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Effect of Physical Condition on Outcomes in Transplant Patients: A Retrospective Data Analysis

Andres, Kayla MD1; Wayman, Brooke PT, MS, MHA2; Rodriguez, Tina RN, BSN, BMTCMN3; Kline, Margaret MS4; Haveman, Joshua BS5; Brower, Chelsea6; Williams, Stephanie F. MD, FACP7

Author Information
doi: 10.1097/01.REO.0000000000000215
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Stem cell transplantation is a potential curative procedure for many patients with hematologic malignancies. These patients because of age, comorbid medical conditions, and prior therapies can present in various physical conditions from good performance status to poor or frail.1 This may affect transplant outcomes in terms of survival and relapse-free survival.

Several meta-analyses have concluded that physical exercise is safe in patients with cancer during and after therapy.2–4 Liang et al3 concluded that the best time to start physical therapy in patients with a hematopoietic stem cell transplant is prior to transplantation. Several studies have shown exercise in the peritransplant period to improve quality of life, fatigue, and distress.3,5,6 Lakoski et al7 found a survival benefit for patients with a higher cardiopulmonary fitness at midlife in lung, prostate, and colon cancer. One small study on patients who underwent hematopoietic stem cell transplant found that a lower pretransplant cardiopulmonary fitness was associated with increased symptom burden, worse health-related quality of life, and increased risk of death.8 Other studies have shown an inverse relationship between physical activity and cancer-related death in patients with breast cancer.9 Very few studies have looked at performance status and exercise on hematopoietic stem cell transplant outcomes and survival.

Performance status, measured by the Karnofsky Performance Status (KPS) score, is required to be reported to our registry, the Center for International Blood and Marrow Transplant Research (CIBMTR). At our institution, a KPS of 70% or greater is considered a good performance status; however, patients with lower KPS scores will go on to transplant at the discretion of the transplant physician. Studies in advanced cancer and solid tumors have shown increased survival with a higher KPS (≥80).10,11 The relationship of KPS scores to survival outcomes in patients undergoing transplant is less clear. One study in patients with multiple myeloma undergoing transplant did not find any association between KPS and event-free survival,12 while another study in patients with multiple myeloma undergoing transplantation found that a KPS score less than 70% was associated with decreased survival.13 Studies in patients with an allogeneic transplant having a KPS score of 80 or less was associated with higher grade 3 and 4 toxicities, increased mortality, and increased relapse rate.14,15

There is little data on the relationship between KPS and exercise. One small randomized study by DeFor et al16 showed that those in the exercise arm with a KPS score of less than 90 were more likely to improve their KPS to more than 90 by day 100 posttransplant than those in the control arm with an initial KPS score of less than 90. For all KPS scores, there was no statistically significant difference in change in KPS between the exercise and control arms. From this small study we would expect patients with lower KPS scores to get the most benefit from an exercise program.

A component of our transplant program is a pretransplant evaluation with cancer rehabilitation specialists. Standard measures are obtained including the visual analog scales for pain and fatigue, Timed Up and Go, and distress thermometer. An exercise program is prescribed for the patient prior to admission as well as during hospitalization and discharge. At day 60 after transplant, these standard measures are reassessed. The objective of our study was to assess the relationship of measurable physical conditioning metrics to survival, progression-free survival, relapse rate, and transplant-related mortality.


Patient Selection

We reviewed the records of consecutive patients from the start of our transplant program in February 2013 through May 2018. We identified 212 patients who had 6 months of follow-up posttransplant. All patients 18 years and older who underwent a stem cell transplant for hematology malignancy with at least 6 months of posttransplant follow-up were included in our study. We excluded 2 patients who had 2 transplants during this time and 3 patients who had nonmalignant disease.

