Novel MAGIC composite scores using both clinical symptoms and biomarkers best predict treatment outcomes of acute GVHD.

Acute graft-vs-host disease (GVHD) grading systems that use only clinical symptoms at treatment initiation such as Minnesota risk identify standard and high risk categories but lack a low risk category suitable to minimize immunosuppressive strategies. We developed a new grading system that includes a low risk stratum based on clinical symptoms alone and determined whether the incorporation of biomarkers would improve the model's prognostic accuracy. We randomly divided 1863 patients in the Mount Sinai Acute GVHD International Consortium (MAGIC) who were treated for GVHD into training and validation cohorts. Patients in the training cohort were divided into 14 groups based on similarity of clinical symptoms and similar NRM; we used a classification and regression tree (CART) algorithm to create three Manhattan risk groups that produced a significantly higher area under the receiver operating characteristic curve (AUC) for 6-month NRM than the Minnesota risk classification (0.69 vs. 0.64, P=0.009) in the validation cohort. We integrated serum GVHD biomarker scores with Manhattan risk using patients with available serum samples and again used a CART algorithm to establish three MAGIC composite scores that significantly improved prediction of NRM compared to Manhattan risk (AUC, 0.76 vs. 0.70, P=0.010). Each increase in MAGIC composite score also corresponded to a significant decrease in day 28 treatment response (80% vs. 63% vs. 30%, P<0.001). We conclude that the MAGIC composite score more accurately predicts response to therapy and long term outcomes than systems based on clinical symptoms alone and may help guide clinical decisions and trial design.

Effective treatment of low-risk acute GVHD with itacitinib monotherapy.

The standard primary treatment for acute graft-versus-host disease (GVHD) requires prolonged, high-dose systemic corticosteroids (SCSs) that delay reconstitution of the immune system. We used validated clinical and biomarker staging criteria to identify a group of patients with low-risk (LR) GVHD that is very likely to respond to SCS. We hypothesized that itacitinib, a selective JAK1 inhibitor, would effectively treat LR GVHD without SCS. We treated 70 patients with LR GVHD in a multicenter, phase 2 trial (NCT03846479) with 28 days of itacitinib 200 mg/d (responders could receive a second 28-day cycle), and we compared their outcomes to those of 140 contemporaneous, matched control patients treated with SCSs. More patients responded to itacitinib within 7 days (81% vs 66%, P = .02), and response rates at day 28 were very high for both groups (89% vs 86%, P = .67), with few symptomatic flares (11% vs 12%, P = .88). Fewer itacitinib-treated patients developed a serious infection within 90 days (27% vs 42%, P = .04) due to fewer viral and fungal infections. Grade ≥3 cytopenias were similar between groups except for less severe leukopenia with itacitinib (16% vs 31%, P = .02). No other grade ≥3 adverse events occurred in >10% of itacitinib-treated patients. There were no significant differences between groups at 1 year for nonrelapse mortality (4% vs 11%, P = .21), relapse (18% vs 21%, P = .64), chronic GVHD (28% vs 33%, P = .33), or survival (88% vs 80%, P = .11). Itacitinib monotherapy seems to be a safe and effective alternative to SCS treatment for LR GVHD and deserves further investigation.

Lung Injury Prediction Model in Bone Marrow Transplantation: A Multicenter Cohort Study.

