The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement: Explanation and Elaboration.

The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed to promote the conduct of, and provide guidance for, predictive analyses of heterogeneity of treatment effects (HTE) in clinical trials. The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risk with versus without the intervention, taking into account all relevant patient attributes simultaneously, to support more personalized clinical decision making than can be made on the basis of only an overall average treatment effect. The authors distinguished 2 categories of predictive HTE approaches (a "risk-modeling" and an "effect-modeling" approach) and developed 4 sets of guidance statements: criteria to determine when risk-modeling approaches are likely to identify clinically meaningful HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. They discuss limitations of these methods and enumerate research priorities for advancing methods designed to generate more personalized evidence. This explanation and elaboration document describes the intent and rationale of each recommendation and discusses related analytic considerations, caveats, and reservations.

The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement.

Heterogeneity of treatment effect (HTE) refers to the nonrandom variation in the magnitude or direction of a treatment effect across levels of a covariate, as measured on a selected scale, against a clinical outcome. In randomized controlled trials (RCTs), HTE is typically examined through a subgroup analysis that contrasts effects in groups of patients defined "1 variable at a time" (for example, male vs. female or old vs. young). The authors of this statement present guidance on an alternative approach to HTE analysis, "predictive HTE analysis." The goal of predictive HTE analysis is to provide patient-centered estimates of outcome risks with versus without the intervention, taking into account all relevant patient attributes simultaneously. The PATH (Predictive Approaches to Treatment effect Heterogeneity) Statement was developed using a multidisciplinary technical expert panel, targeted literature reviews, simulations to characterize potential problems with predictive approaches, and a deliberative process engaging the expert panel. The authors distinguish 2 categories of predictive HTE approaches: a "risk-modeling" approach, wherein a multivariable model predicts the risk for an outcome and is applied to disaggregate patients within RCTs to define risk-based variation in benefit, and an "effect-modeling" approach, wherein a model is developed on RCT data by incorporating a term for treatment assignment and interactions between treatment and baseline covariates. Both approaches can be used to predict differential absolute treatment effects, the most relevant scale for clinical decision making. The authors developed 4 sets of guidance: criteria to determine when risk-modeling approaches are likely to identify clinically important HTE, methodological aspects of risk-modeling methods, considerations for translation to clinical practice, and considerations and caveats in the use of effect-modeling approaches. The PATH Statement, together with its explanation and elaboration document, may guide future analyses and reporting of RCTs.

EFFICACY-TO-EFFECTIVENESS CLINICAL TRIALS.

Efficacy trials, which assess treatments in optimally selected patients under advantageous conditions for relatively short time periods, are necessary to gain regulatory approval for marketing. In contrast, effectiveness trials, which test treatments across a spectrum of patients in real-world conditions with follow-up periods that match typical treatment regimens, provide critical information on drug effects in those patients who may ultimately receive the treatment. We previously proposed a study design that integrates efficacy and effectiveness trials into a 2-component "efficacy-to-effectiveness (E2E) trial," in which if the initial efficacy trial component is positive, then the trial immediately and seamlessly transitions to the effectiveness trial component. However, we believe that total study duration could be even further shortened by simultaneously addressing efficacy and effectiveness too (EE2). An EE2 trial rigorously demonstrates efficacy, but uses broad inclusion characteristics of effectiveness trials. An example of a study using EE2 design, the IMMEDIATE (Immediate Myocardial Metabolic enhancement During Initial Assessment and Treatment in Emergency Care) trial, is provided.

Infarct size, left ventricular function, and prognosis in women compared to men after primary percutaneous coronary intervention in ST-segment elevation myocardial infarction: results from an individual patient-level pooled analysis of 10 randomized trials.

