Abstract
Background:
Evidence has begun to emerge indicating that cancer survivors experience accelerated aging. This study examines this phenomenon by evaluating trajectories of functional decline in older adults with a history of a cancer diagnosis relative to those without a history of cancer.
Methods:
Community dwelling healthy volunteers in the Baltimore Longitudinal Study of Aging were evaluated in the Clinical Research Unit of the National Institute on Aging Intramural Research Program. Between 2006 to 2019, 1728 men and women (aged 22 to 100) underwent clinical evaluation of functional status; 359 reported having a history of cancer. Longitudinal associations between self-reported cancer history and measures of functional decline were examined using generalized estimating equations. Additionally, time-to-event and Cox proportional hazards models were used to examine trajectories of decline. Where appropriate, age-stratified associations were examined, and models were adjusted for sex, BMI, race, smoking status, education, and number of comorbid conditions.
Results:
Among all participants, a history of cancer was associated with 1.42 (95% CI, 1.11 – 1.81) greater odds of weak grip strength. Among older participants (> 65 years of age), those with a history of cancer had 1.61 (95% CI, 1.28, 2.02) greater odds of slow gait speed and a 0.11 unit (95% CI, 0.19 – 0.03) lower physical performance score than those with no cancer history. Time to event analysis showed that older individuals with a history of cancer experienced steeper decline in grip strength and gait speed, than older adults with no history of cancer (p < 0.01).
Conclusion:
Cancer survivors, especially older individuals, demonstrate greater odds of and accelerated functional decline, suggesting that cancer and/or its treatment may alter aging trajectories. Observational and intervention studies are needed for prevention, mitigation, and/or reversal of aging-related effects of cancer and its treatment.
Keywords: Cancer, Aging, Grip Strength, Gait Speed, Functional Decline
INTRODUCTION
In 2019 in the United States, an estimated 16.9 million individuals had a history of cancer; this number is projected to reach 22.1 million by the year 2030.1 Despite the fact that cancer survivors are, in general, living longer, they are particularly prone to age-related functional decline due to the impact of cancer and its treatment.2 Epidemiologic studies have shown that childhood and young adult cancer survivors have lower physiologic reserve and higher rates of comorbid conditions than persons of similar age without a history of cancer.3–8 Some young survivors in their 20s and 30s exhibit higher rates of poor endurance, mobility and muscle strength, and power that are comparable to individuals in their 60s and 70s.8–14 Despite these observations, research on clinically-measured functional decline among survivors of adult-onset cancers remains limited. Three previously published studies showed accelerated declines in fatiguability, endurance, and self-reported functional status among individuals diagnosed with cancer compared to those without a history of cancer15–17; one study showed no statistically significant difference in the trajectory of self-reported physical functioning between the two groups.18
The potential synergy between aging and cancer may place older cancer survivors at risk of early decline in strength, mobility, and functional performance. Therefore, assessing the trajectories of functional decline among older adults with cancer history is important in understanding when, and how quickly this decline occurs. This knowledge can aid in the development of clinical guidelines to assess physical functioning among those at risk for early and accelerated functional decline as well as interventions to prevent, mitigate, or reverse decline, with the ultimate goal of extending the health span of all cancer survivors.
METHODS
Study sample
Established in 1958, the Baltimore Longitudinal Study of Aging (BLSA) is the longest-running scientific study of human aging. Conducted by the National Institute of Aging (NIA) Intramural Research Program, the BLSA’s primary goals are to quantify indicators of natural, age-related decline in factors such as physical strength and performance; to understand the relationship between health risk factors and aging; and to track trends in behaviors that promote health or increase risk for disease.19 Physical and cognitive markers of aging are assessed among participants during regular intervals over the course of their lives. Those under the age of 60 are assessed every 4 years; those aged 60 to 79 are assessed every 2 years, and those aged 80 and older are assessed annually. BLSA participants are generally healthy volunteers; at the time of enrollment, participants must be free of major chronic conditions such as cardiovascular disease, diabetes, neurological and gastrointestinal diseases, etc. Cancer history, including cancer type(s) and age(s) at diagnosis, is collected via self-report and those with a history of cancer are eligible to enroll in the study upon being cancer free for at least 10 years.20 Information on cancer treatment is not collected. Following enrollment, all participants are followed for life, regardless of disease development. The study protocol was approved by the National Institutes of Health Intramural Institutional Review Board (BLSA approved protocol: 03-AG-0325). Informed consent was obtained from all participants at each study visit.
