Abstract
This secondary analysis of a large, multi-center Blood and Marrow Transplant Clinical Trials Network (BMT CTN) randomized trial assessed whether patient-reported outcomes (PROs) and socioeconomic status (SES) before hematopoietic stem cell transplantation (HCT) are associated with each other and predictive of clinical outcomes including time to hematopoietic recovery, acute graft-versus-host disease, hospitalization days, and overall survival (OS) among 646 allogeneic and autologous HCT recipients. Pre-transplant Cancer and Treatment Distress (CTXD), Pittsburgh Sleep Quality Index (PSQI), and mental and physical component scores (MCS and PCS) of the SF-36 were correlated with each other and with SES variables. PROs and SES variables were further evaluated as predictors of clinical outcomes, with the PSQI and CTXD evaluated as OS predictors (p<.01 considered significant given multiple testing). Lower attained education was associated with increased distress (p=.002); lower income was related to worse physical functioning (p=.005) and increased distress (p=.008); lack of employment pre-transplant was associated with worse physical functioning (p<.01); unmarried status was associated with worse sleep (p=.003). In this large heterogeneous cohort of HCT recipients, while PROs and SES variables were correlated at baseline, they were not associated with any clinical outcomes. Future research should focus on HCT recipients at greater psychosocial disadvantage.
Keywords: patient-reported outcomes, socioeconomic status, quality of life, hematopoietic cell transplantation, hematopoietic recovery, survival
Introduction
Previous research has shown that baseline patient-reported outcome (PRO) and socioeconomic status (SES) measures predict morbidity and mortality following hematopoietic cell transplantation (HCT) [1–6]. In contrast to other cancer populations, there is minimal published research investigating more proximal clinical events or immunologic determinants to suggest candidate biobehavioral mechanisms that might explain this relationship [7,8]. Lower levels of optimism and increased anxiety, depression, and post-traumatic symptoms in the peri-transplant period are associated with impaired white blood cell recovery post-HCT [9–11]. Increased anxiety has also been associated with acute graft-versus-host disease (GVHD) [12] and depression has been associated with increased inflammation [10]. Finally, absence of spirituality has been associated with greater incidence of infection, sepsis, and GVHD [5]. However, these studies have been limited by small sample sizes derived from single institutions, retrospective designs, and utilization of a variety sampling measures, some of which are non-validated.
Social factors, including SES, confer risk for adverse HCT outcomes [2,13,14]. In other cancer populations such as laryngeal and prostate cancer as well as multiple myeloma, SES-related outcome disparities persist after controlling for differences in access to care and health behaviors [15–19]. The mechanisms by which SES and social factors affect outcomes are not well defined. Lifestyle and stress associated with low SES can activate psychobiological processes that lead to altered neural, endocrine, and immune activation [20,21]. A recent study suggests that low SES among unrelated donor HCT recipients is associated with increased gene expression patterns representative of chronic adversity [22]. This gene profile is predictive of adverse clinical outcomes including increased relapse and decreased leukemia-free survival [22].
The purpose of the current study was to evaluate whether PROs and SES factors influence morbidity and mortality outcomes among HCT recipients from a large Blood and Marrow Transplant Clinical Trials Network (BMT CTN) randomized controlled trial (RCT) [23]. The RCT was a 2×2 factorial trial of whether an exercise and/or a stress intervention versus usual care for each improved quality of life (QOL) after HCT, in which participants additionally reported survey data prior to HCT and randomization. The primary aim of the current study was to examine the relationship between self-reported pre-HCT PROs and SES and determine whether these factors were associated with time to hematopoietic recovery. Secondary endpoints included acute GVHD (aGVHD), days of life out of the hospital within the first 100 days, and overall survival (OS). Specifically, we hypothesized that 1) worse pre-transplant PROs (including distress, sleep quality, and physical and mental health-related QOL) would be associated with adverse SES factors, and 2) better pre-transplant PROs and SES would predict decreased time to hematopoietic recovery, decreased incidence and severity of aGVHD, increased days of life out of the hospital within the first 100 days, and better OS.
Methods
Participants
The current study was a secondary analysis of BMT CTN protocol 0902, a randomized trial of the effect of self-directed exercise and stress management on QOL in HCT recipients (ClinicalTrials.gov identifier: NCT01278927, protocol available at www.bmtctn.net) [23]. BMT CTN 0902 inclusion criteria were: age ≥18 years, ability to exercise at low to moderate intensity (as judged by self-reported ability to walk up 1 flight of stairs), no requirement for supplemental oxygen, and autologous or allogeneic transplant to occur within six weeks of trial enrollment. Exclusion criteria included orthopedic, neurologic, or other problems that prevented safe ambulation or adherence to the protocol; participation in another trial with HR-QOL or functional status as a primary endpoint; planned donor lymphocyte infusion within 100 days after HCT; planned tandem transplantation; and planned anticancer therapies other than tyrosine kinase inhibitors or rituximab within 100 days after HCT. The 0902 trial was designed to be broadly representative of the general HCT population. A protocol review committee appointed by the National Heart, Lung and Blood Institute (NHLBI) and all participating transplant center Institutional Review Boards or Ethics Committees approved the research protocol. All participants provided written informed consent. Eligible participants for this secondary analysis were those from the BMT CTN 0902 trial (n=711) who 1) completed the baseline assessment and 2) had Center for International Blood and Marrow Transplantation (CIBMTR) pre- and post-transplant essential data (TED) forms completed. The final analysis included 310 allogeneic HCT recipients and 336 autologous HCT recipients; this final sample of n=646 included patients from the original study who were evaluable for multivariate analysis and were not missing data on pertinent major variables. The parent study did not show an effect of the intervention on the primary outcomes, which were the Physical and Mental Component Summary (PCS and MCS) scores of the Medical Outcomes Study Short Form 36 (SF-36) at Day +100 [23]. Therefore, we did not anticipate that the intervention would confound our interpretation of the prognostic ability of our selected PRO measures to predict clinical outcomes.