During the pretransplant evaluation with cancer rehabilitation specialists, standard measures were obtained, including the visual analog scales for pain and fatigue, Timed Up and Go, and distress thermometer. An exercise program was prescribed to the patients at the time of the pretransplant evaluation as well as during hospital admission and discharge. Each patient received the same exercise program, which was adapted from a study on high-intensity strength training in cancer survivors.17 The patients were asked to exercise for 30 minutes per day at a perceived exertion of 3 to 5 (moderate to hard).18 The recommended exercises included marching in place, standing bicep curls using a resistance band, standing up from sitting in a chair, arm circles, standing side leg raise, wall push-ups, horizontal shoulder abduction with a resistance band, standing toe raises, and sitting bicep curls using a resistance band. They were instructed to perform as many repetitions of each movement as they could in 45 seconds, rest for 15 seconds, and then move to the next exercise until they had completed all 9 movements. The patients were asked to complete 3 sets throughout the day for approximately 30 minutes of activity total. Modifications were given for patients if they needed it. For example, standing exercises were modified to sitting and lighter resistance bands were given for the exercises that involved a resistance band. The patients were seen during their admission for transplant by the physical therapy team who would reinforce the prescribed exercise program and work with the patients on any specific functional deficits they may have had. At day 60 posttransplant, the patients met with a cancer rehabilitation specialist and the functional and standard measures were reassessed. Figure 1 shows a timeline of our assessments.

Fig. 1.
Fig. 1.:
Timeline of evaluation. This figure is available in color online (

Baseline characteristics such as age, sex, disease, disease status at transplant, date of transplant, and type of transplant were recorded. Data were collected from each patient's pretransplant cancer rehabilitation evaluation and their 60-day posttransplant evaluation including their KPS, as well as their Timed Up and Go score, and their fatigue and distress thermometers. Outcome data including graft-versus-host disease (acute or chronic), survival, progression-free survival, time to relapse, and transplant-related mortality were obtained from the electronic medical record.

A visual analog scale was used to rate patients' pain on a scale of 1 to 10 cm. Patients were asked to rate their current pain (pain now), pain at its worst, and average pain at each assessment. A change in 3 cm was considered significant consistent with the findings of Lee.19

Patient fatigue was rated using a visual analog scale from 1 to 10 cm. Patients were asked to rate their current fatigue (fatigue now), fatigue at its worst, and average fatigue at each assessment. A change in 3 cm was considered significant.20

The NCCN distress thermometer was used to measure patients' distress on a scale of 1 to 10. A change of 3 was considered significant.

The Timed Up and Go test was performed to assess mobility. A score of more than 12 seconds was considered clinically significant.21,22

Patients were also assigned a KPS score by 1 of 3 physicians on their initial evaluation with the blood marrow transplant (BMT) team. Patients were then stratified into high performers, KPS greater than or equal to 80 (n = 91), and low performers, KPS less than or equal to 70 (n = 114). These cutoffs were determined by splitting the range of KPS scores to balance the sample size and are consistent with ranges used in previous studies.10,11 Scores for all patients ranged from 60 to 100.

Statistical Analysis

The 2 treatment groups compared in the study are the high and low performers. Data are described using summary statistics. Normally distributed quantitative data are shown as the mean ± SD, while nonnormally distributed data are shown as the median and the interquartile range (25th to 75th percentile). Nominal data are shown as a frequency and percentage. Paired t tests were performed for data with normal distributions and Wilcoxon signed rank tests were used for data with nonnormal distributions to determine whether there was a difference in the standard measures scores taken pretransplant versus 60 days posttransplant for pain and fatigue (current, at worst, and on average), Timed Up and Go, and the distress thermometer.

Log-rank tests were used to determine differences in survival and progression-free survival. A Cox proportional-hazards model was run to determine whether any factors influenced overall survival. χ2 tests were used to examine the proportions of high and low performers that relapsed and had transplant-related mortality.

χ2 or Fisher exact tests were used to determine whether significant changes in the standard measures taken pre- and posttransplant are related to overall survival, progressive-free survival, and transplant-related mortality.

Significance was assessed at P < .05. Statistical analyses were performed using SAS version 9.4 (SAS Institute Inc, Cary, North Carolina).


There were 207 patients who met our entry criteria. General demographic and clinical information describing the 2 groups is shown in Table 1. The majority of subjects in both groups were male, and the average age in both groups was more than 55 years. A total of 40 patients had died at the time data were collected.

