• Risky health behaviors were associated with increased hazard of all-cause and nonrelapse–related late mortality after BMT.

We examined the association between risky health behaviors (smoking, heavy alcohol consumption, and lack of vigorous physical activity) and all-cause and cause-specific late mortality after blood or marrow transplantation (BMT) to understand the role played by potentially modifiable risk factors. Study participants were drawn from the BMT Survivor Study (BMTSS) and included patients who received transplantation between 1974 and 2014, had survived ≥2 years after BMT, and were aged ≥18 years at study entry. Survivors provided information on sociodemographic characteristics, chronic health conditions, and health behaviors. National Death Index was used to determine survival and cause of death. Multivariable regression analyses determined the association between risky health behaviors and all-cause mortality (Cox regression) and nonrecurrence-related mortality (NRM; subdistribution hazard regression), after adjusting for relevant sociodemographic, clinical variables and therapeutic exposures. Overall, 3866 participants completed the BMTSS survey and were followed for a median of 5 years to death or 31 December 2021; and 856 participants (22.1%) died after survey completion. Risky health behaviors were associated with increased hazard of all-cause mortality (adjusted hazard ratio [aHR] former smoker, 1.2; aHR current smoker, 1.7; reference, nonsmoker; aHR heavy drinker, 1.4; reference, nonheavy drinker; and aHR no vigorous activity, 1.2; reference, vigorous activity) and NRM (aHR former smoker, 1.3; aHR current smoker, 1.6; reference, nonsmoker; aHR heavy drinker, 1.4; reference: nonheavy drinker; and aHR no vigorous activity, 1.2; reference, vigorous activity). The association between potentially modifiable risky health behaviors and late mortality offers opportunities for development of interventions to improve both the quality and quantity of life after BMT.

Blood or marrow transplantation (BMT) is an established therapeutic option for patients with hematologic malignancies and other life-threatening illnesses. Over 20 000 individuals in the United States receive BMT every year.1,2 Although improvement in transplantation strategies and supportive care have resulted in a decline in early mortality, BMT recipients carry a significant burden of late-occurring morbidity that is directly related to therapeutic exposures and places the survivors at high risk for late mortality when compared with the general population.3-14 Previous studies suggest that the risk of mortality remains elevated for at least 30 years after BMT.15-21 A recent report from the BMT Survivor Study (BMTSS) showed that the excess mortality translates into 8.7 years of life lost per person, conditional on surviving the first 2 years after allogeneic BMT.22 Previous studies have identified nonmodifiable factors associated with late mortality (eg, refractory disease and therapeutic exposures for control of primary disease).21,22 The association between modifiable factors such as risky health behaviors (smoking, alcohol consumption, and lack of physical activity) and cancer mortality has been documented in epidemiological studies in nontransplant populations.23-28 However, the association between risky health behaviors and late mortality (all-cause and cause-specific) among BMT survivors, and the interaction between these health behaviors and therapeutic exposures remains unknown. We addressed this knowledge gap by using the resources offered by BMTSS.

Study participants and data collection

BMTSS is a cohort study, which examines the long-term outcomes of individuals who survived ≥2 years after BMT performed between 1974 and 2014 at the University of Alabama at Birmingham, City of Hope, or University of Minnesota. Study participation consisted of completion of the BMTSS survey by transplant recipients to capture the following: sociodemographics (race/ethnicity, education, annual household income, and health insurance), chronic health conditions as diagnosed by health care providers, chronic graft-versus-host disease (cGvHD), height and weight at the time of study participation that allowed us to calculate body mass index, health behaviors (smoking, alcohol consumption, and physical activity), and mental health (using Brief Symptom Inventory-18). Chronic health conditions were graded using the Common Terminology Criteria for Adverse Events, v5.0.29 Brief Symptom Inventory-18 includes 3 symptom subscales: somatization, depression, and anxiety, with each subscale comprising 6 items; raw scores are converted to T-scores based on gender-specific normative data from community-dwelling US adults.30 Mental health was classified as impaired if the T-score values were ≥63 on any 2 of the 3 subscales.31 Survivors’ age at BMT, sex, primary diagnosis (indication for BMT), type of transplant (autologous or allogeneic), risk of relapse at BMT (standard risk or high risk), conditioning regimen, and conditioning intensity (myeloablative conditioning or nonmyeloablative/reduced intensity conditioning) were retrieved from institutional transplant databases and/or participants’ medical records. National Death Index Plus provided data regarding the date and cause of death till 31 December 2020.32 Additional data from Accurint databases extended vital status information till 31 December 2021. The institutional review board (IRB) at the University of Alabama at Birmingham served as the single IRB of record and approved the study. Participants provided informed consent according to the Declaration of Helsinki. A waiver of consent was granted by the IRB for linking the cohort to National Death Index and Accurint databases. This report includes survivors who were aged ≥18 years at study participation.

Outcome

The primary outcome of interest was death after the completion of the BMTSS survey. Suicides, homicides, and accidents were classified as external causes of death. A cause of death matching the pretransplant diagnosis was classified as recurrence-related mortality (RRM). All other causes of death were classified as nonrecurrence-related mortality (NRM: deaths due to malignant diseases differing from the pretransplant diagnosis [subsequent malignant neoplasms or SMNs], cardiovascular disease, late infections, renal disease, etc).

Exposures

Primary exposures of interest included smoking, alcohol consumption, and lack of vigorous physical activity, examined individually, as well as an ordinal variable: absence of any risky behavior or presence of a single behavior, 2 behaviors, or 3 behaviors.

Smoking

Questions in the BMTSS survey and responses used to classify participants into never smokers, former smokers, and current smokers are detailed in supplemental Table 1.

Alcohol consumption

Questions in the BMTSS survey and responses used to classify participants into never drinkers and drinkers are in supplemental Table 1. Drinkers were further categorized as heavy drinkers and nonheavy drinkers (supplemental Table 1).

Vigorous physical activity

Vigorous physical activity was estimated as the self-reported number of exercise sessions per week (frequency) multiplied by session duration (in minutes), weighted by the standardized classification of energy expenditure for vigorous exercise (ie, metabolic equivalent tasks [METs]) expressed as average MET hour/week-1.33 Levels of vigorous physical activity were defined as 0 MET hour/week-1 (<20 minutes of vigorous exercise/week–1), 3 to <9 MET hour/week-1 (20 minutes to <60 minutes of vigorous exercise/week), and ≥9 MET hour/week–1 (≥60 minutes of vigorous exercise/week) (supplemental Table 1).

Statistical analysis

Descriptive statistics were reported using mean (standard deviation), median (range), or counts (percentages) as appropriate. Kaplan-Meier analyses were used to calculate overall survival. Cox proportional hazards regression analysis with time from completing the survey to death or end of study (December 21) as the time axis was used for identifying the association between each risky health behavior (and clusters of risky health behaviors) and all-cause mortality. Cox proportional hazards regression model assumption was examined using Schoenfeld residuals. The following variables were examined for their possible inclusion in the model: age at BMT, sex, race/ethnicity, education, annual household income, health insurance, body mass index, primary diagnosis, disease status at BMT, BMT type (autologous, allogeneic), cGvHD, stem cell source (bone marrow, peripheral blood stem cells, or cord blood), conditioning intensity (myeloablative conditioning or nonmyeloablative/reduced intensity conditioning), conditioning regimen, chronic health conditions, mental health, cancer-related pain and anxiety, time from BMT to survey completion, and BMT era (1974-1989, 1990-2004, and 2005-2014).1 Potential confounders were selected to be included in the multivariable model on the basis of their significant association with late mortality. Race/ethnicity and stem cell source were included in the multivariable analysis because of previous evidence for the association between racial/ethnic and source of stem cell disparities and survival.22,34 

Proportional subdistribution hazard (Fine-Gray) models35 were used to examine the association between each risky health behavior (and clusters of risky health behaviors) and NRM; RRM and external causes of death served as competing risk. Survivors with missing or unknown cause of death were excluded from the proportional subdistribution hazard model. We also stratified the analysis by age at study participation (≤56 years; >56 years), years since BMT to study participation (≤10 years; >10 years), age at BMT (<21 years; ≥21 years), and BMT type (autologous; allogeneic). We examined statistical interaction between sex and risky health behaviors and between total body irradiation (TBI) and risky health behaviors to assess whether the effect of risky health behaviors was modified by sex or exposure to TBI.

We used 2003 age-sex–specific US life-table data from the Centers for Disease Control and Prevention36 to calculate expected population mortality rates (the median year of BMT for the cohort in this study was 2003).

We used the standardized mortality ratio, which is the ratio of observed to expected number of deaths, and compared the mortality experienced by this cohort with the age-, sex-, and calendar-specific mortality of the US population.36 The Poisson regression method was used to calculate 95% confidence intervals (CIs) of the standardized mortality ratio. We evaluated excess mortality, which was calculated as the difference between the observed number of deaths among BMT survivors who practiced risky health behaviors and the average excepted number of deaths in the US population.

All analyses were performed using SAS v9.4 (SAS Institute, Cary, NC). Findings noted with 2-sided tests were considered statistically significant at P < .05.

Supplemental Figure 1 shows the CONSORT diagram for the study participants. Of 4253 participants approached for study participation, 3866 completed the full version of the BMTSS survey at a median of 9 years (range, 2-41) from BMT. The median length of follow-up from BMTSS survey completion to death or end of follow-up (December 2021) was 5 years (range, 0-22). Of the 3866 study participants, 856 died (22.1%) after survey completion. Table 1 summarizes the clinical and demographic characteristics of the study population. The median age at BMT was 45 years (range, 0-74) and at survey completion was 56 years (range, 18-84). In this cohort, 1944 participants were autologous BMT recipients (50.3%), 1736 were female (44.9%), and 2858 were non-Hispanic White (73.9%). Primary indications for BMT included Hodgkin or non-Hodgkin lymphoma (32.4%), acute lymphoblastic leukemia/ acute myeloid leukemia/ myelodysplastic syndrome ( 31.6%), plasma cell dyscrasias (17.8%), chronic myeloid leukemia (10.2%), and other diagnoses (8.0%). Peripheral blood stem cells were used as the source of stem cells for 2566 participants (66.4%) and myeloablative conditioning regimens were used in 2673 patients (69.1%). Of the 1922 allogeneic BMT recipients, 1040 carried a history of cGvHD (54.1%). Fifty-eight percent of the survivors reported grade 3 or 4 chronic health conditions (n = 2254); 5% reported impaired mental health, and 4.7% reported cancer-related anxiety.

Table 1.

