Background

Cancer is a global health concern. According to the Global Cancer Observatory data released by the International Agency for Research on Cancer, there were close to 20 million new cancer cases worldwide in 2022 and the disease caused approximately 9.7 million deaths1. At this rate, nearly one in five people in the world will develop cancer in their lifetime2.

Survival is the primary outcome of concern in cancer therapies3. Cytotoxic agents, including newer targeted therapies and immunotherapies, surgery and radiotherapy, are routinely used to eradicate malignant cells4. Their administration also significantly affects healthy tissues and causes unwanted and common side effects such as nausea, vomiting, diarrhoea, appetite loss, peripheral neuropathy, fatigue and many others5. As a result, cancer treatment can be physically and emotionally challenging for the patients, affecting them socially and financially.

Cancer and its treatment could have long-term impacts on patients. With improvements in therapeutics coupled with early detection, people are now living longer after cancer diagnosis6. Hence, there is a growing focus on the importance of supportive care rather than merely on cancer cure. The quality of life (QoL) outcome of cancer patients becomes a crucial clinical consideration3,7,8. Improving the QoL of patients through complementary and supportive treatments has been suggested to enhance overall well-being and disease outcomes9,10.

Rice bran arabinoxylan compound (RBAC) is a plant-based immunomodulator that has exhibited anticancer properties in research and demonstrated immune restorative function in cancer patients clinically by upregulating natural killer (NK) cell activity and enhancing inflammatory and cytotoxic responses11. Previous reviews by the lead author11,12 found evidence showing RBAC as a complementary therapy used with conventional cancer treatment, which enhanced the immune profile, especially in boosting the NK cell activity, reduced treatment side effects, improved treatment outcomes and survival rates. RBAC was hypothesised to impact the QoL of cancer patients by improving immune function and lowering systemic inflammation, leading to reducing treatment toxicity, symptom severity, and behavioural comorbidities while enhancing the nutritional status and physical functioning13. However, there is a lack of well-designed clinical trials assessing the impact of RBAC supplementation on the QoL of cancer patients using validated QoL instruments11,12.

The present pilot study was conducted to obtain preliminary data for informing the design of a future large-scale clinical trial. This study utilises an internationally validated questionnaire, the European Organisation for the Research and Treatment of Cancer (EORTC) core 30-item QoL questionnaire (QLQ-C30), to determine the potential effects of RBAC compared with placebo on the QoL of cancer patients undergoing active anticancer treatment of either chemotherapy or immunotherapy. Secondary objectives were to ascertain potential associations between RBAC intervention, nutritional, and immune markers as possible mechanisms influencing the QoL of the patients.

Methods

Trial design

The RBAC-QoL study was a randomised, placebo-controlled trial consisting of two parallel groups. The trial was approved by the Human Research Ethics Committee (HREC) of Concord Repatriation General Hospital, Sydney Local Health District (Application No. 2019/ ETH00489) and the Charles Sturt University HREC (Protocol No. H19244) and registered with the Australian New Zealand Clinical Trials Registry (ANZCTR Reg No: ACTRN12619000562178p; First registration on 10/04/2019).

The study protocol was available for open access14. A report documenting the approved protocol variations, statistical methods, and interim analysis has also been published15. A more detailed description of the study methodology can also be found in Supplementary S1. Readers are encouraged to refer to them for further details. All methods were carried out in accordance with the principles, regulations, governance and guidelines for conducting clinical trials based on the National Clinical Trial Governance Framework of Australia16. This report adheres to the Consolidated Standards of Reporting Trials (CONSORT) 2010 guidelines17.

The trial included adult patients (≥ 18 years old) diagnosed with any solid organ cancer (≥ stage II) and undergoing chemotherapy or immunotherapy treatment, recruited from four outpatient cancer centres in New South Wales, Australia. The recruitment target was 50 participants, with equal distribution across two groups based on a priori calculations. Participants were randomly assigned to either the RBAC or placebo group using a computerised stratified algorithm with metastatic status (yes/no) and treatment (chemotherapy or immunotherapy) as inputs. The patient, the treating oncologist, and the study coordinator were blinded to the group allocation.