Data Collection Instruments
The pre-transplant PRO measures completed at study enrollment included: 1) Cancer and Treatment Distress (CTXD) [24,25], a 27-item measure of distress with subscales of uncertainty, health burden, family strain, identity, and managing the medical system, as well as distress interference with function; 2) Pittsburgh Sleep Quality Index (PSQI) [26,27], a 7-item measure of sleep patterns and difficulties such as sleep quality, sleep latency, sleep efficiency, and use of sleeping medications; and 3) the SF-36, a 36-item, generic multidimensional health-related QOL measure with two summary domains, a physical (PCS) and a mental (MCS) component and 8 subscales. The age- and sex-adjusted normal population mean for the MCS and PCS is 50 with a standard deviation of 10. A clinically meaningful change is considered to be 0.5 standard deviation, or 5 points, with higher scores indicating better health-related QOL. For the CTXD and PSQI, higher scores indicate greater symptom burden; a CTXD score of >1.1 is indicative of more clinically significant distress [28] and a PSQI score of >5 indicates disturbed sleep as adjusted for cancer populations [26,27].
Measurements of SES included patient-reported marital status, education level, employment status, and household income in the past year. Data collection was performed through the BMT CTN and the CIBMTR [23].
Study Outcomes
The primary outcome was time to hematopoietic recovery, defined as time to absolute neutrophil count (ANC) > 0.5 × 109/L sustained for three consecutive days for neutrophil engraftment, and time to achieve a platelet count of >20 × 109/L independent of platelet transfusions for seven consecutive days for platelet engraftment. Secondary outcomes included days of life out of the hospital within the first 100 days after HCT and incidence of grade II-IV aGVHD (among allogeneic recipients), defined as occurrence (yes vs. no) of stage II-IV skin, gastrointestinal or liver abnormalities fulfilling the NIH Consensus criteria of aGVHD by 6 months. OS was evaluated as death from any cause, with the time to this event defined as the days from HCT to death or last follow-up.
Statistical Analyses
As a first step, linear regression was used to define associations between each pre-transplant PRO on SES and clinical variables. Data on all 646 patients were used for fitting these linear models.
Next, generalized linear models were used to assess whether PRO and SES measures predicted time to neutrophil and platelet engraftment, incidence of aGVHD by day 180 after transplant, the number of days out of the hospital in the first 100 days following transplant, and OS. The PROs MCS and PCS were not assessed as predictors of OS in these models, as these results have been previously reported by Wood et al [29]. Cox proportional hazards models were used for the time-to-event outcomes (OS, engraftment), logistic regression was used to model the probability of having aGVHD (allogeneic recipients only) by day 180, and Poisson and negative binomial regression were used to model the number of days out of hospital in the first 100 days. Separate models were constructed for autologous and allogeneic HCT patients.
Each of these models adjusted for the four SES factors and other relevant clinical variables. Tested clinical variables included age, baseline Karnofsky performance score (KPS; site-reported, not validated by independent review), alcohol use (yes/no), tobacco use (yes/no), body mass index at baseline, hematopoietic cell transplantation-specific comorbidity index (HCT-CI) [30], disease risk index (DRI) [31], prior transplant (yes/no), conditioning regimen (myeloablative or not), and graft type (bone marrow, peripheral blood, or cord blood). Additional clinical variables analyzed for allogeneic transplants included cytomegalovirus (CMV) status, degree of donor/recipient matching, anti-thymocyte globulin (ATG)/Campath use, and GVHD prophylaxis. Stepwise variable selection at a 0.05 significance level was used to identify the clinical variables to include in the final linear and generalized linear models. Because they were found to affect the PROs, the four SES variables were included in all final models, regardless of their statistical significance.
The correlation between each pair of SES and PRO variables was checked to assess for collinearity between predictors. The final assessment of whether the PRO and SES variables impacted the outcomes in these models was made using a significance level of 0.01. This stricter criterion was chosen to help control the overall false positive rate due to the number of main effects and outcomes considered.
