Giving Information Systematically and Transparently in Lung and GI Cancer Phase 2
NCT ID: NCT04179305
Last Updated: 2023-04-24
Study Results
Results available
Outcome measurements, participant flow, baseline characteristics, and adverse events have been published for this study.
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Recruitment Status
COMPLETED
Clinical Phase
NA
Total Enrollment
37 participants
Study Classification
INTERVENTIONAL
Study Start Date
2020-10-25
Study Completion Date
2023-01-19
Brief Summary
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When advanced disease progresses, there comes a time when an oncologists must explain to their patients that they only have months left to live. During these discussions the oncologist attempts to explain to the patient their prognoses and what it means for them going forward. However our prior studies shown that even when patients only have months left to live, most do not understand that their cancer is incurable and that it is late/end-stage.
Dying cancer patients who fully understand their prognosis are able to make more informed decisions and are therefore more likely to engage in advanced care planning, and receive care what in consistent with their values and preferences. They are also in a better position to avoid burdensome, non-beneficial care. The investigator developed Oncolo-GIST in order to help increase the number of patients who fully understand their prognosis and its implications.
Oncolo-GIST is an intervention aimed at enhancing clinicians' communication with patients by teaching them to relay information both sensitively and using simple terminology. The Oncolo-GIST training will provide instruction in areas such as how to introduce the topic of prognosis (describe scan results as "worse"), how to phrase the prognosis itself ("likely months, not years"), how to explain expected treatment outcomes (e.g., "not expected to be cured by treatment") and how to describe expected treatments impact on quality of life - that is, whether the anticancer treatment is likely to make them feel overall better or worse. The training materials consist of a manual and a set of videos that act out situations described in the manual.
The second phase of this study will be a randomized controlled trial. The investigator will recruit (n=50) adults with metastatic GI or lung cancers with scan results that reveal progression (worsened disease) on an initial systemic treatment; that is, patients whose life-expectancy can reliably be estimated to be months, not years. Medical oncologists (n=4) who care for these patients will also be consented for study participation and half (n=2) will be randomized to receive the Oncolo-GIST training.
Patients will be assessed by trained research staff in the week prior to a scheduled meeting with their oncologist to discuss the scan results. This will provide patients' baseline levels of prognostic understanding and enable the investigator to determine how the intervention relates to pre-post scan visit changes in prognostic understanding. Patients will be assessed post-scan within a week of that progressive scan visit.
The assessment battery that will be administered at these time-points will measure the patient's degree of prognostic understanding, the primary outcome of the study. Other outcomes that will be measured by the assessment battery include the patients quality of life, therapeutic alliances of the patient, whether or not a DNR was ordered, the care received by the patient, whether or not the patient preferred greater quality of longer quantity of life, and whether or not the patients received "value-consistent" care.
Dying cancer patients who fully understand their prognosis are able to make more informed decisions and are therefore more likely to engage in advanced care planning, and receive care what in consistent with their values and preferences. They are also in a better position to avoid burdensome, non-beneficial care. The investigator developed Oncolo-GIST in order to help increase the number of patients who fully understand their prognosis and its implications.
Oncolo-GIST is an intervention aimed at enhancing clinicians' communication with patients by teaching them to relay information both sensitively and using simple terminology. The Oncolo-GIST training will provide instruction in areas such as how to introduce the topic of prognosis (describe scan results as "worse"), how to phrase the prognosis itself ("likely months, not years"), how to explain expected treatment outcomes (e.g., "not expected to be cured by treatment") and how to describe expected treatments impact on quality of life - that is, whether the anticancer treatment is likely to make them feel overall better or worse. The training materials consist of a manual and a set of videos that act out situations described in the manual.
The second phase of this study will be a randomized controlled trial. The investigator will recruit (n=50) adults with metastatic GI or lung cancers with scan results that reveal progression (worsened disease) on an initial systemic treatment; that is, patients whose life-expectancy can reliably be estimated to be months, not years. Medical oncologists (n=4) who care for these patients will also be consented for study participation and half (n=2) will be randomized to receive the Oncolo-GIST training.
