Efficacy of Cereal-based Oral Nutrition Supplement on Nutritional Status, Inflammatory Cytokine Secretion and Quality of Life in Cancer Patients Under Cancer Therapy.

A rapid increase in cancer incidence accompanied by aging population requires evidence-based supportive cancer care practices. Cancer therapies often accompany adverse events which induce malnutrition and declined quality of life. We conducted an 8-week non-randomized clinical trial to evaluate efficacy of cereal-based oral nutritional supplement (ONS) intervention on nutritional status, quality of life and inflammatory responses in cancer patients undergoing cancer therapy with 5% < weight loss. The study included 34 pateints (24 in control group, 10 in intervention group) with 15 drop-outs. ONS used in this intervention contained 0.5% arabinoxylan-rich fermented rice bran powder and 5.5% black rice powder as active ingredients in a regular cereal-based formula. Results showed that ONS intervention for 8 weeks did not show significant improvement in blood biomarkers of nutritional status or patient-generated subjective global assessment scores. However, 8-week of intervention showed reduced interleukin (IL)-6 and IL-1β secretion in lipopolysaccharide-stimulated peripheral blood mononuclear cells while IL-12p70 level was increased. For health-related quality of life (HRQoL) indices, emotional functioning and fatigue symptoms were improved after 4 weeks only in the intervention group although no difference was found at week 8. These results suggest that ONS intervention may improve chronic inflammatory status and HRQoL indices (at week 4) in cancer patients receiving treatments.

INTRODUCTION

Cancer is a leading cause of deaths in different countries around the world, and the estimated new cancer cases in 2018 were 18.1 million [1]. Although advances in cancer treatments have increased the cancer survival rate, the majority of patients suffer from adverse events originated from cancer chemotherapy, radiotherapy and surgery. Malnutrition in cancer patients increases the risk of cancer deaths [2]. Cancer malnutrition is associated with cancer cachexia as well as cancer therapy-induced decreases in food intake. It has been noted that cancer cachexia occurs in 80% of patients [3]. The diagnosis of cancer cachexia requires one of following criteria; 1) weight loss greater than 5%, 2) weight loss greater than 2% in patients already exhibiting body mass index (BMI) < 20 kg/m2, and 3) sarcopenia [4]. It has been reported that cancer cachexia induces substantial metabolic alterations with respect to carbohydrate, fat and protein, which differ greatly from those seen in starvation [5]. Also, surgical procedures especially in patients with gastrointestinal tract cancers significantly affect food intake and bioavailability. Anti-cancer drugs often cause dysphagia, vomiting, and diarrhea. Radiotherapy and chemotherapy are known to induce mucositis leading to decreased food intake and malnutrition [6].

Therefore, nutritional intervention has been suggested as a critical supportive care to accomplish successful cancer treatment. In a recent systemic analysis based on 28 nutrition formula intervention studies, 65% of the studies suggests one or more of nutritional indices are improved by the intervention, and either immune function or inflammatory response was improved, implying that nutritional supplements may be an effective option to improve nutritional status [7].

Despite the importance of nutritional support for a successful cancer treatment, emphasis on research and development in nutritional supplement formula has been rather insufficient. Cancer patients often experience taste and smell changes, which possibly affect the palatability influencing nutritional intake. Previous studies have reported that cancer patients experience altered threshold for tastes [8-10]. Most common post-chemotherapy and postradiotherapy taste alterations include bitter, metallic, chemical and nauseating tastes [11,12]. Therefore, palatability of oral nutritional supplements (ONS) needs to be one of the most important considerations in product development to support cancer management.

ONS used in this study included fermented rice bran and black rice. Active components in fermented rice bran and black rice are arabinoxylan and anthocyanins, respectively, which have been shown to possess immune-modulatory and anti-inflammatory activities [13-15]. Recently, ONS enriched with several active ingredients to improve immunological homeostasis have been introduced [5,16] Long-chain omega-3 fatty acids, eicosapentanoic acid and decosahexanoic acid are used as functional ingredients to reduce elevated proinflammatory cytokines in cancer patients under cancer therapy. Arginine was shown to prolong survival through enhancing immune responses [17]. Branched chain amino acids including leucine are suggested to suppress muscle loss in anorexic cancer patients improving quality of life (QoL) and survival rate [5].

