Long-term Trajectories of Physical Function Decline in Women With and Without Cancer

Elizabeth M Cespedes Feliciano; Sowmya Vasan; Juhua Luo; Alexandra M Binder; Rowan T Chlebowski; Charles Quesenberry; Hailey R Banack; Bette J Caan; Electra D Paskett; Grant R Williams; Ana Barac; Andrea Z LaCroix; Ulrike Peters; Kerryn W Reding; Kathy Pan; Aladdin H Shadyab; Lihong Qi; Garnet L Anderson

doi:10.1001/jamaoncol.2022.6881

. 2023 Jan 19;9(3):395–403. doi: 10.1001/jamaoncol.2022.6881

Long-term Trajectories of Physical Function Decline in Women With and Without Cancer

Elizabeth M Cespedes Feliciano ^1,^✉, Sowmya Vasan ², Juhua Luo ³, Alexandra M Binder ^4,⁵, Rowan T Chlebowski ⁶, Charles Quesenberry ¹, Hailey R Banack ^7,⁸, Bette J Caan ¹, Electra D Paskett ⁹, Grant R Williams ¹⁰, Ana Barac ¹¹, Andrea Z LaCroix ¹², Ulrike Peters ², Kerryn W Reding ¹³, Kathy Pan ⁶, Aladdin H Shadyab ¹², Lihong Qi ¹⁴, Garnet L Anderson ²

¹Kaiser Permanente Northern California Division of Research, Oakland

²Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington

³Department of Epidemiology and Biostatistics, School of Public Health, University of Indiana at Bloomington, Bloomington

⁴Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu

⁵Department of Epidemiology, University of California, Los Angeles

⁶Medical Oncology, The Lundquist Institute, Torrance, California

⁷Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, New York

⁸Epidemiology Division, University of Toronto Dalla Lana School of Public Health, Toronto, Ontario, Canada

⁹Division of Cancer Prevention and Control, College of Medicine, The Ohio State University, Columbus

¹⁰Institute for Cancer Outcomes and Survivorship, School of Medicine, The University of Alabama at Birmingham, Birmingham

¹¹Cardio-Oncology Program, MedStar Heart and Vascular Institute, Georgetown University School of Medicine, Washington, DC

¹²Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla

¹³Biobehavioral Nursing and Health Informatics, School of Nursing, University of Washington, Seattle

¹⁴Public Health Sciences, School of Medicine, University of California at Davis, Davis

Accepted for Publication: October 5, 2022.

Published Online: January 19, 2023. doi:10.1001/jamaoncol.2022.6881

^✉

Corresponding Author: Elizabeth M. Cespedes Feliciano, ScD, SM, Kaiser Permanente Northern California Division of Research, 2000 Broadway, 5th Floor, 051R16, Oakland, CA 94612 (elizabeth.m.cespedes@kp.org).

Author Contributions: Dr Anderson and Ms Vasan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Cespedes Feliciano, Vasan, Luo, Binder, Barac, Peters, Anderson.

Acquisition, analysis, or interpretation of data: Cespedes Feliciano, Vasan, Luo, Binder, Chlebowski, Quesenberry, Banack, Caan, Paskett, Williams, LaCroix, Reding, Pan, Shadyab, Qi, Anderson.

Drafting of the manuscript: Cespedes Feliciano, Vasan, Banack.

Critical revision of the manuscript for important intellectual content: Cespedes Feliciano, Luo, Binder, Chlebowski, Quesenberry, Banack, Caan, Paskett, Williams, Barac, LaCroix, Peters, Reding, Pan, Shadyab, Qi, Anderson.

Statistical analysis: Cespedes Feliciano, Vasan, Luo, Binder, Quesenberry, Banack, Williams, Shadyab, Qi.

Obtained funding: Chlebowski, Caan, Paskett, Anderson.

Administrative, technical, or material support: Banack, Paskett.

Supervision: Cespedes Feliciano, Anderson.

Conflict of Interest Disclosures: Dr Cespedes Feliciano reported grants from National Cancer Institute (NCI) and National Institute of Aging during the conduct of the study. Dr Binder reported grants from the NCI of the National Institutes of Health (NIH) under Award Number K07CA225856 during the conduct of the study. Dr Chlebowski reported grants from NCI; National Heart, Lung, and Blood Institute (NHLBI); NIH; and US Department of Health and Human Services (HHS) during the conduct of the study; and personal fees from Novartis, AstraZeneca, Genentech, Pfizer, Puma, and Amgen outside the submitted work. Dr Quesenberry reported grants from NCI during the conduct of the study. Dr Caan reported grants from NIH during the conduct of the study. Dr Paskett reported grants from Merck Foundation, Pfizer, and Genentech outside the submitted work. Dr LaCroix reported grants from NHLBI, NIH during the conduct of the study. No other disclosures were reported.