For the primary outcome of interest (time to hematopoietic recovery), we assessed the power of the Cox model to detect differences of 20% and 10% in engraftment rates of neutrophils at day 14 and platelets at day 28 between patients in the low and high categories of PSQI (≤5 vs. >5) and CTXD (≤1.1 vs. >1.1). The engraftment rates for the low (control) categories were assumed to be the estimates obtained from the Aalen-Johansen estimators of cumulative incidence at day 14/28 for these groups. Power was assessed separately for each of these two factors, for each engraftment rate, and for patients of each transplant type. For neutrophil engraftment, we had > 84% power for each factor with both autologous and allogeneic patients to detect a 20% difference. For platelet engraftment, we had > 80% power in autologous patients and > 90% power in allogeneic patients to detect a 20% difference for each factor. For both neutrophil and platelet engraftment, we found that we had low power to detect a 10% difference, ranging from 18–34% for each factor with both autologous and allogeneic patients.
Testing found no violation of the proportional hazards assumption for any predictor in the Cox models. Cause-specific hazard rates were modeled for the engraftment outcomes, which are competing risks. All analyses were performed in SAS 9.4 (SAS Institute, Cary, NC).
Results
Participant characteristics
Baseline characteristics for the 646 individuals included in these analyses are shown in Tables 1 and 2. Allogeneic transplant-specific variables are included in Table 3. The population was evenly divided between autologous and allogeneic HCT recipients. Fifty-nine percent of recipients had a Karnofsky Performance Status ≥ 90, 80% had an education level greater than a high school degree, 53% were not employed at the time of transplant, and two-thirds (66%) had an income at the time of HCT of ≥ $50,000. At the time of analysis, the median follow-up of survivors was 13 months for autologous transplant recipients and 23 months for allogeneic recipients.
Table 1.
Baseline patient demographic characteristics of secondary analysis participants
| Variable | Autologous | Allogeneic |
|---|---|---|
| Number of enrolled patients | 336 | 310 |
| Number of centers | 23 | 19 |
| Age at transplant, years, median(range) |
59 (19–76) | 54 (20–75) |
| Age at transplant, n (%) | ||
| ≤ 40 | 29 (9) | 58 (19) |
| 40-<65 | 211 (63) | 205 (66) |
| ≥ 65 | 96 (29) | 47 (15) |
| Ethnicity, n (%) | ||
| Hispanic | 20 (6) | 15 (5) |
| Non-Hispanic | 316 (94) | 295 (95) |
| Race, n (%) | ||
| American Indian/Alaska | 0 | 1 (<1) |
| Native | ||
| Asian | 5 (1) | 5 (2) |
| Hawaiian/Pacific Islander | 0 | 3 (<1) |
| Black or African American | 44 (13) | 10 (3) |
| White | 285 (85) | 284 (92) |
| More than one race | 1 (<1) | 5 (2) |
| Other/unknown | 1 (<1) | 2 (<1) |
| Recipient sex, n (%) | ||
| Male | 193 (57) | 173 (56) |
| Female | 143 (43) | 137 (44) |
| Marital status, n (%) | ||
| Married/Living with partner | 243 (72) | 242 (78) |
| Single, never married | 32 (10) | 39 (13) |
| Separated, Divorced | 47 (14) | 20 (6) |
| Widowed | 10 (3) | 7 (2) |
| Missing | 4 (1) | 2 (<1) |
| Education, n (%) | ||
| <=High School | 68 (20) | 60 (19) |
| College graduate | 197 (59) | 191 (62) |
| Postgraduate | 69 (21) | 58 (19) |
| Missing | 2 (<1) | 1 (<1) |
| Employment status, n (%) | ||
| No | 184 (55) | 160 (52) |
| Yes | 152 (45) | 150 (48) |
| Income, n (%) | ||
| Under $15,000 | 16 (5) | 21 (7) |
| $15,000–$24,999 | 23 (7) | 21 (7) |
| $25,000–$49,999 | 71 (21) | 52 (17) |
| $50,000–$74,999 | 71 (21) | 64 (21) |
| $75,000–$99,999 | 48 (14) | 40 (13) |
| $100,000 or above | 87 (26) | 92 (30) |
| Missing | 20 (6) | 20 (6) |
| Karnofsky score, %, n (%) | ||
| ≥ 90 | 192 (57) | 190 (61) |
| 70 – 80 | 139 (41) | 113 (36) |
| 50 – 60 | 5 (1) | 5 (2) |
| Missing/Not done | 0 | 2 (<1) |
| Tobacco use, n (%) | ||
| No | 306 (91) | 288 (93) |
| Yes | 28 (8) | 20 (6) |
| Unknown | 2 (<1) | 2 (<1) |
| Alcohol use, n (%) | ||
| No | 189 (56) | 190 (61) |
| Yes | 146 (43) | 120 (39) |
| Unknown | 1 (<1) | 0 |
| BMI, median (range) | 28.31 (16.10–52.27) | 27.65 (17.06–55.55) |
| BMI, n(%) | ||
| < 25 | 78 (23) | 88 (28) |
| 25– 29.9 | 125 (37) | 112 (36) |
| ≥ 30 | 133 (40) | 110 (35) |
| Baseline intervention, n (%) | ||
| No | 2 (<1) | 4 (1) |
| Yes | 333 (99) | 306 (99) |
| Unknown | 1 (<1) | 0 |
| Baseline SF36 Physical Component Score |
||
| Median | 43 | 44 |
| IQR | 34–49 | 36–51 |
| Range | 13–64 | 13–65 |
| Baseline SF36 Mental Component Score |
||
| Median | 52 | 52 |
| IQR | 46–58 | 43–57 |
| Range | 18–74 | 7–68 |
| PSQI at baseline | ||
| Median | 4.0 | 4.0 |
| IQR | 2.0–7.0 | 2.0–6.0 |
| Range | 0.0–14.0 | 0.0–15.0 |
| Missing | 8 | 11 |
| CTXD at baseline | ||
| Median | 1.0 | 1.1 |
| IQR | 0.7–1.5 | 0.8–1.6 |
| Range | 0.0–2.8 | 0.0–3.0 |
| Exercise Intervention, n (%) | ||
| No | 165 (49.1) | 150 (48.4) |
| Yes | 171 (50.9) | 160 (51.6) |
| Stress Intervention, n (%) | ||
| No | 167 (49.7) | 157 (50.6) |
| Yes | 169 (50.3) | 153 (49.4) |
| Median follow-up of survivors (range), months |
13 (2–36) | 23 (6–35) |
Table 2.
