QoL and Patients' Care

Investigating the temporal course, relevance and risk factors of fatigue over 5 years: a prospective study among patients receiving allogeneic HSCT

Abstract

Although allogeneic hematopoietic stem cell transplantation (HSCT) features severe physical and psychological strain, no previous study has prospectively investigated fatigue beyond 3 years after transplantation. We investigated the temporal course of fatigue over 5 years, compared patients with the general population (GP) and tested for treatment- and complication-related risk factors. Patients were assessed before conditioning (T0, N=239) and at 100-day (T1, N=150), 1-year (T2, N=102) and 5-year (T3, N=45) follow-up. We measured fatigue with the Multidimensional Fatigue Inventory-20. Patients were compared with the GP at T0 and at T3. Global fatigue increased from T0 to T1 (t=3.85, P<0.001), decreased from T1 to T2 (t=−2. 92, P=0.004) and then remained stable (t=0.45, P=0.656). No difference in global fatigue was found between T0 and T3 (t=0.68, P=0.497). Compared with the GP, patients showed higher global fatigue at T0 (t=−6.02, P<0.001) and T3 (t=−2.50, P=0.014). These differences reached meaningful effect sizes (d0.5). Acute and chronic GvHD predicted global fatigue at T1 (γ=0.34, P=0.006) and T2 (γ=0.38, P=0.010), respectively. To conclude, fatigue among allogeneic HSCT patients improves with time, finally returning to pretransplantation levels. However, even after 5 years, the difference from the GP remains relevant. Patients with GvHD are at risk for increased fatigue.

Introduction

Patients undergoing allogeneic hematopoietic stem cell transplantation (HSCT) are confronted with a range of strongly adverse events, including conditioning, immunosuppressive medication and life-threatening immune reactions, such as GvHD.1, 2, 3, 4 A major problem most likely resulting from this toxicity is fatigue,1 a multidimensional and subjective feeling of exhaustion that adversely affects quality of life (QoL).5 Across reviews, fatigue is shown to be the most prominent, severe and persistent issue among HSCT patients.1, 6

According to previous studies, fatigue increases between pre and post HSCT and then decreases with time.7, 8, 9, 10, 11, 12, 13, 14, 15 After the first year, however, fatigue remains stable.11, 13 Furthermore, fatigue levels in patients are higher than in healthy comparison groups up to 10 years after HSCT.13, 16, 17, 18, 19, 20 Two studies showed that the toxicity of treatment did not have an impact on fatigue levels,20, 21 whereas Prieto et al.22 found such an influence. Chronic GvHD was shown to have a negative impact on fatigue symptoms,14 whereas physical functioning and QoL were adversely affected by both GvHD types.23, 24

To our knowledge, 12 studies provided longitudinal data on fatigue in allogeneic and/or autologous HSCT patients so far.7, 8, 9, 10, 11, 12, 13, 15, 20, 21, 22, 23 However, interpretation of results is limited: for example, few studies assessed fatigue beyond the first year after HSCT.11, 12, 13 Furthermore, most studies had small baseline samples of N100.7, 8, 9, 10, 12, 15, 20, 23 To date, only four longitudinal studies exclusively investigated allogeneic HSCT patients.11, 13, 15, 23 Only one study presented trajectories for the different dimensions of fatigue.10

To our knowledge, we present the first longitudinal data on fatigue among HSCT patients beyond 3 years after transplantation. Our sample is relatively large and homogenous and provides detailed medical data obtained from the medical records. Finally, we present fatigue in its different dimensions. We aimed to answer the following questions:

  1. 1

    What is the long-term temporal course of fatigue, from before HSCT to 5-year follow-up?

  2. 2

    Do levels of fatigue differ between HSCT patients and the general population (GP), and if so, are these effects meaningful?

  3. 3

    Do treatment- and complication-related factors predict the level of fatigue before and after allogeneic HSCT?

Based on previous research, we hypothesized fatigue to increase between pre and post HSCT, to decrease within the first year post-HSCT and then to remain stable. We further assumed that patients show higher fatigue than the GP 5 years after HSCT. We finally expected GvHD to negatively influence fatigue levels. Our results could be very important for practitioners, enabling them to estimate when and for whom medical or psychological interventions addressing fatigue are most important.

Patients and methods

Sample and procedure

Data were collected within a multicenter study at six university medical centers in Germany investigating cognitive impairments in patients with allogeneic HSCT.25 Assessment took place before HSCT conditioning (T0) and 100 days (T1), 1 year (T2) and 5 years (T3) after HSCT. At first, patients were contacted personally or by phone and asked to participate. Interested and eligible patients (at least 18 years old, suffering from a hematological disease and scheduled for allogeneic HSCT) were sent a set of self-report questionnaires. Patients filled out the questionnaires at home and brought them to the individual assessments that were performed at the respective institutions. This procedure was repeated at the three follow-ups. The research was approved by the local ethics committees or the institutional review boards. The file number of the main approval by the medical association of Hamburg is 2389. Prior to participation, all patients provided written informed consent. Study assessment was carried out from 6 June 2005 to 11 June 2012.

