Tuesday, November 30, 2021

Diego Adrienzen Herrara on Geographic Disparities in Cardiovascular Death Among Patients with Myelodysplastic Syndromes.

 


Congratulations to Diego Adrienzen Herrara, MD, Assistant Professor of Medicine and CTS graduate student, for his recent publication on the geography of cardiovascular disease among patient with myelodysplastic syndromes.

Diego Adrianzen Herrera, Andrew D Sparks, Neil A. Zakai, Benjamin Littenberg; Geographic Disparities in Cardiovascular Death Among Patients with Myelodysplastic Syndromes. Blood 2021; 138 (Supplement 1): 3060. doi: https://doi.org/10.1182/blood-2021-146683

Introduction:

Acquired somatic mutations in hematopoietic stem cells lead to myelodysplastic syndromes (MDS) and are also associated with accelerated atherosclerosis. In subjects without MDS, these mutations constitute a potent cardiovascular risk factor: clonal hematopoiesis (CH). In a previous analysis, we demonstrated that an MDS diagnosis was an independent risk factor for cardiovascular disease (CVD) compared to propensity matched non-cancer controls. CVD is the most common non-cancer cause of death in MDS, and rural residence has been independently associated with many CVD risk factors. However, there are no studies examining the association of geographic disparities and cardiovascular death in patients with MDS.

Methods:

We identified adult patients diagnosed with MDS between 2001 and 2016 using the Surveillance, Epidemiology, and End Results (SEER) database. MDS risk was classified as low, intermediate or high, using International Classification of Diseases for Oncology 3 rd Edition (ICDO-3) codes. Rural and urban populations were categorized using the US Department of Agriculture's Rural-Urban Continuum Codes (RUCC). Primary cause of death reported to State Registries (SEER COD recode) was used to estimate cause-specific survival, calculated from date of MDS diagnosis to date of CVD-related death. Cases with missing data on any key variable were excluded from analysis. SEER*Stat version 8.3.9 was used to calculate incidence rates. Chi-square and t-test were used to compare categorical and continuous variables, respectively. Survival analyses employed the Kaplan-Meier method and log-rank tests. Multivariable Cox-proportional hazards repression estimated the association of rural residence with CVD death adjusting for age, sex, race, ethnicity, MDS risk, and geographic location. SAS version 9.4 was used for statistical analysis.

Results:

We included 52,750 patients with MDS, 56.8% were male and 84.8% were white. Low, intermediate and high histologic risk were seen in 18.7%, 64.4% and 16.9% respectively. Most patients were from urban areas (88%), however the estimated incidence rate for MDS was 6.7 per 100,000 per population at risk in both urban and rural populations. The rural MDS population was younger (median age 75 vs 77 years, p<0.004) and had a higher proportion of whites (90.5% vs 84%, p<0.001), but no difference in MDS risk distribution was noted by rurality (Table 1). Unadjusted analyses revealed a trend towards lower overall survival in the rural MDS population (24 vs 25 months, p=0.051). After adjusting for age, sex, race, ethnicity, MDS risk and area of residence, rural subjects with MDS had a 12% increased hazard (HR 1.12, 95%CI 1.03 - 1.22) for CVD-related death compared to urban subjects (Figure 1). Further, the adjusted HR for CVD-related death was 1.23 (CI95% 1.01 - 1.50) for those who lived in the most rural areas (RUCC codes 8 and 9, less than 2,500 urban population). Among young MDS patients (age<65), those residing in rural areas had a higher proportion of CVD-related death (6% vs 4.7%, p=0.031) and significantly shorter CVD-specific survival compared to urban patients (Figure 2). MDS histologic risk was also a significant factor in the multivariable model (Table 2). Compared to low risk MDS, patients with intermediate and high risk had adjusted HR for CVD-related death of 1.17 (95%CI 1.11 - 1.24) and 1.2 (95%CI 1.09 - 1.32), respectively. Other factors significantly associated with increased hazard for CVD-related death in the adjusted model were advancing age and male sex.

Discussion:

In a large population-based study, we found that rural area of residence is significantly associated with a higher burden of CVD-related death in subjects with MDS, after adjusting for demographic risk factors and MDS risk classification. Although aging is an important issue in rural areas, the geographical disparities in CVD-related death among MDS patients are not explained by age alone and the difference was notable in young MDS patients. These findings should prompt hematologists caring for patients with MDS from rural areas to rigorously evaluate and address CVD risk factors. As novel treatments improve cancer-specific survival in MDS, marginalized populations with different CVD risk profiles may be disproportionally affected by the cardiovascular risk from CH, which should be considered when developing MDS surveillance programs.

