• Despite overall improvements, patients with HMs in the United States remain more likely to die in the hospital than at home.

  • Concerning place of death disparities exist along age, marital status, cancer subsite, race, and ethnic lines.

Patients with hematologic malignancies (HMs) often receive aggressive end-of-life care and less frequently use hospice. Comprehensive longitudinal reporting on place of death, a key quality indicator, is lacking. Deidentified death certificate data were obtained via the National Center for Health Statistics for all HM deaths from 1999 to 2015. Multivariate regression analysis (MVA) was used to test for disparities in place of death associated with sociodemographic variables. During the study period, there were 951 435 HM deaths. Hospital deaths decreased from 54.6% in 1999 to 38.2% in 2015, whereas home (25.9% to 32.7%) and hospice facility deaths (0% to 12.1%) increased (all P < .001). On MVA of all cancers, HM patients had the lowest odds of home or hospice facility death (odds ratio [OR], 0.55; 95% confidence interval, 0.54-0.55). Older age (40-64 years: OR, 1.34; ≥65 years: OR, 1.89), being married (OR, 1.62), and having myeloma (OR, 1.34) were associated with home or hospice facility death, whereas being black or African American (OR, 0.68), Asian (OR, 0.58), or Hispanic (OR, 0.84) or having chronic leukemia (OR, 0.83) had decreased odds of dying at home or hospice (all P < .001). In conclusion, despite hospital deaths decreasing over time, patients with HMs remained more likely to die in the hospital than at home.

More than 50 000 people die annually from hematological malignancies (HMs) in the United States.1  Surveys suggest that only 1% of patients with cancer prefer an in-hospital death2 ; most want to die at home.3  However, patients with HMs more frequently receive aggressive end-of-life care,4  and home hospice is seldom used.5  They are up to 4 times more likely to die in the hospital than those with solid tumors6  and, if referred to hospice, are more often enrolled in the last 24 hours of life.7 

However, more comprehensive modern evaluation of place of death in the United States is limited, because prior research was based on Medicare data8  (therefore, only patients age ≥65 years) or institutional reporting.9  We therefore sought to evaluate changes in place of death for the HM population over time, using a more inclusive data set, and to describe any associated health care disparities.

Deidentified death certificate data were obtained from the National Center for Health Statistics. The National Center for Health Statistics is part of the Centers for Disease Control and Prevention and provides national statistical information to help guide policies to improve health in the United States. We included all deaths resulting from HMs from 1999 to 2015. Place and year of death were documented along with sociodemographic information including age, sex, race, ethnicity, marital status, and education. HM deaths were compared with those resulting from solid tumors and then with one another based on subtype (acute leukemia, chronic leukemia, aggressive lymphoma, nonaggressive lymphoma, myeloma).

Using data from all years with full place-of-death reporting (2003-2015), multivariate logistic regression was used to test for disparities in place of death. Statistical analyses were performed using SPSS software (version 21; Armonk, NY). All comparisons were 2 tailed. The Duke University Medical Center Institutional Review Board provided a waiver (Pro00045337) for this study.

There were 951 435 deaths resulting from HMs in the study period. A majority of those who died were male (54.9%), white (88.0%), and non-Hispanic (93.9%); 9.6% were black or African American, 2.1% were Asian, and 0.4% were American Indian. Most were age ≥65 years at time of death (73.9%), with median age of 72 years (interquartile range, 63-81 years). Acute leukemia caused the most deaths (21.7%), followed by myeloma (20.0%) and chronic leukemia (10.5%).

Between 1999 and 2015, hospital (54.6% to 38.2%) and nursing facility deaths (13.1% to 11.9%) both decreased, whereas home (25.9% to 32.7%) and hospice facility deaths (0% to 12.1%) increased (all P < .001). Comparing states with the highest and lowest rates, New York had the highest rate of hospital death (61.6%), almost twice the lowest rate in Utah (32.5%). Utah had the highest home death rate (50.0%), almost 3 times the rate in South Dakota (17.5%). Florida had the highest hospice facility death rate (20.2%); it was >20 times the lowest rate in Utah (≤0.2%). Eleven states (Maryland, Idaho, Colorado, Hawaii, Alaska, Massachusetts, Virginia, North Dakota, West Virginia, Utah, Alabama) had aggregate hospice facility utilization of <2% since 2003, the first available year for this data element in the data set.