Funding/Support: Dr Cespedes Feliciano’s time was supported by a grant from the National Cancer Institute (K01CA226155). The WHI program is funded by the NHLBI, NIH, HHS through contracts N01WH22110, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, and 44221; The Women’s Health Initiative (WHI) Life and Longevity After Cancer Study (LILAC) study is funded by UM1 CA173642.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank Adam Boroian for administrative and editorial assistance. He was not compensated beyond his salary for his contributions. We thank the WHI investigators, staff, and the trial participants for their outstanding dedication and commitment. The WHI investigators: Program Office: (National Heart, Lung, and Blood Institute, Bethesda, Maryland) Jacques Rossouw, Shari Ludlam, Joan McGowan, Leslie Ford, and Nancy Geller; Clinical Coordinating Center: (Fred Hutchinson Cancer Research Center, Seattle, WA) Garnet Anderson, Ross Prentice, Andrea LaCroix, and Charles Kooperberg; Investigators and Academic Centers: (Brigham and Women's Hospital, Harvard Medical School, Boston, MA) JoAnn E. Manson; (MedStar Health Research Institute/Howard University, Washington, DC) Barbara V. Howard; (Stanford Prevention Research Center, Stanford, CA) Marcia L. Stefanick; (The Ohio State University, Columbus, OH) Rebecca Jackson; (University of Arizona, Tucson/Phoenix, AZ) Cynthia A. Thomson; (University at Buffalo, Buffalo, NY) Jean Wactawski-Wende; (University of Florida, Gainesville/Jacksonville, FL) Marian Limacher; (University of Iowa, Iowa City/Davenport, IA) Jennifer Robinson; (University of Pittsburgh, Pittsburgh, PA) Lewis Kuller; (Wake Forest University School of Medicine, Winston-Salem, NC) Sally Shumaker; (University of Nevada, Reno, NV) Robert Brunner; Women’s Health Initiative Memory Study: (Wake Forest University School of Medicine, Winston-Salem, NC) Mark Espeland. For a list of all the investigators who have contributed to WHI science, please visit: https://s3-us-west-2.amazonaws.com/www-whi-org/wp-content/uploads/WHI-Investigator-Long-List.pdf. The WHI program is funded by the NHLBI, NIH, HHS through 75N92021D00001, 75N92021D00002, 75N92021D00003, 75N92021D00004, 75N92021D00005.

^✉

Corresponding author.

PMCID: PMC9857739 PMID: 36656572

Key Points

Question

Do long-term physical function trajectories in postmenopausal women with cancer differ from before to after diagnosis, or compared with age-matched controls?

Findings

In this prospective cohort study of 9203 incident cancers and 45 358 matched controls, prediagnosis, women with local cancers had similar physical function decline to controls; women with regional stage had accelerated declines. Following diagnosis, compared with controls, survivors experienced accelerated declines that varied by type, stage, and treatment modality; survivors of cancer’s average function scores were below those of controls even several years after diagnosis.

Meaning

Survivors of cancer are at increased risk for accelerated declines following diagnosis; interventions to preserve physical functioning during and after treatment should be tested.

Abstract

Importance

Patients with cancer experience acute declines in physical function, hypothesized to reflect accelerated aging driven by cancer-related symptoms and effects of cancer therapies. No study has examined long-term trajectories of physical function by cancer site, stage, or treatment compared with cancer-free controls.

Objective

Examine trajectories of physical function a decade before and after cancer diagnosis among older survivors and cancer-free controls.

Design, Setting, and Participants

This prospective cohort study enrolled patients from 1993 to 1998 and followed up until December 2020. The Women’s Health Initiative, a diverse cohort of postmenopausal women, included 9203 incident cancers (5989 breast, 1352 colorectal, 960 endometrial, and 902 lung) matched to up to 5 controls (n = 45 358) on age/year of enrollment and study arm.

Exposures

Cancer diagnosis (site, stage, and treatment) via Medicare and medical records.

Main Outcomes and Measures

Trajectories of self-reported physical function (RAND Short Form 36 [RAND-36] scale; range: 0-100, higher scores indicate superior physical function) estimated from linear mixed effects models with slope changes at diagnosis and 1-year after diagnosis.

Results

This study included 9203 women with cancer and 45 358 matched controls. For the women with cancer, the mean (SD) age at diagnosis was 73.0 (7.6) years. Prediagnosis, physical function declines of survivors with local cancers were similar to controls; after diagnosis, survivors experienced accelerated declines relative to controls, whose scores declined 1 to 2 points per year. Short-term declines in the year following diagnosis were most severe in women with regional disease (eg, −5.3 [95% CI, −6.4 to −4.3] points per year in regional vs −2.8 [95% CI, −3.4 to −2.3] for local breast cancer) or who received systemic therapy (eg, for local endometrial cancer, −7.9 [95% CI, −12.2 to −3.6] points per year with any chemotherapy; −3.1 [95% CI, −6.0 to −0.3] with radiation therapy alone; and −2.6 [95% CI, −4.2 to −1.0] with neither, respectively). While rates of physical function decline slowed in the later postdiagnosis period (eg, women with regional colorectal cancer declined −4.3 [95% CI, −5.9 to −2.6] points per year in the year following diagnosis vs −1.4 [95% CI, −1.7 to −1.0] points per year in the decade thereafter), survivors had estimated physical function significantly below that of age-matched controls 5 years after diagnosis.

Conclusions and Relevance

In this prospective cohort study, survivors of cancer experienced accelerated declines in physical function after diagnosis, and physical function remained below that of age-matched controls even years later. Patients with cancer may benefit from supportive interventions to preserve physical functioning.

This cohort study examines long-term trajectories of physical function decline in postmenopausal women with and without cancer.