Clinical and demographic characteristics of study participants by vital status

Variables of interestVital statusP value
Alive
N = 3010 (77.9%)
Deceased
N = 856 (22.1%)
Age at completing the survey in y 
Median (range) 56 (18-83) 60 (18-84) <.0001 
Age at completing the survey, n (%) 
≤56y 1492 (49.6) 328 (38.3) <.0001 
>56y 1518 (50.4) 528 (61.7)  
Follow-up from completing the survey to death or end offollow-upin y 
Median (range) 6 (1-22) 4 (0-22) <.0001 
BMT era, n (%) 
1974-1989 210 (7.0) 108 (12.6) <.0001 
1990-2004 1249 (41.5) 418 (48.8)  
2005-2014 1551 (51.5) 330 (38.5)  
Sex, n (%) 
Female 1428 (47.4) 308 (36.0) <.0001 
Male 1582 (52.6) 548 (64.0)  
Race/ethnicity, n (%) 
African American 154 (5.1) 30 (3.5) .1131 
Non-Hispanic White 2204 (73.2) 654 (76.4)  
Hispanic 398 (13.2) 112 (13.1)  
Asian 168 (5.6) 34 (4.0)  
Other  83 (2.8) 26 (3.0)  
Missing 3 (0.1) 0 (0.0)  
Health insurance, n (%) 
Not insured 98 (3.3) 34 (4.0) .2700 
Insured 2887 (95.9) 801 (93.6)  
Missing 25 (0.8) 21 (2.4)  
Annual household income, n (%) 
<$19 999 848 (28.2) 250 (29.2) <.0001 
$20 000-$49 999 510 (16.9) 219 (25.6)  
>$50 000 1366 (45.4) 313 (36.6)  
Missing 286 (9.5) 74 (8.6)  
Educational status, n (%) 
High school or less 535 (17.8) 179 (20.9) .0411 
Post high school education 2436 (80.9) 669 (78.2)  
Missing 39 (1.3) 8 (0.9)  
Age at BMT in y 
Median (IQR) 43 (0-74) 50 (1-72) <.0001 
Follow-up from BMT to completing the survey in y 
Median (range) 9 (2-41) 7 (2-37) <.0001 
BMI, n (%) 
Underweight (<18.5 kg/m297 (3.2) 32 (3.7) .3824 
Normal weight (18.5-<25 kg/m2979 (32.5) 260 (30.4)  
Overweight (25-<30 kg/m2897 (29.8) 243 (28.4)  
Obese (≥30 kg/m2592 (19.7) 138 (16.1)  
Unknown 445 (14.8) 183 (21.4)  
Primary diagnosis, n (%) 
AML/MDS/ALL 986 (32.8) 237 (27.7) <.0001 
CML 282 (9.4) 112 (13.1)  
HL/NHL 978 (32.5) 273 (31.9)  
PCD 475 (15.8) 213 (24.9)  
Other  289 (9.6) 21 (2.4)  
Disease status at first BMT, n (%) 
High risk 1246 (41.4) 483 (56.4) <.0001 
Standard risk 1371 (45.5) 331 (38.7)  
Missing 393 (13.1) 42 (4.9)  
BMT type/cGvHD, n (%) 
Autologous 1443 (47.9) 501 (58.5) <.0001 
Allogeneic with cGvHD 794 (26.4) 246 (28.7)  
Allogeneic without cGvHD 718 (23.8) 104 (12.2)  
Allogeneic missing cGvHD 55 (1.8) 5 (0.6)  
Stem cell source, n (%) 
Bone marrow/cord blood 1034 (34.3) 265 (31.0) .0627 
Peripheral stem cells 1975 (65.6) 591 (69.0)  
Missing 1 (0.03) 0 (0.0)  
Conditioning intensity, n (%) 
MAC 2062 (68.5) 611 (71.4) <.0001 
RIC/NMA 647 (21.5) 114 (13.3)  
Missing 301 (10.0) 313 (15.3)  
Conditioning agents, n (%) 
TBI 1324 (44.0) 424 (49.5) .0040 
Cyclophosphamide 1601 (53.2) 416 (48.6) .0177 
Nitrosoureas 414 (13.8) 87 (10.2) .0058 
Etoposide 1056 (35.1) 279 (32.6) .1765 
Busulfan 363 (12.1) 48 (5.6) <.0001 
Cytarabine 199 (6.6) 54 (6.3) .7519 
Melphalan 782 (26.0) 226 (26.4) .8041 
Fludarabine 519 (17.2) 80 (9.4) <.0001 
Chronic health conditions, n (%) 
Grade 3 or 4 1694 (56.3) 560 (65.4) <.0001 
Mental health , n (%) 
Not impaired 2892 (96.1) 779 (91.0) <.0001 
Impaired 118 (3.9) 77 (9.0)  
Some pain from cancer, n (%) 
No 921 (30.6) 264 (30.8) .7931 
Yes 2065 (68.6) 579 (67.6)  
Missing 24 (0.8) 13 (1.5)  
Anxiety from cancer treatments, n (%) 
Absent 2821 (93.7) 784 (91.6) .7439 
Present 139 (4.6) 41 (4.8)  
Missing 50 (1.7) 31 (3.6)  
Ever smoke, n (%) 
No 1992 (66.2) 438 (51.2) <.0001 
Yes 1005 (33.4) 410 (47.9)  
Missing 13 (0.4) 8 (0.9)  
Smoking status, n (%) 
Never smoker 1992 (66.2) 438 (51.2) <.0001 
Former smoker 863 (28.7) 352 (41.1)  
Current smoker 142 (4.7) 58 (6.8)  
Missing 13 (0.4) 8 (0.9)  
Ever drink alcohol, n (%) 
No 1395 (46.3) 268 (31.3) <.0001 
Yes 1577 (52.4) 562 (65.7)  
Missing 38 (1.3) 26 (3.0)  
Heavy drinker, n (%) 
No 1464 (90.7) 485 (82.5) <.0001 
Yes 113 (7.0) 77 (13.1)  
Missing 38 (2.3) 26 (4.4)  
Vigorous physically active, n (%) 
No 1572 (52.2) 403 (47.1) .029 
Yes 1421 (47.2) 448 (52.3)  
Missing 17 (0.6) 5 (0.6)  
Levels of vigorous exercise (total metabolic equivalent h/wk-1) 
0 MET h/wk-1 1748 (58.1) 578 (67.5) <.0001 
3 to <9 MET h/wk-1 964 (32.0) 120 (14.0)  
≥9 MET h/wk-1 281 (9.3) 153 (17.9)  
Missing 17 (0.6) 5 (0.6)  
Variables of interestVital statusP value
Alive
N = 3010 (77.9%)
Deceased
N = 856 (22.1%)
Age at completing the survey in y 
Median (range) 56 (18-83) 60 (18-84) <.0001 
Age at completing the survey, n (%) 
≤56y 1492 (49.6) 328 (38.3) <.0001 
>56y 1518 (50.4) 528 (61.7)  
Follow-up from completing the survey to death or end offollow-upin y 
Median (range) 6 (1-22) 4 (0-22) <.0001 
BMT era, n (%) 
1974-1989 210 (7.0) 108 (12.6) <.0001 
1990-2004 1249 (41.5) 418 (48.8)  
2005-2014 1551 (51.5) 330 (38.5)  
Sex, n (%) 
Female 1428 (47.4) 308 (36.0) <.0001 
Male 1582 (52.6) 548 (64.0)  
Race/ethnicity, n (%) 
African American 154 (5.1) 30 (3.5) .1131 
Non-Hispanic White 2204 (73.2) 654 (76.4)  
Hispanic 398 (13.2) 112 (13.1)  
Asian 168 (5.6) 34 (4.0)  
Other  83 (2.8) 26 (3.0)  
Missing 3 (0.1) 0 (0.0)  
Health insurance, n (%) 
Not insured 98 (3.3) 34 (4.0) .2700 
Insured 2887 (95.9) 801 (93.6)  
Missing 25 (0.8) 21 (2.4)  
Annual household income, n (%) 
<$19 999 848 (28.2) 250 (29.2) <.0001 
$20 000-$49 999 510 (16.9) 219 (25.6)  
>$50 000 1366 (45.4) 313 (36.6)  
Missing 286 (9.5) 74 (8.6)  
Educational status, n (%) 
High school or less 535 (17.8) 179 (20.9) .0411 
Post high school education 2436 (80.9) 669 (78.2)  
Missing 39 (1.3) 8 (0.9)  
Age at BMT in y 
Median (IQR) 43 (0-74) 50 (1-72) <.0001 
Follow-up from BMT to completing the survey in y 
Median (range) 9 (2-41) 7 (2-37) <.0001 
BMI, n (%) 
Underweight (<18.5 kg/m297 (3.2) 32 (3.7) .3824 
Normal weight (18.5-<25 kg/m2979 (32.5) 260 (30.4)  
Overweight (25-<30 kg/m2897 (29.8) 243 (28.4)  
Obese (≥30 kg/m2592 (19.7) 138 (16.1)  
Unknown 445 (14.8) 183 (21.4)  
Primary diagnosis, n (%) 
AML/MDS/ALL 986 (32.8) 237 (27.7) <.0001 
CML 282 (9.4) 112 (13.1)  
HL/NHL 978 (32.5) 273 (31.9)  
PCD 475 (15.8) 213 (24.9)  
Other  289 (9.6) 21 (2.4)  
Disease status at first BMT, n (%) 
High risk 1246 (41.4) 483 (56.4) <.0001 
Standard risk 1371 (45.5) 331 (38.7)  
Missing 393 (13.1) 42 (4.9)  
BMT type/cGvHD, n (%) 
Autologous 1443 (47.9) 501 (58.5) <.0001 
Allogeneic with cGvHD 794 (26.4) 246 (28.7)  
Allogeneic without cGvHD 718 (23.8) 104 (12.2)  
Allogeneic missing cGvHD 55 (1.8) 5 (0.6)  
Stem cell source, n (%) 
Bone marrow/cord blood 1034 (34.3) 265 (31.0) .0627 
Peripheral stem cells 1975 (65.6) 591 (69.0)  
Missing 1 (0.03) 0 (0.0)  
Conditioning intensity, n (%) 
MAC 2062 (68.5) 611 (71.4) <.0001 
RIC/NMA 647 (21.5) 114 (13.3)  
Missing 301 (10.0) 313 (15.3)  
Conditioning agents, n (%) 
TBI 1324 (44.0) 424 (49.5) .0040 
Cyclophosphamide 1601 (53.2) 416 (48.6) .0177 
Nitrosoureas 414 (13.8) 87 (10.2) .0058 
Etoposide 1056 (35.1) 279 (32.6) .1765 
Busulfan 363 (12.1) 48 (5.6) <.0001 
Cytarabine 199 (6.6) 54 (6.3) .7519 
Melphalan 782 (26.0) 226 (26.4) .8041 
Fludarabine 519 (17.2) 80 (9.4) <.0001 
Chronic health conditions, n (%) 
Grade 3 or 4 1694 (56.3) 560 (65.4) <.0001 
Mental health , n (%) 
Not impaired 2892 (96.1) 779 (91.0) <.0001 
Impaired 118 (3.9) 77 (9.0)  
Some pain from cancer, n (%) 
No 921 (30.6) 264 (30.8) .7931 
Yes 2065 (68.6) 579 (67.6)  
Missing 24 (0.8) 13 (1.5)  
Anxiety from cancer treatments, n (%) 
Absent 2821 (93.7) 784 (91.6) .7439 
Present 139 (4.6) 41 (4.8)  
Missing 50 (1.7) 31 (3.6)  
Ever smoke, n (%) 
No 1992 (66.2) 438 (51.2) <.0001 
Yes 1005 (33.4) 410 (47.9)  
Missing 13 (0.4) 8 (0.9)  
Smoking status, n (%) 
Never smoker 1992 (66.2) 438 (51.2) <.0001 
Former smoker 863 (28.7) 352 (41.1)  
Current smoker 142 (4.7) 58 (6.8)  
Missing 13 (0.4) 8 (0.9)  
Ever drink alcohol, n (%) 
No 1395 (46.3) 268 (31.3) <.0001 
Yes 1577 (52.4) 562 (65.7)  
Missing 38 (1.3) 26 (3.0)  
Heavy drinker, n (%) 
No 1464 (90.7) 485 (82.5) <.0001 
Yes 113 (7.0) 77 (13.1)  
Missing 38 (2.3) 26 (4.4)  
Vigorous physically active, n (%) 
No 1572 (52.2) 403 (47.1) .029 
Yes 1421 (47.2) 448 (52.3)  
Missing 17 (0.6) 5 (0.6)  
Levels of vigorous exercise (total metabolic equivalent h/wk-1) 
0 MET h/wk-1 1748 (58.1) 578 (67.5) <.0001 
3 to <9 MET h/wk-1 964 (32.0) 120 (14.0)  
≥9 MET h/wk-1 281 (9.3) 153 (17.9)  
Missing 17 (0.6) 5 (0.6)  

ALL, acute lymphoblastic leukemia; AML, acute myeloid leukemia; BMI, body mass index; CML, chronic myeloid leukemia; HL, Hodgkin lymphoma; IQR, interquartile range; MAC, myeloablative conditioning; MDS, myelodysplastic syndrome; NMA, nonmyeloablative; NHL, non-Hodgkin lymphoma; PCD, plasma cell dyscrasias; RIC, reduced intensity conditioning.

