Faculty Bibliography

BACKGROUND:The novel coronavirus-associated ARDS (COVID-19 ARDS) often requires invasive mechanical ventilation. A spectrum of atypical ARDS with different phenotypes (high vs low static compliance) has been hypothesized in COVID-19. METHODS:test, chi-square test, ANOVA test, and Pearson correlation was used to identify relationship between subject variables and respiratory mechanics. The primary outcome was duration of mechanical ventilation. Secondary outcomes were correlation between fluid status, C- reactive protein, PEEP, and D-dimer with respiratory and ventilatory parameters. RESULTS:= .02). CONCLUSIONS:In our cohort of mechanically ventilated COVID-19 ARDS subjects, high PEEP and D-dimer were associated with increase in physiologic dead space without significant effect on oxygenation, raising the question of potential microvascular dysfunction.

BACKGROUND:Immune-related adverse events (irAEs) are common, clinically significant autoinflammatory toxicities observed with immune checkpoint inhibitors (ICI). Preexisting immune-mediated inflammatory disease (pre-IMID) is considered a relative contraindication to ICI due to the risk of inciting flares. Improved understanding of the risks and benefits of treating pre-IMID patients with ICI is needed. METHODS:We studied melanoma patients treated with ICI and enrolled in a prospective clinicopathological database. We compiled a list of 23 immune-mediated inflammatory diseases and evaluated their presence prior to ICI. We tested the associations between pre-IMID and progression-free survival (PFS), overall survival (OS), and irAEs. RESULTS:In total, 483 melanoma patients were included in the study; 74 had pre-IMID and 409 did not. In patients receiving ICI as a standard of care (SoC), pre-IMID was significantly associated with irAEs (p = 0.04) as well as improved PFS (p = 0.024) and OS (p = 0.007). There was no significant association between pre-IMID and irAEs (p = 0.54), PFS (p = 0.197), or OS (p = 0.746) in patients treated through a clinical trial. Pre-IMID was significantly associated with improved OS in females (p = 0.012), but not in males (p = 0.35). CONCLUSIONS:The dichotomy of the impact of pre-IMID on survival and irAEs in SoC versus clinical trial patients may reflect the inherit selection bias in patients accrued in clinical trials. Future mechanistic work is required to better understand the differences in outcomes between female and male pre-IMID patients. Our data challenge the notion that clinicians should avoid ICI in pre-IMID patients, although close monitoring and prospective clinical trials evaluating ICI in this population are warranted.

