Faculty Bibliography

Migraine is a leading cause of disability worldwide. A minority of individuals with migraine develop resistant or refractory conditions characterised by ≥ 8 monthly days of debilitating headaches and inadequate response, intolerance, or contraindication to ≥3 or all preventive drug classes, respectively. Resistant and refractory migraine are emerging clinical definitions stemming from better knowledge of the pathophysiology of migraine and from the advent of migraine-specific preventive treatments. Resistant migraine mostly results from drug failures, while refractory migraine has complex and still unknown mechanisms that impair the efficacy of preventive treatments. Individuals with resistant migraine can be treated with migraine-specific preventive drugs. The management of refractory migraine is challenging and often unsuccessful, being based on combinations of different drugs and non-pharmacological treatment. Future research should aim to identify individuals at risk of developing treatment failures, prevent the condition, investigate the mechanisms of refractoriness to treatments, and find effective treatment strategies.

BACKGROUND:We previously reported a higher incidence of a pathogenic germline variant in the kinase insert domain receptor (KDR) in melanoma patients compared to the general population. Here, we dissect the impact of this genotype on melanoma tumor growth kinetics, tumor phenotype, and response to treatment with immune checkpoint inhibitors (ICIs) or targeted therapy. METHODS:The KDR genotype was determined and the associations between the KDR Q472H variant (KDR-Var), angiogenesis, tumor immunophenotype, and response to MAPK inhibition or ICI treatment were examined. Melanoma B16 cell lines were transfected with KDR-Var or KDR wild type (KDR-WT), and the differences in tumor kinetics were evaluated. We also examined the impact of KDR-Var on the response of melanoma cells to a combination of VEGFR inhibition with MAPKi. RESULTS:= 0.0159), and KDR-Var cells showed synergistic cytotoxicity to the combination of dabrafenib and lenvatinib. CONCLUSIONS:Our data demonstrate a role of germline KDR-Var in modulating melanoma behavior, including response to treatment. Our data also suggest that anti-angiogenic therapy might be beneficial in patients harboring this genotype, which needs to be tested in clinical trials.

Greater maternal depressive symptoms are consistently associated with higher levels of behavioral difficulties in children, emerging in early childhood and with long-lasting consequences for children's development. Interventions promoting early relational health have been shown to have benefits for children's behavior; however, these impacts are not always realized in the context of maternal depression. This study examined whether tiered programs could address this limitation by focusing on both parenting, through universal primary prevention, and psychosocial stressors and parent mental health, through tailored secondary prevention. Analysis of a randomized controlled trial (RCT) of the Smart Beginnings (SB) intervention was conducted to determine whether SB attenuated the association between maternal depression and early childhood internalizing and externalizing behaviors. Maternal depression significantly predicted both internalizing and externalizing behaviors in linear regression models. Further, there was a significant interaction between maternal depression and treatment group, such that among mothers with higher depressive symptoms, the SB treatment attenuated the magnitude of the association between depression and child behavior. Findings suggest that while parenting support is important for all families, it may be particularly critical for those with higher levels of depression and underscores the need to consider multidimensional family processes in both research and clinical practice.

Cardiovascular-kidney-metabolic (CKM) syndrome is a novel construct recently defined by the American Heart Association in response to the high prevalence of metabolic and kidney disease. Epidemiological data demonstrate higher absolute risk of both atherosclerotic cardiovascular disease (CVD) and heart failure as an individual progresses from CKM stage 0 to stage 3, but optimal strategies for risk assessment need to be refined. Absolute risk assessment with the goal to match type and intensity of interventions with predicted risk and expected treatment benefit remains the cornerstone of primary prevention. Given the growing number of therapies in our armamentarium that simultaneously address all 3 CKM axes, novel risk prediction equations are needed that incorporate predictors and outcomes relevant to the CKM context. This should also include social determinants of health, which are key upstream drivers of CVD, to more equitably estimate and address risk. This scientific statement summarizes the background, rationale, and clinical implications for the newly developed sex-specific, race-free risk equations: PREVENT (AHA Predicting Risk of CVD Events). The PREVENT equations enable 10- and 30-year risk estimates for total CVD (composite of atherosclerotic CVD and heart failure), include estimated glomerular filtration rate as a predictor, and adjust for competing risk of non-CVD death among adults 30 to 79 years of age. Additional models accommodate enhanced predictive utility with the addition of CKM factors when clinically indicated for measurement (urine albumin-to-creatinine ratio and hemoglobin A1c) or social determinants of health (social deprivation index) when available. Approaches to implement risk-based prevention using PREVENT across various settings are discussed.