Baseline disease related characteristics of secondary analysis participants
| Variable | Autologous | Allogeneic |
|---|---|---|
| Disease, n (%) | ||
| AML/ALL | 0 | 163 (53) |
| CML | 0 | 12 (4) |
| MDS/MPS | 0 | 44 (14) |
| MM/PCD | 172 (51) | 14 (5) |
| Lymphoma | 164 (49) | 57 (18) |
| CLL/SLL | 0 | 20 (6) |
| Disease status, n (%) | ||
| AML/ALL | ||
| Early | 116 (71) | |
| Intermediate | 30 (18) | |
| Late | 17 (10) | |
| CML | ||
| Early | 6 (50) | |
| Intermediate | 4 (33) | |
| Late | 2 (17) | |
| MDS/MPS | ||
| Early | 21 (48) | |
| Intermediate | 9 (20) | |
| Late | 14 (32) | |
| MM/PCD | ||
| Early | 24 (14) | 3 (21) |
| Intermediate | 135 (78) | 8 (57) |
| Late | 13 (8) | 3 (21) |
| Lymphoma | ||
| Early | 57 (35) | 3 (5) |
| Intermediate | 69 (42) | 28 (49) |
| Late | 38 (23) | 25 (44) |
| Missing | 0 | 1 (2) |
| CLL/SLL | ||
| Early | 5 (25) | |
| Intermediate | 7 (35) | |
| Late | 8 (40) | |
| Hematopoietic cell transplantation- specific comorbidity index (HCT-CI), n (%) |
||
| 0 | 109 (32) | 108 (35) |
| 1–2 | 107 (32) | 93 (30) |
| 3+ | 115 (34) | 106 (34) |
| Missing | 5 (1) | 3 (<1) |
| Disease risk index, n (%) | ||
| Low | 64 (19) | 54 (17) |
| Intermediate | 224 (67) | 144 (46) |
| High | 22 (7) | 52 (17) |
| Very high | 14 (4) | 11 (4) |
| Missing | 12 (4) | 49 (16) |
| EBMT score, n (%) | ||
| 1 | 6 (2) | 58 (19) |
| 3 | 72 (21) | 73 (24) |
| 4 | 220 (65) | 137 (44) |
| ≥5 | 38 (11) | 42 (14) |
| Prior transplant, n (%) | ||
| No | 318 (95) | 267 (86) |
| Yes | 18 (5) | 43 (14) |
| Prior cytotoxic chemotherapy, n (%) | ||
| No | 32 (10) | 43 (14) |
| Yes | 281 (84) | 250 (81) |
| Unknown | 23 (7) | 17 (5) |
| Patient CMV status, n (%) | ||
| Positive | 196 (58) | 165 (53) |
| Negative | 139 (41) | 145 (47) |
| Missing | 1 (<1) | 0 |
| In allogeneic, conditioning intensity, n (%) |
||
| MA | 135 (44) | |
| RIC/NMA | 175 (56) | |
| Graft type, n (%) | ||
| BM | 0 | 39 (13) |
| PB | 336 | 246 (79) |
| Double CB | 0 | 25 (8) |
| Disease/Disease risk index | ||
| AML/ALL | ||
| Low | 20 (12) | |
| Intermediate | 68 (42) | |
| High | 31 (19) | |
| TBD | 44 (27) | |
| CML | ||
| Low | 8 (67) | |
| Intermediate | 2 (17) | |
| TBD | 2 (17) | |
| MDS/MPS | ||
| Low | 5 (11) | |
| Intermediate | 30 (68) | |
| High | 9 (20) | |
| MM/PCD | ||
| Intermediate | 158 (92) | 11 (79) |
| High | 14 (8) | 3 (21) |
| Lymphoma | ||
| Low | 64 (39) | 12 (21) |
| Intermediate | 66 (40) | 23 (40) |
| High | 8 (5) | 9 (16) |
| Very high | 14 (9) | 10 (18) |
| TBD | 12 (7) | 3 (5) |
| CLL/SLL | ||
| Low | 9 (45) | |
| Intermediate | 10 (50) | |
| Very high | 1 (5) |
