MyLungHealth for Lung Cancer Screening
(MyLungHealth Trial)
Recruiting in Palo Alto (17 mi)
+1 other location
Overseen byKensaku Kawamoto, MD, PhD, MHS
Age: 18+
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: University of Utah
Disqualifiers: Lung cancer, Recent LDCT, others
No Placebo Group
Trial Summary
What is the purpose of this trial?
Early lung cancer screening (LCS) through low-dose computed tomography (LDCT) is crucial but underused due to various barriers, including incomplete or inaccurate patient smoking data in the electronic health record and limited time for shared decision-making. The objective of this trial is to investigate a patient-centered intervention, MyLungHealth, delivered through the patient portal. The intervention is designed to improve LCS rates through increased identification of eligible patients and informed decision making.
Will I have to stop taking my current medications?
The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.
What data supports the effectiveness of the MyLungHealth treatment for lung cancer screening?
The DecisionPrecision tool, part of the MyLungHealth treatment, is a web-based decision support tool that helps tailor lung cancer screening discussions to a patient's individual risk, potentially improving decision-making and outcomes. Additionally, data mining from large cancer screening trials can guide personalized screening management, optimizing the benefit-to-risk ratio for patients.12345
Is MyLungHealth safe for humans?
How is the MyLungHealth treatment different from other lung cancer screening treatments?
MyLungHealth, also known as DecisionPrecision+, is unique because it is a web-based tool designed to support shared decision-making by providing personalized lung cancer risk assessments and tailored screening recommendations, helping patients and clinicians make more informed decisions about lung cancer screening.110111213
Eligibility Criteria
The MyLungHealth study is for people aged 50-79 who have a history of smoking and have visited a participating primary care clinic in the past year. Participants must also have used the patient portal at least once in the previous year.Inclusion Criteria
I have smoked tobacco in the past or am currently smoking.
I have used the patient portal at least once in the past year.
I have visited the study's primary care clinic in the last year.
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Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
1-2 weeks
1 visit (virtual)
Intervention
Participants engage with the MyLungHealth intervention through the patient portal, including pre-visit smoking history questionnaires and education tools.
1 year
Ongoing virtual engagement
Follow-up
Participants are monitored for the completion of LDCT and other lung cancer screening activities.
1 year
Treatment Details
Interventions
- DecisionPrecision+ (Behavioral Intervention)
- MyLungHealth (Behavioral Intervention)
Trial OverviewThis trial tests MyLungHealth, an intervention aimed to improve lung cancer screening rates by identifying eligible patients and supporting informed decision-making through a patient portal called DecisionPrecision+.
Participant Groups
4Treatment groups
Experimental Treatment
Active Control
Group I: Study 2 (Study of Patients with Documented LCS Eligibility) Intervention ArmExperimental Treatment2 Interventions
Patients allocated to the intervention arm will be offered the MyLungHealth education tool in addition to the DecisionPrecision+ intervention. The pre-visit questionnaire will directly invite patients to use the MyLungHealth education app, rather than first asking about smoking history to confirm eligibility. When patients affirm in the patient portal that they were able to successfully open the MyLungHealth education tool, their providers will be notified of their potential interest in LCS through a passive (non-interruptive) prompt in the EHR.
Group II: Study 1 (Study of Patients with Uncertain LCS Eligibility) Intervention ArmExperimental Treatment1 Intervention
Patients allocated to the intervention arm of Study 1 will be exposed to the MyLungHealth intervention in addition to usual care. The Study 1 MyLungHealth eligibility questionnaires will consist of pre-visit smoking history questions asked through the EHR patient portal to increase the identification of screening-eligible patients (Figure 2). Patients will be prompted to engage in the intervention through pre-visit questionnaires for primary care visits administered up to 7 days prior to the visits. These questions will ask about the patients' smoking history and determine whether patients meet LCS eligibility criteria. Study 1 patients who meet LCS eligibility criteria will be offered the intervention provided to patients in the intervention arm of Study 2 immediately after confirming eligibility but will not be considered participants in Study 2.