Introduction

By 2040, two-thirds of a projected 26 million survivors of cancer will be older than 65 years.^1,2 Rates of morbidity and frailty are high, and older survivors report poor physical function (PF) and reduced quality of life.^3,4,5 Aging is characterized by an accumulation of PF deficits, reflecting declines in physiological reserve that influence daily life.⁶ In short-term follow-up studies patients with cancer experience declines in PF following cancer treatment.^7,8,9,10 In cross-sectional studies, long-term survivors of cancer have poor PF and/or worse PF than age-matched controls.^{11,12,13,14,15} Deficits in PF have been associated with falls, diminished ability to live independently, and poorer self-reported health.¹⁶ Prior attempts to characterize trajectories of PF decline among survivors of cancer have been limited by: lack of prediagnosis data; short follow-up (<3 years); misalignment of measurements with time since diagnosis; small samples, often exclusively breast cancer; lack of age-matched controls to represent PF decline without cancer; and/or lack of treatment information.^{17,18,19,20,21,22,23,24,25}

To address these gaps, we leveraged the Women’s Health Initiative (WHI), a large, diverse cohort of postmenopausal women with longitudinal measures of self-reported PF collected using the RAND Short Form 36 (RAND-36), a well-validated scale.^26,27,28 We examined trajectories of PF scores over 2 decades, before and after cancer diagnosis, among women with breast, colorectal, lung, and endometrial cancer, compared with matched controls representing aging without cancer. We examined differences by cancer type, stage, treatment modality, and age at diagnosis to identify when accelerated PF declines emerged and inform future interventions to improve PF and promote healthy aging in older survivors.

Methods

Study Population

The WHI is a large, prospective study that enrolled 161 808 postmenopausal women, aged 50 to 79 years, through 40 US clinical sites between 1993 and 1998: 68 132 into clinical trials (CT) and 93 676 into an observational study (OS).²⁹ Women signed a consent form that the institutional review board at each site had approved. In 2005, 115 407 women (77% of eligible) consented to extended follow-up. In 2010, 93 567 (87%) again consented to extended follow-up, which continues to the present.

Cancer Diagnosis and Treatment

First primary, incident invasive breast, colorectal, endometrial, and lung cancers (the most common cancer sites among US women) were verified by medical record review by trained physician adjudicators at local clinical centers.³⁰ Final adjudication and coding were performed centrally following SEER rules.³¹ We limited analyses to women diagnosed with local (confined to organ) or regional (without distant spread) disease. Medical record and Medicare data were used to extract information about initial cancer treatments; where sample size allowed, treatments were categorized as: any chemotherapy, radiation therapy without chemotherapy, or neither.³²

Matching and Cohort Definition

Women diagnosed with cancer were matched with up to 5 controls on age, enrollment year, and participation in various study components (eg, trial arms). Controls were required to be alive and in active follow-up at the time of diagnosis of the matched case (referred to as index date), and cancer-free at selection (February 28, 2020). All participants had PF assessed at enrollment and 3-year follow-up. The CT participants had additional assessments at year 1, trial closeout (2002 to 2004) and at 6-year and 9-year follow-up. All WHI CT and OS participants who consented to extension studies had assessments annually after 2005. We excluded women without PF information within ±10 years of diagnosis/index date (n = 93). The analytic sample (Table 1) included 45 358 controls matched to 9203 cases of: breast (n = 5989 cases; n = 29 612 controls); colorectal (n = 1352 cases; n = 6664 controls); lung (n = 902 cases; n = 4467 controls); and endometrial cancer (n = 980 cases; n = 4615 controls).

Table 1. Characteristics of Cases and Matched Controls at Enrollment Into the Women’s Health Initiative.