The participant took either RBAC or a placebo powder (dissolved in water) as an oral supplement (3 g/day) for 24 weeks. All intervention packs were manufactured by the same company and were identical in appearance, containing RBAC or placebo powder with similar colour, odour, and taste. All participants continued their oncological treatment during the trial and were required to attend five study visits, spaced 6 weeks apart, to provide data and undergo blood tests (total duration: 24 weeks).

Outcome measures

The primary outcome measure was self-reported QoL based on the QLQ-C30 completed either on paper or electronically. The scoring of QLQ-C30 followed the procedures stipulated by EORTC18 with a global QoL scale, five functional scales (physical, role, emotional, cognitive, and social), and nine symptom-related measures (fatigue, nausea and vomiting, pain, dyspnoea, insomnia, appetite loss, constipation, diarrhoea) plus a financial difficulties item.

The secondary outcome measures of this study included body composition parameters (body weight, body fat ratio, and muscle mass), body mass index (BMI), and biochemical indices for nutritional assessment based on immunological and inflammatory markers. These nutritional status indices were the neutrophil-to-lymphocyte ratio (NLR) and the inflammatory-nutritional index (INI = the ratio of C-reactive protein and albumin).

Fifteen human cytokine/chemokine markers, including granulocyte-macrophage colony-stimulating factor, interferon-gamma (IFN-γ), interleukin (IL)-1β, IL-1RA, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p40, IL-12p70, IL-13, monocyte chemoattractant protein-1, and tumour necrosis factor-alpha (TNF-α), were analysed using multiplex quantification via Luminex xMAP technology (Luminex, Austin, TX, USA) to explore the immunomodulating effects of RBAC. The multiplexing analysis was conducted by Eve Technologies Corp. (Calgary, AB, Canada).

Patient safety was assessed with routine blood tests during cancer treatment, including complete blood count, liver function, electrolytes, urea, creatinine, and prealbumin. Adverse events reported by participants during clinical visits throughout the trial were also tracked and documented based on the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0.

Data on the participants’ lifestyle factors were also collected using the Australian Eating Survey (AES) for dietary quality19, the International Physical Activity Questionnaire (IPAQ) for physical activeness20, and custom-designed Use of Complementary and Alternative Medicine Questionnaire (CAMQ) for usage and perceived value of complementary therapies14.

Statistical methods

Datasets were analysed with RStudio version 2024.09.0 Build 375 (Posit, Boston, MA, USA), running R version 4.4.0. Data analysis was based on the intention-to-treat principle. Every data point collected from participants in the trial was used regardless of withdrawal. Between-group comparisons over different time points were analysed with RM ANOVA. Pairwise comparisons were conducted when statistical significance was observed with the false discovery rates applied to adjust the p-values for multiple comparisons. Pearson’s correlation coefficient (r) was used to detect the strengths and directions of the relationships among the significant outcome variables.

Outcome measures with data not conforming to normality were tested using nonparametric tests with ANOVA-type statistics utilising the npartLD R software package21.

Between-group comparisons were analysed for baseline characteristics and adverse events. Continuous variables were reported as mean ± standard deviation. The difference between any two means was analysed using two-sided Student’s t-statistics. Fisher’s exact test was used to determine if there were nonrandom associations between two categorical variables. A p-value of less than or equal to 0.05 was considered statistically significant.

Results

Recruitment flow

Recruitment was conducted from June 2020 to December 2023, with interruptions during the COVID-19 pandemic. Follow-up with the last participant was completed in April 2024. The trial concluded short of the recruitment target due to resource and financial constraints. The participant flow report is presented in a CONSORT flowchart22, depicted in Fig. 1.

Fig. 1
Fig. 1
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The recruitment flow of the RBAC-QoL study in a CONSORT diagram.

In summary, 30 eligible participants were randomly assigned to the two intervention groups (RBAC = 12, placebo = 18). Runs test for randomness (Wald-Wolfowitz test⁠) on the allocation sequence yielded a p-value of 0.441, indicating that the group allocation was random. Eleven of them withdrew in various stages with only 19 completed the trial: 10 in the RBAC group and 9 in the placebo group. Overall, among those who completed the trial, the compliance rate was high, averaging 99%, indicating the ease of consuming the oral supplements.

