Abstract
Aims
This study aimed to quantify the prevalence of frailty, and investigate the impact of frailty on adverse outcomes, in older patients with cancer in Vietnam.
Methods
A prospective, observational study was conducted in adults aged 65 or above with cancer who attended the outpatient clinics of two urban hospitals in Vietnam from September 2023 to May 2024. Frailty was defined by the Carolina Frailty Index (CFI) and participants with a CFI >0.35 were identified as frail. All participants were followed up for 3 months after discharge, recording falls, all-cause hospitalization, and all-cause mortality.
Results
There were 379 participants (mean age 72.3 years, 48.5% female). The prevalence of frailty was 26.6% (95%CI 22.2% - 31.0%), highest in participants with stomach cancer (35.7%) and lung cancer (33.9%). Participants with advanced stages of cancer had a significantly higher prevalence of frailty: 39.3% in stage 4, 21.7% in stage 3, compared to 18.1% in stage 2 and 13.0% in stage 1. During the follow up, 19.0% of the participants had a fall (44.4% in the frail vs. 9.7% in the non-frail, p<0.001), 33.4% were admitted to hospitals (42.2% in the frail vs. 30.1% in the non-frail, p=0.026). The mortality rate was 1.9% (5.1% in the frail vs. 0.7% in the non-frail, p=0.017). Odds ratios were 7.48 (95%CI 4.24 – 13.40, p<0.001) for falls, 1.71 (95%CI 1.06 – 2.75, p=0.027) for all-cause hospitalization, and 7.10 (95%CI 1.36 – 37.22, p=0.020) for all-cause mortality.
Conclusion
Frailty was common among the participants, with the highest prevalence among those with stomach and lung cancer. Frailty significantly increased the odds of falls, hospitalization, and mortality in three months post-discharge. Further research is needed to gain a better understanding of the impact of frailty on adverse outcomes, and the quality of life for older adults with cancer in Vietnam.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12877-026-07738-7.
Keywords: Frailty, Cancer, Geriatric oncology, Vietnam
Introduction
Globally, a significant proportion of adults diagnosed with cancer are older individuals (aged 65 years or above), contributing to approximately 80% of the annual mortality rates associated with cancer [1, 2]. In older adults with cancer, frailty is common and is of particular importance for this population [2, 3]. The treatment and follow up for older adults with cancer present significant challenges due to their complex health needs and the presence of multiple chronic health conditions, as well as geriatric syndromes such as frailty [2, 3]. Frailty is increasingly acknowledged as an essential consideration in clinical practice, particularly when it comes to the evaluation and care of cancer patients [2, 4, 5]. It encompasses a multidimensional syndrome that reflects reduced physiological reserve and increased vulnerability to stressors, which can significantly influence a patient’s overall health status and treatment outcomes [5, 6]. The pathophysiology of frailty involves multiple factors, including chronic systemic inflammation, nutritional deficiencies and impaired neuromuscular function [7–10]. A systematic review in 2015 of 20 studies (n = 2916 participants) from 13 countries (Australia, Austria, Belgium, Canada, France, Germany, Italy, Japan, Norway, Spain, Singapore, the Netherlands, and USA) revealed that the prevalence of frailty in patients with cancer was 42% (range 6%–86%) [11]. Frailty was independently associated with increased all-cause mortality, increased risk of postoperative mortality, and cancer treatment complications [3, 11–14]. These highlight the crucial role of frailty assessment in making decisions regarding the management of older patients with cancer. In clinical practice, frailty is recognized as a crucial factor in conducting comprehensive assessments and guiding treatment decisions for cancer patients, especially when evaluating the benefits and risks of various cancer treatment [2, 5, 6].
In Vietnam, it is projected that the burden of cancer incidence will increase significantly in the two largest populated cities in Vietnam (Ho Chi Minh City and Hanoi), with the number of cancer cases being predicted to double from 2013 to 2025 for most types of cancers [15]. Lung, colorectum, breast and thyroid, and liver cancer represent approximately 67% of the overall cancer burden [15]. Data from the ASEAN CosTs In ONcology (ACTION) study showed that this is an under-resourced issue, with over 75% of patients with cancer in Vietnam and other Southeast Asian countries experiencing death or family financial catastrophe within one year of cancer incidence [16]. With a 17% growth in the overall population, and an increasingly aging population in Vietnam, the burden of cancer incidence will increase sharply over the next decades. Given the differences in demographic characteristics, healthcare systems, and social factors, the applicability of frailty research findings in older adults with cancer from other countries to Vietnam is questionable. Consequently, studies of frailty in older cancer patients in Vietnam are essential to provide locally relevant evidence. Over the past ten year, studies in Vietnam reported high prevalence of frailty, with community-based studies reporting rates between 11% and 22% and hospital-based studies indicating frailty prevalence of up to 55% [17–25]. However, these studies utilized various frailty assessment tools, such as Fried’s Frailty Phenotype, the Edmonton Frail Scale, and the Frailty Index based on routine hospital data. Each of these frailty assessment tools captures different aspects of frailty, leading to substantial variability in the prevalence reported and limiting comparability between studies. Furthermore, there has been limited research specifically focused on cancer patients, a group for whom frailty may manifest differently due to cancer-related factors such as cachexia, treatment toxicity, and systemic inflammation. Understanding the burden of frailty in this population is crucial, as it can significantly influence their treatment outcomes and increase adverse events. Frailty is a common geriatric syndrome among older people and has significant clinical and social implications, especially for older adults with cancer. In Vietnam, where the long-term care systems for the elderly are still developing, the impact of frailty can be even more pronounced. It can impose a considerable burden on healthcare systems, families, and society, leading to a decreased quality of life, diminished self-care abilities, and increased dependence on caregivers.
Therefore, this study aimed to quantify the prevalence of frailty, using the Carolina Frailty Index (CFI) [26], a cumulative deficit model specifically developed for elderly cancer patients, and investigate the impact of frailty on adverse outcomes, in older patients with cancer in Vietnam. The CFI incorporates various factors relevant to oncological geriatrics, enabling our study to provide further evidence on frailty using a frailty assessment framework that is more suitable for older patients with cancer.