In this study, we evaluated the intervention efficacy of cereal-based ONS containing fermented rice bran powder and super black rice powder in cancer patients undergoing cancer therapy with body weight loss more than 5% since diagnosis.

MATERIALS AND METHODS

Study participants

Patients were recruited from the Departments of Hemato-Oncology and Clinical Nutrition Medicine in Bundang Jesaeng Hospital between November 2014 and October 2015. Adult patients newly diagnosed as having malignant tumor(s) were screened for eligibility and 49 patients were enrolled. Inclusion criteria were as follows: currently receiving one or more cancer therapies, more than 5% of weight loss since the diagnosis, not taking any nutritional supplements. Patients who had acute infectious diseases, cardiac insufficiency, hepatic insufficiency or patients receiving hemodialysis were excluded. The study was approved by the Bundang Jesaeng Hospital ethics review board (IMG14-01). During the course of the study, 15 patients dropped out of the study and final analysis was performed in 24 patients in control group and 10 patients in the intervention group.

Study design and ONS preparation

This study is a non-randomized intervention trial and cancer patients eligible for the study were allocated to the experimental group and then the control group. The intervention period was 8 weeks and patients visited study center three times (week 0, 4 and 8) to have clinical and biochemical measurements taken (Fig. 1). Three-day dietary records were collected at each visit during the intervention. Both control and experimental groups received regular nutrition counseling and education, while only experimental group was asked to take ONS twice a day. To determine the compliance, patients in experimental group were asked to record the amount of ONS consumed. ONS was supplied by Erom Co. (Chuncheon, Korea) in a powder form, and the experimental group consumed two packages (pkg) of ONS (40 g/pkg, 150 kcal/pkg)/d dissolved in 200 mL (per pkg) of water or milk. The composition of the ONS is provided in Table S1.

Figure 1

Study design.

ONS, oral nutritional supplement; PG-SGA, patient-generated subjective global assessment; EORTC-QLQ C30, European Organization for Research and Treatment of Cancer-Quality of Life Questionnaire - Core Questionnaire.

Anthropometric and clinical measurements

Anthropometric measurements were taken at each visit. Patient-Generated Subjective Global Assessment (PG-SGA) was used to evaluate improvements in nutritional status of the study participants. A trained dietitian filled out questionnaires in A section of the PG-SGA by face-to-face interview (weight changes, food intake, clinical symptoms associated with eating behavior, and activities and functions). Body temperature, triceps skinfold thickness, mid-arm muscle circumference were also used to determine PG-SGA score. Dietary intake was assessed by using a 3-day 24-hour recall and concurrent dietary records at each visit. A dietitian interviewed patients for their 3-day recall and patients were asked to record their dietary intake by using food model and food weight table. Nutrient intake was analyzed by Can-pro 4.0 (Korean Nutrition Society, Seoul, Korea). Patients were also telephone-interviewed by a dietitian for their ONS intake. QoL was determined by using European Organization for Research and Treatment of Cancer (EORTC)-Quality of Life Questionnaire - Core Questionnaire developed by EORTC. The questionnaire is composed of 30 questions including global health status, functional scales and symptom scales.

Biochemical measurements

Venous blood samples were collected at each visit and nutritional biomarkers were analyzed at the central laboratory of Bundang Jesaeng Hospital. Peripheral blood mononuclear cells (PBMCs) were prepared from venous blood collected in heparin tube using Axis Shield Poc AsTM LymphoPrepTM (Thermo Fisher Scientific, Oslo, Norway). PBMCs were incubated in RPMI1640 media containing glutamine, penicillin-streptomycin and 10% fetal bovine serum for 6 hours followed by Escherichia coli lipopolysaccharide treatment for 24 hours. Concentrations of interleukin (IL)-12p70, TNF-α, IL-10, IL-6, IL-1β, and IL-8 were measured in the media using Human Cytokine Beads array (BD Biosciences, Franklin, NJ, USA).