Rationale: Pulmonary complications contribute significantly to nonrelapse mortality following hematopoietic stem cell transplantation (HCT). Identifying patients at high risk can help enroll such patients into clinical studies to better understand, prevent, and treat posttransplantation respiratory failure syndromes. Objectives: To develop and validate a prediction model to identify those at increased risk of acute respiratory failure after HCT. Methods: Patients underwent HCT between January 1, 2019, and December 31, 2021, at one of three institutions. Those treated in Rochester, MN, formed the derivation cohort, and those treated in Scottsdale, AZ, or Jacksonville, FL, formed the validation cohort. The primary outcome was the development of acute respiratory distress syndrome (ARDS), with secondary outcomes including the need for invasive mechanical ventilation (IMV) and/or noninvasive ventilation (NIV). Predictors were based on prior case-control studies. Measurements and Main Results: Of 2,450 patients undergoing stem cell transplantation, there were 1,718 hospitalizations (888 patients) in the training cohort and 1,005 hospitalizations (470 patients) in the test cohort. A 22-point model was developed, with 11 points from prehospital predictors and 11 points from posttransplantation or early (<24-h) in-hospital predictors. The model performed well in predicting ARDS (C-statistic, 0.905; 95% confidence interval [CI], 0.870-0.941) and the need for IMV and/or NIV (C-statistic, 0.863; 95% CI, 0.828-0.898). The test cohort differed markedly in demographic, medical, and hematologic characteristics. The model also performed well in this setting in predicting ARDS (C-statistic, 0.841; 95% CI, 0.782-0.900) and the need for IMV and/or NIV (C-statistic, 0.872; 95% CI, 0.831-0.914). Conclusions: A novel prediction model incorporating data elements from the pretransplantation, posttransplantation, and early in-hospital domains can reliably predict the development of post-HCT acute respiratory failure.

Venetoclax plus hypomethylating agents in DDX41-mutated acute myeloid leukaemia and myelodysplastic syndrome: Mayo Clinic series on 12 patients.

Venetoclax (VEN) is an FDA-approved selective inhibitor of B-cell leukaemia/lymphoma-2 (BCL-2), used for treating elderly or unfit acute myeloid leukaemia (AML) patients unable to undergo intensive chemotherapy. Combining VEN with hypomethylating agents (HMAs) has shown impressive response rates in high-risk myelodysplastic syndromes (MDS) and relapsed/refractory AML. However, the efficacy of VEN and HMAs in treating DDX41-mutated (mDDX41) MDS/AML patients remains uncertain. Despite the favourable prognostic nature of mDDX41 MDS/AML patients, there is a lack of clinical experience regarding their response to different treatment regimens, leading to an unknown optimal therapeutic approach.

Cardiac events in newly diagnosed acute myeloid leukaemia during treatment with venetoclax + hypomethylating agents.

Among 301 newly diagnosed patients with acute myeloid leukaemia receiving venetoclax and a hypomethylating agent, 23 (7.6%) experienced major cardiac complications: 15 cardiomyopathy, 5 non-ST elevation myocardial infarction and/or 7 pericarditis/effusions. Four patients had more than one cardiac complication. Baseline characteristics included median age ± interquartile range; 73 ± 5 years; 87% males; 96% with cardiovascular risk factors; and 90% with preserved baseline ejection fraction. In multivariate analysis, males were more likely (p = 0.02) and DNMT3A-mutated cases less likely (p < 0.01) to be affected. Treatment-emergent cardiac events were associated with a trend towards lower composite remission rates (43% vs. 62%; p = 0.09) and shorter survival (median 7.7 vs. 13.2 months; p < 0.01). These observations were retrospectively retrieved and warrant further prospective examination.

Genetic landscape and clinical outcomes of patients with BCOR mutated myeloid neoplasms.

The BCL6-corepressor (BCOR) is a tumor-suppressor gene located on the short arm of chromosome X. Data are limited regarding factors predicting survival in BCOR-mutated (mBCOR) acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). We evaluated 138 patients with mBCOR myeloid disorders, of which 36 (26.1%) had AML and 63 (45.6%) had MDS. Sixty-six (47.8%) patients had a normal karyotype while 18 (13%) patients had complex karyotype. BCOR-mutated MDS/AML were highly associated with RUNX1 and U2AF1 co-mutations. In contrast, TP53 mutation was infrequently seen with mBCOR MDS. Patients with an isolated BCOR mutation had similar survival compared to those with high-risk co-mutations by European LeukemiaNet (ELN) 2022 criteria (median OS 1.16 vs. 1.27 years, P=0.46). Complex karyotype adversely impacted survival among mBCOR AML/MDS (HR 4.12, P<0.001), while allogeneic stem cell transplant (alloSCT) improved survival (HR 0.38, P=0.04). However, RUNX1 co-mutation was associated with an increased risk of post-alloSCT relapse (HR 88.0, P=0.02), whereas melphalan-based conditioning was associated with a decreased relapse risk (HR 0.02, P=0.01). We conclude that mBCOR is a high-risk feature across MDS/AML, and that alloSCT improves survival in this population.