Methods
Study populations
This prospective, observational cohort study was conducted at the outpatient clinics of two major hospitals in Vietnam (Thong Nhat Hospital in Ho Chi Minh City and Nguyen Trai Hospital) from September 2023 to May 2024. Consecutive patients aged ≥ 65 diagnosed with cancer who visited the clinics during the study period were recruited. The exclusion criteria were: (1) refusal to participate in the study, (2) inability to obtain consent, (3) severe visual or hearing impairment that affected the patient’s ability to answer the study questions.
The study was approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 676/HDDD-DHYD). Informed consent was obtained from all participants. This study was conducted in accordance with the Declaration of Helsinki.
Data collection
Data were collected from patient interviews and medical records. Information obtained from medical records included demographic characteristics, lifestyles, height, weight, medical history, duration of living with a cancer diagnosis, cancer types, cancer stages, cancer treatment, and comorbidities. Patient interviews were conducted by one of the study investigators (QHHT) and included lifestyles, instrumental activities of daily living, self-reported health, physical function, number of daily medications, vision, hearing, nutrition, mental health, cognition, and social activity.
Body mass index (BMI) was calculated from measured weight and height. Smoking was defined as current smoking (yes/no). Regular exercise was defined as doing exercise at least five days per week (yes/no). Polypharmacy was defined as using 5 or more medications on a daily basis (yes/no) [27].
Comorbidities were documented from the medical records based on a predefined list, including hypertension, coronary heart disease, heart failure, stroke, dyslipidemia, diabetes, chronic kidney disease, osteoarthritis, gastroesophageal reflux disease (GERD), musculoskeletal pain, sleep disorder, depression, and anorexia. In addition, cognitive function was assessed using a 6-item Blessed Orientation-Memory-Concentration (BOMC) test, and a BOMC score ≥ 5 was defined as cognitive decline [28]. Anemia was defined as a serum hemoglobin concentration of less than 12 g/dL for women and less than 13 g/dL for men [29]. Depression was defined using the Geriatric Depression Scale (GDS), and a GDS score ≥ 5 indicated depression [30]. The overall comorbidity burden was also assessed using the Charlson Comorbidity Index [31].
Nutritional status was assessed using the Mini Nutritional Assessment Short Form (MNA-SF), and participants with a score ≤ 7/14 were identified as having malnutrition [32]. Risk of falls was assessed using the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) questionnaire [33]. Activities of daily living (ADL), and instrumental activities of daily living (IADL) were assessed and participants with an ADL score < 6 were identified as having ADL impairment, while those with an IADL score < 8 were identified as having IADL impairment [34].
Frailty was defined by the Carolina Frailty Index (CFI) [26]. The CFI was constructed from 36 variables, including instrumental activities of daily living, self-reported health, physical function, comorbidities, number of daily medications, vision, hearing, nutrition, mental health, social activity, and cognition. The CFI scores range from 0 to 1, with higher scores indicating greater levels of frailty. Participants with a CFI > 0.35 were identified as frail [26]
All participants were followed up for 3 months after discharge, recording adverse outcomes including falls, all-cause hospitalization, and all-cause mortality. The information was obtained through phone calls and by reviewing participants’ medical records.
Sample size calculation
We chose the sample size to be sufficient to estimate the percentage of participants with frailty in cancer patients with an error, taken to be the width of the 95% confidence interval, of no more than ± 5%. To compute this requires an estimate of the expected percentage frail, which we took to be 42% based on a systematic review of frailty in patients with cancer worldwide in 2015 [11]. The resultant sample size requirement was 374.
Statistical analysis
Continuous variables are presented as means and standard deviation (SD), and categorical variables as frequencies and percentages. Comparisons between frail and non-frail participants were conducted using the chi-square test or Fisher’s exact test for categorical variables. For continuous variables, their distributions were assessed using Q-Q plots, and Student’s t-tests or Mann-Whitney U tests were applied accordingly when comparing between frail and non-frail participants.
To quantify the association between frailty and the adverse outcomes of interest (falls, all-cause hospitalization and all-cause mortality), multivariable logistic regression models were applied, adjusting for age, sex, and cancer stages. These covariates were selected a priori based on clinical relevance, prior literature, and their potential role as confounders of the relationship between frailty and study outcomes. Variables that substantially overlapped with components of the frailty index were not included in the adjusted models to avoid over-adjustment. Age was categorized at 70 years, corresponding to the median age of the cohort, to allow balanced group comparisons.
In addition, we conducted sensitivity analyses, fitting the adjusted models for covariates with p-values < 0.05 or < 0.25 from univariable analyses. Univariable analyses were conducted for the following covariates: age, sex, rural/urban living, educational status, marital status, living alone, smoking, alcohol consumption, exercise, underweight, overweight, cancer stages, cancer types, time since cancer diagnosis, Charlson Comorbidity Index, comorbidity types (hypertension, coronary heart disease, heart failure, stroke, dyslipidaemia, diabetes, chronic kidney disease, osteoarthritis, gastroesophageal reflux disease, cognitive decline, anaemia, musculoskeletal pain, sleep disorder, anorexia), geriatric syndromes (impairment in Instrumental Activities of Daily Living, impairment in Activities of Daily Living, polypharmacy, malnutrition, depression, having high risk of falls) (Supplementary Tables 1 and 2).
We also conducted subgroup analysis by sex. Previous studies have shown that women generally exhibit higher rates of frailty, while men face a greater risk of mortality at similar levels of frailty [35, 36]. Additionally, in the context of cancer, biological differences, disease burden, treatment tolerance, and social factors between men and women may affect the relationship between frailty and negative outcomes [37, 38]. The results are presented as odds ratios (OR) and 95% confidence intervals (CI) plus women-to-men ratios of ORs (RORs) with CIs. A women-to-men ratio of ORs greater than 1 suggests that the effect of frailty on the study outcomes is more pronounced in women than in men. All statistical tests were two-sided and a p-value < 0.05 was considered to confer statistical significance.