Statistical analyses

Per protocol analyses were applied. All measurements were expressed as mean ± SD. Anthropometric measures were compared by Student t-test where it is applicable. Differences (differences between control group and experimental group for changes in each measures; week 0 vs. week 4, week 4 vs. week 8, week 0 vs. week 8) in nutrient intake, biochemical nutritional indices, PG-SGA score and cytokine secretion in lipopolysaccharides (LPS)-stimulated PBMC was compared by Wilcoxon signed rank test and Mann–Whitney test. In measures which did not show statistical differences, further comparisons were performed for differences between control group and experimental group at each week, and differences between each week within the group by using Student t-test.

RESULTS

This study included 24 control participants and 10 ONS intervention participants. Anthropometric measures did not differ significantly between two groups (Table 1). Primary diagnosis in the control group were 9 colon, 5 stomach, 3 rectum, 2 esophageal, 2 lung, 1 anal, 1 gallbladder, 1 lymphoma and that of the ONS intervention group were 5 colon, 2 rectum, 2 lung, 1 gallbladder. Percentage of patients in cancer stage were 17.9% (stage II), 32.1% (stage III), 50% (stage IV) in the control group and 30% (stage I), 40% (stage II), 30% (stage III) in the intervention group. Percentages of the patients who received surgery, chemotherapy and radiotherapy were 46.4%, 94.4%, 14.3% in the control group and 60%, 90%, 30% in the intervention group. Among 49 patients enrolled, 15 patients dropped out of the study. Reasons for drop-outs during the protocol were the transfer to another hospital (n = 1), symptom of diarrhea (n = 3), refusal to continue (n = 2), cancer therapy-associated adverse events (n = 5). Four of the patients died during the course of the study.

Table 1

Baseline characteristics of study patients

	Control group (n = 24)	Intervention group (n = 10)	P-valuea
Age (yr)	6.54 ± 10.46	63.7 0 ± 11.25	0.9850
Height (cm)	161.39 ± 10.05	160.06 ± 10.21	0.8659
Body mass index (kg/m2)	22.85 ± 3.16	23.92 ± 4.16	0.2892
Current body weight (kg)	59.60 ± 10.06	60.54 ± 7.13	0.7079
Past body weight (kg)	66.45 ± 12.60	65.84 ± 8.90	0.9401
Body weight change (%)	9.92 ± 5.06	7.82 ± 4.54	0.2572
Sex
Male	16 (66.67)	7 (70.00)
Female	8 (33.33)	3 (30.00)
Primary diagnosis
Anal	1 (4.17)	0 (0.00)
Colon	9 (37.50)	5 (50.00)
Esophageal	2 (8.33)	0 (0.00)
Gallbladder	1 (4.17)	1 (10.00)
Lung	2 (8.33)	2 (20.00)
Lymphoma	1 (4.17)	0 (0.00)
Rectal	3 (12.50)	2 (20.00)
Stomach	5 (20.83)	0 (0.00)
Complication
Diabetes	6 (25.00)	3 (30.00)
Hypertension	2 (8.33)	2 (20.00)
Hyperlipidemia	0 (0.00)	1 (10.00)
Others	4 (16.67)	1 (10.00)
Smoking status
Never	14 (58.33)	3 (30.00)
Former	8 (33.33)	7 (70.00)
Current	2 (8.33)	0 (0.00)
Drinking
Never	10 (41.67)	4 (40.00)
Former	11 (45.83)	6 (60.00)
Current	3 (12.50)	0 (0.00)

Values are presented as mean ± SD or number (%). aDifferences between control group and intervention group were compared by using Student’s t-test.

