Factors associated with early quality-of-life response to palliative care during hematopoietic cell transplantation.

Introduction

Specialty palliative care (PC) improves quality of life (QOL) and reduces physical symptom burden and psychological distress during hematopoietic cell transplantation (HCT) hospitalization. 1 , 2 The benefits of specialty PC are sustained at 6 months after HCT, with improvement in depression and posttraumatic stress disorder (PTSD) symptoms. 3 Furthermore, HCT recipients have positive perceptions of PC. 4 Thus, the integration of PC into standard HCT care is immensely beneficial for patients with hematologic malignancy undergoing HCT.

Despite the benefits of PC in HCT, we do not have a detailed understanding of patient-, clinical-, and transplant-related factors that might be associated with response to PC intervention in this population. Previous studies demonstrate that PC clinicians focus on symptom management and coping support during HCT hospitalization, 5 and improvements in physical and psychological symptom burden mediate long-term improvements in psychological distress after HCT. 3 , 5 Interestingly, the use of supportive medications, including patient-controlled analgesia and atypical antipsychotics such as antiemetics, did not mediate the effect of integrated PC on QOL or psychological distress during HCT hospitalization. 5 In patients with advanced lung cancer and acute myeloid leukemia, coping is an important mediator of the benefits of integrated PC. Yet, understanding of the role of coping and the nature of PC visits in determining patients’ response to PC during HCT remains limited. 6 , 7 , 8

A comprehensive understanding of factors associated with response to PC during HCT hospitalization may play a crucial role in future implementation and adoption of PC interventions during HCT. Although specialty PC is effective and acceptable to HCT recipients, HCT clinicians remain reticent to involve specialty PC, in part due to a sense of ownership in addressing their patients’ supportive care needs. 9 , 10 Consequently, the availability and integration of specialty PC clinicians into standard HCT practice remains suboptimal, and significant workforce shortages further limit access to specialty PC for patients undergoing HCT. 11 , 12 A refined understanding of factors associated with PC response may be helpful in educating HCT clinicians and potentially identifying patients most likely to benefit from PC intervention during HCT.

In this secondary analysis, we aimed to describe early QOL response to PC during HCT hospitalization. We then explored baseline patient-, clinical-, and transplant-related factors that are associated with PC response. We subsequently evaluated the association between early QOL response to PC and longitudinal patient-reported QOL, symptoms, and coping. We then investigated the content of inpatient PC visits related to response to PC to further understand how PC improves outcomes in this population.

Methods

Study design

We conducted a secondary analysis of participants assigned to receive an integrated specialty PC intervention during HCT hospitalization in 2 randomized clinical trials: the first (ClinicalTrials.gov identifier: NCT02207322 ) was conducted at Massachusetts General Hospital, Boston, Massachusetts, from August 2014 to January 2016; and the second (ClinicalTrials.gov identifier: NCT03641378 ) was a multisite study at Massachusetts General Hospital, Duke University Hospital, Durham, North Carolina, and the Fred Hutchinson Cancer Center, Seattle, Washington, from October 2018 to July 2022. Only participants randomly assigned to receive the PC intervention were included in this analysis. The institutional review boards at all participating sites approved the studies, and all participants provided informed consent. Study procedures were consistent across sites and during the COVID-19 pandemic.

Participants

Eligibility criteria were the same for both studies. 13 , 14 Eligible participants were adults (age ≥18 years) with hematologic malignancies who were hospitalized to undergo allogeneic or autologous HCT and randomly assigned to receive the specialty PC intervention during HCT. Eligibility criteria also entailed the ability to read and respond to questions and complete questionnaires in English or Spanish, with assistance from an interpreter. With permission from their HCT clinician, study staff approached participants in person within 72 hours of their admission for HCT. We excluded participants undergoing HCT for benign hematologic conditions, those undergoing outpatient HCT, and patients with uncontrolled psychiatric or cognitive conditions, which the transplant clinicians believed would preclude their ability to provide informed consent. We also excluded patients who are already receiving inpatient PC. Of note, both studies stratified randomization by HCT type, ensuring balance among participants undergoing allogeneic and autologous HCT. In this secondary analysis, we included all participants randomized to the PC intervention and completed study assessments at baseline and week 2 during HCT hospitalization.

