Behavioral Medicine

ISSN: 0896-4289 (Print) 1940-4026 (Online) Journal homepage: http://www.tandfonline.com/loi/vbmd20

Correlated and Coupled Trajectories of CancerRelated Worries and Depressive Symptoms among Long-Term Cancer Survivors George Kypriotakis, Gary T. Deimling, Andrea M. Piccinin & Scott M. Hofer To cite this article: George Kypriotakis, Gary T. Deimling, Andrea M. Piccinin & Scott M. Hofer (2014): Correlated and Coupled Trajectories of Cancer-Related Worries and Depressive Symptoms among Long-Term Cancer Survivors, Behavioral Medicine, DOI: 10.1080/08964289.2014.949216 To link to this article: http://dx.doi.org/10.1080/08964289.2014.949216

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Date: 05 November 2015, At: 13:11

BEHAVIORAL MEDICINE, 0: 1–11, 2014 Copyright Ó Taylor & Francis Group, LLC ISSN: 0896-4289 print / 1940-4026 online DOI: 10.1080/08964289.2014.949216

Correlated and Coupled Trajectories of CancerRelated Worries and Depressive Symptoms among Long-Term Cancer Survivors George Kypriotakis

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The University of Texas M. D. Anderson Cancer Center

Gary T. Deimling Case Western Reserve University

Andrea M. Piccinin, and Scott M. Hofer University of Victoria

The quality of life over time of long-term survivors has become an important part of both cancer and aging research. This paper examines individual differences in trajectories of cancerrelated worries and depressive symptoms of 179 participants who completed four waves of annual interviews. Cancer-related worries were significantly associated with both initial level and trajectories of depressive symptoms. In a parallel process growth curve model, the initial level of depressive symptoms was significantly correlated with both the initial level and rate of change in cancer-related worry over time. Our findings indicate that cancer survivors are never completely removed from cancer’s threats to quality of life, even as they survive into later life. These findings also suggest that older adults face the dual vulnerability of aging with its growing number of comorbidities and related symptoms along with the vulnerability conferred by cancer-related sequelae and the possibility of recurrence or new cancers.

Keywords: cancer survivors, cancer worry, depression, long-term, quality of life INTRODUCTION Cancer can be viewed primarily as a disease of older adults because most new cancers occur in people over 65 years of age. As the incidence of cancer increases dramatically after age 60,1,2 aging is one of the most significant risk factors in developing cancer.3 With the proportion of the U.S. population over age 65 increasing rapidly, the numbers of older individuals who will be diagnosed with cancer is also likely to grow dramatically in the foreseeable future. Of the more than 10 million cancer survivors, 60% are over 65 years of age and more than 16% of U.S4,5 adults aged 65 or older are cancer survivors. Given these large numbers and the potential vulnerability of older adults facing a variety of chronic conditions,5 older cancer survivors have become an Address correspondence to George Kypriotakis, UT M.D. Anderson Cancer Center, Behavioral Science, 1155 Pressler Road, Houston, TX 77030. E-mail: [email protected]

especially important group to study with both health care needs and financial implications.6 As Blank and Bellizzi7 note in their discussion of aging and cancer, there is a “mixture of both positive and negative trajectories in different aspects of their [survivor] lives” and soon after diagnosis “individuals begin to vary greatly from each other in patterns of psychological adjustment”(p.2570). Their comments point to the need for research that can document the impact of cancer on older adults as they age and become temporally distant from the illness. It also points to a need for research that can identify the factors that predict these diverse trajectories, which is the primary aim of the research reported here.

LONG-TERM SURVIVORSHIP Research has already documented that cancer survivors continue to experience diminished quality of life (QOL) from physiological problems, psychological distress, and

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KYPRIOTAKIS ET AL.

social life disruption, even decades after diagnosis and initial treatment.8,9(for a review) As Stein and colleagues point out, the same treatments that have improved long-term cancer survival rates can also create both physical and psychological sequelae.10 They further note that the distress and burden that result from the cancer experience are dynamic and fluid across time. This suggests that to fully understand the psychological impact of cancer we need to know “how specific stresses and burden evolve over time, resulting in the waxing and waning of specific concerns.” (p.2586) This is particularly important for older adults who are likely to have other illness symptoms related to comorbidities that may overlay cancer-related symptoms. Unfortunately, much of the research on the physical and mental health effects of cancer focuses on the acute stage of survivorship (first 1–3 years) and is typically based on cross-sectional data.11 While there has been increased interest in longitudinal research, the focus of these studies is on a relatively short period of time early in the survivorship experience.12 We know of no published data on the mental health trajectories of long-term survivors over an extended period of time (5 or more years). We also know of no research that examines these issues among older adult survivors who face the dual vulnerability of cancer and aging. The research reported here was designed specifically to address this limitation in existing research.