Patients will be assessed by trained research staff in the week prior to a scheduled meeting with their oncologist to discuss the scan results. This will provide patients' baseline levels of prognostic understanding and enable the investigator to determine how the intervention relates to pre-post scan visit changes in prognostic understanding. Patients will be assessed post-scan within a week of that progressive scan visit.
The assessment battery that will be administered at these time-points will measure the patient's degree of prognostic understanding, the primary outcome of the study. Other outcomes that will be measured by the assessment battery include the patients quality of life, therapeutic alliances of the patient, whether or not a DNR was ordered, the care received by the patient, whether or not the patient preferred greater quality of longer quantity of life, and whether or not the patients received "value-consistent" care.
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Detailed Description
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Despite exciting recent advances in cancer treatments, there still, ultimately, comes a time when advanced disease progresses, and patients can reliably be expected to have months, not years, left to live. For patients with metastatic cancers studied in the investigator's Coping with Cancer NCI R01s, this comes after progression on 1st- or 2nd-line therapy -- be it chemo-, immune-, or targeted therapy. Prior studies conducted by the investigator have found that oncologists can reliably predict when patients have only months to live (e.g., remarkable agreement between oncologist estimates of months to live shared with patients and patients' actual survival of months). By contrast, patients appear largely unaware of their prognosis. For example, 5% of patients a median of 5 months from death, accurately understood they had incurable, late/end-stage, terminal cancer, and likely only months to live. Dying cancer patients appear to lack the prognostic understanding needed to make informed choices.
Patients who grasp that they are dying (e.g., the 8.6% who "get the gist" that they likely have months to live), relative to those who do not, have been shown to have: a) higher rates of advance care planning (ACP), b) receive less burdensome, unbeneficial care (e.g., fewer intensive care unit, ICU, stays, less cardiopulmonary resuscitation, CPR), and c) more value-consistent care. The investigator has found that patient prognostic understanding is improved by oncologist discussions of life-expectancy, but despite 71% of patients wanting to discuss prognosis with their oncologists (83% adult cancer patients thought prognostic information was extremely/very important), only 17.6% of cancer patients within months of death reported that they had discussed prognosis with their oncologist. Not only do oncologists appear to discuss prognosis less than patients want them to, but even when prognostic discussions do occur, the investigator has found that some approaches (e.g., matter-of-fact) are more effective than others (e.g., vague) for promoting patients' prognostic understanding. Thus, prior work identifies a need to improve communication to promote patient prognostic understanding in a way that oncologists will likely learn, accept, use, and possibly implement more broadly in clinical practice.
To address this need, the investigator developed the "Giving Information Simply \&Transparently" (GIST), Oncolo-GIST intervention -- a manualized oncologist communication intervention that simplifies how to impart prognostic information by focusing on 4 basic steps: 1) Giving scan information, 2) Informing prognosis, 3) Strategizing sensitively, and 4) Transparently asking what the patient heard. Unlike traditional emphasis on numerical or medical details, the Oncolo-GIST approach is based on Reyna's Fuzzy-Trace Theory of decision-making, which emphasizes the need for an understanding of the bottom-line gist of a situation. The Oncolo-GIST approach distills prognostic discussions to clear communication of end-of-life (EoL) decision-making essentials (e.g., life-expectancy). 3 specific aims of the Oncolo-GIST approach will be tested in 2 phases:
Phase 1 will consist of two parts: 1) An interview of key stakeholders/key informants regarding Oncolo-GIST Version 1.0 in order to inform refinements to produce Oncolo-GIST Version 2.0. 2) An open trial of Oncolo-GIST Version 1.0 to inform refinements to produce Oncolo-GIST Version 2.0.
Phase 2 will involve a cluster randomized controlled trial (RCT) of Oncolo-GIST Version 2.0 on 50 patients with metastatic cancers worse on at least 1 line of therapy (chemo-, immune-, targeted), whose oncologists do not expect them to survive 12 months. Patients will be assessed in the week prior to their scheduled scan, within 1 week of the clinic visit in which progressive scan results are discussed, and then 2 and 4 months later to explore intervention effects on primary and secondary outcomes, respectively. Oncologists will be assessed in the week following that same clinic visit to obtain their impressions of the discussion of prognosis and the patient's prognostic understanding.