There was also significant variation in place of death by cancer subtype (Figure 1A) and race (Figure 1B). There was an overall downtrend in hospital death for each category. Patients with acute leukemia and Asian race had the highest rates of hospital death. Black or African American patients and those with chronic leukemia were the least likely to die at home. Compared with solid tumor deaths, HM deaths were more likely to occur in the hospital and less likely to occur at home. By 2015, patients with HMs were still 65% more likely to die in the hospital (HMs, 38.2% vs non-HMs, 23.2%) and 25% less likely to die at home (32.7% vs 43.6%; both P < .001).

Figure 1.

Trends in place of death resulting from HMs (1999-2015). Location by primary site (A) and by race and ethnicity (B).

Figure 1.

Trends in place of death resulting from HMs (1999-2015). Location by primary site (A) and by race and ethnicity (B).

Close modal

Place of death either at home or in a hospice facility was examined; all assessed categories were associated on univariate analysis (P < .05) and included in the final model. On multivariate analysis of all cancers, HM diagnosis had the strongest negative association with home/hospice facility death (odds ratio [OR], 0.55; 95% confidence interval [CI], 0.54-.055; Table 1). On multivariate analysis limited to HMs, older age (age 40-64 years: OR, 1.34; 95% CI, 1.28-1.39; age ≥65 years: OR, 1.89; 95% CI, 1.81-1.97), being married (OR, 1.62; 95% CI, 1.57-1.66), and having myeloma (OR, 1.34; 95% CI, 1.31-1.36) were associated with home/hospice facility death. Black or African American (OR, 0.68; 95% CI, 0.66-0.70) and Asian patients (OR, 0.58; 95% CI, 0.55-0.60), those of Hispanic ethnicity (OR, 0.84; 95% CI, 0.82-0.86), and those with a diagnosis of chronic leukemia (OR, 0.83; 95% CI, 0.81-0.85) had decreased odds of dying at home or hospice (Table 1).

Table 1.

Univariate and multivariate analysis–modeled results: death resulting from HMs at home or in hospice facility (vs death in another location)