All participants with at least some data collected were included in the intention-to-treat analysis. Only one participant from the placebo group was omitted, as the participant withdrew before providing any baseline data. Thus, data from 29 participants (RBAC = 12, placebo = 17) were analysed for the primary outcome.

Participant characteristics

The characteristics of both groups are shown in Table 1, comparing age, sex, body composition, cancer type, cancer stage, recurrence, metastasis, treatment type, lifestyle factors, and trial status. No significant differences were detected between the groups in baseline characteristics. Although the withdrawal rate appears higher in the placebo group (41.2%) than in the RBAC group (8.3%), the difference in frequency distribution did not reach statistical significance.

Table 1 Participant characteristics.
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Primary outcome analysis

The global QoL scale (QL2) was analysed with RM ANOVA and showed statistical differences between groups (F[1,15] = 5.67, p = 0.031, eta2[g] = 0.147). However, the effects of time and the interaction between time and group were not statistically significant (See Table S2.1 in Supplementary S2). Pairwise comparisons of mean QL2 between groups for each time point are shown in Table 2. Clinically and statistically significant differences were observed at week 6 and week 24 with large effect sizes. At week 6, the RBAC group scored 75.8 ± 14.41 in mean QL2 compared to 57.6 ± 17.93 in the placebo group (p = 0.017, Cohen’s d = 1.118). The mean QL2 difference between RBAC and placebo at week 24 was 79.2 ± 19.74 and 57.41 ± 24.81, respectively (p = 0.041, Cohen’s d = 0.971).

Table 2 Pairwise comparisons of mean global quality of life score (QL2) between groups over time.
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Figure 2 shows the difference in mean QL2 scores between groups over time. The plot shows a dip in the global QoL of the placebo group at week 6, which recovered over the subsequent two visits before dropping again at the last visit (week 24). Conversely, the RBAC group showed an upward trend at week 6 and minor drops at weeks 12 and 18 before improvement at week 24. However, these differences over time were not statistically significant in pairwise comparison.

Fig. 2
Fig. 2
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Plots showing the mean (± standard error) for global quality of life scores (QL2) for RBAC and placebo groups over time. *Significant difference p ≤ 0.05. RBAC = rice bran arabinoxylan compound.

Datasets of the remaining 14 scales/items for QLQ-C30 did not fulfil the normality criterion of RM ANOVA and were analysed based on nonparametric tests with ANOVA-type statistics. The results are shown in Table 3.

Table 3 The modified ANOVA-type statistic based on the group effect for 14 QLQ-C30 scales/items.
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Among the five functional scales of QLQ-C30, statistical differences between groups were detected in role (RF2, p < 0.001) and social functioning (SF, p = 0.037). Meanwhile, the difference in cognitive functioning was marginally significant (CF, p = 0.054). There was also a marginally significant difference between groups concerning financial difficulties (FI, p = 0.058).

The relative treatment effects (RTE) of both groups were compared at each visit for these functional scales, as visualised in Fig. 3. The RBAC group demonstrated superior results compared to the placebo group on these functional scales, indicating a higher or healthier level of functioning in these domains. Most notably, participants taking RBAC reported significantly better role functioning (p < 0.05) than their placebo counterparts at every visit after baseline, most prominently at weeks 12 and 18 (p < 0.01). The RBAC group also reported significantly higher social functioning than the placebo group at weeks 6 and 12. Pairwise comparisons in cognitive functioning found no significant differences between the groups over time. Worsening outcomes in functioning may have contributed to greater concerns over financial difficulties in the placebo group, as shown in Fig. 3.

Fig. 3
Fig. 3
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Plots showing the relative treatment effects (RTE with 95% confidence interval) between RBAC and placebo groups in terms of role functioning (RF2), social functioning (SF), cognitive functioning (CF), financial difficulties (FI), fatigue (FA), pain (PA), dyspnoea (DY) and appetite loss (AP) over time. Significant difference*p ≤ 0.05,**p ≤ 0.01 and marginally + p ≈ 0.05. RBAC = rice bran arabinoxylan compound.

