Fatigue After Cancer And Cancer Survivors Confess Fears Of Recurrence
Overview
Cancer-related fatigue (CRF) and fear of cancer recurrence (FCR) are two prevalent issues faced by cancer survivors. However, the interplay between these concerns remains unclear, and it is uncertain if CRF and FCR influence one another over time.
This study utilized data from the American Cancer Society’s Study of Cancer Survivors-I (SCS-I), a national, prospective, longitudinal research project. Surveys were completed by 1,395 survivors of ten different cancer types at three time-points: 1.3 years (T1), 2.2 years (T2), and 8.8 years (T3) post-diagnosis. CRF was measured using the fatigue-inertia subscale of the Profile of Mood States, while FCR was assessed with the FCR subscale of the Cancer Problems in Living Scale. To examine the prospective associations between CRF and FCR, multiple group random intercepts cross-lagged panel models were employed.
Among younger participants (55 years or younger, n = 697), CRF at T1 and T2 significantly predicted FCR at T2 and T3, respectively. However, no reciprocal effects of FCR on subsequent CRF were found. For participants older than 55 years, no cross-lagged effects were detected.
In conclusion, CRF and FCR are significant side effects of cancer and its treatments. The findings suggest that CRF might be a predictor of FCR, indicating that early detection and management of CRF could potentially reduce the severity of FCR.
Introduction
By 2030, cancer diagnoses in Canada are projected to rise by 80% from 2005 levels, while the United States expects a 131% increase from 2019 levels. Despite this surge, advancements in screening, early detection, and treatment have led to decreased cancer mortality rates, with the current 5-year survival rate at 64%. However, extended survival often involves challenging treatments and debilitating symptoms such as cancer-related fatigue (CRF).
CRF is a complex condition characterized by persistent physical, emotional, and cognitive exhaustion that is disproportionate to recent activity and impairs daily functioning.
Approximately 52% of cancer patients experience CRF during their illness, significantly impacting their quality of life. The causes of CRF are not well understood but may include cancer treatments, the disease itself, genetic factors, and environmental influences. Moreover, CRF often continues long after the initial diagnosis and treatment, with about 52% of survivors reporting persistent fatigue years later.
Another prevalent issue among cancer survivors is the fear of cancer recurrence (FCR), affecting up to 79% of survivors. FCR, the fear that cancer will return or progress, can lead to prolonged emotional distress and a decreased quality of life. Both CRF and FCR are more common in younger patients and somewhat more prevalent in women. Lifestyle factors, such as smoking, also increase the risk of experiencing these symptoms.
The relationship between CRF and FCR remains poorly understood, with previous studies showing varying degrees of correlation. Anxiety before treatment, a factor related to FCR, predicts higher levels of CRF during and after treatment. Additionally, physical symptoms like pain can worsen FCR, suggesting that CRF might contribute to FCR. It is also possible that CRF and FCR influence each other through shared psychological processes like catastrophizing and anxiety vulnerability. Evidence from mindfulness interventions supports the idea that improved mindfulness skills can reduce both CRF and FCR.
This study aims to investigate the interplay between CRF and FCR over time. Specifically, it seeks to determine if CRF reported about a year after diagnosis is associated with increased FCR over time, if early FCR predicts higher CRF later, or if these issues mutually influence each other. Considering previous findings on the relationships between age, CRF, and FCR, this study will examine these associations in younger versus older survivors, controlling for gender and smoking status. The results could provide crucial insights into prioritizing interventions for managing cancer patients.
Method
The data for this study was sourced from the American Cancer Society’s Study on Cancer Survivors-I (SCS-I), a nationwide prospective longitudinal study. Participants completed surveys at three time points: Time 1 (T1, M = 1.3 years, SD = 0.32), Time 2 (T2, M = 2.2 years, SD = 0.34), and Time 3 (T3, M = 8.8 years, SD = 0.63) after their cancer diagnosis. At T1, 6,309 individuals participated, with retention rates of 80% at T2 and 70% at T3. Additional methodological details can be found elsewhere. The study received approval from Emory University’s Institutional Review Board and the University of Ottawa’s Research and Ethics Board.
Participants were recruited from 25 randomly selected cancer registries across the United States. Eligibility criteria included being over 18, diagnosed with one of the ten most common cancers (prostate, female breast, lung, colorectal, urinary bladder, non-Hodgkin lymphoma, skin melanoma, kidney, ovarian, or uterine cancer), having a SEER Summary Stage cancer diagnosis, residing in the state at diagnosis, and being diagnosed between April 2001 and March 2002. Exclusions were made for individuals unable to complete the survey, non-English or non-Spanish speakers, terminally ill patients, those with cancer recurrence, metastasis, or multiple cancers, and those with incomplete data across all three waves. This resulted in a final sample size of 1,395 participants.
