Risk factors of preoperative frailty in elderly inpatients with gastrointestinal cancer

doi:10.21203/rs.3.rs-132348/v1

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Research Article

Risk factors of preoperative frailty in elderly inpatients with gastrointestinal cancer

https://doi.org/10.21203/rs.3.rs-132348/v1

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Background

Frailty is emerging as an important determinant for health, while researches in the field of frailty start at a later stage in China and mainly focuses on community elderly dwellers. Little is known about frailty in cancer patients in China, nor the risk factors of frailty. This study aimed to investigate the prevalence of frailty and its risk factors in elderly inpatients with gastrointestinal cancer.

Methods

This cross-sectional study was performed at a tertiary hospital in China from Mar. 2020 to Nov. 2020. The study enrolled 265 inpatients aged 60 and older with gastrointestinal cancer who successfully underwent surgery. The demographic and clinical characteristics, biochemical laboratory parameters, and anthropometric data were collected from all patients. The Groningen Frailty Indicator was applied to assess patients’ frailty status. Multivariate logistic regression model analysis was carried out to identify risk factors of frailty and estimate their 95% confidence intervals.

Results

The prevalence of frailty in elderly inpatients with gastrointestinal cancer was 43.8%. A multivariate logistic regression analysis showed that older age (OR = 1.065, 95% CI: 1.001–1.132, P = 0.045), low handgrip strength (OR = 4.346, 95% CI: 1.739–10.863, P = 0.002), no regular exercise habit (OR = 3.228, 95% CI: 1.230–8.469, P = 0.017), and low MNA-SF score (OR = 11.090, 95% CI: 5.119–24.024, P < 0.001) were risk factors of frailty.

Conclusions

This study suggested that the prevalence of frailty was high among elderly inpatients with gastrointestinal cancer. Older age, low handgrip strength, no regular exercise habit, and low MNA-SF score were risk factors of frailty.

Geriatrics & Gerontology

Frailty

Geriatric assessment

Risk factors

Gastrointestinal cancer

Groningen Frailty Indicator

The aging population is accelerating rapidly. As of the end of 2017, there were 241 million people aged 60 and older in China, accounting for 17.3% of the total population[1]. To some extent, age is an important risk factor for cancer, as extended lifespan is accompanied by increased exposure to carcinogenic factors and the prolonged accumulation of genetic changes[2]. Gastric and colorectal cancers are commonly diagnosed cancers worldwide, respectively, ranking the third and fifth in terms of incidence but the second and third in terms of mortality, as reported in Global Cancer Statistics 2018[3]. A recent study shows that a large proportion of new cancer cases in China are diagnosed at age 60 years and older[4], with age-related declines in immunity system[5], organs function, and physical performance[6], thus posing a challenge to promote recovery and reduce adverse clinical outcomes.

Frailty, the most troublesome problem of population aging[7], refers to the state of increased vulnerability for the development of increased dependency and/or death when being exposed to stressors[8]. Several studies have revealed that frailty is an important risk factor for the prediction of postoperative complications[9], readmission[10], and mortality[11] in cancer patients who accepted surgery. For those older patients, the internal complicated biological changes of aging along with immune senescence, inflammation, age-related chronic diseases, and external environmental and psychosocial factors significantly influence the development of individual malignant tumors and their physiological reserves and vulnerability[12]. As we all know, the cancer itself and treatments (e.g., surgery, chemotherapy, and radiotherapy) can be significant stressors that challenge the physiological reserves of older patients, all of which can increase the risk of frailty. Notably, it is also challenging for clinical personnel to decide the optimum treatment for older patients who are heterogeneous in terms of comorbidities, disability, physical reserves, and geriatric conditions[13]. Therefore, the geriatric frailty assessment should be used to provide an appropriate surgical risk assessment for clinical personnel to help guide cancer treatments.