We have also analyzed basal dietary intake based on 3-day 24-hour recall and dietary intake record data (data not shown). Basal dietary intake did not include nutrient intake supplied by ONS intervention. Results showed no difference within and between groups except vitamin B1 and copper which were consumed in higher amounts in the intervention group at week 8 compared to those in the control group.

Biomarkers of nutritional status including albumin, prealbumin, cholesterol, and blood cell counts and sizes were determined (Table 2). Albumin and prealbumin concentrations were 3.76 g/dL (control) and 4.25 g/dL (intervention) which lies at lower end of normal range. Blood cholesterol concentrations were 162.79 mg/dL (control) and 161.70 mg/dL (intervention) at baseline, which is relatively low compared to their healthy counterparts. Hemoglobin concentrations in both control and intervention groups were slightly below the normal range, and the concentration was slightly increased only in the ONS intervention group. Red blood cell counts were also below the normal value range both in control and intervention group, while white blood cell counts were within the normal range. In all biomarkers, however no difference was observed between and within groups during the 8 week intervention period.

Table 2

Changes in blood nutritional biomarkers

	Control group (n = 24)			Intervention group (n = 10)
	Baseline	4 weeks	8 weeks	Baseline	4 weeks	8 weeks
Albumin (g/dL)NS	3.76 ± 0.39	3.91 ± 0.82	3.72 ± 0.44	4.25 ± 1.15	4.01 ± 0.30	3.96 ± 0.36
Prealbumin (mg/dL)NS	17.15 ± 5.86	21.15 ± 8.15	19.46 ± 7.35	22.89 ± 8.40	25.92 ± 8.40	23.84 ± 9.67
Cholesterol (mg/dL)NS	162.79 ± 41.12	154.14 ± 37.35	155.64 ± 44.12	161.70 ± 17.70	159.10 ± 38.79	163.89 ± 50.94
WBC (103/μL)NS	6.81 ± 2.46	6.02 ± 3.78	6.73 ± 3.51	9.81 ± 6.54	6.67 ± 4.28	6.84 ± 3.30
RBC (1003/μL)NS	3.99 ± 0.60	3.86 ± 0.68	3.79 ± 0.68	4.03 ± 0.35	3.99 ± 0.69	4.87 ± 3.02
Hb (g/dL)NS	11.49 ± 1.98	11.18 ± 1.68	11.17 ± 1.74	12.02 ± 1.24	11.91 ± 1.95	14.91 ± 9.55
Hct (%)NS	34.97 ± 5.00	34.23 ± 5.25	34.26 ± 5.03	35.70 ± 3.15	35.56 ± 5.12	40.64 ± 16.28
MCV (fL)NS	88.15 ± 7.17	89.20 ± 6.29	91.12 ± 6.34	88.58 ± 4.26	89.71 ± 4.48	84.20 ± 22.01
MCHC (g/dL)NS	32.78 ± 1.62	32.72 ± 1.32	32.59 ± 1.10	33.63 ± 1.12	33.43 ± 1.38	50.97 ± 53.27
MPV (fL)NS	9.60 ± 0.70	9.28 ± 0.75	9.28 ± 0.90	9.56 ± 1.10	9.27 ± 1.11	8.34 ± 3.19
Lymphocyte (%)NS	26.69 ± 9.23	32.36 ± 14.59	30.77 ± 16.64	25.48 ± 15.27	32.72 ± 15.43	25.80 ± 18.52
Eosinophil (%)NS	2.57 ± 1.80	1.90 ± 3.06	2.14 ± 2.99	4.05 ± 5.01	2.51 ± 3.40	1.60 ± 1.63
Basophil (%)NS	0.44 ± 0.33	0.52 ± 0.36	0.39 ± 0.31	0.53 ± 0.60	0.43 ± 0.21	0.36 ± 0.37

Values are presented as mean ± SD. NS indicates no significance in statistical analyses (Wilcoxon signed rank test, Mann–Whitney test, and Student’s t-test at P < 0.05) was found. WBC, white blood cell; RBC, red blood cell; Hb, hemoglobin; Hct, hematocrit; MCV, mean corpuscular volume; MCHC, mean corpuscular hemoglobin concentration; MPV, mean platelet volume.