BACKGROUND CONTEXT: The inter-relationship between the hip and spine has been increasingly studied in recent years, particularly as it pertains to the effect of spinal deformity and hip osteoarthritis (OA). Changing from standing (ST) to seated (SE) requires rotation of the femur from an almost vertical plane to the horizontal. OA of the hip significantly limits hip extension, resulting in less ability to recruit pelvic tilt (PT) in ST, and requiring increased PT in SE to compensate for loss of hip flexion. To date, the effect of total hip arthroplasty (THA) in altering spinopelvic SE and ST mechanics has not been reported. PURPOSE: To investigate the change in spinopelvic alignment parameters between seated and standing positions in pre and post THA patients. STUDY DESIGN/SETTING: Retrospective review at a single academic institution. PATIENT SAMPLE: Adult patients undergoing THA with full body sitting and standing radiographs pre- and post-THA. OUTCOME MEASURES: Spinopelvic alignment measures including pelvic incidence (PI), pelvic tilt (PT), T1 pelvic angle (TPA), sacral slope (SS), sagittal vertical axis (SVA), pelvic incidence and lumbar lordosis mismatch (PI-LL), and lumbar lordosis (LL).
METHOD(S): Patients >=18yo undergoing THA for hip OA with full spine SE and ST radiographs pre and post THA were included. Spinopelvic alignment was analyzed pre-THA and post-THA in both ST and SE positions in a relaxed posture with the fingers on the clavicles. Paired t-test analysis was performed to compare Pre-and Post-THA groups. The effect of TL deformity (SVA>50, TPA>20, PI-LL>10) on these changes was also analyzed. Statistical significance set at p<0.05.
RESULT(S): There were 192 patients assessed. 179 patients had thoracolumbar (TL) deformity; TPA>20 (N=46), PI-LL>10 (N=55), and SVA>50 (N=78). In standing position, patients have a significant reduction in SVA post THA vs pre THA (34.09+/-42.69 vs 45.03+/-46.87, p=0.001) as a result of an increase in PT (15.7+/-9.74 o vs 14.6+/-9.88o,p=0.028), without significant changes in spinal alignment parameters including lumbar lordosis (-51.26+/-14.59 vs -50.26+/-14.87, p=0.092), thoracic kyphosis (35.98+/-12.72 vs 35.40+/-13.16, p=0.180), sacral slope (38.15+/-10.77 vs 38.83+/-11.31, p=0.205), T1 pelvic angle (14.22+/-9.94 vs 14.51+/-10.13, p=0.053) and PI-LL mismatch (2.59+/-14.61 vs 3.35+/-14.92, p=0.183). This change in ST_SVA was larger in patients with TL deformity, specifically in those with SVA>50 (61.29+/-45.69 vs 89.48+/-35.91, p=0.001), in PI-LL > 10 (59.08+/-45.49 vs 73.36+/-48.50, p=0.001) and in TPA>20 subsets (62.14+/-49.94 vs 82.28+/-49.55, p=0.001). When moving from ST to SE, the DELTAPT was reduced post THA (16.70+/-15.27o vs 20.85+/-17.27o, p=0.001) in addition to a smaller SE_PT vs pre-THA (32.41+/-14.47 vs 35.46+/-14.20, p=0.006).
CONCLUSION(S): Post Total Hip Arthroplasty (THA), patients demonstrated an increased recruitment of pelvic retroversion to achieve a better global balance by reduction in standing SVA. This compensation was achieved solely by greater mobility of their hip and pelvis, and without a significant change in spinal alignment. ST_SVA reduction was more pronounced in patients with thoracolumbar (TL) spinal deformity (SVA>50, TPA>20, PI-LL>10). On the converse, PT was reduced in sitting (SE) post-THA compared to pre-THA, and the compensatory change in PT was also reduced between ST and SE as a result of restoration of hip flexion. FDA DEVICE/DRUG STATUS: This abstract does not discuss or include any applicable devices or drugs.
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BACKGROUND:Early reports on cancer patients with coronavirus disease 2019 (COVID-19) corroborated speculation that cancer patients are at increased risk for becoming infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and developing severe COVID-19. However, cancer patients are a heterogeneous population and their corresponding risk may be different. AIM/OBJECTIVE:To compare COVID-19 presentation in patients with active malignancy to those with a history of cancer to determine the impact of cancer status on COVID-19 outcomes in the two groups. METHODS AND RESULTS/RESULTS:Of the 6724 patients who were hospitalized at NYU Langone Health (3/16/20-7/31/20) and tested positive for SARS-CoV-2, 580 had either active cancer (n = 221) or a history of cancer (n = 359). We compared the baseline clinicodemographic characteristics and hospital courses of the two groups. We studied the relationship between cancer status and the rate of admission to the intensive care unit (ICU), use of invasive mechanical ventilation (IMV), and all-cause mortality. The two groups had similar laboratory results associated with COVID-19 infection, incidence of venous thromboembolism, and incidence of severe COVID-19. Active cancer status was not associated with the rate of ICU admission (p = .307) or use of IMV (p = .236), but was significantly associated with worse all-cause mortality in both univariate and multivariate analysis with odds ratios of 1.48 (95% confidence interval [CI]: 1.04-2.09; p = .028) and 1.71 (95% CI: 1.12-2.63; p = .014), respectively. CONCLUSION/CONCLUSIONS:Active cancer patients had worse survival outcomes compared to patients with a history of cancer despite similar COVID-19 disease characteristics in the two groups. Our data suggest that cancer care should continue with minimal interruptions during the pandemic to bring about response and remission as soon as possible.

The widespread availability of high-dimensional electronic healthcare record (EHR) datasets has led to significant interest in using such data to derive clinical insights and make risk predictions. More specifically, techniques from machine learning are being increasingly applied to the problem of dynamic survival analysis, where updated time-to-event risk predictions are learned as a function of the full covariate trajectory from EHR datasets. EHR data presents unique challenges in the context of dynamic survival analysis, involving a variety of decisions about data representation, modeling, interpretability, and clinically meaningful evaluation. In this paper we propose a new approach to dynamic survival analysis which addresses some of these challenges. Our modeling approach is based on learning a global parametric distribution to represent population characteristics and then dynamically locating individuals on the time-axis of this distribution conditioned on their histories. For evaluation we also propose a new version of the dynamic C-Index for clinically meaningful evaluation of dynamic survival models. To validate our approach we conduct dynamic risk prediction on three real-world datasets, involving COVID-19 severe outcomes, cardiovascular disease (CVD) onset, and primary biliary cirrhosis (PBC) time-to-transplant. We find that our proposed modeling approach is competitive with other well-known statistical and machine learning approaches for dynamic risk prediction, while offering potential advantages in terms of interepretability of predictions at the individual level.