Bold indicates statistically significant (P < 0.05).

Race other includes multiracial (n = 94), American Indian (n = 13), and Pacific Islander (n = 2).

Primary diagnosis other includes severe aplastic anemia, other leukemia, and other.

Mental health is impaired if T-score ≥63 on any 2 of symptom scales of the 3 Brief Symptom Inventory-18 items subscales (depression, somatization, or anxiety).

Risky health behaviors

Smoking

Overall, 1415 participants (36.8%) were ever smokers; of these, 1215 (85.9%) were former smokers and 200 (14.1%) were current smokers. Supplemental Figure 2 shows the prevalence of tobacco products used by smokers. The median age at smoking initiation was 17 years (interquartile range, 10-57). As shown in Table 2, ever smokers were more likely to be male (59.7% vs 52.3%) and non-Hispanic White (79.8% vs 70.7%). Smokers were more likely to report ever drinking alcohol (70.2% vs 46.8%), but the prevalence of participants engaging in vigorous physical activity was comparable by smoking status (47.9% vs 48.8%).

Table 2.

Clinical and demographic characteristics of study participants by exposure of interest

Variables of interestEver smokeEver drink alcoholVigorous physically active
No
n = 2430 (63.0%)
Yes
n = 1415 (36.8%)
No
n = 1663 (43.7%)
Yes
n = 2139 (56.3%)
No
n = 1975 (51.4%)
Yes
n = 1869 (48.6%)
Age at completing the survey in y 
Median (range) 54 (18-84) 59 (18-83) 57 (18-84) 56 (18-83) 60 (18-84) 52 (18-80) 
P value <.0001 <.0001 <.0001 
BMT era, n (%) 
1974-1989 211 (8.7) 106 (7.4) 103 (6.2) 207 (9.7) 109 (5.5) 208 (11.3) 
1990-2004 1043 (42.9) 614 (43.4) 670 (40.3) 957 (44.7) 730 (37.0) 931 (49.8) 
2005-2014 1176 (48.4) 695 (49.1) 890 (53.5) 975 (45.6) 1136 (57.5) 730 (39.1) 
P value .4311 <.0001 <.0001 
Sex, n (%) 
Female 1159 (47.7) 570 (40.3) 899 (54.1) 813 (38.0) 999 (50.6) 726 (38.8) 
Male 1271 (52.3) 845 (59.7) 764 (45.9) 1326 (62.0) 976 (49.4) 1143 (61.2) 
P value <.0001 <.0001 <.0001 
Race/ethnicity, n (%) 
African American 126 (5.2) 56 (4.0) 118 (7.1) 62 (2.9) 124 (6.3) 59 (3.2) 
Non-Hispanic White 1719 (70.7) 1129 (79.8) 1118 (67.2) 1729 (80.8) 1430 (72.4) 1419 (75.9) 
Hispanic 365 (15.0) 140 (10.0) 238 (14.3) 227 (10.6) 236 (11.9) 265 (14.2) 
Asian 153 (6.3) 48 (3.4) 132 (8.0) 69 (3.2) 115 (5.8) 86 (4.6) 
Other  66 (2.7) 41 (2.9) 57 (3.4) 50 (2.3) 70 (3.5) 38 (2.0) 
Missing 1 (0.04) 1 (0.1) 0 (0.0) 2 (0.1) 0 (0.0) 2 (0.1) 
P value <.0001 <.0001 <.0001 
Health insurance, n (%) 
Not insured 84 (3.5) 48 (3.4) 58 (3.5) 74 (3.5) 48 (2.4) 83 (4.4) 
Insured 2325 (95.7) 1344 (95.0) 1604 (96.4) 2061 (96.3) 1925 (97.5) 1743 (93.3) 
Missing 21 (0.9) 23 (1.6) 1 (0.1) 4 (0.2) 2 (1.1) 43 (2.3) 
P value .1010 .5632 <.0001 
Annual household income, n (%) 
<$19 999 659 (27.1) 435 (30.7) 571 (34.3) 506 (23.7) 665 (33.7) 426 (22.8) 
$20 000-$49 999 418 (17.2) 310 (21.9) 252 (15.2) 460 (21.5) 314 (15.9) 413 (22.1) 
>$50 000 1121 (46.1) 552 (39.0) 655 (39.4) 1018 (47.6) 812 (41.1) 862 (46.1) 
Missing 232 (9.5) 118 (8.3) 185 (11.1) 155 (7.2) 184 (9.3) 168 (9.0) 
P value <.0001 <.0001 <.0001 
Educational status, n (%) 
≤High school or less 383 (15.8) 327 (23.1) 353 (21.2) 319 (14.9) 419 (21.2) 288 (15.4) 
Post high school 2011 (82.8) 1083 (76.5) 1283 (77.1) 1807 (84.5) 1532 (77.6) 1564 (83.7) 
Missing 36 (1.5) 5 (0.4) 27 (1.6) 13 (0.6) 24 (1.2) 17 (0.9) 
P value <.0001 <.0001 <.0001 
Age at BMT in y 
Median (range) 42 (0-74) 49 (0-74) 44 (0-74) 45 (0-74) 49 (0-74) 39 (0-72) 
P value <.0001 <.0001 <.0001 
Follow-up since BMT to study start in y 
Median (range) 9 (2-41) 8 (2-41) 9 (3-41) 8 (2-41) 8 (3-41) 9 (2-41) 
P value <.0001 <.0001 <.0001 
BMI, n (%) 
Underweight (<18.5 kg/m293 (3.8) 35 (2.5) 75 (4.5) 52 (2.4) 68 (3.4) 61 (3.3) 
Normal weight (18.5 to <25 kg/m2838 (34.5) 394 (27.8) 538 (32.3) 693 (32.4) 581 (29.4) 652 (34.9) 
Overweight (25 to <30 kg/m2674 (27.7) 464 (32.8) 445 (29.8) 691 (32.3) 574 (29.1) 560 (30.0) 
Obese (≥30 kg/m2429 (17.7) 298 (21.1) 356 (21.4) 369 (17.2) 456 (23.1) 271 (14.5) 
Unknown 396 (16.3) 224 (15.8) 249 (15.0) 52 (2.4) 296 (15.0) 325 (17.4) 
P value <.0001 <.0001 <.0001 
Primary diagnosis , n (%) 
AML/MDS/ALL 796 (32.8) 420 (29.7) 549 (33.0) 653 (30.5) 605 (30.6) 612 (32.7) 
CML 245 (10.1) 148 (10.5) 153 (9.2) 227 (10.6) 157 (7.9) 237 (12.7) 
HL/NHL 709 (29.2) 531 (37.5) 471 (28.3) 766 (35.8) 641 (32.5) 601 (32.2) 
PCD 429 (17.6) 257 (18.2) 322 (19.4) 356 (16.6) 433 (21.9) 248 (13.3) 
Other  251 (10.3) 59 (4.2) 168 (10.1) 137 (6.4) 139 (7.0) 171 (9.2) 
P value <.0001 <.0001 .3239 
Disease status at first BMT, n (%) 
High risk 1038 (42.7) 681 (48.1) 726 (43.7) 976 (45.6) 959 (48.6) 758 (40.5) 
Standard risk 1073 (44.2) 618 (43.7) 743 (44.7) 927 (43.3) 842 (42.6) 850 (45.5) 
Missing 319 (13.1) 116 (8.2) 194 (11.7) 236 (11.0) 174 (8.8) 261 (14.0) 
P value <.0001 .4661 <.0001 
BMT type/cGvHD, n (%) 
Autologous 1157 (47.6) 774 (54.7) 796 (47.9) 1123 (52.5) 1030 (52.2) 898 (48.0) 
Allogeneic with cGvHD 685 (28.2) 349 (24.7) 470 (28.3) 545 (25.5) 532 (26.9) 504 (27.0) 
Allogeneic without cGvHD 555 (22.8) 266 (18.8) 366 (22.0) 443 (20.7) 374 (18.9) 447 (23.9) 
Allogeneic missing cGvHD 33 (1.4) 26 (1.8) 31 (1.9) 28 (1.3) 39 (2.0) 20 (1.1) 
P value <.0001 .0256 .0002 
Stem cell source, n (%) 
Bone marrow/cord blood 867 (35.7) 427 (30.2) 541 (32.5) 721 (33.7) 537 (27.2) 760 (40.7) 
Peripheral stem cells 1562 (64.3) 988 (69.8) 1121 (67.4) 1418 (66.3) 1438 (72.8) 1108 (59.3) 
Missing 1 (0.04) 0 (0.0) 1 (0.1) 0 (0.0) 0 (0.0) 1 (0.05) 
P value .0017 .3965 <.0001 
Conditioning intensity, n (%) 
MAC 1625 (66.9) 1032 (72.9) 1092 (65.7) 1534 (71.7) 1303 (66.0) 1354 (72.4) 
RIC/NMA 498 (20.5) 258 (18.2) 381 (22.9) 373 (17.4) 449 (22.7) 309 (16.5) 
Missing 307 (12.6) 125 (8.8) 190 (11.4) 232 (10.9) 223 (11.3) 206 (11.0) 
P value <.0001 <.0001 <.0001 
Conditioning regimen, n (%) 
TBI 1102 (45.3) 635 (44.9) 687 (41.3) 1022 (47.8) 766 (38.8) 976 (52.2) 
P value .7760 <.0001 <.0001 
Cyclophosphamide 1249 (51.4) 756 (53.4) 815 (49.0) 1181 (55.2) 928 (47.0) 1081 (57.8) 
P value .2246 .0001 <.0001 
Nitrosoureas 289 (11.9) 207 (14.6) 191 (11.5) 306 (14.3) 272 (13.4) 226 (12.1) 
P value .0147 .0105 .1210 
Etoposide 812 (33.4) 511 (36.1) 530 (31.9) 772 (36.1) 609 (30.8) 717 (38.4) 
P value .0895 .0065 <.0001 
Busulfan 273 (11.2) 135 (9.5) 223 (13.4) 182 (8.5) 223 (11.3) 184 (9.8) 
P value .1000 <.0001 .1452 
Cytarabine 137 (5.6) 114 (8.1) 99 (6.0) 151 (7.1) 153 (7.7) 98 (5.2) 
P value .0038 .1722 .0017 
Melphalan 598 (24.6) 404 (28.5) 470 (28.3) 527 (24.6) 642 (32.5) 358 (19.1) 
P value .0072 .0117 <.0001 
Fludarabine 379 (15.6) 216 (15.3) 293 (17.6) 302 (14.1) 363 (18.4) 234 (12.5) 
P value .7839 .0032 <.0001 
Chronic health conditions, n (%) 
Grade 3 or 4 1394 (57.4) 847 (59.9) 1023 (61.5) 1215 (56.8) 1344 (68.0) 899 (48.1) 
P value <.0001 .0034 <.0001 
Mental health , n (%) 
Not impaired 2317 (95.4) 1325 (93.6) 1579 (95.0) 2019 (94.4) 1858 (94.1) 1782 (95.4) 
Impaired 113 (4.6) 90 (6.4) 84 (5.0) 120 (5.6) 117 (5.9) 87 (4.6) 
P value .0222 .4480 .0794 
Some pain from cancer, n (%) 
No 791 (32.55) 388 (27.4) 454 (27.3) 701 (32.8) 419 (21.2) 761 (40.7) 
Yes 1616 (66.5) 1016 (71.8) 1189 (71.5) 1424 (66.6) 1538 (77.9) 1093 (58.5) 
Missing 23 (1.0) 11 (0.8) 20 (1.2) 14 (0.6) 18 (0.9) 15 (0.8) 
P value .0030 .0004 <.0001 
Anxiety from cancer treatments, n (%) 
Absent 2280 (93.8) 1308 (92.4) 1559 (93.7) 2025 (94.7) 1849 (93.6) 1740 (93.1) 
Present 104 (4.3) 74 (5.2) 85 (5.1) 93 (4.3) 108 (5.5) 70 (3.7) 
Missing 46 (1.9) 33 (2.3) 19 (1.1) 21 (1.0) 18 (0.9) 59 (3.2) 
P value .2507 .4773 .0170 
Vital status, n (%) 
Deceased 438 (18.0) 410 (29.0) 268 (16.1) 562 (26.3) 403 (20.4) 448 (24.0) 
Alive 1992 (82.0) 1005 (71.0) 1395 (83.9) 1577 (73.7) 1572 (79.6) 1421 (76.0) 
P value <.0001 <.0001 .0078 
Cause of death, n (%) 
Nonrecurrence§  204 (46.6) 209 (51.0) 113 (42.2) 288 (51.2) 159 (39.4) 256 (57.1) 
Recurrence 134 (30.6) 112 (27.3) 77 (28.7) 162 (28.8) 128 (31.8) 118 (26.3) 
Unknown 95 (21.7) 80 (19.5) 78 (29.1) 98 (17.4) 113 (28.0) 63 (14.1) 
External 5 (1.1) 9 (2.2) 0 (0.0) 14 (2.5) 3 (0.7) 11 (2.5) 
P value .3161 <.0001 <.0001 
Ever smoke, n (%) 
No - - 1266 (73.1) 1138 (53.2) 1231 (62.3) 1186 (63.5) 
Yes - - 394 (23.7) 994 (46.5) 735 (37.2) 678 (36.3) 
Missing - - 3 (0.2) 7 (0.3) 9 (0.5) 5 (0.3) 
P value - <.0001 .5071 
Smoking status, n (%) 
Former smoker 1215 (85.9) 335 (85.0) 854 (85.9) 638 (86.8) 575 (84.8) 
Current smoker 200 (14.1) 59 (15.0) 140 (14.1) 97 (13.2) 103 (15.2) 
Age at smoking initiation 
Median (IQR) 17 (10-57) 17 (10-48) 17 (10-57) 17 (10-57) 17 (10-50) 
Total y of smoking 
Median (IQR) 15 (1-57) - - - - 
Ever drink alcohol, n (%) 
No 1266 (52.1) 394 (27.8) - - 1079 (54.6) 575 (30.8) 
Yes 1138 (46.8) 994 (70.2) - - 883 (44.7) 1251 (66.9) 
Missing 26 (1.1) 27 (1.9) 13 (0.7) 43 (2.3) 
P value <.0001 <.0001 
Heavy drinker, n (%) 
No 1058 (93.0) 884 (88.9) 1949 (91.1) 839 (95.0) 1105 (88.3) 
Yes 80 (7.0) 110 (11.1) 190 (8.9) 44 (5.0) 146 (11.7) 
P value .0011 <.0001 