FLT3 inhibitors potentially improve response rates in acute myeloid leukemia harboring t(6;9)(DEK::NUP214): The Mayo Clinic experience.

Not available.

Cladribine plus cytarabine plus venetoclax in acute myeloid leukemia relapsed or refractory to venetoclax plus hypomethylating agent.

Not available.

Prognostic impact of SF3B1 mutation and multilineage dysplasia in myelodysplastic syndromes with ring sideroblasts: a Mayo Clinic study of 170 informative cases.

The revised 4th edition of the World Health Organization (WHO4R) classification lists myelodysplastic syndromes with ring sideroblasts (MDS-RS) as a separate entity with single lineage (MDS-RS-SLD) or multilineage (MDS-RS-MLD) dysplasia. The more recent International Consensus Classification (ICC) distinguishes between MDS with SF3B1 mutation (MDS-SF3B1) and MDS-RS without SF3B1 mutation; the latter is instead included under the category of MDS not otherwise specified. The current study includes 170 Mayo Clinic patients with WHO4R-defined MDS-RS, including MDS-RS-SLD (N=83) and MDS-RS-MLD (N=87); a subset of 145 patients were also evaluable for the presence of SF3B1 and other mutations, including 126 with (87%) and 19 (13%) without SF3B1 mutation. Median overall survival for all 170 patients was 6.6 years with 5- and 10-year survival rates of 59% and 25%, respectively. A significant difference in overall survival was apparent between MDS-RS-MLD and MDS-RS-SLD (p<0.01) but not between MDS-RS with and without SF3B1 mutation (p=0.36). Multivariable analysis confirmed the independent prognostic contribution of MLD (HR 1.8, 95% CI 1.1-2.8; p=0.01) and also identified age (p<0.01), transfusion need at diagnosis (p<0.01), and abnormal karyotype (p<0.01), as additional risk factors; the impact from SF3B1 or other mutations was not significant. Leukemia-free survival was independently affected by abnormal karyotype (p<0.01), RUNX1 (0.02) and IDH1 (p=0.01) mutations, but not by MLD or SF3B1 mutation. Exclusion of patients not meeting ICC-criteria for MDSSF3B1 did not change the observations on overall survival. MLD-based, as opposed to SF3B1 mutationbased, disease classification for MDS-RS might be prognostically more relevant.

Temporal trends in critical care utilization and outcomes in allogeneic hematopoietic stem cell transplant recipients.

Historically, the prognosis of allogeneic hematopoietic stem cell transplant (allo-HCT) recipients who require intensive care unit (ICU) admission has been poor. We aimed to describe the epidemiological trends of ICU utilization and outcomes in allo-HCT patients. We conducted a retrospective cohort study including adults (≥ 18) undergoing allo-HCT between 01/01/2005 and 31/12/2020 at Mayo Clinic, Rochester. Temporal trends in outcomes were assessed by robust linear regression modelling. Risk factors for hospital mortality were chosen a priori and assessed with multivariable logistic regression modelling. Of 1,249 subjects, there were 486 ICU admissions among 287 individuals. Although older patients underwent allo-HCT (1.64 [95% CI: 1.11 to 2.45] years per year; P = 0.025), there was no change in ICU utilization over time (P = 0.91). The ICU and hospital mortality rates were 19.2% (55/287) and 28.2% (81/287), respectively. There was a decline in ICU mortality (-0.38% [95% CI: -0.70 to -0.06%] per year; P = 0.035). The 1-year post-HCT mortality for those requiring ICU admission was 56.1% (161/287), with no significant difference over time, versus 15.8% (141/891, 71 missing) among those who did not. The frequency and duration of invasive mechanical ventilation (IMV) declined. In multivariable analyses, higher serum lactate, higher sequential organ failure assessment (SOFA) scores, acute respiratory distress (ARDS), and need for IMV were associated with greater odds of hospital mortality. Over time, rates of ICU utilization have remained stable, despite increasing patient age. Several trends suggest improvement in outcomes, notably lower ICU mortality and frequency of IMV. However, long-term survival remains unchanged. Further work is needed to improve long-term outcomes in this population.