Univariate analysisMultivariate analysis
OR (95% CI)POR (95% CI)P
All cancers (HMs and solid tumors)     
 Year of death (continuous variable) 1.058 (1.058-1.058) <.001 1.047 (1.046-1.047) <.001 
 Age, y     
  Age (continuous variable) 0.997 (0.0997-0.998) <.001 — <.001 
  0-39 1.000  1.000  
  40-64 1.366 (1.351-1.381) <.001 1.095 (1.077-1.112) <.001 
  ≥65 1.295 (1.281-1.309) <.001 1.050 (1.034-1.067) <.001 
 Sex     
  Female (reference) 1.000  1.000  
  Male 1.030 (1.027-1.033) <.001 0.930 (0.926-0.934) <.001 
 Marital status*  <.001  <.001 
  Single (reference) 1.000  1.000  
  Married 2.027 (2.058-2.082) <.001 1.997 (1.982-2.013) <.001 
  Divorced/separated 1.361 (1.352-1.370) <.001 1.284 (1.273-1.296) <.001 
  Widowed 1.411 (1.403-1.419) <.001 1.388 (1.376-1.400) <.001 
 Education level    <.001 
  Some high school or less (reference) 1.000 <.001 1.000  
  High school graduate (≥4 y) 1.047 (1.042-1.052) <.001 0.976 (0.970-0.981) <.001 
  Some college/associates degree 1.174 (1.167-1.181) <.001 1.068 (1.061-1.076) <.001 
  College graduate (≥4 y) 1.163 (1.155-1.171) <.001 1.055 (1.047-1.063) <.001 
  Advanced degree 1.206 (1.196-1.216) <.001 1.092 (1.082-1.102) <.001 
 Race  <.001  <.001 
  White (reference) 1.000  1.000  
  Black or African American 0.669 (0.666-0.672) <.001 0.693 (0.731-0.757) <.001 
  Asian or Pacific Islander 0.776 (0.768-0.783) <.001 0.636 (0.629-0.644) <.001 
  American Indian or Alaska Native 0.888 (0.869-0.906) <.001 0.859 (0.836-0.883) <.001 
 Ethnicity     
  Non-Hispanic (reference) 1.000  1.000  
  Hispanic 1.089 (1.082-1.096) <.001 0.954 (0.946-0.962) <.001 
 Primary cancer diagnosis     
  Solid tumor (reference) 1.000  1.000  
  HM 0.570 (0.567-0.573) <.001 0.547 (0.543-0.551) <.001 
HMs only     
 Year of death (continuous variable) 1.058 (1.058-1.058) <.001 1.053 (1.051-1.055) <.001 
 Age, y     
  Age (continuous variable) 0.997 (0.0997-0.998) <.001 — <.001 
  0-39 1.000  1.000  
  40-64 1.366 (1.351-1.381) <.001 1.335 (1.281-1.390) <.001 
  ≥65 1.295 (1.281-1.309) <.001 1.888 (1.814-1.965) <.001 
 Sex     
  Female (reference) 1.000  1.000  
  Male 1.030 (1.027-1.033) <.001 0.990 (0.977-1.003) .133 
 Marital status*  <.001  <.001 
  Single (reference) 1.000  1.000  
  Married 2.027 (2.058-2.082) <.001 1.612 (1.570-1.655) <.001 
  Divorced/separated 1.361 (1.352-1.370) <.001 1.241 (1.204-1.280) <.001 
  Widowed 1.411 (1.403-1.419) <.001 1.417 (1.377-1.458) <.001 
 Education level  <.001  <.001 
  Some high school or less (reference) 1.000  1.000  
  High school graduate (≥4 y) 1.047 (1.042-1.052) <.001 0.969 (0.952-0.986) <.001 
  Some college/associates degree 1.174 (1.167-1.181) <.001 1.030 (1.010-1.051) .004 
  College graduate (≥4 y) 1.163 (1.155-1.171) <.001 0.984 (0.963-1.007) .174 
  Advanced degree 1.206 (1.196-1.216) <.001 1.000 (0.974-1.026) .991 
 Race  <.001  <.001 
  White (reference) 1.000  1.000  
  Black or African American 0.669 (0.666-0.672) <.001 0.680 (0.664-0.695) <.001 
  Asian or Pacific Islander 0.776 (0.768-0.783) <.001 0.575 (0.552-0.599) <.001 
  American Indian or Alaska Native 0.888 (0.869-0.906) <.001 0.884 (0.804-0.972) .011 
 Ethnicity     
  Non-Hispanic (reference) 1.000  1.000  
  Hispanic 1.089 (1.082-1.096) <.001 0.843 (0.824-0.864) <.001 
 Primary cancer diagnosis  <.001  <.001 
  Acute leukemia (reference) 1.000  1.000  
  Chronic leukemia 0.887 (0.870-0.904) <.001 0.829 (0.810-0.849) <.001 
  Aggressive lymphoma 1.244 (1.209-1.279) <.001 1.141 (1.103-1.180) <.001 
  Nonaggressive lymphoma 1.077 (1.044-1.110) <.001 1.181 (1.136-1.227) <.001 
  Myeloma 1.325 (1.305-1.344) <.001 1.338 (1.313-1.364) <.001 
  Other leukemia/lymphoma 1.155 (1.140-1.169) <.001 1.133 (1.115-1.152) <.001 