Results
We obtained data from 379 participants. They had a mean age of 72.3 (SD 6.0) years and 48.5% were female. The prevalence of frailty was 26.6% (95%CI 22.2% − 31.0%). Frailty prevalence differed among participants with different types of cancer: 35.7% in participants with stomach cancer, 33.9% in participants with lung cancer, 31.3% in participants with prostate cancer, 24.8% in participants with colorectal cancer, 18.1% in participants with breast cancer, 9.1% in participants with liver cancer, and 30.4% in participants with other types of cancer (p = 0.226) (Fig. 1). Participants with advanced stages of cancer had a significantly higher prevalence of frailty: 39.3% in stage 4, 21.7% in stage 3, 18.1% in stage 2 and 13.0% in stage 1 (p < 0.001, Fig. 2).
Fig. 1.
Frailty prevalence by cancer types
Fig. 2.
Frailty prevalence by cancer stages
Frail participants were significantly older (mean age 75.6 versus 71.1 years in the non-frail, p < 0.001). The percentages having a low level of education, being single/ divorced/ widowed, being underweight, and having advanced stages of cancer were higher in frail participants compared to the non-frail. The mean value of the Charlson Comorbidity Index was significantly higher in frail participants (5.0, SD 1.9) compared to non-frail participants (3.7, SD 2.0), p < 0.001. The percentages of participants receiving cancer surgery was significantly lower in the frail (57.4%) compared to the non-frail (71.2%, p = 0.011), and the proportion of receiving palliative care was significantly higher in the frail (14.9% versus 3.6 in the non-frail, p < 0.001) (Tables 1 and 2).
Table 1.
Participant characteristics
| Variables | All participants (N = 379) | Non-frail (N = 278) |
Frail (N = 101) |
p-values |
|---|---|---|---|---|
| Age (years) | 72.3 (6.0) | 71.1 (5.1) | 75.6 (6.9) | < 0.001 |
| Age group | ||||
| ≤ 70 | 189 (49.9) | 156 (56.1) | 33 (32.7) | < 0.001 |
| >70 | 190 (50.1) | 122 (43.9) | 68 (67.3) | |
| Sex | ||||
| Male | 195 (51.5) | 149 (53.6) | 46 (45.5) | 0.166 |
| Female | 184 (48.5) | 129 (46.4) | 55 (54.5) | |
| Rural/urban living | ||||
| Rural | 87 (23.0) | 66 (23.7) | 21 (20.8) | 0.546 |
| Urban | 292 (77.0) | 212 (76.3) | 80 (79.2) | |
| Marital status | ||||
| Married | 284 (74.9) | 219 (78.8) | 65 (64.4) | 0.004 |
|
Single/divorced/ widowed |
95 (25.1) | 59 (21.2) | 36 (35.6) | |
| Education | ||||
| Primary school | 67 (17.7) | 38 (13.7) | 29 (28.7) | 0.009 |
| Secondary school | 88 (23.2) | 64 (23.0) | 24 (23.8) | |
| High school | 138 (36.4) | 109 (39.2) | 29 (28.7) | |
| University/College | 76 (20.1) | 58 (20.9) | 18 (17.8) | |
| Postgraduate | 10 (2.6) | 9 (3.2) | 1 (1.0) | |
| Living alone | 26 (6.9) | 17 (6.1) | 9 (8.9) | 0.341 |
| Smoking | 83 (21.9) | 64 (23.0) | 19 (18.8) | 0.381 |
| Regular alcohol consumption | 40 (10.6) | 33 (11.9) | 7 (6.9) | 0.166 |
| Body mass index (kg/m2) | ||||
| <18.50 | 46 (12.1) | 21 (7.6) | 25 (24.8) | < 0.001 |
| 18.50-24.99 | 272 (71.8) | 210 (75.5) | 62 (61.4) | |
| ≥ 25.0 | 61 (16.1) | 47 (16.9) | 14 (13.9) | |
| Charlson Comorbidity Index | 4.0 (2.1) | 3.7 (2.0) | 5.0 (1.9) | < 0.001 |
| Comorbidities | ||||
| Hypertension | 253 (66.8) | 179 (64.4) | 74 (73.3) | 0.105 |
| Coronary heart disease | 95 (25.1) | 70 (25.2) | 25 (24.8) | 0.932 |
| Heart failure | 15 (4.0) | 1 (0.4) | 14 (13.9) | < 0.001 |
| Stroke | 8 (2.1) | 3 (1.1) | 5 (5.0) | 0.034 |
| Dyslipidemia | 130 (34.3) | 94 (33.8) | 36 (35.6) | 0.740 |
| Diabetes | 95 (25.1) | 59 (21.2) | 36 (35.6) | 0.004 |
| Chronic kidney disease | 14 (3.7) | 8 (2.9) | 6 (5.9) | 0.162 |
| Osteoarthritis | 59 (15.6) | 36 (12.9) | 23 (22.8) | 0.020 |
| GERD | 53 (14.0) | 35 (12.6) | 18 (17.8) | 0.194 |
| Cognitive decline | 102 (26.9) | 50 (18.0) | 52 (51.5) | < 0.001 |
| Anemia | 240 (63.3) | 163 (58.6) | 77 (76.2) | 0.002 |
| Musculoskeletal pain | 202 (53.3) | 134 (48.2) | 68 (67.3) | < 0.001 |
| Sleep disorder | 158 (41.7) | 91 (32.7) | 67 (66.3) | < 0.001 |
| Anorexia | 125 (33.0) | 66 (23.7) | 59 (58.4) | < 0.001 |
| Geriatric syndromes: | ||||
| IADL impairment | 214 (56.5) | 119 (42.8) | 95 (94.1) | < 0.001 |
| ADL impairment | 6 (1.6) | 1 (0.4) | 5 (5.0) | 0.006 |
| Polypharmacy | 131 (34.6) | 78 (28.1) | 53 (52.5) | < 0.001 |
| Malnutrition | 66 (17.4) | 28 (10.1) | 38 (37.6) | < 0.01 |
| Depression | 21 (5.5) | 12 (4.3) | 9 (8.9) | 0.084 |
| Having high risk of falls | 161 (42.5) | 78 (28.1) | 83 (82.2) | < 0.001 |
Continuous data are presented as mean (standard deviation). Categorical data are shown as n (%). Comparison between frail and non-frail participants were conducted using Chi-square test or Fisher’s exact test for categorical variables, and Student’s t-test for continuous variables
GERD gastroesophageal reflux disease, ADL Activities of daily living, IADL instrumental activities of daily living
Table 2.