Granularity in disease classification impacts survival prediction in advanced systemic mastocytosis: A single institution study of 329 informative cases.

The World Health Organization (WHO) classification system categorizes advanced systemic mastocytosis (SM-Adv) into aggressive SM (ASM), mast cell leukemia (MCL), and SM with associated hematological neoplasm (SM-AHN). By contrast, the International Consensus Classification (ICC) requires "immature" MC cytomorphology for the diagnosis of MCL and limits SM-AHN to myeloid neoplasms (SM-AMN). The current study includes 329 patients with SM-Adv (median age 65 years, range 18-88; males 58%): WHO subcategories SM-AHN (N = 212; 64%), ASM (N = 99; 30%), and MCL (N = 18; 6%); ICC subcategories SM-AMN (N = 190; 64%), ASM (N = 99; 33%), and MCL (N = 9; 3%); WHO-defined MCL with "mature" MC cytomorphology and SM-AHN associated with lymphoid neoplasms were operationally labeled as "MCL-mature" (N = 9) and SM-ALN (N = 22), respectively, and distinguished from ICC-defined MCL and SM-AMN. Multivariable analysis that included the Mayo alliance risk factors for survival in SM (age >60 years, anemia, thrombocytopenia, increased alkaline phosphatase) revealed more accurate survival prediction with the ICC versus WHO classification order: (i) survival was significantly worse with MCL-immature versus MCL-mature (hazard ratio [HR] 15; p < .01), (ii) prognostic distinction between MCL and SM-AHN/AMN was confirmed in the context of ICC (HR 9.3; p < .01) but not WHO classification order (p = .99), (iii) survival was similar between MCL-mature and SM-AMN (p = .18), and (iv) SM-AMN (HR 1.7; p < .01) but not SM-ALN (p = .37) was prognostically distinct from ASM. The current study provides evidence for the independent prognostic contribution of both the ICC system for SM-Adv and the Mayo alliance risk factors for survival in SM.

Reappraisal of mast cell leukemia based on a single institution review of 16 cases: Mast cell morphology determines clinical outcome.

Cytologic abnormalities of atypical mast cells in mastocytosis. The mature mast cells have oval-shaped nuclei, cytoplasmic hypogranulation and spindle-shaped cytology. or well-differentiated displaying a round nucleus with condensed chromatin, and abundant dense cytoplasmic granulations. Immature mast cells include promastocytes and metachromatic blast-like forms.

Venetoclax and hypomethylating agent combination therapy in newly diagnosed acute myeloid leukemia: Genotype signatures for response and survival among 301 consecutive patients.

