Abstract
Context
Hematologic cancer patients use palliative care services less frequently than their solid tumor counterparts. Prior work suggests these patients have a sizeable symptom burden, but comparisons between hematologic and solid tumor patients near the end of life are limited.
Objectives
To compare unmet symptom needs in a cohort of hematologic and solid tumor patients referred to specialty palliative care services.
Methods
Using a novel data registry of initial palliative care encounters, we performed a cross-sectional analysis of cancer patients receiving care across seventeen sites within the Global Palliative Care Quality Alliance. We compared clinically-significant symptoms (rated as 4 or greater in severity) between hematologic and solid tumor patients and performed multivariate logistic regression analyses examining the relationship between symptom burden and tumor type.
Results
We identified 1,235 cancer patients, 108 of which had hematologic malignancies. Pain, dyspnea, nausea, and anorexia burden was as high among patients with hematologic as those with solid malignancies. Blood cancer patients had higher rates of clinically-significant tiredness (51% vs. 42%; p=0.03) than solid tumor patients. Finally, blood cancer patients had greater odds of being tired (odds ratio, 2.19; CI 1.22-3.91) and drowsy (odds ratio, 1.81; CI 1.07-3.07) than solid tumor patients independent of age, gender, race, and performance status.
Conclusions
Hematologic and solid tumor patients both have significant symptom burden at time of referral to palliative care services. Blood cancer patients may have unique concerns warranting targeted attention, including substantial drowsiness and tiredness. Our findings suggest a need to optimize palliative care usage in the hematologic cancer population.
Keywords: Palliative care, hematologic malignancies, healthcare delivery, healthcare resources
Introduction
Hematologic malignancies comprise of a diverse group of diseases unique in many ways from solid tumors. While many solid tumors tend to share similar trajectories of illness, hematologic malignancies demonstrate more heterogeneity. For example, certain hematologic cancers are indolent or manageable with intermittent disease-directed treatments of relatively low intensity (e.g. chronic lymphoid leukemia, follicular lymphoma); others are aggressive and necessitate the use of highly toxic, high-risk therapies such as chemotherapy or stem cell transplant (e.g. acute myeloid leukemias, diffuse large B-cell non-Hodgkin lymphomas). Although the latter treatments may lead to cure—unlike what is typically possible with advanced solid tumors—treatment can cause significant morbidity and distress placed on patients and their caregivers(1-5), and it is not a guarantee. Despite experiencing such high levels of distress, patients with hematologic cancers tend to have less access to palliative care services and greater use of low-value, aggressive care near the end of life(6-11). By low-value care, we mean interventions that may not meaningfully extend survival or improve quality of life, such as chemotherapy in the last few weeks of life(12) or use of intensive care unit services at the end of life.
Palliative care integration early in the disease course can help to address these aggressive end-of-life interventions and improve patients’ quality of life in other advanced cancer settings(13-18), but the unpredictable nature of blood cancers and the general attitudes of some hematologic oncologists towards palliative care provide several barriers to increased access(7, 19-21). Despite these barriers, a trend towards increased palliative care referral has been observed(22), along with a renewed call to examine the intersection between palliative care and the quality of life of blood cancer patients(23, 24), especially amid initial evidence of feasibility and efficacy in subpopulations such as those undergoing stem cell transplantations(25). These calls highlight the imperative to provide care across multiple domains of palliative care, including physical, psychological, spiritual, legal, and cultural aspects—for all patients with serious illness, even in hematology, amid greater prognostic uncertainty.
Unmet symptom and functional needs have been comprehensively studied in solid tumor patients; however, due to the aforementioned differences we know significantly less about such needs in patients with hematologic malignancies. Using a novel registry of specialty palliative care visits, we aimed to compare the unmet needs of patients with hematologic malignancies to that of solid tumor patients at the time of palliative care referral, in order to better address the palliative care needs of this unique population.