Univariate analysisMultivariate analysis
OR (95% CI)POR (95% CI)P
All cancers (HMs and solid tumors)     
 Year of death (continuous variable) 1.058 (1.058-1.058) <.001 1.047 (1.046-1.047) <.001 
 Age, y     
  Age (continuous variable) 0.997 (0.0997-0.998) <.001 — <.001 
  0-39 1.000  1.000  
  40-64 1.366 (1.351-1.381) <.001 1.095 (1.077-1.112) <.001 
  ≥65 1.295 (1.281-1.309) <.001 1.050 (1.034-1.067) <.001 
 Sex     
  Female (reference) 1.000  1.000  
  Male 1.030 (1.027-1.033) <.001 0.930 (0.926-0.934) <.001 
 Marital status*  <.001  <.001 
  Single (reference) 1.000  1.000  
  Married 2.027 (2.058-2.082) <.001 1.997 (1.982-2.013) <.001 
  Divorced/separated 1.361 (1.352-1.370) <.001 1.284 (1.273-1.296) <.001 
  Widowed 1.411 (1.403-1.419) <.001 1.388 (1.376-1.400) <.001 
 Education level    <.001 
  Some high school or less (reference) 1.000 <.001 1.000  
  High school graduate (≥4 y) 1.047 (1.042-1.052) <.001 0.976 (0.970-0.981) <.001 
  Some college/associates degree 1.174 (1.167-1.181) <.001 1.068 (1.061-1.076) <.001 
  College graduate (≥4 y) 1.163 (1.155-1.171) <.001 1.055 (1.047-1.063) <.001 
  Advanced degree 1.206 (1.196-1.216) <.001 1.092 (1.082-1.102) <.001 
 Race  <.001  <.001 
  White (reference) 1.000  1.000  
  Black or African American 0.669 (0.666-0.672) <.001 0.693 (0.731-0.757) <.001 
  Asian or Pacific Islander 0.776 (0.768-0.783) <.001 0.636 (0.629-0.644) <.001 
  American Indian or Alaska Native 0.888 (0.869-0.906) <.001 0.859 (0.836-0.883) <.001 
 Ethnicity     
  Non-Hispanic (reference) 1.000  1.000  
  Hispanic 1.089 (1.082-1.096) <.001 0.954 (0.946-0.962) <.001 
 Primary cancer diagnosis     
  Solid tumor (reference) 1.000  1.000  
  HM 0.570 (0.567-0.573) <.001 0.547 (0.543-0.551) <.001 
HMs only     
 Year of death (continuous variable) 1.058 (1.058-1.058) <.001 1.053 (1.051-1.055) <.001 
 Age, y     
  Age (continuous variable) 0.997 (0.0997-0.998) <.001 — <.001 
  0-39 1.000  1.000  
  40-64 1.366 (1.351-1.381) <.001 1.335 (1.281-1.390) <.001 
  ≥65 1.295 (1.281-1.309) <.001 1.888 (1.814-1.965) <.001 
 Sex     
  Female (reference) 1.000  1.000  
  Male 1.030 (1.027-1.033) <.001 0.990 (0.977-1.003) .133 
 Marital status*  <.001  <.001 
  Single (reference) 1.000  1.000  
  Married 2.027 (2.058-2.082) <.001 1.612 (1.570-1.655) <.001 
  Divorced/separated 1.361 (1.352-1.370) <.001 1.241 (1.204-1.280) <.001 
  Widowed 1.411 (1.403-1.419) <.001 1.417 (1.377-1.458) <.001 
 Education level  <.001  <.001 
  Some high school or less (reference) 1.000  1.000  
  High school graduate (≥4 y) 1.047 (1.042-1.052) <.001 0.969 (0.952-0.986) <.001 
  Some college/associates degree 1.174 (1.167-1.181) <.001 1.030 (1.010-1.051) .004 
  College graduate (≥4 y) 1.163 (1.155-1.171) <.001 0.984 (0.963-1.007) .174 
  Advanced degree 1.206 (1.196-1.216) <.001 1.000 (0.974-1.026) .991 
 Race  <.001  <.001 
  White (reference) 1.000  1.000  
  Black or African American 0.669 (0.666-0.672) <.001 0.680 (0.664-0.695) <.001 
  Asian or Pacific Islander 0.776 (0.768-0.783) <.001 0.575 (0.552-0.599) <.001 
  American Indian or Alaska Native 0.888 (0.869-0.906) <.001 0.884 (0.804-0.972) .011 
 Ethnicity     
  Non-Hispanic (reference) 1.000  1.000  
  Hispanic 1.089 (1.082-1.096) <.001 0.843 (0.824-0.864) <.001 
 Primary cancer diagnosis  <.001  <.001 
  Acute leukemia (reference) 1.000  1.000  
  Chronic leukemia 0.887 (0.870-0.904) <.001 0.829 (0.810-0.849) <.001 
  Aggressive lymphoma 1.244 (1.209-1.279) <.001 1.141 (1.103-1.180) <.001 
  Nonaggressive lymphoma 1.077 (1.044-1.110) <.001 1.181 (1.136-1.227) <.001 
  Myeloma 1.325 (1.305-1.344) <.001 1.338 (1.313-1.364) <.001 
  Other leukemia/lymphoma 1.155 (1.140-1.169) <.001 1.133 (1.115-1.152) <.001 
*