TABLE 1 - Demographic and Clinical Characteristics of High-Performance and Low-Performance Patientsa
Variable Performance Group
High (n = 91) Low (n = 114)
Age 57.1 ± 14.1 60.5 ± 10.6
Male 61 (67.0) 69 (60.5)
Female 30 (33.0) 45 (39.5)
Type of transplant
Allogeneic 25 (27.5) 42 (36.8)
Autologous 66 (72.5) 72 (63.2)
Type of disease
Leukemia 23 (25.3) 36 (31.6)
Plasma 36 (39.5) 51 (44.7)
NHL/lymphomas 32 (35.2) 27 (23.7)
Disease status at transplant
CR 36 (40.0) 47 (42.0)
PIF 8 (8.9) 7 (6.2)
PR 24 (26.7) 30 (26.8)
REL 7 (7.8) 6 (5.4)
Stable 9 (10.0) 7 (6.2)
Not responding 6 (6.6) 15 (13.4)
HCT Comorbidity Index
≤3 63 (69.2) 70 (61.4)
>3 28 (30.8) 44 (38.6)
Abbreviations: CR, complete remission; HCT, Hematopoietic Cell Transplantation; NHL, non-Hodgkin's lymphoma; PIF, primary induction failure; PR, partial response; REL, relapse.
aHigh-performance patients had a Karnofsky Performance Status score ≥80; low-performance patients had a Karnofsky Performance Status score ≤70; age is presented as the mean ± SD, while the nominal data are listed as the count, with the percent in parentheses.

There were statistically significant decreases in pain, fatigue, Timed Up and Go, and distress posttransplant compared with pretransplant (Table 2). These differences were not statistically different between the low- and high-performance groups (Table 3).

TABLE 2 - Comparison of Pre- to Posttransplant Scores for Standard Measuresa
Standard Measure Pretransplant Score
(n = 207)
Posttransplant Score
(n = 207)
P Value
Pain, current 1.0 [0.0-3.0] 0.0 [0.0-2.0] .0013
Pain, at worst 5.13 ± 3.32 4.14 ± 3.20 <.0001
Pain, on average 2.95 ± 2.42 2.29 ± 2.11 <.0001
Fatigue, current 2.83 ± 2.24 2.15 ± 2.11 .0004
Fatigue, at worst 6.73 ± 2.46 5.80 ± 2.60 <.0001
Fatigue, on average 3.94 ± 1.95 3.16 ± 1.91 <.0001
Timed Up and Go 8.26 [6.95-10.52] 8.08 [6.67-9.92] .0031
Distress thermometer 3.07 ± 2.50 1.73 ± 2.04 <.0001
aNormally distributed measures represented as mean ± standard deviation and nonnormal distributions shown as the median with the interquartile range in brackets (25th to 75th percentiles).

TABLE 3 - Comparison of Pre/Posttransplant Differences for Standard Measures Between High-Performance and Low-Performance Patientsa
Change in Standard Measure
(Pretransplant to Posttransplant)
High Performers
(n = 91)
Low Performers
(n = 114)
P Value
Pain, current −0.52 ± 1.86 −0.42 ± 2.46 .7594
Pain, at worst −1.33 ± 3.45 −0.71 ± 3.49 .2061
Pain, on average −0.68 ± 1.87 −0.63 ± 2.03 .8571
Fatigue, current −0.65 ± 2.81 −0.61 ± 2.52 .2741
Fatigue, at worst −0.64 ± 2.97 −1.11 ± 3.09 .2741
Fatigue, on average −0.58 ± 2.33 −0.85 ± 2.14 .3921
Timed Up and Go −0.60 ± 1.73 −0.43 ± 3.51 .6558
Distress thermometer −1.29 ± 2.31 −1.38 ± 2.39 .7679
aHigh-performance patients had a Karnofsky Performance Status score ≥80; low-performance patients had a Karnofsky Performance Status score ≤70.

There was no significant difference in survival benefit between high performers and low performers (Figure 2). We also did not find a statistically significant difference in progression-free survival (P = .840) or relapse rate (P = .489) between high performers and low performers.

Fig. 2.
Fig. 2.:
Kaplan-Meier curve of overall survival comparing high-performance and low-performance patients. This figure is available in color online (

However, when using the dependent variable of overall survival in the Cox model, when controlling for transplant type, high performers had less than half the hazard of dying compared with low performers (hazard ratio: 0.48; 95% confidence interval: 0.24-0.98; P = .042). Additionally, type of transplant affected overall survival with autologous transplant patients living longer (P = .0002) than allogeneic transplant patients. The Hematopoietic Cell Transplantation Comorbidity Index (HCT-CI) did not influence overall survival (P = .219).

Patients with a clinically significant change in their average fatigue score had a lower proportion who died compared with those without a significant change (P = .033). However, a clinically significant change in any of the other standard measures (eg, current fatigue, worst fatigue, pain, distress, and Timed Up and Go) was not associated with a statistically significant effect upon overall survival. Additionally, a clinically significant change in any of the standard measures was not associated with a statistically significant difference in progression-free survival.