DEPRESSION AND CANCER A number of studies have documented the prevalence of depression among cancer survivors.13–16 In one study of the quality of life of long-term colorectal cancer survivors,17 found that cancer survivors had higher levels of the Center for Epidemiological Studies Depression Scale (CES-D), with 14% having scores at or above 16 compared to 9.9% in an age-matched comparison group without a history of cancer. They also found that the single best predictor of depression among survivors was the number of comorbidities, not cancer-related factors. In contrast, other studies have not found a link between having had cancer and higher levels of depression. For example, Keating and colleagues18 did not find a significant difference in level of depression among long-term survivors, compared with individuals in their study who had not had cancer. They did find, however, significantly higher levels of depressive symptoms to be associated with health conditions and symptom distress, such as heart disease and arthritis and symptoms such as pain and incontinence. In another study of long-term survivors,19 found that survivors did not differ in depression from a comparison group of individuals who did not had cancer. In fact, they found that depression declined slightly over time among survivors, while increasing slightly for the comparison group.

From the above research it is apparent that the link between cancer and depression is complex and may be related to non-cancer factors, requiring a multivariate approach that differentiates the effects of cancer from the effects of other illnesses. The impact of cancer on the mental health of survivors may be due to comorbid conditions as well as the associated symptoms and functional problems. Population based studies document that both the prevalence and number of comorbidities increase with age.20 Among cancer survivors, nearly one-third report having two or more comorbid conditions.21 In our prior research, illness symptoms in older cancer survivors that are linked to other comorbid health conditions were found to be associated with psychosocial outcomes such as depression.13,22

Cancer-Related Worry Research has shown that for many survivors the stressors associated with cancer persist long after treatment has ended, even when survival is virtually assured.9,14,16,22,23 However, the sources and nature of that distress may be very different compared to those faced by patients in treatment or during the acute phase of survivorship. During treatment, concerns about the noxious effects of radiation or chemotherapy and invasive procedures are likely. In the period shortly after treatment other effects of the cancer or its treatment may linger such as pain, fatigue, swelling or incontinence. It is during this period that cancer-related worries, such as fear of recurrence, are likely to commence. For example, in one study24 the authors found that worry about cancer recurrence was prevalent and stable through 3 months following treatment for breast cancer. Importantly still other research has shown that these cancer-related concerns persist into the extended period of survivorship (ie, after the first year), and these concerns are a key aspect of cancer-related distress.10,25,26 They may be exacerbated by the distress associated with continued testing and monitoring.27,28 However, some research has suggested that fear of recurrence may decrease over time29,30 and that age may be inversely associated with these fears.31–33 Of special significance for our research were findings32 documenting that other health problems and somatic concerns are significant correlates of fear of recurrence. For older adults with accelerating trajectories of comorbidity and related symptoms, fears of recurrence may be aggravated by other, perhaps ambiguous symptoms. Fear of recurrence is not the only source of cancerrelated worry for long-term survivors. Most survivors are also aware that they are vulnerable to other types of cancer either from the treatment they received, a genetic predisposition for cancer or a recognition that cancer risks increase with age. For example, a study by Mullens et al30 found that colorectal survivors worried more about a new primary cancer than they worried about a recurrence or any other

CANCER-RELATED WORRIES AND DEPRESSIVE SYMPTOMS

health condition. These other types of cancer-related fears are therefore included in our measurement.

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Linking Cancer-related Worry and Depressive Symptoms Research in psycho-oncology has found a link between cancer-related worries, such as fear of recurrence, and general indicators of mental health and specific psychosocial outcomes such as depression. For example, Hart et al31 found that fear of recurrence was a significant predictor of overall mental health and that these fears persisted 18 months posttreatment; and Koch et al34 recently documented the association between cancer worry and both depression (CES-D) and negative affect (PANAS). Further, Simard and Savard35 found that each of the seven dimensions of fear of recurrence they studied was significantly associated with depression (HADS), anxiety (HADS) and post-traumatic stress disorder (PTSD) symptoms (IES). Finally, our own prior cross-sectional research with older long-term survivors25 documented the link between cancer-related worries and a number of mental health outcomes including depression. That same analysis also identified the predictive power of non-cancer as well as cancer-related factors on both cancer-related worries and depression. Recent reviews have found strong evidence of a consistent relationship (correlations ranged between r D .19 to r D .57) between fear of cancer recurrence and depression.36,37 However, none of the above mentioned research, including our own, examined the effect of cancer and non-cancer predictors on the trajectories of cancer-related worries and depressive symptoms among long-term survivors over an extended period of time. The Conceptual Model The conceptual models that organized our analyses are shown in Figures 1–3. Based on the research reviewed above, the model in Figure 1 proposes that the trajectory of cancer-related worry over time (data collected over a 5year period) is a function of a range of personal characteristics (ie, age, race, and sex) along with age-related factors (ie, comorbid health conditions and related illness symptoms) and cancer-related factors (ie, stage at diagnosis and number of types of treatment received, continuing cancerrelated symptoms, and cancer-related worry). In this model, the predictors include time-invariant factors (eg, race, sex, cancer stage, and treatment) and other health-related factors that are measured at baseline (eg, comorbidities, non-cancer symptoms). The model in Figure 2 proposes that the trajectories among individuals in depressive symptoms over time are the product of these same factors, along with cancerrelated worry measured at baseline. This allows us to examine the predictive value of cancer-related worry when the effects of survivors’ personal characteristics and other