Although there is no golden standard for the assessment of frailty[14], several common frailty tools have been used in clinical practices. The comprehensive geriatric assessment (CGA) is a systematic procedure for the detection of vulnerability in elderly patients with cancer that focuses on functional, somatic, and psychosocial domains[13]. However, conducting CGA is time-consuming[13, 15] and may not be feasible in an oncology ward with limited resources. The Groningen Frailty Indicator (GFI), originally developed by Steverink et al[16], is a frailty screening tool with good predictive performance[17], and it has been widely used for screening frailty in patients with different types of cancers, including stomach[11], colorectum[18], head and neck[19], ovarian[20], breast[21], and non-Hodgkin lymphoma[22]. Recently, Xiang et al[23] has translated the GFI into Chinese, and the Chinese GFI displays good internal consistency (Cronbach’s α = 0.712), excellent test-retest reliability (ICC = 0.939), and satisfactory validity (AUC = 0.823) among Chinese nursing home residents.

Compared with western countries, researches in the field of frailty started at a later stage in China and mainly focused on community elderly dwellers[24]. Two recent studies have reported that the prevalence of frailty among Chinese community residents aged 60 and older, ranged from 38.6–60.5% based on the GFI criterion[23, 25]. Being female, increasing age, ADL disability, and developing three or more chronic diseases were risk factors for frailty in this group[26]. However, to our best knowledge, there is little known about the prevalence of frailty in cancer patients in China, nor the risk factors of frailty. Therefore, the aim of this study was to investigate the prevalence of preoperative frailty in elderly inpatients with gastrointestinal cancer and to further explore the factors that were associated with frailty in these patients.

Study design and participants

This was a cross-sectional study to assess the prevalence of frailty and its risk factors in patients with gastrointestinal cancer. The patients who successfully underwent surgery participated in this study. They were all recruited from the First Affiliated Hospital of Anhui Medical University from Mar. 2020 to Nov. 2020. The inclusion criteria were as follows: (1) with diagnosed gastric or colorectal cancer; (2) ≥ 60 years old; (3) had normal function of limb movement; (4) signed informed consent. The exclusion criteria were as follows: (1) postoperative histopathology confirmed the diagnosis of precancerous or mesothelioma or benign lesions; (2) with recurrent gastric or colorectal cancer; (3) admitted to hospital with acute intestinal obstruction or massive alimentary tract bleeding; (4) had severely diseased heart, liver, kidney, brain, etc.; (5) had a severe infection or inflammatory disease within 1 month.

Ethical consideration

Ethical approval was granted from the Clinical Medical Research Ethics Committee of the First Affiliated Hospital of Anhui Medical University (PJ2020-03-29). This study conformed to the standards of the Declaration of Helsinki and was registered with Chinese Clinical Trial Registry (ChiCTR2000031250).

Laboratory parameters

After a 12-h overnight fast, all patients’ venous blood samples, including blood routine (white blood cell, WBC; red blood cell, RBC; hemoglobin, HGB; reticulocyte, RET; lymphocyte, LYMPH), plasma protein (prealbumin, PA; albumin, ALB; globulin, GLO; total protein, TP), and tumor markers (alpha-fetoprotein, AFP; carcino-embryonic antigen, CEA; carbohydrate antigen 125, CA125; carbohydrate antigen 19-9, CA19-9; carbohydrate antigen 72-4, CA72-4), were collected together in the morning. Blood routine, plasma protein, and tumor markers were detected with an automatic blood analyzer (XN-9000, Sysmex, Japan), an automatic chemistry analyzer (Cobas 8000, Roche, Germany), and an automatic electrochemiluminescence immunoassay analyzer (Cobas 6000, Roche, Germany), respectively. Tumor area, stage, and histological grade were collected as well after surgery.

Demographic and clinical characteristics

A self-designed questionnaire that included detailed information such as age, sex, body mass index (BMI), educational background, marital status, smoking history, drinking history, past medical history, have regular exercise habit or not, cancer type, preoperative chemoradiotherapy, and blood transfusion before or after surgery, was used to collect patients’ general demographic and clinical data. Smoking/Drinking history is defined as the patients who are currently smoking/drinking, or they used to smoke/drink, but now they do not smoke/drink.

