Confidence score: a data-driven measure for inclusive systematic reviews considering unpublished preprints

OBJECTIVES

COVID-19, since its emergence in December 2019, has globally impacted research. Over 360 000 COVID-19-related manuscripts have been published on PubMed and preprint servers like medRxiv and bioRxiv, with preprints comprising about 15% of all manuscripts. Yet, the role and impact of preprints on COVID-19 research and evidence synthesis remain uncertain.

MATERIALS AND METHODS

We propose a novel data-driven method for assigning weights to individual preprints in systematic reviews and meta-analyses. This weight termed the "confidence score" is obtained using the survival cure model, also known as the survival mixture model, which takes into account the time elapsed between posting and publication of a preprint, as well as metadata such as the number of first 2-week citations, sample size, and study type.

RESULTS

Using 146 preprints on COVID-19 therapeutics posted from the beginning of the pandemic through April 30, 2021, we validated the confidence scores, showing an area under the curve of 0.95 (95% CI, 0.92-0.98). Through a use case on the effectiveness of hydroxychloroquine, we demonstrated how these scores can be incorporated practically into meta-analyses to properly weigh preprints.

DISCUSSION

It is important to note that our method does not aim to replace existing measures of study quality but rather serves as a supplementary measure that overcomes some limitations of current approaches.

CONCLUSION

Our proposed confidence score has the potential to improve systematic reviews of evidence related to COVID-19 and other clinical conditions by providing a data-driven approach to including unpublished manuscripts.

Dynamic prediction modeling of postoperative mortality among patients undergoing surgical aortic valve replacement in a statewide cohort over a 12-year period

Objective

Clinical prediction models for surgical aortic valve replacement mortality, are valuable decision tools but are often limited in their ability to account for changes in medical practice, patient selection, and the risk of outcomes over time. Recent research has identified methods to update models as new data accrue, but their effect on model performance has not been rigorously tested.

Methods

The study population included 44,546 adults who underwent an isolated surgical aortic valve replacement from January 1, 1999, to December 31, 2018, statewide in Pennsylvania. After chronologically splitting the data into training and validation sets, we compared calibration, discrimination, and accuracy measures amongst a nonupdating model to 2 methods of model updating: calibration regression and the novel dynamic logistic state space model.

Results

The risk of mortality decreased significantly during the validation period (P < .01) and the nonupdating model demonstrated poor calibration and reduced accuracy over time. Both updating models maintained better calibration (Hosmer-Lemeshow χ2 statistic) than the nonupdating model: nonupdating (156.5), calibration regression (4.9), and dynamic logistic state space model (8.0). Overall accuracy (Brier score) was consistently better across both updating models: dynamic logistic state space model (0.0252), calibration regression (0.0253), and nonupdating (0.0256). Discrimination improved with the dynamic logistic state space model (area under the curve, 0.696) compared with the nonupdating model (area under the curve, 0.685) and calibration regression method (area under the curve, 0.687).

Conclusions

Dynamic model updating can improve model accuracy, discrimination, and calibration. The decision as to which method to use may depend on which measure is most important in each clinical context. Because competing therapies have emerged for valve replacement models, updating may guide clinical decision making.

Dynamic logistic state space prediction model for clinical decision making

Prediction modeling for clinical decision making is of great importance and needed to be updated frequently with the changes of patient population and clinical practice. Existing methods are either done in an ad hoc fashion, such as model recalibration or focus on studying the relationship between predictors and outcome and less so for the purpose of prediction. In this article, we propose a dynamic logistic state space model to continuously update the parameters whenever new information becomes available. The proposed model allows for both time-varying and time-invariant coefficients. The varying coefficients are modeled using smoothing splines to account for their smooth trends over time. The smoothing parameters are objectively chosen by maximum likelihood. The model is updated using batch data accumulated at prespecified time intervals, which allows for better approximation of the underlying binomial density function. In the simulation, we show that the new model has significantly higher prediction accuracy compared to existing methods. We apply the method to predict 1 year survival after lung transplantation using the United Network for Organ Sharing data.

A Conceptual Model for Sources of Differential Selection in Lung Transplant Allocation

Rationale: In the United States, donor lungs are allocated to transplant candidates on the basis of lung allocation scores (LAS). However, additional factors beyond the LAS can impact who is transplanted, including listing and donor-organ acceptance practices. These factors can result in differential selection, undermining the objectivity of lung allocation. Yet their impact on the lung transplant pathway has been underexplored. Objectives: We sought to systematically examine sources of differential selection in lung transplantation via qualitative methods. Methods: We conducted semistructured qualitative interviews with lung transplant surgeons and pulmonologists in the United States between June 2019 and June 2020 to understand clinician perspectives on differential selection in lung transplantation and the LAS. Results: A total of 51 respondents (30 surgeons and 21 pulmonologists) identified many sources of differential selection arising throughout the pathway from referral to transplantation. We synthesized these sources into a conceptual model with five themes: 1) transplant center's degree of risk tolerance and accountability; 2) successfulness and fairness of the LAS; 3) donor-organ availability and regional competition; 4) patient health versus program health; and 5) access to care versus responsible stewardship of organs. Conclusions: Our conceptual model demonstrates how differential selection can arise throughout lung transplantation and facilitates the further study of such selection. As new organ allocation models are developed, differential selection should be considered carefully to ensure that these models are more equitable.

Modified Brier score for evaluating prediction accuracy for binary outcomes

The Brier score has been a popular measure of prediction accuracy for binary outcomes. However, it is not straightforward to interpret the Brier score for a prediction model since its value depends on the outcome prevalence. We decompose the Brier score into two components, the mean squares between the estimated and true underlying binary probabilities, and the variance of the binary outcome that is not reflective of the model performance. We then propose to modify the Brier score by removing the variance of the binary outcome, estimated via a general sliding window approach. We show that the new proposed measure is more sensitive for comparing different models through simulation. A standardized performance improvement measure is also proposed based on the new criterion to quantify the improvement of prediction performance. We apply the new measures to the data from the Breast Cancer Surveillance Consortium and compare the performance of predicting breast cancer risk using the models with and without its most important predictor.

Underprescribing vs underfilling to oral anticoagulation: An analysis of linked medical record and claims data for a nationwide sample of patients with atrial fibrillation

BACKGROUND: Oral anticoagulants (OAC) is indicated for stroke prevention in patients with atrial fibrillation (AF) with a moderate or high risk of stroke. Despite the benefits of stroke prevention, only 50%-60% of Americans with nonvalvular AF and a moderate or high risk of stroke receive OAC medication. OBJECTIVE: To understand the extent to which low OAC use by patients with AF is attributed to underprescribing or underfilling once the medication is prescribed. METHODS: This is a retrospective cohort study that used linked claims data and electronic health records from Optum Integrated data. Participants were adults (aged ≥ 18 years) with first AF between January 2013 and June 2017. The outcomes included (1) being prescribed OACs within 180 days of AF diagnosis or not and (2) filling an OAC prescription or not among patients with AF who were prescribed an OAC within 150 days of AF diagnosis. Multivariable logistic regression models were constructed to determine factors associated with underprescribing and underfilling. RESULTS: Of the 6,141 individuals in the study cohort, 51% were not prescribed OACs within 6 months of their AF diagnosis. Of the 2,956 patients who were prescribed, 19% did not fill it at the pharmacy. In the final adjusted model, younger age, location (Northeast and South), a low CHA₂DS₂-VASc score, and a high HAS-BLED score were associated with a lower likelihood of being prescribed OACs. Among patients who were prescribed, Medicare enrollment (odds ratio [OR] [95% CI] = 2.2 [1.3-3.7]) and having a direct oral anticoagulant prescription (1.5 [1.2-1.9]) were associated with a lower likelihood of filling the prescription. CONCLUSIONS: Both underprescribing and underfilling are major drivers of low OAC use among patients with AF, and solutions to increase OAC use must address both prescribing and filling. DISCLOSURES: Research reported in this study was supported by the National Heart, Lung and Blood Institute (K01HL142847 and R01HL157051). Dr Guo is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK133465), PhMRA Foundation Research Starter Award, and the University of Florida Research Opportunity Seed Fund. Dr Hernandez reports scientific advisory board fees from Pfizer and Bristol Myers Squibb, outside of the submitted work.