Cancer-related characteristics
| Variables | All participants (N = 379) | Non-frail (N = 278) |
Frail (N = 101) |
p-values |
|---|---|---|---|---|
| Cancer types | ||||
| Colorectal | 121 (31.9) | 91 (32.7) | 30 (29.7) | 0.226 |
| Breast | 72 (19.0) | 59 (21.2) | 13 (12.9) | |
| Lung | 59 (15.6) | 39 (14.0) | 20 (19.8) | |
| Prostate | 32 (8.4) | 22 (7.9) | 10 (9.9) | |
| Stomach | 28 (7.4) | 18 (6.5) | 10 (9.9) | |
| Liver | 11 (2.9) | 10 (3.6) | 1 (1.0) | |
| Other | 56 (14.8) | 39 (14.0) | 17 (16.8) | |
| Cancer stage | ||||
| 0 | 7 (1.8) | 5 (1.8) | 2 (2.0) | < 0.001 |
| 1 | 46 (12.1) | 40 (14.4) | 6 (5.9) | |
| 2 | 116 (30.6) | 95 (34.2) | 21 (20.8) | |
| 3 | 60 (15.8) | 47 (16.9) | 13 (12.9) | |
| 4 | 150 (39.6) | 91 (32.7) | 59 (58.4) | |
| Time since cancer diagnosis | ||||
| < 3 months | 114 (30.1) | 86 (30.9) | 28 (27.7) | 0.941 |
| 3 months – 1 year | 80 (21.1) | 58 (20.9) | 22 (21.8) | |
| 1–3 years | 96 (25.3) | 69 (24.8) | 27 (26.7) | |
| > 3 years | 89 (23.5) | 65 (23.4) | 24 (23.8) | |
| Cancer treatment | ||||
| Surgery | 256 (67.5) | 198 (71.2) | 58 (57.4) | 0.011 |
| Chemotherapy | 246 (64.9) | 186 (66.9) | 60 (59.4) | 0.176 |
| Radiation therapy | 28 (7.4) | 19 (6.8) | 9 (8.9) | 0.494 |
| Hormone therapy | 59 (15.6) | 42 (15.1) | 17 (16.8) | 0.682 |
| Immunotherapy | 31 (8.2) | 21 (7.6) | 10 (9.9) | 0.461 |
| Palliative care | 25 (6.6) | 10 (3.6) | 15 (14.9) | < 0.001 |
Continuous data are presented as mean (standard deviation). Categorical data are shown as n (%). Comparison between frail and non-frail participants were conducted using Chi-square test or Fisher’s exact test
During the 3 months after discharge, 11 participants (2.9%) were lost to follow-up, and data of falls, all-cause hospitalization, all-cause mortality were obtained for 368 participants. The event rates were 19.0% (44.4% in the frail vs. 9.7% in the non-frail, p < 0.001) for falls, 33.4% (42.4% in the frail vs. 30.1% in the non-frail, p = 0.026) for all-causes hospitalization, and 1.9% (5.1% in the frail vs. 0.7% in the non-frail, p = 0.017) for all-cause mortality. (Table 3)
Table 3.
Adverse events by frailty status
| Variables | All participants with follow-up data (N = 368) | Non-frail (N = 278) |
Frail (N = 101) |
p-values |
|---|---|---|---|---|
| Falls | 70 (19.0) | 26 (9.7) | 44 (44.4) | < 0.001 |
| All-cause hospitalization | 123 (33.4) | 81 (30.1) | 42 (42.4) | 0.026 |
| All-cause mortality | 7 (1.9) | 2 (0.7) | 5 (5.1) | 0.017 |
Data are shown as n (%). Comparison between frail and non-frail participants were conducted using chi-square tests or Fisher’s exact test
Frailty was associated with increased odds of falls, all-cause hospitalization and all-cause mortality. The unadjusted ORs were 7.48 (95%CI 4.24–13.40, p < 0.001) for falls, 1.71 (95%CI 1.06–2.75, p = 0.027) for all-cause hospitalization, and 7.10 (95%CI 1.36–37.22, p = 0.020) for all-cause mortality. These relationships are still significant after adjusting for age and sex. The adjusted ORs were 7.06 (95%CI 3.94–12.67) for falls, 1.68 (95%CI 1.03–2.75) for all-cause hospitalization, and 6.74 (95%CI 1.23–36.88) for all-cause mortality. After adding cancer stages to the model, the impact of frailty on falls (adjusted OR 6.56, 95%CI 3.62–11.90)) and all-cause mortality (adjusted OR 6.44, 95%CI 1.14–36.31) remained significant, although the effect on all-cause hospitalization was slightly reduced (adjusted OR 1.62, 95%CI 0.98–2.68) (Table 4). Sensitivity analyses showed similar results (Supplementary Tables 1 and 2), supporting the robustness of the results.
Table 4.