Methods
We performed a cross-sectional analysis of initial palliative care encounters from seventeen community and academic sites within the Global Palliative Care Quality Alliance (GPCQA), a quality measurement, improvement, and learning collaborative for specialty palliative care that includes medical centers in regions ranging from very rural areas to large metropolitan centers. Data were collected from the Quality Data Collection Tool (QDACT, Duke Cancer Institute, Durham, NC), a secure electronic interface used by clinicians to input clinical data from patients and/or their surrogates during face-to-face palliative care visits(26). The feasibility and usability of QDACT to assess clinical gaps for improvement have been studied previously(27). We selected patients from the QDACT database who had a cancer diagnosis listed in their enrollment visit. Encounters spanned from January 2, 2014 to June 1, 2016. This study was approved by the Duke Institutional Review Board (Pro00035703).
We selected first visits for patients with a diagnosis of cancer and categorized them into hematologic or solid tumor types. Patients with “other” cancer diagnoses were excluded if a specific cancer diagnosis was not explicitly written in; all categorizations were reviewed by authors (MJH, TWL) to appropriately classify them as hematologic or solid. Those with missing, unknown, or zero performance status scores were also excluded; zero means the patient is deceased.
Demographic and clinical data were collected at the beginning of the clinical encounters. Demographics included age, gender, and race/ethnicity. QDACT uses several Likert scales to measure outcomes such as quality of life (QOL). The Edmonton Symptom Assessment Scale (ESAS)(28) and the Palliative Performance Scale (PPS)(29) are used to measure patient symptoms and performance status, respectively. The ESAS symptom labeled “other problem” was excluded from our analyses. For analyses of performance status, we grouped patients into poor (PPS of 10-30), moderate (40-60), and optimal (70-100) levels, as others have done previously(30).
Our primary study objective was to compare the unmet palliative care needs among hematologic and solid tumor patients at time of initial palliative care consultation. First, we compared patient demographics and clinical characteristics. Next, we examined the symptom burden in both populations. We first compared the prevalence of clinically-significant symptoms (considered 4 or greater in severity) in blood and solid cancer patient populations, using chi-square and Fisher exact tests as appropriate. We next performed logistic regression analysis to examine the relationship between unmet symptom needs and tumor type while accounting for patient age, gender, race, and performance status (PPS). For this analysis, symptoms were considered binary (either present or absent). Finally, to illustrate symptom distribution, we developed a stacked bar graph for both groups.
Results
Of the 1,235 patients with a cancer diagnosis in our database, 108 had tumors classified as hematologic and the remaining 1,127 had solid tumors (Table 1). More blood cancer patients were male (56%) than female (34%;); solid tumor patients had the opposite gender distribution (37% male, 52% female; p<0.01 for solid vs. hematologic). The difference in performance status distribution was non-significant, with 26% of solid tumor patients and 20% of blood cancer patients having PPS scores ranging from 70 to 100.
Table 1.
Demographic and clinical characteristics of hematologic and solid tumor patients referred for palliative care with a Palliative Performance Score (PPS) greater than 0. Bold denotes statistical significance at a threshold of p≤ 0.05.