PG-SGA scores at baseline were 11.88 and 10.60 in control and intervention group, respectively (Table 3). No significant difference within and between groups was observed. Scores from total and A, B, C sections (A: self-recorded information on weight, food intake, symptoms, activities and functions, B: nutrient requirement due to specific diseases; C: metabolic demands, D: physical examinations) were not different, while SGA D score of intervention group was significantly higher at baseline compared to that of the control group.

Table 3

Changes in PG-SGA

	Control group (n = 24)			Intervention group (n = 10)
	Baseline	4 weeks	8 weeks	Baseline	4 weeks	8 weeks
Total PG-SGANS	11.88 ± 3.43	8.33 ± 3.07	9.13 ± 4.05	10.60 ± 3.75	9.70 ± 3.80	9.38 ± 4.07
SGA ANS	5.67 ± 3.06	2.67 ± 2.99	3.46 ± 3.66	5.10 ± 3.21	4.10 ± 3.03	3.63 ± 3.38
SGA BNS	1.54 ± 0.51	1.50 ± 0.59	1.54 ± 0.51	1.60 ± 0.52	1.60 ± 0.52	1.50 ± 0.53
SGA CNS	0.00 ± 0.00	0.13 ± 0.34	0.17 ± 0.38	0.20 ± 0.42	0.20 ± 0.42	0.13 ± 0.35
SGA DNS	4.67 ± 1.05	4.04 ± 1.52	3.96 ± 1.12	3.70 ± 1.06a	3.80 ± 1.03	3.50 ± 1.07

Value are presented as mean ± SD. NS indicates no significance in statistical analyses (Wilcoxon Signed Rank test, Mann–Whitney test and Student’s t-test at P < 0.05) was found. PG-SGA, patient-generated subjective global assessment; SGA A, score from worksheet 1; SGA B, score from worksheet 2; SGA C, score from worksheet 3; SGA D, score from worksheet 4. aSignificantly different between control and experimental group at baseline (P < 0.05, Student t-test).

Inflammatory status of the patients were indirectly measured by using cytokine secretion in LPS-treated PBMC (Table 4). At week 8, decreases in concentrations of IL-6 and IL-8 were significant only the intervention group. However, the concentration of IL-12p70 was increased at week 8 in the intervention group.

Table 4

Changes in inflammatory cytokines in LPS-stimulated PBMC

	Control group (n = 24)			Intervention group (n = 10)
	Baseline	8 weeks	△8 weeks-baseline	Baseline	8 weeks	△8 weeks-baseline
IL-12p70 (pg/mL)	0.36 ± 0.82	0.02 ± 0.06	–0.45 ± 0.93	0.85 ± 1.07	7.85 ± 9.62a	7.17 ± 8.98a
TNF-α (ng/mL)	1.51 ± 1.56	2.89 ± 2.66	1.77 ± 2.28	0.94 ± 0.69	3.55 ± 4.23	2.86 ± 4.35
IL-10 (pg/mL)	467.74 ± 560.80	743.99 ± 648.30	292.32 ± 829.48	261.04 ± 391.34	472.39 ± 337.01	219.33 ± 393.06c
IL-6 (ng/mL)	19.33 ± 18.30	84.70 ± 48.71	77.10 ± 39.18	29.08 ± 34.30	30.18 ± 38.48a	15.96 ± 42.33b
IL-1β (ng/mL)	2.13 ± 1.69	6.82 ± 6.09	6.13 ± 5.81	2.09 ± 1.83	2.36 ± 2.85a	0.74 ± 3.17b
IL-8 (ng/mL)	26.12 ± 9.88	46.44 ± 8.77	21.31 ± 11.52	29.45 ± 12.83	32.34 ± 17.98a	7.81 ± 17.57

Value are presented as mean ± SD. LPS, lipopolysaccharides; PBMC, peripheral blood mononuclear cell; IL, interleukin. aSignificantly different between control and experimental group at week 8 (P < 0.05, Student’s t -test). bSignificantly different within treatment changefrom-baseline (P < 0.05, Wilcoxon signed rank test). cSignificantly different between treatment change-from baseline (P = 0.056, Mann–Whitney test).

