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Frailty indicators and functional status in older patients after colorectal cancer surgery
Journal of Geriatric Oncology
The number of older survivors from colorectal cancer is increasing, but little is known regarding long-term consequences of cancer treatment in this patient group. Physical function is an important outcome for older patients, affecting both autonomy and quality of life. We aimed to investigate physical function in older patients with colorectal cancer before and after surgery, and to examine the role of individual frailty indicators as predictors of functional decline.
Material and Methods
We present 16–28
Eighty-four patients were included and the median age was 82
In our population of older patients with surgically treated colorectal cancer, there was a significant decline in ADL- and IADL-scores at follow-up. No change was found in TUG or grip strength, and frailty indicators did not predict decline in physical function.
Keywords: Colorectal cancer, Frailty, Physical function, Geriatric oncology, Geriatric surgery, Older cancer patients.
Colorectal cancer is one of the most common cancer types. In Norway, approximately 85% of patients are older than 60
In geriatric oncology, the use of a Geriatric Assessment (GA) is suggested to aid clinicians when caring for older patients with cancer.2 A GA generally includes evaluation of comorbid conditions, medications, physical function, nutrition, depression, cognitive function and social support, and may detect unknown – and possibly reversible – health problems.3 and 4 A systematic review from 2012 concluded that conducting a GA is feasible in the heterogeneous population of older patients with malignant disease, though studies investigating targeted interventions based on a GA are scarce.5 Furthermore, little is known about the possible predictive role of a GA with regards to long-term outcomes after cancer treatment.
The GA may serve as an approach to identifying frailty in an older individual.6 Frailty is defined as a state of increased vulnerability towards stressors, and several ways to measure frailty in clinical practice have been proposed. Among the definitions of frailty, the “frailty phenotype”, and the “accumulation of deficits”, developed by Fried et al. and Rockwood et al., respectively, are widely used.7 and 8 It is hypothesized that activation of inflammatory pathways and of the coagulation system contributes to the pathogenesis of frailty, and markers of inflammation such as C-reactive protein (CRP) and interleukin-6 (IL-6) have been linked to different frailty measures.9, 10, and 11 Identifying frailty in older patients with cancer may be relevant in order to optimize treatment and predict treatment outcomes. We have previously shown that frailty as determined by a GA can predict postoperative complications in older patients undergoing elective surgical resections of colorectal cancer, and that IL-6 is an independent predictor of postoperative complications in the same patient population.12 and 13
While several authors have dealt with postoperative mortality and morbidity after colorectal cancer surgery in older patients, only a few studies have investigated consequences for immediate and long-term functional status in this patient population. We therefore conducted a longitudinal study of older patients with colorectal cancer in order to describe and compare their physical function before and after elective surgery. Further, we explored the impact of the following variables on functional outcomes: individual frailty indicators, inflammatory biomarkers, and the occurrence of postoperative complications.
2. Material and Method
The study was approved by the Regional Committee for Medical and Health Research Ethics in Eastern Norway. All patients provided a written informed consent.
The patients were recruited from an observational prospective cohort study evaluating predictors of postoperative complications in older patients with colorectal cancer.12 All participants were aged ≥
Preoperative blood samples were collected and serum was obtained by centrifugation at 3400–3700
Patients from the original study were consecutively contacted by post and telephone in order to inform them about the follow-up study. Patients who consented to participation received a home visit from the head researcher (BR) between 16 and 28
3. Statistical Approach and Definition of Cut-off Values
Non-parametric statistical methods were applied due to skewed distribution of most variables. To determine significant changes in functional measure scores before surgery and at follow-up, the Wilcoxon signed rank test was used. Exploratory analyses indicated that there was no homogeneous relationship between preoperative frailty indicators and the odds of certain postoperative functional outcomes. Accordingly, the requirements for analyzing the explanatory variables as continuous were not fulfilled. We therefore dichotomized our variables and built logistic regression models.