| Hematologic (N=108) |
Solid (N=1127) |
Total (N=1235) |
P value | |
|---|---|---|---|---|
| Age | 0.111 | |||
| N | 99 | 1008 | 1107 | |
| Missing | 9 | 119 | 128 | |
| Mean (SD) | 66.6 (15.2) | 64.8 (14.1) | 65.0 (14.2) | |
| Range | (24.0-93.0) | (21.0-100.0) | (21.0-100.0) | |
| Gender | <0.012 | |||
| Missing | 10 | 123 | 133 | |
| Male | 61 (62.2%) | 418 (41.6%) | 479 (43.5%) | |
| Female | 37 (37.8%) | 586 (58.4%) | 623 (56.5%) | |
| Ethnicity | 0.323 | |||
| Missing | ||||
| Hispanic or Latino | 19 | 190 | 209 | |
| Not Hispanic or Latino | 4 (4.5%) | 26 (2.8%) | 30 (2.9%) | |
| Race | 85 (95.5%) | 911 (97.2%) | 996 (97.1%) | 0.262 |
| Missing | ||||
| White | ||||
| Black or African American | 22 | 231 | 253 | |
| Other | 68 (79.1%) | 705 (78.7%) | 773 (78.7%) | |
| PPS Score | 0.282 | |||
| PPS 10-30 | 22 (20.4%) | 177 (15.7%) | 199 (16.1%) | |
| PPS 40-60 | 64 (59.3%) | 657 (58.3%) | 721 (58.4%) | |
| PPS 70-100 | 22 (20.4%) | 293 (26.0%) | 315 (25.5%) | |
| Cancer Diagnoses | ||||
| Brain | 0 (0.0%) | 32 (2.8%) | 32 (2.6%) | |
| Breast | 0 (0.0%) | 131 (11.6%) | 131 (10.6%) | |
| GI | 0 (0.0%) | 286 (25.4%) | 286 (23.2%) | |
| Genitourinary | 0 (0.0%) | 121 (10.7%) | 121 (9.8%) | |
| Head and neck | 0 (0.0%) | 63 (5.6%) | 63 (5.1%) | |
| Leukemia | 42 (38.9%) | 0 (0.0%) | 42 (3.4%) | |
| Lung | 0 (0.0%) | 234 (20.8%) | 234 (18.9%) | |
| Lymphoma | 43 (39.8%) | 0 (0.0%) | 43 (3.5%) | |
| Melanoma | 0 (0.0%) | 25 (2.2%) | 25 (2.0%) | |
| Multiple myeloma | 22 (20.4%) | 0 (0.0%) | 22 (1.8%) | |
| Other Cancer | 1 (0.9%) | 33 (2.9%) | 34 (2.8%) | |
| Ovarian/peritoneal | 0 (0.0%) | 107 (9.5%) | 107 (8.7%) | |
| Thyroid | 0 (0.0%) | 7 (0.6%) | 7 (0.6%) | |
| Uterine, cervical, vaginal | 0 (0.0%) | 88 (7.8%) | 88 (7.1%) |
Kruskal Wallis
Chi-Square
Fisher Exact
SD—Standard Deviation, PPS—Palliative Performance Scale
Examining the prevalence of symptoms in hematologic and solid patients, we found that hematologic tumor patients reported similar rates of many clinically-significant symptoms, including pain, tiredness, anorexia, anxiety, and depression (Table 2). Blood cancer patients had higher rates of clinically-significant tiredness compared to solid tumor patients (51% vs. 42%; p=0.03). Blood cancer patients also had higher levels of drowsiness than solid tumor patients (30% vs. 20%), but this difference did not reach statistical significance (p=0.05). Our stacked bar graph (Figure 1) provides further context to these results by displaying the distribution of symptom severity among both patient groups.
Table 2.
Comparison of symptoms in solid and hematologic cancer patients seen during initial palliative care consultation. Bold denotes statistical significance at a threshold of p≤ 0.05.
| Hematologic (N=108) |
Solid (N=1127) |
Total (N=1235) |
P value | |
|---|---|---|---|---|
| Pain | 0.331 | |||
| 0 | 26 (24.1%) | 224 (19.9%) | 250 (20.2%) | |
| 1-3 | 21 (19.4%) | 271 (24.0%) | 292 (23.6%) | |
| ≥4 | 45 (41.7%) | 510 (45.3%) | 555 (44.9%) | |
| Anxiety | 0.431 | |||
| 0 | 26 (24.1%) | 333 (29.5%) | 359 (29.1%) | |
| 1-3 | 30 (27.8%) | 265 (23.5%) | 295 (23.9%) | |
| ≥4 | 16 (14.8%) | 199 (17.7%) | 215 (17.4%) | |
| Dyspnea | 0.431 | |||
| 0 | 37 (34.3%) | 475 (42.1%) | 512 (41.5%) | |
| 1-3 | 28 (25.9%) | 244 (21.7%) | 272 (22.0%) | |
| ≥4 | 20 (18.5%) | 200 (17.7%) | 220 (17.8%) | |
| Constipation | 0.141 | |||
| 0 | 52 (48.1%) | 475 (42.1%) | 527 (42.7%) | |