Clinical impact of a modified lung allocation score that mitigates selection bias

BACKGROUND

The Lung Allocation Score (LAS) is used in the U.S. to prioritize lung transplant candidates. Selection bias, induced by dependent censoring of waitlisted candidates and prediction of posttransplant survival among surviving, transplanted patients only, is only partially addressed by the LAS. Recently, a modified LAS (mLAS) was designed to mitigate such bias. Here, we estimate the clinical impact of replacing the LAS with the mLAS.

METHODS

We considered lung transplant candidates waitlisted during 2016 and 2017. LAS and mLAS scores were computed for each registrant at each observed organ offer date; individuals were ranked accordingly. Patient characteristics associated with better priority under the mLAS were investigated via logistic regression and generalized linear mixed models. We also determined whether differences in rank were explained more by changes in predicted pre- or posttransplant survival. Simulations examined how 1-year waitlist, posttransplant, and overall survival might change under the mLAS.

RESULTS

Diagnosis group, 6-minute walk distance, continuous mechanical ventilation, functional status, and age demonstrated the highest impact on differential allocation. Differences in rank were explained more by changes in predicted pretransplant survival than changes in predicted posttransplant survival, suggesting that selection bias has more impact on estimates of waitlist urgency. Simulations suggest that for every 1000 waitlisted individuals, 12.8 (interquartile range: 5.2-24.3) fewer waitlist deaths per year would occur under the mLAS, without compromising posttransplant and overall survival.

CONCLUSIONS

Implementing a mLAS that mitigates selection bias into clinical practice can lead to important differences in allocation and possibly modest improvement in waitlist survival.

The development and initial validation of the PROMIS®+HF-27 and PROMIS+HF-10 profiles

AIMS

Heart failure (HF) is a common and morbid condition impacting multiple health domains. We previously reported the development of the PROMIS®-Plus-HF (PROMIS+HF) profile measure, including universal and HF-specific items. To facilitate use, we developed shorter, PROMIS+HF profiles intended for research and clinical use.

METHODS AND RESULTS

Candidate items were selected based on psychometric properties and symptom range coverage. HF clinicians (n = 43) rated item importance and clinical actionability. Based on these results, we developed the PROMIS+HF-27 and PROMIS+HF-10 profiles with summary scores (0-100) for overall, physical, mental, and social health. In a cross-sectional sample (n = 600), we measured internal consistency reliability (Cronbach's alpha and Spearman-Brown), test-retest reliability (intraclass coefficient; n = 100), known-groups validity via New York Heart Association (NYHA) class, and convergent validity with Kansas City Cardiomyopathy Questionnaire (KCCQ) scores. In a longitudinal sample (n = 75), we evaluated responsiveness of baseline/follow-up scores by calculating mean differences and Cohen's d and comparing with paired t-tests. Internal consistency was good to excellent (α 0.82-0.94) for all PROMIS+HF-27 scores and acceptable to good (α/Spearman-Brown 0.60-0.85) for PROMIS+HF-10 scores. Test-retest intraclass coefficients were acceptable to excellent (0.75-0.97). Both profiles demonstrated known-groups validity for the overall and physical health summary scores based on NYHA class, and convergent validity for nearly all scores compared with KCCQ scores. In the longitudinal sample, we demonstrated responsiveness for PROMIS+HF-27 and PROMIS+HF-10 overall and physical summary scores. For the PROMIS+HF overall summary scores, a group-based increase of 7.6-8.3 points represented a small to medium change (Cohen's d = 0.40-0.42). For the PROMIS+HF physical summary scores, a group-based increase of 5.0-5.9 points represented a small to medium change (Cohen's d = 0.29-0.35).

CONCLUSIONS

The PROMIS+HF-27 and PROMIS+HF-10 profiles demonstrated good psychometric characteristics with evidence of responsiveness for overall and physical health. These new measures can facilitate patient-centred research and clinical care, such as improving care quality through symptom monitoring, facilitating shared decision-making, evaluating quality of care, assessing new interventions, and monitoring during the initiation and titration of guideline-directed medical therapy.

A Comparison of Methods to Detect Changes in Prediction Models

BACKGROUND

Prediction models inform decisions in many areas of medicine. Most models are fitted once and then applied to new (future) patients, despite the fact that model coefficients can vary over time due to changes in patients' clinical characteristics and disease risk. However, the optimal method to detect changes in model parameters has not been rigorously assessed.

METHODS

We simulated data, informed by post-lung transplant mortality data and tested the following two approaches for detecting model change: (1) the "Direct Approach," it compares coefficients of the model refit on recent data to those at baseline; and (2) "Calibration Regression," it fits a logistic regression model of the log-odds of the observed outcomes versus the linear predictor from the baseline model (i.e., the log-odds of the predicted probabilities obtained from the baseline model) and tests whether the intercept and slope differ from 0 and 1, respectively. Four scenarios were simulated using logistic regression for binary outcomes as follows: (1) we fixed all model parameters, (2) we varied the outcome prevalence between 0.1 and 0.2, (3) we varied the coefficient of one of the ten predictors between 0.2 and 0.4, and (4) we varied the outcome prevalence and coefficient of one predictor simultaneously.

RESULTS

Calibration regression tended to detect changes sooner than the Direct Approach, with better performance (e.g., larger proportion of true claims). When the sample size was large, both methods performed well. When two parameters changed simultaneously, neither method performed well.

CONCLUSION

Neither change detection method examined here proved optimal under all circumstances. However, our results suggest that if one is interested in detecting a change in overall incidence of an outcome (e.g., intercept), the Calibration Regression method may be superior to the Direct Approach. Conversely, if one is interested in detecting a change in other model covariates (e.g., slope), the Direct Approach may be superior.

Comparable Cardiorenal Benefits of SGLT2 Inhibitors and GLP-1RAs in Asian and White Populations: An Updated Meta-analysis of Results From Randomized Outcome Trials

BACKGROUND

Whether the cardiorenal benefits of sodium-glucose cotransporter 2 (SGLT2) inhibitors and glucagon-like peptide 1 receptor agonists (GLP-1RAs) are comparable between White and Asian populations remains unclear.

PURPOSE

To compare the cardiorenal benefits of SGLT2 inhibitors and GLP-1RAs between White and Asian populations and to compare the cardiorenal benefits between the two agents in Asian patients.

DATA SOURCES

Electronic databases were searched up to 28 March 2021.

STUDY SELECTION

We included the cardiovascular (CV) and renal outcome trials of SGLT2 inhibitors and GLP-1RAs where investigators reported major adverse CV events (MACE), CV death/hospitalization for heart failure (HHF), or composite renal outcomes with stratification by race.

DATA EXTRACTION

We extracted the hazard ratio of each outcome stratified by race (Asian vs. White populations).

DATA SYNTHESIS

In 10 SGLT2 inhibitor trials, there was no significant difference between Asian and White populations for MACE (P = 0.55), CV death/HHF (P = 0.87), or composite renal outcomes (P = 0.97). In seven GLP-1RA trials, we observed a similar MACE benefit between Asian and White populations (P = 0.10). In our networkmeta-analysis we found a comparable benefit for MACE between SGLT2 inhibitors and GLP-1RAs in Asian patients.

LIMITATIONS

The data were from stratified analyses.

CONCLUSIONS

There appear to be comparable cardiorenal benefits of SGLT2 inhibitors and GLP-1RAs between Asian and White participants enrolled in CV and renal outcome trials; the two therapies seem to have similar CV benefits for Asian participants.

Identifying Patients at Risk of Acute Kidney Injury Among Medicare Beneficiaries With Type 2 Diabetes Initiating SGLT2 Inhibitors: A Machine Learning Approach

Introduction: To predict acute kidney injury (AKI) risk in patients with type 2 diabetes (T2D) prescribed sodium-glucose cotransporter two inhibitors (SGLT2i).

Methods: Using a 5% random sample of Medicare claims data, we identified 17,694 patients who filled ≥1 prescriptions for canagliflozin, dapagliflozin and empagliflozin in 2013–2016. The cohort was split randomly and equally into training and testing sets. We measured 65 predictor candidates using claims data from the year prior to SGLT2i initiation. We then applied three machine learning models, including random forests (RF), elastic net and least absolute shrinkage and selection operator (LASSO) for risk prediction.