Characteristic	No. (%)
	Breast cancer case status		Colorectal cancer case status		Endometrial cancer case status		Lung cancer case status
	Yes (n = 5989)	No (n = 29 612)	Yes (n = 1352)	No (n = 6664)	Yes (n = 980)	No (n = 4615)	Yes (n = 902)	No (n = 4467)
Age at diagnosis/index, mean (SD), y	72.3 (7.7)	72.3 (7.7)	75.2 (7.5)	75.1 (7.5)	72.1 (7.4)	72.0 (7.4)	75.2 (6.6)	75.1 (6.6)
BMI^b, mean (SD)	28.0 (5.8)	27.7 (5.8)	28.2 (5.7)	27.8 (5.8)	29.4 (7.2)	27.5 (5.9)	27.1 (5.6)	27.6 (5.6)
Alcohol consumption, mean (SD), servings per week	2.9 (5.5)	2.4 (4.8)	2.9 (5.8)	2.4 (4.7)	3.1 (6.6)	2.5 (4.9)	3.4 (5.7)	2.5 (4.7)
Physical activity, mean (SD), MET-h/wk	12.5 (13.0)	12.8 (13.8)	12.0 (12.8)	12.4 (13.4)	13.3 (14.1)	13.1 (13.9)	12.9 (14.7)	12.6 (13.7)
Race^c
American Indian/Alaska Native	13 (0.2)	97 (0.3)	2 (0.1)	23 (0.3)	1 (0.1)	12 (0.3)	3 (0.3)	16 (0.4)
Asian	104 (1.7)	695 (2.3)	24 (1.8)	145 (2.2)	12 (1.3)	138 (3.0)	10 (1.1)	101 (2.3)
Black	294 (4.9)	2402 (8.1)	77 (5.7)	501 (7.5)	45 (4.7)	323 (7.0)	52 (5.8)	298 (6.7)
Native Hawaiian/other PI	5 (0.1)	24 (0.1)	1 (0.1)	5 (0.1)	0	7 (0.2)	1 (0.1)	1 (<0.1)
White	5465 (91.3)	25 589 (86.4)	1211 (89.6)	5823 (87.4)	892 (92.9)	4017 (87.0)	823 (91.2)	3950 (88.4)
More than 1 race	65 (1.1)	355 (1.2)	19 (1.4)	78 (1.2)	5 (0.5)	54 (1.2)	10 (1.1)	58 (1.3)
Unknown/not reported	43 (0.7)	450 (1.5)	18 (1.3)	89 (1.3)	5 (0.5)	64 (1.4)	3 (0.3)	43 (1.0)
Ethnicity^c
Hispanic/Latina	133 (2.2)	1199 (4.0)	32 (2.4)	238 (3.6)	14 (1.5)	189 (4.1)	20 (2.2)	152 (3.4)
Not Hispanic/Latina	5834 (97.4)	28 279 (95.5)	1315 (97.3)	6393 (95.9)	943 (98.2)	4389 (95.1)	875 (97.0)	4300 (96.3)
Unknown/not reported	22 (0.4)	134 (0.5)	5 (0.4)	33 (0.5)	3 (0.3)	37 (0.8)	7 (0.8)	15 (0.3)
Highest education level
0-8 y	27 (0.5)	428 (1.5)	11 (0.8)	96 (1.4)	5 (0.5)	63 (1.4)	8 (0.9)	40 (0.9)
Some high school	117 (2.0)	955 (3.2)	42 (3.1)	246 (3.7)	24 (2.5)	127 (2.8)	30 (3.4)	137 (3.1)
High school diploma/GED	830 (13.9)	4942 (16.8)	236 (17.5)	1223 (18.5)	125 (13.1)	665 (14.5)	163 (18.2)	792 (17.8)
School after high school	2109 (35.4)	10 993 (37.4)	526 (39.1)	2503 (37.8)	305 (32.0)	1642 (35.8)	349 (39.0)	1683 (37.9)
College degree or higher	2872 (48.2)	12 071 (41.1)	531 (39.5)	2556 (38.6)	495 (51.9)	2094 (45.6)	344 (38.5)	1787 (40.3)
Missing	34 (0.6)	223 (0.8)	6 (0.4)	40 (0.6)	6 (0.6)	24 (0.5)	8 (0.9)	28 (0.6)
Diabetes (treated with pills or shots)	175 (2.9)	1088 (3.7)	77 (5.7)	272 (4.1)	37 (3.9)	154 (3.3)	42 (4.7)	181 (4.1)
Smoking status
Never	2846 (48.2)	15 395 (52.6)	661 (49.8)	3508 (53.2)	515 (54.2)	2326 (51.0)	145 (16.2)	2355 (53.3)
Past	2700 (45.7)	12 147 (41.5)	573 (43.2)	2741 (41.5)	389 (40.9)	1930 (42.4)	525 (58.7)	1829 (41.4)
Current	363 (6.1)	1732 (5.9)	92 (6.9)	349 (5.3)	47 (4.9)	301 (6.6)	224 (25.1)	238 (5.4)
Missing	80 (1.3)	338 (1.1)	26 (1.9)	66 (1.0)	9 (0.9)	58 (1.3)	8 (0.9)	45 (1.0)
CT trial participant^a	2707 (45.2)	13 294 (44.9)	671 (49.6)	3284 (49.3)	417 (43.4)	1945 (42.1)	422 (46.8)	2075 (46.5)
Hormone therapy trial participant^a	919 (15.3)	4472 (15.1)	292 (21.6)	1420 (21.3)	131 (13.6)	598 (13.0)	200 (22.2)	978 (21.9)
Long life study participant^a	392 (6.5)	1741 (5.9)	100 (7.4)	435 (6.5)	47 (4.9)	171 (3.7)	52 (5.8)	237 (5.3)

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Abbreviations: BMI, body mass index; CT, chemotherapy; GED, General Educational Development; MET, metabolic equivalents task; PI, Pacific Islander.

^{^a}

Matching factors are indicated; missing data was accounted for in multivariable models using an indicator.

^{^b}

Body mass index was calculated as weight in kilograms divided by height in meters squared.

^{^c}

Race and ethnicity were participant reported within National Institutes of Health categories.

Outcome and Covariate Assessment

Physical Function

Physical function was assessed using a 10-item RAND-36 scale, a well-validated assessment of self-reported PF that has been used to measure mobility disability in various populations, including survivors of cancer, and is associated with biological aging, predictive of outcomes such as falls and mortality, and sensitive to changes including after surgery or chemotherapy.^{26,27,28,33,34,35,36,37,38} The scale (range: 0-100) includes general domains of moderate/vigorous activities (2 items), strength (4 items), walking abilities (3 items), and self-care (1 item), with higher scores indicating superior PF.

Covariates

All models adjusted for matched set, age (centered at index date), WHI participation status (eg, CT/OS, long-life study), and potential confounders at enrollment, including: socioeconomic status (participant-reported race, ethnicity and education); lifestyle (smoking, alcohol consumption, total energy from recreational physical activity in metabolic equivalents task hours per week); treated diabetes history; and body mass index (BMI, calculated as weight in kilograms divided by height in meters squared with weight and height measured by standardized procedures).