Abbreviations for Tables 1 and 2: BMI = Body Mass Index; PSQI = Pittsburgh Sleep Quality Index; CTXD = Cancer and Treatment Distress scale; LSI = Leisure Score Index; SRC = Stress Reduction Checklist; AML = Acute Myeloid Leukemia; ALL = Acute Lymphoblastic Leukemia; CML = Chronic Myeloid Leukemia; MDS = Myelodysplastic Syndrome; MPS = Myeloproliferative Syndrome; MM = Multiple Myeloma; PCD = Plasma Cell Dyscrasia; CLL = Chronic Lymphocytic Leukemia; SLL = Small Lymphocytic Lymphoma; EBMT = European Group for Blood and Marrow Transplantation; CMV = Cytomegalovirus; MA = myeloablative; RIC = Reduced Intensity Conditioning; NMA = Non-myeloablative; BM = Bone Marrow; PB = Peripheral Blood; CB = Cord Blood; IQR = Interquartile Range
Table 3.
Allogeneic transplant-specific variables
| Variable | N (%) |
|---|---|
| Number of enrolled patients | 310 |
| Number of centers | 19 |
| Donor type, n (%) | |
| HLA identical sibling | 106 (34) |
| Other Related | 20 (6) |
| Unrelated | 159 (51) |
| CB | 25 (8) |
| Donor match, n (%) | |
| HLA identical sibling | 27 (79) |
| Other Related | |
| Partially matched | 1 (3) |
| Mismatched | 6 (18) |
| Unrelated | |
| Well matched | 16 (43) |
| Partially matched | 21 (57) |
| Donor sex, n (%) | |
| Male | 184 (59) |
| Female | 126 (41) |
| Recipient/Donor CMV, n (%) | |
| +/+ | 75 (24) |
| +/− | 87 (28) |
| −/+ | 29 (9) |
| −/− | 106 (34) |
| Missing | 13 (4) |
| GVHD prophylaxis, n (%) | |
| CD34 selection+/− post-tx immune | 10 (3) |
| Cyclophosphamide | 2 (<1) |
| FK+MMF+others, FK+/−others | 42 (14) |
| FK+MTX | 42 (14) |
| CSA+MMF+others,CSA+/−others | 54 (17) |
| Other GVHD prophylaxisa | 4 (1) |
| Missing due to no CRF forms | 156 (50) |
Other GVHD prophylaxis: mtx + other, not specified (n=3), other, not specified (n=1)
Pre-transplant PROs and SES
Associations between pre-transplant SES and PRO variables are presented in Table 4. Each SES variable was found to be associated with at least one PRO at a significance level of 0.05. The correlation between each pair of SES and PRO variables was fairly weak (Spearman correlations < 0.4). Therefore, collinearity between predictors had no appreciable impact on the results. Among the entire cohort, lower education was associated with increased distress (CTXD, p<0.01). Clinical interpretation of these findings, for example, indicate that patients with high school education or less had CTXD scores 0.18 points higher on average (almost half a standard deviation) than those with post-high school education, all other covariates being equal. Lower pre-transplant household income was significantly related to worse physical functioning (PCS, p<0.01) and increased distress (CTXD, p<0.01). Lack of employment at the time of transplant was significantly associated with worse physical functioning (PCS, p<0.01). Not being married was associated with worse sleep (PSQI, p<0.01).
Table 4.
Associations between baseline socioeconomic status and patient-reported outcomes.