| 1-3 | 18 (16.7%) | 195 (17.3%) | 213 (17.2%) | |
| ≥4 | 12 (11.1%) | 225 (20.0%) | 237 (19.2%) | |
| Tiredness | 0.032 | |||
| 0 | 5 (4.6%) | 73 (6.5%) | 78 (6.3%) | |
| 1-3 | 8 (7.4%) | 196 (17.4%) | 204 (16.5%) | |
| ≥4 | 55 (50.9%) | 477 (42.3%) | 532 (43.1%) | |
| Nausea | 0.241 | |||
| 0 | 53 (49.1%) | 533 (47.3%) | 586 (47.4%) | |
| 1-3 | 14 (13.0%) | 234 (20.8%) | 248 (20.1%) | |
| ≥4 | 15 (13.9%) | 139 (12.3%) | 154 (12.5%) | |
| Depression | 0.111 | |||
| 0 | 23 (21.3%) | 341 (30.3%) | 364 (29.5%) | |
| 1-3 | 27 (25.0%) | 199 (17.7%) | 226 (18.3%) | |
| ≥4 | 15 (13.9%) | 173 (15.4%) | 188 (15.2%) | |
| Drowsiness | 0.051 | |||
| 0 | 23 (21.3%) | 345 (30.6%) | 368 (29.8%) | |
| 1-3 | 22 (20.4%) | 237 (21.0%) | 259 (21.0%) | |
| ≥4 | 32 (29.6%) | 222 (19.7%) | 254 (20.6%) | |
| Appetite | 0.371 | |||
| 0 | 10 (9.3%) | 169 (15.0%) | 179 (14.5%) | |
| 1-3 | 15 (13.9%) | 166 (14.7%) | 181 (14.7%) | |
| ≥4 | 41 (38.0%) | 414 (36.7%) | 455 (36.8%) | |
| Well-being | 0.332 | |||
| 0 | 1 (0.9%) | 36 (3.2%) | 37 (3.0%) | |
| 1-3 | 8 (7.4%) | 129 (11.4%) | 137 (11.1%) | |
| ≥4 | 31 (28.7%) | 323 (28.7%) | 354 (28.7%) |
Chi-Square
Fisher Exact
Figure 1.
S—solid malignancies, H—hematologic malignancies
Symptom severity distribution of solid and hematologic cancer patients during initial palliative care consultation. Severity was categorized as high (rated 8-10 out of 10), moderate (5-7), low (1-4), or no severity (0). Symptoms are derived from the Edmonton Symptom Assessment Scale (ESAS).
Multivariate logistic regression showed that patients with hematologic malignancies had significantly greater odds of being tired (odds ratio [OR], 2.19; 95% confidence interval [CI], 1.22-3.91; p<0.01) and drowsy (OR, 1.81; CI, 1.07-3.07; p<0.03) than solid tumor patients when accounting for age, gender, race, and performance status (Table S2). On the other hand, solid tumor patients had greater odds of being constipated, but this difference was not statistically significant (OR, 0.51; CI, 0.25-1.01; p=0.05).
Discussion
Using data collected from a diverse array of clinical sites with a large sample size, we compared the symptoms faced by hematologic and solid tumor patients at referral to palliative care services. The most poignant findings are as follows. First, hematologic and solid tumor patients are similarly affected by most symptoms evaluated in our study. Second, a key difference was found: blood cancer patients had greater odds of being affected by fatigue-related symptoms, such as drowsiness and tiredness. Our results suggest significant unmet needs in both groups, with some unique concerns among patients with hematologic malignancies.
First, we found both hematologic and solid tumor patients had similarly high rates of clinically-significant pain, dyspnea, nausea, and anorexia—symptoms that are commonly seen by palliative care specialists and are potentially actionable problems. This finding corroborates prior single-institution studies finding that blood cancer patients have a substantial symptom burden comparable to that of patients with solid tumors(31-33). Confirming this finding via a multisite, real-world registry is important, as it supports the notion that patients with hematologic malignancies have significant unmet symptom needs, and thus stand to benefit from concurrent specialist palliative care. More study of the impact of palliative care in this population is needed.