Statistical Analysis

We calculated descriptive characteristics at enrollment for cases and controls. Our model was designed to test whether survivors of cancer experience a phase shift (short-term drop in PF followed by continued decline similar to the rate observed prediagnosis or in cancer-free controls) vs accelerated functional aging (an increasingly steep long-term decline), something no prior study has examined.³⁹ Using separate linear mixed effects models to estimate trajectories of PF decline in each cancer type, we parameterized time as a piecewise linear spline in years relative to index date (time t = 0). Models included knots (slope changes) at time t = 0 and at time t = 1, enabling us to test for differences in the preindex, short-term postindex and long-term postindex rates of PF decline. The linear mixed effect model allowed for separate (fixed) intercepts and slopes for each of the 3 predefined time intervals as well as random effects within matched sets for each covariate. We compared differences in the slope of PF decline between cases and controls within time intervals by testing interactions between the fixed time period variable and case/control status. We reported the estimated slopes for each of the 3-time intervals. Missing indicators were used for categorical (~1%) and mean imputation for continuous variables (~5%). Subgroup analyses examined cases according to stage, treatment type, and age at index date within cancer stage.

To assess how death from rapidly fatal cancers (eg, regional lung) impacted rates of PF decline, we reported short and long-term slopes restricting to, first, cases who remained alive and in active follow-up for at least 5 years, and separately, cases who died within 5 years while in active follow-up. In the latter model, follow-up was truncated at 5 years postindex date for both cases and controls. For both models, cases were required to contribute at least 1 PF measurement following the index date, and controls were assigned to their respective cases.

All analyses used SAS statistical software, version 9.4 (SAS Institute Inc). All tests were 2-sided, with a significance threshold of <.05.

Results

This study included 9203 women with cancer and 45 358 matched controls. For the women with cancer, the mean (SD) age at diagnosis was 73.0 (7.6) years. Descriptive characteristics at enrollment are outlined in Table 1. In general, cases were more likely to be non-Hispanic White, to be current or past smokers, and to have had slightly higher alcohol consumption. With the exception of lung cancer, cases were more likely to be college educated with slightly higher BMI. Mean age at diagnosis was 72 years for breast and endometrial and 75 years for colorectal and lung cancer cases. Nearly half of colorectal and lung cancers were diagnosed at regional vs local stages (49% and 47% of these cancers were regional, respectively), compared to a much smaller proportion of breast and endometrial cancers (24% and 16% of these cancers were regional, respectively); correspondingly, rates of chemotherapy use also differed by cancer type (eTable 1 in the Supplement).

With respect to the distribution of repeated measurements, 71% of breast, 70% of colorectal, 67% of endometrial, and 72% of lung cancer cases had at least 2 measurements before and at least 2 measurements after cancer diagnosis/index date (eTable 2 in the Supplement). In each cancer type, the median (IQR) number of measurements prediagnosis was at least 2 (3) and the median number postdiagnosis measurements was 5 (5), with half of participants contributing at least one measurement within one year of diagnosis. eFigure 1 in the Supplement illustrates individual variation in estimated PF trajectories from a random sample of survivors of cancer with repeated measurements.

The proportion of cases and controls who were alive and in active follow-up declined over time (eTable 2 in the Supplement). Attrition by 5 years postindex was most severe among regional lung cancer cases (only 29% alive and in active follow-up vs 74% of controls) and least severe among local breast cancer cases (86% alive and in active follow-up vs 76% of controls).

For most cancer types, there was no difference in mean PF at index date between women with cancer and cancer-free controls. By contrast, women newly diagnosed with lung cancer had lower PF: compared with controls (mean PF = 62 points; 95% CI, 56 to 67), PF scores were 4 points lower (95% CI, −7 to −2) in women with local and 5 points lower (95% CI, −7 to −2) in women with regional lung cancer, respectively (Table 1; eTable 1 in the Supplement).

Trajectories of Physical Function Decline in Regional and Lung Cancers Before Diagnosis

In multivariable-adjusted models, the rate of decline in PF was approximately 1 point-per-year among cancer-free controls (Table 2, Figure; eFigure 2 in the Supplement) as has been observed in other studies of older women.⁴⁰ Even prior to diagnosis, the rate of PF decline was significantly accelerated among women with lung or regional colorectal and endometrial cancer relative to controls (eTable 3 in the Supplement). For other cancers, preindex declines did not differ between cases and their matched controls.

Table 2. Rate of Change in Physical Function Scores per Year by Time Period and Cancer Type and Stage^a.

Characteristic	Slope estimate (95% CI)
Characteristic	Breast	Colorectal	Endometrial	Lung
Local cases
Prediagnosis	−1.01 (−1.10 to −0.92)	−1.25 (−1.50 to −1.01)	−1.10 (−1.32 to −0.89)	−1.46 (−1.72 to −1.20)
Early postdiagnosis	−2.81 (−3.36 to −2.27)	−2.12 (−3.62 to −0.62)	−2.95 (−4.26 to −1.64)	−5.60 (−7.40 to −3.80)
Later postdiagnosis	−1.43 (−1.53 to −1.33)	−1.57 (−1.87 to −1.28)	−1.48 (−1.73 to −1.24)	−2.46 (−2.86 to −2.06)
Regional cases
Prediagnosis	−1.11 (−1.28 to −0.94)	−1.56 (−1.81 to −1.31)	−1.66 (−2.12 to −1.20)	−1.57 (−1.88 to −1.26)
Early postdiagnosis	−5.33 (−6.36 to −4.30)	−4.28 (−5.94 to −2.61)	−9.60 (−12.59 to −6.61)	−15.22 (−17.58 to −12.86)
Later postdiagnosis	−1.21 (−1.41 to −1.01)	−1.39 (−1.74 to −1.03)	−1.15 (−1.81 to −0.49)	−1.38 (−1.99 to −0.76)
Controls
Preindex date	−1.02 (−1.05 to −0.98)	−1.22 (−1.30 to −1.14)	−1.03 (−1.12 to −0.94)	−1.14 (−1.23 to −1.05)
Early postindex date	−1.35 (−1.58 to −1.13)	−1.55 (−2.05 to −1.05)	−1.55 (−2.12 to −0.98)	−1.90 (−2.49 to −1.31)
Later postindex date	−1.48 (−1.52 to −1.44)	−1.79 (−1.89 to −1.69)	−1.54 (−1.65 to −1.42)	−1.78 (−1.90 to −1.66)

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^{^a}

Time t = 0 is the index date or time of diagnosis for the case; the prediagnosis or preindex date time period is defined −10≤t<0, whereas the early postdiagnosis or early postindex date time period is defined as 0≤t<1 and the later postdiagnosis or later postindex period time is defined as 1≤T≤10.