Thursday, November 11, 2021

Clinical Research Oriented Workshop (CROW) Meeting: Nov 11, 2021

 

Present:   Levi Bonnell, Justine Dee, Rocky Kelley, Jen Oshita, Liliane Savard, Adam Sprouse-Blum, Connie van Eeghen (9)

 1.                   Warm Up: Happy Veteran’s Day

2.                   Jen is looking for feedback on her research interest statement (page 4-6). On the Research Interest statement, Do my explanations of my dissertation projects make sense, did I provide too much/too little information, organization of the flow of information better?

Program description

The role of the Pathways program is to mentor early-career clinical scientists in developing strong foundations for independent research careers. Pathways assists participants with developing a 5-year research career plan, acclimating to a research career, building a publication record, and learning about funding mechanisms appropriate to this career stage. The specific goal of the program is to prepare eligible candidates to become competitive applicants for NIDCD Early Career Research (ECR) R21 (formerly the NIDCD R03) or K23 awards. It is intended as an initial step to enhance the training, retention, and funding success of clinical scientists in Communication Sciences and Disorders, with the ultimate goal of advancing the evidence base of the discipline.

a.       Great application; Jen is a compelling candidate

b.       Style:

                                                   i.      Reduce use of names; use citations

                                                 ii.      Focus on what the review committee really needs to know, starting with the Cover Letter; “more bones than color”

                                               iii.      Specify “accommodations” and “disparities”

c.       Content

                                                   i.      Add citations

                                                 ii.      Pump up the achievement of the F31 award

                                               iii.      Each section must stand on its own; no dependencies

                                               iv.      Carefully define CDs (communication disabilities) as inclusive of hearing loss – the province of reviewers who are audiologists – and note the cross org studies in Canada and the US – see a new one from UNC

                                                 v.      Allow the possibility of trans national comparisons

d.       Figure

                                                   i.      Enlarge, no wrap around text

                                                 ii.      Only one Figure title; make large and readable

                                               iii.      Remove the circles; this is not an animated presentation

                                               iv.      Make fonts consistent; let the narrative make your emphasis

3.                   Next week:  TBD

Wednesday, November 3, 2021

Rose to present at Society of Behavioral Medicine

Gail Rose, PhD, Assistant Professor of Psychiatry, will present the latest work of her research team at the Society of Behavioral Medicine Annual Meeting this April in Bethesda, MD. Congratulations, Gail!

A Measure for Integrated Behavioral Health in Primary Care: Improving Clarity and Utility of a Valid Measure

Gail Rose, Mindy L. McEntee, Tara L. Weldon, Dan Mullin, CR Macchi, Connie van Eeghen, Benjamin Littenberg, Matthew Martin, Juvena Hitt, and Rodger Kessler.

The integration of behavioral health (BH) into primary care is a critical step in delivering care that is efficient, effective, and satisfying to patients and clinicians. As models of integration vary across theory and practice, measurement plays a key role in disseminating standards, encouraging practice transformation, and supporting health services research because it enables comparisons across practices and within practices over time. The Practice Integration Profile (PIP) is a reliable and valid 30-item measure that assesses operational and procedural elements that align with established domains of BH integration in the AH
RQ Lexicon. The PIP measures independent attributes of integration with high reliability over time and can serve as a quality improvement or health services research tool. However, a measurement is limited by its level of clarity and utility. Prior analyses of PIP data and feedback from users suggested the measure, previously validated, could benefit from improvement.

Aims

To improve the clarity, utility, and interpretability of the PIP.

Design

Scale development

Methods

 Two rounds of structured cognitive interviews were conducted with clinicians in primary care settings. After each round, an analytic team coded interview transcripts using an iterative and consensus-driven process to identify recurring themes. Themes and recommendations for revisions were presented to our expert panel for review and modification. Panelists reviewed each item, suggested changes in light of feedback from interviews, and sought team consensus before making final decisions.

Results

Based on the themes, recommendations, and a published factor analysis of the PIP, revisions were undertaken to: 1) Clarify the meaning of items that were ambiguous, confusing, or overly broad. 2) Place items in the most useful and appropriate domains. 3) Standardize the response categories. 4) Eliminate redundant or overlapping items. The resulting measure has 28 items in five domains. Conclusion Healthcare measurement tools are more effective when items and formatting are clear and useful to target audiences. In response to identified clinical need, we undertook this data-driven revision to clarify the purpose of the measure, focus the domains, and refine each item to reflect the diverse integrated care clinic processes and practices. PIP 2.0 will need further examination to confirm it’s continuing use as a foundational tool for evaluating integrated care.