Results from QoL measures indicated the emotional functioning score was significantly improved at week 4 compared to those at baseline only in the intervention group (Table 5). Also, fatigue symptom was improved at week 4 compared to that of week 1 in the intervention group and the difference between baseline and week 8 was significantly larger only in the intervention group.

Table 5

Changes in QoL score

	Control group (n = 24)			Intervention group (n = 10)
	Baseline	4 weeks	8 weeks	Baseline	4 weeks	8 weeks
Global health status/QoL	56.60 ± 22.79	54.17 ± 28.97	54.86 ± 30.39	59.17 ± 21.32	63.33 ± 30.48	62.04 ± 22.09
Functional scales
Physical functioning	55.56 ± 27.64	61.67 ± 24.18	60.83 ± 29.83	64.67 ± 31.43	76.00 ± 23.35	71.85 ± 21.29
Role functioning	70.83 ± 28.34	68.06 ± 31.44	57.64 ± 40.82	75.00 ± 31.67	68.33 ± 38.85	66.67 ± 44.10
Emotional functioning	73.61 ± 23.40	73.61 ± 31.34	76.39 ± 25.97	61.67 ± 33.15	90.83 ± 9.98a,d	80.56 ± 23.20b
Cognitive functioning	72.92 ± 29.82	70.83 ± 32.32	71.53 ± 32.03	81.67 ± 32.82	86.67 ± 25.82	81.48 ± 21.15
Social functioning	68.75 ± 31.97	72.22 ± 28.94	65.28 ± 36.09	75.00 ± 22.57	81.67 ± 22.84	79.63 ± 18.22
Symptom scales
Fatigue	51.39 ± 25.76	52.78 ± 30.60	50.93 ± 28.92	43.33 ± 27.44	31.11 ± 25.01d	29.63 ± 22.91c
Nausea and vomiting	20.14 ± 30.68	20.83 ± 30.40	15.28 ± 28.20	13.33 ± 18.92	16.67 ± 33.33	11.11 ± 22.05
Pain	41.67 ± 35.78	36.81 ± 35.77	29.17 ± 30.40	25.00 ± 35.36	20.00 ± 24.60	25.00 ± 38.83
Dyspnea	34.72 ± 30.26	29.17 ± 33.06	22.22 ± 32.10	26.67 ± 40.98	33.33 ± 41.57	20.83 ± 35.36
Insomnia	45.83 ± 44.84	37.50 ± 47.46	36.11 ± 46.02	26.67 ± 43.89	33.33 ± 41.57	20.83 ± 30.54
Appetite loss	44.44 ± 45.75	26.39 ± 36.75	36.11 ± 42.75	23.33 ± 38.65	30.00 ± 42.89	29.17 ± 37.53
Constipation	22.22 ± 27.22	22.22 ± 32.10	19.44 ± 30.95	13.33 ± 32.20	13.33 ± 32.20	16.67 ± 35.63
Diarrhea	25.00 ± 40.82	20.83 ± 32.32	25.00 ± 37.11	23.33 ± 41.72	26.67 ± 40.98	33.33 ± 47.14
Financial difficulties	29.17 ± 34.49	26.39 ± 31.05	34.72 ± 36.09	26.67 ± 26.29	23.33 ± 31.62	41.67 ± 29.55

Value are presented as mean ± SD. QoL, quality of life. aSignificantly different between treatment change-from-baseline (P < 0.05, Mann–Whitney test). bSignificantly different between treatment change-from-baseline (P < 0.05, Mann–Whitney test). cSignificantly different between control and experimental group at week 8 (P < 0.05, Student’s t-test). dSignificantly different within treatment change-frombaseline (P < 0.05, Wilcoxon signed rank test).