AIM: Studies have reported less favourable outcomes in women compared with men after primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI). Whether sex-specific differences in the magnitude or prognostic impact of infarct size or post-infarction cardiac function explain this finding is unknown. METHODS AND RESULTS: We pooled patient-level data from 10 randomized primary PCI trials in which infarct size was measured within 1 month (median 4 days) by either cardiac magnetic resonance imaging or technetium-99m sestamibi single-photon emission computed tomography. We assessed the association between sex, infarct size, and left ventricular ejection fraction (LVEF) and the composite rate of death or heart failure (HF) hospitalization within 1 year. Of 2632 patients with STEMI undergoing primary PCI, 587 (22.3%) were women. Women were older than men and had a longer delay between symptom onset and reperfusion. Infarct size did not significantly differ between women and men, and women had higher LVEF. Nonetheless, women had a higher 1-year rate of death or HF hospitalization compared to men, and while infarct size was a strong independent predictor of 1-year death or HF hospitalization (P < 0.0001), no interaction was present between sex and infarct size or LVEF on the risk of death or HF hospitalization. CONCLUSIONS: In this large-scale, individual patient-level pooled analysis of patients with STEMI undergoing primary PCI, women had a higher 1-year rate of death or HF hospitalization compared to men, a finding not explained by sex-specific differences in the magnitude or prognostic impact of infarct size or by differences in post-infarction cardiac function.

Relationship between therapeutic effects on infarct size in acute myocardial infarction and therapeutic effects on 1-year outcomes: A patient-level analysis of randomized clinical trials.

BACKGROUND: While infarct size in patients with ST-segment elevation myocardial infarction (STEMI) has been generally associated with long-term prognosis, whether a therapeutic effect on infarct size has a corresponding therapeutic effect on long-term outcomes is unknown. METHODS: Using combined patient-level data from 10 randomized trials of primary percutaneous coronary intervention (PCI) for STEMI, we created multivariable Cox proportional hazard models for one-year heart failure hospitalization and all-cause mortality, which included clinical features and a variable representing treatment effect on infarct size. The trials included 2679 participants; infarct size was measured at a median 4 days post infarction. RESULTS: Mean infarct size among the control groups ranged from 16% to 35% of the left ventricle, and from 12% to 36% among treatment groups. There was a significant relationship between treatment effect on infarct size and treatment effect on 1-year heart failure hospitalization (HR 0.85, 95% CI 0.77-0.93, P=.0006), but not on one-year mortality (HR 0.97, 95% CI 0.89-1.06). The treatment effect between infarct size and heart failure hospitalization was stable in sensitivity analyses adjusting for time from STEMI onset to infarct size assessment, and when considering heart failure as the main outcome and death as a competing risk. CONCLUSIONS: We conclude that early treatment-induced effects on infarct size are related in direction and magnitude to treatment effects on heart failure hospitalizations. This finding enables consideration of using infarct size as a valid surrogate outcome measure in assessing new STEMI treatments.

Very early administration of glucose-insulin-potassium by emergency medical service for acute coronary syndromes: Biological mechanisms for benefit in the IMMEDIATE Trial.

AIMS: In the IMMEDIATE Trial, intravenous glucose-insulin-potassium (GIK) was started as early as possible for patients with suspected acute coronary syndrome by ambulance paramedics in communities. In the IMMEDIATE Biological Mechanism Cohort substudy, reported here, we investigated potential modes of GIK action on specific circulating metabolic components. Specific attention was given to suppression of circulating oxygen-wasting free fatty acids (FFAs) that had been posed as part of the early GIK action related to averting cardiac arrest. METHODS: We analyzed the changes in plasma levels of FFA, glucose, C-peptide, and the homeostasis model assessment (HOMA) index. RESULTS: With GIK, there was rapid suppression of FFA levels with estimated levels for GIK and placebo groups after 2 hours of treatment of 480 and 781 µmol/L (P<.0001), even while patterns of FFA saturation remained unchanged. There were no significant changes in the HOMA index in the GIK or placebo groups (HOMA index: placebo 10.93, GIK 12.99; P = .07), suggesting that GIK infusions were not countered by insulin resistance. Also, neither placebo nor GIK altered endogenous insulin secretion as reflected by unchanging C-peptide levels. CONCLUSION: These mechanistic observations support the potential role of FFA suppression in very early cardioprotection by GIK. They also suggest that the IMMEDIATE Trial GIK formula is balanced with respect to its insulin and glucose composition, as it induced no endogenous insulin secretion.

In-hospital measurement of left ventricular ejection fraction and one-year outcomes in acute coronary syndromes: results from the IMMEDIATE Trial.