Vigorous physical activity, n (%) 
No 1231 (50.7) 735 (51.9) 651 (39.1) 626 (29.3) 
Yes 1186 (48.8) 678 (47.9) 575 (34.6) 1251 (58.5) 
Missing 13 (0.5) 2 (0.1) 437 (26.3) 262 (12.2) 
P value .1362 <.0001 
Levels of vigorous exercise (total metabolic equivalent h/wk-1) 
0 MET h/wk-1 1419 (58.4) 898 (63.5) 1157 (69.6) 1134 (53.0) 1975 (100.0) 351 (18.8) 
3 to <9 MET h/wk-1 736 (30.3) 343 (24.2) 410 (24.6) 668 (31.2) 1084 (58.0) 
≥ 9 MET h/wk-1 262 (10.8) 172 (12.2) 87 (5.2) 332 (15.5) 434 (23.2) 
Missing 13 (0.5) 2 (0.1) 9 (0.5) 5 (0.2) 
P value .0001 <.0001 
Variables of interestEver smokeEver drink alcoholVigorous physically active
No
n = 2430 (63.0%)
Yes
n = 1415 (36.8%)
No
n = 1663 (43.7%)
Yes
n = 2139 (56.3%)
No
n = 1975 (51.4%)
Yes
n = 1869 (48.6%)
Age at completing the survey in y 
Median (range) 54 (18-84) 59 (18-83) 57 (18-84) 56 (18-83) 60 (18-84) 52 (18-80) 
P value <.0001 <.0001 <.0001 
BMT era, n (%) 
1974-1989 211 (8.7) 106 (7.4) 103 (6.2) 207 (9.7) 109 (5.5) 208 (11.3) 
1990-2004 1043 (42.9) 614 (43.4) 670 (40.3) 957 (44.7) 730 (37.0) 931 (49.8) 
2005-2014 1176 (48.4) 695 (49.1) 890 (53.5) 975 (45.6) 1136 (57.5) 730 (39.1) 
P value .4311 <.0001 <.0001 
Sex, n (%) 
Female 1159 (47.7) 570 (40.3) 899 (54.1) 813 (38.0) 999 (50.6) 726 (38.8) 
Male 1271 (52.3) 845 (59.7) 764 (45.9) 1326 (62.0) 976 (49.4) 1143 (61.2) 
P value <.0001 <.0001 <.0001 
Race/ethnicity, n (%) 
African American 126 (5.2) 56 (4.0) 118 (7.1) 62 (2.9) 124 (6.3) 59 (3.2) 
Non-Hispanic White 1719 (70.7) 1129 (79.8) 1118 (67.2) 1729 (80.8) 1430 (72.4) 1419 (75.9) 
Hispanic 365 (15.0) 140 (10.0) 238 (14.3) 227 (10.6) 236 (11.9) 265 (14.2) 
Asian 153 (6.3) 48 (3.4) 132 (8.0) 69 (3.2) 115 (5.8) 86 (4.6) 
Other  66 (2.7) 41 (2.9) 57 (3.4) 50 (2.3) 70 (3.5) 38 (2.0) 
Missing 1 (0.04) 1 (0.1) 0 (0.0) 2 (0.1) 0 (0.0) 2 (0.1) 
P value <.0001 <.0001 <.0001 
Health insurance, n (%) 
Not insured 84 (3.5) 48 (3.4) 58 (3.5) 74 (3.5) 48 (2.4) 83 (4.4) 
Insured 2325 (95.7) 1344 (95.0) 1604 (96.4) 2061 (96.3) 1925 (97.5) 1743 (93.3) 
Missing 21 (0.9) 23 (1.6) 1 (0.1) 4 (0.2) 2 (1.1) 43 (2.3) 
P value .1010 .5632 <.0001 
Annual household income, n (%) 
<$19 999 659 (27.1) 435 (30.7) 571 (34.3) 506 (23.7) 665 (33.7) 426 (22.8) 
$20 000-$49 999 418 (17.2) 310 (21.9) 252 (15.2) 460 (21.5) 314 (15.9) 413 (22.1) 
>$50 000 1121 (46.1) 552 (39.0) 655 (39.4) 1018 (47.6) 812 (41.1) 862 (46.1) 
Missing 232 (9.5) 118 (8.3) 185 (11.1) 155 (7.2) 184 (9.3) 168 (9.0) 
P value <.0001 <.0001 <.0001 
Educational status, n (%) 
≤High school or less 383 (15.8) 327 (23.1) 353 (21.2) 319 (14.9) 419 (21.2) 288 (15.4) 
Post high school 2011 (82.8) 1083 (76.5) 1283 (77.1) 1807 (84.5) 1532 (77.6) 1564 (83.7) 
Missing 36 (1.5) 5 (0.4) 27 (1.6) 13 (0.6) 24 (1.2) 17 (0.9) 
P value <.0001 <.0001 <.0001 
Age at BMT in y 
Median (range) 42 (0-74) 49 (0-74) 44 (0-74) 45 (0-74) 49 (0-74) 39 (0-72) 
P value <.0001 <.0001 <.0001 
Follow-up since BMT to study start in y 
Median (range) 9 (2-41) 8 (2-41) 9 (3-41) 8 (2-41) 8 (3-41) 9 (2-41) 
P value <.0001 <.0001 <.0001 
BMI, n (%) 
Underweight (<18.5 kg/m293 (3.8) 35 (2.5) 75 (4.5) 52 (2.4) 68 (3.4) 61 (3.3) 
Normal weight (18.5 to <25 kg/m2838 (34.5) 394 (27.8) 538 (32.3) 693 (32.4) 581 (29.4) 652 (34.9) 
Overweight (25 to <30 kg/m2674 (27.7) 464 (32.8) 445 (29.8) 691 (32.3) 574 (29.1) 560 (30.0) 
Obese (≥30 kg/m2429 (17.7) 298 (21.1) 356 (21.4) 369 (17.2) 456 (23.1) 271 (14.5) 
Unknown 396 (16.3) 224 (15.8) 249 (15.0) 52 (2.4) 296 (15.0) 325 (17.4) 
P value <.0001 <.0001 <.0001 
Primary diagnosis , n (%) 
AML/MDS/ALL 796 (32.8) 420 (29.7) 549 (33.0) 653 (30.5) 605 (30.6) 612 (32.7) 
CML 245 (10.1) 148 (10.5) 153 (9.2) 227 (10.6) 157 (7.9) 237 (12.7) 
HL/NHL 709 (29.2) 531 (37.5) 471 (28.3) 766 (35.8) 641 (32.5) 601 (32.2) 
PCD 429 (17.6) 257 (18.2) 322 (19.4) 356 (16.6) 433 (21.9) 248 (13.3) 
Other  251 (10.3) 59 (4.2) 168 (10.1) 137 (6.4) 139 (7.0) 171 (9.2) 
P value <.0001 <.0001 .3239 
Disease status at first BMT, n (%) 
High risk 1038 (42.7) 681 (48.1) 726 (43.7) 976 (45.6) 959 (48.6) 758 (40.5) 
Standard risk 1073 (44.2) 618 (43.7) 743 (44.7) 927 (43.3) 842 (42.6) 850 (45.5) 
Missing 319 (13.1) 116 (8.2) 194 (11.7) 236 (11.0) 174 (8.8) 261 (14.0) 
P value <.0001 .4661 <.0001 
BMT type/cGvHD, n (%) 
Autologous 1157 (47.6) 774 (54.7) 796 (47.9) 1123 (52.5) 1030 (52.2) 898 (48.0) 
Allogeneic with cGvHD 685 (28.2) 349 (24.7) 470 (28.3) 545 (25.5) 532 (26.9) 504 (27.0) 
Allogeneic without cGvHD 555 (22.8) 266 (18.8) 366 (22.0) 443 (20.7) 374 (18.9) 447 (23.9) 
Allogeneic missing cGvHD 33 (1.4) 26 (1.8) 31 (1.9) 28 (1.3) 39 (2.0) 20 (1.1) 
P value <.0001 .0256 .0002 
Stem cell source, n (%) 
Bone marrow/cord blood 867 (35.7) 427 (30.2) 541 (32.5) 721 (33.7) 537 (27.2) 760 (40.7) 
Peripheral stem cells 1562 (64.3) 988 (69.8) 1121 (67.4) 1418 (66.3) 1438 (72.8) 1108 (59.3) 
Missing 1 (0.04) 0 (0.0) 1 (0.1) 0 (0.0) 0 (0.0) 1 (0.05) 
P value .0017 .3965 <.0001 
Conditioning intensity, n (%) 
MAC 1625 (66.9) 1032 (72.9) 1092 (65.7) 1534 (71.7) 1303 (66.0) 1354 (72.4) 
RIC/NMA 498 (20.5) 258 (18.2) 381 (22.9) 373 (17.4) 449 (22.7) 309 (16.5) 
Missing 307 (12.6) 125 (8.8) 190 (11.4) 232 (10.9) 223 (11.3) 206 (11.0) 
P value <.0001 <.0001 <.0001 
Conditioning regimen, n (%) 
TBI 1102 (45.3) 635 (44.9) 687 (41.3) 1022 (47.8) 766 (38.8) 976 (52.2) 
P value .7760 <.0001 <.0001 
Cyclophosphamide 1249 (51.4) 756 (53.4) 815 (49.0) 1181 (55.2) 928 (47.0) 1081 (57.8) 
P value .2246 .0001 <.0001 
Nitrosoureas 289 (11.9) 207 (14.6) 191 (11.5) 306 (14.3) 272 (13.4) 226 (12.1) 
P value .0147 .0105 .1210 
Etoposide 812 (33.4) 511 (36.1) 530 (31.9) 772 (36.1) 609 (30.8) 717 (38.4) 
P value .0895 .0065 <.0001 
Busulfan 273 (11.2) 135 (9.5) 223 (13.4) 182 (8.5) 223 (11.3) 184 (9.8) 
P value .1000 <.0001 .1452 
Cytarabine 137 (5.6) 114 (8.1) 99 (6.0) 151 (7.1) 153 (7.7) 98 (5.2) 
P value .0038 .1722 .0017 
Melphalan 598 (24.6) 404 (28.5) 470 (28.3) 527 (24.6) 642 (32.5) 358 (19.1) 
P value .0072 .0117 <.0001 
Fludarabine 379 (15.6) 216 (15.3) 293 (17.6) 302 (14.1) 363 (18.4) 234 (12.5) 
P value .7839 .0032 <.0001 
Chronic health conditions, n (%) 
Grade 3 or 4 1394 (57.4) 847 (59.9) 1023 (61.5) 1215 (56.8) 1344 (68.0) 899 (48.1) 
P value <.0001 .0034 <.0001 
Mental health , n (%) 
Not impaired 2317 (95.4) 1325 (93.6) 1579 (95.0) 2019 (94.4) 1858 (94.1) 1782 (95.4) 
Impaired 113 (4.6) 90 (6.4) 84 (5.0) 120 (5.6) 117 (5.9) 87 (4.6) 
P value .0222 .4480 .0794 
Some pain from cancer, n (%) 
No 791 (32.55) 388 (27.4) 454 (27.3) 701 (32.8) 419 (21.2) 761 (40.7) 
Yes 1616 (66.5) 1016 (71.8) 1189 (71.5) 1424 (66.6) 1538 (77.9) 1093 (58.5) 
Missing 23 (1.0) 11 (0.8) 20 (1.2) 14 (0.6) 18 (0.9) 15 (0.8) 
P value .0030 .0004 <.0001 
Anxiety from cancer treatments, n (%) 
Absent 2280 (93.8) 1308 (92.4) 1559 (93.7) 2025 (94.7) 1849 (93.6) 1740 (93.1) 
Present 104 (4.3) 74 (5.2) 85 (5.1) 93 (4.3) 108 (5.5) 70 (3.7) 
Missing 46 (1.9) 33 (2.3) 19 (1.1) 21 (1.0) 18 (0.9) 59 (3.2) 
P value .2507 .4773 .0170 
Vital status, n (%) 
Deceased 438 (18.0) 410 (29.0) 268 (16.1) 562 (26.3) 403 (20.4) 448 (24.0) 
Alive 1992 (82.0) 1005 (71.0) 1395 (83.9) 1577 (73.7) 1572 (79.6) 1421 (76.0) 
P value <.0001 <.0001 .0078 
Cause of death, n (%) 
Nonrecurrence§  204 (46.6) 209 (51.0) 113 (42.2) 288 (51.2) 159 (39.4) 256 (57.1) 
Recurrence 134 (30.6) 112 (27.3) 77 (28.7) 162 (28.8) 128 (31.8) 118 (26.3) 
Unknown 95 (21.7) 80 (19.5) 78 (29.1) 98 (17.4) 113 (28.0) 63 (14.1) 
External 5 (1.1) 9 (2.2) 0 (0.0) 14 (2.5) 3 (0.7) 11 (2.5) 
P value .3161 <.0001 <.0001 
Ever smoke, n (%) 
No - - 1266 (73.1) 1138 (53.2) 1231 (62.3) 1186 (63.5) 
Yes - - 394 (23.7) 994 (46.5) 735 (37.2) 678 (36.3) 
Missing - - 3 (0.2) 7 (0.3) 9 (0.5) 5 (0.3) 
P value - <.0001 .5071 
Smoking status, n (%) 
Former smoker 1215 (85.9) 335 (85.0) 854 (85.9) 638 (86.8) 575 (84.8) 
Current smoker 200 (14.1) 59 (15.0) 140 (14.1) 97 (13.2) 103 (15.2) 
Age at smoking initiation 
Median (IQR) 17 (10-57) 17 (10-48) 17 (10-57) 17 (10-57) 17 (10-50) 
Total y of smoking 
Median (IQR) 15 (1-57) - - - - 
Ever drink alcohol, n (%) 
No 1266 (52.1) 394 (27.8) - - 1079 (54.6) 575 (30.8) 
Yes 1138 (46.8) 994 (70.2) - - 883 (44.7) 1251 (66.9) 
Missing 26 (1.1) 27 (1.9) 13 (0.7) 43 (2.3) 
P value <.0001 <.0001 
Heavy drinker, n (%) 
No 1058 (93.0) 884 (88.9) 1949 (91.1) 839 (95.0) 1105 (88.3) 
Yes 80 (7.0) 110 (11.1) 190 (8.9) 44 (5.0) 146 (11.7) 
P value .0011 <.0001 
Vigorous physical activity, n (%) 
No 1231 (50.7) 735 (51.9) 651 (39.1) 626 (29.3) 
Yes 1186 (48.8) 678 (47.9) 575 (34.6) 1251 (58.5) 
Missing 13 (0.5) 2 (0.1) 437 (26.3) 262 (12.2) 
P value .1362 <.0001 
Levels of vigorous exercise (total metabolic equivalent h/wk-1) 
0 MET h/wk-1 1419 (58.4) 898 (63.5) 1157 (69.6) 1134 (53.0) 1975 (100.0) 351 (18.8) 
3 to <9 MET h/wk-1 736 (30.3) 343 (24.2) 410 (24.6) 668 (31.2) 1084 (58.0) 
≥ 9 MET h/wk-1 262 (10.8) 172 (12.2) 87 (5.2) 332 (15.5) 434 (23.2) 
Missing 13 (0.5) 2 (0.1) 9 (0.5) 5 (0.2) 
P value .0001 <.0001 