DISCUSSION

In this study, we examined the efficacy of cereal-based ONS intervention to improve nutritional status and QoL scores in cancer patients.

Most of cancer patients receiving cancer treatment experience appetite loss and taste aversion. However, little consideration has been made to develop patient-oriented ONS products. In our previous study, the palatability test for different cereal-based ONS trial products in cancer patients and their age- and sex-matched control subjects were performed [18]. We found that cancer patients were more sensitive to taste, viscosity and flavor of the products compared to the control group. The patient group gave higher evaluation scores to products possessing familiar sensory characteristics. These results suggest that ONS product development targeting cancer patients should consider treatment- and tumor-associated changes in appetite. Based on these results, we used cereal-based ONS product that scored highest preference.

Despite malnutrition frequently occurs in cancer patients, nutritional status determinations in cancer patients have not been treated differently from those for other diseaseoriented or age-related malnourished individuals. PG-SGA is the most widely accepted nutrition screening tools for assessing nutritional status of cancer patients [19]. However, subjective measurements in these tools may cause variations in different clinical settings and few validation studies has been performed [20]. Although discrepancies between PG-SGA scores and other nutritional assessment tools in the evaluation of nutritional status were reported [21], PG-SGA has been suggested as a tool reflecting dynamic nutritional status of the patient [22]. We found no significant improvement in PG-SGA scores between two groups possibly due to the small sample size and wide variability in weight loss stages of study subjects. It has been clearly indicated that there is significant association between PG-SGA numerical scores (or categories) and disease status. However, only a handful of research results have been reported for the efficacy of nutrition intervention on PG-SGA scores. A recent ONS intervention trial in pancreatic and bile duct cancer patients indicated 8 weeks of nutrition intervention significantly increased the PG-SGA [23]. Although the authors did not mention % of weight loss at the initiation of intervention, the majority of study subjects were in stage IV implying possibility of severe weight loss. In our study, we included subjects whose weight loss was between 5% to 10% due to applicability of ONS products which may explain no appreciable improvement in ONS group. We have observed PG-SGA and nutrition risk index scores were not associated with treatment-induced adverse events in malnourished stomach cancer patients in our previous study [24] possibly due to the nature of study subjects whose nutritional status was rather stable with a mean PG-SGA score of 7.42. Although PG-SGA scores were 11.88 in the control group and 10.60 in the intervention group at baseline, scores were improved and stabilized in both groups during the intervention possibly due to nutrition counselling and education.

We used a wide range of nutritional status indices other than the PG-SGA score in this study. Previously, the efficacy of ONS in malnourished cancer patients were systematically reviewed [7]. Among qualified 28 intervention studies performed between 2001 and 2015, 20 studies used biochemical measures mostly albumin, prealbumin and transferrin to evaluate the efficacy. Also, 18 studies measured markers of immune responses and inflammatory status. Our study results showed ONS intervention did not improve circulating concentrations of nutritional status biomarkers although hemoglobin concentration was slightly increased only in the intervention group. A recent study showed that nasopharyngeal cancer patients receiving chemoradiotherapy had higher white blood cell counts when the patients were treated with home enteral nutrition [25]. The hemoglobin concentration was negatively associated with PG-SGA score in colorectal cancer patients [26] and nutrition intervention improved the compliance rate of chemotherapy and nutritional status measured by blood concentrations of hemoglobin and albumin [27]. Improved postoperative hemoglobin and albumin status was also observed in primary lung cancer patients receiving ONS [28], and a higher PG-SGA score was suggested to increase the risk of anemia [29]. In cutaneous melanoma patients, female patients with lymph node involvement and metastatic disease were more likely to have a lower hemoglobin concentration [30], and hemoglobin has been suggested as a prognostic marker in head and neck squamous cell carcinoma patients [31]. Although albumin is the most widely used blood biomarker to determine the nutritional status in malnourished population, only 11% of the 28 ONS intervention studies showed significant improvements in cancer patients [7], and results from our study also showed no significant difference in a serum albumin concentration between ONS intervention group and control group.