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health factors are included as covariates. Finally, the model in Figure 3 focuses specifically on the link between cancerrelated worry and depressive symptoms trajectories over the four waves of data collection. Because of the potential causal ambiguity of these two factors over time, we also evaluate a correlational, parallel process model in which we examine the inter-correlation of these two trajectories, rather than causal paths. These models taken together have the potential to provide a more complex view of the impact of cancer-related and non-cancer-related factors on the course of depressive symptoms over time than has been previously presented in the psycho-oncology literature.

METHODS Sample Eligibility/Acquisition Approval to conduct the study was first received from the internal research board (IRB) of University Hospitals (UH) prior to application for funding in 1998. Approval to conduct the project and collect data from the tumor registry was received from the UH IRB (CWRU #2995, 2/24/99), and has been continuously renewed. There are no conflicts of interest involved in this research. Following these approvals sample acquisition for the study began in March 1999. Based on the study’s inclusion criteria, the sampling frame derived from the tumor registry included only persons who (1) were 60 years of age or older, (2) had been treated for breast, colorectal, or prostate cancer, (3) were 5 years or more from diagnosis, and (4) were African American or Caucasian. The resulting sampling frame consisted of 2,129 cancer survivors, including 255 (12%) African-Americans. A stratified random sample was selected from among these individuals to fill the study cells related to race, sex, and cancer type. Of those randomly selected we contacted 635 who met the study criteria. A total of 321 of these ultimately agreed to participate, signed the approved IRB consent form and completed the baseline interview. Sample Characteristics The initial sample consisted of 321 older adult (60C) cancer survivors (5-34 years post-diagnosis) who were part of a longitudinal research project funded by the National Cancer Institute (R01-CA-78975). The sample was randomly selected beginning in 1999 from over 6,000 individuals in the tumor registry of the Ireland Cancer Center (ICC) at University Hospitals Case Medical Center in Cleveland, Ohio who met the study’s age, cancer type, and race inclusion criteria. Cognitively impaired older adults were excluded from this study during the screening process. In this paper, data from the 179 respondents who completed all four waves of interviews (1999–2004) were utilized in

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KYPRIOTAKIS ET AL. t1

t2

t4

-.743*** 11.07*** (9.834***)

Worry Intercept

e

-.809*** (0.714***)

Worry Slope

e

-.01 .00 Age -.20

.17

-.01

Race

.12

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-.10

-.00

Sex

.10* -.09* Non-Cancer Symptoms

-.09

-.14

.05

.02

.16

Cancer Stage

Co-morbidies

-.06

Cancer-Related Symptoms

Number of Treatment Types

Regression coefficients are standardized. *p < .05, ***p < .001. Unstandardizedmeans and variances (in parenthesis) of the growth factors based on the uncondional model are provided. Fit indices for the uncondional model: X2 = 6.281, df = 2, CFI = .977, RMSEA = .109 90% CI = .017-.211, N = 179. Fit indices for the condional model: X2 = 31.715, df = 10, CFI = .9, RMSEA = .110 90% CI = .068-.154, N = 179.