In Phase 2, for the pilot cluster RCT, the investigator will recruit (n=50) adults with metastatic GI or lung cancers with scan results that reveal progression (worsened disease) on an initial systemic treatment; that is, patients whose life-expectancy can reliably be estimated to be months, as opposed to years. Medical oncologists (n=4) who care for these patients will also be consented for study participation and half (n=2) will be randomized to receive the Oncolo-GIST training. The investigator expects 12-13 patients will be clustered within each of the 4 oncologists. Hierarchical Linear Modeling (HLM) techniques will be employed to address the non-independence of patient assessments within each cluster. Patients (n=25) will be seen by either an Oncolo-GIST trained oncologist or an oncologist not trained in the intervention; that is, usual care (n=25). Patients in both arms will have met the same eligibility criteria (i.e., have similar prognoses).
Patients will be assessed by trained research staff in the week prior to a scheduled meeting with their oncologist to discuss the scan results. This will provide patients' baseline levels of prognostic understanding and enable the investigator to determine how the intervention relates to pre-post scan visit changes in prognostic understanding. Patients will be assessed post-scan within a week of that progressive scan visit. Although not all patients are expected to die within the study observation period, given a median life expectancy of \~4-5 months from baseline, the investigator expects nearly half of the enrolled patients will die 4 months from baseline, and that the vast majority will die during the study observation period of 12 months. Thus, for all patients enrolled in this study, the medical care that they receive can reasonably be considered end-of-life care, whether they die during the study observation period or not.
The primary outcome is the patient's degree of prognostic understanding, measured using the investigator's validated 4-item assessment. The investigator will determine if the patient understood the scan results to be "worse" and their understanding of expected outcomes of treatments proffered (re: curability, survival, quality of life). Outcomes will also include whether a DNR order was completed for the patient, the McGill Quality of Life measure, performance status (e.g., Eastern Cooperative Oncology Group, ECOG), and care received (e.g., anticancer, intensive, palliative care). Treatment preferences will be assessed using the SUPPORT question regarding quality vs. quantity of life, which will be used to compare with actual EoL care received to operationalize "value-consistent" care. The investigator's validated Human Connection scale will assess therapeutic alliances from both the patient and oncologist perspective, and the investigator will assess oncologists' sense of how the scan discussion went (e.g., degree to which they think they communicated effectively, and that the patient understood them and had an accurate prognostic understanding). Demographic/background information (e.g., age, race/ethnicity, sex, education) and DNR documentation will be obtained from subject self-report at baseline and the patient's medical records. Previously validated measures will assess potential confounding influences such as time from diagnosis, prior discussions of prognosis, and health literacy using the REALM. Preferences regarding medical decision-making (e.g., an active vs. passive role in deciding the best course of treatment), patients' Religious Beliefs in EoL Care (RBEC), and the question "If your doctor knew how long you had left to live, would you want him/her to tell you?" will be assessed.
Hierarchical Linear Modeling (HLM) will be used to evaluate intervention effects. HLM is statistically appropriate because it accounts for the clustering of patients within oncologists, creating non- independence of clustered assessments. HLM will model oncologists as a random effect as has been done in prior RCTs. Baseline covariates known to affect study outcomes (e.g., patient health literacy) will be included in models to increase the precision of effect size estimates. This will provide a preliminary effect size estimate of Oncolo-GIST Version 2.0's ability to improve patients' prognostic understanding for a future, larger study. Linear and logistic regression models will estimate effects of the Oncolo-GIST intervention on secondary and exploratory outcomes.
The details for Phase 1 of the study are enumerated in a separate record marked "Giving Information Systematically and Transparently in Lung and GI Cancer Phase 1" (Oncolo-GIST P1) with NCT # NCT04158908.
Patients who grasp that they are dying (e.g., the 8.6% who "get the gist" that they likely have months to live), relative to those who do not, have been shown to have: a) higher rates of advance care planning (ACP), b) receive less burdensome, unbeneficial care (e.g., fewer intensive care unit, ICU, stays, less cardiopulmonary resuscitation, CPR), and c) more value-consistent care. The investigator has found that patient prognostic understanding is improved by oncologist discussions of life-expectancy, but despite 71% of patients wanting to discuss prognosis with their oncologists (83% adult cancer patients thought prognostic information was extremely/very important), only 17.6% of cancer patients within months of death reported that they had discussed prognosis with their oncologist. Not only do oncologists appear to discuss prognosis less than patients want them to, but even when prognostic discussions do occur, the investigator has found that some approaches (e.g., matter-of-fact) are more effective than others (e.g., vague) for promoting patients' prognostic understanding. Thus, prior work identifies a need to improve communication to promote patient prognostic understanding in a way that oncologists will likely learn, accept, use, and possibly implement more broadly in clinical practice.
