Surprise Question and Performance Status Indicate Urgency of Palliative Care Needs in Patients with Advanced Cancer at the Emergency Department: An Observational Cohort Study

Verhoef, Mary-Joanne; Nijs, Ellen J M de; Fiocco, Marta; Heringhaus, Christian; Horeweg, Nanda; Linden, Yvette M. van der

doi:10.1089/jpm.2019.0413

Cited by 27 publications

(45 citation statements)

References 44 publications

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“…[19][20][21][22][23] Therefore, these data call for additional efforts toward improving life expectancy assessments, perhaps through predictive modeling methods combining prognostic factors. [27][28][29][30][31][32][33][34][35][36][37] Notable examples include the Chow, 33 NEAT, 38 and TEACHH 39 models, each with demonstrated utility for this setting. Consistent with these validated prognostic tools, our study found significant associations with respect to metastatic site, hospital admission, PS, and primary histology to a lesser extent.…”

Section: Discussionmentioning

confidence: 99%

Early and Midtreatment Mortality in Palliative Radiotherapy: Emphasizing Patient Selection in High-Quality End-of-Life Care

Ning¹,

Das²,

Rosenthal³

et al. 2021

Journal of the National Comprehensive Cancer Network

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Background: Palliative radiotherapy (RT) is effective, but some patients die during treatment or too soon afterward to experience benefit. This study investigates end-of-life RT patterns to inform shared decision-making and facilitate treatment consistent with palliative goals. Materials and Methods: All patients who died ≤6 months after initiating palliative RT at an academic cancer center between 2015 and 2018 were identified. Associations with time-to-death, early mortality (≤30 days), and midtreatment mortality were analyzed. Results: In total, 1,620 patients died ≤6 months from palliative RT initiation, including 574 (34%) deaths at ≤30 days and 222 (14%) midtreatment. Median survival was 43 days from RT start (95% CI, 41–45) and varied by site (P<.001), ranging from 36 (head and neck) to 53 days (dermal/soft tissue). On multivariable analysis, earlier time-to-death was associated with osseous (hazard ratio [HR], 1.33; P<.001) and head and neck (HR, 1.45; P<.001) sites, multiple RT courses ≤6 months (HR, 1.65; P<.001), and multisite treatments (HR, 1.40; P=.008), whereas stereotactic technique (HR, 0.77; P<.001) and more recent treatment year (HR, 0.82; P<.001) were associated with longer survival. No difference in time to death was noted among patients prescribed conventional RT in 1 to 10 versus >10 fractions (median, 40 vs 47 days; P=.272), although the latter entailed longer courses. The 30-day mortality group included 335 (58%) inpatients, who were 27% more likely to die midtreatment (P=.031). On multivariable analysis, midtreatment mortality among these inpatients was associated with thoracic (odds ratio [OR], 2.95; P=.002) and central nervous system (CNS; OR, 2.44; P=.002) indications, >5-fraction courses (OR, 3.27; P<.001), and performance status of 3 to 4 (OR, 1.63; P=.050). Conversely, palliative/supportive care consultation was associated with decreased midtreatment mortality (OR, 0.60; P=.045). Conclusions: Earlier referrals and hypofractionated courses (≤5–10 treatments) should be routinely considered for palliative RT indications, given the short life expectancies of patients at this stage in their disease course. Providers should exercise caution for emergent thoracic and CNS indications among inpatients with poor prognoses due to high midtreatment mortality.

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Section: Discussionmentioning

confidence: 99%

Early and Midtreatment Mortality in Palliative Radiotherapy: Emphasizing Patient Selection in High-Quality End-of-Life Care

Ning¹,

Das²,

Rosenthal³

et al. 2021

Journal of the National Comprehensive Cancer Network

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“…As such, numerous studies have assessed the ability of screening tools to help ED healthcare providers identify ED patients with unmet palliative care needs who may benefit from timely referral to palliative services [ 4 ]. The proportion of patients identified as having unmet palliative care needs across various EDs have ranged considerably, from 5% [ 5 ] to 83% [ 6 ], which is likely due to differences in the criteria for palliative needs among the available screening tools, clinical heterogeneity among the study populations, and variability in healthcare systems. While various studies have identified ED patients with unmet palliative care needs, only a handful of studies have conducted an assessment of whether there are any potential differences in the characteristics and ED management of patients identified as having met or unmet palliative care needs [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…The proportion of patients identified as having unmet palliative care needs across various EDs have ranged considerably, from 5% [ 5 ] to 83% [ 6 ], which is likely due to differences in the criteria for palliative needs among the available screening tools, clinical heterogeneity among the study populations, and variability in healthcare systems. While various studies have identified ED patients with unmet palliative care needs, only a handful of studies have conducted an assessment of whether there are any potential differences in the characteristics and ED management of patients identified as having met or unmet palliative care needs [ 6 , 7 ]. There is some evidence that patients with EOL or palliative conditions have an increased risk of hospitalization [ 6 , 7 ] and increased laboratory testing [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