PC intervention

The PC intervention has been described previously in detail, and study protocols, manuals, and trainings were consistent across both studies. 13 , 14 During study trainings, PC clinicians received guidance on the timing of PC domain delivery during hospitalization. PC clinicians retained discretion to tailor study visits according to clinical judgment and patient preference. All participants included in this secondary data analysis received the integrated inpatient PC intervention during their hospitalization for HCT. The intervention entailed meeting with the inpatient PC clinician (physician or advance practice provider) for a minimum of twice weekly during their HCT hospitalization. Participants and PC clinicians were permitted to initiate additional visits as needed during HCT. Participants did not have any outpatient PC follow-up after discharge.

Sociodemographic and clinical data

Participants self-reported their demographic information, including age, gender, sex, ethnicity, marital status, employment status, education, and income. We also collected clinical variables from the electronic health record, including underlying diagnosis, transplant type, conditioning intensity, and the HCT comorbidity index (HCT-CI).

Patient-reported measures

Participants completed study questionnaires within 72 hours of HCT admission, during the second week of HCT hospitalization (ie, at hematologic nadir when they experience the lowest blood counts and highest symptom burden during HCT) and at 3 and 6 months after HCT. 13 , 15

QOL

We assessed participant QOL with the Functional Assessment of Cancer Therapy–Bone Marrow Transplant (FACT-BMT) scale. 16 Scores range from 0 to 148, with higher scores representing better QOL. FACT-BMT includes subscales assessing physical, functional, emotional, social well-being, and bone marrow transplant–specific concerns. A change of 7 points in FACT-BMT total score is considered clinically significant. 16

Physical symptoms

We used the revised Edmonton Symptom Assessment Scale (ESAS) to assess physical symptom burden. 17 The revised ESAS measures 10 symptoms on a scale of 0 to 10, with higher scores indicating greater symptom burden.

Psychological distress

We used the 14-item Hospital Anxiety and Depression Scale to assess depression and anxiety symptoms. 18 This scale contains 2 7-item subscales that measure symptoms of depression and anxiety within the past week. Each subscale ranges from 0 to 21, with higher subscale scores indicating worse symptoms. Scores >7 indicate clinically significant symptoms. We used the PTSD Checklist–Civilian Version to assess PTSD symptoms. 19 This checklist is a 17-item self-reported measure that evaluates the severity of PTSD symptoms. Scores range from 17 to 85, with higher scores indicating worse PTSD symptoms. Scores >33 are considered clinically significant.

Coping strategies

Participants’ use of coping strategies was measured with the Brief COPE, a 28-item questionnaire that assesses the use of 14 coping methods, with 2 items per method. 20 To reduce questionnaire burden, we limited our assessment to 7 coping strategies previously used in other studies among patients with hematologic malignancies. 21 , 22 As in previous studies, we grouped 7 coping strategies into 2 higher-order domains, informed by previous literature: approach-oriented coping (ie, use of emotional support, active coping, positive reframing, and acceptance) or avoidant coping (ie, self-blame, denial, and behavioral disengagement). 6 , 22 , 23 Higher scores correspond to higher use of the coping strategy. Approach-oriented coping scores range from 8 to 32, and avoidant coping scores range from 6 to 24.

Content of PC visits

During HCT hospitalization, PC clinicians completed weekly electronic surveys indicating the PC domains they addressed during their visits: relationship building, symptom management, illness coping, illness/HCT understanding and education, treatment goals and decision-making, advance care planning, and discharge disposition. Clinicians could select >1 content area and indicated which domain was the primary focus of the visits. When a content area was selected, the clinician was prompted to indicate the specific focus and recommended management strategy. For example, if clinicians selected symptom management, they indicated which of the following symptoms they addressed: pain, nausea/vomiting, diarrhea, constipation, insomnia, fatigue, depression, anxiety, and others. Each selected focus triggered follow-up questions, such as how symptoms were addressed, including education provided and medications recommended. Because most patients undergoing autologous or allogeneic HCT are hospitalized for 3 to 4 weeks, 24 , 25 , 26 we included PC visit content data through the first 4 weeks of HCT hospitalization.