Sociodemographic and medical variables collected at baseline included age, gender, race/ethnicity, family income, educational level, occupation, and cancer treatments. Cancer type and stage were verified using SEER registry data and baseline survey responses. Smoking status was evaluated at T3, with participants categorized as never, former, or current smokers, and a dichotomous variable indicating current versus non-smoker status.
Cancer-related fatigue (CRF) was assessed at all three time points using the Profile of Mood States-Short Form (POMS-SF) fatigue-inertia subscale, which has demonstrated good internal consistency, validity, and reliability. Participants rated their feelings of fatigue on a five-point scale over the past two weeks, with scores ranging from 0 to 20.
Fear of cancer recurrence (FCR) was measured using the Cancer Problems in Living Scale’s FCR subscale (CIPLS-FCR), which has good internal consistency and discriminant validity. Participants rated their concerns about cancer recurrence on a four-point Likert scale over the past 12 months, with scores ranging from 0 to 12. High FCR was classified for individuals with scores above 6 based on prior trajectory analysis.
Statistical Analysis
Frequencies for categorical variables and means and standard deviations for continuous variables across three waves were calculated. One-way ANOVAs with Bonferroni-corrected pairwise comparisons identified significant differences in CRF or FCR by sociodemographic and medical variables at each wave (p < 0.05).
A multiple group (MG) random intercepts cross-lagged panel model (RI-CLPM) was used to examine prospective associations between CRF and FCR, separating within- and between-person variances while accounting for individual differences. The MG-RI-CLPM comprises four elements: (1) random intercepts with constrained factor loadings, (2) within-unit fluctuations with measurement error variances set to zero, (3) lagged regressions between within-unit components, and (4) covariances for both between and within components. The grouping variable, based on median split self-reported age at T1 (0 = younger, 1 = older, n = 697 and 698, respectively), allowed variations in means, lagged regression coefficients, (residual) variances, and (residual) covariances across groups. Mplus Version 8.2 was used for the analysis, with default settings for the model estimator (maximum likelihood), maximum iterations (1000), and convergence criterion (0.500D-04). Fit was assessed using the comparative fit index (CFI), Tucker-Lewis index (TLI), normative fit index (NFI), and root-mean-square error of approximation (RMSEA), with good fit indicated by CFI, TLI, and NFI values ≥0.95 and RMSEA ≤0.06.
Result
In the analyzed sample, the mean age was 56.5 years (SD = 10.9, median = 55.1). The cohort was predominantly female (62.6%) and Non-Hispanic White (91.8%), with 70.3% having some college education. At the initial time point (T1), 76.6% were married, and 25.7% had annual family incomes below $40,000. The cancer types included breast (32.3%), prostate (20.6%), colorectal (13.3%), uterine (8.0%), skin melanoma (5.9%), NHL (5.4%), kidney (5.2%), ovarian (3.5%), lung (3.4%), and bladder (2.4%). Most participants had
localized cancers (70.5%), while some had regional (23.4%), distant (4.3%), or in situ (1.8%) cancers. Compared to other respondents, participants in this sample were younger (56.5 vs. 60.9 years), more often female (62.6% vs. 56.4%), Non-Hispanic White (91.8% vs. 83.6%), more educated (70.3% vs. 54.8%), married (76.7% vs. 68.1%), and more frequently diagnosed with breast (32.3% vs. 20.4%) and uterine (8.0% vs. 4.5%) cancers, but less often with lung (3.4% vs. 12.1%) or ovarian (3.5% vs. 7.0%) cancers. Rates for other cancers were similar (below 3%). This sample also had a higher incidence of localized cancers (70.5% vs. 55.8%).
Mean cancer-related fatigue (CRF) scores at T1, T2, and T3 were 5.2 (SD = 4.4), 5.2 (SD = 4.5), and 4.4 (SD = 4.5), respectively. The proportion of clinically fatigued participants was 34% (n = 475) at T1, 33% (n = 461) at T2, and 29.2% (n = 408) at T3. Clinical fatigue was most prevalent among bladder cancer survivors (50%), followed by lung (46.8%), NHL (42.1%), breast (37.3%), uterine (34.2%), kidney (33.3%), ovarian (32.7%), and colorectal (32.3%) cancer survivors. Prostate cancer survivors reported the lowest fatigue levels (26.5%).