ALL, acute lymphoblastic leukemia; AML, acute myeloid leukemia; BMI, body mass index; CML, chronic myeloid leukemia; HL, Hodgkin lymphoma; IQR, interquartile range; MAC, myeloablative conditioning; MDS, myelodysplastic syndrome; NMA, nonmyeloablative; NHL, non-Hodgkin lymphoma; PCD, plasma cell dyscrasias; RIC, reduced intensity conditioning; -, data are not relevant or applicable.

Bold indicates statistically significant (P < 0.05).

Race other includes multiracial (n = 93), American Indian (n = 12), and Pacific Island (n = 2).

Primary diagnosis other includes severe aplastic anemia, other leukemia, and other.

Mental health is impaired outcome (T-score ≥63) in any of the 3 Brief Symptoms Inventory-18 items subscales (depression, somatization, or anxiety).

§

Nonrecurrence cause of death includes SMN (n = 149), cardiac (n = 86), infection (n = 84), pulmonary (n = 29), renal (n = 22), stroke (n = 12), neurologic (n = 10), other (n = 8), hepatic (n = 6), hemorrhage (n = 5), and VTE (n = 2).

Alcohol consumption

Overall, 2139 participants reported consuming alcohol (56.3%); 190 were heavy drinkers (8.9%). As shown in Table 2, participants who reported consuming alcohol were more likely to be male (62% vs 45.9%) and non-Hispanic White (80.8% vs 67.2%). In addition, those reporting alcohol consumption were more likely to be smokers (46.5% vs 23.7%) and more likely to practice vigorous physical activity (58.5% vs 34.6%).

Vigorous physical activity

Overall, 1975 participants reported not engaging in vigorous physical activity (51.4%). Participants not engaging in vigorous physical activity were more likely to be female (50.6% vs 38.8%), report cancer-related pain (77.9% vs 58.5%), and have grade 3 or 4 chronic health conditions (68.0% vs 48.1%) compared with individuals who reported vigorous physical activity. Furthermore, those not engaging in vigorous physical activity were less likely to report consuming alcohol (44.7% vs 54.6%) (Table 2).

Mortality after completing BMTSS survey

Smoking

Smokers had inferior survival probability (Figure 1Ai) and a higher cumulative incidence of NRM (Figure 1Bi) compared with nonsmokers. As shown in Table 3, multivariable analysis revealed significantly higher hazards of all-cause mortality among ever smokers (adjusted hazard ratio [aHR], 1.2; 95% CI, 1.1-1.5; reference, never smokers). Furthermore, all-cause mortality was higher among former smokers (aHR, 1.2; 95% CI, 1.1-1.5) and current smokers (aHR, 1.7; 95% CI, 1.2-2.5) than nonsmokers. The adjusted hazard of NRM was 1.3-fold higher for former smokers (aHR, 1.3; 95% CI, 1.0-1.8) and 1.6-fold higher for current smokers (aHR, 1.6; 95% CI, 1.0-2.7) than for nonsmokers (Table 3). Figure 2 shows the common causes of death among smokers (RRM, 27.3%; SMNs, 18.3%; cardiovascular disease, 14%; and pulmonary disease, 3%). The specific SMN-related deaths among smokers were more likely because of smoking-related malignancies (76% vs 24%), such as lung, bladder, esophagus, stomach, hypopharynx, tongue, leukemia, colon, rectum, kidney, liver, and pancreas. There was a significant interaction (P = .019) between TBI and smoking, such that smokers who had received TBI had a 1.4-fold higher hazard of all-cause mortality (95% CI, 1.1-1.9), whereas smokers who had not received TBI did not demonstrate a higher hazard of all-cause mortality (HR, 1.1; 95% CI, 0.8-1.4). As shown in Table 4, the never smokers, former smokers, and current smokers were at a 4.3-fold, 4.5-fold, and 8.7-fold higher risk of death than the age- and sex-matched general population, respectively. The corresponding excess deaths per 1000 person-years were 25.5, 36.9, and 39.4, respectively.

Figure 1.

Risk of mortality by risky health behaviors. (A) Risk of all-cause mortality after blood or marrow transplantation (BMT). (B) Risk of non-recurrence mortality after BMT.

Figure 1.

Risk of mortality by risky health behaviors. (A) Risk of all-cause mortality after blood or marrow transplantation (BMT). (B) Risk of non-recurrence mortality after BMT.

Close modal
Table 3.