Primary outcome: early QOL response to the PC intervention

We defined early QOL response to PC as change in QOL (FACT-BMT total score) from HCT admission to week 2 (ie, hematologic nadir). Positive values correspond to improvements in QOL. We used the median change in QOL in the study sample to define “high” and “low” responders to PC during HCT hospitalization. Previous studies of patients undergoing HCT or those with hematologic malignancies have used median split method to dichotomize patient-reported outcomes. 22 , 27 Given the observed clinically significant deterioration of QOL during HCT in previous studies and the exploratory nature of this analysis, 13 , 15 we elected to categorize high and low PC response with a study population–specific metric (ie, median split).

Statistical analysis

We calculated descriptive statistics, including means or medians for continuous variables and proportions for categorical variables. We considered a 2-sided P value <.05 as statistically significant. Given the exploratory nature of this secondary analysis, P values were not adjusted for multiple testing. We performed all statistical analyses using R version 4.4 (R Foundation for Statistical Computing, Vienna, Austria).

We used univariate logistic regression to identify baseline patient-, clinical-, and transplant-related factors that are associated with being a high PC responder. Given the exploratory and post hoc nature of these analyses, we elected to evaluate univariate (as opposed to multivariate) models. Of note, our included patient-reported outcomes are often correlated with each other, which precludes inclusion in multivariate models due to heteroskedasticity.

We characterized trajectories of changes in participants' outcomes using linear mixed-effects models. In our models, we included random participant intercepts and fixed effects for categorical time. Separate mixed-effects models were fit for each outcome. To explore differences in outcomes by response to PC, we added terms for high (vs low) response to PC and the interaction between PC and categorical time to our base models.

To describe the utilization and content of PC visits during HCT hospitalization, we used descriptive statistics to characterize PC utilization (number of PC visits and time spent) and assessed longitudinal changes in PC content. For each weekly PC clinician survey, we used descriptive statistics to report the primary focus of PC visits, the topic areas covered during the visits, and the PC interventions to address these topics. We grouped PC domains into 4 categories: “relationship,” “symptom management,” “education/coping,” and “advanced care planning, goals, and others.”

Given the low missingness rate of QOL data during HCT hospitalization (<5%) and PC clinician survey data (<2.5%), we used complete case method to assemble the data set and conduct analyses of outcomes and content of PC visits during HCT hospitalization. Our linear mixed-effects models incorporated all available data and were fit using maximum likelihood estimation.

Results

Baseline sociodemographic and clinical characteristics

Overall, 261 participants were randomized to the PC intervention during HCT across both trials, and 252 (96.6%) had complete data at baseline and week 2 and were included in this analysis. Table 1 displays the baseline sociodemographic and clinical characteristics of study participants. Most participants identified as male (n = 138 [54.8%]) and White (n = 196 [78.7%]) and were married or cohabitating with a long-term partner (n = 184 [73.3%]). The most common diagnoses were multiple myeloma (n = 81 [32.3%]) and acute leukemia (acute myeloid leukemia and acute lymphoblastic leukemia, n = 68 [27.1%]). A total of 129 participants (51.2%) underwent autologous HCT, 58 (23.0%) underwent allogeneic HCT with myeloablative conditioning, and 65 (25.8%) underwent allogeneic HCT with reduced-intensity conditioning. Table 1. Baseline characteristics of recipients of PC consultation n (%) Age, mean (SD) 55.9 (12.5) Female, n (%) 114 (45.2) Race White 196 (78.7) Black 23 (9.2) Asian 8 (3.2) American Indian/Alaskan 4 (1.6) Other 18 (7.2) Hispanic 20 (8) Married/cohabitating, n (%) 184 (73.3) College degree or higher, n (%) 135 (59.7) Income >$100 000, n (%) 89 (35.3) HCT-CI score, mean (SD) 2.1 (2) Diagnosis Acute leukemia 68 (27.1) MDS/MPN 42 (16.7) Lymphoma 60 (23.9) Multiple myeloma 81 (32.3) Transplant type Autologous 129 (51.2) MAC allogeneic 58 (23.0) RIC allogeneic 65 (25.8) Study Pilot ( NCT02207322 ) 80 (31.7) Multisite ( NCT03641378 ) 172 (68.3) Year of HCT 2014-2016 80 (31.8) 2018-2020 112 (44.4) 2021-2022 60 (23.8) MAC, myeloablative conditioning; MDS/MPN, myelodysplastic syndrome/myeloproliferative neoplasm; RIC, reduced-intensity conditioning; SD, standard deviation.