In terms of symptom scores, significant between-group differences (p < 0.05) were detected for fatigue, pain, dyspnoea, and appetite loss. As shown in Fig. 3, the placebo group exhibited higher RTE values than the RBAC group in each of these symptom measures, indicating a greater level of symptomatology or problems in these areas. Pairwise comparisons found significant differences between the groups at weeks 18 and 24 for dyspnoea (p < 0.05) and at week 12 for appetite loss (p < 0.01).

Secondary outcome analysis

RM ANOVA was conducted on body weight, BMI, plus nutritional status indices of NLR and INI (See Table S2.2, S2.3 in Supplementary S2). No statistically significant differences were detected between the groups at baseline and across all time points for these parameters. Therefore, this study was not able to explain the effect of RBAC on QoL beyond that of placebo based on the outcome measures.

Cytokine profile analysis

Cytokine profile analysis was an optional exploratory outcome measure for study sites due to additional logistics requirements for collecting, centrifuging, transporting and storing serum samples. Consequently, the cytokine profile analysis was performed with samples from only 19 participants (RBAC = 9, placebo = 10). Fourteen participants (7 in each group) fully completed the trial. Notwithstanding. among the 15 cytokines/chemokines analysed with RM ANOVA, three parameters yielded significant differences across time: IFN-γ (F[4, 44] = 2.887, p = 0.033, eta2[g] = 0.017), IL-1RA (F[4, 44] = 2.716, p = 0.042, eta2[g] = 0.030), and IL-12p40 (F[4, 44] = 2.716, p = 0.038, eta2[g] = 0.027). However, the effect sizes (eta2[g]) of the differences are considered small (Details are shown in Table S2.4 in the Supplementary S2).

Table 4 shows the pairwise comparisons of the means of IFN-γ, IL-1RA, and IL-12p40 for the two groups across different time points. Due to the small effect sizes, no significant differences were detected for all measures at individual time points. Nonetheless, for IFN-γ, at week 18, the difference between RBAC and placebo groups was marginally significant (1.91 ± 0.20 vs. 1.69 ± 0.23, p = 0.065). Overall, the RBAC group demonstrated slightly higher cytokine activities than the placebo group (Fig. 4).

Table 4 Pairwise comparisons of interferon-gamma (IFN-γ), interleukin-1RA (IL-1RA), and interleukin-12p40 (IL-12p40) between groups over time.
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Fig. 4
Fig. 4
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Plots of (I) mean interferon-gamma (IFN-γ), (II) interleukin-1RA (IL-1RA), and (III) interleukin-12p40 (IL-12p40) for RBAC and placebo groups over time.*Significant difference p ≤ 0.05. RBAC = rice bran arabinoxylan compound.

Safety outcome analysis

The study did not detect any safety issues in any of the participants based on routine clinical assessments, including complete blood count, liver function, electrolytes, urea, creatinine and prealbumin. Based on RM ANOVA analysis, three markers, namely white blood cell count (WBC), total protein (TP) and aspartate transferase (AST), showed significant differences (See Table S2.5, S2.6, S2.7 and S2.8 in Supplementary S2). The WBC (F[4, 60] = 2.540, p = 0.049, eta2[g] = 0.071) and AST (F[4, 60] = 2.855, p = 0.031, eta2[g] = 0.040) were significantly different across time, whereas TP showed a significant interaction effect between group and time (F[4, 56] = 3.057, p = 0.024, eta2[g] = 0.051).

Table 5 shows the pairwise comparisons of the means of WBC, TP, and AST for the two groups across different time points. A significant difference in TP was observed at week 18, with the RBAC group showing 74.88 ± 6.81 g/L compared to 67.78 ± 5.36 g/L) in the placebo group (p = 0.030, Cohen’s d = 1.158). Trends in the WBC, TP, and AST for the two groups over time are visualised in Fig. 5. Although time effects were detected as statistically significant with RM ANOVA, pairwise comparisons of different time points by groups did not yield any significant difference.

