Outcomes of Prognostic Disclosure: Associations With Prognostic Understanding, Distress, and Relationship With Physician Among Patients With Advanced Cancer

Enzinger, Andrea C.; Zhang, Baohui; Schrag, Deborah; Prigerson, Holly G.

doi:10.1200/jco.2015.61.9239

Cited by 315 publications

(336 citation statements)

References 57 publications

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“…Despite this preference, in the same sample of terminally ill patients, only 18% reported that their oncologist provided them with a prognostic estimate. 1 A realistic sense of life expectancy has been shown to facilitate end-of-life discussions and planning, which leads to lower medical care costs, avoidance of unnecessarily aggressive care, and improved quality of death. [2][3][4][5][6] Nevertheless, physicians are reluctant to communicate a lifeexpectancy estimate to their patients.…”

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confidence: 99%

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Accuracy of Oncologists' Life-Expectancy Estimates Recalled by Their Advanced Cancer Patients: Correlates and Outcomes

LambdenJason

ZhangBaohui

FriedlanderRobert

et al. 2016

Journal of Palliative Medicine

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Background: Oncologists are often reluctant to discuss life-expectancy estimates with their patients because of concerns about their inaccuracy and limited evidence regarding benefits. Objective: Determine oncologist accuracy in predicting their advanced cancer patients' life expectancy and correlates associated with accuracy. Design: Multicenter prospective, longitudinal study of patients with advanced cancer, assessed once at baseline and followed to death. At baseline, patients were asked whether their oncologist had provided them with a lifeexpectancy estimate. Setting/Subjects: Eighty-five patients with advanced cancer recruited from outpatient cancer clinics. Measurements: Patients' baseline sociodemographic and time to death, and clinical characteristics were examined to determine their associations with the accuracy of the oncologists' life-expectancy estimates as recalled by their patients. Results: Seventy-four percent (63/85) of patients recalled that physician life-expectancy estimates were accurate to within a year; estimates were most accurate when patients had 9-12 months to live. Factors significantly ( p < 0.05) positively associated with oncologists' greater accuracy to within a year were the patient's age, recruitment from a community-based oncology clinic, poor performance status, and quality-of-life at baseline. Oncologists' prognoses that were accurate to within a year were associated with greater likelihood of patients, at baseline, acknowledging that they were terminally ill (OR = 12.20, 95% CI = 2.24-66.59), engaging in an end-of-life discussion (OR = 4.22, 95% CI = 1.45-12.29), completing a do-not-resuscitate (DNR) order (OR = 2.94, 95% CI = 1.03-8.41), a lower likelihood of using palliative chemotherapy (OR = 0.30, 95% CI = 0.11-0.85), and clinical trial enrollment (OR = 0.09, 95% CI = 0.02-0.50). Conclusions: Oncologists are able to estimate their patients' life expectancy to within a year. Accuracy to within a year is associated with higher rates of DNR order completion, advance care planning, and lower likelihood of chemotherapy use near death.

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confidence: 99%

“…1,2 In a study of terminally ill cancer patients who were asked: ''If your doctor knew how long you had left to live, would you want him/her to tell you?'' Seventy-one percent responded ''yes.''…”

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confidence: 99%

Accuracy of Oncologists' Life-Expectancy Estimates Recalled by Their Advanced Cancer Patients: Correlates and Outcomes

LambdenJason

ZhangBaohui

FriedlanderRobert

et al. 2016

Journal of Palliative Medicine

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“…In this study, 590 patients with advanced cancer were analyzed, and patients for whom their prognosis was disclosed had a more realistic understanding of life expectancy than those for whom it was not (median patient self-estimates of life expectancy 12 months versus 48 months). Moreover, patients with a realistic understanding of life expectancy preferred comfort-oriented over life-prolonging care, with a higher likelihood of a do-not-resuscitate order without deteriorating the patients' emotional well-being or the patient-physician relationship [91]. Despite the limitation of being an observational study, however, this study produced meaningful indings for the association between prognosis disclosure and advance care planning (ACP).…”

Section: Clinical Utility Of Prognostic Disclosurementioning

confidence: 74%

“…To the best of our knowledge, there are no clinical trials, but a few observational studies have been reported. In 2015, Enzinger et al reported on a large prospective cohort study, "Coping with Cancer" [91]. In this study, 590 patients with advanced cancer were analyzed, and patients for whom their prognosis was disclosed had a more realistic understanding of life expectancy than those for whom it was not (median patient self-estimates of life expectancy 12 months versus 48 months).…”

Section: Clinical Utility Of Prognostic Disclosurementioning

confidence: 99%

Prognosis Prediction Models and their Clinical Utility in Palliative Care

Uneno¹,

Kanai²

2017

Highlights on Several Underestimated Topics in Palliative Care

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Prognosis prediction is a clinically relevant issue to facilitate optimal decision-making for both physicians and patients with cancer. Many previous studies revealed that prognosis prediction based on the physician's intuition and/or clinical experience is inaccurate and often optimistic, which means that there is a tendency to overestimate patient survival in daily clinical practice. In recent decades, many eforts have been made to develop prognosis prediction models which aid physicians to make more accurate prognosis prediction. In this chapter, we review the representative prognosis prediction models in palliative care and related studies. In addition, we refer to several prognosis prediction models developed by unique methods (for instance, case-crossover design or machine learning). Finally, we focus on the possible clinical utility of prognosis prediction models. In fact, no previous studies have clearly demonstrated whether the application of such prognosis prediction models truly beneits patient care in daily clinical practice.Therefore, we will discuss how the application of prognosis prediction models could beneit patients under palliative care.

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“…Evidence suggests the majority of such patients want to know their prognosis, and that when it is discussed it does not worsen the patientphysician relationship, sadness, or anxiety. 5 Despite this, among physicians who have formulated a prognosis for patients with advanced cancer, even if they were asked directly by those patients about their prognosis, 23% of the time they would communicate no prognosis. Forty percent of the time they would communicate a different prognosis than what they had formulated, with 70% of those being optimistically discrepant.…”

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confidence: 99%

It's a matter of respect

Sokol‐Hessner

2016

Journal of Hospital Medicine

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Outcomes of Prognostic Disclosure: Associations With Prognostic Understanding, Distress, and Relationship With Physician Among Patients With Advanced Cancer

Abstract: Prognostic disclosures are associated with more realistic patient expectations of LE, without decrements to their emotional well-being or the patient-physician relationship.

Cited by 315 publications

References 57 publications

Accuracy of Oncologists' Life-Expectancy Estimates Recalled by Their Advanced Cancer Patients: Correlates and Outcomes

Accuracy of Oncologists' Life-Expectancy Estimates Recalled by Their Advanced Cancer Patients: Correlates and Outcomes

Prognosis Prediction Models and their Clinical Utility in Palliative Care

It's a matter of respect

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