Gene Therapy Versus Common Care for Eligible Individuals With Sickle Cell Disease in the United States : A Cost-Effectiveness Analysis.

BACKGROUND: Sickle cell disease (SCD) and its complications contribute to high rates of morbidity and early mortality and high cost in the United States and African heritage community. OBJECTIVE: To evaluate the cost-effectiveness of gene therapy for SCD and its value-based prices (VBPs). DESIGN: Comparative modeling analysis across 2 independently developed simulation models (University of Washington Model for Economic Analysis of Sickle Cell Cure [UW-MEASURE] and Fred Hutchinson Institute Sickle Cell Disease Outcomes Research and Economics Model [FH-HISCORE]) using the same databases. DATA SOURCES: Centers for Medicare & Medicaid Services claims data, 2008 to 2016; published literature. TARGET POPULATION: Persons eligible for gene therapy. TIME HORIZON: Lifetime. PERSPECTIVE: U.S. health care sector and societal. INTERVENTION: Gene therapy versus common care. OUTCOME MEASURES: Incremental cost-effectiveness ratios (ICERs), equity-informed VBPs, and price acceptability curves. RESULTS OF BASE-CASE ANALYSIS: At an assumed $2 million price for gene therapy, UW-MEASURE and FH-HISCORE estimated ICERs of $193 000 per QALY and $427 000 per QALY, respectively, under the health care sector perspective. Corresponding estimates from the societal perspective were $126 000 per QALY and $281 000 per QALY. The difference in results between models stemmed primarily from considering a slightly different target population and incorporating the quality-of-life (QOL) effects of splenic sequestration, priapism, and acute chest syndrome in the UW model. From a societal perspective, acceptable (>90% confidence) VBPs ranged from $1 million to $2.5 million depending on the use of alternative effective metrics or equity-informed threshold values. RESULTS OF SENSITIVITY ANALYSIS: Results were sensitive to the costs of myeloablative conditioning before gene therapy, effect on caregiver QOL, and effect of gene therapy on long-term survival. LIMITATION: The short-term effects of gene therapy on vaso-occlusive events were extrapolated from 1 study. CONCLUSION: Gene therapy for SCD below a $2 million price tag is likely to be cost-effective when applying a societal perspective at an equity-informed threshold for cost-effectiveness analysis. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute.

Longitudinal adherence to breast cancer surveillance following cancer genetic testing in an integrated health care system.

PURPOSE: Screening with mammography and breast magnetic resonance imaging (MRI) is an important risk management strategy for individuals with inherited pathogenic variants (PVs) in genes associated with increased breast cancer risk. We describe longitudinal screening adherence in individuals who underwent cancer genetic testing as part of usual care in a vertically integrated health system. METHODS: We determined the proportion time covered (PTC) by annual mammography and breast MRI for individuals with PVs in TP53, BRCA1, BRCA2, PALB2, NF1, CHEK2, and ATM. We determined time covered by biennial mammography beginning at age 50 years for individuals who received negative results, uncertain results, or with PVs in genes without specific breast cancer screening recommendations. RESULTS: One hundred and forty individuals had PVs in TP53, BRCA1, BRCA2, PALB2, NF1, CHEK2, or ATM. Among these individuals, average PTC was 48% (range 0-99%) for annual screening mammography and 34% (range 0-100%) for annual breast MRI. Average PTC was highest for individuals with PVs in CHEK2 (N = 14) and lowest for individuals with PVs in TP53 (N = 3). Average PTC for biennial mammography (N = 1,027) was 49% (0-100%). CONCLUSION: Longitudinal screening adherence in individuals with PVs in breast cancer associated genes, as measured by the proportion of time covered, is low; adherence to annual breast MRI falls below that of annual mammography. Additional research should examine screening behavior in individuals with PVs in breast cancer associated genes with a goal of developing interventions to improve adherence to recommended risk management.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

A Scoping Review of the Use of Machine Learning in Health Economics and Outcomes Research: Part 1-Data From Wearable Devices.