| N | PCS | MCS | PSQI | CTXD | |||||
|---|---|---|---|---|---|---|---|---|---|
| Estimate (95% CI) | p-value+ | Estimate (95% CI) | p-value+ | Estimate (95% CI) | p-value+ | Estimate (95% CI) | p-value+ | ||
| Marital status: |
|||||||||
| Yes | 485 | - | - | - | - | - | - | - | - |
| No | 155 | 0.22 (−1.75, 2.20) | 0.82 | −0.68 (−2.69, 1.32) | 0.51 | 1.03 (0.34, 1.71) | 0.003* | 0.00 (−0.12, 0.11) | 0.98 |
| Education level: |
|||||||||
| >HS | 515 | - | - | - | - | - | - | - | - |
| ≤HS | 128 | 0.71 (−1.32, 2.73) | 0.49 | −1.93 (−3.97, 0.10) | 0.06 | 0.66 (−0.04, 1.36) | 0.06 | 0.18 (0.07, 0.30) | 0.002* |
| Employment status: |
|||||||||
| Yes | 302 | - | - | - | - | - | - | - | - |
| No | 344 | −2.17(−3.81, −0.53) | <0.01* | −1.38 (−3.08, 0.32) | 0.11 | 0.54 (−0.05,1.12) | 0.07 | 0.05 (−0.05, 0.15) | 0.33 |
| Income: | 0.005* | 0.10 | 0.66 | 0.008* | |||||
| >$75,000 | 267 | - | - | - | - | - | - | - | - |
| $25K–$75K | 258 | −2.70 (−4.45, −0.95) | 0.003* | −1.32 (−3.08, 0.45) | 0.14 | 0.28 (−0.32, 0.87) | 0.37 | 0.16 (0.06, 0.26) | 0.002* |
| ≤$25,000 | 81 | −3.29 (−6.05, −0.53) | 0.02 | −2.99 (−5.86, −0.12) | 0.04 | 0.24 (−0.74, 1.22) | 0.62 | 0.16 (−0.01, 0.32) | 0.06 |
PCS = Physical Component Summary; MCS = Mental Component Summary; PSQI = Pittsburgh Sleep Quality Index; CTXD = Cancer and Treatment Distress scale; HS = high school
denotes overall p-value from a 2 degree of freedom test;
denotes significance at <.01 level
Predictors of Immune Recovery, Overall Survival and Other Clinical Endpoints
None of the pre-transplant SES or PRO variables assessed in this study were significantly associated with the primary (neutrophil or platelet engraftment; see Table 5) or secondary (aGVHD, days of life out of the hospital by day 100, or OS (data not shown)) endpoints among either autologous or allogeneic HCT recipients at the p<0.01 significance level. Neutrophil engraftment at day 14 and platelet engraftment at day 28 was 89.0% and 79.8% for autologous recipients and 53.9% and 78.0% for allogeneic recipients, respectively. Effects of physical and mental functioning on OS have been previously reported [29]. Assignment to exercise or stress intervention was not predictive of any clinical outcomes assessed.
Table 5.
Impact of baseline patient-reported outcomes and socioeconomic variables on primary outcomes of time to neutrophil and platelet engraftment by transplant type.
| Neutrophil Engraftment | Platelet Engraftment | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Autologous | Allogeneic | Autologous | Allogeneic | |||||||||
| N | HR (95% CI) |
p-value | N | HR (95% CI) |
p-value | N | HR (95% CI) |
p-value | N | HR (95% CI) |
p-value | |
| PCS | - | 1.001 (0.98,1.02) |
0.91 | - | 1.00 (0.98,1.01) |
0.61 | - | 1.00 (0.99,1.02) |
0.57 | - | 1.02 (1.00,1.03) |
0.03 |
| MCS | - | 0.98 (0.97,1.00) |
0.02 | - | 1.00 (0.99,1.02) |
0.68 | - | 0.99 (0.98,1.01) |
0.28 | - | 1.01 (0.99,1.02) |
0.27 |
| PSQI | ||||||||||||
| ≤5 | 223 | 1.00 | - | 205 | 1.00 | - | 223 | 1.00 | - | 205 | 1.00 | - |
| >5 | 113 | 0.86 (0.66,1.13) |
0.28 | 105 | 0.92 (0.69,1.21) |
0.53 | 113 | 1.11 (0.86,1.45) |
.41 | 105 | 0.83 (0.61,1.12) |
0.22 |
| CTXD | ||||||||||||
| ≤1.1 | 186 | 1.00 | - | 158 | 1.00 | - | 186 | 1.00 | - | 158 | 1.00 | - |
| >1.1 | 150 | 1.02 (0.75,1.37) |
0.91 | 152 | 1.17 (0.86,1.59) |
0.33 | 150 | 0.97 (0.73,1.30) |
0.85 | 152 | 1.21 (0.86,1.69) |
0.27 |
| Marital status: | ||||||||||||
| Yes | 243 | 1.00 | - | 242 | 1.00 | - | 243 | 1.00 | - | 242 | 1.00 | 0.03 |
| No | 89 | 1.17 (0.90,1.53) |
0.25 | 66 | 1.11 (0.77,1.59) |
0.47 | 89 | 0.98 (0.74,1.29) |
0.87 | 66 | 1.51 (1.03,2.20) |
|
| Education level: |
||||||||||||
| >HS | 266 | 1.00 | - | 249 | 1.00 | - | 266 | 1.00 | - | 249 | 1.00 | - |
| ≤HS | 68 | 0.88 (0.66,1.17) |
0.38 | 60 | 0.85 (0.61,1.17) |
0.32 | 68 | 0.83 (0.61,1.13) |
0.23 | 60 | 1.18 (0.83,1.67) |
0.37 |
| Employment status: |
||||||||||||
| Yes | 152 | 1.00 | - | 150 | 1.00 | - | 152 | 1.00 | - | 150 | 1.00 | - |
| No | 184 | 0.92 (0.72,1.17) |
0.50 | 160 | 0.96 (0.75,1.22) |
0.73 | 184 | 1.02 (0.79,1.31) |
0.88 | 160 | 0.80 (0.59,1.05) |
0.11 |
| Income: | 0.50 | 0.63 | 0.66 | 0.24 | ||||||||
| >$75,000 | 135 | 1.00 | - | 132 | 1.00 | - | 135 | 1.00 | - | 132 | 1.00 | - |
| $25K–$75K | 142 | 1.16 (0.90,1.49) |
0.15 | 116 | 1.08 (0.82,1.42) |
0.58 | 142 | 1.10 (0.85,1.43) |
0.48 | 116 | 0.84 (0.61,1.14) |
0.26 |
| ≤$25,000 | 39 | 1.14 (0.77,1.68) |
0.28 | 42 | 1.24 (0.79,1.94) |
0.35 | 39 | 1.20 (0.78,1.84) |
0.41 | 42 | 0.65 (0.39,1.09) |
0.10 |
PCS = Physical Component Summary; MCS = Mental Component Summary; PSQI = Pittsburgh Sleep Quality Index; CTXD = Cancer and Treatment Distress scale; HR = hazard ratio; HS = high school
Discussion