FIGURE 1 Latent growth curve model of cancer worry with covariates.

for the total sample and 71.4 for the longitudinal panel sample. The mean age at diagnosis was approximately 62 years. The most prominent type of cancer in the study’s initial sample was breast (41.4%), followed by colorectal (29.9%), and prostate (28.7%). Most survivors had in situ (6.5%) or localized cancer (56.7%) at diagnosis. However, nearly 30% had more advanced disease, either regional (27.7%) or distal (1.9%). Most survivors were diagnosed in their 60’s and had survived, on average, approximately ten years at the time of the study’s first interviews.

the analyses in order to examine the dynamics of cancerrelated worry and depressive symptoms over time. The original sample included 131 men and 190 women. The panel sample used in the analyses presented here includes the 64 men and 115 women who completed all four waves of interviews administered yearly. African Americans comprised approximately 41% of the overall sampling frame and constituted 35% of the original sample and 40% in the four-wave panel, respectively. The mean age, based on tumor registry information, was 72.3 years t1

7.522*** (20.432*** )

t2

t3

t4

-.546* Depression Intercept

e

Depression Slope

e

-.216 (1.004***)

-.25*

-.14 .13

.31*

Age .01

Cancer Worry

-.01

.13

Race

-.04 .15 Sex

-.05

-.11 .26** Non-Cancer Symptoms

-.02

.33*

Co-morbidies

.19*

-.18 Cancer Stage

-.09

.01

Cancer-Related Symptoms

Number of Treatment Types

Regression coefficients are standardized. *p < .05, ***p < .001. . Unstandardizedmeans and variances (in parenthesis) of the growth factors based on the uncondional model are provided. Fit indices for the uncondional model: (X2 = 10.613, df = 8, CFI = .991, RMSEA = .043 90% CI = .000-.103, N = 179). Fit indices for the condional model: (X2 = 51.481, df = 26, CFI = .83, RMSEA = .07 90% CI = .044-.104, N = 179)

FIGURE 2 Latent growth curve model of depression with covariates.

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CANCER-RELATED WORRIES AND DEPRESSIVE SYMPTOMS

5

FIGURE 3 Latent growth curve parallel process analysis of depression and cancer worry: A correlational model.

The largest subsample (43.9%) received surgery as the only type of treatment, reflecting the localized nature of the disease. The remainder of the sample received combined therapies, including radiation, chemotherapy, and hormone therapy. Approximately 12% received both surgery and radiation therapy and about 10% had surgery and chemotherapy. Only 5% of the sample was treated with this combination of surgery, radiation, and chemotherapy, however nearly 30% had other combined therapies. Instrumentation and Measures In-person interviews were conducted with older adult cancer survivors by experienced interviewers, who had received extensive training in administering the structured interview instrument. On average, it took approximately two hours to conduct each interview. The questionnaire covered a range of issues related to the illness experience, such as disease and treatment characteristics, short and long-term health and psychosocial sequelae. In addition to the demographic characteristics described above (ie, age, race, sex) a number of additional measures are used to operationalize key predictor variables and growth curve factors in this analysis. These are detailed below. Survivor Characteristics The Comorbidity measure used is a sum of the number of diagnosed health conditions (other than cancer) that the survivor reported from a list of 27 possible conditions based on the Older Americans Resources and Services (OARS).38 The psychometric properties of this index have been well established for use with older adults by Fillenbaum,39 who provides extensive information on the validity and reliability of the OARS methodology. The actual range in this

research was 0–11 health conditions reported. The mean in the total sample was 3.7 (SD D 2.4) and 3.9 (SD D 2.3) in the longitudinal panel at T1. A Non-cancer Symptom Index was constructed to document the number of current symptoms NOT attributed to cancer or its treatment as reported by the respondent. A list of 22 possible symptoms was provided including nausea, vomiting, weakness, pain, swelling, impaired immunity, loss of balance, numbness, and burns. The presence of each symptom was totaled in the index, resulting in a potential range from 0 to 22, with an actual range of 0–13. On average, respondents in the total sample reported 2.6 (SD D 2.4) symptoms not attributed to either cancer or its treatment and an average of 2.7 (SD D 2.5) in the longitudinal panel at T1.

Cancer/Treatment Measures The type of cancer and stage at diagnosis were based on tumor registry information. For statistical analysis, type of cancer was binary coded for breast, colorectal and prostate s (0, did not have; 1, had this type of cancer). Staging of the cancer was coded by the tumor registry as “in situ,” “localized,” “regional,” or “distal.” These were given numeric codes ranging from one to four for statistical analysis. The mean stage was 2.3 (SD D 0.6) in the total sample and 2.2 in the panel at T1. The length of survivorship, measured as the number of years survived since diagnosis, was based on tumor registry data and confirmed during the interview. There was considerable variation in the duration of survivorship, ranging from 5 to 34 years. The mean number of years since diagnosis was 10.4 (SD D 5.5) in the total sample and 12.8 (SD D 8.38) in the longitudinal panel.

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KYPRIOTAKIS ET AL.

