to match patients with constipation in a 1:1 ratio to those without constipation. Generalized linear models were used to evaluate healthcare utilization and costs during the 12months after initiating opioid therapy. After matching, 1369 patients were included in each cohort. Patients with constipation were more than twice as likely as those without constipation to have an all-cause inpatient hospitalization (odds ratio [95% confidence interval (CI)], 2.47 [2.11-2.90]), or pain-related hospitalization (2.15 [1.82-2.54]) during the 12months after initiating therapy. Mean unadjusted overall healthcare costs during the first 12months post-index were $21,629 (95% CI, $14,850-$29,018) higher for patients with constipation than for those without constipation. For patients with constipation, total mean (SD) constipation-related costs were $9196 ($26,896). These results suggest that OIC is associated with significantly increased healthcare and economic burden in cancer pain patients and that early and ongoing recognition and management of OIC are unmet needs in this population.

Evaluation of a Diabetes Self-Management Program: Claims Analysis on Comorbid Illnesses, Health Care Utilization, and Cost.

BackgroundAn estimated 30.3 million Americans have diabetes mellitus. The US Department of Health and Human Services created national objectives via its Healthy People 2020 initiative to improve the quality of life for people who either have or are at risk for diabetes mellitus, and hence, lower the personal and national economic burden of this debilitating chronic disease. Diabetes self-management education interventions are a primary focus of this initiative.ObjectiveThe aim of this study was to evaluate the impact of the Better Choices Better Health Diabetes (BCBH-D) self-management program on comorbid illness related to diabetes mellitus, health care utilization, and cost.MethodsA propensity score matched two-group, pre-post design was used for this study. Retrospective administrative medical and pharmacy claims data from the HealthCore Integrated Research Environment were used for outcome variables. The intervention cohort included diabetes mellitus patients who were recruited to a diabetes self-management program. Control cohort subjects were identified from the HealthCore Integrated Research Environment by at least two diabetes-associated claims (International Classification of Diseases-Ninth Revision, ICD-9 250.xx) within 2 years before the program launch date (October 1, 2011-September 30, 2013) but did not participate in BCBH-D. Controls were matched to cases in a 3:1 propensity score match. Outcome measures included pre- and postintervention all-cause and diabetes-related utilization and costs. Cost outcomes are reported as least squares means. Repeated measures analyses (generalized estimating equation approach) were conducted for utilization, comorbid conditions, and costs.ResultsThe program participants who were identified in HealthCore Integrated Research Environment claims (N=558) were matched to a control cohort of 1669 patients. Following the intervention, the self-management cohort experienced significant reductions for diabetes mellitus–associated comorbid conditions, with the postintervention disease burden being significantly lower (mean 1.6 [SD 1.6]) compared with the control cohort (mean 2.1 [SD 1.7]; P=.001). Postintervention all-cause utilization was decreased in the intervention cohort compared with controls with −40/1000 emergency department visits vs +70/1000; P=.004 and −5780 outpatient visits per 1000 vs −290/1000; P=.001. Unadjusted total all-cause medical cost was decreased by US $2207 in the intervention cohort compared with a US $338 decrease in the controls; P=.001. After adjustment for other variables through structural equation analysis, the direct effect of the BCBH-D was –US $815 (P=.049).ConclusionsPatients in the BCBH-D program experienced reduced all-cause health care utilization and costs. Direct cost savings were US $815. Although encouraging, given the complexity of the patient population, further study is needed to cross-validate the results.

PCN213 - Economic Burden Of Locally Advanced Or Metastatic Merkel Cell Carcinoma In The United States: An Analysis Of Electronic Health Records