Many of the functional measures used in this study were first introduced into the BLSA protocol in 2006. In this analysis, the first visit completed after implementation of these measures is referred to as the participant’s index visit. We identified 1,742 BLSA participants with an index visit between January 4, 2006 and March 31, 2019 (Figure 1). Those who reported only having a history of nonmalignant skin cancers (basal, squamous) were included in the cancer free control group (n = 212). Fourteen participants with missing cancer history data were excluded from the analytic data set. Our final dataset contained 1,728 participants, with 359 participants reporting a cancer diagnosis either at the index visit or afterwards, and 1,369 participants reporting no history of cancer.
Figure 1.
Analysis flowchart for identifying cancer patients (incident/prevalent) and those without a history of cancer. a Including those who only reported having a history of nonmalignant skin cancer (basal, squamous). b Gastrointestinal cancers include colon, stomach, pancreas and liver cancers. c OB/GYN cancers include cervical, endometrial and ovarian cancers. d Other cancers include bladder, brain, thyroid and cancers not otherwise specified.
Outcomes
At each visit, BLSA participants provide a detailed medical history and undergo a standardized physical performance assessment with trained and certified technicians using standardized protocols. Maximum grip strength (kg) was measured using a hydraulic handheld dynamometer (Jamar) from 3 trials on each hand. For this analysis, data on the stronger grip strength reading between the left and right hand was utilized. ‘Weak’ grip strength was defined as a grip strength <26 kg for men and <16 kg for women.21 Usual gait speed (m/s) was measured twice over a 6-meter course; the faster of the two trials was used for our study. ‘Slow’ usual gait speed was defined as gait speed <0.8 m/s.22, 23 The Health, Aging and Body Composition physical performance battery (HABC PPB) metric measures performance in four mobility-related tasks: 1) usual gait speed, 2) time taken to stand up and sit back down five times on an armless chair without assistance, 3) ability to hold three balance-related positions: semi-tandem, full-tandem and single-leg stands for up to 30 seconds each, and 4) capacity and time to walk a narrow (20 cm wide) 6 meter course.24 The HABC PPB score is continuous, ranging from 0 to 4 with ability to complete all four tasks at maximum speed assigned a score of 4 and inability to complete all of the tasks assigned a score of 0. Details regarding HABC PPB score assignments and calculations have been previously described.25, 26
Covariates
The following covariates were considered in the analyses: age, sex, education, race, body mass index (BMI), smoking status, and total number of co-morbid conditions. Age was analyzed primarily as a continuous variable and dichotomized into categories of 65 years or younger and older than 65 in the interaction and stratified analysis. BMI was derived using height and weight that were assessed in light clothing using a stadiometer and calibrated scale. BMI was included in the models as a continuous variable. Demographic factors and smoking history were obtained from standardized self-reported questionnaires. Race was dichotomized as White and Non-White. The following comorbidities were used to derive number of comorbid conditions: cardiovascular disease, hypertension, pulmonary disease, diabetes, stroke, liver disease, kidney disease, peripheral neuropathy, arthritis, and depression.
Statistical analysis
Chi-squared and Fisher’s exact tests were used to compare index visit demographic and medical history characteristics among participants with and without a history of cancer. For the continuous variables (BMI, age, number of comorbidities), differences by cancer history were examined using Student’s t-tests.