GFI questionnaire

Frailty was measured with the self-report version of GFI that has been revised by Peters et al[27], and it contains 15 items on physical, cognitive, social, and psychological domains. The answer to each item has the score of either 0 or 1, with 1 indicating a dependent problem. The total score of GFI ranges from 0 to 15, with higher scores indicating greater frailty. The cut-off value of GFI ≥3 was considered frail in geriatric oncology[17]. Two studies[23, 27] have proved moderate internal consistency of the GFI (Cronbach’s α ranged from 0.68 to 0.712). All patients filled out the GFI questionnaires within three days of their hospital admission.

Short-Form Mini-Nutritional Assessment (MNA-SF) questionnaire

The MNA-SF, revised by Rubenstein et al[28] based on the Mini-Nutritional Assessment[29], is a validated tool to screen malnourished hospitalized patients. The sensitivity, specificity, and diagnostic accuracy of MNA-SF for the prediction of malnutrition were 97.9%, 100%, and 98.7%, respectively[28]. It contains 6 items, namely, weight loss, body mass index, stress or illness, mobility, dementia or depression, and loss of appetite. The total score of MNA-SF ranges from 0 to 14, with the score >11 (£11) being well-nourished (at risk of malnutrition or malnourished). Trained researchers routinely obtained patients’ MNA-SF scores within three days of their hospital admission.

Handgrip strength

Handgrip strength was measured in kilograms (Kg) with a handheld dynamometer based on the digital strain gauge sensors (Jamar^® Plus+, Performance Health Supply, Inc., Cedarburg, WI, USA). Before performing tests, researchers explained the detailed methods to the patients. Measurements were conducted with the patient seated, shoulders adducted and neutrally rotated, elbow in 90° flexion, and the forearm and twist in neutral position[30]. All patients were asked to squeeze the dynamometer as much as possible with the dominant hand. Two tests were performed with a rest interval of at least 30 seconds, and the maximum value of the two tests was recorded. If the two results differed over 10%, a third test would be carried out[31]. Low handgrip strength is defined as <26 kg for male and <18 kg for female[32].

4-Meter Walk Test

Walking speed was performed through a 4-meter walk test, with an additional two meters being added at the beginning and the end of the walkway that was provided for accelerating or decelerating[33]. Patients in standing still position were asked to walk at their usual pace (normal gait speed) with or without using auxiliary aids (e.g., canes, walkers). Walking time was measured by a trained researcher with a digital stopwatch (PS-60, China) from the moment that the patient’s first foot crossed the 2-m line until the moment that the patient’s first foot completely crossed the 6-m line. The test was performed twice, and the shortest time was applied for analysis[34]. Slow gait speed is defined as £0.8 m/s[32].

Mid-upper arm circumference (MUAC) and calf circumference (CC)

MUAC and CC were measured to the nearest 0.1 cm with a non-elastic tape (Deli, China) without compressing the subcutaneous tissue. MUAC was measured at the mid-point around the arm between the acromion and the ulnar olecranon, with the patient’s upper limb in a state of natural hanging[35]. CC was measured around the widest part of the calf, while subjects stood with their legs shoulder-width apart[35].

Statistical analysis

The Kolmogorov-Smirnov test was conducted to verify the normal distribution of continuous variables. All data were expressed as mean ± standard deviation, or median and inter-quartile range, or frequency and percentiles. Differences in demographic and clinical characteristics and biochemical laboratory parameters data between frail and non-frail patients were tested using two independent-samples t test or non-parametric test or chi-square test. To determine risk factors that were associated with frailty and estimate their 95% confidence intervals (CI), independent variables with a P value<0.05 (was set at a stringent level) on univariate analysis as described above were entered into a multivariate logistic regression model analysis by adopting the Forward LR method. Data analyses were performed with SPSS 23.0 software package (IBM, Armonk, NY, USA). A P value<0.05 was considered statistically significant.

Demographic and clinical characteristics in all patients

Overall, 330 patients from gastrointestinal surgery ward were screened, among which 65 patients didn’t meet the inclusion criteria. Hence, 265 patients were included in the final analysis (Figure 1), with 116 (43.8%) in the frail group and 149 (56.2%) in the non-frail group.