Group III: Study 1 (Study of Patients with Uncertain LCS Eligibility) Control ArmActive Control1 Intervention
In Study 1 (Study of Patients with Uncertain LCS Eligibility), patients allocated to the control arm will not be exposed to the project intervention unless their EHR data change during the trial so that they have documented LCS eligibility. In these rare cases, these patients will be exposed to the intervention provided to patients in the control arm of Study 2 but will not be considered participants in Study 2.
Group IV: Study 2 (Study of Patients with Documented LCS Eligibility) Control ArmActive Control1 Intervention
In Study 2 (Study of Patients with Documented LCS Eligibility), patients allocated to the control arm will be exposed to the DecisionPrecision+ intervention because DecisionPrecision+ intervention automatically identifies patients with documented LCS eligibility in the EHR. The DecisionPrecision+ intervention is designed to promote LCS and LCS SDM; the intervention consists of provider-facing EHR preventive care reminders, a provider-facing EHR SDM tool, and simple patient-facing preventive care reminders (only available at UUH). Simple patient-facing preventive care reminders will be available at UUH, but not NYU, because NYU does not use this type of reminders.
DecisionPrecision+ is already approved in United States for the following indications:
🇺🇸 Approved in United States as Decision Precision+ for:
- Lung cancer screening for individuals with a history of heavy smoking
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
NYU Langone HealthNew York, NY
University of Utah HealthSalt Lake City, UT
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Who Is Running the Clinical Trial?
University of UtahLead Sponsor
References
Implementation of a Web-Based Tool for Shared Decision-making in Lung Cancer Screening: Mixed Methods Quality Improvement Evaluation. [2023]Lung cancer risk and life expectancy vary substantially across patients eligible for low-dose computed tomography lung cancer screening (LCS), which has important consequences for optimizing LCS decisions for different patients. To account for this heterogeneity during decision-making, web-based decision support tools are needed to enable quick calculations and streamline the process of obtaining individualized information that more accurately informs patient-clinician LCS discussions. We created DecisionPrecision, a clinician-facing web-based decision support tool, to help tailor the LCS discussion to a patient's individualized lung cancer risk and estimated net benefit.
Focused Decision Support: a Data Mining Tool to Query the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Dataset and Guide Screening Management for the Individual Patient. [2018]The Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial enrolled ~155,000 participants to determine whether certain screening exams reduced mortality from prostate, lung, colorectal, and ovarian cancer. Repurposing the data provides an unparalleled resource for matching patients with the outcomes of demographically or diagnostically comparable patients. A web-based application was developed to query this subset of patient information against a given patient's demographics and risk factors. Analysis of the matched data yields outcome information which can then be used to guide management decisions and imaging software. Prognostic information is also estimated via the proportion of matched patients that progress to cancer. The US Preventative Services Task Force provides screening recommendations for cancers of the breast, colorectal tract, and lungs. There is wide variability in adherence of clinicians to these guidelines and others published by the Fleischner Society and various cancer organizations. Data mining the PLCO dataset for clinical decision support can optimize the use of limited healthcare resources, focusing screening on patients for whom the benefit to risk ratio is the greatest and most efficacious. A data driven, personalized approach to cancer screening maximizes the economic and clinical efficacy and enables early identification of patients in which the course of disease can be improved. Our dynamic decision support system utilizes a subset of the PLCO dataset as a reference model to determine imaging and testing appropriateness while offering prognostic information for various cancers.
Informed decision making does not affect health-related quality of life in lung cancer screening (NELSON trial). [2010]It is believed that making an informed decision about (screening) participation is associated with better health-related quality of life (HRQoL) outcomes. This is the first study in cancer screening to explore this association in subjects participating in a lung cancer computed tomography (CT) screening trial.
Aiding shared decision making in lung cancer screening: two decision tools. [2021]Shared decision making (SDM) preceding lung cancer screening is important for populations that are underrepresented in lung cancer screening trials. Current evidence-based guidelines; however, do not address personal risk and outcomes in underrepresented populations. This study compared two SDM decision aids (Option Grids and Shouldiscreen.com) for SDM efficacy, decision regret and knowledge.