A clinically significant change in current or average fatigue was associated with a significantly lower proportion of people with transplant-related mortality (P = .036 and P = .001, respectively). Significant changes in worst fatigue, pain, distress, and Timed Up and Go were not associated with any transplant-related mortality benefit.


Our finding of improved standard measures 60 days after transplant is somewhat different from previous findings. Esser et al23 looked at the temporal course of fatigue in patients who underwent allogeneic hematopoietic stem cell transplant and found fatigue worsens after transplant but improves to baseline levels around 12 months after transplant. Anderson et al24 found fatigue was the worst at white count nadir, improved 30 days after transplant, but not back to baseline. This same study showed improved pain 30 days after transplant compared with baseline, which is consistent with our findings. Another study by Hacker et al25 found patients who underwent hematopoietic stem cell transplant experienced increased fatigue and poorer quality of life. However, exercise would be expected to improve fatigue.3,5 The effect of exercise on pain in patients with cancer is not well studied, although a small randomized control trial on patients with breast cancer did find a positive association with pain and exercise.26,27 We suspect that participation in exercise in the peritransplant period improved pain outcomes. Our outcomes of improved distress are consistent with the findings of Wiskemann et al.5 Both low performers and high performers had the same intervention of a standardized exercise plan, which may explain why improvement in standard measures was seen in both groups regardless of performance status.

When controlling for transplant type we did find a survival advantage between higher performers and low performers. While this difference was not statistically significant on the univariate analysis, we suspect with longer follow-up time high performers would have statistically higher survival rates compared with low performers (see Figure 2). Wingard et al28 did not find any survival benefit between patients who exercised and those who did not at 180 days on secondary analysis of the Blood and Marrow Transplant Clinical Trials Network (BMT CTN). Another secondary analysis of the BMT CTN by Wood et al29 found that patient-reported outcomes provided prognostic information in hematopoietic cell transplant but did not find KPS to be associated with survival outcomes. They did acknowledge there was a healthier-than-average population participating in their study.

One single center study at a Canadian transplant center found KPS greater than or equal to 90 as a predictor of nonrelapse mortality and overall survival in patients who underwent allogeneic transplant compared with those with a KPS of less than 90.30 This same study did not find that HCT-CI significantly predicted nonrelapse mortality or overall survival.30 Our study is consistent with these findings, as when controlling for transplant-type high performers had half the risk of dying compared with low performers, and the HCT-CI did not influence mortality. Wingard et al28 hypothesized that physical function exerts a more powerful influence on survival than engagement in exercise, given the considerable variability in the level of exercise at each level of physical function. Our results seem to be consistent with this hypothesis; however, we did not measure engagement in exercise.

A significant improvement in fatigue after transplant was associated with improved survival and reduced transplant-related mortality. Wood et al29 found that patient-reported outcomes prior to allogeneic transplant provided prognostic information using the 36-item short form survey (SF-36) physical component score. Certainly, fatigue can influence the physical component score of the SF-36 and it is possible fatigue could be a marker of transplant outcomes.

It is worth noting that KPS score is sometimes criticized for being a subjective measure with significant variability among providers assigning KPS scores. We kept a KPS description chart at each physician's workstation to minimize differences between our 3 transplant physicians.

Some limitations to our study include the patients were not supervised in their physical activity, and adherence to the prescribed regimen is unknown. Each patient received the same exercise program, and increasingly literature supports an individualized exercise program to optimize exercise training.31–33 Unfortunately, our institution did not have the resources to prescribe individualized exercise programs at the time of initiation. Further studies, including a randomized control trial of a prescribed and individualized exercise program with monitoring, would help to further delineate whether it is our exercise program or the underlying physical condition that predicts improvement in survival and standard measure posthematopoietic stem cell transplant. Assessing the standard measures at more frequent intervals may also be insightful for the peritransplant course of rehabilitation.


Our study demonstrated that our patients have better posttransplant standard measures regardless of initial performance status. Improvement of fatigue posttransplant may be an important marker of better transplant outcomes. Our data suggest that patients with a better pretransplant performance status have better overall survival. Our data support that further studies on our rehabilitation program are feasible and warranted. Based on our results we will be developing a more proactive rehabilitation program prior to transplant to see whether this can improve standard measures and overall survival further.


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cancer; fatigue; Karnofsky Performance Status

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