Generalized estimating equations (GEE), Kaplan-Meier, and Cox proportional hazards models were used to examine associations between cancer history and the outcomes of interest: grip strength, gait speed, and HABC PPB. GEE models used exchangeable correlation matrix structures to estimate odds ratios for categorical outcomes and mean differences were computed for continuous outcomes, respectively, adjusting for age, sex, race, BMI, and number of comorbidities. Number of years since index visit was used as the time variable in the GEE, Kaplan-Meier, and Cox models. In both GEE and Cox models, effect modification of the association by age was examined by entering an interaction term for cancer history and age. If the interaction was statistically significant (p<0.05), age-stratified estimates were reported.
Subgroup analyses were conducted to assess whether the associations between cancer history and the outcomes were similar among participants with a history of breast, prostate, lung, and colorectal cancers. These four cancers tend to impact the highest number of individuals in the general population and have well established treatment regimens and survivorship guidelines in the literature than less common cancer types.27 Additionally, we conducted sensitivity analysis to assess whether associations differ between individuals with prevalent cancer and those with incident cancers.
All statistical analyses were conducted using SAS software, Version 9.4 of the SAS System for Windows. (Copyright © SAS Institute Inc.) Survival analysis plots were generated using RStudio. (RStudio Team (2020). RStudio: Integrated Development for R. RStudio, PBC, Boston, MA.)
RESULTS
Study participants
Among the 1,728 BLSA participants in the analytic data set, 359 reported a history of cancer including 240 participants who had a history of cancer at the index visit (prevalent cases) and 119 participants who reported being diagnosed after the index date (incident cases). Among the 359 cancer survivors, the most commonly reported cancer types were prostate (38.7%), breast (17.0%), and melanoma (15.0%) (Figure 1). Overall, the mean number of visits completed by each participant was 3 (range 1–13 visits), and the mean number of follow-up years per participant was 5.0 years (SD = 4.2 years).
Demographic and medical characteristics of individuals with and without a history of cancer are shown in Table 1. There were no differences (p < 0.05) in race, sex, BMI, smoking status and certain comorbid conditions such as hypertension and arthritis between participants with prevalent and incident cancer history. Therefore, all analyses (including subsequent p-values) presented in this study (unless otherwise noted) combine incident and prevalent cases and compare them to individuals with no history of cancer. Overall, those with a history of cancer were significantly older, more likely to be men, and had a history of smoking compared to those without a history of cancer (p < 0.01). The prevalence of cardiovascular disease, hypertension, diabetes, stroke, kidney disease, peripheral neuropathy and arthritis were significantly higher among participants with a history of cancer than those without a history of cancer (p < 0.05 across each comparison). No significant differences were observed in prevalence of pulmonary or liver disease, or depression between these two groups.
Table 1.
Characteristics of study sample by cancer status at index visit
| Cancer status (N = 359) |
||||
|---|---|---|---|---|