As seen in Table 1, when compared with non-frail group, frail group tended to be older and contained more female (less male) (P<0.05). MUAC, CC, 4-m gait speed (Slow gait speed: 24.1% vs. 8.7%), handgrip strength (Low strength: 31.9% vs. 5.4%), and MNA-SF score (Low score: 91.4% vs. 47.7%) were significantly lower in the frail group than that in the non-frail group (P<0.05). The frail group had significantly less regular exercise habit (79.3% vs. 92.6%) and more blood transfusion before or after surgery (23.3% vs. 12.1%) compared with the non-frail group (P<0.05). However, no significant differences in BMI, education, marital status, smoking history, drinking history, Charlson comorbidity index, and preoperative chemoradiotherapy were found between the two groups of subjects (P>0.05).

Biochemical laboratory parameters in all patients

The comparisons of biochemical laboratory parameters between the two groups were showed in Table 2. HGB, PA, and ALB were significantly lower in the frail group than that in the non-frail group (P<0.05), while the tumor area was significantly higher in the frail group than that in the non-frail group (P<0.05). However, no significant differences in WBC, RBC, RET, LYMPH, GLO, TP, AFP, CEA, CA125, CA19-9, CA72-4, cancer type, T stage, N stage, M stage, histological grade, and signet ring cells on histological examination were discovered between the two groups of subjects (P>0.05).

Descriptions of variable assignment

The assignment of dependent and significant independent variables was described in Table 3.

Risk factors of frailty in patients with gastrointestinal cancer

The multivariate logistic regression analysis showed that older age (OR=1.065, 95% CI: 1.001-1.132, P=0.045), low handgrip strength (OR=4.346, 95% CI: 1.739-10.863, P=0.002), no regular exercise habit (OR=3.228, 95% CI: 1.230-8.469, P=0.017), and low MNA-SF score (at risk of malnutrition or malnourished) (OR=11.090, 95% CI: 5.119-24.024, P<0.001) were identified as risk factors of frailty in patients with gastrointestinal cancer (see Figure 2).

This study currently investigated the frailty status of elderly inpatients with gastrointestinal cancer with GFI instrument and analyzed its risk factors. The results showed that the prevalence of frailty was 43.8%, and that older age, low handgrip strength, no regular exercise habit, and low MNA-SF score were risk factors of frailty.

To date, the prevalence of frailty in cancer patients is inconsistent worldwide. A systematic review that pooled 20 studies evaluating 2,916 older cancer patients mainly from North America and Europe, suggesting that the median prevalence of frailty was 42%[36], which was similar to the result of this study. However, this review also revealed that the prevalence of frailty varies greatly among different studies (range 6%-86%) due to the differences in the content and approach of frailty assessment[36]. Generally speaking, the prevalence of frailty in cancer patients is higher than that in community dwellers. Collard et al[37] proposed that the overall weighted prevalence of frailty in 61,500 community older dwellers was 10.7%. Nevertheless, the researchers above found that the prevalence of frailty varied considerably (range 4%-59%) among studies due to different operationalization of frailty status. For cancer patients, the cancer itself can be a significant stressor that challenges patients’ physiologic reserve, and thus the prevalence of frailty in older cancer patients is usually higher[38]. Additionally, various cancer types (e.g., urological, colorectal, breast, lung), assessment instruments (e.g., CGA, phenotype, GFI, FRAIL, FI), and research sites (e.g., inpatient, outpatient, general practice) may contribute to the differences of frailty prevalence in cancer patients[36, 38]. Three Chinese studies have reported that the prevalence of frailty among elderly inpatients ranged from 18–36.2%[24, 39, 40]. However, these studies didn’t provide inpatients’ detailed disease information. Another Chinese study revealed that the prevalence of frailty in gastric cancer patients aged 80 and over was 32.7% based on the three baseline frailty traits, including albumin, hematocrit, and creatinine[9]. In a word, given the inconsistent results of prevalence of frailty and especially high prevalence of frailty in cancer patients, therefore, the clinical personnel should promptly assess cancer patients’ frailty status and then take effective measures to reduce the burden of frailty in this population.