BACKGROUND: In patients with acute coronary syndrome (ACS), reduced left ventricular ejection fraction (LVEF) is a known marker for increased mortality. However, the relationship between LVEF measured during index ACS hospitalization and mortality and heart failure (HF) within 1 year are less well-defined. METHODS: We performed a retrospective analysis of 445 participants in the IMMEDIATE Trial who had LVEF measured by left ventriculography or echocardiogram during hospitalization. RESULTS: Adjusting for age and coronary artery disease (CAD) history, lower LVEF was significantly associated with 1-year mortality or hospitalization for HF. For every 5 % LVEF reduction, the hazard ratio [HR] was 1.26 (95 % CI 1.15, 1.38, P < 0.001). Participants with LVEF < 40 % had higher hazard of 1-year mortality or HF hospitalization than those with LVEF > 40 (HR 3.59; 95 % CI 2.05, 6.27, P < 0.001). The HRs for the association of LVEF with the study outcomes were similar whether measured by left ventriculography or by echocardiography, (respectively, HR 1.32; 95 % CI 1.15, 1.51 and 1.21; 95 % CI 1.106, 1.35, interaction P = 0.32) and whether done within 24 h or not within 24 h (respectively, HR 1.28; 95 % CI 1.10, 1.50 and 1.23; 95 % CI 1.10, 1.38, interaction P = 0.67). CONCLUSIONS: Among patients with ACS, lower in-hospital LVEF is associated with increased 1-year mortality or hospitalization for HF, regardless of the method or timing of the LVEF assessment. This has prognostic implications for clinical practice and suggests the possibility of using various methods of LVEF determination in clinical research.

Quantity Over Quality: How the Rise in Quality Measures is Not Producing Quality Results.

Over the past decade, quality measures (QMs) have been implemented nationally in order to establish standards aimed at improving the quality of care. With the expansion of their role in the Affordable Care Act and pay-for-performance, QMs have had an increasingly significant impact on clinical practice. However, adverse patient outcomes have resulted from adherence to some previously promulgated performance measures. Several of these QMs with unintended consequences, including the initiation of perioperative beta-blockers in noncardiac surgery and intensive insulin therapy for critically ill patients, were instituted as QMs years before large randomized trials ultimately refuted their use. The future of quality care should emphasize the importance of evidence-based, peer-reviewed measures.

C-Reactive protein reactions to glucose-insulin-potassium infusion and relations to infarct size in patients with acute coronary syndromes.

BACKGROUND: Some benefits of glucose-insulin-potassium (GIK) in patients with acute coronary syndromes (ACS) may be from an anti-inflammatory effect. The primary aim of this study was to assess the impact of GIK administration early in the course of ACS on inflammatory marker C-reactive protein (CRP) levels. A secondary aim was to investigate the association between CRP and 30-day infarct size. METHODS AND RESULTS: Retrospective analysis of participants with ACS randomly assigned to GIK or placebo for at least 8 h in the IMMEDIATE Trial biological mechanism cohort (n = 143). High sensitivity CRP (hs-CRP) was measured at emergency department presentation, and 6 and 12 h into infusion. Logarithmically transformed hs-CRP values at 12-hours were lower with GIK vs. placebo (mean =0.65 mg/L in GIK, 0.84 mg/L in placebo), with a marginal trend toward significance (P = 0.053). Furthermore, using mixed models of hs-CRP, time, and study group, there was a significant increase in hs-CRP levels over time, but the rate of change did not differ between treatment arms (P = 0.3). Multivariable analysis showed that an elevation in hs-CRP, measured at 12 h, was an independent predictor of 30-day infarct size (ß coefficient, 6.80; P = 0.04) using sestamibi SPECT imaging. CONCLUSIONS: The results of this study show no significant effect of GIK on hs-CRP. In addition our results show that in patients with ACS, hs-CRP measured as early as 12 h can predict 30-day infarct size.

A community consultation survey to evaluate support for and success of the IMMEDIATE trial.