Early QOL responders to PC

Among participants receiving the PC intervention, the median change in QOL from HCT admission to week 2 was –10.7 points (interquartile range, –22.3 to 0.9; range, –77.0 to 52.0). Figure 1 displays baseline and week 2 QOL by high and low PC responders during HCT hospitalization. Figure 2 A displays the mean change in FACT-BMT subscales from HCT admission to week 2. Among high and low responders during HCT hospitalization, QOL domains that improved were emotional (mean Δ, 2.3 vs –0.65; P < .001), social (mean Δ, 1.1 vs –1.2; P < .001), and functional well-being (mean Δ, 1.1 vs –6.3; P < .001) and BMT subscale (0.8 vs –6.9; P < .001). High PC responders also experienced lower decrement in physical well-being from baseline to week 2 than low PC responders (–1.4 vs –10.2; P < .001). Figure 1. Parallel line plot depicting individual participants’ baseline and week 2 QOL (FACT-BMT total score) among high and low early responders to PC during HCT hospitalization. Response to PC was defined using the median split method of change in QOL from baseline (HCT admission) to week 2 (median QOL decrement, –10.7). In this plot, gray dots represent individual participants’ baseline QOL. Blue dots correspond to week 2 QOL of high PC responders, and red dots correspond to week 2 QOL of low PC responders. The lines represent the individual change in QOL from baseline to week 2. Figure 2. QOL during and after HCT hospitalization. (A) Mean change in FACT-BMT total subscales from HCT admission to week 2 by early QOL response to PC. (B) Mean QOL (±95% confidence interval) over time by early QOL response to PC, as estimated by linear mixed-effect model. In both graphs, blue corresponds to high PC responders, and red corresponds to low PC responders. Response to PC was defined using the median split method of change in QOL from HCT admission to week 2.

Association between patient-, clinical-, and transplant-related factors with response to PC

Table 2 displays baseline patient-, clinical-, and transplant-related factors by response to PC. A higher proportion of high PC responders self-identified with a minority race (38/126 [30.4%] vs 15/126 [12.1%]; odds ratio [OR], 3.2; CI, 1.7-6.3; P < .001). There were no differences in age, gender, ethnicity, marital status, education, income, HCT-CI scores, cancer diagnosis, HCT type, or conditioning intensity between high and low PC responders. Among all recipients of specialty PC, HCT type (allogeneic vs autologous) was not associated with differences in QOL, physical symptoms, and psychological distress before HCT or at week 2 of HCT hospitalization ( supplemental Table 1 ). Table 2. Baseline characteristics by response to PC consultation High PC responders, n (%) Low PC responders, n (%) P value ∗ Age, mean (SD) 55.3 (12.8) 56.5 (12.2) .45 Female 62 (49.2) 52 (41.3) .25 Minoritized race 38 (30.4) 15 (12.1) .001 Hispanic ethnicity 13 (10.4) 7 (5.6) .23 Married/cohabitating 90 (71.4) 94 (75.2) .63 College degree or higher 57 (45.2) 61 (48.4) .70 Income >$100 000 42 (33.3) 47 (37.3) .60 HCT-CI score, mean (SD) 2.0 (2.0) 2.2 (2.0) .42 Diagnosis Acute leukemia 36 (28.8) 32 (25.4) .51 MDS/MPN 18 (14.4) 24 (19.0) Lymphoma 27 (21.6) 33 (26.2) Multiple myeloma 44 (35.2) 37 (29.4) HCT type Autologous 65 (51.6) 64 (50.8) .23 MAC allogeneic 24 (19.0) 34 (27.0) RIC allogeneic 37 (29.4) 28 (22.2) Baseline PRO, mean (SD) QOL 101.0 (22.2) 110.8 (15.8) <.001 Physical sx 21.3 (17.7) 15.7 (12.0) .004 Depression sx 4.7 (3.6) 4.1 (3.0) .14 Anxiety sx 5.5 (4.1) 4.7 (3.2) .11 PTSD sx 27.5 (10.3) 24.4 (7.1) .007 MAC, myeloablative conditioning; MDS/MPN, myelodysplastic syndrome/myeloproliferative neoplasm; RIC, reduced-intensity conditioning; PRO, patient-reported outcomes; SD, standard deviation; sx, symptoms. ∗ P values derived from t tests for continuous variables and Fisher's exact test for categorical variables.