“…While various studies have identified ED patients with unmet palliative care needs, only a handful of studies have conducted an assessment of whether there are any potential differences in the characteristics and ED management of patients identified as having met or unmet palliative care needs [ 6 , 7 ]. There is some evidence that patients with EOL or palliative conditions have an increased risk of hospitalization [ 6 , 7 ] and increased laboratory testing [ 6 ]. There is, however, a lack of understanding as to the utilization of available palliative care services [ 6 , 7 ], as well as the frequency of formal goals of care (GOC), which can impact the care delivered in the ED or in their subsequent hospitalization.…”

Section: Introductionmentioning

confidence: 99%

“…There is some evidence that patients with EOL or palliative conditions have an increased risk of hospitalization [ 6 , 7 ] and increased laboratory testing [ 6 ]. There is, however, a lack of understanding as to the utilization of available palliative care services [ 6 , 7 ], as well as the frequency of formal goals of care (GOC), which can impact the care delivered in the ED or in their subsequent hospitalization. Gaining a better understanding of ED patients with unmet palliative care needs may assist emergency physicians, ED staff and health administrators identifying potential gaps in care and ways to improve the services and overall quality of care for patients with EOL conditions [ 4 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

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Comparison of characteristics and management of emergency department presentations between patients with met and unmet palliative care needs

et al. 2021

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Introduction This study examined emergency department (ED) presentations of patients with end of life (EOL) conditions and patients having met and unmet palliative care needs were compared. Methods Presentations for EOL conditions were prospectively identified and screened for palliative care needs. Descriptive data were reported as proportions, means or medians. Bi-variable analysis for dichotomous and continuous variables were performed by chi-squared and T-tests (p≤0.01), respectively. A multivariable logistic regression model identified factors associated with having unmet palliative needs and reported adjusted odds ratios (aOR) with 95% confidence intervals (CI). Results Overall, 663 presentations for EOL conditions were identified; 518 (78%) involved patients with unmet palliative care needs. Presentations by patients with unmet palliative needs were more likely to involve consultations (80% vs. 67%, p = 0.001) and result in hospitalization (69% vs. 51%, p<0.001) compared to patients whose palliative needs were met. Patients with unmet palliative care needs were more likely to have previous ED visits (73% unmet vs. 48% met; p<0.001). While medication, procedures, investigations and imaging ordering were high across all patients with EOL conditions, there were no significant differences between the groups. Consultations with palliative specialists in the ED (6% unmet vs. 1% met) and following discharge (29% unmet vs. 18% met) were similarly uncommon. Patients having two or more EOL conditions (aOR = 2.41; 95% CI: 1.16, 5.00), requiring hospitalization (aOR = 1.93; 95% CI: 1.30, 2.87), and dying during the ED visit (aOR = 2.15; 95% CI: 1.02, 4.53) were strongly associated with having unmet palliative care needs. Conclusions Most ED presentations for EOL conditions were made by patients with unmet palliative care needs, who were significantly more likely to require consultation, hospitalization, and to die. Referrals to palliative care services during and after the ED visit were infrequent, indicating important opportunities to promote these services.

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Prospective Comparison of Medical Oncologists and a Machine Learning Model to Predict 3-Month Mortality in Patients With Metastatic Solid Tumors

et al. 2022

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Key Points Question How do oncologists and a machine learning model compare in predicting 3-month mortality for patients with advanced solid tumors? Findings In this prognostic study, the machine learning model significantly outperformed 74 oncologists in predicting 3-month mortality for 2041 patients with metastatic solid tumors overall and in gastrointestinal and breast cancer subpopulations. Findings were not significant in genitourinary, lung, and rare cancer groups. Meaning The results of this study suggest the potential for a machine learning model trained with electronic health record data to support oncologists in prognostication and clinical decision-making to improve end-of-life care.

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Surprise Question and Performance Status Indicate Urgency of Palliative Care Needs in Patients with Advanced Cancer at the Emergency Department: An Observational Cohort Study

Cited by 27 publications

References 44 publications

Early and Midtreatment Mortality in Palliative Radiotherapy: Emphasizing Patient Selection in High-Quality End-of-Life Care

Early and Midtreatment Mortality in Palliative Radiotherapy: Emphasizing Patient Selection in High-Quality End-of-Life Care

Comparison of characteristics and management of emergency department presentations between patients with met and unmet palliative care needs

Prospective Comparison of Medical Oncologists and a Machine Learning Model to Predict 3-Month Mortality in Patients With Metastatic Solid Tumors

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