Second, we found a few important differences in the symptom profiles of hematologic and solid tumor patients at palliative care referral. Notably, we found blood cancer patients had higher rates of clinically-significant tiredness; additionally, these patients had higher odds of being tired or drowsy when accounting for relevant covariates. This finding is consistent with a smaller, single-institution study showing that blood cancer patients were significantly drowsier compared to those with solid tumors(31). Additionally, tiredness or fatigue has been found to be one of the most prevalent and troublesome symptoms for patients with hematologic malignancies, with 55-69% of patients reporting fatigue in prior studies done in other settings(32, 34). Since the pathophysiology and treatment of many hematologic diseases results in anemia, it is not surprising that fatigue is a major problem for blood cancer patients. However, anemia may not completely explain the etiology of this symptom: one international survey of myelodysplastic syndrome patients found no correlation between patient hemoglobin levels and self-reported fatigue, and no clear correlation with blood transfusions(35). Multiple factors beyond hemoglobin levels have been implicated in causing fatigue in cancer patients, including chemotherapies and psychiatric comorbidities such as anxiety and depression(36-38). More study in this area is needed, including prospective assessment of the impact of transfusion on fatigue and other measures of well-being in patients with hematologic malignancies.
Unlike previous studies comparing the palliative care symptoms of patients with solid and hematologic malignancies(31-34, 39), our study uses a real-world registry in a variety of settings of care and among diverse academic and community sites throughout the continental United States. Our results emphasize the need for improved access to specialty palliative care services among hematologic cancer patients with complex healthcare needs, as they likely have as much to benefit from these services as solid tumor patients do. Improving palliative care access in this population is contingent upon changing physician attitudes through increased palliative care collaboration as well as addressing pragmatic concerns such as access to transfusion services while in hospice care(40-42).
Limitations to our analysis are as follows. First, our sample was limited to cancer patients already referred to palliative care, making it likely that these patients are sicker than the cancer patient population at large given what is known about the prevalence of late referrals to palliative and hospice care services(11, 43). We cannot generalize results to all cancer patients, but our study is relevant to those cancer patients seen in diverse palliative care settings (including outpatient clinics, emergency departments, and intensive care units), and is thus practically useful in identifying unmet palliative care needs among those referred. Of note, the percent of hematologic cancer patients in our study is 8.7%, which is slightly lower than the approximate prevalence of hematologic cancers in the United States (approximately 9.8% of all cancers(44)). This likely reflects under referral of blood cancer patients to specialty palliative care services. Second, our study is cross-sectional and did not prospectively track patient symptoms over time. Lastly, the symptom burden of this population is probably underestimated given that some patients were unable to respond to clinicians.
In conclusion, our large multisite analysis demonstrates significant and comparable symptom burden in hematologic and solid tumor patient populations upon palliative care referral. These findings underscore the need for concurrent palliative care as part of the care of patients with hematologic malignancies, based on unmet symptom needs. More research into how palliative care may benefit blood cancer patients is needed, along with novel models of providing concurrent palliative care in this population.
Supplementary Material
Table S1.
*Adjusted for age, gender, race, and performance score (PPS)
Bold denotes statistical significance at a threshold of p≤ 0.05.
OR—Odds Ratio
Univariate and multivariate logistic regression model for the relationship between unmet symptom needs and patient tumor type. Odds ratios greater than 1.0 suggest hematologic cancer patients are disproportionately affected by the listed symptoms as compared to solid tumor patients.
Acknowledgments
Funding for this study was provided by the National Institute of Nursing Research (grant number U24 NR014637-04) and the Agency for Healthcare Research and Quality (grant numbers K08 HS023681-A1 and R18 HS022763-04). Dr. LeBlanc’s research is supported by a Sojourns Scholars Award from the Cambia Health Foundation, and a Mentored Research Scholar Grant from the American Cancer Society. The Duke Biostatistics Core’s support of this project was made possible by Grant Number UL1TR001117 from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. The design, conduct, analysis, and write-up of the study were performed independently from any sponsoring agency or funding. Its contents do not necessarily represent the official view of any sponsoring agency.