OBJECTIVES: With the emerging use of machine learning (ML) techniques, there has been particular interest in using wearable data for health economics and outcomes research (HEOR). We aimed to understand the emerging patterns of how ML has been applied to wearable data in HEOR. METHODS: We identified studies published in PubMed between January 2016 and March 2021. Studies that included at least 1 HEOR-related Medical Subject Headings term, applied an ML, and used wearable data were eligible for inclusion. Two reviewers abstracted information including ML application types and data on which ML was applied and analyzed them using descriptive analyses. RESULTS: A total of 148 studies were identified from PubMed, among which 32 studies met the inclusion criteria. There has been an increase over time in the number of ML studies using wearable data. ML has been more frequently used for monitoring events in real time (78%) than to predict future events (22%). There has been a wide range of outcomes examined, ranging from general physical or mental health (24%) to more disease-specific outcomes (eg, disease incidence [19%] and progression [13%]) and treatment-related outcomes (eg, treatment adherence [9%] and outcomes [9%]). Data for ML models were more often derived from wearable devices with specific medical purposes (60%) than those without (40%). CONCLUSION: There has been a wide range of applications of ML to wearable data. Both medical and nonmedical wearable devices have been used as a data source, showing the potential for providing rich data for ML studies in HEOR.

Comparing Patient and Provider Priorities Around Amputation Level Outcomes Using Multiple Criteria Decision Analysis.

BACKGROUND: Patients with chronic limb threatening ischemia may require a transmetatarsal amputation (TMA) or a transtibial amputation. When making an amputation-level decision, these patients face a tradeoff-a TMA preserves more limb and may provide better mobility but has a lower probability of primary wound healing and may therefore result in additional same or higher level amputation surgeries with an associated negative impact on function. Understanding differences in how patients and providers prioritize these tradeoffs and other outcomes may enhance shared decision-making. OBJECTIVES: Compare patient priorities with provider perceptions of patient priorities using Multiple Criteria Decision Analysis (MCDA). METHODS: The MCDA Analytic Hierarchy Process was chosen due to its low cognitive burden and ease of implementation. We included 5 criteria (outcomes): ability to walk, healing after amputation surgery, rehabilitation program intensity, limb length, and ease of use of prosthetic/orthotic device. A national sample of dysvascular lower-limb amputees and providers were recruited from the Veterans Health Administration with the MCDA administered online to providers and telephonically to patients. RESULTS: Twenty-six dysvascular amputees and 38 providers participated. Fifty percent of patients had undergone a TMA; 50%, a transtibial amputation. When compared to providers, patients placed higher value on TMA (72% vs. 63%). Patient versus provider priorities were ability to walk (47% vs. 42%), healing (18% vs. 28%), ease of prosthesis use (17% vs. 13%), limb length (11% vs. 13%), and then rehabilitation intensity (7% vs. 6%). LIMITATIONS: Our sample may not generalize to other populations. CONCLUSIONS: Provider perceptions aligned with patient values on amputation level but varied around the importance of each outcome. IMPLICATIONS: These findings illuminate some differences between patients' values and provider perceptions of patient values, suggesting a role for shared decision-making. Embedding this MCDA framework into a future decision aid may facilitate these discussions.

Risk-reducing surgery in unaffected individuals receiving cancer genetic testing in an integrated health care system.

BACKGROUND: Germline genetic testing enables primary cancer prevention, including through prophylactic surgery. We examined risk-reducing surgeries in unaffected individuals tested for hereditary cancer susceptibly between 2010 and 2018 in the Kaiser Permanente Northwest health system. METHODS: We used an internal genetic testing database to create a cohort of individuals who received tests including one or more high-penetrance hereditary cancer susceptibility gene. We then identified, after testing, bilateral mastectomy, bilateral salpingo-oophorectomy (BSO), and total hysterectomy procedures in electronic health record and claims data through 2019. We describe surgery utilization by genetic test results and National Comprehensive Cancer Network (NCCN) guidelines. RESULTS: The cohort included 1020 individuals, 16% with pathogenic/likely pathogenic (P/LP) variants in one or more of the following genes: BRCA1, BRCA2, CHEK2, APC, MUTYH, ATM, MSH2, PALB2, BRIP1, MLH1, MSH6, EPCAM, FLCN, RAD51C, RAD51D, or TP53. Among individuals with P/LP variants making them candidates for mastectomy, BSO, or hysterectomy per NCCN guidelines, 34% (33/97), 24% (23/94), and 8% (1/12), respectively, underwent surgery during follow-up. Fifty-three percent (18/37) of hysterectomies were among APC, BRCA1, and BRCA2 P/LP variant heterozygotes, typically concurrent with BSO. Three individuals with variants of uncertain significance (only) and 22 with negative results had prophylactic surgery after genetic testing. CONCLUSIONS: Uptake of risk-reducing surgery following usual care genetic testing appears to be lower than in studies that actively recruit high-risk patients and provide testing and follow-up care in specialized settings. Factors in addition to genetic test results and NCCN guidelines motivate prophylactic surgery use and deserve further study.