From a clinical point of view, it is very important whether a patient's functional performance has deteriorated or remained stable. Accordingly, the Barthel-score, NEADL-score, time to complete TUG, and grip strength at follow-up were all dichotomized into whether or not the individual's performance had decreased from the pre-operative measurements. These were our primary endpoints. We were not able to find validated cut-offs for clinically significant changes in the chosen assessment tools. Thus, for the Barthel-index, a one-point reduction led to categorization in the reduced group. For NEADL-score, a four-point reduction was set as the cut-off, representing loss of independence in one of the measured activities. TUG-scores were dichotomized into an increase of 1
A number of explanatory variables representing frailty indicators are presented in Table 1, and were created as follows: age was dichotomized into groups of under 80
|Tumor stage||0–II vs. ≥
|ASA-score||1–2 vs. >
|Frailty||Non-frail vs. frail||GA|
|ADL-function||Not dependent (≥
|IADL-function||Not dependent (≥
|Cognitive function||Above median (≥
|Malnutrition||No risk (≥
|Depression||No risk (<
|Comorbidity||Low grade vs. high grade comorbidity||CIRS|
|Self-reported exhaustion||Not present vs. present||EORTC- QLQ C30|
|Grip strength||Above vs. below age- and gender-specific cut-off||Reference values8|
|Performance status||0–1 vs. 2–3||ECOG PS|
|CRP||Below vs. above 25th percentile|
|IL-6||Below vs. above median|
|Postoperative complications||Not present vs. present|
|Severe postoperative complications||Not present vs. present|
We were not able to find validated cut-off criteria for low-grade elevation in the inflammatory biomarkers CRP and IL-6. Based on preliminary distribution analyses we dichotomized into values below/above the 25th percentile (3.0
All analyses were performed using SPSS 19.0 software (Chicago, IL).
A total of 84 patients (46% of those included at baseline, 69% of those eligible for participation) were included, 34 (41%) men and 50 (59%) women. Only one patient lived in an institutional care facility. Median age was 82
Comparisons of pre- and postoperative functional measures are displayed in Table 2. We found a statistically significant decrease in Barthel- and NEADL-scores from the preoperative to the postoperative condition (p
|At baseline||At baseline, only patients included in follow-up||At follow-up||Mean change (SD)||p-Valuea|
|Median (IQR)||20 (19–20)||20 (19–20)||20 (18–20)||(1.3)|
|Median (IQR)||58 (48–63)||60 (51–63)||52 (41–58)||(9.2)|
|Median (IQR)||12 (8–17)||13 (8–16)||11 (8–17)||(17.8)|
|Grip strength b|
|Median (SD)||29.4 (9.9)||29.5 (9.1)||29 (13)||(6.5)|
a By the Wilcoxon signed rank test.
The results from bivariate logistic regression analyses are shown in Table 3. In total, 26 (31%) patients had lost ADL-function as measured by the Barthel-index, and in 58 (69%) patients the IADL-function had decreased. For TUG, 15 patients (39%) performed poorer at follow-up than at baseline, and 15 (38%) had lower grip strength.
|Barthel decreased (N
||NEADL decreased (N
||TUG increased (N
||Grip strength decreased (N
|N||OR||95% CI||N||OR||95% CI||N||OR||95% CI||N||OR||95% CI|
|Low grip strength||1||0.3||0.1–2.8||2||0.2||0.1–1.7||0||NA||NA||1||0.3||0.1–3.2|
|ECOG PS 2–3||6||1.4||0.5–4.4||10||0.7||0.2–2.2||2||0.2||0.1–1.3||6||3.0||0.7–13.4|
There was a statistically significant association between postoperative complications and decreased grip strength at follow-up; however, we were not able to identify any predictors of poorer functional outcome. We also performed linear regression models using the degree of change in the outcomes as continuous variables, but with this strategy we were still unable to identify significant associations between our explanatory variables and the outcome variables (data not shown).
In our group of 84 patients with surgically treated colorectal cancer, we found a significant reduction in ADL and IADL scores from the preoperative to the postoperative state. Approximately one-third of the patients had lost ADL-function, while two-thirds had lost IADL-function. We found no change in the physical performance measures i.e. TUG and grip strength. Except for the occurrence of any postoperative complication, our chosen explanatory variables, which mainly represented frailty indicators, were not able to predict a postoperative decline in functional outcome.
Though statistically significant, the reduction in primary ADL performance was small and hardly clinically relevant, and more than half the patients still had a maximum Barthel-score at follow-up. However, a one-point decline in ADL-score as measured by the Barthel-index may represent a substantial impact on an individual's functional dependency. There was a somewhat larger decline in instrumental ADL, indicating that complex activities were affected to a higher degree than basic daily functions. No reduction in TUG or grip strength was identified. Psychological and social factors may contribute to a patient's understanding of his or her health and functional status, making objective measures insufficient in assessing physical function.