Mean fear of cancer recurrence (FCR) scores at T1, T2, and T3 were 2.4 (SD = 1.9), 2.0 (SD = 1.8), and 2.0 (SD = 2.2), respectively. The proportion of participants with a CPILS-FCR score over 6 at T1, T2, and T3 was 3.9% (n = 54), 1.9% (n = 26), and 4.4% (n = 62), respectively. High FCR at T1 was most prevalent among NHL survivors (13.2%), followed by lung (8.5%), breast (5.1%), kidney (4.2%), and skin melanoma (3.6%) cancer survivors. High FCR rates for other cancers were below 3%.
Cancer-related fatigue (CRF) was higher among younger survivors (<55.1 years) at all three time points. Males reported higher CRF at T1, but females reported higher CRF at T2 and T3. CRF was consistently higher among those with lower household incomes and separated survivors compared to their married or widowed counterparts. Current smokers reported higher CRF levels than never or former smokers.
Fear of cancer recurrence (FCR) was higher among younger and female survivors at all three time points and was lowest among widowed survivors and those with in-situ cancers. Current smokers had higher FCR at T2 and T3 compared to never smokers.
CRF and FCR were positively and significantly correlated at all time points (T1: r = 0.31; T2: r = 0.33; T3: r = 0.33, all p < 0.001). The MG-RI-CLP model indicated good fit, supporting the hypothesis of a lagged effect of CRF on subsequent FCR for younger participants but not for older survivors. Higher CRF at T1 showed a trend toward predicting greater FCR at T2 (standardized coefficient = 0.18, p = 0.09), and higher CRF at T2 significantly predicted greater FCR at T3 (standardized coefficient = 0.16, p = 0.03). The hypothesis of FCR predicting subsequent CRF was not supported for any age group. Additional RI-CLPMs based on sex or smoking status did not achieve good fit (RMSEAs > 0.06).
Conclusion
Cancer-related fatigue (CRF) and fear of cancer recurrence (FCR) are prevalent and distressing consequences of cancer and its treatments. However, the interaction between these two conditions over time is not well understood. The primary objective of this study
was to investigate the longitudinal relationship between CRF and FCR in cancer patients. Specifically, the study aimed to determine if CRF leads to an increase in FCR, if FCR causes increased fatigue, or if there is a mutual influence between the two over time. The study also explored the potential moderating effects of age, sex, and smoking status on this relationship.
The findings indicated that CRF might contribute to FCR in younger cancer patients, with the relationship intensifying over time. However, there was no evidence to suggest that CRF influences FCR in survivors over 55 years old, and no significant moderating effects were found for gender or smoking status. The exacerbation of FCR in younger patients might be due to a lack of awareness about CRF, heightened hypervigilance, catastrophization, negative illness perceptions, or decreased self-efficacy as CRF persists. Younger patients, who are generally less experienced with physical symptoms associated with aging, may misinterpret fatigue and pain as cancer-related, leading to greater illness intrusiveness and FCR.
The study found that the effect of CRF on FCR was more pronounced from the second to the third time points, suggesting that patients might not be adequately informed about the potential persistence of CRF post-treatment. This lack of awareness could contribute to hypervigilance and catastrophization, further impacting FCR. Psychoeducation on the nature, prevalence, persistence, and management of CRF, along with information on recurrence signs, could help mitigate these effects.
Importantly, the study revealed that CRF predicted subsequent FCR, but not vice versa, underscoring the need for early detection and management of CRF. Despite clinical guidelines recommending regular CRF screening post-cancer diagnosis, these are not consistently implemented, leaving many patients undiagnosed and untreated.
Several limitations of the study were noted, including a sample that may not represent the general cancer population due to a higher proportion of female, non-Hispanic White, and married participants. Additionally, the scales used to measure CRF and FCR were limited in scope, and the data collection points were not equally spaced, preventing an examination of the relationship between CRF and FCR at diagnosis and treatment completion. The study’s statistical approach also did not account for differences in time between waves. The possibility of a “healthy survivor” bias was suggested, as those with lower levels of CRF and FCR might have been more likely to participate.
In conclusion, this exploratory study highlighted a modest effect of CRF on FCR in younger cancer survivors, but not in those over 55. The findings emphasize the importance of psychoeducation, early detection, and interventions for CRF, particularly in younger survivors, to potentially reduce long-term FCR. Future research should address the noted limitations and explore the impact of cancer type on the CRF-FCR relationship.
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