Hodgkin lymphoma treatment with ABVD in the US and the EU: neutropenia occurrence and impaired chemotherapy delivery.

BACKGROUND: In newly diagnosed patients with Hodgkin lymphoma (HL) the effect of doxorubicin, bleomycin, vinblastine and dacarbazine (ABVD)-related neutropenia on chemotherapy delivery is poorly documented. The aim of this analysis was to assess the impact of chemotherapy-induced neutropenia (CIN) on ABVD chemotherapy delivery in HL patients. STUDY DESIGN: Data from two similarly designed, prospective, observational studies conducted in the US and the EU were analysed. One hundred and fifteen HL patients who started a new course of ABVD during 2002-2005 were included. The primary objective was to document the effect of neutropenic complications on delivery of ABVD chemotherapy in HL patients. Secondary objectives were to investigate the incidence of CIN and febrile neutropenia (FN) and to compare US and EU practice with ABVD therapy in HL. Pooled data were analysed to explore univariate associations with neutropenic events. RESULTS: Chemotherapy delivery was suboptimal (with a relative dose intensity < or = 85%) in 18-22% of patients. The incidence of grade 4 CIN in cycles 1-4 was lower in US patients (US 24% vs. EU 32%). Patients in both the US and the EU experienced similar rates of FN across cycles 1-4 (US 12% vs. EU 11%). Use of primary colony-stimulating factor (CSF) prophylaxis and of any CSF was more common in the US than the EU (37% vs. 4% and 78% vs. 38%, respectively). The relative risk (RR) of dose delays was 1.54 (95% confidence interval [CI] 1.08-2.23, p = 0.036) for patients with vs. without grade 4 CIN and the RR of grade 4 CIN was 0.35 (95% CI 0.12-1.06, p = 0.046) for patients with vs. without primary CSF prophylaxis. CONCLUSIONS: In this population of HL patients, CIN was frequent and FN occurrence clinically relevant. Chemotherapy delivery was suboptimal. CSF prophylaxis appeared to reduce CIN rates.

Using electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study.

BACKGROUND: The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms that employ EHRs in research are needed to produce clinical evidence in real-world medical settings for informing learning healthcare systems. Adults with comorbid diabetes and substance use disorders (SUDs) tend to use costly inpatient treatments; however, there is a lack of empirical data on implementing behavioral healthcare to reduce health risk in adults with high-risk diabetes. Given the complexity of high-risk patients' medical problems and the cost of conducting randomized trials, a feasibility project is warranted to guide practical study designs. METHODS: We describe the study design, which explores the feasibility of implementing substance use Screening, Brief Intervention, and Referral to Treatment (SBIRT) among adults with high-risk type 2 diabetes mellitus (T2DM) within a home-based primary care setting. Our study includes the development of an integrated EHR datamart to identify eligible patients and collect diabetes healthcare data, and the use of a geographic health information system to understand the social context in patients' communities. Analysis will examine recruitment, proportion of patients receiving brief intervention and/or referrals, substance use, SUD treatment use, diabetes outcomes, and retention. DISCUSSION: By capitalizing on an existing T2DM project that uses home-based primary care, our study results will provide timely clinical information to inform the designs and implementation of future SBIRT studies among adults with multiple medical conditions.

SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication

We propose a novel unsupervised approach for linking records across arbitrarily many files, while simultaneously detecting duplicate records within files. Our key innovation is to represent the pattern of links between records as a {\em bipartite} graph, in which records are directly linked to latent true individuals, and only indirectly linked to other records. This flexible new representation of the linkage structure naturally allows us to estimate the attributes of the unique observable people in the population, calculate $k$-way posterior probabilities of matches across records, and propagate the uncertainty of record linkage into later analyses. Our linkage structure lends itself to an efficient, linear-time, hybrid Markov chain Monte Carlo algorithm, which overcomes many obstacles encountered by previously proposed methods of record linkage, despite the high dimensional parameter space. We assess our results on real and simulated data.