Results: The incidence rate of AKI was 1.1% over a median 1.5 year follow up. Among three machine learning methods, RF produced the best prediction (C-statistic = 0.72), followed by LASSO and elastic net (both C-statistics = 0.69). Among individuals classified in the top 10% of the RF risk score (i.e., high risk group), the actual incidence rate of AKI was as high as 3.7%. In the logistic regression model including 14 important risk factors selected by LASSO, use of loop diuretics [adjusted odds ratio (95% confidence interval): 3.72 (2.44–5.76)] had the strongest association with AKI incidence.

Disscusion: Our machine learning model efficiently identified patients at risk of AKI among Medicare beneficiaries with T2D undergoing SGLT2i treatment.

Comparison of dynamic updating strategies for clinical prediction models

BACKGROUND

Prediction models inform many medical decisions, but their performance often deteriorates over time. Several discrete-time update strategies have been proposed in the literature, including model recalibration and revision. However, these strategies have not been compared in the dynamic updating setting.

METHODS

We used post-lung transplant survival data during 2010-2015 and compared the Brier Score (BS), discrimination, and calibration of the following update strategies: (1) never update, (2) update using the closed testing procedure proposed in the literature, (3) always recalibrate the intercept, (4) always recalibrate the intercept and slope, and (5) always refit/revise the model. In each case, we explored update intervals of every 1, 2, 4, and 8 quarters. We also examined how the performance of the update strategies changed as the amount of old data included in the update (i.e., sliding window length) increased.

RESULTS

All methods of updating the model led to meaningful improvement in BS relative to never updating. More frequent updating yielded better BS, discrimination, and calibration, regardless of update strategy. Recalibration strategies led to more consistent improvements and less variability over time compared to the other updating strategies. Using longer sliding windows did not substantially impact the recalibration strategies, but did improve the discrimination and calibration of the closed testing procedure and model revision strategies.

CONCLUSIONS

Model updating leads to improved BS, with more frequent updating performing better than less frequent updating. Model recalibration strategies appeared to be the least sensitive to the update interval and sliding window length.

Mitigating selection bias in organ allocation models

Background

The lung allocation system in the U.S. prioritizes lung transplant candidates based on estimated pre- and post-transplant survival via the Lung Allocation Scores (LAS). However, these models do not account for selection bias, which results from individuals being removed from the waitlist due to receipt of transplant, as well as transplanted individuals necessarily having survived long enough to receive a transplant. Such selection biases lead to inaccurate predictions.

Methods

We used a weighted estimation strategy to account for selection bias in the pre- and post-transplant models used to calculate the LAS. We then created a modified LAS using these weights, and compared its performance to that of the existing LAS via time-dependent receiver operating characteristic (ROC) curves, calibration curves, and Bland-Altman plots.

Results

The modified LAS exhibited better discrimination and calibration than the existing LAS, and led to changes in patient prioritization.

Conclusions

Our approach to addressing selection bias is intuitive and can be applied to any organ allocation system that prioritizes patients based on estimated pre- and post-transplant survival. This work is especially relevant to current efforts to ensure more equitable distribution of organs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01379-7.

Comparative Safety of Dipeptidyl Peptidase-4 Inhibitors and Sudden Cardiac Arrest and Ventricular Arrhythmia: Population-Based Cohort Studies

In vivo studies suggest that arrhythmia risk may be greater with less selective dipeptidyl peptidase-4 inhibitors, but evidence from population-based studies is missing. We aimed to compare saxagliptin, sitagliptin, and linagliptin with regard to risk of sudden cardiac arrest (SCA)/ventricular arrhythmia (VA). We conducted high-dimensional propensity score (hdPS) matched, new-user cohort studies. We analyzed Medicaid and Optum Clinformatics separately. We identified new users of saxagliptin, sitagliptin (both databases), and linagliptin (Optum only). We defined SCA/VA outcomes using emergency department and inpatient diagnoses. We identified and then controlled for confounders via a data-adaptive, hdPS approach. We generated marginal hazard ratios (HRs) via Cox proportional hazards regression using a robust variance estimator while adjusting for calendar year. We identified the following matched comparisons: saxagliptin vs. sitagliptin (23,895 vs. 96,972) in Medicaid, saxagliptin vs. sitagliptin (48,388 vs. 117,383) in Optum, and linagliptin vs. sitagliptin (36,820 vs. 78,701) in Optum. In Medicaid, use of saxagliptin (vs. sitagliptin) was associated with an increased rate of SCA/VA (adjusted HR (aHR), 2.01, 95% confidence interval (CI) 1.24-3.25). However, in Optum data, this finding was not present (aHR, 0.79, 95% CI 0.41-1.51). Further, we found no association between linagliptin (vs. sitagliptin) and SCA/VA (aHR, 0.65, 95% CI 0.36-1.17). We found discordant results regarding the association between SCA/VA with saxagliptin compared with sitagliptin in two independent datasets. It remains unclear whether these findings are due to heterogeneity of treatment effect in the different populations, chance, or unmeasured confounding.

Evaluation of COVID-19 Testing Strategies for Repopulating College and University Campuses: A Decision Tree Analysis

PURPOSE

The optimal approach to identify SARS-CoV-2 infection among college students returning to campus is unknown. Recommendations vary from no testing to two tests per student. This research determined the strategy that optimizes the number of true positives and negatives detected and reverse transcription polymerase chain reaction (RT-PCR) tests needed.

METHODS

A decision tree analysis evaluated five strategies: (1) classifying students with symptoms as having COVID-19, (2) RT-PCR testing for symptomatic students, (3) RT-PCR testing for all students, (4) RT-PCR testing for all students and retesting symptomatic students with a negative first test, and (5) RT-PCR testing for all students and retesting all students with a negative first test. The number of true positives, true negatives, RT-PCR tests, and RT-PCR tests per true positive (TTP) was calculated.

RESULTS

Strategy 5 detected the most true positives but also required the most tests. The percentage of correctly identified infections was 40.6%, 29.0%, 53.7%, 72.5%, and 86.9% for Strategies 1-5, respectively. All RT-PCR strategies detected more true negatives than the symptom-only strategy. Analysis of TTP demonstrated that the repeat RT-PCR strategies weakly dominated the single RT-PCR strategy and that the thresholds for more intensive RT-PCR testing decreased as the prevalence of infection increased.

CONCLUSION

Based on TTP, the single RT-PCR strategy is never preferred. If the cost of RT-PCR testing is of concern, a staged approach involving initial testing of all returning students followed by a repeat testing decision based on the measured prevalence of infection might be considered.

Risk factors for 30-day readmission in adults hospitalized for pulmonary hypertension

Readmissions for pulmonary hypertension are poorly understood and understudied. We sought to determine national estimates and risk factors for 30-day readmission after pulmonary hypertension-related hospitalizations. We utilized the Healthcare Cost and Utilization Project Nationwide Readmission Database, which has weighted estimates of roughly 35 million discharges in the US. Adult patients with primary International Classification of Disease, Ninth Revision, Clinical Modification diagnosis codes of 416.0 and 416.8 for primary and secondary pulmonary hypertension with an index admission between 2012 and 2014 and any readmission within 30 days of the index event were identified. Predictors of 30-day readmission were identified using multivariable logistic regression with adjustment for covariates. Results showed that the national estimate for Primary Pulmonary Hypertension vs Secondary Pulmonary Hypertension-related index events between 2012 and 2014 with 30-day readmission was 247 vs 2550 corresponding to a national readmission risk estimate of 17% vs 18.3%, respectively. The presence of fluid and electrolyte disorders, renal failure, and alcohol abuse were associated with increased risk of readmission in Primary Pulmonary Hypertension, while factors associated with Secondary Pulmonary Hypertension readmissions included anemia, congestive heart failure, lung disease, fluid and electrolyte disorders, renal failure, diabetes, and liver disease. The median cost of Primary Pulmonary Hypertension admissions and readmissions were $46,132 (IQR: $25,384–$85,647) and $41,604.50 (IQR: $22,481.50–$84,420.50), respectively. The median costs of Secondary Pulmonary Hypertension admissions and readmissions were $34,893 (IQR: $19,670–$66,143) and $36,279 (IQR: $19,059–$74,679), respectively. In conclusion, approximately 19% of Primary Pulmonary Hypertension and Secondary Pulmonary Hypertension hospitalizations result in 30-day readmission, with significant costs accrued during the index hospitalization and readmission. With evolving clinical terminology and diagnostic codes, future study will need to better clarify underlying factors associated with readmissions amongst pulmonary hypertension sub-types, and identify methods and procedures to minimize readmission risk.