Age is a risk factor for both cancer and frailty. A systematic review showed that the risk of frailty in the elderly population increased significantly with the increase of age[26]. As previously mentioned, older patients experienced much more age-related biological changes, multiple diseases, treatment of diseases, and the effects of social-psychological factors that may ultimately led to the onset of frailty[12]. The aging process can be depicted as a time-dependent decline in physiological organ function, thus resulting in the development of diseases, including cancer[41]. To a certain extent, the related toxicity of cancer treatment caused significant impairments in the body function and some evidence proved that cancer treatment may be associated with accelerated aging[42]. Considering these facts, aging, cancer, and cancer treatment might interact with the onset of frailty. In this study, a small proportion of patients who were younger than 65 years (15.8%, data not shown) and who received preoperative chemoradiotherapy (5.7%, data not shown) may reduce and increase the prevalence of frailty, respectively.

Low handgrip strength was identified as an important risk factor for frailty in the present study. Handgrip strength serves as a reliable proxy index of an individual’s hand motor abilities[43], and measuring handgrip strength is a simple and feasible measure of muscle strength[32]. Xue et al[44] conducted a prospective cohort study of 352 elderly women and observed that lower baseline handgrip strength was significantly associated with the higher risk of frailty, which was consistent with our findings. Interestingly, Puts et al[45] put forward that in newly diagnosed elderly cancer patients, only low grip strength could predict therapeutic toxicity, which may help physicians gain insight into effects of cancer treatments. In addition, for older adults of the same age, handgrip strength may be a single marker of frailty that was more important than chronological age alone[46], and it has been proved to be a valuable screening tool for frailty in older patients with recently diagnosed hematological cancer[47]. Based on these facts, we can understand that handgrip strength is closely connected with frailty in normal individuals or cancer patients.

Regular exercise habit was defined as participants who did at least 30 minutes of moderate-intensity exercise (e.g., jogging, brisk walking) per time, with no less than 5 times per week in the present study. No regular exercise habit mainly meant physical inactivity or being sedentary, and it was significantly associated with frailty in our study. Haider et al[48] suggested that performing no regular physical activity was substantially correlated with the higher risk of frailty in community dwellers, which was in line with our findings. Besides, da Silva et al[49] indicated that frailty prevalence significantly increased with physical inactivity combined with excessive time spent in sedentary behavior in older adults. Hopefully, accumulating studies[50–52] gave the information that physical activity offered a model of improving the function of dysregulated multiple physiologic systems, so as to prevent or alleviate frailty. These studies implied that physical activity had the potential to improve the frail status, thus providing a scientific reference for clinical intervention.

Low MNA-SF score implied that these patients were at risk of malnutrition or malnourished, which was a significant risk factor of frailty in this study. Our results were consistent with a previous study[53] that expressed that low MNA score (at risk of malnutrition/malnourished) was significantly correlated with frailty (OR = 2.72 and OR = 17.4, respectively) among 5,685 older community residents in Singapore. A recent study carried out by Liu et al[54] supported that poor nutritional status was associated with increased risk of frailty (OR = 2.66) among 705 nursing home residents in China. Meanwhile, Gabrovec et al[55] also highlighted that malnutrition or being at risk of malnutrition are risk factors of frailty in aging. However, Zhang et al[56] revealed that frailty was significantly associated with the risk of malnutrition (OR = 3.82) in older cancer patients. We speculated that the close connection between frailty and malnutrition in cancer patients might be attributed to similar factors, including physical performance, weight loss, sociodemographic and clinical characteristics. Notably, the causal relationship between malnutrition and frailty requires clinical researches to make clear. Given the fact that malnutrition is common in older cancer patients, and is mostly caused by tumor invasion, side effects of cancer treatment, cachexia, and anorexia of aging[57]. Hence, there is an urgent need for clinical personnel to early identify malnutrition in cancer patients and then take targeted therapy to improve their nutritional status.

There are several limitations in our study. Firstly, we didn’t detect laboratory biomarkers, just as there were several potential biomarkers that may be involved in the development of frailty. Secondly, this was an observational study and the underlying cellular and molecular mechanisms of frailty were far from being understood, thus necessitating further researches to elucidate this. Thirdly, this study was performed at a single center, and multicenter studies should be conducted soon.