BACKGROUND:Although most patients with cutaneous melanoma are non-Hispanic whites (NHWs), minorities consistently suffer worse melanoma-specific survival (MSS). Much of the literature comes from analyses of registries from the 1990s and 2000s. OBJECTIVE:We sought to evaluate whether and to what degree racial disparity in MSS persists since 2010. METHODS:We analyzed 381,035 patients from the Surveillance, Epidemiology, and End Results registry. Race categories included Hispanic, NHW, non-Hispanic black (NHB), non-Hispanic Asian or Pacific Islander (NHAPI), and non-Hispanic American Indian/Alaska Native (NHAIAN). We evaluated the association between MSS and race in 3 time periods: before the year 2000, 2000 to 2009, and 2010 or later. NHW was the reference group for all analyses. RESULTS:Racial disparity worsened from before the year 2000 to 2010 or later for Hispanic (P < .001), NHB (P = .024), and NHAPI (P < .001) patients. Across all minority groups, patients with localized disease suffered increasing disparity (P = .010 for Hispanic, P < .001 for NHB, P = .023 for NHAPI, and P = .042 for NHAIAN patients). Among those with regional and distant disease, Hispanic patients were the only minority to experience worsening disparity (P = .001 and P = .019, respectively). LIMITATIONS/CONCLUSIONS:Lack of immunotherapy and targeted treatment information. CONCLUSIONS:Racial disparity in MSS is worsening. Improving postdiagnosis management for minorities with localized disease is imperative to mitigate disparity and improve survival.

Background: While ~50% of patients (pts) with AML aged >60 years attain complete remission (CR) with intensive chemotherapy (IC), up to 90% who do will eventually relapse. In the continuum of AML care, the highest costs are related to relapsed/refractory disease, and hospitalization is the largest component (~70%) of direct healthcare costs. In the randomized, phase 3 QUAZAR AML-001 trial, maintenance treatment (Tx) with Oral-AZA significantly prolonged overall and relapse-free survival vs. PBO for pts with AML in first remission after IC.
Aim(s): Determine rates of hospitalization and days (d) in hospital with Oral-AZA and PBO for all pts in QUAZAR AML-001, and estimate associated hospitalization costs in Spain from the Spanish National Health System (NHS) perspective, and in the UK from the UK NHS perspective.
Method(s): Eligible pts were age >=55 yrs, had intermediate- or poor-risk cytogenetics and ECOG PS <=3, and were not candidates for transplant. Within 4 months (mo) of achieving CR or CR with incomplete blood count recovery (CRi) after induction +/- consolidation, pts were randomized 1:1 to Oral-AZA 300-mg or PBO QD for 14d/28d cycle. Pts who received >=1 study drug dose were followed for hospitalization from informed consent through 28d after last dose. The mean number of hospital days/mo (30d) was the total number of days in hospital divided by the number of ongoing pts each mo. Hospitalization rates and durations were adjusted for total drug exposure. Confidence intervals (CI) for relative risk (RR) estimates and related P values are based on asymptotic methods. Unit cost of hospitalization in Spain was derived from literature (Arenaza et al. Clinicoecon Outcomes Res, 2019), and in the UK from NHS reference costs (https://urldefense.com/v3/__https://improvement.nhs.uk/resources/reference-__;!!MXfaZl3l!OpCoLHQ2rqK1VsMStsOKp86IRR8bqfjG0A-Ot_EG-SQDYIPd2IxVXtpVGoEKdoxE$ costs/#rc1718), as the average total AML-related hospitalization costs per day, adjusted for inflation to 2019 prices, using the medical component of the consumer price index for each country.
Result(s): 469 pts received Oral-AZA (n=236) or PBO (n=233); median time on Tx was 11.6 vs 5.7 mo, respectively, and total exposures were 363.8 pt-years (PY) and 234.9 PY. Similar proportions of patients were hospitalized during the study: Oral-AZA 46% (n=108), PBO 51% (n=118). Total number of hospitalization events was numerically higher in the Oral-AZA arm (173 vs 151 in the PBO arm), but the exposure-adjusted hospitalization rate was significantly lower with Oral-AZA: 0.48/ PY vs. 0.64/PY (RR 0.740 [95%CI 0.595, 0.920]; P=0.0068). Total days hospitalized were 2,872 in the Oral-AZA arm and 3,139 in the PBO arm; the exposure-adjusted rate was also significantly lower with Oral-AZA (7.89 vs. 13.36 d/PY, respectively; RR 0.591 [95%CI 0.562, 0.621]; P<0.0001). Mean hospitalization cost in Spain was 1,398/d. Using exposure-adjusted days-in-hospital, estimated mean costs of hospitalization in Spain were 11,030/PY with Oral-AZA and 18,676/PY with PBO. Cumulative cost savings with Oral-AZA vs. PBO ranged from 557 at mo 2 to 8,025 by mo 24 (Figure). In the UK, mean hospitalization cost was ?696/d, resulting in estimated exposure-adjusted mean costs of ?5,490/PY with Oral-AZA and ?9,296/ PY with PBO. Cumulative cost savings with Oral-AZA in the UK ranged from ?277 at mo 2 to ?3,995 by mo 24 (Figure). Summary/Conclusion: Compared with PBO, Oral-AZA was associated with significantly reduced exposure-adjusted rates of hospitalization and days in hospital, and considerable estimated cost savings in Spain and the UK. Delaying relapse with Oral-AZA may lead to substantial economic benefits due to lower hospitalization costs