Implementation of pharmacogenomic clinical decision support for health systems: a cost-utility analysis.

We constructed a cost-effectiveness model to assess the clinical and economic value of a CDS alert program that provides pharmacogenomic (PGx) testing results, compared to no alert program in acute coronary syndrome (ACS) and atrial fibrillation (AF), from a health system perspective. We defaulted that 20% of 500,000 health-system members between the ages of 55 and 65 received PGx testing for CYP2C19 (ACS-clopidogrel) and CYP2C9, CYP4F2 and VKORC1 (AF-warfarin) annually. Clinical events, costs, and quality-adjusted life years (QALYs) were calculated over 20 years with an annual discount rate of 3%. In total, 3169 alerts would be fired. The CDS alert program would help avoid 16 major clinical events and 6 deaths for ACS; and 2 clinical events and 0.9 deaths for AF. The incremental cost-effectiveness ratio was $39,477/QALY. A PGx-CDS alert program was cost-effective, under a willingness-to-pay threshold of $100,000/QALY gained, compared to no alert program.

Prevalence and prediction of medical distrust in a diverse medical genomic research sample.

PURPOSE: Medical distrust has been identified as a persistent barrier to medical care, affecting preventative screening, treatment uptake, and treatment adherence. Despite this, little research to date has examined medical distrust in a genomic medicine context. The goal of this work was to assess the prevalence of medical distrust in a genomic medicine research study and examine patient-level demographic, access-related, and health-status characteristics that predict medical distrust. METHODS: We assessed medical distrust in a research sample of adults (N = 967) receiving genomic sequencing to screen for hereditary risk of cancer syndromes in the United States. We used multiple predictive variable selection models to determine predictors of medical distrust followed by marginal mean analyses to characterize the relationships. RESULTS: The prevalence of medical distrust was 32%. The final model indicated that Black and African American race/ethnicity; trans, nonbinary, or nonidentifying gender identity; high education; low income; low access to health care; and poor Short Form 12 mental health composite scores predict medical distrust. CONCLUSION: Medical distrust may pose similar challenges to genomic sequencing, as it does in other medical contexts. The pattern of variables that predict distrust suggest that increasing access and accommodation for stigmatized and underserved communities may help overcome the negative effects of medical distrust.

US private payers' perspectives on insurance coverage for genome sequencing versus exome sequencing: A study by the Clinical Sequencing Evidence-Generating Research Consortium (CSER).

PURPOSE: There is limited payer coverage for genome sequencing (GS) relative to exome sequencing (ES) in the U.S. Our objective was to assess payers' considerations for coverage of GS versus coverage of ES and requirements payers have for coverage of GS. The study was conducted by the NIH-funded Clinical Sequencing Evidence-Generating Research Consortium (CSER). METHODS: We conducted semi-structured interviews with representatives of private payer organizations (payers, N = 12) on considerations and evidentiary and other needs for coverage of GS and ES. Data were analyzed using thematic analysis. RESULTS: We described four categories of findings and solutions: demonstrated merits of GS versus ES, enhanced methods for evidence generation, consistent laboratory processes/sequencing methods, and enhanced implementation/care delivery. Payers see advantages to GS vs. ES and are open to broader GS coverage but need more proof of these advantages to consider them in coverage decision-making. Next steps include establishing evidence of benefits in specific clinical scenarios, developing quality standards, ensuring transparency of laboratory methods, developing clinical centers of excellence, and incorporating the role of genetic professionals. CONCLUSION: By comparing coverage considerations for GS and ES, we identified a path forward for coverage of GS. Future research should explicitly address payers' conditions for coverage.