Martial status is unknown in 0.7% of the 2003-2015 data file.

Education level is unknown in 38.5% of the 2003-2015 data file.

Acute leukemia includes acute myeloid and acute lymphocytic leukemias; chronic leukemia includes chronic myeloid and chronic lymphocytic leukemias; aggressive lymphoma includes diffuse large B-cell and Burkitt’s lymphomas; nonaggressive lymphoma includes Hodgkin disease and follicular lymphoma; and myeloma includes multiple myeloma, plasma cell leukemia, and plasmacytoma.

In this study of all hematological cancer deaths over the past 17 years in the United States, hospital deaths decreased by 30%, with a corresponding rise in home and hospice facility deaths. Despite this overall trend, patients with HMs remained more likely to die in the hospital than patients with solid tumors.

Hospital death has been associated with worse outcomes, with unmet symptom needs for patients10  and prolonged grief disorder for caregivers.11  Appropriate hospice referral and clinician-led shared decision making for end-of-life care can improve goal attainment12  and reduce hospital deaths.13  Unfortunately, patients with HMs have lower palliative care utilization, and surveys show that hematological oncologists may harbor more philosophical resistance to making referrals.14  They may also be less comfortable having goals-of-care discussions,15  especially with those with chronic/indolent lymphomas.16  Additionally, patients themselves may have unrealistic treatment expectations16  and prefer aggressive care, with 28% stating a preference to die in the hospital.17 

Obstacles to palliative care and hospice enrollment may stretch beyond patient and physician perceptions and resistance. Patients with HMs can have uncertain disease trajectories, making it difficult to appropriately identify when to transition away from active treatment.16  There is also evidence that patients with HMs have higher symptom burden,18  which sometimes warrants blood products for palliation; a recent study showed that the rate of transfusion dependence at death or hospice enrollment was 20%.19  Financial constraints driving transfusion exclusion in hospice policies may ironically end up driving up overall health care costs, as patients ultimately end up requiring more costly hospitalizations at the end of life.

Despite these barriers, there have been reports of increased rates of hospice admission and home deaths,20  consistent with our study findings. This overall positive trend may reflect the national shift toward considering palliative care vital to the cancer care continuum. Proliferation of the hospice industry has improved access, although there is still geographic variability,21  which may partially explain the significant state-to-state variation seen in this study. Given the stark regional disparities in place of death, however, there are also likely important social and demographic differences at play. Utah, for example, has the highest rate of home death and the lowest rate of hospice facility death; this may reflect both a population with strong family units (and thus the capacity to care for loved ones at home) and potential religious objection to care in a hospice facility, which may be associated with “giving up.” Alternatively, Florida, with >1 in 5 patients dying in a hospice facility, may reflect the coexistence of an aging retirement population and readily available care facilities.

Our study highlights important racial disparities in end-of-life care, with nonwhite and Hispanic patients much less likely to die at home or in a hospice facility. Although there were important decreases in hospital death rates across all races over time, the utilization gap remained grossly stable. This means that the relative disparity between, for example, white and black or African American patients actually grew with time. These findings are consistent with prior research showing that these populations are at risk for health care disparities,22,23  either because of a desire for more aggressive end-of-life care, distrust of the health care system, or decreased referral by providers to palliative care services.

Likewise, significant variation based on cancer subtype identifies patients for whom palliative care services may not be optimally deployed. Whereas patients with myeloma have high hospice enrollment and limited late enrollment,24  patients with acute leukemia are at high risk for aggressive care and hospital death.8,9  This may be due to initial presentation for patients with acute leukemia, where both diagnosis and death may occur in the same hospitalization, or to the increased risks for bleeding and infection that come with standard induction chemotherapy regimens, which may require prolonged hospital stays. Patients with chronic leukemia may have the lowest rate of home death because, as an older population, they require more significant care needs and thus disproportionately die in nursing facilities.