Table 5 Pairwise comparisons of white blood cell count (WBC), total protein (TP), and transferase (AST) between groups over time.
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Fig. 5
Fig. 5
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Plots of (I) mean white blood cell count (WBC), (II) total protein, and (III) aspartate transferase (AST) for RBAC and placebo groups over time.*Significant difference p ≤ 0.05. RBAC = rice bran arabinoxylan compound.

Adverse events

Comparisons between the two groups regarding the adverse events reported during the trial period are shown in Table 6. The mean adverse events reported per participant in the RBAC group was lower at 2.33 ± 3.22 compared to 4.59 ± 2.87 in the placebo group, although the difference did not reach statistical significance (p = 0.066).

Table 6 Comparisons of the adverse events reported between RBAC and placebo groups.
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Adverse events based on the CTCAE classification were mostly mild (RBCA = 75.0%, placebo = 79.5%) and moderate (RBCA = 21.4%, placebo = 11.5%), with the grading distribution not significantly different between groups. Notwithstanding, there was one incident of life-threatening bowel obstruction in the placebo group where the patient was hospitalised. The event was resolved and deemed unlikely to be related to the study intervention. In the RBAC group, one death resulted from complications from a fast-growing malignancy unrelated to the study intervention two weeks after starting the trial. There was also a death incident in the placebo group; the participant missed visit 3 and subsequently withdrew from the trial due to a deteriorating condition and passed away one week later.

Overall, there was a significant difference in the distribution of the most commonly reported adverse events between groups (p = 0.006). Fatigue was the most common adverse event reported in both groups (RBAC = 14.3%, placebo = 12.8%), followed by diarrhoea and nausea. Oral thrush and rash were reported in the placebo group, but not in the RBAC group. Other commonly reported adverse events include constipation, cough, peripheral neuropathy, pain, and shortness of breath. These adverse events were typical side-effects of oncological treatment and thus considered not related (RBAC = 53.6%, placebo = 70.5%) or unlikely to be related (RBAC = 42.9%, placebo = 26.9%) to the study interventions. Nonetheless, the oncologists rated three adverse events (diarrhoea, abdominal pain, and dysgeusia) as possibly study-related at the time of reporting, with one in the RBAC group and two in the placebo group. As these adverse events were mild and mostly resolved during the trial, they were subsequently deemed not likely to be caused by the study interventions. Overall, RBAC was considered safe to consume.

Correlations of significant outcomes

Table 7 shows the pairwise correlation coefficients of the QL2, IFN-γ, IL-1RA, IL-12p40, WBC, AST, and TP as significant outcomes of this trial. A linear association between the global QoL of the participants (QL2) with IL-1RA (r = 0.245), IL-12p40 (r = 0.246) and TP (r = 0.310) was detected, demonstrating a positive link between QoL and the immune response (IFN-γ, IL-1RA, IL-12p40) and nutritional status (TP). IL-1RA and IL-12p40 exhibited a very high correlation (r = 0.907), indicating the interrelatedness of these two cytokines. Although the correlation between IFN-γ and QL2 was not significant (r = 0.168), the level of antitumour IFN-γ did exhibit strong correlations with both IL-1RA (r = 0.738) and IL-12p40 (r = 0.804). Moreover, the WBC level was also shown to correlate positively with TP (r = 0.407) and with the cytokines of IFN-γ (r = 0.211), IL-1RA (r = 0.205) and IL-12p40 (r = 0.200). These results suggest that cellular immunity plays a vital role in the observed improved QoL of the RBAC group over the placebo group. In contrast, the liver function marker AST correlates negatively with IFN-γ (r = 0.240), IL-12p40 (r = 0.270) and TP (r = 0.258).

Table 7 Pairwise comparisons of the correlation among global quality of life score (QL2), interferon-gamma (IFN-γ), interleukin-1RA (IL-1RA), interleukin-12p40 (IL-12p40), white blood cell count (WBC), creatinine (Cr) and total protein (TP).
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Analysis of lifestyle factors

RM ANOVA was applied to analyse the Australian Recommended Food Score (ARFS) derived from AES for diet assessment19, metabolic equivalent of task (MET) score for physical activity and CAMQ score for usage and belief in complementary therapies. Analyses of ARFS and CAMQ scores were unremarkable. Only the MET score showed a significant difference for time effect (F[4, 56] = 4.193, p = 0.005, eta2[g] = 0.134). However, pairwise comparisons between time points by group did not reveal any significant difference for both groups after adjustment for multiple comparisons. Hence, physical activity level was unlikely to be a confounding variable that could influence the between-group differences in the current research.