These data demonstrate that low SES is associated with worse pre-transplant physical functioning as well as increased distress and poor sleep quality. Neither SES nor the pre-transplant PROs physical and mental functioning, distress, and sleep quality were associated with the primary outcome of hematopoietic recovery after HCT. This is the largest HCT cohort to date evaluating SES and PROs as predictors of hematopoietic recovery. These factors were also not significantly associated with the secondary clinical outcomes assessed, including aGVHD and days of life out of the hospital by day 100; distress and sleep quality were not associated with OS.
In other studies, social disparities were found to contribute additional independent risk for people with cancer [4,7,8,32–35], with patients of lower SES at risk of increased morbidity and mortality [36–42]. In the HCT setting, low SES, independent of race, has a negative impact on unrelated and related donor outcomes, including worse OS and higher transplant-related mortality (TRM) [14,43]. The current findings support the recent CDC survey data that serious psychological distress is a significant health issue, particularly among individuals of low SES [44]. They also corroborate previous research demonstrating that low SES among allogeneic HCT recipients is associated with increased expression of the “conserved transcriptional response to adversity” (CTRA), a profile of 53 genes that are up-regulated under conditions of chronic stress and associated with worse clinical outcomes [22].
The present null findings are somewhat unexpected given prior evidence from other HCT populations suggesting an association between pre-transplant SES and PRO variables and clinical outcomes [4,5,9,11,12,22,29,35,45]. Recently, Wood et al. [29] identified that the pre-transplant PCS scale independently predicted overall mortality in the same cohort of autologous and allogeneic HCT recipients used in the present study. It may be that physical status, and not perceived distress or mental health-related QOL, as evaluated here, is a more sensitive PRO for predicting clinical outcomes. In the current study, PCS was associated with lack of employment at time of transplant. While multivariate modeling indicated that the covariates KPS (p<0.001) and HCT-CI (p<0.01), but not DRI, were significant when SES factors were assessed in relation to PCS (complete data not shown), it is possible this relationship is reflective of longer disease duration prior to transplant, though this was not directly assessed.
The current findings support an association between unmarried status and poorer sleep quality, underscoring the importance of assessing close relationships when evaluating sleep and health [46]. Prior research indicates that married older adults have better actigraph-estimated sleep [47] and married women with metastatic breast cancer have better sleep quality [48]. It may be that HCT recipients who are unmarried are more likely to be sleeping alone; accommodating a caretaker in patients’ homes post-transplant could prove to be disruptive to sleep hygiene. This relationship should be further explored among HCT recipients in future studies.
We performed additional post hoc analyses evaluating the relationship between pre-transplant factors and outcomes in only the groups with PRO scores >1 SD from the mean, since these were the patients reporting the greatest psychosocial and functional distress (data not shown); no significant relationship was identified. It is possible that the significant physical and immunological perturbation inherent in the HCT process and the underlying heterogeneity of the study population obfuscate any potential relationship between emotional status and immunologic determinants that could impact outcomes. In particular, the powerful immunosuppressive agents used to prevent and treat GVHD in allogeneic recipients may overshadow any influence of SES and PRO factors on immune function, although there is prior evidence to suggest otherwise [4,45]. Given the observation of this relationship in smaller cohorts, it seems less plausible that true associations would not be evident in our significantly larger cohort, unless there was not sufficient adjustment for other transplant-, disease-, and patient-related factors in prior studies. Incorporating infused number of CD34+ cells could help confirm the presence of these true associations by assessing whether engraftment in the present cohort was what would be expected; however, rates of missing data on cell dose were too high to evaluate this conclusively. Investigational analyses (not reported) suggest that this relationship was as would be expected in the present cohort and that cell dose did not affect the relationships between PROs or SES and outcomes. This should be further evaluated in future studies. While time to hematopoietic recovery was assessed as a continuous variable in both the current and prior studies, analytic strategies employed varied, which can result in different outcomes.