Profound Short-term Declines in Physical Function After Diagnosis

Cancer diagnosis served as an inflection point, after which survivors experienced accelerated decline of PF relative to the prediagnosis rate among cases and to the postindex rate among age-matched controls (Table 2 and Table 3, Figure; eTables 3-6 in the Supplement).

Table 3. Rate of Change in Physical Function Scores per Year by Time Period, Cancer Type, Stage, and Initial Treatment Type^a.

Characteristic	Slope estimate (95% CI)
Characteristic	Breast	Colorectal^b	Endometrial	Lung
Local cases
No chemotherapy or radiation therapy
No.	1276	590	536	341
Prediagnosis	−1.31 (−1.48 to −1.15)	−1.23 (−1.49 to −0.96)	−0.95 (−1.22 to −0.68)	−1.38 (−1.69 to −1.06)
Early postdiagnosis	−3.54 (−4.54 to −2.54)	−1.92 (−3.52 to −0.32)	−2.61 (−4.23 to −0.99)	−5.39 (−7.46 to −3.31)
Later postdiagnosis	−1.54 (−1.74 to −1.33)	−1.70 (−2.02 to −1.38)	−1.28 (−1.58 to −0.98)	−2.49 (−2.93 to −2.05)
Radiation therapy without chemotherapy
No.	2452	NA	164	60
Prediagnosis	−0.84 (−0.96 to −0.71)	NA	−1.14 (−1.60 to −0.68)	−1.95 (−2.63 to −1.28)
Early postdiagnosis	−2.63 (−3.38 to −1.89)	NA	−3.12 (−5.97 to −0.26)	−6.89 (−12.13 to −1.64)
Later postdiagnosis	−1.47 (−1.60 to −1.34)	NA	−2.11 (−2.68 to −1.55)	−3.24 (−4.98 to −1.50)
Any chemotherapy
No.	701	73	59	57
Prediagnosis	−0.90 (−1.14 to −0.65)	−1.35 (−2.11 to −0.60)	−0.95 (−1.63 to −0.26)	−1.51 (−2.31 to −0.71)
Early postdiagnosis	−2.54 (−3.98 to −1.10)	−3.04 (−7.94 to 1.86)	−7.89 (−12.19 to −3.59)	−7.65 (−13.22 to −2.08)
Later postdiagnosis	−1.04 (−1.29 to −0.78)	−0.78 (−1.70 to 0.15)	−2.16 (−3.08 to −1.23)	−2.03 (−3.25 to −0.80)
Regional cases
No chemotherapy or radiation therapy
No.	177	242	24	119
Prediagnosis	−1.55 (−1.98 to −1.12)	−1.76 (−2.15 to −1.36)	−2.29 (−3.72 to −0.86)	−1.88 (−2.44 to −1.31)
Early postdiagnosis	−4.08 (−6.81 to −1.35)	−1.39 (−4.09 to 1.30)	−2.90 (−10.84 to 5.04)	−6.06 (−10.10 to −2.03)
Later postdiagnosis	−1.75 (−2.32 to −1.19)	−2.02 (−2.63 to −1.42)	−0.93 (−2.50 to 0.63)	−1.88 (−2.82 to −0.95)
Radiation therapy without chemotherapy
No.	304	NA	71	40
Prediagnosis	−1.21 (−1.54 to −0.88)	NA	−1.07 (−1.78 to −0.35)	−0.95 (−1.99 to 0.08)
Early postdiagnosis	−4.29 (−6.29 to −2.29)	NA	−7.14 (−11.73 to −2.56)	−14.87 (−24.52 to −5.21)
Later postdiagnosis	−1.65 (−2.07 to −1.24)	NA	−1.93 (−2.87 to −0.98)	−2.26 (−4.71 to 0.20)
Any chemotherapy
No.	841	387	55	224
Prediagnosis	−0.88 (−1.11 to −0.64)	−1.33 (−1.68 to −0.99)	−1.77 (−2.45 to −1.08)	−1.45 (−1.86 to −1.03)
Early postdiagnosis	−5.93 (−7.33 to −4.54)	−5.78 (−7.96 to −3.59)	−14.67 (−19.35 to −9.99)	−19.77 (−22.91 to −16.63)
Later postdiagnosis	−0.89 (−1.14 to −0.65)	−1.15 (−1.59 to −0.70)	−0.27 (−1.43 to 0.90)	−1.12 (−2.00 to −0.24)
Controls
No.	29 430	6613	4615	4422
Preindex date	−1.02 (−1.05 to −0.98)	−1.22 (−1.30 to −1.14)	−1.03 (−1.12 to −0.94)	−1.14 (−1.23 to −1.05)
Early postindex date	−1.36 (−1.58 to −1.13)	−1.55 (−2.05 to −1.05)	−1.56 (−2.13 to −0.99)	−1.91 (−2.49 to −1.32)
Later postindex date	−1.48 (−1.52 to −1.44)	−1.78 (−1.89 to −1.68)	−1.54 (−1.65 to −1.42)	−1.78 (−1.90 to −1.66)

Open in a new tab

Abbreviation: NA, not applicable.