Venetoclax + hypomethylating agent (Ven-HMA) is currently the standard frontline therapy for older/unfit patients with newly diagnosed acute myeloid leukemia (ND-AML). Our objective in the current retrospective study of 301 adult patients (median age 73 years; 62% de novo) with ND-AML was to identify molecular predictors of treatment response to Ven-HMA and survival; European LeukemiaNet (ELN) genetic risk assignment was favorable 15%, intermediate 16%, and adverse 69%. Complete remission, with (CR) or without (CRi), count recovery, was documented in 182 (60%) patients. In multivariable analysis, inclusive of mutations only, "favorable" predictors of CR/CRi were NPM1 (86% vs. 56%), IDH2 (80% vs. 58%), and DDX41 (100% vs. 58%) and "unfavorable" TP53 (40% vs. 67%), FLT3-ITD (36% vs. 63%), and RUNX1 (44% vs. 64%) mutations; significance was sustained for each mutation after adjustment for age, karyotype, and therapy-related qualification. CR/CRi rates ranged from 36%, in the presence of unfavorable and absence of favorable mutation, to 91%, in the presence of favorable and absence of unfavorable mutation. At median follow-up of 8.5 months, 174 deaths and 41 allogeneic stem cell transplants (ASCT) were recorded. In multivariable analysis, risk factors for inferior survival included failure to achieve CR/CRi (HR 3.4, 95% CI 2.5-4.8), adverse karyotype (1.6, 1.1-2.6), TP53 mutation (1.6, 1.0-2.4), and absence of IDH2 mutation (2.2, 1.0-4.7); these risk factors were subsequently applied to construct an HR-weighted risk model that performed better than the ELN genetic risk model (AIC 1661 vs. 1750): low (n = 130; median survival 28.9 months), intermediate (n = 105; median 9.6 months), and high (n = 66; median 3.1 months; p < .001); survival in each risk category was significantly upgraded by ASCT. The current study identifies genotype signatures for predicting response and proposes a 3-tiered, CR/CRi-based, and genetics-enhanced survival model for AML patients receiving upfront therapy with Ven-HMA.

Venetoclax duration (14 vs. 21 vs. 28 days) in combination with hypomethylating agent in newly diagnosed acute myeloid leukemia: Comparative analysis of response, toxicity, and survival.

Overall survival and response rates of 270 patients with newly diagnosed acute myeloid leukemia receiving venetoclax (Ven) plus hypomethylating agent, stratified by Ven dosing schedule (Cycle 1 Ven 14 vs. 21 vs. 28 days).

Towards Machine-FAIR: Representing software and datasets to facilitate reuse and scientific discovery by machines.

OBJECTIVE: To use software, datasets, and data formats in the domain of Infectious Disease Epidemiology as a test collection to evaluate a novel M1 use case, which we introduce in this paper. M1 is a machine that upon receipt of a new digital object of research exhaustively finds all valid compositions of it with existing objects. METHOD: We implemented a data-format-matching-only M1 using exhaustive search, which we refer to as M1DFM. We then ran M1DFM on the test collection and used error analysis to identify needed semantic constraints. RESULTS: Precision of M1DFM search was 61.7%. Error analysis identified needed semantic constraints and needed changes in handling of data services. Most semantic constraints were simple, but one data format was sufficiently complex to be practically impossible to represent semantic constraints over, from which we conclude limitatively that software developers will have to meet the machines halfway by engineering software whose inputs are sufficiently simple that their semantic constraints can be represented, akin to the simple APIs of services. We summarize these insights as M1-FAIR guiding principles for composability and suggest a roadmap for progressively capable devices in the service of reuse and accelerated scientific discovery. CONCLUSION: Algorithmic search of digital repositories for valid workflow compositions has potential to accelerate scientific discovery but requires a scalable solution to the problem of knowledge acquisition about semantic constraints on software inputs. Additionally, practical limitations on the logical complexity of semantic constraints must be respected, which has implications for the design of software.

Identifying social determinants of health from clinical narratives: A study of performance, documentation ratio, and potential bias.