COVID-19 Clinical Trials: A Teachable Moment for Improving Our Research Infrastructure and Relevance

The authors posit the need for rapid evaluation of therapies for COVID-19 as an inflection point spurring a much-needed rethinking of our research enterprise.

Testing small study effects in multivariate meta-analysis

Small study effects occur when smaller studies show different, often larger, treatment effects than large ones, which may threaten the validity of systematic reviews and meta-analyses. The most well-known reasons for small study effects include publication bias, outcome reporting bias, and clinical heterogeneity. Methods to account for small study effects in univariate meta-analysis have been extensively studied. However, detecting small study effects in a multivariate meta-analysis setting remains an untouched research area. One of the complications is that different types of selection processes can be involved in the reporting of multivariate outcomes. For example, some studies may be completely unpublished while others may selectively report multiple outcomes. In this paper, we propose a score test as an overall test of small study effects in multivariate meta-analysis. Two detailed case studies are given to demonstrate the advantage of the proposed test over various naive applications of univariate tests in practice. Through simulation studies, the proposed test is found to retain nominal Type I error rates with considerable power in moderate sample size settings. Finally, we also evaluate the concordance between the proposed tests with the naive application of univariate tests by evaluating 44 systematic reviews with multiple outcomes from the Cochrane Database.

The Galaxy Plot: A New Visualization Tool for Bivariate Meta-Analysis Studies

Funnel plots have been widely used to detect small-study effects in the results of univariate meta-analyses. However, there is no existing visualization tool that is the counterpart of the funnel plot in the multivariate setting. We propose a new visualization method, the galaxy plot, which can simultaneously present the effect sizes of bivariate outcomes and their standard errors in a 2-dimensional space. We illustrate the use of the galaxy plot with 2 case studies, including a meta-analysis of hypertension trials with studies from 1979-1991 (Hypertension. 2005;45(5):907-913) and a meta-analysis of structured telephone support or noninvasive telemonitoring with studies from 1966-2015 (Heart. 2017;103(4):255-257). The galaxy plot is an intuitive visualization tool that can aid in interpreting results of multivariate meta-analysis. It preserves all of the information presented by separate funnel plots for each outcome while elucidating more complex features that may only be revealed by examining the joint distribution of the bivariate outcomes.

A population-based study of risk factors for heart failure in pediatric and adult-onset systemic lupus erythematosus

OBJECTIVES

The increased relative risk of heart failure (HF) from systemic lupus erythematosus (SLE) is greatest at younger ages, but the etiology remains unclear. We identified risk factors for HF in children and adults with SLE and evaluated associations between SLE manifestations and HF.

METHODS

Incident SLE cases without preceding HF were identified using Clinformatics DataMart® (OptumInsight, Eden Prairie, MN) US claims data (2000-2015), and categorized by age of SLE onset (children 5-17, young adults 18-24, adults 25-44 years old). The primary outcome was the first HF ICD-9-CM diagnosis code (428.x), categorized as early-onset (< 6 months) or delayed-onset. Multivariable logistic regression was used to identify factors associated with early or delayed-onset HF. Cox proportional hazards regression was used to identify time-dependent associations between the onset of SLE manifestations and incident HF.

RESULTS

There were 523 (2.3%) HF cases among 1,466 children, 2,163 young adults and 19,349 adults age 25-44 with SLE. HF in children and young adults was early-onset in 50% and 60% of cases, respectively, compared to 35% of cases in adults 25-44 years old. There was a temporal association between incident myopericarditis and valvular disease diagnoses and early-onset HF, whereas nephritis and hypertension were more strongly associated with delayed-onset HF. Black race remained independently associated with a 1.5-fold increased HF risk at any time.

CONCLUSION

Hypertension remains an important traditional CV risk factor across all ages and should be managed aggressively even in younger patients with SLE. Cardiac dysfunction due to acute cardiac manifestations of SLE may contribute to the very high relative incidence of early HF diagnoses among younger SLE patients. Therefore, future prospective studies will need to address heterogeneity in the types and severity of heart failure in order to determine etiology and which patients should be monitored.

Development and Validation of a Seizure Prediction Model in Neonates After Cardiac Surgery

BACKGROUND

Electroencephalographic seizures (ESs) after neonatal cardiac surgery are often subclinical and have been associated with poor outcomes. An accurate ES prediction model could allow targeted continuous electroencephalographic monitoring (CEEG) for high-risk neonates.

METHODS

ES prediction models were developed and validated in a multicenter prospective cohort where all postoperative neonates who underwent cardiopulmonary bypass (CPB) also underwent CEEG.

RESULTS

ESs occurred in 7.4% of neonates (78 of 1053). Model predictors included gestational age, head circumference, single-ventricle defect, deep hypothermic circulatory arrest duration, cardiac arrest, nitric oxide, extracorporeal membrane oxygenation, and delayed sternal closure. The model performed well in the derivation cohort (c-statistic, 0.77; Hosmer-Lemeshow, P = .56), with a net benefit (NB) over monitoring all and none over a threshold probability of 2% in decision curve analysis (DCA). The model had good calibration in the validation cohort (Hosmer-Lemeshow, P = .60); however, discrimination was poor (c-statistic, 0.61), and in DCA there was no NB of the prediction model between the threshold probabilities of 8% and 18%. By using a cut point that emphasized negative predictive value in the derivation cohort, 32% (236 of 737) of neonates would not undergo CEEG, including 3.5% (2 of 58) of neonates with ESs (negative predictive value, 99%; sensitivity, 97%).

CONCLUSIONS

In this large prospective cohort, a prediction model of ESs in neonates after CPB had good performance in the derivation cohort, with an NB in DCA. However, performance in the validation cohort was weak, with poor discrimination, poor calibration, and no NB in DCA. These findings support CEEG of all neonates after CPB.

Genetic Factors Influencing Warfarin Dose in Black-African Patients: A Systematic Review and Meta-Analysis

Warfarin is the most commonly used oral anticoagulant in sub-Saharan Africa. Dosing is challenging due to a narrow therapeutic index and high interindividual variability in dose requirements. To evaluate the genetic factors affecting warfarin dosing in black-Africans, we performed a meta-analysis of 48 studies (2,336 patients). Significant predictors for CYP2C9 and stable dose included rs1799853 (CYP2C9*2), rs1057910 (CYP2C9*3), rs28371686 (CYP2C9*5), rs9332131 (CYP2C9*6), and rs28371685 (CYP2C9*11) reducing dose by 6.8, 12.5, 13.4, 8.1, and 5.3 mg/week, respectively. VKORC1 variants rs9923231 (-1639G>A), rs9934438 (1173C>T), rs2359612 (2255C>T), rs8050894 (1542G>C), and rs2884737 (497T>G) decreased dose by 18.1, 21.6, 17.3, 11.7, and 19.6 mg/week, respectively, whereas rs7294 (3730G>A) increased dose by 6.9 mg/week. Finally, rs12777823 (CYP2C gene cluster) was associated with a dose reduction of 12.7 mg/week. Few studies were conducted in Africa, and patient numbers were small, highlighting the need for further work in black-Africans to evaluate genetic factors determining warfarin response.

A behavioral economics-based telehealth intervention to improve aspirin adherence following hospitalization for acute coronary syndrome

PURPOSE

A significant number of patients with acute coronary syndrome (ACS) are nonadherent to aspirin after hospital discharge, with an associated increased risk of subsequent cardiovascular events. The purpose of this pilot study was to test the efficacy of a telehealth intervention based on behavioral economics to improve aspirin adherence following hospitalization for ACS.

METHODS

We enrolled 130 participants (c¯X = 58 ± 10.7 years of age, 38% female, 45% black) from two hospitals. Patients were eligible if they owned a smartphone and were admitted to the hospital for ACS, prescribed aspirin at discharge, and responsible for administering their own medications. Consenting participants were randomized to the intervention or usual care group. The intervention group was eligible to receive up to $50 per month if they took their medicine daily, with $2 per day deducted if a dose was missed. All participants received an electronic monitoring (EM) pill bottle containing a 90-day supply of aspirin, which was used to measure adherence calculated as the proportion of prescribed drug taken using the EM device. Based on the skewness in the adherence distribution, quantile regression was used to evaluate the effect of the intervention on median adherence over time.