Patients with lower baseline QOL (OR, 0.97; CI, 0.96-0.99; P < .001) and higher physical symptoms (OR, 1.02; CI, 1.0-1.04; P = .004) and PTSD symptoms (OR, 1.04; CI, 1.01-1.07; P = .008) were more likely to be high PC responders. Baseline depression (OR, 1.06; CI, 0.98-1.14; P = .13) and anxiety (OR, 1.06; CI, 0.99-1.13) were not associated with response to PC.

QOL trajectory based on response to PC using linear mixed-effects model

Figure 2 B displays QOL trajectories among high and low PC responders. As expected, high PC responders reported better QOL at week 2 than low PC responders (104.9 [CI, 101.4-108.5] vs 85.4 [CI, 81.9-89.0]; P < .001). However, there were no differences in QOL among high and low early PC responders at 3 months (108.1 [CI, 104.4-111.9] vs 108.1 [CI, 104.4-111.8]; P = .94) and 6 months after HCT (110 [CI, 106.2-113.7] vs 111.3 [CI, 107.5-115.1]; P = .61).

Physical symptom trajectory by PC response using linear mixed-effect model

At week 2, high PC responders reported fewer physical symptoms (ESAS score, 28.1 [CI, 25.2-31.1] vs 41.9 [CI, 38.9-44.8]; P < .001) than low PC responders. There were no differences in physical symptoms at 3 months (17.7 [CI, 14.5-20.8] vs 16.6 [CI, 13.4-19.8]; P = .65) and 6 months after HCT (17.7 [CI, 14.5-20.8] vs 16.6 [CI, 13.5-19.8]; P = .65).

Psychological distress during and after HCT hospitalization by PC response

At week 2, high responders were less likely to report clinically significant depression symptoms (25/126 [20.6%] vs 51/126 [40.5%]; P < .001) compared with low PC responders. There was no difference in clinically significant anxiety (25/126 [20.6%] vs 19/126 [15.1%]) and PTSD symptoms (14/95 [14.7%] vs 17/72 [23.6%]; P = .21) among high and low PC responders. At 6 months after HCT, high PC responders were more likely to report clinically significant anxiety symptoms (26/97 [26.8%] vs 11/84 [13.1%]; P = .03) than low PC responders. In addition, at 6 months after HCT, there was no difference in rates of clinically significant depression (17/98 [17.5%] vs 11/84 [13.1%]; P = .54) and PTSD symptoms (18/100 [18.0%] vs 11/102 [10.8%]; P = .21) by PC response.

Coping strategy trajectory by PC response using linear mixed-effect models

A total of 172 participants (68.3%) included in this analysis reported the use of coping strategies at baseline. Figure 3 displays the trajectory of approach-oriented and avoidant coping by response to PC. Figure 3. Mean approach-oriented and avoidant coping scores (±95% confidence interval) over time by early QOL response to PC during HCT hospitalization as estimated by linear mixed-effect models. Approach-oriented coping scores range from 8 to 32, and avoidant coping scores range from 6 to 24. In both graphs, blue corresponds to high PC responders, and red corresponds to low PC responders. Response to PC was defined using the median split method of change in QOL from HCT admission to week 2.

There was no difference in baseline approach-oriented coping between high and low PC responders (26.4 [CI, 25.4-27.4] vs 25.4 [CI, 24.3-26.6]; P = .23). High PC responders reported a higher use of approach-oriented coping at week 2 (26.7 [CI, 25.7-27.8] vs 24.3 [CI, 23.1-25.5]; P = .002) and 3 months (25.7 [CI, 24.6-26.8] vs 24.0 [CI, 22.8-25.3]; P = .04) and 6 months after HCT (25.8 [CI, 24.7-26.9] vs 23.2 [CI, 21.9-24.5]; P = .003) than low PC responders.