Effectiveness of a Patient Education Class to Enhance Knowledge about Lung Cancer Screening: a Quality Improvement Evaluation. [2021]Best practices to facilitate high-quality shared decision-making for lung cancer screening (LCS) are not well established. In our LCS program, patients are first referred to attend a free group education class on LCS, taught by designated clinician specialists, before a personal shared decision-making visit is scheduled. We conducted an evaluation on the effectiveness of this class to enhance patient knowledge and shared decision-making about LCS. For quality improvement purposes, participants were asked to complete one-page surveys immediately before and after class to assess knowledge and decision-making capacity regarding LCS. To evaluate knowledge gained, we tabulated the distributions of correct, incorrect, unsure, and missing responses to eight true-false statements included on both pre- and post-class surveys and assessed pre-post differences in the number of correct responses. To evaluate decision-making capacity, we tabulated the distributions of post-class responses to items on decision uncertainty. From June 2017 to August 2018, 680 participants completed both pre- and post-class surveys. Participants had generally poor baseline knowledge about LCS. The proportion who responded correctly to each knowledge-related statement increased pre- to post-class, with a mean difference of 0.9 (paired t test, p
Personalised Lung Cancer Screening (PLuS) study to assess the importance of coexisting chronic conditions to clinical practice and policy: protocol for a multicentre observational study. [2023]Lung cancer is the leading cause of cancer death in the USA and worldwide, and lung cancer screening (LCS) with low-dose CT (LDCT) has the potential to improve lung cancer outcomes. A critical question is whether the ratio of potential benefits to harms found in prior LCS trials applies to an older and potentially sicker population. The Personalised Lung Cancer Screening (PLuS) study will help close this knowledge gap by leveraging real-world data to fully characterise LCS recipients. The principal goal of the PLuS study is to characterise the comorbidity burden of individuals undergoing LCS and quantify the benefits and harms of LCS to enable informed decision-making.
Outcomes of Shared Decision-Making for Low-Dose Screening for Lung Cancer in an Academic Medical Center. [2023]Shared decision-making (SDM) helps patients weigh risks and benefits of screening approaches. Little is known about SDM visits between patients and healthcare providers in the context of lung cancer screening. This study explored the extent that patients were informed by their provider of the benefits and harms of lung cancer screening and expressed certainty about their screening choice. We conducted a survey with 75 patients from an academic medical center in the Southeastern U.S. Survey items included knowledge of benefits and harms of screening, patients' value elicitation during SDM visits, and decisional certainty. Patient and provider characteristics were collected through electronic medical records or self-report. Descriptive statistics, Kruskal-Wallis tests, and Pearson correlations between screening knowledge, value elicitation, and decisional conflict were calculated. The sample was predominately non-Hispanic White (73.3%) with no more than high school education (53.4%) and referred by their primary care provider for screening (78.7%). Patients reported that providers almost always discussed benefits of screening (81.3%), but infrequently discussed potential harms (44.0%). On average, patients had low knowledge about screening (score = 3.71 out of 8) and benefits/harms. Decisional conflict was low (score = - 3.12) and weakly related to knowledge (R= - 0.25) or value elicitation (R= - 0.27). Black patients experienced higher decisional conflict than White patients (score = - 2.21 vs - 3.44). Despite knowledge scores being generally low, study patients experienced low decisional conflict regarding their decision to undergo lung cancer screening. Additional work is needed to optimize the quality and consistency of information presented to patients considering screening.