In conclusion, the prevalence of frailty is high among elderly inpatients with gastrointestinal cancer in this study. Older age, low handgrip strength, no regular exercise habit, and low MNA-SF score are risk factors of frailty. Frailty is emerging as an important determinant for health and the mentioned risk factors should be considered when taking interventions to improve frail cancer patients’ health outcomes.

GFI: Groningen Frailty Indicator; WBC: white blood cell; RBC: red blood cell; HGB: hemoglobin; RET: reticulocyte; LYMPH: lymphocyte; PA: prealbumin; ALB: albumin; GLO: globulin; TP: total protein; AFP: alpha-fetoprotein; CEA: carcino-embryonic antigen; CA125: carbohydrate antigen 125; CA19-9: carbohydrate antigen 19-9; CA72-4: carbohydrate antigen 72-4; BMI: body mass index; MNA-SF: Short-Form Mini-Nutritional Assessment; MUAC: mid-upper arm circumference; CC: calf circumference; CI: confidence intervals.

Acknowledgements

We would like to thank all volunteers who participated in this study for their effort and time.

Funding

This work was funded by the National Natural Science Foundation of China (No. 81572350).

Availability of data and materials

Data is not available for online access, however, readers who wish to gain access to the data can email to the corresponding authors SY or AX at [email protected] or [email protected] with their requests.

Authors’ contributions

SY designed this study and wrote the final draft of paper; AX guided the research design and offered funding supports; QZ, MZ, and YZ recruited volunteers and performed the experiments, and QZ wrote the first draft of paper; MZ, SH, LM, and JX analyzed the data and rectified the writing of this paper. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Ethical approval was granted from the Clinical Medical Research Ethics Committee of the First Affiliated Hospital of Anhui Medical University (PJ2020-03-29). Written informed consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Table 1 Subjects’ demographic and clinical characteristics

	Non-frail (n=149)	Frail (n=116)	t/Z/c²	P value
Age (years)	68 (65, 73)	71 (66, 75)	-2.592	0.010^*
BMI (kg/m²)	21.97 (19.84, 23.88)	20.99 (19.40, 23.27)	-1.844	0.065
MUAC (cm)	26.76 ± 2.95	26.01 ± 2.79	2.099	0.037^*
CC (cm)	33.03 ± 2.79	32.15 ± 2.87	2.501	0.013^*
Sex, n (%)			8.515	0.004^*
Male	119 (79.9)	74 (63.8)
Female	30 (20.1)	42 (36.2)
Education, n (%)			-1.742	0.082
Elementary school or lower	97 (65.1)	87 (75.0)
Middle school	31 (20.8)	18 (15.5)
High school or above	21 (14.1)	11 (9.5)
Marital status, n (%)			0.557	0.456
Married	141 (94.6)	112 (96.6)
Widowed	8 (5.4)	4 (3.4)
Smoking history, n (%)			1.717	0.190
No	65 (43.6)	60 (51.7)
Yes	84 (56.4)	56 (48.3)
Drinking history, n (%)			1.921	0.166
No	72 (48.3)	66 (56.9)
Yes	77 (51.7)	50 (43.1)
Charlson comorbidity index, n (%)			1.854	0.173
<3	97 (65.1)	66 (56.9)
³3	52 (34.9)	50 (43.1)
Have regular exercise habit, n (%)			10.075	0.002^*
No	11 (7.4)	24 (20.7)
Yes	138 (92.6)	92 (79.3)
4-m gait speed, n (%)			11.848	0.001^*
>0.8 m/s	136 (91.3)	88 (75.9)
£0.8 m/s	13 (8.7)	28 (24.1)
Handgrip strength, n (%)			32.557	<0.001^*
³26 kg (male), ³18 kg (female)	141 (94.6)	79 (68.1)
<26 kg (male), <18 kg (female)	8 (5.4)	37 (31.9)
Preoperative chemoradiotherapy, n (%)			0.054	0.816
No	141 (94.6)	109 (94.0)
Yes	8 (5.4)	7 (6.0)
Blood transfusion before or after surgery, n (%)			5.799	0.016^*
No	131 (87.9)	89 (76.7)
Yes	18 (12.1)	27 (23.3)
MNA-SF score, n (%)			56.229	<0.001^*
>11	78 (52.3)	10 (8.6)
£11	71 (47.7)	106 (91.4)

^*: Frail vs. Non-frail, P<0.05.