Three measures were used to operationalize the nature and extent of cancer treatment. The first was the reported number of treatment types the individuals received for their cancer (ie, surgery, radiation, chemotherapy, hormone therapy, or other). In this research, the total number of types of treatment is a surrogate measure for the extensiveness of the cancer treatment experienced. All but two individuals in the total sample reported receiving at least one form of treatment, 31.2% received two forms of treatment, 13.1% received three, and 1.2% (four individuals) received four types of treatment. The mean number of treatment types was 1.6 (SD D 0.8) in the total sample, with an identical mean of 1.6 in the panel at T1. The measure of Current Cancer-related Symptoms used the list of 22 possible symptoms described used to document non-cancer symptoms. For this measure the total reflects only those continuing symptoms reported by the respondent that they attribute to cancer or its treatment. On average, respondents reported 0.8 continuing symptoms attributed to either cancer or its treatment (SD D 1.5) in the total sample and 0.7 in the panel at T1. These same items were also used to create a measure of symptoms during treatment. The actual range on this indicator was 0 to 15, with a mean of 1.5 symptoms (SD D 2.0) in the total sample and an identical 1.5 in the panel at T1.

index were included in this research: (1) “I worry about my cancer coming back”; (2) “I am sometimes concerned that symptoms I experience may indicate the recurrence of cancer”; (3) “I worry about future diagnostic tests”; and (4) “I worry about another type of cancer.” Responses were scored on a five-point continuum ranging from 1 (strongly agree) to 5 (strongly disagree). These four items were then summed to construct a cancer-related worries scale which had a potential range of from 4–20. The mean score of this indicator was 11.2 (SD D 3.4) in the total sample and 11.0 in the panel at T1. The alpha reliability for this scale was .84. Because cancer-related worries might be considered an alternative measure of general distress, factor analysis was conducted to determine whether they are empirically distinct from depression. The results of that analysis indicated that the cancer-related worries items do not cross load significantly with the items from the depressive symptoms scale and represents a distinct factor (analysis not shown, available from authors upon request). The second measure of psychological distress used is a widely used measure of depressive symptoms, the CES-D.40 This original scale consists of 20 items asking respondents the frequency during the past year that they have felt depressed, happy, lonely, sad, and fearful. Answer categories ranged from 0 (never/rarely) to 4 (all of the time). The 20 item version of this indicator has a potential range of 0–80. In our research the mean at T1 was 12.5 (SD D 9.2) with a demonstrated alpha reliability of .87. In the longitudinal analysis reported here, we used an abbreviated 10-item form of the scale as suggested by Kohout et al,41 which replicated the original factor structure and reliability comparable to the longer original index. Scores

Psychosocial Measures Two psychosocial measures are used in this analysis. The first measure, cancer-related worries, was conceptualized and measured based on the work of Gotay and colleagues34 and has established psychometric properties with both short- and long-term survivors. Four items from their longer

TABLE 1 Characteristics of the Total Sample (N D 321) and Longitudinal Panel Sub-sample (N D 179) Longitudinal Panel Sub-sample Total Sample

Age % African American % Female % Breast % Colorectal % Prostate Cancer stage # of Treatment types # of Comorbidities # of Symptoms during treatment # of Non-cancer symptoms # of Current cancer-related symptoms Functional Difficulty Index Score Cancer-Related Worry Scale Depressive Symptoms Scale Note. Percentages are identified in italics.

Mean/% 72.4 35 59 42 29 29 2.3 1.6 3.7 1.5 2.6 0.8 5.2 11.2 7.2

(SD) (7.5)

(0.6) (0.8) (2.4) (2.0) (2.4) (1.5) (5.4) (3.4) (5.1)

T1 Mean/% 71.4 40 65 46 28 25 2.2 1.6 3.9 1.5 2.7 0.7 4.8 11.0 7.1

T2 (SD) (7.1) — — — — — (0.6) (0.8) (2.3) (1.9) (2.5) (1.2) (4.6) (3.3) (5.2)

Mean — — — — — — — — — — — 0.5 4.9 10.7 7.8

T3 (SD) — — — — — — — — — — — (0.8) (5.0) (3.6) (4.9)

Mean — — — — — — — — — — — 0.3 4.3 — 7.0

T4 (SD) — — — — — — — — — — — (0.8) (4.3) — (5.0)

Mean — — — — — — — — — — — 0.4 4.8 8.6 6.7

(SD) — — — — — — — — — — — (1.0) (4.9) (2.1) (4.7)

CANCER-RELATED WORRIES AND DEPRESSIVE SYMPTOMS

on this measure have a potential range of 0–40 and a demonstrated alpha reliability of .87 in our sample.