^{^a}

In general, the model for PF score for the i^th person at the j^th time point, Y_ij, was: Y_ij = β₀ + β₁*case_i + β₂*T_ij + β₃*T1_ij + β₄*T2_ij + β₅*case_i*T_ij + β₆*case_i*T1_ij + β₇*case_i*T2_ij + Covariates + b0_i + b1_i*T + b2_i*T1 + b3_i*T2 + e_ij, where T is years from index date, T1 is years postindex date if 0≤T≤10 and 0 otherwise; T2 is (years postindex date – 1) if 1≤T≤10 and 0 otherwise. β₀ through β₇ are the fixed effects’ coefficients, b0_i through b3_i are the random effect coefficients for the i^th individual.

^{^b}

Due to the small sample size for colorectal cancer patients undergoing radiation therapy without chemotherapy (n = 62 [11 cases and 51 matched controls]), these patients were excluded from analysis for this cancer type.

Declines in the first year following cancer diagnosis were most severe in women with regional disease or who received systemic therapy (Table 3; eFigure 2 in the Supplement); eg, among women with regional breast cancer, the rate of PF decline was nearly 4 times the rate in controls at −5.3 (95% CI, −6.4 to −4.3) points per year immediately following diagnosis, representing a 4-point acceleration on the prediagnosis rate. Among women with local breast cancer, the rate of decline was smaller immediately following diagnosis at −2.8 (95% CI, −3.4 to −2.3) points per year, but double the rate among controls and representing a statistically significant acceleration of 2 points per year on the prediagnosis rate for cases. Following diagnosis of local endometrial cancer, the rate of PF decline in women who received chemotherapy accelerated by nearly 7 points to −7.9 (95% CI, −12.2 to −3.6) points per year on the prediagnosis slope (5 times the rate among controls over the same period), whereas women receiving radiation therapy alone declined −3.1 (95% CI, −6.0 to −0.3) points per year (twice as fast as controls, but not statistically different from the prediagnosis slope), and women who received neither chemotherapy nor radiation therapy declined −2.6 (95% CI, −4.2 to −1.0) points per year.

Long-term Trajectories of Physical Function After Diagnosis

While long-term PF declines continued in the later postdiagnosis period, the rate of decline slowed, eg, women with regional colorectal cancer declined −4.3 (95% CI, −5.9 to −2.6) points per year in the year immediately following diagnosis (tripling the prediagnosis rate of decline), which then slowed thereafter to a rate similar to that observed prediagnosis (−1.4 [95% CI, −1.7 to −1.0] points/y) and among controls. However, these initial accelerations meant that survivors of most cancer types had estimated PF significantly below that of age-matched controls even at 5 years postdiagnosis (Figure): eg, compared with age-matched controls at 5 years postindex date, PF scores were −0.9 (95% CI, −1.7 to −0.2) and −3.6 (95% CI, −4.9 to −2.4) points lower for survivors of local and regional breast cancer, respectively, representing accelerated functional aging of approximately 1 and 3 years, respectively. Similar results were observed in survivors of endometrial cancer where at 5 years postindex PF scores were estimated to be −2.0 (95% CI, −3.8 to −0.3) points lower in local and −7.1 (95% CI, −11.0 to −3.2) points lower in regional cases relative to cancer-free controls.

While the estimated rate of long-term PF decline after cancer diagnosis was greater for older survivors of cancer (aged ≥70 vs <70 years at diagnosis; eTable 3 in the Supplement), the short-term acceleration was similar: eg, survivors of local endometrial cancer in both age groups had an estimated short-term acceleration in the rate of decline of 2 points per year on their prediagnosis rate in the first year following cancer diagnosis.

Sensitivity Analyses

Women who died within 5 years of cancer diagnosis experienced dramatic declines in PF in the year following diagnosis (eg, short-term rate of decline of −6.2 [95% CI, −8.8 to −3.6] points per year for women with regional breast cancer, eTable 4 in the Supplement). By contrast, restricting to survivors who remained alive and in active follow-up for at least 5 years, the short-term rate of PF was less dramatic (−3.6 [95% CI, −5.7 to −1.4] points per year for women with regional breast cancer who survived longer than 5 years, eTable 4 and eFigure 3 in the Supplement) and not statistically different from the prediagnosis rate (difference −2.2 [95% CI, −4.5 to 0.1]; P = .06). However, longer-term rates of PF decline (from 1 to 10 years after diagnosis) were significantly accelerated in these long-term survivors, resulting in estimated PF significantly below that of cancer-free controls even 5 years after diagnosis (eg, compared with controls, regional breast cancer cases’ PF was −6.0 [95% CI, −8.3 to −3.6] points lower and local breast cancer cases’ PF was −5.5 [95% CI, −6.9 to −4.1] points lower).