OBJECTIVE: To develop a natural language processing (NLP) package to extract social determinants of health (SDoH) from clinical narratives, examine the bias among race and gender groups, test the generalizability of extracting SDoH for different disease groups, and examine population-level extraction ratio. METHODS: We developed SDoH corpora using clinical notes identified at the University of Florida (UF) Health. We systematically compared 7 transformer-based large language models (LLMs) and developed an open-source package - SODA (i.e., SOcial DeterminAnts) to facilitate SDoH extraction from clinical narratives. We examined the performance and potential bias of SODA for different race and gender groups, tested the generalizability of SODA using two disease domains including cancer and opioid use, and explored strategies for improvement. We applied SODA to extract 19 categories of SDoH from the breast (n = 7,971), lung (n = 11,804), and colorectal cancer (n = 6,240) cohorts to assess patient-level extraction ratio and examine the differences among race and gender groups. RESULTS: We developed an SDoH corpus using 629 clinical notes of cancer patients with annotations of 13,193 SDoH concepts/attributes from 19 categories of SDoH, and another cross-disease validation corpus using 200 notes from opioid use patients with 4,342 SDoH concepts/attributes. We compared 7 transformer models and the GatorTron model achieved the best mean average strict/lenient F1 scores of 0.9122 and 0.9367 for SDoH concept extraction and 0.9584 and 0.9593 for linking attributes to SDoH concepts. There is a small performance gap (∼4%) between Males and Females, but a large performance gap (>16 %) among race groups. The performance dropped when we applied the cancer SDoH model to the opioid cohort; fine-tuning using a smaller opioid SDoH corpus improved the performance. The extraction ratio varied in the three cancer cohorts, in which 10 SDoH could be extracted from over 70 % of cancer patients, but 9 SDoH could be extracted from less than 70 % of cancer patients. Individuals from the White and Black groups have a higher extraction ratio than other minority race groups. CONCLUSIONS: Our SODA package achieved good performance in extracting 19 categories of SDoH from clinical narratives. The SODA package with pre-trained transformer models is available at https://github.com/uf-hobi-informatics-lab/SODA_Docker.

Phase 1/1b study of azacitidine and hedgehog pathway inhibitor sonidegib in patients with myeloid neoplasms.

BACKGROUND: Myeloid neoplasms (myelodysplastic syndrome [MDS], myelofibrosis, and chronic myelomonocytic [CMML]) are aggressive hematological malignancies for which, despite recent approvals, novel therapies are needed to improve clinical outcomes. The hedgehog (HH) pathway is one of the main pathways for cancer stem cells survival and several HH inhibitors (HHi) are approved in clinical practice. METHODS: Sonidegib (SON), an oral HHi, was tested in this phase 1/1b trial in combination with azacitidine (AZA, 75 mg/m2 days ×7) in patients with newly diagnosed and relapsed/refractory (r/r) chronic MN or acute myeloid leukemia (AML). RESULTS: Sixty-two patients (28 [45%] newly diagnosed) were treated in this study, including 10 patients in the dose-finding component and 52 patients in phase 1b. SON 200 mg oral daily on days 1-28 each cycle was deemed the recommended dose for phase 1b. Out of 21 rrAML patients, two achieved response (one complete response/one morphologic leukemia-free state) with no responses seen in seven r/r MDS/CMML patients. In newly diagnosed AML/MDS, response was seen in six (three had complete remission, two had morphological leukemia-free status) of 27 patients. Median overall survival was 26.4 and 4.7 months for newly diagnosed MDS and AML, respectively. Safety was satisfactory with common (>20%) side effects including fatigue, constipation, nausea, cough, insomnia, and diarrhea. Only 7% of patients died in the study, and none of the deaths were deemed related to treatment. CONCLUSIONS: Our study shows that AZA + SON are a safe combination in a patient with MN. Similar to other hedgehog inhibitors, this combination yielded limited response rate in patients with myeloid neoplasms.

Postoperative Overtriage to an Intensive Care Unit Is Associated With Low Value of Care.