| Prevalent (n = 240) | Incident (n = 119) | No history of cancer (n = 1369) | ||
|
| ||||
| Characteristic | n (%) | n (%) | n (%) | p-value (Cancer vs No Cancer) |
| Age | ||||
| mean (SD) | 74.2 (12.1) | 68.6 (11.5) | 64.8 (15.4) | |
| <=65 | 50 (20.8) | 45 (37.8) | 684 (50.0) | |
| >65 | 190 (79.2) | 74 (62.2) | 685 (50.0) | <0.001 |
| Sex | ||||
| Men | 146 (60.8) | 70 (58.8) | 605 (44.2) | |
| Women | 94 (39.2) | 49 (41.2) | 764 (55.8) | <0.001 |
| BMI: mean (SD) | 27.34 (4.8) | 27.52 (4.6) | 26.99 (5.1) | 0.91 |
| Race | ||||
| White | 191 (79.6) | 78 (65.6) | 951 (79.5) | |
| Otherᶧ | 49 (20.4) | 31 (34.5) | 417 (20.5) | 0.003 |
| Smoking status | ||||
| Never smoker | 122 (51.1) | 75 (63.0) | 879 (64.9) | |
| Quit >10 years ago | 107 (44.8) | 38 (31.9) | 401 (29.6) | |
| Quit <10 years ago | 6 (2.5) | 2 (1.7) | 35 (2.6) | |
| Current smoker | 4 (1.7) | 4 (3.4) | 39 (2.9) | 0.003 |
| Comorbidities | ||||
| Number: mean (SD) | 1.9 ± 1.3 | 1.5 ± 1.2 | 1.4 ± 1.3 | <0.001 |
| Cardiovascular disease | 48 (20.0) | 12 (10.1) | 130 (9.5) | <0.001 |
| Hypertension | 121 (50.4) | 58 (48.7) | 544 (39.7) | 0.001 |
| Pulmonary disease | 35 (14.6) | 11 (9.2) | 185 (13.5) | 0.96 |
| Diabetes | 45 (18.8) | 18 (15.1) | 173 (12.6) | 0.02 |
| Stroke | 11 (4.6) | 6 (5.0) | 40 (2.9) | 0.02 |
| Liver disease | 2 (0.8) | 1 (0.8) | 13 (0.9) | 0.6 |
| Kidney disease | 16 (6.7) | 5 (4.2) | 59 (4.3) | 0.003 |
| Peripheral neuropathy | 29 (12.1) | 6 (5.0) | 94 (6.9) | 0.005 |
| Arthritis | 134 (55.8) | 52 (43.7) | 547 (40.0) | 0.002 |
| Depression | 42 (17.5) | 17 (14.3) | 216 (15.8) | 0.56 |
BMI = body mass index; SD = standard deviation
Includes Black, American Indian, Chinese, Japanese, Hawaiian, other Non-White and Filipino
Longitudinal Analysis
At the index visit, 11.7% of participants with a history of cancer were classified as having weak grip strength (Table 2); a proportion which increased to 23.2% at the latest visit. Among those without a history of cancer, 9.3% had weak grip strength at the index visit and 16.4% at the latest visit. After adjusting for age, sex, race, BMI, and comorbidities, participants with a history of cancer had 1.42 (95% CI, 1.11 – 1.81) increased odds of having a weak grip strength than those without a history of cancer. Similarly, assessing grip strength as a continuous variable, we found participants with a history of cancer had 2.0 kg (95% CI, 3.06 – 0.84) lower grip strength, on average, than those with no cancer history. No evidence of statistical interaction between age and cancer history was observed in our analysis of grip strength as either a binary (p < 0.43) or continuous variable (p < 0.19).
Table 2.
Unadjusted and adjusted associations between history of cancer and continuous and categorical functional decline outcomes
| Index visit: | Latest visit | |||||
|---|---|---|---|---|---|---|
|
| ||||||
| Cancer | No Cancer | Cancer | No Cancer | |||
|
|
||||||
| Categorical Measures | n (%) | n (%) | n (%) | n (%) | Unadjusted OR (95% CI) | Adjusted OR (95% CI)ᶧ |
| Weak grip strength a | 25 (11.7) | 130 (9.3) | 76 (23.2) | 208 (16.4) | 1.46 (1.16, 1.84) | 1.42 (1.11, 1.81) |
| Slow gait speedᶧᶧb | ||||||
| ≤65 years | 2 (6.5) | 43 (8.9) | 4 (8.9) | 39 (8.2) | 1.01 (0.49, 2.09) | 0.96 (0.44, 2.09) |
| >65 years | 74 (40.4) | 272 (30.2) | 157 (56.3) | 326 (42.0) | 1.59 (1.27, 2.0) | 1.61 (1.28, 2.02) |
|
|
||||||
| Index visit | Latest visit: | |||||
|
| ||||||
| Cancer | No Cancer | Cancer | No Cancer | |||
|
|
||||||
