Prototype of an evidence-based tool to aid individualized treatment for type 2 diabetes.
Ontology highlight
ABSTRACT:
SUBMITTER: Buse JB
PROVIDER: S-EPMC8251774 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundAdolescents with type 1 diabetes mellitus have difficulty achieving optimal glycemic control, partly due to competing priorities that interfere with diabetes self-care. Often, significant diabetes-related family conflict occurs, and adolescents' thoughts and feelings about diabetes management may be disregarded. Patient-centered diabetes outcomes may be better when adolescents feel engaged in the decision-making process.ObjectiveThe objective of our study was to codesign a clinic intervention using shared decision making for addressing diabetes self-care with an adolescent patient and parent advisory board.MethodsThe patient and parent advisory board consisted of 6 adolescents (teens) between the ages 12 and 18 years with type 1 diabetes mellitus and their parents recruited through our institution's Pediatric Diabetes Program. Teens and parents provided informed consent and participated in 1 or both of 2 patient and parent advisory board sessions, lasting 3 to 4 hours each. Session 1 topics were (1) patient-centered outcomes related to quality of life, parent-teen shared diabetes management, and shared family experiences; and (2) implementation and acceptability of a patient-centered diabetes care plan intervention where shared decision making was used. We analyzed audio recordings, notes, and other materials to identify and extract ideas relevant to the development of a patient-centered diabetes management plan. These data were visually coded into similar themes. We used the information to develop a prototype for a diabetes management plan tool that we pilot tested during session 2.ResultsSession 1 identified 6 principal patient-centered quality-of-life measurement domains: stress, fear and worry, mealtime struggles, assumptions and judgments, feeling abnormal, and conflict. We determined 2 objectives to be principally important for a diabetes management plan intervention: (1) focusing the intervention on diabetes distress and conflict resolution strategies, and (2) working toward a verbalized common goal. In session 2, we created the diabetes management plan tool according to these findings and will use it in a clinical trial with the aim of assisting with patient-centered goal setting.ConclusionsPatients with type 1 diabetes mellitus can be effectively engaged and involved in patient-centered research design. Teens with type 1 diabetes mellitus prioritize reducing family conflict and fitting into their social milieu over health outcomes at this time in their lives. It is important to acknowledge this when designing interventions to improve health outcomes in teens with type 1 diabetes mellitus.
| S-EPMC7434065 | biostudies-literature
Project description:AimThe purpose of this study was to translate evidence from Cochrane Reviews into a format that can be used to facilitate shared decision making during the consultation, namely patient decision aids.MethodsA systematic development process (a) established a stakeholder committee; (b) developed a prototype according to the International Patient Decision Aid Standards; (c) applied the prototype to a Cochrane Review and used an interview-guided survey to evaluate acceptability/usability; (d) created 12 consult decision aids; and (e) used a Delphi process to reach consensus on considerations for creating a consult decision aid.ResultsThe 1-page prototype includes (a) a title specifying the decision; (b) information on the health condition, options, benefits/harms with probabilities; (c) an explicit values clarification exercise; and (d) questions to screen for decisional conflict. Hyperlinks provide additional information on definitions, probabilities presented graphically, and references. Fourteen Cochrane Consumer Network members and Cochrane Editorial Unit staff participated. Thirteen reported that it would help patient/clinician discussions and were willing to use and/or recommend it. Seven indicated the right amount of information, six not enough, and one too much. Changes to the prototype were more links to definitions, more white space, and details on GRADE evidence ratings. Creating 12 consult decision aids took about 4 h each. We identified ten considerations when selecting Cochrane Reviews for creating consult decision aids.ConclusionsUsing a systematic process, we developed a consult decision aid prototype to be populated with evidence from Cochrane Reviews. It was acceptable and easy to apply. Future studies will evaluate implementation of consult decision aids.
| S-EPMC5107194 | biostudies-literature
Project description:Despite the known heterogeneity of type 2 diabetes and variable response to glucose lowering medications, current evidence on optimal treatment is predominantly based on average effects in clinical trials rather than individual-level characteristics. A precision medicine approach based on treatment response would aim to improve on this by identifying predictors of differential drug response for people based on their characteristics and then using this information to select optimal treatment. Recent research has demonstrated robust and clinically relevant differential drug response with all noninsulin treatments after metformin (sulfonylureas, thiazolidinediones, dipeptidyl peptidase 4 [DPP-4] inhibitors, glucagon-like peptide 1 [GLP-1] receptor agonists, and sodium-glucose cotransporter 2 [SGLT2] inhibitors) using routinely available clinical features. This Perspective reviews this current evidence and discusses how differences in drug response could inform selection of optimal type 2 diabetes treatment in the near future. It presents a novel framework for developing and testing precision medicine-based strategies to optimize treatment, harnessing existing routine clinical and trial data sources. This framework was recently applied to demonstrate that "subtype" approaches, in which people are classified into subgroups based on features reflecting underlying pathophysiology, are likely to have less clinical utility compared with approaches that combine the same features as continuous measures in probabilistic "individualized prediction" models.