Risky health behaviors and hazard of subsequent all-cause and nonrecurrence–related late mortality

Variables of interestCrude HR (95% CI)aHR (95% CI)
All-cause mortalityAll-cause mortalityNonrecurrence-related mortality
Ever smoke  
No Reference Reference Reference 
Yes 1.5 (1.4-1.8) 1.2 (1.1-1.5) 1.3 (1.0-1.8) 
Smoking status  
Non-smoker Reference Reference Reference 
Former smoker 1.6 (1.4-1.8) 1.2 (1.1-1.5) 1.3 (1.0-1.8) 
Current smoker 1.4 (1.1-1.9) 1.7 (1.2-2.5) 1.6 (1.0-2.7) 
Ever drink alcohol  
No Reference Reference Reference 
Yes 1.3 (1.1-1.5) 1.1 (0.9-1.3) 1.1 (0.9-1.4) 
Heavy drinker  
No Reference Reference Reference 
Yes 0.9 (0.7-1.2) 1.4 (1.0-1.8) 1.4 (1.0-2.0) 
Vigorous physical activity for at least 10 min at a time§  
Yes Reference Reference Reference 
No 1.5 (1.3-1.7) 1.2 (1.1-1.4) 1.2 (1.0-1.6) 
Levels of vigorous exercise (total metabolic equivalent h/wk-1)§  
≥ 9 MET h/wk-1 Reference Reference Reference 
3 to <9 MET h/wk-1 0.6 (0.4-0.8) 0.7 (0.5-1.0) 0.7 (0.6-0.1) 
0 MET h/wk-1 1.4 (1.2-1.7) 1.3 (1.1-1.7) 1.3 (1.0-1.7) 
Variables of interestCrude HR (95% CI)aHR (95% CI)
All-cause mortalityAll-cause mortalityNonrecurrence-related mortality
Ever smoke  
No Reference Reference Reference 
Yes 1.5 (1.4-1.8) 1.2 (1.1-1.5) 1.3 (1.0-1.8) 
Smoking status  
Non-smoker Reference Reference Reference 
Former smoker 1.6 (1.4-1.8) 1.2 (1.1-1.5) 1.3 (1.0-1.8) 
Current smoker 1.4 (1.1-1.9) 1.7 (1.2-2.5) 1.6 (1.0-2.7) 
Ever drink alcohol  
No Reference Reference Reference 
Yes 1.3 (1.1-1.5) 1.1 (0.9-1.3) 1.1 (0.9-1.4) 
Heavy drinker  
No Reference Reference Reference 
Yes 0.9 (0.7-1.2) 1.4 (1.0-1.8) 1.4 (1.0-2.0) 
Vigorous physical activity for at least 10 min at a time§  
Yes Reference Reference Reference 
No 1.5 (1.3-1.7) 1.2 (1.1-1.4) 1.2 (1.0-1.6) 
Levels of vigorous exercise (total metabolic equivalent h/wk-1)§  
≥ 9 MET h/wk-1 Reference Reference Reference 
3 to <9 MET h/wk-1 0.6 (0.4-0.8) 0.7 (0.5-1.0) 0.7 (0.6-0.1) 
0 MET h/wk-1 1.4 (1.2-1.7) 1.3 (1.1-1.7) 1.3 (1.0-1.7) 

Bolded values indicate statistical significance (CI does not include 1).

Adjusted for sex, race/ethnicity, BMT era, time from BMT to study entry, age at BMT, primary diagnosis, stem cell source, disease status at BMT, BMT type, cGvHD, conditioning intensity, TBI, cyclophosphamide, nitrosoureas, busulfan, fludarabine, household income, educational status, chronic health conditions, mental health, physical activity status, alcohol consumption (ever), and total years of smoking. Survivors with missing smoking status were excluded from this analysis.

Adjusted for sex, race/ethnicity, BMT era, time from BMT to study entry, stem cell source, age at BMT, primary diagnosis, disease status at BMT, BMT type, cGvHD, conditioning intensity, TBI, cyclophosphamide, nitrosoureas, busulfan, fludarabine, household income, chronic health conditions, educational status, mental health, physical activity status, and smoking status (ever). Survivors with missing alcohol consumption status were missing from this analysis.

§

Adjusted for sex, race/ethnicity, BMT era, time from BMT to study entry, stem cell source, age at BMT, primary diagnosis, disease status at BMT, BMT type, cGvHD, conditioning intensity, TBI, cyclophosphamide, nitrosoureas, busulfan, fludarabine, household income, chronic health condition, educational status, mental health, anxiety from cancer treatment, smoking status (ever), and alcohol consumption (ever). Survivors with missing physical activity status were excluded from this analysis.

Figure 2.

Survivors’ risk of cause-specific mortality by risky health behaviors.

Figure 2.

Survivors’ risk of cause-specific mortality by risky health behaviors.

Close modal
Table 4.

Study participants’ age- and sex-standardized mortality ratio compared with US general population and excess deaths per 1000 person-years

SMR (95% CI)Excess deaths per 1000 person-y (95% CI)
Smoking status  
Never 4.3 (3.8-4.7) 25.5 (22-29) 
Former 4.5 (4.0-5.0) 36.9 (32-42) 
Current 8.7 (6.4-10.9) 39.4 (28-51) 
Alcohol consumption status 
Nonheavy drinker 4.0 (3.6-4.3) 30.7 (28-34) 
Heavy drinker 13.0 (10.0-15.9) 53.5 (40-67) 
Levels of vigorous exercise (total metabolic equivalent h/wk-1) 
0 MET h/wk-1 4.9 (4.4-5.2) 35.4 (32-39) 
3 to <9 MET h/wk-1 2.4 (1.9-2.8) 11.0 (7-15) 
≥9 MET h/wk-1 6.7 (5.7-7.9) 30.4 (24-36) 
SMR (95% CI)Excess deaths per 1000 person-y (95% CI)
Smoking status  
Never 4.3 (3.8-4.7) 25.5 (22-29) 
Former 4.5 (4.0-5.0) 36.9 (32-42) 
Current 8.7 (6.4-10.9) 39.4 (28-51) 
Alcohol consumption status 
Nonheavy drinker 4.0 (3.6-4.3) 30.7 (28-34) 
Heavy drinker 13.0 (10.0-15.9) 53.5 (40-67) 
Levels of vigorous exercise (total metabolic equivalent h/wk-1) 
0 MET h/wk-1 4.9 (4.4-5.2) 35.4 (32-39) 
3 to <9 MET h/wk-1 2.4 (1.9-2.8) 11.0 (7-15) 
≥9 MET h/wk-1 6.7 (5.7-7.9) 30.4 (24-36) 

SMR, standardized mortality ratio.

Alcohol consumption

We did not observe a significant difference in all-cause mortality (aHR, 1.1; 95% CI, 0.9-1.3) or NRM (aHR, 1.1; 95% CI, 0.9-1.4) between patients who reported ever drinking alcohol and those who did not (Table 3). Figure 1Aii,Bii show that heavy drinkers had a lower risk of all-cause mortality and NRM after BMT than nonheavy drinkers. However, after adjusting for time from BMT to study entry, age at BMT, sex, race/ethnicity, BMT era, stem cell source, primary diagnosis, disease status at BMT, BMT type, cGvHD, conditioning intensity, TBI, cyclophosphamide, nitrosoureas, busulfan, fludarabine, household income, chronic health conditions, educational status, mental health, physical activity status, and smoking status, a significantly higher hazard of all-cause mortality was observed among heavy drinkers (aHR, 1.4; 95% CI, 1.0-1.8; reference, nonheavy drinkers). In addition, heavy alcohol drinkers were at increased risk of NRM compared with nonheavy drinkers (aHR, 1.4; 95% CI, 1.0-2.0) (Table 3). The most common causes of death among heavy drinkers included disease recurrence (18.2%), SMNs (27.3%), cardiovascular disease (13%), and infection (6.5%) (Figure 2). Alcohol consumption did not show any interaction with TBI in increasing the hazard of all-cause mortality (ever drinker: P = .627; heavy drinker: P = .136). As shown in Table 4, the nonheavy and heavy drinkers were at a 4.0-fold and a 13.0-fold higher risk of death than the age- and sex-matched general population, respectively. The corresponding excess deaths per 1000 person-years were 30.7 and 53.5, respectively.

Vigorous physical activity

Figure 1Aiii,Biii show that survivors who exercised 3 to <9 MET hour/week-1 had the greatest survival probability (all-cause mortality and NRM) after BMT compared with the other groups. Increased hazard of all-cause mortality was observed among those not engaging in vigorous physical activity (HR, 1.2; 95% CI, 1.1-1.4; reference, reported vigorous physical activity). Survivors who exercised 0 MET hour/week-1 were at a higher risk of all-cause mortality than individuals who exercised ≥9 MET hour/week-1 (aHR, 1.3; 95% CI, 1.1-1.7). Individuals who exercised 3 to <9 MET hour/week-1 were at 30% lower risk of all-cause mortality than those who exercised ≥9 MET hour/week-1 (aHR, 0.7; 95% CI, 0.5-1.0) (Table 3). Individuals who exercised 0 MET hour/week-1 were at higher risk of NRM (aHR=1.3, 95%CI=1.0-1.7) than individuals who exercised ≥9 MET hour/week-1. Individuals who exercised 3 to <9 MET hour/week-1 were at lower risk of NRM than those who exercised ≥9 MET hour/week-1 (aHR, 0.7; 95% CI, 0.6-1.0). As shown in Figure 2, the causes of death did not differ by level of vigorous exercise, with the exception of SMN-related deaths, in which the prevalence was highest among those with the highest level of activity. However, the adjusted hazards of SMN-related deaths revealed that survivors who exercised 0 MET hour/week-1 had a higher risk of SMN-related deaths than survivors who exercised ≥9 MET hour/week-1 (aHR, 1.9; 95% CI, 0.4-1.2) (supplemental Table 3). Vigorous physical activity did not demonstrate a significant interaction with TBI in increasing the hazard of all-cause mortality (P = .627). As shown in Table 4, survivors who practiced 0 MET hour/week-1, 3 to >9 MET hour/week-1, and ≥9 MET hour/week-1 were at a 4.9-fold, 2.4-fold, and 6.7-fold higher risk of death than the age- and sex-matched general population, respectively. The corresponding excess deaths per 1000 person-years were 35.4, 11.0, and 30.4, respectively.

Risky health behaviors and late mortality by clinical/demographic characteristics

The association between risky health behaviors of interest and all-cause late mortality did not differ based on sex. Time from BMT to study participation, age at BMT, and BMT type were not effect-modifiers (supplemental Table 2). Analyses stratified by age at survey completion (<56 years; ≥56 years) revealed that the magnitude of association between risky health behaviors and late mortality did not differ by age at study participation, with the exception that the association between lack of physical activity and mortality was higher in the younger age group (supplemental Figures 3-5).

Risk health behaviors in clusters

Supplemental Figure 6 shows the numbers of participants practicing risky health behaviors in clusters. The hazard of all-cause mortality and NRM increased with the number of risk behaviors. The hazard of all-cause mortality (aHR, 3.7; 95% CI, 1.8-7.6; reference, no risky behavior) and NRM (aHR, 2.9; 95% CI, 0.8-9.5; reference, no risky behavior) was highest among participants who reported practicing all 3 risky behaviors (smoking, heavy alcohol drinking, and lack of physical activity) compared with those practicing no risky behaviors (supplemental Table 4).

This analysis of a large cohort of adult BMT survivors followed for a median of 15 years from BMT, including 5 years after completing a comprehensive health-related survey, indicates that risky health behaviors were associated with increased risk of all-cause mortality. In particular, smoking (current or former), heavy drinking, and not engaging in vigorous physical activity increased the risk of NRM.

Although former smokers were at a 20% higher hazard of all-cause mortality, current smokers were at 70% higher risk. Furthermore, current smokers were at a 60% higher risk of NRM than nonsmokers. The most common causes of nonrecurrence-related death were subsequent malignancies and cardiovascular disease. Our findings are consistent with previous studies in the general population demonstrating a definitive association between smoking and twofold to threefold higher hazards of all-cause mortality.37-45 Epidemiologic studies strongly support the association between cigarette smoking and cardiovascular events and mortality.46-48 Even low-tar cigarette smoking is associated with an increased risk of cardiovascular events and mortality in comparison with not smoking.49,50 Cigarette smoking causes endothelial dysfunction, resulting in thrombotic lesions.51 However, given the high risk of late mortality among BMT recipients,22,52 the addition of smoking, especially in the setting of TBI increases the risk even further.