| Continuous Measures | Mean (SD) | Mean (SD) | Mean (SD) | Mean (SD) | Unadjusted difference (95% CI) | Adjusted difference (95% CI)ᶧ |
| Grip strength | 31.9 (10.6) | 33.4 (16.4) | 30.0 (12.3) | 31.8 (17.0) | −0.70 (−2.01, 0.60) | −2.00 (−3.06, −0.84) |
| Gait speed (m/s)ᶧᶧ | ||||||
| ≤65 years | 1.3 (0.2) | 1.3 (0.2) | 1.3 (0.2) | 1.3 (0.2) | 0.00 (−0.01, 0.01) | 0.00 (−0.03, 0.04) |
| >65 years | 1.0 (0.3) | 1.1 (0.3) | 0.9 (0.3) | 1.0 (0.3) | −0.06 (−0.09, −0.03) | −0.06 (−0.09, −0.03) |
| HABC PPBᶧᶧ | ||||||
| ≤65 years | 2.8 (0.3) | 2.9 (0.4) | 2.8 (0.3) | 3.0 (0.4) | −0.07 (−0.14, 0.00) | −0.06 (−0.14, 0.00) |
| >65 years | 2.2 (0.8) | 2.4 (0.7) | 1.9 (0.9) | 2.4 (0.9) | −0.12 (−0.20, −0.04) | −0.11 (−0.19, −0.03) |
95% CI = 95% confidence interval; HABC PPB = Health ABC Physical Performance Battery; OR = odds ratio; SD = standard deviation
Adjusted for sex, race, body mass index, comorbidities, and education
Analysis was stratified by age due to statistically significant interaction observed between cancer history and age (p < 0.001).
Weak grip strength was defined as a grip strength of <26 kg among men and <16 kg as among women.
Slow gait speed was defined as gait speed <0.8 m/s.
At the index visit, 6.5% of younger participants with a history of cancer had slow gait speed, a proportion that increased to 8.9% at the latest visit. Among older participants with a history of cancer, 40.4% met the criteria for slow gait speed at index visit and this proportion increased to 56.3% at the latest visit. After adjusting for age, sex, race, BMI, and comorbidities, older participants with a history of cancer had 1.61 (95% CI, 1.28 – 2.02) times the odds of having slow gait speed and had a 0.06 m/s (95% CI, 0.09, 0.03) slower mean gait speed than those with no cancer history. No differences in gait speed were apparent for younger participants by cancer history status.
At both the index and most recent visit, the mean HABC PPB score was lower among participants with a history of cancer than those without. In older cancer survivors mean HABC PPB score declined from 2.2 (SD = 0.8) at the index visit to 1.9 (SD = 0.9) at the most recent visit. In the longitudinal adjusted analyses, older cancer survivors had a 0.11 (95% CI, 0.019 – 0.03) lower mean HABC PPB score than those with no cancer history.
The sensitivity analysis showed that restricting the analysis to prevalent cases (those whose malignancies developed prior to study enrollment), and to persons diagnosed with one of the four most common cancer types had no material impact on the findings (Supplementary Table S1).
Survival analysis
Results from log-rank tests of obtaining weak grip strength or slow gait speed are illustrated in Figure 2. Global log-rank tests showed that for both grip strength (Fig 2a) and gait speed (Fig 2b) at least one of the Kaplan-Meier (KM) curves varied significantly from the other KM curves (p < 0.0001). Furthermore, Bonferroni adjustments for multiple comparisons for the Wilcoxon test showed significant differences (p < 0.05) between each stratum across all outcomes. Cox proportional hazards models adjusting for sex, race, BMI, comorbidities, and education showed that cancer survivors had 1.46 times the risk of developing weak grip strength (95% CI, 1.14 – 1.87) and 1.35 times the risk of experiencing slow gait speed (95% CI, 1.12 – 1.62), than persons with no cancer history (Table 3). We did not observe significant interactions between age at index visit and cancer history in the Cox proportional hazards models.
Figure 2.