BACKGROUND: The IMMEDIATE (Immediate Myocardial Metabolic Enhancement During Initial Assessment and Treatment in Emergency care) Trial, a randomized controlled double-blind clinical effectiveness trial of glucose-insulin-potassium (GIK) administered in ambulances in the out-of-hospital setting, used the Exception from Informed Consent Requirements (EFIC) for Emergency Research under Title 21 of the Code of Federal Regulations. EFIC requirements include community consultation that typically involves using a variety of communication methods and venues to inform the public of the research and to receive their feedback. Although not the primary purpose of the community consultation process, a common concern to research sponsors, staff, and institutional review boards (IRBs) is whether there will be a sufficient number of participants to justify mounting a study in their community. Information from community consultation regarding the community acceptance might inform this question. PURPOSE: We evaluated the utility of telephone survey data done as part of the EFIC process as a way to project the ultimate rate of trial participant enrollment. METHODS: A telephone survey community consultation process was undertaken in nine communities planning to be IMMEDIATE Trial sites using a representative sampling of the target population in the areas covered by participating emergency medical service (EMS) agencies. Survey respondents were read a description of the planned study and its informed consent approach that included the option for patients to decline participation in the trial while being transported for acute care in an ambulance. Survey respondents were then asked whether they would object to participating in the study. At the conclusion of actual trial enrollment, the Coordinating Center compared the survey results with the actual rates of enrollment at each site. RESULTS: Approximately 200 (range = 200-271) respondents completed the survey in each of the study communities. Of 2079 survey respondents, 68% (range = 61%-75%) said that they would not object to participating in the trial if experiencing a heart attack, and 85% (range = 79%-89%) said that they would allow the study to be done in their community. During actual trial enrollment in the communities, 79% (range = 63%-91%) of the 828 potential participants agreed in the ambulance to have the study drug started and provided informed consent at the hospital, an average of 13 percentage-points higher than projected by the survey (95% confidence interval (CI): 9%-17%), 19% higher on a relative scale (CI: 14%-25%). CONCLUSIONS: The survey-based approach to community consultation proved to be an efficient way to obtain representative input from potential clinical trial participants. The survey data generated a relatively good and conservative estimate of the ultimate rate of trial enrollment. This information could be useful to investigators and IRBs in projecting enrollment for clinical trials using EFIC.

Academic general internal medicine: a mission for the future.

After five decades of growth that has included advances in medical education and health care delivery, value cohesion, and integration of diversity, we propose an overarching mission for academic general internal medicine to lead excellence, change, and innovation in clinical care, education, and research. General internal medicine aims to achieve health care delivery that is comprehensive, technologically advanced and individualized; instills trust within a culture of respect; is efficient in the use of time, people, and resources; is organized and financed to achieve optimal health outcomes; maximizes equity; and continually learns and adapts. This mission of health care transformation has implications for the clinical, educational, and research activities of divisions of general internal medicine over the next several decades.

Satisfaction and emergency department revisits in patients with possible acute coronary syndrome.

BACKGROUND: Patients with possible acute coronary syndrome (ACS) are typically instructed to return to the emergency department (ED) if their condition worsens. Little is known about the relationship between patient satisfaction in the ED and subsequent return visits. OBJECTIVE: Our aim was to determine the association between satisfaction with ED care and subsequent ED return visits. METHODS: One thousand and five consecutive ED patients with symptoms of possible ACS who participated in a prospective guideline implementation trial at two university hospitals completed a telephone survey at 30-day follow-up. Satisfaction with care at the initial ED visit was measured using items from the Press Ganey satisfaction questionnaire. Logistic regression was used to determine the association between individual satisfaction items and the occurrence of any ED revisits, and the association between satisfaction items and return visits to the same ED. RESULTS: Patients who reported superior ratings of person-centered care ("staff cared about you as a person") were significantly less likely to return to any ED during 30-day follow-up: 59 vs. 71%, adjusted odds ratio = 0.57 (95% confidence interval 0.37-0.87). Among those with ED revisits, superior ratings of personal care and perceived waiting time for emergency physician evaluation were significantly associated with return to the same ED. CONCLUSIONS: Although diagnostic workup and risk stratification are the primary focus in evaluating patients with possible ACS, greater attention to the patient's experience of care may have the positive impact of reducing ED return visits and increasing the likelihood that patients will return to the same ED for re-evaluation.

From a decentralized clinical trial to a decentralized and clinical-trial-in-a-box platform: Towards patient-centric and equitable trials.