RESULTS

After 90 days, adherence fell in the control group but remained high in the intervention group (median adherence 81% vs 90%, P = .18). Rehospitalization was higher in the control group (24% vs 13%, P = .17).

CONCLUSION

A loss aversion behavioral economics-based telehealth intervention is a promising approach to improving aspirin adherence following hospitalization for ACS.

Pharmacoepidemiologic Screening of Potential Oral Anticoagulant Drug Interactions Leading to Thromboembolic Events

Drug-drug interactions (DDIs) with oral anticoagulants may lead to under-anticoagulation and increased risk of thromboembolism. Although warfarin is susceptible to numerous DDIs, few studies have examined DDIs resulting in thromboembolism or those involving direct-acting oral anticoagulants (DOACs). We aimed to identify medications that increase the rate of hospitalization for thromboembolic events when taken concomitantly with oral anticoagulants. We conducted a high-throughput pharmacoepidemiologic screening study using Optum Clinformatics Data Mart, 2000-2016. We performed self-controlled case series studies among adult users of oral anticoagulants (warfarin, dabigatran, rivaroxaban, apixaban, and edoxaban) with at least one hospitalization for a thromboembolic event. Among eligible patients, we identified all oral medications frequently co-prescribed with oral anticoagulants as potential interacting precipitants. Conditional Poisson regression was used to estimate rate ratios comparing precipitant exposed vs. unexposed time for each anticoagulant-precipitant pair. To minimize within-person confounding by indication for the precipitant, we used pravastatin as a negative control object drug. Multiple estimation was adjusted using semi-Bayes shrinkage. We screened 1,622 oral anticoagulant-precipitant drug pairs and identified 226 (14%) drug pairs associated with statistically significantly elevated risk of thromboembolism. Using pravastatin as the negative control object drug, this list was reduced to 69 potential DDI signals for thromboembolism, 33 (48%) of which were not documented in the DDI knowledge databases Lexicomp and/or Micromedex. There were more DDI signals associated with warfarin than DOACs. This study reproduced several previously documented oral anticoagulant DDIs and identified potential DDI signals that deserve to be examined in future etiologic studies.

The risk of sudden cardiac arrest and ventricular arrhythmia with rosiglitazone versus pioglitazone: real-world evidence on thiazolidinedione safety

BACKGROUND

The low cost of thiazolidinediones makes them a potentially valuable therapeutic option for the > 300 million economically disadvantaged persons worldwide with type 2 diabetes mellitus. Differential selectivity of thiazolidinediones for peroxisome proliferator-activated receptors in the myocardium may lead to disparate arrhythmogenic effects. We examined real-world effects of thiazolidinediones on outpatient-originating sudden cardiac arrest (SCA) and ventricular arrhythmia (VA).

METHODS

We conducted population-based high-dimensional propensity score-matched cohort studies in five Medicaid programs (California, Florida, New York, Ohio, Pennsylvania | 1999-2012) and a commercial health insurance plan (Optum Clinformatics | 2000-2016). We defined exposure based on incident rosiglitazone or pioglitazone dispensings; the latter served as an active comparator. We controlled for confounding by matching exposure groups on propensity score, informed by baseline covariates identified via a data adaptive approach. We ascertained SCA/VA outcomes precipitating hospital presentation using a validated, diagnosis-based algorithm. We generated marginal hazard ratios (HRs) via Cox proportional hazards regression that accounted for clustering within matched pairs. We prespecified Medicaid and Optum findings as primary and secondary, respectively; the latter served as a conceptual replication dataset.

RESULTS

The adjusted HR for SCA/VA among rosiglitazone (vs. pioglitazone) users was 0.91 (0.75-1.10) in Medicaid and 0.88 (0.61-1.28) in Optum. Among Medicaid but not Optum enrollees, we found treatment effect heterogeneity by sex (adjusted HRs = 0.71 [0.54-0.93] and 1.16 [0.89-1.52] in men and women respectively, interaction term p-value = 0.01).

CONCLUSIONS

Rosiglitazone and pioglitazone appear to be associated with similar risks of SCA/VA.

Predictive risk stratification using HEART (history, electrocardiogram, age, risk factors, and initial troponin) and TIMI (thrombolysis in myocardial infarction) scores in non-high risk chest pain patients: An African American urban community based hospital study

Validated risk scoring systems in African American (AA) population are under studied. We utilized history, electrocardiogram, age, risk factors, and initial troponin (HEART) and thrombolysis in myocardial infarction (TIMI) scores to predict major adverse cardiovascular events (MACE) in non-high cardiovascular (CV) risk predominantly AA patient population.A retrospective emergency department (ED) charts review of 1266 chest pain patients where HEART and TIMI scores were calculated for each patient. Logistic regression model was computed to predict 6-week and 1-year MACE and 90-day cardiac readmission. Decision curve analysis (DCA) was constructed to differentiate between clinical strategies in non-high CV risk patients.Of the 817 patients included, 500 patients had low HEART score vs. 317 patients who had moderate HEART score. Six hundred sixty-three patients had low TIMI score vs. 154 patients had high TIMI score. The univariate logistic regression model shows odds ratio of predicting 6-week MACE using HEART score was 3.11 (95% confidence interval [CI] 1.43-6.76, P = .004) with increase in risk category from low to moderate vs. 2.07 (95% CI 1.18-3.63, P = .011) using TIMI score with increase in risk category from low to high and c-statistic of 0.86 vs. 0.79, respectively. DCA showed net benefit of using HEART score is equally predictive of 6-week MACE when compared to TIMI.In non-high CV risk AA patients, HEART score is better predictive tool for 6-week MACE when compared to TIMI score. Furthermore, patients presenting to ED with chest pain, the optimal strategy for a 2% to 4% miss rate threshold probability should be to discharge these patients from the ED.

Development and Initial Validation of the PROMIS®-Plus-HF Profile Measure

Background Bringing together generic and heart failure (HF)-specific items in a publicly available, patient-reported outcome measure may facilitate routine health status assessment for improving clinical care and shared decision-making, assessing quality of care, evaluating new interventions, and comparing groups with different conditions. Methods and Results We performed a mixed-methods study to develop and validate the PROMIS®-Plus-HF (Patient-Reported Outcomes Measurement Information System®-Plus-Heart Failure) profile measure-a HF-specific instrument based on the generic PROMIS. We conducted 8 focus groups with 61 patients with HF and phone interviews with 10 HF clinicians. The measure was developed via an iterative process of reviewing existing PROMIS items and developing and testing new HF items. In a 600-patient sample, we estimated reliability (internal consistency; test-retest, with n=100 participants). We conducted validity analyses using Pearson r and Spearman ρ correlations with Kansas City Cardiomyopathy Questionnaire subscores. In a longitudinal sample, we performed responsiveness testing (paired t tests) with 75 patients with HF receiving interventions with expected health status improvement. The PROMIS-Plus-HF measure comprises 86 items (64 existing; 22 new) across 18 domains. Internal consistency reliability (Cronbach α) coefficients ranged from 0.52 to 0.96, with α≥0.70 in 12 of 17 domains. Test-retest intraclass correlation coefficients were ≥0.90. Correlations with Kansas City Cardiomyopathy Questionnaire subscores supported expected convergent ( r/ρ>0.60) and divergent validity ( r/ρ<0.30). In the longitudinal sample, 10 of 18 domains had improved ( P<0.05) scores from baseline to follow-up. Conclusions The PROMIS-Plus-HF profile measure-a complete assessment of physical, mental, and social health-exhibited good psychometric characteristics and may facilitate patient-centered care and research. Subsets of domains and items can be used depending on the clinical or research purpose.

Abstract 101: The Development and Initial Validation of PROMIS-Plus-HF Profile Measure

Background: Bringing together generic and heart failure (HF)-specific items in a publicly-available, patient-reported outcome measure may facilitate better health status comparisons across groups and within individuals longitudinally in learning health systems and clinical research studies.