Kaplan-Meier (KM) survival probabilities for the time to developing (A) weak grip strength and (B) slow gait speed. Analysis was stratified by age at index visit and cancer history. P-values are derived from global log-rank texts; a p < 0.05 indicates that at least one of the KM curves varies significantly from other KM curves.
Table 3.
Multivariable Cox Regression hazard ratios and 95% confidence intervals for functional decline outcomes among those with a history of cancer compared to those without a history of cancer ᶧ
| All participants |
||
|---|---|---|
| HR (95% CI) | p-value | |
|
|
||
| Weak Grip Strength | 1.5 (1.1, 1.9) | 0.003 |
| Slow Gait Speed | 1.4 (1.1, 1.6) | 0.002 |
| Participants aged >65 years |
||
| HR (95% CI) | p-value | |
|
|
||
| Weak Grip Strength | 11.9 (7.4, 19.3) | <0.001 |
| Slow Gait Speed | 4.1 (3.2, 5.1) | <0.001 |
95% CI = 95% confidence interval; HR = hazard ratio
Adjusted for sex, race, body mass index, comorbidities and education
DISCUSSION
To our knowledge, this is the first study utilizing longitudinal information to elucidate the relationship between cancer history and risk of weakness and slowness and poorer overall physical function within a cohort of otherwise healthy adults. We examined not only whether individuals with a history of cancer experience greater risk of poor physical performance, but also trajectories of functional decline in this group. Our major findings are that cancer history is associated with both a higher likelihood and faster rate of functional decline; where grip strength, gait speed, and HABC PPB were analyzed as continuous variables, the small statistically significant differences observed have also been shown in the literature to be clinically meaningful.28, 29 These findings were also consistent across all functional assessments utilized in this study, when prevalent cancers were included and excluded, and when only the four major cancer subtypes were examined.
Findings from this study provide an important step toward elucidating the impact of cancer history on the aging process and functional decline in older adults. Our findings are consistent with Gresham et al., that also used the BLSA study population and found a history of cancer to be associated with greater fatigability and poor endurance, with a significantly greater effect in older adults, compared to younger adults.15 Similarly, in a study conducted by Alibhai et al., grip strength and self-reported physical function were observed to decline as early as 3 months after starting androgen deprivation therapy (ADT) among men with nonmetastatic prostate cancer (n = 87) compared to prostate cancer patients not receiving ADT and those with no history of cancer.16 In addition, using data from the Atherosclerosis Risk in Communities (ARIC) Study (n = 1,434), Petrick et al., showed statistically significant differences in the trajectory of self-reported functional decline one- and five-years post-diagnosis among cancer survivors compared to individuals free of cancer; individuals diagnosed with lung cancer showed declines of the greatest magnitude.17 In contrast, another recent study examining change in strength and self-reported physical function from pre- to post-diagnosis among 117 men with prostate cancer found no difference in functional decline (up to 9 years follow-up) when compared to men without a history of prostate cancer; it should be noted that only a small number of prostate cancer patients received ADT in this study (n = 4).18 This inconsistency in the results examining functional decline among individuals diagnosed with cancers may be due to differences in those included in the history of cancer groups – these differences include the cancer types of the individuals enrolled, cancer treatments received, health of the study population, as well as the number of years followed and tools used to measure functional decline (self-report vs clinical assessment). Future longitudinal studies should be designed to look specifically at factors associated with clinically assessed functional decline among cancer survivors, with the goals of identifying those at highest risk for accelerated functional decline and designing interventions to prevent, reverse, or mitigate this accelerated decline. It is critical that detailed clinical and treatment information be collected in these studies.
The underlying mechanisms explaining the association between cancer history and decline in physical performance are not well understood. The impact of cancer diagnosis and treatment may significantly affect various biological processes that have implications in both cellular and functional aging. These processes, collectively referred to as “hallmarks of aging” include: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication.30, 31 These mechanisms work in synergy and, if adversely affected by cancer therapeutics, they may induce cellular responses that can accelerate accumulation of DNA damage, cell cycle arrest, expression of misfolded proteins, and increased production of reactive oxygen species.31 Therefore, it is probable that the observed relationships between cancer history and functional decline are due to adverse effects that cancer treatments have on the hallmarks of aging, although it is likely that other factors such as unhealthy lifestyle behaviors (e.g. smoking) and poor overall genetic risk profiles, also play a role.