Footnotes
Disclosures
None of the authors have relevant conflicts of interest to report.
References
- 1.El-Jawahri AR, Traeger LN, Kuzmuk K, et al. Quality of life and mood of patients and family caregivers during hospitalization for hematopoietic stem cell transplantation. Cancer. 2015;121:951–9. doi: 10.1002/cncr.29149. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Zimmermann C, Yuen D, Mischitelle A, et al. Symptom burden and supportive care in patients with acute leukemia. Leuk Res. 2013;37:731–6. doi: 10.1016/j.leukres.2013.02.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Bevans M, Sternberg EM. Caregiving burden, stress, and health effects among family caregivers of adult cancer patients. Jama. 2012;307:398–403. doi: 10.1001/jama.2012.29. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Nissim R, Zimmermann C, Minden M, et al. Abducted by the illness: a qualitative study of traumatic stress in individuals with acute leukemia. Leuk Res. 2013;37:496–502. doi: 10.1016/j.leukres.2012.12.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.LeBlanc TW, El-Jawahri A. When and why should patients with hematologic malignancies see a palliative care specialist? Hematology Am Soc Hematol Educ Program. 2015;2015:471–8. doi: 10.1182/asheducation-2015.1.471. [DOI] [PubMed] [Google Scholar]
- 6.LeBlanc TW. Palliative care and hematologic malignancies: old dog, new tricks? J Oncol Pract. 2014;10:e404–7. doi: 10.1200/JOP.2014.000968. [DOI] [PubMed] [Google Scholar]
- 7.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:e230–8. doi: 10.1200/JOP.2014.001859. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Howell DA, Shellens R, Roman E, et al. Haematological malignancy: are patients appropriately referred for specialist palliative and hospice care? A systematic review and meta-analysis of published data. Palliat Med. 2011;25:630–41. doi: 10.1177/0269216310391692. [DOI] [PubMed] [Google Scholar]
- 9.Howell DA, Roman E, Cox H, et al. Destined to die in hospital? Systematic review and meta-analysis of place of death in haematological malignancy. BMC Palliat Care. 2010;9:9. doi: 10.1186/1472-684X-9-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Hui D, Didwaniya N, Vidal M, et al. Quality of end-of-life care in patients with hematologic malignancies: a retrospective cohort study. Cancer. 2014;120:1572–8. doi: 10.1002/cncr.28614. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Hui D, Kim SH, Roquemore J, et al. Impact of timing and setting of palliative care referral on quality of end-of-life care in cancer patients. Cancer. 2014;120:1743–9. doi: 10.1002/cncr.28628. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Prigerson HG, Bao Y, Shah MA, et al. Chemotherapy Use, Performance Status, and Quality of Life at the End of Life. JAMA Oncol. 2015;1:778–84. doi: 10.1001/jamaoncol.2015.2378. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Temel JS, Greer JA, Muzikansky A, et al. Early palliative care for patients with metastatic non-small-cell lung cancer. N Engl J Med. 2010;363:733–42. doi: 10.1056/NEJMoa1000678. [DOI] [PubMed] [Google Scholar]
- 14.Temel JS, Greer JA, El-Jawahri A, et al. Effects of Early Integrated Palliative Care in Patients With Lung and GI Cancer: A Randomized Clinical Trial. J Clin Oncol. 2017;35:834–841. doi: 10.1200/JCO.2016.70.5046. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Bakitas M, Lyons KD, Hegel MT, et al. Effects of a palliative care intervention on clinical outcomes in patients with advanced cancer: the Project ENABLE II randomized controlled trial. Jama. 2009;302:741–9. doi: 10.1001/jama.2009.1198. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Bakitas MA, Tosteson TD, Li Z, et al. Early Versus Delayed Initiation of Concurrent Palliative Oncology Care: Patient Outcomes in the ENABLE III Randomized Controlled Trial. J Clin Oncol. 2015;33:1438–45. doi: 10.1200/JCO.2014.58.6362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Zimmermann C, Swami N, Krzyzanowska M, et al. Early palliative care for patients with advanced cancer: a cluster-randomised controlled trial. The Lancet. 2014;383:1721–1730. doi: 10.1016/S0140-6736(13)62416-2. [DOI] [PubMed] [Google Scholar]