Assessing Payers' Preferences for Real-World Evidence in the United States: A Discrete Choice Experiment.

OBJECTIVES: To rank the US payers' preferences for attributes of real-world evidence (RWE) studies in the context of chronic disease and to quantify trade-offs among them. METHODS: We conducted a discrete choice experiment in which 180 employees from payer organizations were tasked to choose between 2 RWE studies assuming they were assessing evidence to inform formulary decisions for chronic disease treatment. Each RWE study was characterized by 7 attributes with 3 levels each: very informative, moderately informative, and not measured. We used a D-optimal main-effects design. Survey data were fitted to a conditional logit model to obtain a relative measure of the ranking of importance for each attribute. RESULTS: Clinical outcomes were the most preferred attribute. It was 4.68 times as important as productivity outcomes-the least preferred attribute. It was followed by health-related quality of life (2.78), methodologic rigor (2.09), resource utilization (1.71), and external validity (1.56). CONCLUSIONS: This study provides a quantification of the value payers place on key RWE attributes. Across attributes, payers have higher preferences for clinical and health-related quality of life outcomes than the other attributes. Between attributes' levels, payers prefer high levels of information in clinical outcomes and methodologic rigor but are indifferent in other attributes. Our results bridge the gap between the information that payers seek and the attributes that RWE studies prioritize and effectively guide future research design.

Health State Utilities for Sickle Cell Disease: A Catalog Prepared From a Systematic Review.

OBJECTIVES: Sickle cell disease (SCD) is a complex, chronic condition that impairs health-related quality of life of affected individuals and their caregivers. As curative therapies emerge, comprehensive cost-effectiveness models will inform their value. These models will require descriptions of health states and their corresponding utility values that accurately reflect health-related quality of life over the disease trajectory. The objectives of this systematic review were to develop a catalog of health state utility (HSU) values for SCD, identify research gaps, and provide future directions for preference elicitation. METHODS: Records were identified through searches of PubMed and Embase, Tufts Medical Center Cost-Effectiveness Analysis Registry, reference lists of relevant articles, and consultation with SCD experts (2008-2020). We removed duplicate records and excluded ineligible studies. For included studies, we summarized the study characteristics, methods used for eliciting HSUs, and HSU values. RESULTS: Five studies empirically elicited utilities using indirect methods (EQ-5D) (n = 3) and Short Form-6 Dimension (n = 2); these represent health states associated with general SCD (n = 1), SCD complications (n = 2), and SCD treatments (n = 3). Additionally, we extracted HSUs from 7 quality-adjusted life-years-based outcome research studies. The HSU among patients with general SCD without specifying complications ranged from 0.64 to 0.887. Only 36% of the HSUs used in the quality-adjusted life-year-based outcomes research studies were derived from individuals with SCD. No study estimated HSUs in caregivers. CONCLUSIONS: There is a dearth of literature of HSUs for use in SCD models. Future empirical studies should elicit a comprehensive set of HSUs from individuals with SCD and their caregivers.

A Scoping Review of the Use of Machine Learning in Health Economics and Outcomes Research: Part 2-Data From Nonwearables.

OBJECTIVES: Despite the increasing interest in applying machine learning (ML) methods in health economics and outcomes research (HEOR), stakeholders face uncertainties in when and how ML can be used. We reviewed the recent applications of ML in HEOR. METHODS: We searched PubMed for studies published between January 2020 and March 2021 and randomly chose 20% of the identified studies for the sake of manageability. Studies that were in HEOR and applied an ML technique were included. Studies related to wearable devices were excluded. We abstracted information on the ML applications, data types, and ML methods and analyzed it using descriptive statistics. RESULTS: We retrieved 805 articles, of which 161 (20%) were randomly chosen. Ninety-two of the random sample met the eligibility criteria. We found that ML was primarily used for predicting future events (86%) rather than current events (14%). The most common response variables were clinical events or disease incidence (42%) and treatment outcomes (22%). ML was less used to predict economic outcomes such as health resource utilization (16%) or costs (3%). Although electronic medical records (35%) were frequently used for model development, claims data were used less frequently (9%). Tree-based methods (eg, random forests and boosting) were the most commonly used ML methods (31%). CONCLUSIONS: The use of ML techniques in HEOR is growing rapidly, but there remain opportunities to apply them to predict economic outcomes, especially using claims databases, which could inform the development of cost-effectiveness models.