The objective of the study was to describe the demographic and clinical characteristics, health care resource utilization (HRU) and costs of managing patients with locally advanced or metastatic Merkel Cell Carcinoma (MCC). Eligible patients were identified in the HealthCore Integrated Research Environment (HIRE) if they had ≥1 ICD-9-CM or ICD-10 diagnosis code for MCC and were continuously enrolled for at least 6 months during study period (2010 - 2016). Locally advanced or metastatic disease (mMCC) was defined by distal recurrence or stage IIIa, IIIb, or stage IV disease, which was confirmed by linking patient data to 3 US state cancer registries and to HIRE-Oncology dataset. The index date was that of the first MCC diagnosis for newly diagnosed patients and the 180th day of continuous enrollment for all others. All HRU and costs were calculated on a per-patient per-year basis (PPPY) and standardized to 2016 US dollars. Patient characteristics were described at index date; treatments, HRU and costs were described during follow-up. A total of 48 mMCC patients were identified, of which 29.2% were newly diagnosed. The mean age was 71.8 (SD 11.6); 66.7% were male. The mean Deyo-Charlson Comorbidity Index score was 4.8 (SD 4.2). Median follow-up time was 14 months. During follow-up, 58.3% of patients received radiation treatment, 50.0% chemotherapy and 20.8% underwent surgery. Patients had a median of 70 outpatient visits (interquartile range [IQR]: 43.4-158.8) and 0.84 (IQR: 0.0-3.0) hospitalizations PPPY. The median all-cause medical PPPY costs were $56,680 (IQR: $26,580; $120,883), with outpatient care (55.9%) being the primary cost driver. This analysis describes the current clinical management and economic burden of mMCC patients in a real-world setting in the US. New therapies including recently approved immuno-oncology agents may provide effective treatment options for this mainly elderly patient population with significant comorbidities.

PCN214 - Locally Advanced Or Metastatic Urothelial Carcinoma In The United States: Economic Burden And Healthcare Utilization

To describe patient characteristics, comorbidities, treatments patterns, healthcare resource utilization (HRU) and costs in locally advanced or metastatic urothelial carcinoma patients. Eligible patients were identified in the HealthCore Integrated Research Environment (HIRE) if they had ≥1 ICD-9-CM or ICD-10 diagnosis code for urothelial carcinoma and were continuously enrolled for ≥6 months during the study period (2010 - 2016). Locally advanced or metastatic disease (mUC) staging was confirmed by patient record linkage with 3 US state cancer registries and HIRE-Oncology dataset. The index date was the date of first urothelial carcinoma diagnosis for newly diagnosed patients and the 180th day of continuous enrollment for all others. All HRU and costs were calculated on a per-patient per-year basis (PPPY) and adjusted to 2016 US dollars. Patient characteristics were described at index date, and treatments, HRU and costs were described during follow-up. A total of 791 patients with confirmed mUC were identified, 430 (54.4%) of which were newly diagnosed. Mean age ±SD was 69.3 ±11.6 years (median = 70) and 69.9% were men. The mean Deyo-Charlson Comorbidity Index was 3.3 ±3.7 (median = 2). Median follow-up was 15 months. Most patients had ≥1 surgical procedure (61.8 %), and/or received anti-cancer therapy (60.9%); use of radiation therapy was less frequent (19.6%). Patients with mUC had substantial HRU with medians of 72.5 outpatient visits (interquartile range [IQR]: 41.8-110.0) and 1.6 hospitalizations (IQR: 0.5-3.8) PPPY. Median all-cause medical costs amounted to $76,952 (IQR: $34,069; $148,787) PPPY, mainly driven by inpatient costs (36.9%). This analysis describes the clinical management and costs of mUC patients within a managed care environment. It demonstrates that mUC is associated with substantial healthcare resource use and costs, driven primarily by hospitalizations in a mostly elderly and highly comorbid patient population.

Occurrence and characteristics of hospitalizations during first-line chemotherapy among individuals with metastatic colorectal cancer.

691 Background: Choosing chemotherapy for metastatic colorectal cancer (mCRC) requires balancing clinical effectiveness and risk of complications. This study characterized real-world inpatient/ER hospitalizations (HOSP) during first-line chemotherapy among individuals with mCRC. Methods: We conducted a retrospective cohort study of adults with mCRC identified using claims data from the HealthCore Integrated Research Environment as initiating first-line chemotherapy from 12/23/2013 to 06/30/2016 (no minimum follow-up). Cohorts were analyzed in aggregate and for the most frequently observed first-line agents (5 overlapping subcohorts). HOSPs were identified from initiation of first-line chemotherapy to 30 days after the end of first-line chemotherapy or last available data. Results: A total of 717 individuals (mean age 55y; 58% male; 44%/39%/6%/12% with ECOG = 0/1/2+/missing; median follow-up 116 days) met study criteria. Metastasis was most commonly to the liver (51%) and 53% of patients had cancer-attributable morbidities. Chemotherapies included 5-FU (79%), oxaliplatin (67%), bevacizumab (58%), irinotecan (21%), and capecitabine (19%). Overall, 40% of patients had ≥1 HOSP [n = 285; total 415 events], ranging from 38% to 49% across the 5 chemotherapy-based subcohorts; 12% (n = 85) had &gt; 1 HOSP. The median time to first HOSP for patients with an event was 52 days. The median length of inpatient stays was 4 days; Infections/neutropenia (21%), bowel-related complications (17%), cardiac and circulatory disorders (9%), malnutrition (5%), pain (5%) and renal disease (2%) were the most common issues associated with inpatient HOSPs. An increase in HOSPs was observed with worsening ECOG status: 0 (34%), 1 (46%), and 2+ (65%). In regression analyses, ECOG≥1 was associated with a 64%-72% increase (p &lt; 0.01) in the odds of HOSPs compared to patients with ECOG = 0. Conclusions: Approximately 40% of mCRC patients had hospitalizations during the study period. Hospital stays were typically short and associated with infections, neutropenia, or bowel-related complications. Further research is needed to determine how many of these hospitalizations may be avoidable.