| S-EPMC7506836 | biostudies-literature
Project description:IntroductionAs the prevalence of type 2 diabetes mellitus (T2DM) is anticipated to continue to rise worldwide, so too are the treatment options also continuing to expand. Current guidelines recommend individualized treatment plans which allow for provider choice and diversity of pharmacotherapeutic regimens. The glucagon-like peptide-1 receptor agonist (GLP-1 RA) class is rapidly expanding, with dulaglutide (Trulicity™) as a once-weekly agent recently approved.AimsThis article examines the evidence currently available on the efficacy and safety of dulaglutide for use in T2DM.Evidence reviewDulaglutide has been shown to have similar efficacy and safety to other newer GLP-1 RAs, and better glycemic control than placebo. It lowers glycated hemoglobin (A1c), fasting and postprandial glucose levels, and promotes weight loss when used as first-, second-, or third-line therapy. It has also been shown to improve β-cell function and provide cardiovascular benefits, such as lower blood pressure and improved lipid levels. Dulaglutide also has a low risk for hypoglycemia and a similar adverse effect profile to other GLP-1 RAs in the class, with transient gastrointestinal problems and potential risk for pancreatitis.Place in therapyWhile long-term data on safety and efficacy are forthcoming, dulaglutide is positioned to be placed at the same level as other GLP-1 RAs in the class: as second-line therapy in addition to diet and exercise in those patients who cannot achieve glycemic control on monotherapy metformin. It may also be useful as first-line therapy instead of metformin.ConclusionDulaglutide is a once-weekly GLP-1 RA approved for the treatment of T2DM that has shown similar efficacy to other agents in this class.
| S-EPMC4295897 | biostudies-literature
Project description:AimsTo identify clinically meaningful clusters of patients with similar glycated hemoglobin (HbA1c) trajectories among patients with type 2 diabetes.MethodsA retrospective cohort study using unsupervised machine learning clustering methodologies to determine clusters of patients with similar longitudinal HbA1c trajectories. Stability of these clusters was assessed and supervised random forest analysis verified the clusters' reproducibility. Clinical relevance of the clusters was assessed through multivariable analysis, comparing differences in risk for a composite outcome (macrovascular and microvascular outcomes, hypoglycemic events, and all-cause mortality) at HbA1c thresholds for each cluster.ResultsAmong 60,423 patients, three clusters of HbA1c trajectories were generated: stable (n = 45,679), descending (n = 6,084), and ascending (n = 8,660) trends, which were reproduced with 99.8% accuracy using a random forest model. In the clinical relevance assessment, HbA1c levels demonstrated a J-shape association with the risk for outcomes. HbA1c level thresholds for minimizing outcomes' risk differed by cluster: 6.0-6.4% for the stable cluster, <8.0% for the descending cluster, and <9.0 for the ascending cluster.ConclusionsBy applying unsupervised machine learning to longitudinal HbA1c trajectories, we have identified clusters of patients who have distinct risk for diabetes-related complications. These clusters can be the basis for developing individualized models to personalize glycemic targets.