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Analytic Strategy Beyond the descriptive data provided in Table 1, the core of the analysis presented with the longitudinal panel is based on latent growth-curve analysis. This approach can be used to investigate data obtained in longitudinal studies where repeated assessments are nested within individuals42 and permit the evaluation of individual differences in rates of change. The growth curve model summarizes individual level outcome data at three or more occasions in terms of “true” initial level of performance (intercept), slope (improvement or rate of change), and error (residual) parameters. The model estimates fixed (ie, average) and random (ie, varying) intra-individual differences and can include predictors of individual/group differences in intercept and slope. Within-person correlations among occasion-specific residuals—often neglected in the modeling of associations between trajectories—provide information regarding state-like time-specific fluctuation in depressive symptoms and cancer-related worry after controlling for an individual’s trait-like growth trajectories. The within-person correlations represent the extent to which individual

7

deviations from their estimated trajectories tend to be associated across outcomes. In terms of time metrics we estimated models with both individually varying times of observation and fixed time points. We concluded, through superimposing graphically the estimated individual trajectories from each model specification and looking at the results of the two models, that the fixed time points model was not inferior to using individually varying times of observation. In addition, the fixed time points model offers additional flexibility and more efficient computation. In the analysis presented here individual growth curves are estimated for each outcome variable (ie, cancer-related worry, depressive symptoms) using Mplus version 7.43 As applied in our first two models, the focus of the first growth curve analyses is on the predictors of the intercept (or initial level; ie, survivor’s score at T1) and slope (change scores) of either cancer-related worry or depressive symptoms across four points in time, T1 through T4. In the analysis of cancer-related worry, predictors are survivor characteristics measured at T1 including personal characteristics (age, race, and sex), general health measures (noncancer illness symptoms and comorbidities), and cancer factors (stage at diagnosis, number of treatment types, cancer-related symptoms. In the model for depression, cancerrelated worry at T1 is added as an additional time-invariant

TABLE 2 Fixed and Random Effects Estimates and Standard Errors for Depressive Symptoms and Cancer-Related Worries (N D 179) Unconditional Model Depressive Symptoms Fixed-effects level estimate Age Black Female # of Non-cancer symptoms Comorbidities Cancer Stage # of Treatment types Cancer-related Symptoms Cancer-related Worry Rate of change estimate Age Black Female # of Non-cancer symptoms Comorbidities Cancer Stage # Treatment types Cancer-related symptoms Cancer-related worry Variance components Level variance Slope variance Level-slope covariance Log-likelihood

Conditional Model

Cancer-Related Worries

Depressive Symptoms

Cancer-Related Worries

7.522* (0.393)

11.069* (0.249)

11.587* (0.446) ¡0.030 (0.035) ¡0.631 (0.490) ¡0.310 (0.548) 0.311* (0.113) ¡0.051 (0.116) ¡0.429 (0.470) 0.484 (0.331) ¡0.002 (0.057)

¡.216 (0.128)

¡.809* (0.069)

7.881*(2.815) ¡0.396*(0.111) ¡0.091 (0.053) 0.061 (0.732) 0.498* (0.167) ¡0.023 (0.171) 1.453* (0.704) ¡0.542 (0.494) ¡0.183 (0.298) 0.434* (0.113) ¡0.222 (0.183) 0.019 (0.018) ¡0.026 (0.254) ¡0.101 (0.279) ¡0.049 (0.058) 0.143* (0.059) ¡0.303 (0.238) 0.040 (0.170) 0.137 (0.103) ¡0.077* (0.039)

20.431* (3.007) 1.004* (0.327) ¡2.539* (0.816) ¡1911.537

9.834* (1.331) .714* (0.118) ¡1.997* (0.367) ¡1199.821

14.894* (2.455) 0.748* (0.303) ¡1.824* (0.713) ¡4492.934

Note. Standard errors are shown in parentheses. *p < .05.

¡0.875* (0.126) 0.004 (0.010) 0.137 (0.139) 0.004 (0.156) ¡0.075* (0.032) 0.042 (0.033) 0.072 (0.132) ¡0.047 (0.094) ¡0.002 (0.057)

8.378* (1.252) 0.632* (0.115) ¡1.708* (0.353) ¡3361.563

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KYPRIOTAKIS ET AL.

predictor. Age and other predictors were centered on their mean values at Time 1 in the longitudinal panel sample with sex coded as (0, male; 1, female) and race (0, white; 1, African American). We report both the regression estimates as well as the standardized coefficients for each of these on both the intercept and slope of the respective outcomes. The third model is a “parallel process” growth curve model and focuses on the associations among intercepts and slopes between cancer-related worry and depressive symptoms, conditional on the same set of covariates used previously.