There was no difference between high and low PC responders in the use of avoidant coping at baseline, week 2, or 3 months after HCT ( Figure 3 ). At 6 months after HCT, high PC responders reported a higher use of avoidant coping (7.6 [CI, 7.1-8.1] vs 6.6 [CI, 6.0-7.3]; P = .02) than low PC responders.

PC visit content by PC response

A total of 246 participants (97.6%) had available PC clinician data and were included in this analysis. PC clinicians reported 931 PC clinician surveys during the first 4 weeks of HCT hospitalization. There were no differences in the number of PC visits, total number of minutes spent on PC visits, or initial PC assessment of patient condition among high and low PC responders ( Table 3 ). Given the longer length of stay during allogeneic HCT than autologous HCT (mean days, 27.8 vs 17.7; t test, P < .001), participants undergoing allogeneic HCT received more PC study visits and overall time with PC clinicians than those undergoing autologous HCT ( supplemental Table 2 ). Table 3. Characteristics of PC visits by response to PC category High PC responders Low PC responders P value ∗ Clinician surveys, mean (SD) 3.8 (1.4) 4.2 (1.6) .09 Visits 7.5 (4.4) 8.3 (4.0) .17 Time, min 226.2 (124.4) 240.8 (111.8) .34 Initial assessment of patient condition, n (%) Poor 0 (0.0) 1 (0.8) .57 Fair 21 (17.9) 19 (16.0) Good 96 (82.1) 99 (83.2) ∗ P values derived from t tests for continuous variables and Fisher's exact test for categorical variables.

Figure 4 displays change in the primary focus of PC visits during HCT hospitalization from the initial PC consultation to the fourth weekly PC follow-up survey among high and low PC responders. Relationship building was the primary focus during most PC initial consult visits for both groups (82/121 [67.8%] vs 82/125 [65.6%]). During follow-up PC visits, symptom management became the predominant focus. The proportion of visits with symptom management as the primary focus among high and low PC responders was 34.7% (41/118) vs 43.5% (54/124) at week 1; 43.7% (49/112) vs 63.6% (75/118) at week 2; 62.7% (42/67) vs 69.1% (56/81) at week 3; and 64% (16/25) vs 52.5% (21/40) at week 4. High PC responders had more follow-up visits with a primary focus on coping and illness/HCT education than low PC responders: week 1, 22.0% (26/118) vs 12.1% (15/124); week 2, 24.1% (27/112) vs 14.4% (17/118); week 3, 22.4% (15/67) vs 9.9% (8/81); and week 4, 16% (4/25) vs 27.5% (11/40). Across symptoms experienced during HCT, a higher proportion of high PC responders received symptom education during hospitalization ( Figure 5 ). Figure 4. Proportion of weekly PC visits with a primary focus on relationship building (relationship), illness coping and education (coping/education), symptom management, and other (ACP, goals, and dispo) across HCT hospitalization by response to PC group. The denominator of each bar graph represents the total weekly number of PC visits per PC response group. Blue corresponds to high PC responders, and red corresponds to low PC responders. Response to PC was defined using the median split method of change in QOL from HCT admission to week 2. ACP, advanced care planning; dispo, disposition. Figure 5. Proportion of patients during HCT hospitalization receiving individual symptom education by early QOL response to PC. Blue corresponds to high PC responders, and red corresponds to low PC responders. Response to PC was defined using the median split method of change in QOL from HCT admission to week 2.

Supplemental Table 3 displays the proportion of participants who received at least 1 specialty PC visit with a primary focus of relationship building, symptom management, coping/illness education, and advanced care planning, goals, and hospital disposition by HCT type. A higher proportion of participants undergoing allogeneic HCT received at least 1 PC visit primarily focused on symptom management during HCT hospitalization than those undergoing autologous HCT (83.4% vs 65.6%).

Discussion

In this study, we found that a patient’s race, baseline QOL, and symptom burden at the time of admission for HCT were associated with early QOL response to PC intervention during HCT hospitalization. Interestingly, high PC responders maintained approach-oriented coping strategies during HCT and up to 6 months after transplant and had a higher proportion of PC visits focused on coping, HCT education, and symptom education, as opposed to symptom management. These findings provide insights into identifying patients who may respond most effectively to the PC intervention as well as how PC improves outcomes in this population.