Methods and Results: We performed a mixed-methods study to develop and validate the PROMIS ® -Plus-HF profile measure, a HF-specific instrument based on the generic The Patient-Reported Outcomes Measurement Information System (PROMIS). We conducted eight focus groups with 61 HF patients and phone interviews with 10 HF clinicians. The measure was developed via an iterative process of reviewing existing PROMIS items and developing and testing new HF items. In 600-patient sample, we estimated reliability (internal consistency; test-retest, with n=100 participants). We conducted validity analyses using Pearson r and Spearman rho correlations with Kansas City Cardiomyopathy Questionnaire (KCCQ) subscores. In a longitudinal sample, we performed responsiveness testing (paired t-tests) with 75 HF patients receiving interventions with expected health status improvement. The PROMIS-Plus-HF measure comprises 86 items (64 existing; 22 new) across 18 domains. Internal consistency reliability (Cronbach’s alpha) coefficients ranged from 0.52-0.96, with alpha≥0.70 in 12/17 domains. Test-retest intraclass correlation coefficients were ≥0.90. Correlations with KCCQ subscores supported expected convergent ( r/rho >0.60) and divergent validity ( r/rho <0.30). In the longitudinal sample, 10/18 domains had improved (P<0.05) scores from baseline to follow-up.

Conclusions: The PROMIS-Plus-HF profile measure—a complete assessment of physical, mental, and social health—exhibited good psychometric characteristics and may facilitate patient-centered care and research. Subsets of domains, or the entire measure, can be used, depending on the clinical or research purpose.

Incorporating patient-centered factors into heart failure readmission risk prediction: A mixed-methods study

BACKGROUND

Capturing and incorporating patient-centered factors into 30-day readmission risk prediction after hospitalized heart failure (HF) could improve the modest performance of current models.

METHODS

Using a mixed-methods approach, we developed a patient-centered survey and evaluated the additional predictive utility of the survey compared to a traditional readmission risk model (the Krumholz et al. model). Area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow goodness-of-fit statistic quantified the performance of both models. We measured the amount of model improvement with the addition of patient-centered factors to the Krumholz et al. model with the integrated discrimination improvement (IDI). In an exploratory analysis, we used hierarchical clustering algorithms to identify groups with similar survey responses and tested for differences between clusters using standard descriptive statistics.

RESULTS

From 3/24/2014 to 3/12/2015, 183 patients hospitalized with HF were enrolled from an urban, academic health system and followed for 30days after discharge. The Krumholz et al. plus patient-centered factors model had similar-to-slightly lower performance (AUC [95%CI]:0.62 [0.52, 0.71]; goodness-of-fit P=.10) than the Krumholz et al. model (AUC [95%CI]:0.66 [0.57, 0.76]; goodness-of-fit P=.19). The IDI (95%CI) was 0.003 (-0.014,0.020). We identified three patient clusters based on patient-centered survey responses. The clusters differed with respect to gender, self-rated health, employment status, and prior hospitalization frequency (all P<.05).

CONCLUSIONS

The addition of patient-centered factors did not improve 30-day readmission model performance. Rather than designing interventions based on predicted readmission risk, tailoring interventions to all patients, based on their characteristics, could inform the design of targeted, readmission reduction strategies.

Sustained Posttransplantation Diabetes Is Associated With Long-Term Major Cardiovascular Events Following Liver Transplantation

Cardiovascular disease is a leading cause of death among liver transplant (LT) recipients. With a rising burden of posttransplantation metabolic disease, increases in cardiovascular-related morbidity and mortality may reduce life expectancy after LT. It is unknown if the risk of long-term major cardiovascular events (MCEs) differs among LT recipients with varying diabetic states. We performed a retrospective cohort study of LT recipients from 2003 through 2013 to compare the incidence of MCEs among patients (1) without diabetes, (2) with pretransplantation diabetes, (3) with de novo transient posttransplantation diabetes, and (4) with de novo sustained posttransplantation diabetes. We analyzed 994 eligible patients (39% without diabetes, 24% with pretransplantation diabetes, 16% with transient posttransplantation diabetes, and 20% with sustained posttransplantation diabetes). Median follow-up was 54.7 months. Overall, 12% of patients experienced a MCE. After adjustment for demographic and clinical variables, sustained posttransplantation diabetes was the only state associated with a significantly increased risk of MCEs (subdistribution hazard ratio 1.95, 95% confidence interval 1.20-3.18). Patients with sustained posttransplantation diabetes mellitus had a 13% and 27% cumulative incidence of MCEs at 5 and 10 years, respectively. While pretransplantation diabetes has traditionally been associated with cardiovascular disease, the long-term risk of MCEs is greatest in LT recipients with sustained posttransplantation diabetes mellitus.

Thromboembolic and neurologic sequelae of discontinuation of an antihyperlipidemic drug during ongoing warfarin therapy

Warfarin and antihyperlipidemics are commonly co-prescribed. Some antihyperlipidemics may inhibit warfarin deactivation via the hepatic cytochrome P450 system. Therefore, antihyperlipidemic discontinuation has been hypothesized to result in underanticoagulation, as warfarin metabolism is no longer inhibited. We quantified the risk of venous thromboembolism (VTE) and ischemic stroke (IS) due to statin and fibrate discontinuation in warfarin users, in which warfarin was initially dose-titrated during ongoing antihyperlipidemic therapy. Using 1999-2011 United States Medicaid claims among 69 million beneficiaries, we conducted a set of bidirectional self-controlled case series studies-one for each antihyperlipidemic. Outcomes were hospital admissions for VTE/IS. The risk segment was a maximum of 90 days immediately following antihyperlipidemic discontinuation, the exposure of interest. Time-varying confounders were included in conditional Poisson models. We identified 629 study eligible-persons with at least one outcome. Adjusted incidence rate ratios (IRRs) for all antihyperlipidemics studied were consistent with the null, and ranged from 0.21 (0.02, 2.82) for rosuvastatin to 2.16 (0.06, 75.0) for gemfibrozil. Despite using an underlying dataset of millions of persons, we had little precision in estimating IRRs for VTE/IS among warfarin-treated persons discontinuing individual antihyperlipidemics. Further research should investigate whether discontinuation of gemfibrozil in warfarin users results in serious underanticoagulation.

Multisite Investigation of Outcomes With Implementation of CYP2C19 Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention

OBJECTIVES

This multicenter pragmatic investigation assessed outcomes following clinical implementation of CYP2C19 genotype-guided antiplatelet therapy after percutaneous coronary intervention (PCI).

BACKGROUND

CYP2C19 loss-of-function alleles impair clopidogrel effectiveness after PCI.

METHODS

After clinical genotyping, each institution recommended alternative antiplatelet therapy (prasugrel, ticagrelor) in PCI patients with a loss-of-function allele. Major adverse cardiovascular events (defined as myocardial infarction, stroke, or death) within 12 months of PCI were compared between patients with a loss-of-function allele prescribed clopidogrel versus alternative therapy. Risk was also compared between patients without a loss-of-function allele and loss-of-function allele carriers prescribed alternative therapy. Cox regression was performed, adjusting for group differences with inverse probability of treatment weights.

RESULTS

Among 1,815 patients, 572 (31.5%) had a loss-of-function allele. The risk for major adverse cardiovascular events was significantly higher in patients with a loss-of-function allele prescribed clopidogrel versus alternative therapy (23.4 vs. 8.7 per 100 patient-years; adjusted hazard ratio: 2.26; 95% confidence interval: 1.18 to 4.32; p = 0.013). Similar results were observed among 1,210 patients with acute coronary syndromes at the time of PCI (adjusted hazard ratio: 2.87; 95% confidence interval: 1.35 to 6.09; p = 0.013). There was no difference in major adverse cardiovascular events between patients without a loss-of-function allele and loss-of-function allele carriers prescribed alternative therapy (adjusted hazard ratio: 1.14; 95% confidence interval: 0.69 to 1.88; p = 0.60).

CONCLUSIONS

These data from real-world observations demonstrate a higher risk for cardiovascular events in patients with a CYP2C19 loss-of-function allele if clopidogrel versus alternative therapy is prescribed. A future randomized study of genotype-guided antiplatelet therapy may be of value.

Palliative Care in Heart Failure: Rationale, Evidence, and Future Priorities

Patients with heart failure (HF) and their families experience stress and suffering from a variety of sources over the course of the HF experience. Palliative care is an interdisciplinary service and an overall approach to care that improves quality of life and alleviates suffering for those living with serious illness, regardless of prognosis. In this review, we synthesize the evidence from randomized clinical trials of palliative care interventions in HF. While the evidence base for palliative care in HF is promising, it is still in its infancy and requires additional high-quality, methodologically sound studies to clearly elucidate the role of palliative care for patients and families living with the burdens of HF. Yet, an increase in attention to primary palliative care (e.g., basic physical and emotional symptom management, advance care planning), provided by primary care and cardiology clinicians, may be a vehicle to address unmet palliative needs earlier and throughout the illness course.

Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group

Purpose

Implementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing GeNomics In PracTicE (IGNITE) Network’s efforts to promote: 1) a broader understanding of genomic medicine implementation research; and 2) the sharing of knowledge generated in the network.

Methods

To facilitate this goal the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide their approach to: identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross network analyses.

Results

CMG identified ten high-priority CFIR constructs as important for genomic medicine. Of those, eight didn’t have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.

Conclusion

We developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

Association Between Patient-Reported Medication Adherence and Anticoagulation Control

BACKGROUND

The prevention of thromboembolism events remains challenging in cases of poor medication adherence. Unfortunately, clinical prediction of future adherence has been suboptimal. The objective of this study was to examine the correlation between 2 measures of real-time, self-reported adherence and anticoagulation control.

METHODS

The IN-RANGE2 cohort recruited patients initiating warfarin therapy in 3 urban anticoagulation clinics. At each study visit, participants reported adherence using a 100-point visual analogue scale (VAS, marking percentage of pills taken since prior visit on a linear scale) and 7-day recall of pill-taking behavior. Anticoagulation control was measured by between-visit percent time in international normalized ratio range (BVTR), dichotomized at the cohort median. The longitudinal association between adherence and anticoagulation control was estimated using generalized estimating equations, controlling for clinical and demographic characteristics, prior BVTR, and warfarin dose changes.

RESULTS

Among 598 participants with 3204 (median 4) visits, the median BVTR was 36.8% (interquartile range 0%-73.9%). Participants reported ≤80% adherence in 182 visits (5.7%) and missed pills in the past 7 days in 377 visits (11.8%). Multivariable regression analysis found poorer anticoagulation control (BVTR <36.8%) in those with a VAS ≤80% (odds ratio 1.89; 95% confidence interval, 1.12-3.18; P = .02) and self-reported change in adherence since last visit (odds ratio 1.55; 95% confidence interval, 1.20-2.01; P = .001).

CONCLUSION

Self-reported VAS medication adherence at a clinic visit and changes in reported adherence since the last visit are independently associated with BVTR. Clinicians may gain additional insight into patients' medication adherence by incorporating this information into patient management.

Influence of common and rare genetic variation on warfarin dose among African-Americans and European-Americans using the exome array

AIM

We conducted a genome-wide association study using the Illumina Exome Array to identify coding SNPs that may explain additional warfarin dose variability.

PATIENTS & METHODS

Analysis was performed after adjustment for clinical variables and genetic factors known to influence warfarin dose among 1680 warfarin users (838 European-Americans and 842 African-Americans). Replication was performed in an independent sample.

RESULTS

We confirmed the influence of known genetic variants on warfarin dose variability. Our study is the first to show the association between rs12772169 and warfarin dose in African-Americans. In addition, genes COX15 and FGF5 showed significant association in European-Americans.

CONCLUSION

We identified some novel genes/SNPs that underpin warfarin dose response. Further replication is needed to confirm our findings.

Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Pharmacogenetics-Guided Warfarin Dosing: 2017 Update

This document is an update to the 2011 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2C9 and VKORC1 genotypes and warfarin dosing. Evidence from the published literature is presented for CYP2C9, VKORC1, CYP4F2, and rs12777823 genotype-guided warfarin dosing to achieve a target international normalized ratio of 2-3 when clinical genotype results are available. In addition, this updated guideline incorporates recommendations for adult and pediatric patients that are specific to continental ancestry.

Abstract 260: A Qualitative Study of Patient-reported Challenges to Heart Failure Home Management

Background: Patients with heart failure (HF) have high 30-day hospital readmission rates. Interventions designed to prevent readmissions have had mixed success. Viewing HF home management through the lens of a patient’s experience may reframe the readmission “problem” and inform a range of alternative strategies.

Methods: We conducted open-ended, semi-structured interviews with HF patients who had a 30-day readmission or had been discharged in the past month. Data were analyzed using a grounded theory approach. The purpose of the interviews was to understand the challenges to home HF management and the perceived reasons for readmission.

Results: Face-to-face interviews with 31 patients, 16 (52%) with a 30-day readmission, revealed a combination of physical and socio-emotional influences on patients’ home management. Major themes related to readmission included symptom management, adherence vs adaptation, and emotional reactions. While patients reported symptom management as the leading reason for readmission, addressing symptoms was more complex than following recommendations. Patients identified an uncertainty regarding recommendations, caused by unclear instructions and temporal incongruence between behavior and symptom onset, as a factor that impaired their competence in making routine management decisions and resulted in a cycle of limit testing. Patients reported adapting —rather than strictly adhering to— recommendations to accommodate their emotional needs, socio-economic constraints, and comorbidities. For some, the onset of a distressing constellation of symptoms led to a cycle of despair characterized by fear and hopelessness, with the hospital being viewed as the safest place for recovery (see Figure 1).

Conclusion: Anticipatory guidance regarding challenges to adherence may reduce uncertainty, but is likely insufficient. Early palliative care referral may help mitigate distressing symptoms, and address extreme emotions, perhaps forestalling premature readmission.

Postauthorization safety study of the DPP-4 inhibitor saxagliptin: a large-scale multinational family of cohort studies of five outcomes

OBJECTIVE

To evaluate the risk of serious adverse events among patients with type 2 diabetes mellitus initiating saxagliptin compared with oral antidiabetic drugs (OADs) in classes other than dipeptidyl peptidase-4 (DPP-4) inhibitors.

RESEARCH DESIGN AND METHODS

Cohort studies using 2009-2014 data from two UK medical record data sources (Clinical Practice Research Datalink, The Health Improvement Network) and two USA claims-based data sources (HealthCore Integrated Research Database, Medicare). All eligible adult patients newly prescribed saxagliptin (n=110 740) and random samples of up to 10 matched initiators of non-DPP-4 inhibitor OADs within each data source were selected (n=913 384). Outcomes were hospitalized major adverse cardiovascular events (MACE), acute kidney injury (AKI), acute liver failure (ALF), infections, and severe hypersensitivity events, evaluated using diagnostic coding algorithms and medical records. Cox regression was used to determine HRs with 95% CIs for each outcome. Meta-analyses across data sources were performed for each outcome as feasible.

RESULTS

There were no increased incidence rates or risk of MACE, AKI, ALF, infection, or severe hypersensitivity reactions among saxagliptin initiators compared with other OAD initiators within any data source. Meta-analyses demonstrated a reduced risk of hospitalization/death from MACE (HR 0.91, 95% CI 0.85 to 0.97) and no increased risk of hospitalization for infection (HR 0.97, 95% CI 0.93 to 1.02) or AKI (HR 0.99, 95% CI 0.88 to 1.11) associated with saxagliptin initiation. ALF and hypersensitivity events were too rare to permit meta-analysis.

CONCLUSIONS

Saxagliptin initiation was not associated with increased risk of MACE, infection, AKI, ALF, or severe hypersensitivity reactions in clinical practice settings.

TRIAL REGISTRATION NUMBER

NCT01086280, NCT01086293, NCT01086319, NCT01086306, and NCT01377935; Results.

Gastrointestinal bleeding and intracranial hemorrhage in concomitant users of warfarin and antihyperlipidemics

BACKGROUND

Drug interactions, particularly those involving warfarin, are a major clinical and public health problem. Minimizing serious bleeding caused by anticoagulants is a recent major focus of the United States (US) Department of Health and Human Services. This study quantified the risk of gastrointestinal bleeding (GIB) and intracranial hemorrhage (ICH) among concomitant users of warfarin and individual antihyperlipidemics.

METHODS

The authors conducted a high-dimensional propensity score-adjusted cohort study of new concomitant users of warfarin and an antihyperlipidemic, among US Medicaid beneficiaries from five states during 1999-2011. Exposure was defined by concomitant use of warfarin plus one of eight antihyperlipidemics. The primary outcome measure was a composite of GIB/ICH within the first 30days of concomitant use. As a secondary outcome measure, GIB/ICH was examined within the first 180days of concomitant use.