To address this need, the investigator developed the "Giving Information Simply \&Transparently" (GIST), Oncolo-GIST intervention -- a manualized oncologist communication intervention that simplifies how to impart prognostic information by focusing on 4 basic steps: 1) Giving scan information, 2) Informing prognosis, 3) Strategizing sensitively, and 4) Transparently asking what the patient heard. Unlike traditional emphasis on numerical or medical details, the Oncolo-GIST approach is based on Reyna's Fuzzy-Trace Theory of decision-making, which emphasizes the need for an understanding of the bottom-line gist of a situation. The Oncolo-GIST approach distills prognostic discussions to clear communication of end-of-life (EoL) decision-making essentials (e.g., life-expectancy). 3 specific aims of the Oncolo-GIST approach will be tested in 2 phases:
Phase 1 will consist of two parts: 1) An interview of key stakeholders/key informants regarding Oncolo-GIST Version 1.0 in order to inform refinements to produce Oncolo-GIST Version 2.0. 2) An open trial of Oncolo-GIST Version 1.0 to inform refinements to produce Oncolo-GIST Version 2.0.
Phase 2 will involve a cluster randomized controlled trial (RCT) of Oncolo-GIST Version 2.0 on 50 patients with metastatic cancers worse on at least 1 line of therapy (chemo-, immune-, targeted), whose oncologists do not expect them to survive 12 months. Patients will be assessed in the week prior to their scheduled scan, within 1 week of the clinic visit in which progressive scan results are discussed, and then 2 and 4 months later to explore intervention effects on primary and secondary outcomes, respectively. Oncologists will be assessed in the week following that same clinic visit to obtain their impressions of the discussion of prognosis and the patient's prognostic understanding.
In Phase 2, for the pilot cluster RCT, the investigator will recruit (n=50) adults with metastatic GI or lung cancers with scan results that reveal progression (worsened disease) on an initial systemic treatment; that is, patients whose life-expectancy can reliably be estimated to be months, as opposed to years. Medical oncologists (n=4) who care for these patients will also be consented for study participation and half (n=2) will be randomized to receive the Oncolo-GIST training. The investigator expects 12-13 patients will be clustered within each of the 4 oncologists. Hierarchical Linear Modeling (HLM) techniques will be employed to address the non-independence of patient assessments within each cluster. Patients (n=25) will be seen by either an Oncolo-GIST trained oncologist or an oncologist not trained in the intervention; that is, usual care (n=25). Patients in both arms will have met the same eligibility criteria (i.e., have similar prognoses).
Patients will be assessed by trained research staff in the week prior to a scheduled meeting with their oncologist to discuss the scan results. This will provide patients' baseline levels of prognostic understanding and enable the investigator to determine how the intervention relates to pre-post scan visit changes in prognostic understanding. Patients will be assessed post-scan within a week of that progressive scan visit. Although not all patients are expected to die within the study observation period, given a median life expectancy of \~4-5 months from baseline, the investigator expects nearly half of the enrolled patients will die 4 months from baseline, and that the vast majority will die during the study observation period of 12 months. Thus, for all patients enrolled in this study, the medical care that they receive can reasonably be considered end-of-life care, whether they die during the study observation period or not.