Our study has several limitations. Inaccuracy of death certificates may have led to potential discrepancies, although an expert panel found high fidelity in a retrospective review.25  Access to and utilization of hospice care vary widely by income, insurance, and county-level resources, data on which were not available for this analysis. Finally, this place-of-death study may not accurately reflect the intensity of end-of-life care, because patient death on a palliative care service in a hospital would still be coded as “hospital death” in this study.

In conclusion, despite overall improvements, patients with HMs in the United States remain more likely to die in the hospital than at home. Concerning disparities exist along age, marital status, cancer subsite, race, and ethnic lines. Continued efforts are needed to improve the provision of quality end-of-life care in hematology.

Presented as a poster discussion in Patient and Survivor Care at the 2018 American Society of Clinical Oncology Annual Meeting, Chicago, IL, 4 June 2018.

Contribution: F.C. designed research, performed research, analyzed data, and wrote the paper; A.H.K. designed research and wrote the paper; and J.C. and T.W.L. designed research, analyzed data, and wrote the paper.

Conflict-of-interest disclosure: T.W.L. notes funding from American Cancer Society, Cambia Foundation, Seattle Genetics, and AstraZenca and consultancies/advisory boards at AbbVie, Agios, Amgen, CareVive, Celgene, Helsinn, Heron, Medtronic, Otsuka, Pfizer, Seattle Genetics, and Welvie. The remaining authors declare no competing financial interests.

Correspondence: Fumiko Chino, Duke University Medical Center, DUMC 3085, Durham, NC 27710; e-mail: fumiko.chino@duke.edu.