RESULTS

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Cancer-related Worries Figure 1 provides the summary results of our first model in which cancer-related worries is the outcome of interest. This analysis examines the trajectory of cancer-related worries as defined by data collected at T1, T2, and T4 (data on this variable was not collected at T3). In this and subsequent models the standardized coefficient is provided for each path. Additional fixed and random effects estimates including un-standardized coefficients and model fit are provided in Table 2. Shown in Figure 1, the number of reported non-cancer symptoms (T1 score) is a significant predictor of both the intercept (b D .10) and slope (b D –.09) of cancer-related worries. These coefficients indicate that survivors who reported more non-cancer symptoms initial reported more cancer worry initially, but exhibit faster decline in cancer-related worries. Depressive Symptoms The second group of findings presented is from the growthcurve model focusing on depressive symptoms as the outcome. Once again, the survivors demographic, health and cancer-related factors (including cancer-related worries) measured at T-1 are used as predictors in a model that examines the intercept and slope of depressive symptoms across the four waves of interviews (T1 through T4). This model is portrayed in Figure 2 with additional fixed and random effects estimates including un-standardized coefficients and model fit indicators provided in Table 2. Looking first at the role that the survivors’ personal characteristics play in explaining their levels of depressive symptoms, none of these are significant predictors of either the intercept (initial level) or rate of change (slope). However, one of the survivors general health characteristics, the number of non-cancer symptoms at T1, does significantly predict the initial depressive symptoms level (b D .26), but not its slope. This indicates that survivors who had more illness symptoms not attributed to cancer reported higher levels of depressive symptoms. However these illness symptoms were not

significant predictors of the trajectories of individuals’ depression symptoms over time. In contrast, the number of comorbidities they reported initially did have a significant relationship with the trajectories of survivors’ depressive symptoms (b D .33), with those reporting a greater number of co-morbid health conditions demonstrating an increase in depressive symptoms over time. Looking at the cancer-related factors included in the model, cancer stage at diagnosis was a significant predictor of the respondents initial depressive symptoms scale score (b D .19), indicating that survivors who had the most advanced cancer at diagnosis reported the highest level of depressive symptoms at T1 in our study. However, cancer stage was not a significant predictor of the slope of depressive symptoms between T1 and T4. Finally, looking at cancer-related worry, respondents’ scores at T1 were predictive of both the intercept (score at T1) and the slope (T1 through T4) of depressive symptoms (b D .31 and –.25, respectively). Cancer-related Worries and Depression This “parallel process” model examines the relationship of survivor’s scores on cancer-related worries over time (using measures at T1, T2, and T4) with their reported depressive symptoms over time (observed T1 through T4). These relationships are portrayed in Figure 3 with standardized estimates indicated for the respective paths and additional model estimates provided in Table 3. The model examines the inter-correlation among these growth-curve factors rather than directional causal pathways, given the causal ambiguity between cancer-worry and depression. In this analysis we find that the cancer-related worry intercept (T1 score) is significantly associated with the intercept (b D .39) but not the slope for depressive symptoms (b D –.26). This indicates that survivors who reported higher levels of cancer-related worry initially, also reported higher levels of depressive symptoms initially. Additionally, the slope for cancer worry is also significantly TABLE 3 Un-standardized Coefficients of the Parallel Process Model (N D 179) Cancer-related Worry Rate of Change

Depressive Symptoms Initial Level

Rate of Change

Cancer-related worry Initial level ¡2.110* (.409) 5.590* (1.459) ¡.846 (.495) Rate of change ¡1.079* (.421) .229 (.173) Depressive symptoms Initial level ¡2.477* (.807) Note. Standard errors are shown in parentheses. *p < .05.

CANCER-RELATED WORRIES AND DEPRESSIVE SYMPTOMS

associated the intercept for depressive symptoms (b D –.27). However, the slope for cancer-related worry, although comparable in effect size (b D .25), did not achieve significance at the .05 level. Taken together these data suggest a consistent relationship between cancerrelated worry and depressive symptoms with those survivors who have higher initial levels of cancer-related worries also having higher levels of depressive symptoms initially, and those who experienced an increase in cancer-related worries similarly experiencing an increase in depressive symptoms and vice versa.