Measures

Medical variables

Illness- and treatment-related information was obtained from the medical records and transferred from the respective test leader. Acute and chronic GvHD was defined according to the grading systems of Glucksberg and Shulman, respectively. Clinically significant acute GvHD was defined from grade 2. Myelotoxicity in the course of conditioning was categorized according to the guidelines of the European Group for Blood and Marrow Transplantation26 into full-intensity conditioning vs reduced intensity conditioning (including non-myeloablative).

Fatigue

The Multidimensional Fatigue Inventory (MFI-20)27 has been applied to cancer patients28 and validated in German.29 The 20 items encompass the subscales General Fatigue (GF), Physical Fatigue (PF), Reduced Activity (RA), Reduced Motivation (RM) and Mental Fatigue (MF). Each item is rated on a five-point scale, with higher values indicating higher fatigue levels. The score across all variables has been proposed as a valid indicator for Global Fatigue (GloF).29, 30 In our study, internal consistency (Cronbach’s alpha) for GloF ranged between 0.92 and 0.95.

Depression

Depressive symptoms were assessed with the depression scale of the validated German version31 of the Hospital Anxiety and Depression Scale (HADS).32 The scale consists of seven statements with four response options each, with higher values indicating more depressive symptoms. In our study, internal consistency (Cronbach’s alpha) ranged between 0.73 and 0.89.

Comparison group

The comparison groups (in the following: GP) were obtained out of the original data set (N=2037) of a German validation study of the MFI-20.29 This study used a random-route technique and represents the non-institutionalized adult population in Germany.

Statistical analyses

We first provided descriptive statistics for all relevant variables for the baseline sample, the patients at T3 and the drop-outs. Drop-outs were then compared with the patients at T3 via t-tests for continuous variables or chi-square tests for binominal variables.

To investigate the impact of drop-outs on fatigue, we applied pattern mixture modeling, using a random intercept model with time as fixed factor and global fatigue as the dependent variable. Dummy variables indicating drop-out at any time point (P1), drop-out after T0 (P2), drop-out after T1 (P3) and drop-out after T2 (P4) and its respective interaction terms with time were included one after another. None of the patterns or interactions yielded significance (P1: P=0.84; P1 × time: P=0.72; P2: P=0.18; P2 × time: P=0.87; P3: P=0.81; P3 × time: P=0.07; P4: P=0.59; P4 × time: P=0.93). This implies that the results drawn from the available patients can be seen as relatively valid despite the drop-out rate.

The temporal course of fatigue is presented graphically indicating means and s.d. bars. Tests of differences in fatigue levels between time points were calculated with multilevel modeling, using random intercept models with time as fixed factor.

Patients and the GP were compared in fatigue levels via t-tests at T0 and T3. Comparison groups were matched by age and gender, that is, one comparison person identical in age and gender was assigned to every patient at T0 and T3, respectively.

To identify predictors, we calculated cross-sectional multiple regression analyses at each time point with GloF, that is, all items, as dependent variable. Owing to the need for parsimony in regression models and the small sample sizes at later time points, we restricted our number of predictors to those that were most distinctive for allogeneic HSCT, that is, acute and chronic GvHD and toxicity of conditioning. Based on previous results,22, 29, 33 all regression analyses were controlled for age, gender and depressive symptoms. The variables in each regression model are presented in Table 4.

To indicate the relevance of group differences and changes between time points, effect sizes were calculated following Cohen34 and Lakens.35 Correlations between time points for calculating effect sizes regarding changes over time were obtained by t-tests for paired samples. We used a value of d=0.50 to indicate whether effects were meaningful.36 Alpha was two sided and set at 0.05. Missing data of the MFI-20 were low (T0: 1–2%; T1: 3–5%; T2: 1–2%; T3: 2–4%). Listwise exclusion was used for the regression models. All analyses were performed with SPSS,37 the figure was created with R.38

Results

Sample characteristics

Two hundred and thirty-nine of the 394 eligible patients participated at baseline, leading to a T0 response rate of 61%. Reasons for non-responders (n=155) were lack of interest (35%), psychological (34%) or physical (31%) burden. One hundred and fifty patients participated at T1, 102 at T2 and 45 at T3; response rates related to the respective assessment point before and excluding those who deceased were 74% (T1), 75% (T2) and 65% (T3). Important drop-out reasons for the 194 drop-outs throughout the study were death (38%), being too ill (18%) and psychological burden (7%). Drop-outs received significantly more frequent pretreatment with chemotherapy and autologous HSCT than the completers at T3 (Table 1).