Odds ratios for falls and all-cause hospitalization comparing the frail to the non-frail
| Falls | All-cause hospitalization | All-cause mortality | ||||
|---|---|---|---|---|---|---|
| Odds ratios (95%CI) | p-value | Odds ratios (95%CI) | p-value | Odds ratios (95%CI) | p-value | |
| Unadjusted | 7.48 (4.24–13.40) | < 0.001 | 1.71 (1.06–2.75) | 0.027 | 7.10 (1.36–37.22) | 0.020 |
| Adjusted for age (> 70 vs. ≤70) | 6.79 (3.81–12.09) | < 0.001 | 1.65 (1.01–2.68) | 0.045 | 6.27 (1.15–34.25) | 0.034 |
| Adjusted for sex | 7.79 (4.39–13.83) | < 0.001 | 1.75 (1.09–2.83) | 0.022 | 7.69 (1.46–40.67) | 0.016 |
| Adjusted for age and sex | 7.06 (3.94–12.67) | < 0.001 | 1.68 (1.03–2.75) | 0.038 | 6.74 (1.23–36.88) | 0.028 |
| Adjusted for age, sex, and cancer stages | 6.56 (3.62–11.90) | < 0.001 | 1.62 (0.98–2.68) | 0.059 | 6.44 (1.14–36.31) | 0.035 |
Subgroup analyses showed a non-significant increased impact of frailty on adverse outcomes in men compared to women (Table 5). In models adjusted for age and cancer stage, the ORs were 5.03 (95%CI 2.04–12.41) in women vs. 7.49 (95%CI 3.37–16.67) in men (ROR 0.67, 95%CI 0.20–2.24) for falls; 1.22 (95%CI 0.58–2.57) in women vs. 2.04 (95%CI 1.02–4.07) in men (ROR 0.60, 95%CI 0.22–1.65) for hospitalization; and 2.88 (95%CI 0.12–70.38) in women vs. 10.42 (95%CI 1.08–100.95) in men (ROR 0.28, 95%CI 0.01–13.82) for mortality.
Table 5.
Odds ratios for falls, all-cause hospitalization, and all-cause mortality comparing the frail to the non-frail in women and men
| Frailty (frail vs. non-frail) | Women (N = 184) | Men (N = 195) | Women to men ratio of odds ratios (95%CI) | ||
|---|---|---|---|---|---|
| Odds ratios (95%CI) | p-values | Odds ratios (95%CI) | p-values | ||
| Falls | |||||
| Unadjusted | 7.48 (3.20–17.49) | < 0.001 | 8.06 (3.71–17.54) | < 0.001 | 0.93 (0.29–2.93) |
| Adjusted for age (> 70 vs. ≤ 70) | 6.97 (2.91–16.66) | < 0.001 | 7.25 (3.29–15.96) | < 0.001 | 0.96 (0.30–3.12) |
| Adjusted for age (> 70 vs. ≤ 70) and cancer stage (≥ 3 vs. ≤ 2) | 5.03 (2.04–12.41) | < 0.001 | 7.49 (3.37–16.67) | < 0.001 | 0.67 (0.20–2.24) |
| Hospitalization | |||||
| Unadjusted | 1.42 (0.72–2.82) | 0.314 | 2.15 (1.10–4.23) | 0.026 | 0.66 (0.25–1.72) |
| Adjusted for age (> 70 vs. ≤ 70) | 1.40 (0.69–2.83) | 0.354 | 2.03 (1.02–4.04) | 0.043 | 0.69 (0.26–1.85) |
| Adjusted for age (> 70 vs. ≤ 70) and cancer stage (≥ 3 vs. ≤ 2) | 1.22 (0.58–2.57) | 0.608 | 2.04 (1.02–4.07) | 0.044 | 0.60 (0.22–1.65) |
| Mortality | |||||
| Unadjusted | 2.37 (0.15–38.54) | 0.545 | 13.71 (1.49–126.04) | 0.021 | 0.17 (0.00–6.03) |
| Adjusted for age (> 70 vs. ≤ 70) | 2.62 (0.14–47.76) | 0.516 | 11.10 (1.18–105.04) | 0.036 | 0.24 (0.01–9.36) |
| Adjusted for age (> 70 vs. ≤ 70) and cancer stage (≥ 3 vs. ≤ 2) | 2.88 (0.12–70.38) | 0.516 | 10.42 (1.08–100.95) | 0.043 | 0.28 (0.01–13.82) |
Discussion
In this study of older patients with cancer, 26.6% of the participants were found to have frailty, with the highest prevalence observed among those with stomach and lung cancer. Frailty significantly increased the odds of falls, hospitalization, and mortality in three months post-discharge.
Our findings suggest that frailty is a concern for many older patients with cancer and should be considered in the cancer treatment decision-making process. The prevalence of frailty in this study accords with studies in older patients with cancer in other Asian countries. For instance, a study conducted in 83 older patients with colorectal cancer who had surgery in Singapore and Japan found that the prevalence of frailty was 28%, using Fried’s frailty phenotype [39]. Similarly, a study conducted by Yamada and colleagues in 120 older Japanese patients who underwent pancreatic resection for pancreatic ductal adenocarcinoma reported a frailty prevalence of 24.2% (using the Clinical Frailty Scale) [40]. In a study of 662 older patients attending a geriatric oncology clinic in India, 29% were identified as frail, using the Clinical Frailty Scale [41]. Also, a Korean study of 391 older adults with cancer living in the community, reported a 24.8% prevalence of frailty, using Fried’s frailty phenotype [42]. Furthermore, compared with the study conducted by Guerard and colleagues that also used the Carolina Frailty Index to evaluate frailty in older patients with cancer in the US, the prevalence of frailty in our study was slightly higher (26.6% in our study versus 17.8% in theirs) [26], which could be due to differences in ethnicity and socioeconomic conditions. Although the prevalence of frailty observed in this study was broadly consistent with previous reports, comparisons should be interpreted with caution. Different studies used varying frailty assessment tools and thresholds, which can substantially influence prevalence estimates. In particular, the CFI cutoff applied in this study was originally developed in older patients with cancer in the United States, and may not be directly comparable to Vietnamese cohorts. These methodological differences should be considered when contextualising our findings.
We found that the prevalence of frailty was higher in patients with advance stages of cancer, which is similar to findings from Guerard and colleagues in 546 patients with cancer (median age 72 years) in the Carolina Senior UNC Registry for Older Patients [26]. Patients with advanced cancer often undergo intense treatments such as chemotherapy or radiotherapy, which contribute to an increased risk of malnutrition and severe muscle waste [43, 44].