Discussion

This large cohort study of postmenopausal women followed up for 2 decades provides evidence for accelerated functional aging following cancer diagnosis. For survivors of some cancer types (often with regional disease), PF decline accelerated even before diagnosis. In the first year following diagnosis, we found profound, short-term accelerations in PF decline among survivors with regional disease and/or treated with chemotherapy, as expected. Importantly, we also found accelerated longer-term rates of decline that varied by cancer type, treatment, and stage: some survivors (eg, colorectal cancer) had estimated PF similar to age-matched controls by 5 years after diagnosis, while other groups (eg, breast, endometrial, and especially lung cancer) had significant deficits in PF even 5 years after cancer diagnosis. These differences persisted even when analyses were restricted to women who survived at least 5 years. Overall, survivors of cancer experienced declines in PF that accelerated from prediagnosis to postdiagnosis at a rate faster than among age-matched controls. Older survivors with regional cancer may be among the most vulnerable in need of supportive interventions.

By taking a longitudinal approach, our matched cohort enhances the findings of prior cross-sectional studies demonstrating lower PF in survivors of cancer vs controls at a single time point and prior short-term and/or case-only studies simply illustrating a drop in PF from precancer to postcancer treatment.^{17,18,19,20,21,22,23,24,25,41,42} Our results also expand on previous studies that examined trajectories of PF in cancer cases and matched controls, eg, in the Atherosclerosis Risk in Communities Study, self-reported PF declined in the year following diagnosis among incident cancer cases compared with cancer-free controls, and PF continued to decline beyond 1 year after lung or colorectal cancer diagnosis.⁴³ Results from the Health ABC Study examining trajectories of grip strength (an objective measure of PF) found pronounced declines among metastatic cases; however, the sample size was not sufficient to examine differences by treatment modality or the timing of PF changes.²⁵ In the Study of Osteoporotic Fractures, grip strength and gait speed declined significantly faster in breast cancer cases than controls, whereas quadriceps’ strength decreased acutely and then improved; no information was available on cancer treatment.¹⁹

There are several potential explanations for the accelerated rate of PF decline among women with regional disease and/or who received chemotherapy. Women with regional disease are likely to have more symptoms from their underlying cancer than women with local disease, leading to cancer-related fatigue, deconditioning, and impaired PF. Even for local cancers, adverse events involving chemotherapy, including fatigue, nausea, and neuropathy, affect a woman’s ability to function physically. This adverse influence was seen in both the short-term, and, in many, in the long-term as well (PF scores were significantly below those of cancer-free women after 5 years). While mediating mechanisms are not well understood, evidence suggests that cancer treatments result in lasting functional aging deficits in part due to biological changes such as cellular senescence, stem cell exhaustion, DNA damage, and epigenetic alterations.^44,45

Strengths and Limitations

This longitudinal study has strengths including a median of 7 serial measures of PF using a validated metric over 2 decades, before and after cancer diagnosis, on 9203 incident cancer cases matched to up to 5 cancer-free controls. This large sample enabled us to disaggregate trajectories of PF within cancer type by stage and treatment modality. Finally, our mixed effects modeling framework is robust to missing and unevenly spaced data; the inclusion of slope changes enabled us to test something no prior study has examined—whether survivors of cancer experienced a phase shift (a trajectory that starts with a short-term, fast drop in PF, followed by a continuous gradual decline) vs an accelerated functional aging trajectory (progressively accelerated long-term decline).³⁹

This work has limitations. Generalizability to younger patients and men must be verified. Treatment information was limited to initial management of local/regional disease without accounting for recurrence, progression or second cancers, and treatment choices were likely informed by women’s PF, supported by our finding that regional cases without chemotherapy or radiation therapy have the poorest PF. A limitation inherent to studying long-term survivors of cancer is that findings may reflect differences in health characteristics from women who died; in lethal cancers like lung where a minority are alive by year 5 after diagnosis this bias may be large.⁴⁶ Yet, when we examined declines in PF restricted to women who remained alive and in active follow-up for at least 5 years following diagnosis, we still found evidence of accelerated long-term rates of PF decline.

Conclusions

In this large, prospective cohort study, postmenopausal women with cancer experience accelerated declines in PF before and following diagnosis. After diagnosis, at a much faster rate than before diagnosis, women with lung cancer, regional disease, and/or undergoing chemotherapy treatment experience dramatic declines in PF. Yet, even in local disease, accelerated declines led to PF below that of age-matched peers without cancer even 5 years later. Overall, and in the long-term, postmenopausal survivors of cancer have diminished PF compared with matched controls. This information can inform management decisions in postmenopausal women with common cancers. Future studies to define predictors of PF trajectories could inform identification of populations for early interventions to mitigate PF decline.

Supplement.

eFigure 1. Examples of Trajectories of Physical Function from Pre- to Post-Diagnosis in Individual Women with Cancer

eFigure 2. Long-term Trajectories of Physical Function in Women with and without Cancer by Initial Treatment Modality

eFigure 3. Long-term Trajectories of Physical Function from Pre- to Post-Index Date in Long-term Survivors

eTable 1. Cancer-Specific Characteristics by Cancer Type

eTable 2. Mean RAND-36 Physical Function Scores and Number Surviving by Years since Index Date

eTable 3. Fixed Effects Coefficients for Association of Cancer Diagnosis with Rate of Change in Physical Function

eTable 4. Rate of Change in Physical Function Scores per Year by Time Period and Age at Diagnosis

eTable 5. Rate of Change in Physical Function Scores per Year by Time Period and Vital Status at 5 years Post-diagnosis

eTable 6. Fixed Effects Coefficients for Association of Cancer Diagnosis with Rate of Change in Physical Function Scores by Cancer Type and Initial Treatment Modality

Click here for additional data file.^{(464.6KB, pdf)}

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