| S-EPMC6235308 | biostudies-literature
Project description:IntroductionMany parents who choose hypospadias repair for their sons experience decisional conflict (DC) and decisional regret (DR). We previously found that parental decision-making about hypospadias surgery is a complex process characterized by cyclic information-seeking to alleviate anxiety and confusion.ObjectiveThe objective of this study was to engage parents of hypospadias patients and pediatric providers in the co-design of a decision aid (DA) prototype to facilitate shared decision-making about hypospadias surgery and address DC and DR.MethodsFrom August 2018 to January 2019, we conducted three co-design workshops with parents of hypospadias patients, pediatric urology and general pediatric providers to discuss their recommendations for a DA prototype. Activities were audio recorded and professionally transcribed. Transcripts and worksheets were analyzed by six coders using qualitative analysis to identify key aspects of a hypospadias DA desired by stakeholders. We conducted a collaborative design and prototyping session to establish key features and requirements, created a content map visualizing this work, and then developed a DA prototype.ResultsParent participants included 6 mothers and 4 fathers: 8 Caucasian, 2 African-American; median age 31 years. Providers included pediatric urology (n = 7) and general pediatric providers (n = 10): median age 47.5 years, 83.3% Caucasian, 58.3% male, 58.3% MD's and 41.7% nurse practitioners. Participants created user-friendly, interactive DA prototypes with "24/7" availability that had three key functions: 1) provide accurate, customizable, educational content, 2) connect parents with each other, and 3) engage them in a decision-making activity. The prototype consisted of five modules (Extended Summary Figure). "Hypospadias Basics" includes epidemiology and a hypospadias severity scale. "Surgery Basics" includes goals, illustrated steps, and pros/cons of surgery. "Testimonials" includes videos of parents and adolescents discussing their experiences. "Help me Decide" includes a decisional conflict scale and a decision-making activity (i.e. values clarification method). "Frequently Asked Questions" covers general hypospadias information, perioperative expectations and a review of postoperative care.DiscussionTo our knowledge, this is the first DA prototype developed for a pediatric urology condition using a human-centered design approach to engage many key stakeholders in the development process. One limitation of this study is the small population sampled, which limits generalizability and means that our findings may not reflect the views of all parents or pediatric providers involved in hypospadias decision-making.ConclusionsWe created a parent-centered hypospadias DA prototype that provides decision support in an online, interactive format. Future directions include further testing with usability experts, providers and parents.
| S-EPMC7686073 | biostudies-literature
Project description:Mucopolysaccharidosis (MPS) is a group of rare metabolic diseases associated with reduced life expectancy and a substantial unmet medical need. Immunomodulatory drugs could be a relevant treatment approach for MPS patients, although they are not licensed for this population. Therefore, we aim to provide evidence justifying fast access to innovative individual treatment trials (ITTs) with immunomodulators and a high-quality evaluation of drug effects by implementing a risk-benefit model for MPS. The iterative methodology of our developed decision analysis framework (DAF) consists of the following steps: (i) a comprehensive literature analysis on promising treatment targets and immunomodulators for MPS; (ii) a quantitative risk-benefit assessment (RBA) of selected molecules; and (iii) allocation phenotypic profiles and a quantitative assessment. These steps allow for the personalized use of the model and are in accordance with expert and patient representatives. The following four promising immunomodulators were identified: adalimumab, abatacept, anakinra, and cladribine. An improvement in mobility is most likely with adalimumab, while anakinra might be the treatment of choice for patients with neurocognitive involvement. Nevertheless, a RBA should always be completed on an individual basis. Our evidence-based DAF model for ITTs directly addresses the substantial unmet medical need in MPS and characterizes a first approach toward precision medicine with immunomodulatory drugs.
| S-EPMC10221776 | biostudies-literature
Project description:Individualized treatment rules recommend treatments on the basis of individual patient characteristics. A high-quality treatment rule can produce better patient outcomes, lower costs and less treatment burden. If a treatment rule learned from data is to be used to inform clinical practice or provide scientific insight, it is crucial that it be interpretable; clinicians may be unwilling to implement models they do not understand, and black-box models may not be useful for guiding future research. The canonical example of an interpretable prediction model is a decision tree. We propose a method for estimating an optimal individualized treatment rule within the class of rules that are representable as decision trees. The class of rules we consider is interpretable but expressive. A novel feature of this problem is that the learning task is unsupervised, as the optimal treatment for each patient is unknown and must be estimated. The proposed method applies to both categorical and continuous treatments and produces favourable marginal mean outcomes in simulation experiments. We illustrate it using data from a study of major depressive disorder.
| S-EPMC4755313 | biostudies-literature
Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of a total of 3100 capture probes, covering all human, mouse and rat microRNAs annotated in miRBase 18.0, in 8 melanoma samples divided into 4 groups (Control, ALA, US, and SDT group).
2015-01-29 | GSE65390 | GEO
Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of a total of 3100 capture probes, covering all human, mouse and rat microRNAs annotated in miRBase 18.0, in 8 melanoma samples divided into 4 groups (Control, ALA, US, and SDT group). In the study presented here, a consecutively operated, well-defined cohort of 8 melanoma cases was used to acquire miRNA expression profiles with Exiqon arrays based on miRBase 18.0.
2015-01-29 | E-GEOD-65390 | biostudies-arrayexpress