Frailty in patient with cancer is associated with an increased risk of adverse outcomes, such as postoperative complications, treatment intolerance, disease progression, increased hospitalization, and mortality [45, 46]. These highlight the crucial role of frailty assessment in the management of older patients with cancer. Our study found that frailty is strongly associated with falls, all-cause hospitalization and all-cause mortality in the three months of follow-up. These results indicate that frailty is not merely a clinical feature but serves as a significant prognostic factor for elderly cancer patients. The relationship between frailty and falls can be attributed to a decline in muscle strength, motor function, and balance [47, 48]. Additionally, the heightened risk of hospitalization and mortality observed in the frail group reflects a reduction in physiological reserves, making these patients more susceptible to both pathological and therapeutic stress. Musculoskeletal weakness is a significant component of the frailty syndrome [47, 48]. In older patients with cancer, the impact of cancer treatment and its side effects, including anorexia and malnutrition, can lead to a decline in both muscle mass and strength. This condition not only limits mobility but can also impairs ability to perform daily activities, and increases the risk of falls and fractures [49–51]. Previous studies in other countries showed that frailty status was associated with increased hospital admissions. Williams et al. evaluated the associations between frailty and long-term functional outcomes and found that frailty increased the risk of hospital admission by 2.5-fold and long-term care admission by 1.9-fold [52]. Shahrokni et al., in a cohort of 1137 patients with cancer, reported that higher frailty scores were significantly associated with a longer postsurgical length of stay and a higher risk of intensive care unit admission and 1-year mortality [53]. In a 2015 systematic review including 20 observational studies (2916 participants) with data on the prevalence and/or outcomes of frailty in older cancer patients, frailty was independently associated with increased all-cause mortality, and increased intolerance to cancer treatment [11]. Another review on the impact of frailty on health outcomes in older adults with lung cancer, revealed that frailty had a strong and consistent association with mortality [54].
Our findings have important clinical implications. Our findings indicate that frailty is linked to an increased risk of falls, hospitalization, and short-term mortality, underscoring the importance of frailty as a marker for identifying high-risk older cancer patients. In clinical practice, assessing frailty can enhance risk stratification and contribute to a comprehensive patient evaluation, particularly in the context of treatment decision-making [2, 3, 6]. Understanding the burden of frailty in older patients with cancer is crucial because it significantly impacts treatment outcomes and quality of life [2, 3, 6]. Frailty measures the overall health and ability to recover, which can vary widely among older adults facing cancer [2, 3, 6]. Understanding frailty helps healthcare providers tailor treatments to individual needs, avoiding overly aggressive therapies that may be harmful or less effective [2, 3, 6, 14]. It also aids in predicting potential complications and guiding decisions around palliative care, ensuring a balanced approach that prioritizes both survival and well-being [2, 3, 6]. It is crucial to implement frailty screening programs and assess frailty regularly during cancer treatment. Integrating frailty assessment into cancer care fosters more personalized, compassionate treatment plans, enhancing patient outcomes and quality of life [2, 3, 6, 14]. In addition, by identifying frailty early on, interventions can be implemented timely to reduce the risk of complications and adverse outcomes [2, 3, 6, 14]. Frail and pre-frail patients should be regularly monitored for falls risk. However, because of the observational nature of this study and its limited follow-up period, these results should be interpreted with caution and do not provide enough evidence to make specific intervention recommendations. Future studies with more rigorous designs and extended follow-up times are necessary to clarify the impact of frailty-based intervention strategies on improving clinical outcomes.
To the best of our understanding, this is the first study in Vietnam examining frailty and its impact on adverse outcomes in older patients with cancer, using a validated frailty assessment tool. However, the study has several limitations. First, it was conducted at two urban hospitals in one city, which may not be representative for all older patients with cancer in Vietnam. Therefore, the findings should be interpreted with caution when considering their application to different healthcare systems or policy contexts. Patient characteristics, healthcare access, and treatment practices may differ in rural settings. Nevertheless, the study reflects routine clinical practice in a large urban healthcare system, which may enhance its applicability to similar settings. Second, the relatively short follow-up duration of three months may limit the ability to capture longer-term outcomes, particularly mortality. Third, potential selection bias and the nature and quality of the collected data may affect the interpretation of the findings. In this study, a threshold of ≥ 65 years was applied as an inclusion criterion for participants. Although a threshold of 65 years is widely used in geriatric oncology research and aligns with established geriatric assessment frameworks, definitions of older adulthood may differ across regions. In some Southeast Asian countries, including Vietnam, a threshold of ≥ 60 years is commonly applied due to differences in demographic structure, health status, and life expectancy. Therefore, using a 65-year cut-off in this study may limit its comparability with some regional studies and should be considered when interpreting the generalizability of the findings. Fourth, in the logistic regression models, participants’ age was categorized at 70 years, corresponding to the cohort’s median, to support model stability and interpretability in the context of limited event numbers. However, categorization of continuous variables may reduce statistical power and introduce residual confounding, and the chosen threshold may have limited clinical relevance or comparability with other studies. Fifth, although the Carolina Frailty Index is based on widely used deficit accumulation principles, formal cultural adaptation and validation procedures specific to the Vietnamese setting were not performed. Certain components, particularly those related to functional and instrumental activities of daily living, may be influenced by cultural and healthcare context, which could affect interpretation of frailty status and limit generalisability of the findings. Six, although complete-case analysis was used due to the low proportion of missing data, the potential for bias related to missing follow-up cannot be fully excluded. In addition, odds ratios derived from logistic regression may overestimate associations for more common outcomes and should therefore be interpreted with caution. Furthermore, for outcomes such as all-cause mortality, the small number of events may substantially limit the precision and reliability of the estimates. Finally, other important outcomes for patients with cancer, such as quality of life, were not examined in this study.
Conclusions
In this study of older patients with cancer, frailty was common among the participants, with the highest prevalence of frailty found in participants with stomach cancer and lung cancer. Frailty significantly increased the odds of falls, hospitalization, and mortality by three months post-discharge. Further research with a larger sample size and longer follow up is necessary to gain a better understanding of the impact of frailty on adverse outcomes, as well as quality of life in older adults with cancer in Vietnam. Future investigations on frailty in older patients with cancer should also focus on its impact on cancer treatment decisions and outcomes.
Supplementary Information
Authors' contributions
TVN and TNN conceived the study. TVN and QHHT designed the study protocol, led the ethics application and conducted recruitment. TVN and TNN conducted the statistical analyses and led the manuscript writing. All authors were involved in data interpretation. The manuscript was revised for important scientific content by all authors. All authors approved the final version of the manuscript.