This is, to our knowledge, the largest study to date describing factors associated with response to PC in patients undergoing HCT. Given the high symptom burden associated with conditioning chemotherapy and the isolation of HCT hospitalization, 15 integrated PC for HCT recipients is thought to primarily attenuate the expected QOL decline through comprehensive symptom management and coping support. 5 , 13 Although this framework holds, on average, across HCT recipients receiving PC, our analysis refines this model of response to PC during HCT hospitalization. First, there is substantial variation in QOL changes during HCT hospitalization, and many high responders to PC surprisingly report clinically significant improvement in QOL at week 2 compared with their baseline QOL at the time of HCT admission. Patients with hematologic malignancies experience tremendous uncertainty in their illness and HCT course, which contributes to decreased QOL and increased psychological distress. 28 Thus, it is plausible that PC’s emphasis on symptom education and coping attenuates this uncertainty, enabling adequate preparation for the HCT course and facilitating improvements in QOL during the HCT hospitalization. It is notable that conditioning intensity was not associated with response to PC in our study, which further supports the hypothesis that realistic expectations of physical and psychological symptoms during hematologic nadir and intensive symptom management support leads to higher response to PC. In addition, we did not observe that HCT type was associated with early QOL response to PC. Our data affirm prior findings of similar patient experiences during hospitalization for autologous and allogeneic HCT, 15 highlighting the need to tailor supportive care to patient needs as opposed to HCT type alone.

Our study adds to the growing literature regarding the effect of integrated PC among racial and ethnic minorities. It is intriguing that patients who identify as racial minorities were more likely to be high PC responders. Prior studies of integrated PC in patients with hematologic malignancy had limited racial and ethnic diversity. 13 , 29 Disparities in PC utilization in terms of symptom management, illness communication, and treatment decision-making among racial and ethnic minorities are well documented. 30 Our findings emphasize that PC may play a particularly important role in supporting racial and ethnic minorities during HCT hospitalization and underscore the importance of developing supportive care models to increase the availability of PC for underrepresented minorities with hematologic malignancies.

It is encouraging that integrated PC particularly helps those with worse baseline QOL and symptom burden, which are typically associated with worse post-HCT outcomes. 31 , 32 A recent multicenter study in patients with advanced lung cancer demonstrated that a stepped PC model, considering QOL decrements to tailor the PC dose, was noninferior to monthly early integrated PC in this population. 33 These findings support the use of patient-reported outcomes to tailor PC for patients with cancer. 33 Our findings highlight a high-risk population, identifying patients who may benefit the most from an augmented PC intervention during HCT. Providing PC to patients most likely to benefit may also help alleviate the mounting pressures on our PC workforce, given the known shortages in the availability of PC clinicians to meet the needs of all patients with cancer. 11 , 12 , 28 Future studies should evaluate how to incorporate patient-reported outcomes as well as other potential triggers to identify patients who may benefit the most from the incorporation of early PC during HCT hospitalization.

Our findings further establish the critical importance of coping support and HCT education in the integrated PC efforts to improve QOL during HCT hospitalization. Previous studies of PC integration in patients with advanced solid tumors and acute leukemia have consistently found that improvements in patient’s coping mediate the benefits of PC intervention on patient-reported outcomes. 5 , 6 , 8 , 21 Our results at both the PC visit and patient levels are consistent: those with higher responses to PC receive more visits focused on coping and subsequently maintain the use of adaptive coping strategies. Even in the realm of symptom management, those with higher responses to PC received more comprehensive symptom education than those with lower responses. These findings have important clinical implications for the development and testing of alternative supportive care models such as primary PC, in which HCT clinicians are trained to incorporate PC domains into their clinical practice. Our findings also underscore the critical importance of communication training, with a particular focus on coping and HCT education as a priority for future primary PC interventions.

Finally, our study highlights the potential need for supportive care interventions to improve QOL after HCT. The specialty PC interventions evaluated in the included clinical trials were limited to the inpatient setting and designed to improve QOL during HCT hospitalization. However, events after HCT, including graft-versus-host disease, infection, and disease relapse, negatively affect QOL, 34 , 35 , 36 , 37 and additional studies are needed to design supportive care interventions for these vulnerable post-HCT populations. It is also not known whether patients with early QOL response to PC are the same as those who experience durable long-term benefits such as reduction in PTSD symptoms. In fact, our null findings of psychological distress outcomes at 6 months after HCT despite maintenance in longitudinal approach-oriented coping suggest that those with early and late benefits of specialty PC may be different. Future work is sorely needed to evaluate QOL and symptom trajectories after HCT.