The primary outcome is the patient's degree of prognostic understanding, measured using the investigator's validated 4-item assessment. The investigator will determine if the patient understood the scan results to be "worse" and their understanding of expected outcomes of treatments proffered (re: curability, survival, quality of life). Outcomes will also include whether a DNR order was completed for the patient, the McGill Quality of Life measure, performance status (e.g., Eastern Cooperative Oncology Group, ECOG), and care received (e.g., anticancer, intensive, palliative care). Treatment preferences will be assessed using the SUPPORT question regarding quality vs. quantity of life, which will be used to compare with actual EoL care received to operationalize "value-consistent" care. The investigator's validated Human Connection scale will assess therapeutic alliances from both the patient and oncologist perspective, and the investigator will assess oncologists' sense of how the scan discussion went (e.g., degree to which they think they communicated effectively, and that the patient understood them and had an accurate prognostic understanding). Demographic/background information (e.g., age, race/ethnicity, sex, education) and DNR documentation will be obtained from subject self-report at baseline and the patient's medical records. Previously validated measures will assess potential confounding influences such as time from diagnosis, prior discussions of prognosis, and health literacy using the REALM. Preferences regarding medical decision-making (e.g., an active vs. passive role in deciding the best course of treatment), patients' Religious Beliefs in EoL Care (RBEC), and the question "If your doctor knew how long you had left to live, would you want him/her to tell you?" will be assessed.
Hierarchical Linear Modeling (HLM) will be used to evaluate intervention effects. HLM is statistically appropriate because it accounts for the clustering of patients within oncologists, creating non- independence of clustered assessments. HLM will model oncologists as a random effect as has been done in prior RCTs. Baseline covariates known to affect study outcomes (e.g., patient health literacy) will be included in models to increase the precision of effect size estimates. This will provide a preliminary effect size estimate of Oncolo-GIST Version 2.0's ability to improve patients' prognostic understanding for a future, larger study. Linear and logistic regression models will estimate effects of the Oncolo-GIST intervention on secondary and exploratory outcomes.
The details for Phase 1 of the study are enumerated in a separate record marked "Giving Information Systematically and Transparently in Lung and GI Cancer Phase 1" (Oncolo-GIST P1) with NCT # NCT04158908.
Conditions
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Critical Illness
Oncology
Communication
Study Design
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Allocation Method
NON_RANDOMIZED
Intervention Model
PARALLEL
Non-randomized controlled trial
Primary Study Purpose
SUPPORTIVE_CARE
Blinding Strategy
SINGLE
Participants
Study Groups
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Oncolo-GIST Arm - Patients
Patients assigned to this arm will discuss scan results revealing progressive disease with an Oncolo-GIST trained physician.
Oncolo-GIST: Behavioral: Oncolo-GIST Oncolo-GIST is a brief, manualized communication intervention that guides oncologists in "gist communication" by itemizing 4 key steps in the process of imparting prognostic information.
Topics covered include:
Principles of introducing prognosis in the setting of worsened scan results Coupling communicating realistic prognoses with psychological support (e.g., saying "average life-expectancy is months…" with emphasizing that the oncology team "will always provide care for you") Addressing informational needs and psychological reactions Applying proven techniques for supporting patients who are reluctant to discuss prognosis.
Group Type
EXPERIMENTAL
Oncolo-GIST
Intervention Type
BEHAVIORAL
Behavioral: Oncolo-GIST Oncolo-GIST is a brief, manualized communication intervention that guides oncologists in "gist communication" by itemizing 4 key steps in the process of imparting prognostic information.
Topics covered include:
Principles of introducing prognosis in the setting of worsened scan results Coupling communicating realistic prognoses with psychological support (e.g., saying "average life-expectancy is months…" with emphasizing that the oncology team "will always provide care for you") Addressing informational needs and psychological reactions Applying proven techniques for supporting patients who are reluctant to discuss prognosis.
The 4-step guide will include brief video-clips of demonstrating each "talking point" with a standardized patient, including ideal scenarios, common pitfalls to avoid, and how to respond to patient reactions that are particularly challenging, such as responding to optimism, death anxiety, and reliance on faith.
Usual Care Arm - Patients
Patients assigned to this arm will will discuss scan results revealing progressive disease with a physician that was not trained with the Oncolo-GIST intervention.
Usual Care Arm: Oncologists will provide care in non-specific manner.
Group Type
PLACEBO_COMPARATOR
Usual Care Arm
Intervention Type
BEHAVIORAL
Oncologists will provide care in non-specific manner.
Oncolo-GIST Arm - Physicians
Physicians assigned to this arm will receive the Oncolo-GIST training intervention.
Group Type
EXPERIMENTAL
Oncolo-GIST
Intervention Type
BEHAVIORAL
Behavioral: Oncolo-GIST Oncolo-GIST is a brief, manualized communication intervention that guides oncologists in "gist communication" by itemizing 4 key steps in the process of imparting prognostic information.