Heavy alcohol consumption was associated with a 40% higher hazard of all-cause mortality and NRM. Common causes of nonrecurrence-related mortality included subsequent malignancies and cardiovascular disease. Our findings are consistent with several previous studies among cancer and noncancer populations.53-56 Observational studies have consistently shown a higher risk of all-cause and cardiovascular mortality in people with high level of alcohol consumption in the general population.57,58 High doses of alcohol are associated with the development of hypertension, coronary and peripheral atherosclerosis, changes in lipid profile, and an increased risk of stroke.59,60 

Physical inactivity increases the risk of coronary heart disease, type 2 diabetes, and breast and colon cancers, resulting in a shortened life expectancy.61 We found that lack of vigorous exercise among BMT survivors was associated with a higher risk of all-cause mortality and NRM. Survivors who did not exercise vigorously had a 20% higher risk of all-cause mortality and NRM than those who did. Previous studies in the general population report higher hazards of all-cause mortality among participants who are inactive.62,63 A report from the Childhood Cancer Survivor Study suggested that vigorous exercise is associated with a lower risk of mortality in adult survivors of childhood cancer.64 When examining the intensity of vigorous activity, we found a 30% higher hazard of all-cause mortality and NRM among participants who exercised 0 MET hour/week-1 than those who exercised ≥9 MET hour/week-1. Interestingly, the hazard of all-cause mortality and NRM among participants who reported 3 to >9 MET hour/week-1 vigorous physical activity was lower than in individuals who exercised ≥9 MET hour/week-1. Previous studies suggest that exercise dose-response associations with mortality are not necessarily linear.63,65 Several studies have demonstrated a U-shaped or a reverse J-shaped relationship between physical activity and mortality (ie, the mortality risk reduction is attenuated or eliminated at a high threshold of physical activity).66 Long-term excessive exercise may induce pathologic structural remodeling of the heart and large arteries. Emerging data suggest that excessive exercise can cause transient acute volume overload of the atria and right ventricle, with transient reductions in right ventricular ejection fraction and elevations of cardiac biomarkers, all of which return to normal within 1 week. Over months to years of repetitive injury, this process, in some individuals, may lead to patchy myocardial fibrosis, particularly in the atria, interventricular septum, and right ventricle, creating a substrate for atrial and ventricular arrhythmias. Additionally, long-term excessive sustained exercise may be associated with coronary artery calcification, diastolic dysfunction, and large-artery wall stiffening.67 

From a public health perspective, addressing risky health behaviors and promoting positive health behaviors is important because they are potentially modifiable.68 Previous studies in the general population report that smoking, alcohol-related disorders, and physical inactivity can directly affect health–related quality of life.69-74 The association between these potentially modifiable factors and late mortality offers opportunities for development of interventions to improve both the quality and quantity of life after BMT.

This study needs to be placed in the context of its limitations. Our analysis relied on self-reported measures, which are subject to reporting and recall bias. There is a potential for survival bias because the time from BMT to survey completion varied between survivors. We adjusted for time from BMT to survey completion to address this concern, and the magnitude of the association between risky behaviors and mortality did not differ when stratified by time from BMT to survey completion. There is a potential for behavior change between completion of the survey and last follow-up or death. We attempted to address this by using the time from survey to death or end of follow-up as the time axis in the analysis. These limitations notwithstanding, to our knowledge, this is the first large, multi-institutional study with mature follow-up that evaluated risky health behaviors and their association with late mortality. Investigating these risky health behaviors could inform the development of interventions to reduce late mortality after BMT. It also highlights the importance of educating survivors and their health care providers about their risks and the need for long-term surveillance.

This work was supported in part by the National Cancer Institute (R01 CA078938 and U01 CA213140; S.B.) and the Leukemia and Lymphoma Society (R6502-16; S.B.).

Contribution: S.B., S.J.F., D.J.W., S.H.A., and R.B. contributed to study conception and design; S.B., L.H., E.R., N.B, A.B., H.S.T., F.L.W. and Q.M. collected and assembled the data; N.B. and S.B. analyzed and interpreted the data and drafted the manuscript; S.B., L.H., W.L., E.R., and N.B. provided administrative, technical, or material support; S.B.  and S.H.A. supervised the study; and all authors critically reviewed the manuscript for important intellectual content and approved the final manuscript.

Conflict-of-interest disclosure: The authors declare no competing financial interests.

Correspondence: Smita Bhatia, The University of Alabama at Birmingham, 1600 7th Ave South, Lowder 500, Birmingham, AL 35233; e-mail: smitabhatia@uabmc.edu.