Application of validated mapping algorithms between generic PedsQL scores and utility values to individuals with sickle cell disease.

PURPOSE: There is a paucity of empirically estimated health state utility (HSU) values to estimate health-related quality of life among individuals with sickle cell disease (SCD). This study aims to map the Pediatric Quality of Life Inventory generic core scales (PedsQL GCS) to HSUs for children and adolescents with SCD in the United States, using published algorithms, and to assess the construct validity of these HSUs against SCD-specific PedsQL scores. METHODS: We used the published mapping algorithms identified in four published articles, in which the PedsQL GCS was mapped to either the EuroQol-5 Dimension 3-Level, Youth Version or the Child Health Utility 9-Dimension to obtain HSUs. We employed the algorithms to calculate HSUs for a sample of children and adolescents from the Sickle Cell Clinical Research and Intervention Program. To assess the construct validity of the mapped HSUs in SCD patients, we computed Spearman's correlation coefficient comparing the HSUs with the PedsQL SCD total score and separately with each PedsQL SCD dimension-specific score. RESULTS: The mean mapped HSU across published algorithms was 0.792 (95% CI: 0.782-0.801). It was significantly higher among children aged 5-12 years than children aged 13-17 years. The Spearman's correlation coefficient for HSUs versus PedsQL SCD total scores was 0.64 (95% CI: 0.57-0.71). Correlations ranged from 0.40 (95% CI: 0.32-0.48) to 0.60 (95% CI: 0.54-0.66) for HSUs versus PedsQL SCD dimension-specific scores. CONCLUSIONS: The existing mapping algorithms show acceptable construct validity in children and adolescents with SCD. Additional algorithms are needed for adults and for specific SCD comorbidities.

Geographic variation in the use of triptans and opioids for the acute treatment of migraine attacks.

OBJECTIVE: To assess the geographic variations in triptan and opioid prescribing patterns for patients with migraine. BACKGROUND: Numerous guidelines recommend triptans as the standard of care for migraine attacks, yet opioids are still widely used for migraine treatment. Variation in the use of opioids and triptans for the treatment of migraine by geographic location is not well known. METHODS: Using a US claims database, we conducted a retrospective cohort study of adults diagnosed with migraine between 2016 and 2018. We used a 12-month follow-up period to assess triptan and opioid utilization, stratified by the nine Census Bureau-designated divisions. To examine the geographic factors that affect triptan and opioid use among patients, we conducted two sets of multivariable analyses. First, we analyzed the odds of a patient being a triptan or opioid user in the follow-up period, defined as ≥1 triptan or opioid claim. We then analyzed the medication use rate among triptan or opioid users. RESULTS: Overall, we had a final study population of 113,921 patients. In the follow-up period, 52.9% (60,247/113,921) [range: 48.0%-56.3%] of patients were triptan users and 41.0% (46,708/113,921) [range: 28.9%-48.4%] of patients were opioid users with significant differences across census divisions (p < 0.001). Triptan users had a mean (SD) of 4.8 (4.7) triptan claims annually with no significant differences across divisions (p = 0.188). Opioid users had a mean (SD) of 5.4 (6.8) opioid claims annually with significant differences across divisions (p < 0.001). The observed variation in opioid use stemmed from the proportion of patients using opioids in each region and not from the number of opioid prescriptions per user. CONCLUSIONS: There was a significant geographic variation in the use of opioids and to a lesser degree the use of triptans. The widespread use of opioids and the large variation in use other than triptans as the standard of care suggest that improvements could be made in the acute treatment of migraine attacks.

Comparative effects of telemedicine and face-to-face warfarin management: A systematic review and network meta-analysis.