Discussion

This pilot study determined that RBAC improved patients’ overall QoL during active cancer treatment, with a statistically significant difference compared to placebo. Notably, the mean global QoL scales of participants taking RBAC were significantly higher than those taking placebo at weeks 6 and 24, with effect size estimates (Cohen’s d) of 1.118 and 0.971, respectively. Based on the evidence-based guidelines by Cocks, King23 for the interpretation of QLQ-C30, the effect size of cross-sectional differences in the global QoL for clinical relevance can be interpreted as small (0.2–0.4), medium (0.4–0.6), or large (> 0.6). Hence, the QoL differences observed in this study were considered large and thus clinically significant. Such favourable results in QoL maintenance with RBAC are consistent with the findings of Tan and Flores24, who reported a statistically significant difference in the mean global QoL scales (p = 0.019), favouring RBAC over placebo two months after radiation treatment in participants with head and neck cancers.

The final results of global QoL scores are also consistent with those observed during the interim analysis15, albeit with a marginally lower effect size estimate (0.147 vs. 0.267). Since the effect size statistic measures the variance of the sample rather than the population, it will tend to overestimate the effect size with a small sample and the bias is reduced with a larger cohort25. Notably, a matched comparison of 33 interim-final analyses in oncology clinical trials reported that the effect sizes of final analyses were lower by a median of 31% compared to the effect sizes from interim analyses26. Hence, a reduction in the effect size estimate in the present study is within expectation.

In addition to improving global QoL, participants in the RBAC group reported significantly lower symptom severity for fatigue, pain, dyspnoea, and appetite loss compared to the placebo group, as measured by the EORTC QLQ-C30. RTE estimates indicated significantly greater reductions in these symptoms in the RBAC group compared to the placebo group at multiple time points, most notably for appetite loss at week 12 (p < 0.01) and dyspnoea at week 18 (p < 0.05). This finding is supported by a marginally lower mean number of adverse events per participant in the RBAC group compared to the placebo group (2.33 ± 3.22 vs. 4.59 ± 2.87). These findings suggest that the relatively reduced symptom burden during cancer treatment may have contributed to improved role, social, and possibly cognitive functioning in the RBAC group as well as lowering the perceived cancer-related financial stress.

Consistent with these results, Masood, Sheikh27 reported that breast cancer patients taking RBAC during six cycles of chemotherapy experienced fewer incidences of anorexia/tiredness, nausea/vomiting, alopecia, and weight loss compared to the control group who did not take RBAC. Similarly, Petrovics, Szigeti28 demonstrated that in cancer patients with chronic fatigue syndrome, RBAC plus oncothermia, a specialised type of hyperthermia targeting tumours, significantly alleviated fatigue symptoms (p < 0.001) compared to the control group, during active treatment.

The higher occurrence of adverse events and side effects from the cancer treatment led to a higher dropout in the placebo group in this study. Specifically, seven out of the 16 who received the placebo (43.75%) discontinued the trial, compared to only one out of 11 participants in the RBAC group (9.09%). The higher dropout rate in the placebo group could be partially due to the higher number of participants receiving chemotherapy treatment in the placebo (n = 12) versus RBAC (n = 7), as chemotherapy is known to be less tolerable than immunotherapy in advanced solid-organ malignancies29. Five of the seven participants in the placebo group who dropped out were undergoing chemotherapy (one with stage IV cancer and four with stage III cancer).

This disparity in attrition rates, despite the blinded design, raises potential concerns about the study’s internal validity; however, it does not necessarily bias the results30. In clinical research, lower health-related QoL values are known to be related to dropout and death. Most prominently, the global QoL scale, role functioning, physical functioning, and fatigue symptom score in the QLQ-C30 were key early dropout indicators, according to Gebert, Schindel31. Hence, unequal dropout rates should be expected if one group has a significantly better QoL in a controlled trial.