2.
Macmillan Cancer Support
. No regrets: How talking more openly about death could help people die well. https://www.macmillan.org.uk/documents/aboutus/health_professionals/endoflife/no-regrets-talking-about-death-report.pdf.
Accessed 9 May 2018
.
3.
Gomes
B
,
Higginson
IJ
,
Calanzani
N
, et al
;
PRISMA
.
Preferences for place of death if faced with advanced cancer: a population survey in England, Flanders, Germany, Italy, the Netherlands, Portugal and Spain
.
Ann Oncol
.
2012
;
23
(
8
):
2006
-
2015
.
4.
Earle
CC
,
Landrum
MB
,
Souza
JM
,
Neville
BA
,
Weeks
JC
,
Ayanian
JZ
.
Aggressiveness of cancer care near the end of life: is it a quality-of-care issue?
J Clin Oncol
.
2008
;
26
(
23
):
3860
-
3866
.
5.
Moreno-Alonso
D
,
Porta-Sales
J
,
Monforte-Royo
C
,
Trelis-Navarro
J
,
Sureda-Balarí
A
,
Fernández De Sevilla-Ribosa
A
.
Palliative care in patients with haematological neoplasms: An integrative systematic review
.
Palliat Med
.
2018
;
32
(
1
):
79
-
105
.
6.
Bruera
E
,
Russell
N
,
Sweeney
C
,
Fisch
M
,
Palmer
JL
.
Place of death and its predictors for local patients registered at a comprehensive cancer center
.
J Clin Oncol
.
2002
;
20
(
8
):
2127
-
2133
.
7.
LeBlanc
TW
,
Abernethy
AP
,
Casarett
DJ
.
What is different about patients with hematologic malignancies? A retrospective cohort study of cancer patients referred to a hospice research network
.
J Pain Symptom Manage
.
2015
;
49
(
3
):
505
-
512
.
8.
Wang
R
,
Zeidan
AM
,
Halene
S
, et al
.
Health care use by older adults with acute myeloid leukemia at the end of life
.
J Clin Oncol
.
2017
;
35
(
30
):
3417
-
3424
.
9.
El-Jawahri
AR
,
Abel
GA
,
Steensma
DP
, et al
.
Health care utilization and end-of-life care for older patients with acute myeloid leukemia
.
Cancer
.
2015
;
121
(
16
):
2840
-
2848
.
10.
Teno
JM
,
Clarridge
BR
,
Casey
V
, et al
.
Family perspectives on end-of-life care at the last place of care
.
JAMA
.
2004
;
291
(
1
):
88
-
93
.
11.
Wright
AA
,
Keating
NL
,
Balboni
TA
,
Matulonis
UA
,
Block
SD
,
Prigerson
HG
.
Place of death: correlations with quality of life of patients with cancer and predictors of bereaved caregivers’ mental health
.
J Clin Oncol
.
2010
;
28
(
29
):
4457
-
4464
.
12.
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
;
28
(
7
):
1203
-
1208
.
13.
Stein
RA
,
Sharpe
L
,
Bell
ML
,
Boyle
FM
,
Dunn
SM
,
Clarke
SJ
.
Randomized controlled trial of a structured intervention to facilitate end-of-life decision making in patients with advanced cancer
.
J Clin Oncol
.
2013
;
31
(
27
):
3403
-
3410
.
14.
LeBlanc
TW
,
O’Donnell
JD
,
Crowley-Matoka
M
, et al
.
Perceptions of palliative care among hematologic malignancy specialists: a mixed-methods study
.
J Oncol Pract
.
2015
;
11
(
2
):
e230
-
e238
.
15.
Hui
D
,
Bansal
S
,
Park
M
, et al
.
Differences in attitudes and beliefs toward end-of-life care between hematologic and solid tumor oncology specialists
.
Ann Oncol
.
2015
;
26
(
7
):
1440
-
1446
.
16.
Odejide
OO
,
Cronin
AM
,
Condron
NB
, et al
.
Barriers to quality end-of-life care for patients with blood cancers
.
J Clin Oncol
.
2016
;
34
(
26
):
3126
-
3132
.
17.
Howell
DA
,
Wang
HI
,
Roman
E
, et al
.
Preferred and actual place of death in haematological malignancy
.
BMJ Support Palliat Care
.
2017
;
7
(
2
):
150
-
157
.
18.
Hochman
MJ
,
Yu
Y
,
Wolf
SP
, et al
:
Comparing the palliative care needs of patients with hematologic and solid malignancies
.
J Pain Symptom Manage
.
55
(
1
):
82
-
88.e1
,
2018
.
19.
LeBlanc
TW
,
Egan
PC
,
Olszewski
AJ
.
Transfusion dependence, use of hospice services, and quality of end-of-life care in leukemia
.
Blood
.
2018
;
132
(
7
):
717
-
726
.
20.
Howell
DA
,
Wang
HI
,
Smith
AG
,
Howard
MR
,
Patmore
RD
,
Roman
E
.
Place of death in haematological malignancy: variations by disease sub-type and time from diagnosis to death
.
BMC Palliat Care
.
2013
;
12
(
1
):
42
.
21.
Carlson
MD
,
Bradley
EH
,
Du
Q
,
Morrison
RS
.
Geographic access to hospice in the United States
.
J Palliat Med
.
2010
;
13
(
11
):
1331
-
1338
.
22.
Bhatt
VR
,
Shostrom
V
,
Gundabolu
K
,
Armitage
JO
.
Utilization of initial chemotherapy for newly diagnosed acute myeloid leukemia in the United States
.
Blood Adv
.
2018
;
2
(
11
):
1277
-
1282
.
23.
Odejide
OO
,
Cronin
AM
,
Earle
CC
,
LaCasce
AS
,
Abel
GA
.
Hospice use among patients with lymphoma: impact of disease aggressiveness and curability
.
J Natl Cancer Inst
.
2015
;
108
(
1
):
djv280
.
24.
Odejide
OO
,
Li
L
,
Cronin
AM
, et al
.
Meaningful changes in end-of-life care among patients with myeloma
.
Haematologica
.
2018
;
103
(
8
):
1380
-
1389
.
25.
Turner
EL
,
Metcalfe
C
,
Donovan
JL
, et al
.
Contemporary accuracy of death certificates for coding prostate cancer as a cause of death: Is reliance on death certification good enough? A comparison with blinded review by an independent cause of death evaluation committee
.
Br J Cancer
.
2016
;
115
(
1
):
90
-
94
.