BACKGROUND:Treatment with methadone and buprenorphine medications for opioid use disorder (MOUD) during incarceration may lead to better community re-entry, but evidence on these relationships have been mixed. We aimed to identify community re-entry patterns and examine the association between in-jail MOUD and a pattern of successful reentry defined by rare occurrence of reincarceration and preventable healthcare utilization. METHODS:Data came from a retrospective, observational cohort study of 6066 adults with opioid use disorder who were incarcerated in New York City jails and released to the community during 2011-14. An outcome was community re-entry patterns identified by sequence analysis of 3-year post-release reincarceration, emergency department visits, and hospitalizations. An exposure was receipt of in-jail MOUD versus out-of-treatment (42 % vs. 58 %) for the last 3 days before discharge. The study accounted for differences in baseline demographic, clinical, behavioral, housing, and criminal legal characteristics between in-jail MOUD and out-of-treatment groups via propensity score matching. RESULTS:This study identified five re-entry patterns: stability (64 %), hospitalization (23 %), delayed reincarceration (7 %), immediate reincarceration (4 %), and continuous incarceration (2 %). After addressing confounding, 64 % and 57 % followed the stability pattern among MOUD and out-of-treatment groups who were released from jail in 2011, respectively. In 2012-14, the prevalence of following the stability pattern increased year-by-year while a consistently higher prevalence was observed among those with in-jail MOUD. CONCLUSIONS:Sequence analysis helped define post-release stability based on health and criminal legal system involvement. Receipt of in-jail MOUD was associated with a marker of successful community re-entry.

Following the publication of the original article [1] the authors requested to update the "Competing interests" section as follows: "The authors declare that Anne Sales is co-Editor-in-Chief of the journal".

PURPOSE/OBJECTIVE:Clinic-based or community-based interventions can improve adherence to guideline-directed medication therapies (GDMTs) among patients with heart failure (HF). However, opportunities for such interventions are frequently missed, as providers may be unable to recognise risk patterns for medication non-adherence. Machine learning algorithms can help in identifying patients with high likelihood of non-adherence. While a number of multilevel factors influence adherence, prior models predicting non-adherence have been limited by data availability. We have established an electronic health record (EHR)-based cohort with comprehensive data elements from multiple sources to improve on existing models. We linked EHR data with pharmacy refill data for real-time incorporation of prescription fills and with social determinants data to incorporate neighbourhood factors. PARTICIPANTS/METHODS:Patients seen at a large health system in New York City (NYC), who were >18 years old with diagnosis of HF or reduced ejection fraction (<40%) since 2017, had at least one clinical encounter between 1 April 2021 and 31 October 2022 and active prescriptions for any of the four GDMTs (beta-blocker, ACEi/angiotensin receptor blocker (ARB)/angiotensin receptor neprilysin inhibitor (ARNI), mineralocorticoid receptor antagonist (MRA) and sodium-glucose cotransporter 2 inhibitor (SGLT2i)) during the study period. Patients with non-geocodable address or outside the continental USA were excluded. FINDINGS TO DATE/RESULTS:Among 39 963 patients in the cohort, the average age was 73±14 years old, 44% were female and 48% were current/former smokers. The common comorbid conditions were hypertension (77%), cardiac arrhythmias (56%), obesity (33%) and valvular disease (33%). During the study period, 33 606 (84%) patients had an active prescription of beta blocker, 32 626 (82%) had ACEi/ARB/ARNI, 11 611 (29%) MRA and 7472 (19%) SGLT2i. Ninety-nine per cent were from urban metropolitan areas. FUTURE PLANS/UNASSIGNED:We will use the established cohort to develop a machine learning model to predict medication adherence, and to support ancillary studies assessing associates of adherence. For external validation, we will include data from an additional hospital system in NYC.