Table 1 Sample characteristics before conditioning, 5 years after HSCT and for drop-outs (if not else noted: raw values, rounded valid percentages in parentheses)

Temporal course of fatigue

The temporal course delineated in Figure 1 largely corresponded with our hypotheses: Most scale scores significantly increased from T0 to T1, significantly decreased from T1 to T2 but did not significantly change between T2 and T3 (Table 2).

Figure 1
figure1

Temporal course of fatigue levels across assessment points. Higher values indicate higher fatigue. Data points indicate means (range: 1–5), error bars s.d.

Table 2 Tests of differences in fatigue levels between time points

Comparison between patients and the GP

As hypothesized, patients experienced higher fatigue levels compared with GP 5 years post-HSCT (Table 3). Group effects were also found before HSCT. At both time points, differences in GF, PF and GloF reached effect sizes considered meaningful (d0.50).

Table 3 Tests of mean difference in fatigue levels between patients and the general population (matched by age and gender) before conditioning (T0) and 5 years after HSCT (T3)

Predictors of fatigue

As hypothesized, GvHD negatively influenced fatigue levels (Table 4). In detail, when controlled for depressive symptoms, age and gender, acute GvHD and chronic GvHD predicted fatigue at T1 and T2, respectively. No impact was found for the variable indicating myelotoxicity of conditioning.

Table 4 Multiple regression analyses for severity of Global Fatigue

Discussion

Main findings

Fatigue increased after allogeneic transplantation but improved within the first year after HSCT to levels comparable to baseline values. In the long-term, however, fatigue remained stable on a level that was significantly above population norms. Patients with acute and chronic GvHD were shown to be at risk for elevated fatigue. On the contrary, intensity of conditioning regimen did not influence fatigue levels.

Temporal course of fatigue

The increase between pre- and post-HSCT and the decrease between 100 days and 1 year after HSCT in most fatigue dimensions is largely in line with previous results.7, 8, 9, 10, 11, 12, 13, 15 Our findings also support studies showing fatigue to remain stable after the first year following HSCT.11, 13 Five years after HSCT, all scales did return to levels comparable to the respective baseline values. As an exception, motivation decreased (as RM increased) between these time points, reaching an almost meaningful effect (d=0.49). In this context, only one previous study10 presented trajectories of different fatigue dimensions, which were shown to be similar within the first 14 days after HSCT. However, our results could show that, in the long-term, trajectories of certain fatigue dimensions such as RM differ from others, which highlights the need for multidimensional assessment. Furthermore, as most previous studies partly or exclusively focused on patients with autologous HSCT, our findings provide important results for the long-term course of fatigue among patients undergoing allogeneic HSCT.

Comparison between patients and the GP

The significant group differences between patients and GP in the long term is in line with previous literature.13, 16, 17, 18, 19 The meaningful effect sizes in GF, PF and GloF correspond with a previous study by Andrykowski et al.17

Importantly, patients differed from GP even before the transplantation, which validates results of cross-sectional studies showing lower functioning and QoL compared with norms pre-HSCT.39, 40 Looking at the medical history of our patients, it can be assumed that these high levels of fatigue at baseline reflect the adverse effect of the amount of treatments that patients had already undergone before allogeneic HSCT (80% chemotherapy, 3% TBI, 11% long-term therapy and 21% autologous HSCT). Surprisingly and as an exception, patients showed higher levels of motivation (as they scored ‘better’ in RM) than GP before HSCT, an effect which vanished 5 years after HSCT. This result indicates that the decrease between pre-HSCT and 5-year follow-up in the motivation dimension of fatigue (see section above) is a return to an average level. Looking at the items of this scale (for example, to want to do nice things, to have lots of plans), this above-average ‘motivation to live’ before HSCT might be an expression of a high appreciation of life in the face of possible death owing to the treatment.