1.
D’Souza
A
,
Fretham
C
,
Lee
SJ
, et al
.
Current use of and trends in hematopoietic cell transplantation in the United States
.
Biol Blood Marrow Transplant
.
2020
;
26
(
8
):
e177
-
e182
.
2.
Niederwieser
D
,
Baldomero
H
,
Szer
J
, et al
.
Hematopoietic stem cell transplantation activity worldwide in 2012 and a SWOT analysis of the Worldwide Network for Blood and Marrow Transplantation Group including the global survey
.
Bone Marrow Transplant
.
2016
;
51
(
6
):
778
-
785
.
3.
Majhail
NS
.
Long-term complications after hematopoietic cell transplantation
.
Hematol Oncol Stem Cell Ther
.
2017
;
10
(
4
):
220
-
227
.
4.
Gangaraju
R
,
Chen
Y
,
Hageman
L
, et al
.
Venous thromboembolism in autologous blood or marrow transplantation survivors: a report from the blood or marrow transplant survivor study
.
Biol Blood Marrow Transplant
.
2019
;
25
(
11
):
2261
-
2266
.
5.
Arora
M
,
Chen
Y
,
Hageman
L
, et al
.
Morbidity burden in survivors of multiple myeloma who underwent autologous transplantation: a bone marrow transplantation survivor study
.
Cancer
.
2020
;
126
(
14
):
3322
-
3329
.
6.
Sharafeldin
N
,
Bosworth
A
,
Patel
SK
, et al
.
Cognitive functioning after hematopoietic cell transplantation for hematologic malignancy: results from a prospective longitudinal study
.
J Clin Oncol
.
2018
;
36
(
5
):
463
-
475
.
7.
Baker
KS
,
Ness
KK
,
Steinberger
J
, et al
.
Diabetes, hypertension, and cardiovascular events in survivors of hematopoietic cell transplantation: a report from the bone marrow transplantation survivor study
.
Blood
.
2007
;
109
(
4
):
1765
-
1772
.
8.
Sun
CL
,
Francisco
L
,
Kawashima
T
, et al
.
Prevalence and predictors of chronic health conditions after hematopoietic cell transplantation: a report from the Bone Marrow Transplant Survivor Study
.
Blood
.
2010
;
116
(
17
):
3129
-
3139
. quiz 3377.
9.
Sun
CL
,
Kersey
JH
,
Francisco
L
, et al
.
Burden of morbidity in 10+ year survivors of hematopoietic cell transplantation: report from the bone marrow transplantation survivor study
.
Biol Blood Marrow Transplant
.
2013
;
19
(
7
):
1073
-
1080
.
10.
Armenian
SH
,
Sun
CL
,
Shannon
T
, et al
.
Incidence and predictors of congestive heart failure after autologous hematopoietic cell transplantation
.
Blood
.
2011
;
118
(
23
):
6023
-
6029
.
11.
Arora
M
,
Sun
CL
,
Ness
KK
, et al
.
Physiologic frailty in nonelderly hematopoietic cell transplantation patients: results from the bone marrow transplant survivor study
.
JAMA Oncol
.
2016
;
2
(
10
):
1277
-
1286
.
12.
Armenian
SH
,
Sun
CL
,
Mills
G
, et al
.
Predictors of late cardiovascular complications in survivors of hematopoietic cell transplantation
.
Biol Blood Marrow Transplant
.
2010
;
16
(
8
):
1138
-
1144
.
13.
Gangaraju
R
,
Chen
Y
,
Hageman
L
, et al
.
Late-occurring venous thromboembolism in allogeneic blood or marrow transplant survivors: a BMTSS-HiGHS2 risk model
.
Blood Adv
.
2021
;
5
(
20
):
4102
-
4111
.
14.
McDonald
AM
,
Chen
Y
,
Wu
J
, et al
.
Total body irradiation and risk of breast cancer after blood or marrow transplantation: a blood or marrow transplantation survivor study report
.
J Clin Oncol
.
2020
;
38
(
25
):
2872
-
2882
.
15.
Wong
FL
,
Teh
JB
,
Atencio
L
, et al
.
Conditional survival, cause-specific mortality, and risk factors of late mortality after allogeneic hematopoietic cell transplantation
.
J Natl Cancer Inst
.
2020
;
112
(
11
):
1153
-
1161
.
16.
Holmqvist
AS
,
Chen
Y
,
Wu
J
, et al
.
Assessment of late mortality risk after allogeneic blood or marrow transplantation performed in childhood
.
JAMA Oncol
.
2018
;
4
(
12
):
e182453
.
17.
Bhatia
S
,
Francisco
L
,
Carter
A
, et al
.
Late mortality after allogeneic hematopoietic cell transplantation and functional status of long-term survivors: report from the Bone Marrow Transplant Survivor Study
.
Blood
.
2007
;
110
(
10
):
3784
-
3792
.
18.
Duell
T
,
van Lint
MT
,
Ljungman
P
, et al
.
Health and functional status of long-term survivors of bone marrow transplantation. EBMT Working Party on Late Effects and EULEP Study Group on Late Effects. European Group for Blood and Marrow Transplantation
.
Ann Intern Med
.
1997
;
126
(
3
):
184
-
192
.
19.
Socie
G
,
Stone
JV
,
Wingard
JR
, et al
.
Long-term survival and late deaths after allogeneic bone marrow transplantation. Late effects Working Committee of the International Bone Marrow Transplant Registry
.
N Engl J Med
.
1999
;
341
(
1
):
14
-
21
.
20.
Pond
GR
,
Lipton
JH
,
Messner
HA
.
Long-term survival after blood and marrow transplantation: comparison with an age- and gender-matched normative population
.
Biol Blood Marrow Transplant
.
2006
;
12
(
4
):
422
-
429
.
21.
Martin
PJ
,
Counts
GW
,
Appelbaum
FR
, et al
.
Life expectancy in patients surviving more than 5 years after hematopoietic cell transplantation
.
J Clin Oncol
.
2010
;
28
(
6
):
1011
-
1016
.
22.
Bhatia
S
,
Dai
C
,
Landier
W
, et al
.
Trends in late mortality and life expectancy after allogeneic blood or marrow transplantation over 4 decades: a blood or marrow transplant survivor study report
.
JAMA Oncol
.
2021
;
7
(
11
):
1626
-
1634
.
23.
Shopland
DR
.
Tobacco use and its contribution to early cancer mortality with a special emphasis on cigarette smoking
.
Environ Health Perspect
.
1995
;
103
(
Suppl 8
):
131
-
142
.
24.
Bradshaw
PT
,
Ibrahim
JG
,
Khankari
N
, et al
.
Post-diagnosis physical activity and survival after breast cancer diagnosis: the Long Island Breast Cancer Study
.
Breast Cancer Res Treat
.
2014
;
145
(
3
):
735
-
742
.
25.
Kenfield
SA
,
Stampfer
MJ
,
Giovannucci
E
,
Chan
JM
.
Physical activity and survival after prostate cancer diagnosis in the health professionals follow-up study
.
J Clin Oncol
.
2011
;
29
(
6
):
726
-
732
.
26.
Campbell
PT
,
Patel
AV
,
Newton
CC
,
Jacobs
EJ
,
Gapstur
SM
.
Associations of recreational physical activity and leisure time spent sitting with colorectal cancer survival
.
J Clin Oncol
.
2013
;
31
(
7
):
876
-
885
.
27.
Sasco
AJ
,
Secretan
MB
,
Straif
K
.
Tobacco smoking and cancer: a brief review of recent epidemiological evidence
.
Lung Cancer
.
2004
;
45
(
Suppl 2
):
S3
-
9
.
28.
Bagnardi
V
,
Rota
M
,
Botteri
E
, et al
.
Alcohol consumption and site-specific cancer risk: a comprehensive dose-response meta-analysis
.
Br J Cancer
.
2015
;
112
(
3
):
580
-
593
.
29.
Common Terminology Criteria for Adverse Events (version 3)
. Cancer Therapy Evaluation Program.
2013
.
30.
Recklitis
CJ
,
Blackmon
JE
,
Chang
G
.
Validity of the Brief Symptom Inventory-18 (BSI-18) for identifying depression and anxiety in young adult cancer survivors: comparison with a structured clinical diagnostic interview
.
Psychol Assess
.
2017
;
29
(
10
):
1189
-
1200
.
31.
Merport
A
,
Recklitis
CJ
.
Does the Brief Symptom Inventory-18 case rule apply in adult survivors of childhood cancer? Comparison with the Symptom Checklist-90
.
J Pediatr Psychol
.
2012
;
37
(
6
):
650
-
659
.
32.
Centers for Disease Control and Prevention
. National Center for Health Statistics.
National death index
;
2022
Accessed 31 December 2020. https://www.cdc.gov/nchs/ndi/index.htm.
33.
Ainsworth
BE
,
Haskell
WL
,
Herrmann
SD
, et al
.
2011 Compendium of physical activities: a second update of codes and MET values
.
Med Sci Sports Exerc
.
2011
;
43
(
8
):
1575
-
1581
.
34.
Majhail
NS
,
Nayyar
S
,
Santibañez
MEB
,
Murphy
EA
,
Denzen
EM
.
Racial disparities in hematopoietic cell transplantation in the United States
.
Bone Marrow Transplant
.
2012
;
47
(
11
):
1385
-
1390
.
35.
Fine
JP
,
Gray
RJ
.
A proportional hazards model for the subdistribution of a competing risk
.
J Am Stat Assoc
.
1997
(
99
):
496
-
509
.
36.
National Center for Health Statistics
. Centers for Disease Control and Prevention.
Health data interactive
;
2022
Accessed 1 August 2023. https://www.cdc.gov/nchs/products/life_tables.htm.
37.
Jee
SH
,
Samet
JM
,
Ohrr
H
,
Kim
JH
,
Kim
IS
.
Smoking and cancer risk in Korean men and women
.
Cancer Causes Control
.
2004
;
15
(
4
):
341
-
348
.
38.
Kenfield
SA
,
Stampfer
MJ
,
Rosner
BA
,
Colditz
GA
.
Smoking and smoking cessation in relation to mortality in women
.
JAMA
.
2008
;
299
(
17
):
2037
-
2047
.
39.
Thun
MJ
,
Carter
BD
,
Feskanich
D
, et al
.
50-year trends in smoking-related mortality in the United States
.
N Engl J Med
.
2013
;
368
(
4
):
351
-
364
.
40.
Ezzati
M
,
Lopez
AD
.
Estimates of global mortality attributable to smoking in 2000
.
Lancet
.
2003
;
362
(
9387
):
847
-
852
.
41.
Jones
LW
,
Liu
Q
,
Armstrong
GT
, et al
.
Exercise and risk of major cardiovascular events in adult survivors of childhood Hodgkin lymphoma: a report from the childhood cancer survivor study
.
J Clin Oncol
.
2014
;
32
(
32
):
3643
-
3650
.
42.
GBD 2015 Tobacco Collaborators
.
Smoking prevalence and attributable disease burden in 195 countries and territories, 1990-2015: a systematic analysis from the Global Burden of Disease Study 2015
.
Lancet
.
2017
;
389
(
10082
):
1885
-
1906
.
43.
Sakata
R
,
McGale
P
,
Grant
EJ
,
Ozasa
K
,
Peto
R
,
Darby
SC
.
Impact of smoking on mortality and life expectancy in Japanese smokers: a prospective cohort study
.
BMJ
.
2012
;
345
:
e7093
.
44.
Jha
P
,
Ramasundarahettige
C
,
Landsman
V
, et al
.
21st-century hazards of smoking and benefits of cessation in the United States
.
N Engl J Med
.
2013
;
368
(
4
):
341
-
350
.
45.
Banks
E
,
Joshy
G
,
Weber
MF
, et al
.
Tobacco smoking and all-cause mortality in a large Australian cohort study: findings from a mature epidemic with current low smoking prevalence
.
BMC Med
.
2015
;
13
:
38
.
46.
Hammond
E
,
Horn
D
.
Smoking and death rates: report on forty-four months of follow-up of 187,783 men. 2. Death rates by cause
.
J Am Med Assoc
.
1958
;
166
(
11
):
1294
-
1308
.
47.
Doll
R
,
Peto
R
.
Mortality in relation to smoking: 20 years' observations on male British doctors
.
Br Med J
.
1976
;
2
(
6051
):
1525
-
1536
.
48.
Willett
WC
,
Green
A
,
Stampfer
MJ
, et al
.
Relative and absolute excess risks of coronary heart disease among women who smoke cigarettes
.
N Engl J Med
.
1987
;
317
(
21
):
1303
-
1309
.
49.
Negri
E
,
Franzosi
MG
,
La Vecchia
C
,
Santoro
L
,
Nobili
A
,
Tognoni
G
.
Tar yield of cigarettes and risk of acute myocardial infarction. GISSI-EFRIM Investigators
.
BMJ
.
1993
;
306
(
6892
):
1567
-
1570
.
50.
Bolinder
G
,
Alfredsson
L
,
Englund
A
,
de Faire
U
.
Smokeless tobacco use and increased cardiovascular mortality among Swedish construction workers
.
Am J Public Health
.
1994
;
84
(
3
):
399
-
404
.
51.
Ambrose
JA
,
Barua
RS
.
The pathophysiology of cigarette smoking and cardiovascular disease: an update
.
J Am Coll Cardiol
.
2004
;
43
(
10
):
1731
-
1737
.
52.
Bhatia
S
,
Dai
C
,
Landier
W
, et al
.
Trends in late mortality and life expectancy after autologous blood or marrow transplantation over three decades: a BMTSS report
.
J Clin Oncol
.
2022
;
40
(
18
):
1991
-
2003
.
53.
Xi
B
,
Veeranki
SP
,
Zhao
M
,
Ma
C
,
Yan
Y
,
Mi
J
.
Relationship of alcohol consumption to all-cause, cardiovascular, and cancer-related mortality in U.S. adults
.
J Am Coll Cardiol
.
2017
;
70
(
8
):
913
-
922
.
54.
Di Castelnuovo
A
,
Costanzo
S
,
Bagnardi
V
,
Donati
MB
,
Iacoviello
L
,
de Gaetano
G
.
Alcohol dosing and total mortality in men and women: an updated meta-analysis of 34 prospective studies
.
Arch Intern Med
.
2006
;
166
(
22
):
2437
-
2445
.
55.
Ronksley
PE
,
Brien
SE
,
Turner
BJ
,
Mukamal
KJ
,
Ghali
WA
.
Association of alcohol consumption with selected cardiovascular disease outcomes: a systematic review and meta-analysis
.
BMJ
.
2011
;
342
:
d671
.
56.
Behrens
G
,
Leitzmann
MF
,
Sandin
S
, et al
.
The association between alcohol consumption and mortality: the Swedish women's lifestyle and health study
.
Eur J Epidemiol
.
2011
;
26
(
2
):
81
-
90
.
57.
Day
E
,
Rudd
JHF
.
Alcohol use disorders and the heart
.
Addiction
.
2019
;
114
(
9
):
1670
-
1678
.
58.
Goel
S
,
Sharma
A
,
Garg
A
.
Effect of alcohol consumption on cardiovascular health
.
Curr Cardiol Rep
.
2018
;
20
(
4
):
19
.
59.
Fernandez-Sola
J
.
Cardiovascular risks and benefits of moderate and heavy alcohol consumption
.
Nat Rev Cardiol
.
2015
;
12
(
10
):
576
-
587
.
60.
O'Keefe
EL
,
DiNicolantonio
JJ
,
O'Keefe
JH
,
Lavie
CJ
.
Alcohol and CV health: Jekyll and Hyde J-curves
.
Prog Cardiovasc Dis
.
2018
;
61
(
1
):
68
-
75
.
61.
Lee
IM
,
Shiroma
EJ
,
Lobelo
F
, et al
.
Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy
.
Lancet
.
2012
;
380
(
9838
):
219
-
229
.
62.
Lee
IM
,
Sesso
HD
,
Oguma
Y
,
Paffenbarger
RS
.
The "weekend warrior" and risk of mortality
.
Am J Epidemiol
.
2004
;
160
(
7
):
636
-
641
.
63.
O'Donovan
G
,
Lee
IM
,
Hamer
M
,
Stamatakis
E
.
Association of "Weekend Warrior" and other leisure time physical activity patterns with risks for all-cause, cardiovascular disease, and cancer mortality
.
JAMA Intern Med
.
2017
;
177
(
3
):
335
-
342
.
64.
Scott
JM
,
Li
N
,
Liu
Q
, et al
.
Association of exercise with mortality in adult survivors of childhood cancer
.
JAMA Oncol
.
2018
;
4
(
10
):
1352
-
1358
.
65.
Arem
H
,
Moore
SC
,
Patel
A
, et al
.
Leisure time physical activity and mortality: a detailed pooled analysis of the dose-response relationship
.
JAMA Intern Med
.
2015
;
175
(
6
):
959
-
967
.
66.
Lee
DH
,
Rezende
LFM
,
Ferrari
G
, et al
.
Physical activity and all-cause and cause-specific mortality: assessing the impact of reverse causation and measurement error in two large prospective cohorts
.
Eur J Epidemiol
.
2021
;
36
(
3
):
275
-
285
.
67.
O'Keefe
JH
,
Patil
HR
,
Lavie
CJ
,
Magalski
A
,
Vogel
RA
,
McCullough
PA
.
Potential adverse cardiovascular effects from excessive endurance exercise
.
Mayo Clin Proc
.
2012
;
87
(
6
):
587
-
595
.
68.
Filippidis
FT
,
Agaku
IT
,
Vardavas
CI
.
Geographic variation and socio-demographic determinants of the co-occurrence of risky health behaviours in 27 European Union member states
.
J Public Health
.
2016
;
38
(
2
):
e13
-
20
.
69.
Cui
Y
,
Forget
EL
,
Torabi
M
,
Oguzoglu
U
,
Ohinmaa
A
,
Zhu
Y
.
Health-related quality of life and economic burden to smoking behaviour among Canadians
.
Can J Public Health
.
2019
;
110
(
5
):
533
-
541
.
70.
Heikkinen
H
,
Jallinoja
P
,
Saarni
SI
,
Patja
K
.
The impact of smoking on health-related and overall quality of life: a general population survey in Finland
.
Nicotine Tob Res
.
2008
;
10
(
7
):
1199
-
1207
.
71.
Tillmann
M
,
Silcock
J
.
A comparison of smokers' and ex-smokers' health-related quality of life
.
J Public Health Med
.
1997
;
19
(
3
):
268
-
273
.
72.
Srivastava
S
,
Bhatia
MS
.
Quality of life as an outcome measure in the treatment of alcohol dependence
.
Ind Psychiatry J
.
2013
;
22
(
1
):
41
-
46
.
73.
Bize
R
,
Johnson
JA
,
Plotnikoff
RC
.
Physical activity level and health-related quality of life in the general adult population: a systematic review
.
Prev Med
.
2007
;
45
(
6
):
401
-
415
.
74.
Gillison
FB
,
Skevington
SM
,
Sato
A
,
Standage
M
,
Evangelidou
S
.
The effects of exercise interventions on quality of life in clinical and healthy populations; a meta-analysis
.
Soc Sci Med
.
2009
;
68
(
9
):
1700
-
1710
.

Author notes

Data will be available upon reasonable request from the corresponding author, Smita Bhatia (smitabhatia@uabmc.edu).

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

Supplemental data