Another randomised controlled trial of RBAC also observed a considerable disparity in dropout rates, albeit in a different cancer patient group. Takahara and Sano32 evaluated the adjunctive effects of RBAC on standard complementary and supportive care in people with progressive and metastasised cancer over 18 months. Of the 109 assigned to the control group, 53 (49%) patients dropped out due to increased intensity of cancer-related symptoms and did not survive at the end of the trial. In contrast, no dropout was observed in the RBAC group (n = 96). The QoL scores improved in both groups among those who remained in the trial, but the RBAC group had a better increase in appetite. Thus, future trials of RBAC supplements should consider incorporating dropout rates due to adverse events as a formal outcome measure as it could be an indirect indicator for QoL.

Nutritional status strongly predicts QoL in cancer patients33. However, no significant between-group differences in body composition parameters and nutritional status indices (INI and NLR) were detected in this study. The discordance could be due to the small sample size, the heterogeneity in cancer types, and the aptness of the chosen outcome measures. Notwithstanding, the present research revealed significant differences in TP between RBAC and the placebo group with a medium effect size. Specifically, the RBAC group showed a significantly higher TP level at week 18 compared to the placebo group, even though TP levels of both groups remained within the normal range. Furthermore, TP and global QoL scores showed a positive correlation. Chemotherapy is known to lower serum TP due to its toxicity34. An improved TP level in the present study suggests that RBAC could better preserve the hepatic and renal function during treatment contributing to better QoL. Serum TP level, along with its components of albumin and globulin and their ratio (A/G ratio), has been suggested as markers for protein-energy malnutrition by Rahman and Begum35. However, this study found no significant between-group differences in albumin level and A/G ratio over time. Thus, the impact of RBAC on the nutritional status of cancer patients during treatment remains unclear and needs further investigation.

In the previous interim analysis of the same trial15, there was also a significant difference in WBC between group and time. Additionally, the TP level was strongly correlated with WBC. This final analysis, however, yields a much weaker correlation between TP and WBC, and thus does not support the proposition that RBAC could potentially improve QoL through preserving WBC level and nutritional status. Hence, further research is required to explore the underlying mechanisms that influence the QoL enhancement effect of RBAC in cancer patients. For example, the inflammation-induced tryptophan-kynurenine pathway linked to fatigue, depression, and decreased QoL in patients with solid tumours can be a potential candidate for investigation in future studies36.

This study also found evidence of cytokine modulation by RBAC with significant differences in IFN-γ, IL-1RA, and IL-12p40 over time between RBAC and placebo groups. The RBAC group appeared to have elevated levels of these cytokines compared to the placebo group. Moreover, these cytokines showed positive correlations with global QoL and WBC. IFN-γ is a pleiotropic cytokine produced mainly by NK cells and NK T cells, which exhibits antitumour, antiviral, and immunomodulatory functions37. An animal study by Badr El-din, Noaman38 showed that tumour-bearing mice treated with RBAC had significantly higher IFN-γ levels (154.54%) that contributed to significantly lower tumour volume (63.27%) and tumour weight (45.2%) as compared to controls (p < 0.01). It is well known that RBAC can elevate NK cell activity39,40. The activation of NK cell function depends on type-1 macrophages and type-1 dendritic cells producing IL-1241. IL-12p40 is a subunit of the IL-12 cytokine produced by dendritic cells to activate the Th1 response and stimulate NK cells to secrete IFN-γ42. Hence, the observed elevation in IFN-γ and IL-12p40 in the RBAC group is consistent with increased NK cell activation. Similarly, Cholujova, Jakubikova43 has also reported that the plasma concentrations of the Th1 cytokines (IL-12, IL-17, TNF-α, and INF-γ) in multiple myeloma patients were significantly elevated (p < 0.05) by RBAC (n = 32) compared with placebo (n = 16) after 3 months in a randomised controlled trial.