Cereal-based ONS products used in this study contain fermented rice bran. Studies have suggested that fermentation of rice bran produces arabinoxylan, a functional polysaccharide possessing immune stimulatory activities [32]. A recent report has suggested that arabinoxylan rice bran can be used to alleviate radiation-induced suppressions in complete blood counts [33]. We have also shown that 2.5% to 5% dietary supplementation of wheat bran arabinoxylan significantly suppresses the intestinal mucosa mRNA expression of proinflammatory cytokines as well as the number of apoptotic cells in BALB/c mice treated with 5-fluorouracil, a widely used anti-cancer drug causing mucositis [16]. Although no significant difference was found in body weight, a 5-fluorouracil-induced decrease in thymus weight was significantly recovered in animals fed diet supplemented with arabinoxylan. In this study, we observed significant decreases in IL-6 and IL-1β production in LPS-stimulated PBMC isolated from study subjects and these results are in agreement with results of our preclinical study [16]. Apart from fermented rice bran, other major functional ingredients in ONS product used in this study include black rice powder (5% w/w) and chiaseed powder (5% w/w), which are high in anthocyanin and omega-3 fatty acids, respectively. These compounds are well known to possess anti-inflammatory activities which presumably contributed to the suppressed production of pro-inflammatory cytokines. Since chemotherapy or radiotherapy induced inflammatory responses in tissue epithelium especially in digestive tract contribute to mucositis resulting in decreased food intake, ONS products containing anti-inflammatory functional components may not only increase the nutrient intake but also decrease therapy-induced epithelial inflammation.

Health-related quality of life (HRQoL) is one of the most important supportive care issue in cancer patients. A systematic review and meta-analysis to examine the efficacy of ONS intervention in malnourished cancer patients indicated that ONS intervention exerted significant improvements only in some aspects of HRQoL such as emotional functioning, dyspnea, loss of appetite and global QoL, but no significant difference was found in body weight or mortality [34]. We observed emotional functioning and fatigue symptoms were improved after 4 weeks of intervention although no difference was found at week 8. A recent study with bile duct/pancreatic patients also showed ONS intervention for 8 weeks improved fatigue in the symptomatic scale category [23]. Cancer-related fatigue (CRF) is defined as an unusual, persistent, and subjective sense of tiredness that is not proportional to recent activity and interferes with usual functioning [35]. Earlier systematic analyses have indicated that exercise is an effective mean to improve CRF while evidences for nutritional supplements is not established [36]. A most recent meta-analysis including 15 intervention studies demonstrated nutrition therapy did not show definite effects on CRF and QoL in cancer patients [37]. Among these intervention trials, however, plant-based anti-inflammatory diets suggested possible benefits on CRF [38,39]. We also found that ONS intervention alleviated symptoms of nausea and vomiting. Chemotherapy often induces nausea and vomiting which adversely affect food intake and QoL. Chemotherapeutic agents are known to trigger the secretion of neurotransmitters such as serotonin and substance P mitigating vagal signaling [40]. Currently a limited number of studies have investigated the efficacy of nutrition intervention for cancer treatment associated nausea and vomiting nutrition intervention in palliative cancer patients improved patient-rated symptom of nausea and vomiting while there was difference in other measures [41]. Another intervention study using a home delivery meal service found significantly positive association between energy and protein intake and QoL indicating improved food intake [42]. Contrary to these findings, ONS intervention in patients with nasopharyngeal cancer during chemotherapy improved body weight, BMI and prealbumin, while no difference was observed for QoL [43]. Further nutrition interventions are needed to prove causeeffect relationship between nutrition intervention and chemoor radio-therapy associated adverse events. In conclusion, our study results provided evidence that ONS with immunemodulatory functional components may reduce circulating concentrations of pro-inflammatory cytokines and improve some of QoL indices in a short-time period.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.15430/JCP.2020.25.1.55