Funding
This paper was funded by the University of Medicine and Pharmacy at Ho Chi Minh City under Contract No. 003-NNC/2026/HÐ-ÐHYD, signed on January 30, 2026, in support of the Comprehensive Geriatrics and Older Adults Leading Research Group (Code: 003.TCM2026).
Data availability
The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
The study was approved by the Ethics Committee of the University of Medicine and Pharmacy at Ho Chi Minh City (Reference Number 676/HDDD-DHYD). Informed consent was obtained from all participants.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Siegel RL, Miller KD, Jemal A. Cancer Statistics, 2017. CA Cancer J Clin. 2017;67(1):7–30. [DOI] [PubMed] [Google Scholar]
- 2.Extermann M, Brain E, Canin B, et al. Priorities for the global advancement of care for older adults with cancer: an update of the International Society of Geriatric Oncology Priorities Initiative. Lancet Oncol. 2021;22(1):e29–36. [DOI] [PubMed] [Google Scholar]
- 3.Ethun CG, Bilen MA, Jani AB, Maithel SK, Ogan K, Master VA. Frailty and cancer: Implications for oncology surgery, medical oncology, and radiation oncology. CA Cancer J Clin. 2017;67(5):362–77. [DOI] [PubMed] [Google Scholar]
- 4.Amsalu E, Nguyen TV, Klimis H, Woodward M, Nguyen T. The Role of Frailty in Cardio-oncology and its Challenges. Eur Cardiol. 2025;20:e35. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Lyon AR, López-Fernández T, Couch LS, et al. 2022 ESC Guidelines on cardio-oncology developed in collaboration with the European Hematology Association (EHA), the European Society for Therapeutic Radiology and Oncology (ESTRO) and the International Cardio-Oncology Society (IC-OS): Developed by the task force on cardio-oncology of the European Society of Cardiology (ESC). Eur Heart J. 2022;43(41):4229–361. [DOI] [PubMed] [Google Scholar]
- 6.Goede V. Frailty and Cancer: Current Perspectives on Assessment and Monitoring. Clin Interv Aging. 2023;18:505–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9868):752–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Lan T, Chen L, Wei X. Inflammatory cytokines in cancer: comprehensive understanding and clinical progress in gene therapy. Cells. 2021;10(1):100. [DOI] [PMC free article] [PubMed]
- 9.Schmidt SF, Rohm M, Herzig S, Berriel Diaz M. Cancer Cachexia: More Than Skeletal Muscle Wasting. Trends Cancer. 2018;4(12):849–60. [DOI] [PubMed] [Google Scholar]
- 10.Aversa Z, Costelli P, Muscaritoli M. Cancer-induced muscle wasting: latest findings in prevention and treatment. Ther Adv Med Oncol. 2017;9(5):369–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Handforth C, Clegg A, Young C, et al. The prevalence and outcomes of frailty in older cancer patients: a systematic review. Ann Oncol. 2015;26(6):1091–101. [DOI] [PubMed] [Google Scholar]
- 12.Fletcher JA, Fox ST, Reid N, Hubbard RE, Ladwa R. The impact of frailty on health outcomes in older adults with lung cancer: A systematic review. Cancer Treat Res Commun. 2022;33:100652. [DOI] [PubMed] [Google Scholar]
- 13.Overcash J, Cope DG, Van Cleave JH. Frailty in Older Adults: Assessment, Support, and Treatment Implications in Patients With Cancer. Clin J Oncol Nurs. 2018;22(6):8–18. [DOI] [PubMed] [Google Scholar]
- 14.Torre I, Tinti L, Amore L, Lombardo A, Camilli M. Frailty Meets Cardio-oncology: A New Frontier in Personalised Cancer Care. Eur Cardiol. 2026;21:e04. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Nguyen SM, Deppen S, Nguyen GH, Pham DX, Bui TD, Tran TV. Projecting Cancer Incidence for 2025 in the 2 Largest Populated Cities in Vietnam. Cancer Control. 2019;26(1):1073274819865274. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.The ASG. Catastrophic health expenditure and 12-month mortality associated with cancer in Southeast Asia: results from a longitudinal study in eight countries. BMC Med. 2015;13(1):190. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Nguyen TV, Tran HM, Trinh HBT, Vu VH, Bang VA. Prevalence of frailty according to the hospital frailty risk score and related factors in older patients with acute coronary syndromes in Vietnam. Australas J Ageing. 2024;43(2):288–96. [DOI] [PubMed]
- 18.Nguyen AT, Nguyen TX, Nguyen TN, et al. The impact of frailty on prolonged hospitalization and mortality in elderly inpatients in Vietnam: a comparison between the frailty phenotype and the Reported Edmonton Frail Scale. Clin Interv Aging. 2019;14:381–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Nguyen HT, Do HT, Nguyen HVB, Nguyen TV. Fried Frailty Phenotype in Elderly Patients with Chronic Coronary Syndrome: Prevalence, Associated Factors, and Impact on Hospitalization. J Multidiscip Healthc. 2024;17:1265–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Nguyen AT, Nguyen LH, Nguyen TX, et al. Frailty prevalence and association with health-related quality of life impairment among rural community-dwelling older adults in Vietnam. Int J Environ Res Public Health. 2019;16(20):3869. [DOI] [PMC free article] [PubMed]
- 21.Nguyen TV, Le D, Tran KD, Bui KX, Nguyen TN. Frailty in Older Patients with Acute Coronary Syndrome in Vietnam. Clin Interv Aging. 2019;14:2213–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Nguyen HT, Nguyen AH, Le PTM. Sex differences in frailty of geriatric outpatients with type 2 diabetes mellitus: a multicentre cross-sectional study. Sci Rep. 2022;12(1):16122. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Khuc AHT, Doan VT, Le TT, et al. Determinants of Frailty among Patients with Type 2 Diabetes In Urban Hospital. Hosp Top. 2023;101(3):215–22. [DOI] [PubMed] [Google Scholar]
- 24.Huynh TQH, Pham TLA, Vo VT, Than HNT, Nguyen TV. Frailty and Associated Factors among the Elderly in Vietnam: A Cross-Sectional Study. Geriatr (Basel). 2022;7(4). [DOI] [PMC free article] [PubMed]