Alternatively, it is possible that the selection bias with this particular cohort who agreed to participate in an effort-based intervention resulted in an inherently less vulnerable group with better PRO measures and SES than previous smaller cohorts. Indeed, the mean mental functioning score in the current sample is representative of a general normative adult population. This is in contrast to other literature indicating high levels of distress in HCT patients both prior to and following HCT [24,49,50]. Further, distress levels are lower in the present cohort (median CTXD = 1.0; Interquartile range (IQR) = 0.7 – 1.5 in autologous recipients) as compared to both the initial multicenter study establishing CTXD psychometric validity (median CTXD = 1.2; SD = 0.5) [28] and the population evaluated by McGregor et al. demonstrating distress modulating post-transplant white blood cell recovery (median CTXD = 1.2; IQR = 0.8 – 1.6 in autologous recipients) [9]. Finally, SES may not have been associated with OS or other outcomes in this study because the present sample was not necessarily representative of individuals from lower SES categories who may be more vulnerable to adverse clinical outcomes; approximately 80% of the present sample had education beyond high school, which is substantially greater than the 65% national average [51]. Future studies could assess whether this is reflective of clinical trial participation or high SES in general of HCT patients. Although strengths of this study include its large cohort size, enrollment of transplant recipients from over twenty centers, and a range of potential demographic and psychosocial stressors, a limitation is our lack of knowledge of who declined participation or was not approached for study consent. Taken together, a possible limitation is that the present sample may not fully represent the distribution of stressors inherent in the general HCT population.
In conclusion, this study demonstrates limited support for SES and PROs as risk prognosticators for hematopoietic recovery, aGVHD incidence, days of life out of the hospital, or survival. Future research may evaluate more sensitive biological measures - such as gene expression - in addition to clinical outcomes, and may focus on HCT recipient subsets reporting worse PROs at baseline, indicating perhaps greater vulnerability to adverse outcomes.
Highlights.
PRO and SES variables were correlated pre-transplant.
Neither PRO nor SES variables were significantly associated with clinical outcomes.
Future research should focus on HCT patients at greater psychosocial disadvantage.
Acknowledgments
Support for this study was provided by grant U10HL069294 to the Blood and Marrow Transplant Clinical Trials Network from the National Heart, Lung, and Blood Institute and the National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the above mentioned parties. The second author (KLS) was supported by a grant from the National Cancer Institute (CA160684). The CIBMTR is supported by Public Health Service Grant/Cooperative Agreement 5U24-CA076518 from the National Cancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI) and the National Institute of Allergy and Infectious Diseases (NIAID); a Grant/Cooperative Agreement 5U10HL069294 from NHLBI and NCI; a contract HHSH250201200016C with Health Resources and Services Administration (HRSA/DHHS); two Grants N00014-15-1-0848 and N00014-16-1-2020 from the Office of Naval Research; and grants from Alexion; *Amgen, Inc.; Anonymous donation to the Medical College of Wisconsin; Astellas Pharma US; AstraZeneca; Be the Match Foundation; *Bluebird Bio, Inc.; *Bristol Myers Squibb Oncology; *Celgene Corporation; Cellular Dynamics International, Inc.; *Chimerix, Inc.; Fred Hutchinson Cancer Research Center; Gamida Cell Ltd.; Genentech, Inc.; Genzyme Corporation; *Gilead Sciences, Inc.; Health Research, Inc. Roswell Park Cancer Institute; HistoGenetics, Inc.; Incyte Corporation; Janssen Scientific Affairs, LLC; *Jazz Pharmaceuticals, Inc.; Jeff Gordon Children’s Foundation; The Leukemia & Lymphoma Society; Medac, GmbH; MedImmune; The Medical College of Wisconsin; *Merck & Co, Inc.; Mesoblast; MesoScale Diagnostics, Inc.; *Miltenyi Biotec, Inc.; National Marrow Donor Program; Neovii Biotech NA, Inc.; Novartis Pharmaceuticals Corporation; Onyx Pharmaceuticals; Optum Healthcare Solutions, Inc.; Otsuka America Pharmaceutical, Inc.; Otsuka Pharmaceutical Co, Ltd. – Japan; PCORI; Perkin Elmer, Inc.; Pfizer, Inc; *Sanofi US; *Seattle Genetics; *Spectrum Pharmaceuticals, Inc.; St. Baldrick’s Foundation; *Sunesis Pharmaceuticals, Inc.; Swedish Orphan Biovitrum, Inc.; Takeda Oncology; Telomere Diagnostics, Inc.; University of Minnesota; and *Wellpoint, Inc. This publication was also supported in part by the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant Numbers UL1TR001436 and KL2TR001438. The views expressed in this article do not reflect the official policy or position of the National Institute of Health, the Department of the Navy, the Department of Defense, Health Resources and Services Administration (HRSA) or any other agency of the U.S. Government.
*Corporate Members
Footnotes
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Financial disclosure: Conflict of interest statement: There are no conflicts of interest to report.
This work was presented, in part, at the World Congress of Psycho-Oncology, 2015, and the Psychoneuroimmunology Research Society Meeting, 2016.
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