Topics covered include:
Principles of introducing prognosis in the setting of worsened scan results Coupling communicating realistic prognoses with psychological support (e.g., saying "average life-expectancy is months…" with emphasizing that the oncology team "will always provide care for you") Addressing informational needs and psychological reactions Applying proven techniques for supporting patients who are reluctant to discuss prognosis.
The 4-step guide will include brief video-clips of demonstrating each "talking point" with a standardized patient, including ideal scenarios, common pitfalls to avoid, and how to respond to patient reactions that are particularly challenging, such as responding to optimism, death anxiety, and reliance on faith.
Usual Care Arm - Physicians
Physicians assigned to this arm will not receive the Oncolo-GIST training intervention.
Group Type
PLACEBO_COMPARATOR
Usual Care Arm
Intervention Type
BEHAVIORAL
Oncologists will provide care in non-specific manner.
Interventions
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Oncolo-GIST
Behavioral: Oncolo-GIST Oncolo-GIST is a brief, manualized communication intervention that guides oncologists in "gist communication" by itemizing 4 key steps in the process of imparting prognostic information.
Topics covered include:
Principles of introducing prognosis in the setting of worsened scan results Coupling communicating realistic prognoses with psychological support (e.g., saying "average life-expectancy is months…" with emphasizing that the oncology team "will always provide care for you") Addressing informational needs and psychological reactions Applying proven techniques for supporting patients who are reluctant to discuss prognosis.
The 4-step guide will include brief video-clips of demonstrating each "talking point" with a standardized patient, including ideal scenarios, common pitfalls to avoid, and how to respond to patient reactions that are particularly challenging, such as responding to optimism, death anxiety, and reliance on faith.
Intervention Type
BEHAVIORAL
Usual Care Arm
Oncologists will provide care in non-specific manner.
Intervention Type
BEHAVIORAL
Eligibility Criteria
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Inclusion Criteria
* Specialize in Lung and GI cancers
* Currently provide care at the WCM Lung and GI cancer clinics
* Fluent in English
* Receiving ongoing care (≥ 2 visits) that includes regular scans
* Progression on at least 1 line of systemic cancer therapy
* Prognosis from an oncologist of less than 12 months
* Receiving care from an oncologist participating in the Oncolo-GIST study
* Fluent in English
* Currently provide care at the WCM Lung and GI cancer clinics
* Fluent in English
* Receiving ongoing care (≥ 2 visits) that includes regular scans
* Progression on at least 1 line of systemic cancer therapy
* Prognosis from an oncologist of less than 12 months
* Receiving care from an oncologist participating in the Oncolo-GIST study
* Fluent in English
Exclusion Criteria
* Does not specialize in Lung and GI cancers
* Does not currently provide care at the WCM Lung and GI cancer clinics
* Not fluent in English
Patients
* Does not specialize in Lung and GI cancers
* Does not currently provide care at the WCM Lung and GI cancer clinics
* Not fluent in English
* Does not currently provide care at the WCM Lung and GI cancer clinics
* Not fluent in English
Patients
* Does not specialize in Lung and GI cancers
* Does not currently provide care at the WCM Lung and GI cancer clinics
* Not fluent in English
Minimum Eligible Age
18 Years
Eligible Sex
ALL
Accepts Healthy Volunteers
No
Sponsors
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National Institute of Nursing Research (NINR)
NIH
Sponsor Role
collaborator
Weill Medical College of Cornell University
OTHER
Sponsor Role
lead
Responsible Party
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Responsibility Role
SPONSOR
Principal Investigators
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Holly G Prigerson, PhD
Role: PRINCIPAL_INVESTIGATOR
Weill Medical College of Cornell University
Locations
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Weill Cornell Medical Center
New York, New York, United States
Site Status
Countries
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United States
References
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Lambden J, Zhang B, Friedlander R, Prigerson HG. Accuracy of Oncologists' Life-Expectancy Estimates Recalled by Their Advanced Cancer Patients: Correlates and Outcomes. J Palliat Med. 2016 Dec;19(12):1296-1303. doi: 10.1089/jpm.2016.0121. Epub 2016 Aug 30.