- 25.Vu HTT, Nguyen TX, Nguyen TN, et al. Prevalence of frailty and its associated factors in older hospitalised patients in Vietnam. BMC Geriatr. 2017;17(1):216. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Guerard EJ, Deal AM, Chang Y, et al. Frailty Index Developed From a Cancer-Specific Geriatric Assessment and the Association With Mortality Among Older Adults With Cancer. J Natl Compr Canc Netw. 2017;15(7):894–902. [DOI] [PubMed] [Google Scholar]
- 27.Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. What is polypharmacy? A systematic review of definitions. BMC Geriatr. 2017;17(1):230. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Tuch G, Soo WK, Luo KY, et al. Cognitive Assessment Tools Recommended in Geriatric Oncology Guidelines: A Rapid Review. Curr Oncol. 2021;28(5):3987–4003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Gómez JM, Carrera F. What should the optimal target hemoglobin be? Kidney Int Suppl. 2002;80:39–43. [DOI] [PubMed] [Google Scholar]
- 30.Hoyl MT, Alessi CA, Harker JO, et al. Development and testing of a five-item version of the Geriatric Depression Scale. J Am Geriatr Soc. 1999;47(7):873–8. [DOI] [PubMed] [Google Scholar]
- 31.Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis. 1987;40(5):373–83. [DOI] [PubMed] [Google Scholar]
- 32.Kaiser MJ, Bauer JM, Ramsch C, et al. Validation of the Mini Nutritional Assessment short-form (MNA-SF): a practical tool for identification of nutritional status. J Nutr Health Aging. 2009;13(9):782–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Lin CC, Meardon S, O’Brien K. The Predictive Validity and Clinical Application of Stopping Elderly Accidents, Deaths & Injuries (STEADI) for Fall Risk Screening. Adv Geriatr Med Res. 2022;4(3). [DOI] [PMC free article] [PubMed]
- 34.Katz S. Assessing self-maintenance: activities of daily living, mobility, and instrumental activities of daily living. J Am Geriatr Soc. 1983;31(12):721–7. [DOI] [PubMed] [Google Scholar]
- 35.Gordon EH, Peel NM, Samanta M, Theou O, Howlett SE, Hubbard RE. Sex differences in frailty: A systematic review and meta-analysis. Exp Gerontol. 2017;89:30–40. [DOI] [PubMed] [Google Scholar]
- 36.Park C, Ko FC. The Science of Frailty: Sex Differences. Clin Geriatr Med. 2021;37(4):625–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Kim HI, Lim H, Moon A. Sex Differences in Cancer: Epidemiology, Genetics and Therapy. Biomol Ther (Seoul). 2018;26(4):335–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Bernardez B, Higuera O, Martinez-Callejo V, et al. Sex and gender differences in cancer pathogenesis and pharmacology. Clin Transl Oncol. 2025;27(10):3837–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Tan KY, Kawamura YJ, Tokomitsu A, Tang T. Assessment for frailty is useful for predicting morbidity in elderly patients undergoing colorectal cancer resection whose comorbidities are already optimized. Am J Surg. 2012;204(2):139–43. [DOI] [PubMed] [Google Scholar]
- 40.Yamada S, Shimada M, Morine Y, et al. Significance of frailty in prognosis after surgery in patients with pancreatic ductal adenocarcinoma. World J Surg Oncol. 2021;19(1):94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Rao AR, Ramaswamy A, Kumar S, et al. Prevalence and outcomes of frailty in older patients with cancer: a prospective study from geriatric oncology clinic. J Clin Oncol. 2022;40(16_suppl):e24011–e.
- 42.Kang H. Correlates of Frailty in Community-Dwelling Older Adults with Cancer: 2017 Survey of Living Condition of Elderly Study in South Korea. Asia Pac J Oncol Nurs. 2021;8(3):287–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Arends J, Bachmann P, Baracos V, et al. ESPEN guidelines on nutrition in cancer patients. Clin Nutr. 2017;36(1):11–48. [DOI] [PubMed] [Google Scholar]
- 44.Fearon K, Strasser F, Anker SD, et al. Definition and classification of cancer cachexia: an international consensus. Lancet Oncol. 2011;12(5):489–95. [DOI] [PubMed] [Google Scholar]
- 45.Ethun CG, Bilen MA, Jani AB, Maithel SK, Ogan K, Master VA. Frailty and cancer: implications for oncology surgery, medical oncology, and radiation oncology. Cancer J Clin. 2017;67(5):362–77. [DOI] [PubMed] [Google Scholar]
- 46.Ness KK, Wogksch MD. Frailty and aging in cancer survivors. Translational Res. 2020;221:65–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol Biol Sci Med Sci. 2001;56(3):M146–56. [DOI] [PubMed] [Google Scholar]
- 48.Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2018;48(1):16–31. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Dunne RF, Loh KP, Williams GR, Jatoi A, Mustian KM, Mohile SG. Cachexia and Sarcopenia in Older Adults with Cancer: A Comprehensive Review. Cancers (Basel). 2019;11(12). [DOI] [PMC free article] [PubMed]
- 50.Ali S, Garcia JM. Sarcopenia, cachexia and aging: diagnosis, mechanisms and therapeutic options - a mini-review. Gerontology. 2014;60(4):294–305. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Morris R, Lewis A. Falls and Cancer. Clin Oncol. 2020;32(9):569–78. [DOI] [PubMed] [Google Scholar]
- 52.Williams GR, Dunham L, Chang Y, et al. Geriatric assessment predicts hospitalization frequency and long-term care use in older adult cancer survivors. J Oncol Pract. 2019;15(5):e399–409. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Shahrokni A, Tin A, Alexander K, et al. Development and evaluation of a new frailty index for older surgical patients with cancer. JAMA Netw Open. 2019;2(5):e193545–e. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Fletcher JA, Fox ST, Reid N, Hubbard RE, Ladwa R. The impact of frailty on health outcomes in older adults with lung cancer: A systematic review. Cancer Treat Res Commun. 2022;33:100652. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.