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DISCUSSION Our prior research on cancer-related worries found that these concerns persist in over half of all survivors.13 That and the research reported here indicates that these worries continue largely unabated over an extended period of time and suggests that they represent an ongoing threat to the psychosocial quality of life of survivors long after diagnosis and treatment. This replicates the prominence and persistence of cancer-related worries and depressive symptoms among older adult survivors found in other research.18,32,35,37,44 However, the key finding in this research, that cancer-related worries co-vary with depressive symptoms over time, issues of causal direction notwithstanding, has important implications for those working with long-term survivors. This novel finding of co-evolution of depressive symptoms and cancer worry explicates the interdependence of experiences of cancer survivors and the potential fueling of psychological burden over time. It suggests the need for health care and mental health practitioners to assess survivors for the presence of both of these threats to quality of life. Moreover, these findings suggest the need for intervention to interrupt the potentially downward spiral of worry leading to depressive symptoms leading to greater worry, and so on. Additionally, the results indicate that the trajectories of both cancer worry and depressive symptoms over time are linked to non-cancer as well as cancer-related factors. This is consistent with and an extension of our prior cross-sectional research13 that demonstrated that both cancer-related worries and depressive symptoms are predicted by other health problems and symptoms as well as cancer-related factors. It is possible that for older survivors, ambiguous illness symptoms stemming from other illness conditions play a role in increasing the uncertainty they experience, which in turn translate into cancer-related concerns. These findings suggest an important role that health care practitioners can play helping older survivors evaluate the symptoms they are experiencing, especially ambiguous ones that may represent either a new comorbid condition or the recurrence

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of the prior cancer or a new cancer. We should note that despite our data being more than 10 years old this study is relevent for three reasons: (a) the increasing number of cancer survivors living beyond 5 years after diagnosis who experience increased fear of cancer recurrence and depression45; (b) The lack of in-depth understanding of how cancer-worry and depression compromise the well-being of long term cancer survivors, understanding that can be used to design improved psychosocial interventions45,46 and (c) the recent call for monitoring the psychosocial concerns of survivors, as a priority for clinicians outlined by the National Comprehensive Cancer Network.47 Moreover, advances in treatments and changes in cancer prevalence based on cancer sites, as outlined by the Annual Report to the Nation on the Status of Cancer,48 have not significantly modified the psychosocial experiences of long-term survivors, as indicated in recent studies,45,46,49 and are similar to the experiences we found in our data. We acknowledge important limitations, however. First, we did not include subjects with incomplete data over time. It is possible that missing data are not missing at random (MAR) in the two processes under study, and explicitly modeling the missing process may improve the plausibility of our results. We are currently exploring the presence of alternative missing mechanisms in future work. Preliminary results show no substantive differences in direction and size of the coefficients between the total (321) and the completers (179) analyses (results available upon request). Second, the findings would have become more informative if a comparison group of adults survivors (perhaps between ages 40 and 60) were included, as older adults tend to report less distress generally. Third, we acknowledge the possibility of recall bias in some of our measures (eg symptoms during treatment). Fourth, although the models in this study converged, the relatively small sample size may have affected the size of the regression effects. Studies with larger sample sizes are needed to replicate these results. Finally, a potential correlate of cancer worry may be past and concurrent levels of anxiety. We have not inlcuded anxiety in our models, and it is possible that part of the association of depression and cancer worry may be accounted for by anxiety. Overall, our findings indicate that those who have been diagnosed and treated for cancer are never completely removed from its threats to their quality of life, even as they survive into later life and experience an increase in other health problems. These findings also suggest that older adults face the dual vulnerability of aging with its growing number of comorbidities and related symptoms along with the vulnerability conferred by cancer-related sequelae and the possibility of recurrence or new cancers. As such, older adult survivors represent an important target group for the development

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of mental health interventions to deal with worry/ depressive symptoms issues, as well as health care interventions to better assess the threats of the symptoms that stem from either cancer or comorbidities.

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CONCLUSIONS The finding that the specific depressed mood trajectory (whether increasing or decreasing) of the long-term cancer survivor is significantly associated with the trajectory of cancer worry, in addition to the baseline relationship of the two processes, is a novel finding with potentially important implications in decision making in terms of refining and adapting treatment aiming at improving qualty of life for long-term cancer survivors. Combining mental health expertise with knowledge of the dynamic interplay between cancer worry and depression would enable care providers to make better informed decisions and dynamic patient-specific evaluations, and thus improve the mental health of older adult survivors. This can be achieved by evaluating the strength of the relationship between cancer worry and depression in a patient based on the totality of the patients depression experience (level and change) and adapting mental health treatment strategies to reflect this experience. Patients not only experience different levels of depressed mood and cancer worry but also their experience and relationship of these two processes changes in different ways within individuals. Explicating the nature of this dynamic relationship, between cancer worry and depressed mood, and integrating it into an individualized treatment plan that addresses the individual course of experience in a continuum may improve patient outcomes in terms of QoL. This is especially critical in the care for long-term cancer survivors where the time persistent effects of a cancer diagnosis on mental health are not explicated, and thus not integrated in mental health treatment plans.

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