Background/Objective: Despite the intuitive attractiveness of bringing research to participants rather than making them come to central study sites, widespread decentralized enrollment has not been common in clinical trials. Methods: The need for clinical research in the context of the COVID-19 pandemic, along with innovations in technology, led us to use a decentralized trial approach in our Phase 2 COVID-19 trial. We used real-time acquisition and transmission of health-related data using home-based monitoring devices and mobile applications to assess outcomes. This approach not only avoids spreading COVID-19 but it also can support inclusion of participants in more diverse socioeconomic circumstances and in rural settings. Results: Our team developed and deployed a decentralized trial platform to support patient engagement and adverse event reporting. Clinicians, engineers, and informaticians on our research team developed a Clinical-Trial-in-a-Box tool to optimally collect and analyze data from multiple decentralized platforms. Conclusion: Applying the decentralized model in Long COVID, using digital health technology and personal devices integrated with our telehealth platform, we share the lessons learned from our work, along with challenges and future possibilities.

The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations.

Introduction: Ideally, real-world data (RWD) collected to generate real-world evidence (RWE) should lead to impact on the care and health of real-world patients. Deriving from care in which clinicians and patients try various treatments to inform therapeutic decisions, N-of-1 trials bring scientific methods to real-world practice. Methods: These single-patient crossover trials generate RWD and RWE by giving individual patients various treatments in a double-blinded way in sequential periods to determine the most effective treatment for a given patient. Results: This approach is most often used for patients with chronic, relatively stable conditions that provide the opportunity to make comparisons over multiple treatment periods, termed Type 1 N-of-1 trials. These are most helpful when there is heterogeneity of treatment effects among patients and no a priori best option. N-of-1 trials also can be done for patients with rare diseases, potentially testing only one treatment, to generate evidence for personalized treatment decisions, designated as Type 2 N-of-1 trials. With both types, in addition to informing individual's treatments, when uniform protocols are used for multiple patients with the same condition, the data collected in the individual N-of-1 trials can be aggregated to provide RWD/RWE to inform more general use of the treatments. Thereby, N-of-1 trials can provide RWE for the care of individuals and for populations. Conclusions: To fulfill this potential, we believe N-of-1 trials should be built into our current healthcare ecosystem. To this end, we are building the needed infrastructure and engaging the stakeholders who should receive value from this approach.

Development and validation of a predictive model for the diagnosis of rheumatic heart disease in low-income countries based on two cross-sectional studies.

Objectives: We developed a questionnaire-based risk-scoring system to identify children at risk for rheumatic heart disease (RHD) in rural India. The resulting predictive model was validated in Nepal, in a population with a similar demographic profile to rural India. Methods: The study involved 8646 students (mean age 13.0 years, 46% boys) from 20 middle and high schools in the West Midnapore district of India. The survey asked questions about the presence of different signs and symptoms of RHD. Students with possible RHD who experienced sore throat and joint pain were offered an echocardiogram to screen for RHD. Their findings were compared with randomly selected students without these symptoms. The data were analyzed to develop a predictive model for identifying RHD. Results: Based on our univariate analyses, seven variables were used for building a predictive model. A four-variable model (joint pain plus sore throat, female sex, shortness of breath, and palpitations) best predicted the risk of RHD with a C-statistic of 0.854. A six-point scoring system developed from the model was validated among similarly aged children in Nepal. Conclusions: A simple questionnaire-based predictive instrument could identify children at higher risk for this disease in low-income countries where RHD remains prevalent. Echocardiography could then be used in these high-risk children to detect RHD in its early stages. This may support a strategy for more effective secondary prophylaxis of RHD.

Approaches for enhancing the informativeness and quality of clinical trials: Innovations and principles for implementing multicenter trials from the Trial Innovation Network.