Our study has several limitations. First, this was an exploratory analysis. Results are intended to be hypothesis generating, and we cannot make any causal inferences from our findings. Given the exploratory and post hoc study design, we accordingly did not conduct multivariate analyses. Although PC response groups were balanced according to key clinical and transplant characteristics, our analyses may not completely account for confounding variables, including patient and study site factors. Second, although >20% of the study population identified as a minoritized race, most patients identified as White, were married, received at least a college-level education, and reported a high family income. Thus, our findings may not be generalizable across racial, ethnic, and socioeconomic groups. Third, the included studies encompassed a wide range of years (2014-2022) during which HCT clinical and supportive care practices greatly evolved. It is plausible that a secular trend of improvement in HCT and supportive care techniques influences observed response to PC during HCT hospitalization over the study period. Fourth, the decision to dichotomize PC response using the median may limit generalizability, and future work is needed to optimally define response to supportive care interventions during HCT. Using established cut points for clinically significant changes is an alternative approach to define improved and/or stable QOL. However, during intense interventions such as HCT, supportive care interventions such as specialty PC still likely benefits those with clinically significant deteriorations, and careful attention is needed to avoid labeling those patients as “nonresponders.”

In summary, patient-level factors such as pre-HCT patient-reported outcomes and PC visit content emphasizing coping support and illness education likely affect response to PC among patients undergoing HCT. Future studies are needed to confirm these findings and examine strategies to best tailor PC and other scalable supportive care interventions to meet the needs of patients undergoing HCT.

Conflict-of-interest disclosure: J.W. reports honoraria from 10.13039/100013596 American Academy of Hospice and Palliative Medicine . V.J. reports honoraria from, and is the cochair of clinical advisory board for, Tuesday Health. T.W.L. reports honoraria for consulting/advisory boards from 10.13039/100006483 AbbVie , Agilix, 10.13039/100016471 Agios / 10.13039/501100011725 Servier , 10.13039/100019531 Apellis , Astellas , BeiGene, BlueNote, Bristol Myers Squibb ( BMS )/ 10.13039/100006436 Celgene , 10.13039/100004328 Genentech , 10.13039/100005564 Gilead , GlaxoSmithKline ( GSK) , Lilly , Menarini/Stemline, Meter 10.13039/100018696 Health , 10.13039/100004336 Novartis , and Pfizer; speaking-related honoraria from 10.13039/100006483 AbbVie , 10.13039/100016471 Agios , Astellas , BMS / 10.13039/100006436 Celgene , GSK , 10.13039/100017655 Incyte , and Rigel; equity interest in Dosentrx and Thyme Care (stock options in privately held companies); royalties from UpToDate; and research funding from 10.13039/100006483 AbbVie , 10.13039/100004325 AstraZeneca , BMS , Deverra Therapeutics/Coeptis, GSK , 10.13039/100011096 Jazz Pharmaceuticals , and Seattle Genetics. The remaining authors declare no competing financial interests.

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Supplementary Material

Supplemental Tables

Acknowledgments

Time for data analysis and manuscript preparation was supported by the 10.13039/100000054 National Cancer Institute through grants R01CA222014 (A.E.-J.), K08CA251654 (H.L.A.), and T32CA092203 (R.N.). T.W.L. is a scholar in Clinical Research awardee of the Leukemia & Lymphoma Society.

Authorship

Contribution: R.N., H.L.A., and A.E.-J. conceived and designed analysis; R.N., A.R.K., K.C.W., M.R., P.L., and K.O. contributed to data collection and contribution; R.N. and D.J.R. performed the analysis; and all authors wrote and edited the manuscript.

Presented in abstract form at the 66th anual meeting of the American Society of Hematology, 9 December 2024, San Diego, CA.

The data that support the findings of this study are available upon reasonable request from the corresponding author, Richard Newcomb ( richard.newcomb@mgh.harvard.edu ).

The full-text version of this article contains a data supplement.