Tumor-infiltrating lymphocytes (TIL) have potential prognostic value in melanoma and have been considered for inclusion in the American Joint Committee on Cancer (AJCC) staging criteria. However, interobserver discordance continues to prevent the adoption of TIL into clinical practice. Computational image analysis offers a solution to this obstacle, representing a methodological approach for reproducibly counting TIL. We sought to evaluate the ability of a TIL-quantifying machine learning algorithm to predict survival in primary melanoma. Digitized hematoxylin and eosin (H&E) slides from prospectively enrolled patients in the NYU melanoma database were scored for % TIL using machine learning and manually graded by pathologists using Clark's model. We evaluated the association of % TIL with recurrence-free survival (RFS) and overall survival (OS) using Cox proportional hazards modeling and concordance indices. Discordance between algorithmic and manual TIL quantification was assessed with McNemar's test and visually by an attending dermatopathologist. In total, 453 primary melanoma patients were scored using machine learning. Automated % TIL scoring significantly differentiated survival using an estimated cutoff of 16.6% TIL (log-rank P < 0.001 for RFS; P = 0.002 for OS). % TIL was associated with significantly longer RFS (adjusted HR = 0.92 [0.84-1.00] per 10% increase in % TIL) and OS (adjusted HR = 0.90 [0.83-0.99] per 10% increase in % TIL). In comparison, a subset of the cohort (n = 240) was graded for TIL by melanoma pathologists. However, TIL did not associate with RFS between groups (P > 0.05) when categorized as brisk, nonbrisk, or absent. A standardized and automated % TIL scoring algorithm can improve the prognostic impact of TIL. Incorporation of quantitative TIL scoring into the AJCC staging criteria should be considered.

BACKGROUND:Comorbid chronic conditions are common among people with type 2 diabetes. We developed an artificial intelligence algorithm, based on reinforcement learning (RL), for personalized diabetes and multimorbidity management, with strong potential to improve health outcomes relative to current clinical practice. METHODS:We modeled glycemia, blood pressure, and cardiovascular disease (CVD) risk as health outcomes, using a retrospective cohort of 16,665 patients with type 2 diabetes from New York University Langone Health ambulatory care electronic health records in 2009-2017. We trained an RL prescription algorithm that recommends a treatment regimen optimizing patients' cumulative health outcomes using their individual characteristics and medical history at each encounter. The RL recommendations were evaluated on an independent subset of patients. RESULTS:The single-outcome optimization RL algorithms, RL-glycemia, RL-blood pressure, and RL-CVD, recommended consistent prescriptions as that observed by clinicians in 86.1%, 82.9%, and 98.4% of the encounters, respectively. For patient encounters in which the RL recommendations differed from the clinician prescriptions, significantly fewer encounters showed uncontrolled glycemia (A1c > 8% in 35% of encounters), uncontrolled hypertension (blood pressure > 140 mmHg in 16% of encounters), and high CVD risk (risk > 20% in 25% of encounters) under RL algorithms compared with those observed under clinicians (43%, 27%, and 31% of encounters, respectively; all p < 0.001). CONCLUSIONS:A personalized RL prescriptive framework for type 2 diabetes yielded high concordance with clinicians' prescriptions, and substantial improvements in glycemia, blood pressure, and CVD risk outcomes.