OBJECTIVE: To determine the comparative effects of different types of telemedicine on anticoagulation control and adverse outcomes in patients taking warfarin. DATA SOURCES: A systematic search was conducted in PubMed, the Cochrane library, EMBASE, CINAHL, OpenGrey, and DART-Europe from inception to September 2019. STUDY SELECTION: Randomized controlled trials, quasi-experimental and cohort studies were included if they evaluated the effect of telemedicine in patients using warfarin for 3 months or more. METHODS: Two reviewers extracted and assessed the quality of studies by means of the Cochrane Effective Practice and Organization of Care Group. Network meta-analyses were performed using a random-effects model. Surface under the cumulative ranking curve (SUCRA) methods were used to rank different telemedicine types. RESULTS: Of the 14,673 articles retrieved, 12 studies involving 11,478 patients met the inclusion criteria. The 5 types of telemedicine categorized were 1) laboratory draw with individual telephonic follow-up by health care (HC) providers (Lab/Tel/HC); 2) laboratory draw with individual telephonic follow-up with periodic, routine routine face-to-face (F2F) visit (Lab/Tel+F2F/HC); 3) laboratory draw with individual and group follow-up via online access (Lab/Online/HC); 4) patient self-test (PST) with telephonic or Web-based follow-up by automated management system (PST/Tel-Online/Auto); and 5) PST with telephonic follow-up by HC provider (PST/Tel/HC). PST/Tel-Online/Auto appears to be superior to F2F for TTR (mean difference 8.78%; 95% CI 0.06%-17.50%) and Lab/Online/HC for in-range INR (odds ratio 2.59; 95% CI 1.04-6.46). The SUCRAs suggested that PST/Tel-Online/Auto was preferred for both TTR and INR, at 84.2% and 93.9%, respectively, whereas Lab/Tel/HC was preferred to prevent major bleeding (74.1%) or thromboembolic event (70.7%). CONCLUSION: According to the current evidence of uncertain quality, the best effects on anticoagulation control and adverse outcomes were achieved from different types of telemedicine. Variations in the effects of telemedicine on diverse outcomes should be considered before implementing telemedicine interventions in patients taking warfarin.

Projected Cost-Effectiveness for 2 Gene-Drug Pairs Using a Multigene Panel for Patients Undergoing Percutaneous Coronary Intervention.

BACKGROUND: For patients undergoing percutaneous coronary intervention, gene-drug associations exist relevant to first-line treatment options-antiplatelet agent, clopidogrel, and pain medication, tramadol. Knowledge of genotype information may allow for avoidance of adverse drug events during critical clinical windows. OBJECTIVE: This evaluation estimated cost-effectiveness associated with a multi-gene panel pre-emptively testing two genes providing CYP2C19 genotype-guided strategy for antiplatelet therapy, with CYP2D6 genotype-guided pain management, compared to single gene test for CYP2C19 with random assignment for pain treatment, and to no testing (empiric clopidogrel with random assignment for pain treatment). METHODS: Decision analysis modeling was used to project costs from a payer perspective and patient quality-adjusted life years (QALYs) from the three strategies. The model captured composite risks of major adverse cardiovascular events and pain therapy-related adverse drug events and associated utility estimates. We conducted sensitivity analyses to assess influential input parameters. RESULTS: Over 15 months, multi-gene testing was least costly and yielded more QALYs compared to both single gene and no testing; total incremental costs were $1646 lower with incremental gains of 0.04 QALYs for multi-gene compared with single gene and $11 368 lower with 0.17 QALY gains compared to no test. Base case analyses revealed multi gene was dominant compared to both single gene and no test, as it demonstrated cost savings with increased QALYs. CONCLUSIONS: For these patients, a multi-gene-guided strategy yields a favorable incremental cost-effectiveness ratio compared to the other two treatment strategies. Pre-emptively ascertaining additional gene-drug pair information can inform clinical and economic decision-making at the point of care.

Trials with patient-reported outcomes registered on the Australian New Zealand Clinical Trials Registry (ANZCTR).