RESULTS

Among 236,691 persons newly-exposed to warfarin and an antihyperlipidemic, the crude incidence of GIB/ICH was 13.2 (95% confidence interval 12.7 to 13.8) per 100person-years. Users were predominantly older, female, and Caucasian. Adjusted hazard ratios (aHRs) for warfarin and individual statins were consistent with no association. Warfarin+gemfibrozil was associated with an 80% increased risk of GIB/ICH within the first month of concomitant use (aHR=1.8, 1.4 to 2.4). Warfarin+fenofibrate was associated with a similar increased risk (aHR=1.8, 1.2 to 2.7), yet with an onset during the second month of concomitant use.

CONCLUSIONS

Among warfarin-treated persons, the use of fibrates-but not statins-increases the risk of hospital presentation for GIB/ICH.

Comparing the Standard Rating Scale and the Magnifier Scale for Assessing Risk Perceptions

Objective. A new risk perception rating scale (“magnifier scale”) was recently developed to reduce elevated perceptions of low-probability health events, but little is known about its performance. The authors tested whether the magnifier scale lowers risk perceptions for low-probability (in 0%–1% magnifying glass section of scale) but not high-probability (>1%) events compared to a standard rating scale (SRS). Method. In studies 1 (n = 463) and 2 (n = 105), undergraduates completed a survey assessing risk perceptions of high- and low-probability events in a randomized 2X 2 design: in study 1 using the magnifier scale or SRS, numeric risk information provided or not, and in study 2 using the magnifier scale or SRS, high- or low-probability event. In study 3, hypertension patients at the Philadelphia Veterans Affairs hospital completed a similar survey (n = 222) assessing risk perceptions of 2 self-relevant high-probability events—heart attack and stroke—with the magnifier scale or the SRS. Results. In study 1, when no risk information was provided, risk perceptions for both high- and low-probability events were significantly lower (P < 0.0001) when using the magnifier scale compared to the SRS, but risk perceptions were no different by scale when risk information was provided (interaction term: P = 0.003). In studies 2 and 3, risk perceptions for the high-probability events were significantly lower using the magnifier scale than the SRS (P = 0.015 and P = 0.014, respectively). Conclusions. The magnifier scale lowered risk perceptions but did so for low- and high-probability events, suggesting that the magnifier scale should not be used for assessments of risk perceptions for high-probability events.

A randomized trial of lottery-based incentives and reminders to improve warfarin adherence: the Warfarin Incentives (WIN2) Trial

BACKGROUND

Previous research has suggested that daily lottery incentives could improve medication adherence. Such daily incentives include implicit reminders. However, the comparative effectiveness of reminders alone versus daily incentives has not been tested.

METHODS

A total of 270 patients on warfarin were enrolled in a four-arm, multi-center, randomized controlled trial comparing a daily lottery-based incentive, a daily reminder, and a combination of the two against a control group (usual care).

RESULTS

Participants in the reminder group had the lowest percentage of time out of target international normalized ratio (INR) range, the primary outcome, with an adjusted odds of an out-of-range INR 36% lower than among those in the control group, 95%CI [7%, 55%]. No other group had a statistically significant improvement in anticoagulation control relative to the control group or to each other. The only group that had significant improvement in incorrect adherence was the lottery group (incorrect adherence: 12.1% compared with 23.7% in the control group, difference of -7.4% 95%CI [-14%, -0.3%]). However, there was no relationship between changes in adherence and anticoagulation control in the lottery group.

CONCLUSIONS

Automated reminders led to the largest improvements in anticoagulation control, although without impacting measured adherence. Lottery-based reminders improved measured adherence but did not lead to improved anticoagulation control. Copyright © 2016 John Wiley & Sons, Ltd.

Trial of a novel prostacyclin analog, UT-15, in patients with severe intermittent claudication

Prostacyclin is an endothelially derived vasodilator and inhibitor of platelet aggregation. Despite its therapeutic potential for peripheral arterial disease, the short half-life and chemical instability are barriers to routine therapy. Accordingly, prostacyclin analogs are being evaluated in patients with peripheral arterial disease. State-of-the-art non-invasive ultrasonography allows for serial testing of the hemodynamic effects of vasoactive drugs. The safety, efficacy and hemodynamic effects of UT-15, a novel, long-acting prostacyclin analog, were studied in patients with severe intermittent claudication. A total of eight patients with stable severe intermittent claudication, Fontaine classes IIb-III, were admitted to the hospital for intravenous infusion of UT-15. A symptom-limited, dose-escalation protocol was instituted, beginning with placebo and then with increasing dosage at 60-min intervals, followed by a 2-h period of maintenance dose at the maximum well-tolerated infusion rate. The hemodynamic response in the lower limbs was assessed with serial ultrasonography, segmental arterial pressures and pulse volumes. Blood flow in the common femoral artery increased 29% (p = 0.003) by the end of the maintenance period and remained above baseline throughout the washout period (p = 0.044). Blood velocity in the lower limb increased in most of the peripheral arteries. These increases achieved statistical significance in the common femoral artery (p = 0.025) and anterior tibial artery (p = 0.019), and approached significance in the popliteal artery (p=0.062). In two of four patients in whom blood flow was undetectable before the infusion, arterial blood flow at the ankle level became apparent on ultrasonography during maintenance infusion. UT-15 infusion improved the pulse volume recording (p = 0.016) but the ankle/brachial index did not change significantly. Common side effects at peak dose included headache and nausea. There were no serious adverse events attributable to UT-15 treatment. In most patients, the optimal infusion rate was 10-20 ng/kg per min. In conclusion, ultrasonography is a novel approach for assessing the hemodynamic response to vasoactive agents. UT-15 is well tolerated when given for up to 2 h and increases arterial blood flow and velocity in patients with severe intermittent claudication.

Physician predictions of length of stay of patients admitted with heart failure

Physicians' ability to predict length of stay is understudied, particularly for patients with heart failure (HF) admissions. The objective of this prospective, observational cohort study was to measure the accuracy of inpatient physicians' predictions of length of stay at the time of admission of patients admitted to an academic tertiary care hospital with HF and to determine whether level of experience improves accuracy. The patients included 165 adults consecutively admitted with heart failure, about whom 415 predictions were made within 24 hours of admission. Mean and median lengths of stay were 10.9 and 8 days, respectively. The mean difference between predicted and actual length of stay was statistically significant for all groups: interns, -5.9 days (95% confidence interval [CI]: -8.2 to -3.6, P < 0.0001); residents, -4.3 days (95% CI: -6.0 to -2.7, P = 0.0001); attending cardiologists, -3.5 days (95% CI: -5.1 to -2.0, P < 0.0001). There were no differences in accuracy by level of experience (P = 0.61). Physicians, regardless of experience, underestimate length of stay of patients admitted with HF. Journal of Hospital Medicine 2016;11:642-645. © 2016 Society of Hospital Medicine.

Predicting prolonged dose titration in patients starting warfarin

PURPOSE

Patients initiating warfarin therapy generally experience a dose-titration period of weeks to months, during which time they are at higher risk of both thromboembolic and bleeding events. Accurate prediction of prolonged dose titration could help clinicians determine which patients might be better treated by alternative anticoagulants that, while more costly, do not require dose titration.

METHODS

A prediction model was derived in a prospective cohort of patients starting warfarin (n = 390), using Cox regression, and validated in an external cohort (n = 663) from a later time period. Prolonged dose titration was defined as a dose-titration period >12 weeks. Predictor variables were selected using a modified best subsets algorithm, using leave-one-out cross-validation to reduce overfitting.

RESULTS

The final model had five variables: warfarin indication, insurance status, number of doctor's visits in the previous year, smoking status, and heart failure. The area under the ROC curve (AUC) in the derivation cohort was 0.66 (95%CI 0.60, 0.74) using leave-one-out cross-validation, but only 0.59 (95%CI 0.54, 0.64) in the external validation cohort, and varied across clinics. Including genetic factors in the model did not improve the area under the ROC curve (0.59; 95%CI 0.54, 0.65). Relative utility curves indicated that the model was unlikely to provide a clinically meaningful benefit compared with no prediction.

CONCLUSIONS

Our results suggest that prolonged dose titration cannot be accurately predicted in warfarin patients using traditional clinical, social, and genetic predictors, and that accurate prediction will need to accommodate heterogeneities across clinical sites and over time. Copyright © 2016 John Wiley & Sons, Ltd.