Validation of a Case-Finding Algorithm for Identifying Patients with Non-small Cell Lung Cancer (NSCLC) in Administrative Claims Databases.

Objective: To assess the validity of a treatments- and tests-based Case-Finding Algorithm for identifying patients with non-small cell lung cancer (NSCLC) from claims databases.Data sources: Primary data from the HealthCore Integrated Research Environment (HIRE)-Oncology database and the HealthCore Integrated Research Database (HIRD) were collected between June 1, 2014, and October 31, 2015.Study design: A comparative statistical evaluation using receiver operating characteristic (ROC) curve analysis and other validity measures was used to validate the NSCLC Case-Finding Algorithm vs. a control algorithm.Data collection: Patients with lung cancer were identified based on diagnosis and pathology classifications as NSCLC or small-cell lung cancer. Records from identified patients were linked to claims data from Anthem health plans. Three-month pre-index and post-index data were included.Principal findings: The NSCLC Case-Finding Algorithm had an area under the curve (AUC) of 0.88 compared with 0.53 in the control (p < 0.0001). Promising diagnostic accuracy was observed for the NSCLC Case-Finding Algorithm based on sensitivity (94.8%), specificity (81.1%), positive predictive value (PPV) (95.3%), negative predictive value (NPV) (79.6%), accuracy (92.1%), and diagnostic odds ratio (DOR) (78.8).Conclusions: The NSCLC Case-Finding Algorithm demonstrated strong validity for distinguishing patients with NSCLC from those with SCLC in claims data records and can be used for research into NSCLC populations.

Opioid utilization patterns among patients with cancer and noncancer pain.

194 Background: Opioids are used to manage moderate to severe pain in patients with cancer and non-cancer pain. Limited data exist comparing opioid utilization patterns between these two patient populations. Methods: This retrospective, commercial administrative claims database analysis (HealthCore Integrated Research Environment) investigated opioid use patterns, including opioid dose escalation, in adult patients with cancer-related (CP) and non-cancer-related pain (NCP). Adults (age ≥18 years) with at least one pharmacy claim for an opioid between July 1, 2006, and September 30, 2014, were identified (index date). Patients selected for analysis had to have continuous plan eligibility for 6 months pre- and 12 months post-index date and opioid use for at least 4 weeks. Patients with opioid use related to cancer pain were identified by a medical claim for a cancer diagnosis coded within 30 days prior to the index opioid date. Results: A total of 9,209 patients with CP and 409,703 patients with NCP were analyzed. Patients with CP were older than patients with NCP (mean [SD]: 62.6 [12.9] yrs vs. 49.3 [15.3] yrs); other demographics were similar between cohorts. The most common cancer diagnoses were breast, lung, and prostate. Hydrocodone was the most common opioid prescribed for both cohorts. Total mean (SD) days of opioid therapy were 167.1 (341.8) for CP and 196.6 (421.1) for NCP, with similar rates of opioid use for ≥1 year (10.6% for CP; 13.6% for NCP). Median index opioid doses were consistent between the cohorts (CP: 51.7 morphine-equivalent units (MEU); NCP: 45.0 MEU). Median post-index (after the first 30 days) opioid doses were also similar (CP: 55.8 MEU; NCP: 45.3 MEU). Post-index opioid dose reductions occurred in approximately one-third of both cohorts. Opioid dose escalations (up to dose doubling) occurred in 31.8% of CP and 28.3% of NCP patients. More patients died during the follow-up period in the CP cohort (24.1%) compared with the NCP cohort (0.02%). Conclusions: The use of opioids bears many similarities between patients with cancer pain and non-cancer pain, including clinically similar rates of chronic opioid utilization and dose escalation. This study was supported by AstraZeneca.