One challenge for multisite clinical trials is ensuring that the conditions of an informative trial are incorporated into all aspects of trial planning and execution. The multicenter model can provide the potential for a more informative environment, but it can also place a trial at risk of becoming uninformative due to lack of rigor, quality control, or effective recruitment, resulting in premature discontinuation and/or non-publication. Key factors that support informativeness are having the right team and resources during study planning and implementation and adequate funding to support performance activities. This communication draws on the experience of the National Center for Advancing Translational Science (NCATS) Trial Innovation Network (TIN) to develop approaches for enhancing the informativeness of clinical trials. We distilled this information into three principles: (1) assemble a diverse team, (2) leverage existing processes and systems, and (3) carefully consider budgets and contracts. The TIN, comprised of NCATS, three Trial Innovation Centers, a Recruitment Innovation Center, and 60+ CTSA Program hubs, provides resources to investigators who are proposing multicenter collaborations. In addition to sharing principles that support the informativeness of clinical trials, we highlight TIN-developed resources relevant for multicenter trial initiation and conduct.

Decentralized clinical trials in the trial innovation network: Value, strategies, and lessons learned.

New technologies and disruptions related to Coronavirus disease-2019 have led to expansion of decentralized approaches to clinical trials. Remote tools and methods hold promise for increasing trial efficiency and reducing burdens and barriers by facilitating participation outside of traditional clinical settings and taking studies directly to participants. The Trial Innovation Network, established in 2016 by the National Center for Advancing Clinical and Translational Science to address critical roadblocks in clinical research and accelerate the translational research process, has consulted on over 400 research study proposals to date. Its recommendations for decentralized approaches have included eConsent, participant-informed study design, remote intervention, study task reminders, social media recruitment, and return of results for participants. Some clinical trial elements have worked well when decentralized, while others, including remote recruitment and patient monitoring, need further refinement and assessment to determine their value. Partially decentralized, or "hybrid" trials, offer a first step to optimizing remote methods. Decentralized processes demonstrate potential to improve urban-rural diversity, but their impact on inclusion of racially and ethnically marginalized populations requires further study. To optimize inclusive participation in decentralized clinical trials, efforts must be made to build trust among marginalized communities, and to ensure access to remote technology.

Development, implementation, and dissemination of operational innovations across the trial innovation network.

Improving the quality and conduct of multi-center clinical trials is essential to the generation of generalizable knowledge about the safety and efficacy of healthcare treatments. Despite significant effort and expense, many clinical trials are unsuccessful. The National Center for Advancing Translational Science launched the Trial Innovation Network to address critical roadblocks in multi-center trials by leveraging existing infrastructure and developing operational innovations. We provide an overview of the roadblocks that led to opportunities for operational innovation, our work to develop, define, and map innovations across the network, and how we implemented and disseminated mature innovations.

Leveraging the Expertise of the CTSA Program to Increase the Impact and Efficiency of Clinical Trials.

Importance: Multicenter clinical trials play a critical role in the translational processes that enable new treatments to reach all people and improve public health. However, conducting multicenter randomized clinical trials (mRCT) presents challenges. The Trial Innovation Network (TIN), established in 2016 to partner with the Clinical and Translational Science Award (CTSA) Consortium of academic medical institutions in the implementation of mRCTs, consists of 3 Trial Innovation Centers (TICs) and 1 Recruitment Innovation Center (RIC). This unique partnership has aimed to address critical roadblocks that impede the design and conduct of mRCTs, in expectation of accelerating the translation of novel interventions to clinical practice. The TIN's challenges and achievements are described in this article, along with examples of innovative resources and processes that may serve as useful models for other clinical trial networks providing operational and recruitment support. Observations: The TIN has successfully integrated more than 60 CTSA institution program hubs into a functional network for mRCT implementation and optimization. A unique support system for investigators has been created that includes the development and deployment of novel tools, operational and recruitment services, consultation models, and rapid communication pathways designed to reduce delays in trial start-up, enhance recruitment, improve engagement of diverse research participants and communities, and streamline processes that improve the quality, efficiency, and conduct of mRCTs. These resources and processes span the clinical trial spectrum and enable the TICs and RIC to serve as coordinating centers, data centers, and recruitment specialists to assist trials across the National Institutes of Health and other agencies. The TIN's impact has been demonstrated through its response to both historical operational challenges and emerging public health emergencies, including the national opioid public health crisis and the COVID-19 pandemic. Conclusions and Relevance: The TIN has worked to reduce barriers to implementing mRCTs and to improve mRCT processes and operations by providing needed clinical trial infrastructure and resources to CTSA investigators. These resources have been instrumental in more quickly and efficiently translating research discoveries into beneficial patient treatments.