Table 2 Subjects’ biochemical laboratory parameters

	Non-frail (n=149)	Frail (n=116)	t/Z/c²	P value
WBC (×10^9/L)	5.49 (4.55, 6.53)	5.55 (4.60, 6.63)	-0.638	0.523
RBC (×10^12/L)	4.05 (3.74, 4.52)	4.04 (3.52, 4.34)	-1.878	0.060
HGB (g/L)	124.00 (110.00, 140.00)	118.50 (94.00, 129.75)	-3.191	0.001^*
RET (×10^12/L)	0.0640 (0.0490, 0.0855)	0.0620 (0.0503, 0.0788)	-0.763	0.446
LYMPH (×10^9/L)	1.59 (1.30, 1.98)	1.53 (1.22, 1.92)	-1.146	0.252
PA (mg/L)	214.50 ± 51.04	193.33 ± 55.35	3.228	0.001^*
ALB (g/L)	40.60 (39.05, 42.75)	40.10 (36.50, 42.18)	-2.517	0.012^*
GLO (g/L)	25.40 (23.10, 27.75)	25.25 (23.23, 28.78)	-0.665	0.506
TP (g/L)	66.23 ± 5.00	65.65 ± 6.69	0.773	0.441
AFP (ng/mL)	2.02 (1.31, 3.10)	1.89 (1.09, 2.80)	-1.344	0.179
CEA (ng/mL)	3.49 (1.82, 6.56)	3.16 (1.79, 7.16)	-0.057	0.954
CA125 (U/mL)	10.95 (8.22, 16.35)	11.67 (8.07, 19.49)	-1.142	0.253
CA19-9 (U/mL)	11.11 (6.83, 20.92)	10.94 (6.19, 19.57)	-1.036	0.300
CA72-4 (U/mL)	1.82 (1.01, 5.39)	2.29 (1.19, 6.95)	-1.326	0.185
Tumor area (cm²)	12.00 (6.43, 22.25)	18.00 (9.00, 29.38)	-3.453	0.001^*
Cancer type, n (%)			4.865	0.088
Rectum	21 (14.1)	28 (24.1)
Colon	24 (16.1)	20 (17.2)
Stomach	104 (69.8)	68 (58.6)
T stage, n (%)			-0.299	0.765
1	13 (8.7)	17 (14.7)
2	19 (12.8)	16 (13.8)
3	78 (52.3)	47 (40.5)
4	39 (26.2)	36 (31.0)
N stage, n (%)			-1.161	0.246
0	60 (40.3)	56 (48.3)
1	32 (21.5)	21 (18.1)
2	30 (20.1)	21 (18.1)
3	27 (18.1)	18 (15.5)
M stage, n (%)			0.620	0.431
0	141 (94.6)	107 (92.2)
1	8 (5.4)	9 (7.8)
Histological grade, n (%)			-1.572	0.116
Highly differentiated	2 (1.3)	6 (5.2)
Moderately differentiated	72 (48.3)	61 (52.6)
Poorly differentiated	75 (50.3)	49 (42.2)
Signet ring cells on histological examination, n (%)			1.108	0.293
Absent	140 (94.0)	105 (90.5)
Present	9 (6.0)	11 (9.5)

^*: Frail vs. Non-frail, P<0.05.

Table 3 Descriptions of variables assignment

Variables	Description
Age	Continuous variable
MUAC
CC
HGB
PA
ALB
Tumor area

Frailty status	Non-frail=0, Frail=1
Sex	Female=0, Male=1
Have regular exercise habit	Yes=0, No=1
4-m gait speed	>0.8 m/s=0, £0.8 m/s=1
Handgrip strength	³26/18 kg (male/female) =0, <26/18 kg (male/female) =1
Blood transfusion before or after surgery	No=0, Yes=1
MNA-SF score	>11 points=0, £11 points=1

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Risk factors of preoperative frailty in elderly inpatients with gastrointestinal cancer

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