This clinical trial compares the use of a new screening tool designed to evaluate patients' information needs, preferences, and illness understanding to the usual care to improve illness understanding in patients with lung cancer that has spread from where it first started (primary site) to other places in the body (metastatic) or for which no curative treatment is currently available (incurable). Goal concordant care is a model of care that aligns a patient's medical care with their values, preferences, and goals. Often, patients may not fully understand their illness and prognosis, but this information is important so that they can make fully informed decisions regarding their care that are consistent with their values, preferences, and goals. Completing the Information Needs, Preferences, and Understanding Trial (INPUT) screening tool may allow for more frequent and regular discussions regarding disease status and treatment goals, ultimately resulting in improved patient illness understanding and goal concordant care for patients with metastatic or incurable lung cancer.
Primary Objectives To estimate the within group effect of perception of curability over 3 months in both the systematic screening group and the usual care group among patients with metastatic or incurable lung cancer who present to the thoracic medical oncology clinic at The University of Texas MD Anderson Cancer Center.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SUPPORTIVE_CARE
Masking
NONE
Enrollment
100
Other Best Practice best practice, standard of care, standard of care, standard of care, standard therapy Undergo standard of care oncology follow-up visits
Ancillary studies
MD Anderson Cancer Center
Houston, Texas, United States
RECRUITINGChange in illness understanding
Binary curability status is derived from the response to the INPUT Screening survey question #2. Will be similarly modeled by mixed-effect logistic regression.
Time frame: At 3 months
Difference between treatment groups in illness understanding
Based upon the Prigerson Measure of Illness Understanding. The Likert-scale and composite score responses (excluding the acceptability of screening tool assessment) will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts.
Time frame: At 3 and 6 months
Quality of communication
Assessed via the Quality of Communication questionnaire. The Likert-scale and composite score responses will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts, without adjustment for multiple comparisons since this is a pilot study. Baseline variables which show evidence of differences may be utilized as model covariates to control for associated bias. Binary responses (including the primary objective) will be similarly modeled by mixed-effect logistic regression. Survey responses which are neither Likert, composite, nor binary, may have categories collapsed such that they can be analyzed as binary.
Time frame: At 3 and 6 months
Feeling heard and understood by healthcare team
Assessed via the Feeling Heard and Understood scale. The Likert-scale and composite score responses will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts, without adjustment for multiple comparisons since this is a pilot study. Baseline variables which show evidence of differences may be utilized as model covariates to control for associated bias. Binary responses (including the primary objective) will be similarly modeled by mixed-effect logistic regression. Survey responses which are neither Likert, composite, nor binary, may have categories collapsed such that they can be analyzed as binary.
Time frame: At 3 and 6 months
Death-related anxiety
Assessed via the Death and Dying Distress scale. The Likert-scale and composite score responses will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts, without adjustment for multiple comparisons since this is a pilot study. Baseline variables which show evidence of differences may be utilized as model covariates to control for associated bias. Binary responses (including the primary objective) will be similarly modeled by mixed-effect logistic regression. Survey responses which are neither Likert, composite, nor binary, may have categories collapsed such that they can be analyzed as binary.
Time frame: At 3 and 6 months
Anxiety related symptoms
Assessed via the Generalized Anxiety Disorder scale. The Likert-scale and composite score responses will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts, without adjustment for multiple comparisons since this is a pilot study. Baseline variables which show evidence of differences may be utilized as model covariates to control for associated bias. Binary responses (including the primary objective) will be similarly modeled by mixed-effect logistic regression. Survey responses which are neither Likert, composite, nor binary, may have categories collapsed such that they can be analyzed as binary.
Time frame: At 3 and 6 months
Depression
Assessed via the Patient Health Questionnaire, 9 items. The Likert-scale and composite score responses will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts, without adjustment for multiple comparisons since this is a pilot study. Baseline variables which show evidence of differences may be utilized as model covariates to control for associated bias. Binary responses (including the primary objective) will be similarly modeled by mixed-effect logistic regression. Survey responses which are neither Likert, composite, nor binary, may have categories collapsed such that they can be analyzed as binary.
Time frame: At 3 and 6 months
Health related quality of life
Assessed via the Functional Assessment of Cancer Therapy - General. The Likert-scale and composite score responses will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts, without adjustment for multiple comparisons since this is a pilot study. Baseline variables which show evidence of differences may be utilized as model covariates to control for associated bias. Binary responses (including the primary objective) will be similarly modeled by mixed-effect logistic regression. Survey responses which are neither Likert, composite, nor binary, may have categories collapsed such that they can be analyzed as binary.
Time frame: At 3 and 6 months
Symptoms of advanced cancer
Assessed via the Edmonton Symptom Assessment System. The Likert-scale and composite score responses will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts, without adjustment for multiple comparisons since this is a pilot study. Baseline variables which show evidence of differences may be utilized as model covariates to control for associated bias. Binary responses (including the primary objective) will be similarly modeled by mixed-effect logistic regression. Survey responses which are neither Likert, composite, nor binary, may have categories collapsed such that they can be analyzed as binary.
Time frame: At 3 and 6 months
Acceptability of screening tool
Assessed via the Ease of Use, Acceptability, Usefulness, and Safety questionnaire.
Time frame: At 3 months
Goals of care
Assessed via Goals of Care. The Likert-scale and composite score responses will be modeled by mixed-effect analysis of variance with relation to treatment group and time point, with interaction. Change from baseline at each time point will be assessed by contrasts, without adjustment for multiple comparisons since this is a pilot study. Baseline variables which show evidence of differences may be utilized as model covariates to control for associated bias. Binary responses (including the primary objective) will be similarly modeled by mixed-effect logistic regression. Survey responses which are neither Likert, composite, nor binary, may have categories collapsed such that they can be analyzed as binary.
Time frame: At 3 and 6 months
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