IMPORTANCE/UNASSIGNED:Medication nonadherence is common among patients with heart failure with reduced ejection fraction (HFrEF) and can lead to increased hospitalization and mortality. Patients living in socioeconomically disadvantaged areas may be at greater risk for medication nonadherence due to barriers such as lower access to transportation or pharmacies. OBJECTIVE/UNASSIGNED:To examine the association between neighborhood-level socioeconomic status (nSES) and medication nonadherence among patients with HFrEF and to assess the mediating roles of access to transportation, walkability, and pharmacy density. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:This retrospective cohort study was conducted between June 30, 2020, and December 31, 2021, at a large health system based primarily in New York City and surrounding areas. Adult patients with a diagnosis of HF, reduced EF on echocardiogram, and a prescription of at least 1 guideline-directed medical therapy (GDMT) for HFrEF were included. EXPOSURE/UNASSIGNED:Patient addresses were geocoded, and nSES was calculated using the Agency for Healthcare Research and Quality SES index, which combines census-tract level measures of poverty, rent burden, unemployment, crowding, home value, and education, with higher values indicating higher nSES. MAIN OUTCOMES AND MEASURES/UNASSIGNED:Medication nonadherence was obtained through linkage of health record prescription data with pharmacy fill data and was defined as proportion of days covered (PDC) of less than 80% over 6 months, averaged across GDMT medications. RESULTS/UNASSIGNED:Among 6247 patients, the mean (SD) age was 73 (14) years, and majority were male (4340 [69.5%]). There were 1011 (16.2%) Black participants, 735 (11.8%) Hispanic/Latinx participants, and 3929 (62.9%) White participants. Patients in lower nSES areas had higher rates of nonadherence, ranging from 51.7% in the lowest quartile (731 of 1086 participants) to 40.0% in the highest quartile (563 of 1086 participants) (P < .001). In adjusted analysis, patients living in the lower 2 nSES quartiles had significantly higher odds of nonadherence when compared with patients living in the highest nSES quartile (quartile 1: odds ratio [OR], 1.57 [95% CI, 1.35-1.83]; quartile 2: OR, 1.35 [95% CI, 1.16-1.56]). No mediation by access to transportation and pharmacy density was found, but a small amount of mediation by neighborhood walkability was observed. CONCLUSIONS AND RELEVANCE/UNASSIGNED:In this retrospective cohort study of patients with HFrEF, living in a lower nSES area was associated with higher rates of GDMT nonadherence. These findings highlight the importance of considering neighborhood-level disparities when developing approaches to improve medication adherence.

SIGNIFICANCE STATEMENT/CONCLUSIONS:New eGFR equations from Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and European Kidney Function Consortium (EKFC) using creatinine (eGFRcr), cystatin C (eGFRcys), and both (eGFRcr-cys) have sufficient accuracy for use in clinical practice, leading to uncertainty in selecting equations for implementation. The authors evaluated performance of equations in an independent population of 4050 adults and evaluated other considerations important for implementation. They found that CKD-EPI and EKFC equations are approaching convergence, with better performance of eGFRcr-cys equations in the overall group and fewer differences among race, sex, and age subgroups than eGFRcr equations. Larger differences among eGFRcr equations reflect regional population differences in creatinine, forcing a trade-off between accuracy and uniformity in global implementation of eGFRcr equations. More widespread use of cystatin C could avoid this trade-off. BACKGROUND:New CKD-EPI and EKFC eGFR equations using eGFRcr, eGFRcys, and both (eGFRcr-cys) have sufficient accuracy for use in clinical practice. A better understanding of the equations, including their performance in race, sex and age subgroups, is important for selection of eGFR equations for global implementation. METHODS:We evaluated performance (bias and P 30 ) of equations and methods used for equation development in an independent study population comprising 4050 adults pooled from 12 studies. The mean (SD) measured GFR was 76.4 (29.6) ml/min per 1.73 m 2 and age 57.0 (17.4) years, with 1557 (38%) women and 579 (14%) Black participants. RESULTS:Coefficients for creatinine, cystatin C, age, and sex in the CKD-EPI and EKFC equations are similar. Performance of the eGFRcr-cys equations in the overall population (bias <±5 ml/min per 1.73 m 2 and P 30 >90%) was better than the eGFRcr or eGFRcys equations, with fewer differences among race, sex, and age subgroups. Differences in performance across subgroups reflected differences in diversity of source populations and use of variables for race and sex for equation development. Larger differences among eGFRcr equations reflected regional population differences in non-GFR determinants of creatinine. CONCLUSION/CONCLUSIONS:CKD-EPI and EKFC equations are approaching convergence. It is not possible to maximize both accuracy and uniformity in selecting one of the currently available eGFRcr equations for implementation across regions. Decisions should consider methods for equation development in addition to performance. Wider use of cystatin C with creatinine could maximize both accuracy and uniformity of GFR estimation using currently available equations.