Reference Type
BACKGROUND
Enzinger AC, Zhang B, Schrag D, Prigerson HG. Outcomes of Prognostic Disclosure: Associations With Prognostic Understanding, Distress, and Relationship With Physician Among Patients With Advanced Cancer. J Clin Oncol. 2015 Nov 10;33(32):3809-16. doi: 10.1200/JCO.2015.61.9239. Epub 2015 Oct 5.
Reference Type
BACKGROUND
Epstein AS, Prigerson HG, O'Reilly EM, Maciejewski PK. Discussions of Life Expectancy and Changes in Illness Understanding in Patients With Advanced Cancer. J Clin Oncol. 2016 Jul 10;34(20):2398-403. doi: 10.1200/JCO.2015.63.6696. Epub 2016 May 23.
Reference Type
BACKGROUND
Mack JW, Weeks JC, Wright AA, Block SD, Prigerson HG. End-of-life discussions, goal attainment, and distress at the end of life: predictors and outcomes of receipt of care consistent with preferences. J Clin Oncol. 2010 Mar 1;28(7):1203-8. doi: 10.1200/JCO.2009.25.4672. Epub 2010 Feb 1.
Reference Type
BACKGROUND
Wright AA, Zhang B, Keating NL, Weeks JC, Prigerson HG. Associations between palliative chemotherapy and adult cancer patients' end of life care and place of death: prospective cohort study. BMJ. 2014 Mar 4;348:g1219. doi: 10.1136/bmj.g1219.
Reference Type
BACKGROUND
Prigerson HG. Socialization to dying: social determinants of death acknowledgement and treatment among terminally ill geriatric patients. J Health Soc Behav. 1992 Dec;33(4):378-95.
Reference Type
BACKGROUND
Wright AA, Zhang B, Ray A, Mack JW, Trice E, Balboni T, Mitchell SL, Jackson VA, Block SD, Maciejewski PK, Prigerson HG. Associations between end-of-life discussions, patient mental health, medical care near death, and caregiver bereavement adjustment. JAMA. 2008 Oct 8;300(14):1665-73. doi: 10.1001/jama.300.14.1665.
Reference Type
BACKGROUND
Mack JW, Fasciano KM, Block SD. Communication About Prognosis With Adolescent and Young Adult Patients With Cancer: Information Needs, Prognostic Awareness, and Outcomes of Disclosure. J Clin Oncol. 2018 Jun 20;36(18):1861-1867. doi: 10.1200/JCO.2018.78.2128. Epub 2018 Apr 23.
Reference Type
BACKGROUND
Reyna VF. Theories of medical decision making and health: an evidence-based approach. Med Decis Making. 2008 Nov-Dec;28(6):829-33. doi: 10.1177/0272989X08327069. No abstract available.
Reference Type
BACKGROUND
Elsayyad A. Informed consent for comparative effectiveness trials. N Engl J Med. 2014 May 15;370(20):1958-9. doi: 10.1056/NEJMc1403310. No abstract available.
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Spellecy R, Tarima S, Denzen E, Moore H, Abhyankar S, Dawson P, Foley A, Gersten I, Horwitz M, Idossa L, Joffe S, Kamani N, King R, Lazaryan A, Morris L, Horowitz MM, Majhail NS. Easy-to-Read Informed Consent Form for Hematopoietic Cell Transplantation Clinical Trials: Results from the Blood and Marrow Transplant Clinical Trials Network 1205 Study. Biol Blood Marrow Transplant. 2018 Oct;24(10):2145-2151. doi: 10.1016/j.bbmt.2018.04.014. Epub 2018 Apr 18.
Reference Type
BACKGROUND
Tulsky JA, Arnold RM, Alexander SC, Olsen MK, Jeffreys AS, Rodriguez KL, Skinner CS, Farrell D, Abernethy AP, Pollak KI. Enhancing communication between oncologists and patients with a computer-based training program: a randomized trial. Ann Intern Med. 2011 Nov 1;155(9):593-601. doi: 10.7326/0003-4819-155-9-201111010-00007.
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Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Document Type: Informed Consent Form
Other Identifiers
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19-07020392-Phase2
Identifier Type: -
Identifier Source: org_study_id
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