These findings are overall in concordance with other studies. Amemiya et al. found that only a small fraction of patients over 75
When exploring frailty indicators and postoperative complications as predictors of functional outcomes, we did not find any significant associations. No consensus has to date been reached on what truly constitutes frailty as a concept or syndrome. This is the reason why we chose to explore individual frailty markers. However, most of our hypothesized frailty indicators are included in one or more frailty definitions, and it was surprising that no predictive values were identified. We cannot exclude inclusion-bias, as it is possible that better or poorer physical function affected patients' acceptance of participation. It is also a possibility that the preoperative frailty indicators were associated with mortality before follow-up. If this is true, our population was pre-selected, and we plan to further investigate these issues with a study of the association between frailty indicators and long-term survival at a later time.
Some of the chosen frailty indicators showed non-significant trends towards poorer functional outcome at follow-up, and we cannot rule out that there is an association between frailty markers and functional outcomes that fails to show because of the limited sample size (type II error). We were only able to include 84 of the original population of 182 patients, because 26% were dead and 31% of those eligible for inclusion denied participation. Predictors of early (median 20
We chose to create patient groups based on dichotomization, but the lack of statistically significant associations was confirmed in linear regression analyses. Another explanation is that our proposed frailty indicators may in fact not be related to the development of reduced physical function in this patient population. Identifying frailty might be more useful when planning health services, deciding treatment intensity, and optimizing pre- and postoperative care, than for the prediction of long-term functional outcomes. For instance, a recent paper concluded that the frailty phenotype predicted postoperative complications and length of stay, as well as discharge to a skilled or assisted-living facility in patients over 65
A strength of the study is the use of both functional status and physical performance measures as outcome variables. Our data represent an important addition to current knowledge about the postoperative functional trajectory in this patient group. Physical function affects autonomy as well as quality of life in older adults. Our results support the practice of resecting colorectal tumors in patients with advanced age and some degree of frailty, as patients are likely to retain their physical function level up to several months after surgery.
The GA is a useful preoperative assessment tool for predicting short-term outcomes in older surgical patients.5 Its role in predicting long-term physical function remains unclear. Further clarification of GA's possible role in pre-, peri- and postoperative care for frail patients with cancer warrants more observational studies as well as intervention studies.
Disclosures and Conflict of Interest Statements
The authors declare that there are no conflicts of interest.
Concept and design: B. Rønning, T. Wyller, and S. Kristjansson.
Data collection: A. Nesbakken, A. Bakka, and I. Seljeflot.
Analysis and interpretation of data: B. Rønning, T. Wyller, and S. Kristjansson.
Manuscript writing and approval: B. Rønning, S. Kristjansson, T. Wyller, M. Jordhøy, A. Bakka, I. Seljeflot, and A. Nesbakken.
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a Department of Geriatric Medicine, Oslo University Hospital, Pb 4956 Nydalen, 0424 Oslo, Norway Department of Geriatric Medicine, Oslo University Hospital, Pb 4956 Nydalen, Oslo, 0424, Norway
b Institute of Clinical Medicine, University of Oslo, Oslo, Norway Institute of Clinical Medicine, University of Oslo, Oslo, Norway
c Department of Internal Medicine, Innlandet Hospital Trust Gjøvik, Gjøvik, Norway Department of Internal Medicine, Innlandet Hospital Trust Gjøvik, Gjøvik, Norway
d Regional Center of Excellence in Palliative Care, Oslo University Hospital, Oslo, Norway Regional Center of Excellence in Palliative Care, Oslo University Hospital, Oslo, Norway
e Department of Gastroenterological Surgery, Oslo University Hospital, Oslo, Norway Department of Gastroenterological Surgery, Oslo University Hospital, Oslo, Norway
f Department of Digestive Surgery, Akershus University Hospital, University of Oslo, Lorenskog, Norway Department of Digestive Surgery, Akershus University Hospital, University of Oslo, Lorenskog, Norway
g Center for Clinical Heart Research, Department of Cardiology, Oslo University Hospital Ullevål, Oslo, Norway Center for Clinical Heart Research, Department of Cardiology, Oslo University Hospital Ullevål, Oslo, Norway
h Diakonhjemmet Hospital, Department of Medicine, Diakonvn 12, 0319 Oslo, Norway Diakonhjemmet Hospital, Department of Medicine, Diakonvn 12, Oslo, 0319, Norway
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