OBJECTIVE: We test the hypothesis that for low-acuity surgical patients, postoperative intensive care unit (ICU) admission is associated with lower value of care compared with ward admission. BACKGROUND: Overtriaging low-acuity patients to ICU consumes valuable resources and may not confer better patient outcomes. Associations among postoperative overtriage, patient outcomes, costs, and value of care have not been previously reported. METHODS: In this longitudinal cohort study, postoperative ICU admissions were classified as overtriaged or appropriately triaged according to machine learning-based patient acuity assessments and requirements for immediate postoperative mechanical ventilation or vasopressor support. The nearest neighbors algorithm identified risk-matched control ward admissions. The primary outcome was value of care, calculated as inverse observed-to-expected mortality ratios divided by total costs. RESULTS: Acuity assessments had an area under the receiver operating characteristic curve of 0.92 in generating predictions for triage classifications. Of 8592 postoperative ICU admissions, 423 (4.9%) were overtriaged. These were matched with 2155 control ward admissions with similar comorbidities, incidence of emergent surgery, immediate postoperative vital signs, and do not resuscitate order placement and rescindment patterns. Compared with controls, overtraiged admissions did not have a lower incidence of any measured complications. Total costs for admission were $16.4K for overtriage and $15.9K for controls ( P =0.03). Value of care was lower for overtriaged admissions [2.9 (2.0-4.0)] compared with controls [24.2 (14.1-34.5), P <0.001]. CONCLUSIONS: Low-acuity postoperative patients who were overtriaged to ICUs had increased total costs, no improvements in outcomes, and received low-value care.

Avenues for Strengthening PCORnet's Capacity to Advance Patient-Centered Economic Outcomes in Patient-Centered Outcomes Research (PCOR).

PCORnet, the National Patient-Centered Clinical Research Network, provides the ability to conduct prospective and observational pragmatic research by leveraging standardized, curated electronic health records data together with patient and stakeholder engagement. PCORnet is funded by the Patient-Centered Outcomes Research Institute (PCORI) and is composed of 8 Clinical Research Networks that incorporate at total of 79 health system "sites." As the network developed, linkage to commercial health plans, federal insurance claims, disease registries, and other data resources demonstrated the value in extending the networks infrastructure to provide a more complete representation of patient's health and lived experiences. Initially, PCORnet studies avoided direct economic comparative effectiveness as a topic. However, PCORI's authorizing law was amended in 2019 to allow studies to incorporate patient-centered economic outcomes in primary research aims. With PCORI's expanded scope and PCORnet's phase 3 beginning in January 2022, there are opportunities to strengthen the network's ability to support economic patient-centered outcomes research. This commentary will discuss approaches that have been incorporated to date by the network and point to opportunities for the network to incorporate economic variables for analysis, informed by patient and stakeholder perspectives. Topics addressed include: (1) data linkage infrastructure; (2) commercial health plan partnerships; (3) Medicare and Medicaid linkage; (4) health system billing-based benchmarking; (5) area-level measures; (6) individual-level measures; (7) pharmacy benefits and retail pharmacy data; and (8) the importance of transparency and engagement while addressing the biases inherent in linking real-world data sources.

Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software.

BACKGROUND: Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is a popular approach for metabolomics data acquisition and requires many data processing software tools. The FAIR Principles - Findability, Accessibility, Interoperability, and Reusability - were proposed to promote open science and reusable data management, and to maximize the benefit obtained from contemporary and formal scholarly digital publishing. More recently, the FAIR principles were extended to include Research Software (FAIR4RS). AIM OF REVIEW: This study facilitates open science in metabolomics by providing an implementation solution for adopting FAIR4RS in the LC-HRMS metabolomics data processing software. We believe our evaluation guidelines and results can help improve the FAIRness of research software. KEY SCIENTIFIC CONCEPTS OF REVIEW: We evaluated 124 LC-HRMS metabolomics data processing software obtained from a systematic review and selected 61 software for detailed evaluation using FAIR4RS-related criteria, which were extracted from the literature along with internal discussions. We assigned each criterion one or more FAIR4RS categories through discussion. The minimum, median, and maximum percentages of criteria fulfillment of software were 21.6%, 47.7%, and 71.8%. Statistical analysis revealed no significant improvement in FAIRness over time. We identified four criteria covering multiple FAIR4RS categories but had a low %fulfillment: (1) No software had semantic annotation of key information; (2) only 6.3% of evaluated software were registered to Zenodo and received DOIs; (3) only 14.5% of selected software had official software containerization or virtual machine; (4) only 16.7% of evaluated software had a fully documented functions in code. According to the results, we discussed improvement strategies and future directions.