Using a Patient Decision Aid Video to Assess Current and Former Smokers' Values About the Harms and Benefits of Lung Cancer Screening With Low-Dose Computed Tomography. [2023]Background. Recent policy changes require discussing the potential benefits and harms of lung cancer screening with low-dose computed tomography. This study explored how current and former smokers value potential benefits and harms after watching a patient decision aid, and their screening intentions. Methods. Current or former smokers (quit within 15 years) with no history of lung cancer watched the decision aid and responded to items assessing the value of potential benefits and harms in their decision making, and their screening intentions. Results. After viewing the decision aid, participants (n = 30; mean age 61.5 years, mean 30.4 pack-year history) were well-informed (mean 80.5% correct responses) and rated anticipated regret and finding cancer early as highly important in their decision (medians >9 out of 10), along with moderate but variable concerns about false positives, overdiagnosis, and radiation exposure (medians 7.0, 6.0, and 5.0, respectively). Most participants (90.0% to 96.7%) felt clear about how they personally valued the potential benefits and harms and prepared for decision making (mean 86.7 out of 100, SD = 21.3). After viewing the decision aid, most participants (90%) intended to discuss screening with their doctor. Limitations. The study is limited to current and former smokers enrolled in a tobacco treatment program, and it may not generalize to other patient populations. Conclusions. The majority of current and former smokers were strongly concerned about anticipated regret and finding cancer early, while concerns about radiation exposure, false positives, and overdiagnosis were variable. After viewing the decision aid, current and former smokers reported strong preparedness and intentions to talk with their doctor about lung cancer screening with low-dose computed tomography.
Effect of a Patient Decision Aid on Lung Cancer Screening Decision-Making by Persons Who Smoke: A Randomized Clinical Trial. [2021]Lung cancer screening with low-dose computed tomography lowers lung cancer mortality but has potential harms. Current guidelines support patients receiving information about the benefits and harms of lung cancer screening during decision-making.
A Comparison of Web-Based Cancer Risk Calculators That Inform Shared Decision-making for Lung Cancer Screening. [2022]To align patient preferences and understanding with harm-benefit perception, the Centers for Medicare & Medicaid Services (CMS) mandates that providers engage patients in a collaborative shared decision-making (SDM) visit before LDCT. Nonetheless, patients and providers often turn instead to the web for help making decisions. Several web-based lung cancer risk calculators (LCRCs) provide risk predictions and screening recommendations; however, the accuracy, consistency, and subsequent user interpretation of these predictions between LCRCs is ambiguous. We conducted a systematic review to assess this variability.
What is the Optimum Screening Strategy for the Early Detection of Lung Cancer. [2018]Early diagnosis of lung cancer is currently the most effective way of reducing lung cancer mortality other than quitting smoking because the treatment of late stage disease has little impact. Improving the awareness of the risk of lung cancer and warning symptoms, recognition and prompt referral, and screening with low dose computed tomography (LDCT) are potential ways to improve early diagnosis. Currently the evidence is strongest for LDCT, where one large trial, the US National Lung Screening Trial (NLST), showed a 20% relative reduction in lung cancer-related mortality and a 6.7% reduction in all-cause mortality in patients who had LDCT compared with chest X-ray. Although many questions remain about optimal methodology and cost-effectiveness, lung cancer screening is now being implemented in the USA using the NLST screening criteria. Many of these questions are being answered by on-going European trials that are reporting their findings. Here we review the research evidence for LDCT screening and explore the important issues that need to be addressed to optimise effectiveness.
Evaluation of a Personalized, Web-Based Decision Aid for Lung Cancer Screening. [2018]Informed decision making has been highlighted as an important aspect of lung cancer screening programs. This study seeks to assess the efficacy of a web-based patient decision aid for lung cancer screening, www.shouldiscreen.com.
Reviewing Lung Cancer Screening: The Who, Where, When, Why, and How. [2019]Lung cancer screening with annual low-dose computed tomography (CT) decreases lung cancer mortality in high-risk patients, as defined by smoking history (> 30 pack-years) and age (55-74 years). Risks to screening include overdiagnosis, anxiety about indeterminate nodules, and radiation exposure. To be effective, lung cancer screening must combine individualized risk assessment, shared decision-making, smoking cessation, structured reporting, high quality and multi-specialty cancer care, and reliable follow-up; a multidisciplinary approach is crucial. Specialty organizations have outlined both the components of high quality lung cancer screening programs and the proposed metrics that programs should track. Long-term outcomes of lung cancer screening in the general population, further refinement of who to screen, and use of biomarkers for early cancer detection are ongoing research questions.