- 18.Grudzen CR, Richardson LD, Johnson PN, et al. Emergency Department-Initiated Palliative Care in Advanced Cancer: A Randomized Clinical Trial. JAMA Oncol. 2016 doi: 10.1001/jamaoncol.2015.5252. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.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 doi: 10.1093/annonc/mdv028. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Odejide OO, Salas Coronado DY, Watts CD, Wright AA, Abel GA. End-of-life care for blood cancers: a series of focus groups with hematologic oncologists. J Oncol Pract. 2014;10:e396–403. doi: 10.1200/JOP.2014.001537. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Morikawa M, Shirai Y, Ochiai R, Miyagawa K. Barriers to the Collaboration Between Hematologists and Palliative Care Teams on Relapse or Refractory Leukemia and Malignant Lymphoma Patients’ Care: A Qualitative Study. Am J Hosp Palliat Care. 2016;33:977–984. doi: 10.1177/1049909115611081. [DOI] [PubMed] [Google Scholar]
- 22.Corbett CL, Johnstone M, Trauer JM, Spruyt O. Palliative care and hematological malignancies: increased referrals at a comprehensive cancer centre. J Palliat Med. 2013;16:537–41. doi: 10.1089/jpm.2012.0377. [DOI] [PubMed] [Google Scholar]
- 23.Niscola P, Tendas A, Giovannini M, et al. Caring for terminal patients in haematology: the urgent need of a new research agenda. Support Care Cancer. 2015;23:5–7. doi: 10.1007/s00520-014-2489-4. [DOI] [PubMed] [Google Scholar]
- 24.LeBlanc TW. Addressing End-of-Life Quality Gaps in Hematologic Cancers: The Importance of Early Concurrent Palliative Care. JAMA Intern Med. 2016;176:265–6. doi: 10.1001/jamainternmed.2015.6994. [DOI] [PubMed] [Google Scholar]
- 25.El-Jawahri A, LeBlanc T, VanDusen H, et al. Effect of Inpatient Palliative Care on Quality of Life 2 Weeks After Hematopoietic Stem Cell Transplantation: A Randomized Clinical Trial. Jama. 2016;316:2094–2103. doi: 10.1001/jama.2016.16786. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Kamal AH, Bull J, Kavalieratos D, et al. Development of the Quality Data Collection Tool for Prospective Quality Assessment and Reporting in Palliative Care. J Palliat Med. 2016 doi: 10.1089/jpm.2016.0036. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Kamal AH, Kavalieratos D, Bull J, et al. Usability and Acceptability of the QDACT-PC, an Electronic Point-of-Care System for Standardized Quality Monitoring in Palliative Care. J Pain Symptom Manage. 2015;50:615–21. doi: 10.1016/j.jpainsymman.2015.05.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Bruera E, Kuehn N, Miller MJ, Selmser P, Macmillan K. The Edmonton Symptom Assessment System (ESAS): a simple method for the assessment of palliative care patients. J Palliat Care. 1991;7:6–9. [PubMed] [Google Scholar]
- 29.Anderson F, Downing GM, Hill J, Casorso L, Lerch N. Palliative performance scale (PPS): a new tool. J Palliat Care. 1996;12:5–11. [PubMed] [Google Scholar]
- 30.Agar M, Currow D, Plummer J, et al. Changes in anticholinergic load from regular prescribed medications in palliative care as death approaches. Palliat Med. 2009;23:257–65. doi: 10.1177/0269216309102528. [DOI] [PubMed] [Google Scholar]
- 31.Fadul NA, El Osta B, Dalal S, Poulter VA, Bruera E. Comparison of symptom burden among patients referred to palliative care with hematologic malignancies versus those with solid tumors. J Palliat Med. 2008;11:422–7. doi: 10.1089/jpm.2007.0184. [DOI] [PubMed] [Google Scholar]