AIMS: It is important to understand the number, types and regions of trials that include patient-reported outcomes (PROs) to appreciate how patient experiences have been considered in studies of health and interventions. Twenty-seven percent of trials registered with ClinicalTrials.gov (2007-2013) included PROs; however, a regional breakdown was not provided and no reviews have been conducted of the Australia New Zealand Clinical Trials Registry (ANZCTR). We aimed to identify trials registered with ANZCTR with PRO endpoints and describe their characteristics. METHODS: ANZCTR was systematically searched from inception (2005) to 31 March 2017 for trials with PRO endpoints. Search terms included PRO measures listed in Patient-Reported Outcomes Quality of Life Instrument Database and Grid-Enabled Measures, as well as generic PRO terms (e.g. "quality of life" (QOL)). Trial endpoints were individually coded using an established framework to identify trials with PROs for the analysis. RESULTS: Of 13,666 registered trials, 6168 (45.1%) included a PRO. The proportion of studies including PROs increased between 2006 and 2016 (r = 0.74, p = 0.009). Among the 6168 trials, there were 17,961 individual PRO endpoints, including symptoms/functional outcomes/condition-specific QOL (65.6%), generic QOL (13.2%), patient-reported experiences (9.9%), patient-reported behaviours (7.9%). Mental health was the most common category (99.8% included PROs), followed by physical medicine/rehabilitation (65.6%), musculoskeletal (63.5%), public health (63.1%), and cancer (54.2%). DISCUSSION: Our findings suggest growing use of PROs in the assessment of health and interventions in ANZ. Our review identifies trial categories with limited patient-reported information and provides a basis for future work on the impact of PRO findings in clinical care.

Correction to: Trials with patient-reported outcomes registered on the Australian New Zealand Clinical Trials Registry (ANZCTR).

In the original publication of the article, the sentence "The ANZCTR is the fifth largest trial registry internationally, with 21,330 registered trials as at January 2018 [5]" in the Introduction section was published incorrectly.

Primary Care-Based Models for the Treatment of Opioid Use Disorder: A Scoping Review.

Greater integration of medication-assisted treatment (MAT) for opioid use disorder (OUD) in U.S. primary care settings would expand access to treatment for this condition. Models for integrating MAT into primary care vary in structure. This article summarizes findings of a technical report for the Agency for Healthcare Research and Quality describing MAT models of care for OUD, based on a literature review and interviews with key informants in the field. The report describes 12 representative models of care for integrating MAT into primary care settings that could be considered for adaptation across diverse health care settings. Common components of existing care models include pharmacotherapy with buprenorphine or naltrexone, provider and community education, coordination and integration of OUD treatment with other medical and psychological needs, and psychosocial services and interventions. Models vary in how each component is implemented. Decisions about adopting MAT models of care should be individualized to address the unique milieu of each implementation setting.

Minimal residual disease prior to allogeneic hematopoietic cell transplantation in acute myeloid leukemia: a meta-analysis.

Minimal residual disease prior to allogeneic hematopoietic cell transplantation has been associated with increased risk of relapse and death in patients with acute myeloid leukemia, but detection methodologies and results vary widely. We performed a systematic review and meta-analysis evaluating the prognostic role of minimal residual disease detected by polymerase chain reaction or multiparametric flow cytometry before transplant. We identified 19 articles published between January 2005 and June 2016 and extracted hazard ratios for leukemia-free survival, overall survival, and cumulative incidences of relapse and non-relapse mortality. Pre-transplant minimal residual disease was associated with worse leukemia-free survival (hazard ratio=2.76 [1.90-4.00]), overall survival (hazard ratio=2.36 [1.73-3.22]), and cumulative incidence of relapse (hazard ratio=3.65 [2.53-5.27]), but not non-relapse mortality (hazard ratio=1.12 [0.81-1.55]). These associations held regardless of detection method, conditioning intensity, and patient age. Adverse cytogenetics was not an independent risk factor for death or relapse. There was more heterogeneity among studies using flow cytometry-based than WT1 polymerase chain reaction-based detection (I2=75.1% vs. <0.1% for leukemia-free survival, 67.8% vs. <0.1% for overall survival, and 22.1% vs. <0.1% for cumulative incidence of relapse). These results demonstrate a strong relationship between pre-transplant minimal residual disease and post-transplant relapse and survival. Outcome heterogeneity among studies using flow-based methods may underscore site-specific methodological differences or differences in test performance and interpretation.