Predictors of fatigue

We did not find any influence of myelotoxicity on fatigue. These finding corresponds with the studies of Brandberg et al.21 and Hann et al.20 but is contrary to the findings of Prieto et al.22 However, this inconsistency could be explained by the different operationalization of myelotoxicity across the four studies (marrow-supported high-dose chemotherapy vs tailored therapy21; Bearman Toxicity Scale22; three specific conditioning regimens20; guidelines of the EBMT in our study). The only stable effect on fatigue was shown for depressive symptoms, which is in line with previous findings.22, 33 One explanation of this effect could be item overlap. In that context, Smets et al.28 claimed that, compared with other depression scales, the HADS is advantageous in fatigue studies as it does not directly refer to tiredness or sleepiness and only the item ‘I feel as if I am slowed down’ was assumed to overlap with depression. However, they showed that the overall correlation between the HADS depression scale and the MFI remained high even when excluding this item. Furthermore, Jacobsen et al.33 noted that correlations between fatigue and depression were also high when depression is operationalized as depressive mood. Such results suggest that the association between these two constructs cannot be explained by methodological issues alone. This in turn poses the question of any causal relationship: To date, however, there is no consensus about whether fatigue is caused by depression, vice versa or whether there is no causal relationship but an underlying mechanism.33 Acute and chronic GvHD predicted fatigue at one time point, respectively. That implies that both disease types are independent but only temporary predictors of fatigue, an assumption that is confirmed by two studies measuring the effect of GvHD on physical functioning and QoL.23, 24 However, it remains unclear whether the effects of acute and chronic GvHD on fatigue reflect the impact of the complications themselves or the immediate effect of the (for example, immunosuppressive) treatment of these complications. Contrary to our results, previous studies showed an impact of chronic GvHD on fatigue and other QoL measures >2 years following HSCT.14, 41, 42 Thus, given a statistical trend of the effect of chronic GvHD on fatigue 5 years after HSCT (P=0.09), statistical significance might have been missed owing to insufficient test power.

Strengths and limitations

To our knowledge, our study was the first to prospectively assess fatigue among HSCT patients beyond 3 years after transplantation. Furthermore, we had a relatively large and homogenous sample, provided detailed medical data and assessed fatigue in its different dimensions. Therefore, our results can both verify and expand previous results at the interface between allogeneic HSCT and fatigue.

However, despite a large baseline sample (N=239), we had a substantial drop-out rate, which led to small sample sizes and therefore to reduced test power at later time points. We tried to statistically compensate for this problem by conducting multilevel modeling and cross-sectional regression analyses, with both enabling us to use information of all patients at each time point. Another approach to keep statistical power as high as possible was to restrict the number of predictors. Therefore, we solely included the most important control variables and variables distinctive for allogeneic HSCT. Nevertheless, especially 5 years after allogeneic HSCT, it is possible that predictors were not detected owing to insufficient test power.34

The drop-outs also complicate the interpretation of the fatigue levels: As more than a half of participants dropped out owing to death, physical or psychological problems, it is possible that it was only the very resilient patients who were kept in the study. This in turn could have led to an underestimation in fatigue levels at later time points. Furthermore, as 65% of the non-responders did not participate in our study owing to physical or psychological burden, this bias could also have occurred at baseline. Nevertheless, our patients were recruited within a multicenter study, an approach which improves generalizability43 and therefore might partly compensate for this participation bias. Second and more important, pattern mixture modeling revealed that drop-out patterns did not have a significant impact on fatigue levels and its trajectory. This result implies that the descriptive results drawn from the available patients can be seen as relatively valid despite the high drop-out rate. However, conclusions about levels of fatigue, especially at later time points, should only be drawn with caution. Owing to the lack of effect sizes for multilevel models, we calculated effect sizes analog to Cohen’s d for repeated measures,35 for which we used correlations of t-tests for paired samples. Thus effect sizes regarding changes between time points should be interpreted as an orientation guide.

Conclusions and implications

Although fatigue peaked 3 months after allogeneic HSCT, levels are also relevant pre-HSCT and in the long term. Therefore, regular assessment of fatigue and therapeutic approaches, for example, physical exercise,44 are necessary at time points that go beyond common psychosocial care. The impact of GvHD on fatigue shows that patients with this condition should be screened closely. Given the high motivation shortly before transplantation, this phenomenon could be used in psychological intervention techniques. For example, reminding patients about their will to live before HSCT could help them to better accept and adapt to long-term effects. Clinicians could inform patients that fatigue-related impairments are likely to return to baseline levels, a prospect which might calm patients in the acute phase of the treatment. Further prospective long-term studies are warranted to validate our results. Multicenter studies would help to enlarge baseline samples, which is particularly necessary given the high mortality rate among this specific population. To further investigate the relationship between myelotoxicity and fatigue, use of international toxicity indices and consideration of possibly moderating or mediating effects on fatigue would be crucial.

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Acknowledgements

This work was supported by the German foundation José Carreras Leukämie-Stiftung e.V. (grant nos. DJCLS R 04/29pf, DJCLS R 07/37pf and DJCLS R 10/38p). The funding source was not involved in any stage of the research process.

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Esser, P., Kuba, K., Mehnert, A. et al. Investigating the temporal course, relevance and risk factors of fatigue over 5 years: a prospective study among patients receiving allogeneic HSCT. Bone Marrow Transplant 52, 753–758 (2017). https://doi.org/10.1038/bmt.2016.344

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