- 32.Manitta V, Zordan R, Cole-Sinclair M, Nandurkar H, Philip J. The symptom burden of patients with hematological malignancy: a cross-sectional observational study. J Pain Symptom Manage. 2011;42:432–42. doi: 10.1016/j.jpainsymman.2010.12.008. [DOI] [PubMed] [Google Scholar]
- 33.LeBlanc TW, Smith JM, Currow DC. Symptom burden of haematological malignancies as death approaches in a community palliative care service: a retrospective cohort study of a consecutive case series. Lancet Haematol. 2015;2:e334–8. doi: 10.1016/S2352-3026(15)00111-8. [DOI] [PubMed] [Google Scholar]
- 34.Johnsen AT, Tholstrup D, Petersen MA, Pedersen L, Groenvold M. Health related quality of life in a nationally representative sample of haematological patients. Eur J Haematol. 2009;83:139–48. doi: 10.1111/j.1600-0609.2009.01250.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Steensma DP, Heptinstall KV, Johnson VM, et al. Common troublesome symptoms and their impact on quality of life in patients with myelodysplastic syndromes (MDS): results of a large internet-based survey. Leuk Res. 2008;32:691–8. doi: 10.1016/j.leukres.2007.10.015. [DOI] [PubMed] [Google Scholar]
- 36.Romito F, Montanaro R, Corvasce C, Di Bisceglie M, Mattioli V. Is cancer-related fatigue more strongly correlated to haematological or to psychological factors in cancer patients? Support Care Cancer. 2008;16:943–6. doi: 10.1007/s00520-007-0357-1. [DOI] [PubMed] [Google Scholar]
- 37.Tchekmedyian NS, Kallich J, McDermott A, Fayers P, Erder MH. The relationship between psychologic distress and cancer-related fatigue. Cancer. 2003;98:198–203. doi: 10.1002/cncr.11463. [DOI] [PubMed] [Google Scholar]
- 38.Wagner LI, Cella D. Fatigue and cancer: causes, prevalence and treatment approaches. Br J Cancer. 2004;91:822–8. doi: 10.1038/sj.bjc.6602012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Hung YS, Wu JH, Chang H, et al. Characteristics of patients with hematologic malignancies who received palliative care consultation services in a medical center. Am J Hosp Palliat Care. 2013;30:773–80. doi: 10.1177/1049909112471423. [DOI] [PubMed] [Google Scholar]
- 40.Mannis GN, McNey LM, Gupta NK, Gross DM. The transfusion tether: Bridging the gap between end-stage hematologic malignancies and optimal end-of-life care. Am J Hematol. 2016;91:364–5. doi: 10.1002/ajh.24294. [DOI] [PubMed] [Google Scholar]
- 41.Odejide OO. A Policy Prescription for Hospice Care. Jama. 2016;315:257–8. doi: 10.1001/jama.2015.18424. [DOI] [PubMed] [Google Scholar]
- 42.Odejide OO, Cronin AM, Earle CC, Tulsky JA, Abel GA. Why are patients with blood cancers more likely to die without hospice? Cancer. 2017 doi: 10.1002/cncr.30735. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.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. Journal of Pain and Symptom Management. 2015;49:505–512. doi: 10.1016/j.jpainsymman.2014.07.003. [DOI] [PubMed] [Google Scholar]
- 44.Howlader N, AM N, M K, et al. SEER Cancer Statistics Review. In: 1975-2014. In: Howlader N, Noone AM, Krapcho M, Miller D, Bishop K, Kosary CL, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA, editors. SEER Cancer Statistics Review, 1975–2014. National Cancer Institute; Bethesda, MD: https://seer.cancer.gov/csr/1975_2014/, based on November 2016 SEER data submission, posted to the SEER web site, April 2017. [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1.
*Adjusted for age, gender, race, and performance score (PPS)
Bold denotes statistical significance at a threshold of p≤ 0.05.
OR—Odds Ratio
Univariate and multivariate logistic regression model for the relationship between unmet symptom needs and patient tumor type. Odds ratios greater than 1.0 suggest hematologic cancer patients are disproportionately affected by the listed symptoms as compared to solid tumor patients.