A major strength of this study is the longitudinal design which enables us to examine risks and trajectories of decline in physical performance in a well-characterized population with and without a history of cancer. Other strengths include the relatively low percentage of participants lost to follow-up; BLSA is a stable cohort of participants dedicated to completing in-depth functional assessments and regular visits.32 This high retention rate is key for avoiding bias due to differential loss to follow-up and enhancing statistical power in longitudinal and time-to-event analyses. Further, BLSA physical performance assessments were conducted by trained personnel, following a standard set of well-validated protocols. As a result, there is a low likelihood of measurement error across all assessments.
Several limitations should be noted. BLSA is a study of normative human aging and not a study of cancer risk or survivorship. Therefore, no data were available on cancer stage, pathology, or, perhaps most importantly, treatment. Additionally, BLSA participants with a history of cancer prior to enrolling in the study (prevalent cancer cases, n = 240) were required to be cancer free for at least 10 years. Therefore, there may be potential survivor bias introduced by participants with a history of prevalent disease due to the fact that they had to survive their cancer for a number of years (10 or more for certain participants) to be enrolled into BLSA and have an “index visit”. This may impact our observations by skewing our results closer to the null. Additionally, BLSA participants are generally healthy and free from major chronic diseases upon enrollment. Therefore, the results may not be generalizable to the overall population.
The measures of physical performance utilized in this study consistently have been shown in the literature to predict functional decline, hospitalization, nursing home placement, and death among healthy individuals.25, 33–35 These tests are also relatively inexpensive, easy to administer in research, clinical and home settings and have been used in intervention studies.35 Grip strength has been shown to be associated with functional disability and has excellent reliability (ICC = 0.92) and gait speed has been shown to have well-documented predictive value for major health related outcomes including mortality.22, 36–39 Incorporating these physical performance assessments in future longitudinal studies of cancer survivors will enable researchers to better understand the impact of cancer and its treatments on trajectories of age-related functional decline.
Whether the etiology of this accelerated aging observed in our study stems from the impact of the cancer and/or its treatment and/or underlying behavioral, environmental and/or genetic risk factors for cancer remains to be interrogated. However, this study reinforces the need to develop intervention studies in order to identify strategies to prevent or mitigate cancer and treatment associated functional decline. In addition to elucidating the methodological considerations outlined in this study, strategies to incorporate interventions related to exercise therapy, nutrition, cancer-related cognitive impairment, novel pharmacological therapeutics, and supportive care,2 may help reduce the burden of cancer and its treatment.
Supplementary Material
Supplementary Table 1: Odds ratios and 95% confidence intervals for sensitivity and subgroup analyses.
Key Points:
Older cancer survivors experience accelerated functional decline, with greater risk of weak grip strength, slow gait speed, and lower overall physical performance.
Why Does This Matter?
Identifying older cancer survivors at highest risk of functional decline is critical to promoting healthy aging in this population.
ACKNOWLEDGMENTS
This research was supported entirely by the Intramural research Program of the NIH, National institute on Aging, and National Cancer Institute.
This article has not been previously published and is not being considered for publication elsewhere, in whole or in part, in any language. The corresponding author, Dr. Lisa Gallicchio, affirms that she has listed everyone who contributed significantly to the work.
Sponsor’s Role:
No sponsor.
Footnotes
Disclosures: None
We certify that this work is novel and is not under consideration for publication elsewhere.
Conflict of interest: The authors declare no conflict of interest.
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Associated Data
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Supplementary Materials
Supplementary Table 1: Odds ratios and 95% confidence intervals for sensitivity and subgroup analyses.