It should be noted that IFN-γ levels are expected to be higher in immunotherapy recipients than in those receiving chemotherapy, as immune checkpoint therapy is known to upregulate IFN-γ44. The observed high dropout rate among chemotherapy recipients (in both groups) may have influenced its absolute values (in the within-group analysis) in this study. Nevertheless, the effect of RBAC in activating NK cells to increase IFN-γ secretion could potentially enhance the efficacy of immunotherapy and thus has high clinical relevance, given the increasing use of immunotherapy in cancer treatment.

The elevation of IL-1RA in the RBAC group needs further examination. IL-1RA is generally an anti-inflammatory cytokine that binds to IL-1 receptors, thereby preventing the signalling pathway of pro-inflammatory IL-1α and IL-1β. IL-1RA is closely associated with M2 macrophages, along with IL-10, insulin-like growth factor-I, and transforming growth factor-β, in promoting tissue repair, remodelling, and immune suppression45. Thus, elevated IL-1RA levels could reduce NK cell activity. However, research has also found that excessive IL-1 is involved in suppressing the immune response in the tumour microenvironment, leading to tumour resistance to immunotherapy46. Increasing IL-1RA to counteract the pro-inflammatory effects of IL-1 indirectly stimulates IL-2 production, which enhances NK cell activity against tumour cells47. As such, IL-1RA therapy has been used as an anticancer adjuvant to augment the therapeutic efficacy of immunotherapy48. Hence, the elevated levels of IFN-γ, IL-1RA, and IL-12p40 in the RBAC group could result from the immunomodulatory effects of RBAC, particularly through inducing dendritic cell maturation, upregulating NK cell activity, promoting tumour cell apoptosis as previously described in the literature11,50.

It should be noted that the effect size estimates of IFN-γ, IL-1RA, and IL-12p40 were small, and no significant differences were detected in post-hoc analysis with pairwise comparisons. The cytokine profile analysis was an optional trial component performed on a subset of participants (19 out of 29). Due to the small sample size and limited effect sizes, this pilot trial has insufficient power to detect the between-group differences in cytokine profiles at each time point. Therefore, the impact of RBAC intervention on cytokine profiles during active cancer treatment observed in this study is suggestive, and the potential link to patient QoL remains speculative based on the observed trends. These results should be validated in future research.

This pilot study aimed to inform the design of a large-scale clinical trial. Based on the effect size (eta2[g]) of 0.147 for the global QoL scale, a sufficiently powered study needs a sample size of 88 to achieve the estimated power of 95% based on the a priori power analysis of RM ANOVA (2 groups and 5 measurements, α = 0.5, 1-β = 0.95) for within-between interactions. However, anticipating an unequal dropout rate between groups, the future trial should target to recruit up to 115 participants, randomly allocating 66 (~ 40% extra) in the placebo group and 49 (~ 10% extra) in the RBAC group based on an allocation ratio of approximately 1.35 (placebo) to 1 (RBAC).

This study has several limitations. The most notable is the small sample size, which necessitates validation of the results with a larger study. The short trial duration (6 months) also offers no opportunity to observe the participants’ QoL posttreatment. Thus, it is unclear how long the QoL-improving effects of RBAC could last. Additionally, the lack of posttreatment follow-up also renders no outcome data for validating whether RBAC treatment could improve the survival odds of cancer patients. Nonetheless, the positive findings provide valuable insights into the therapeutic potential of RBAC in cancer treatment and lay the foundation for further translational research of RBAC.

Conclusions

The RBAC-QoL study showed favourable results, indicating that RBAC improves the QoL for cancer patients undergoing active treatment. Compared to the placebo group, participants in the RBAC group reported better global QoL scores and significantly lower rates of fatigue, pain, dyspnoea, and appetite loss. RBAC was safe to consume with no known adverse effects. The observed reduction in symptoms experienced during cancer treatment also led to better role and social functioning. Additionally, significant increases in serum TP, IFN-γ, IL-1RA, and IL-12p40 were observed in the RBAC group over time, and the TP, IL-1RA, and IL-12p40 showed positive correlations with the global QoL scales. These findings suggest potential interactions between nutritional status, immune modulation, and QoL. However, with a small sample size, the findings should be interpreted cautiously and cannot be relied on as evidence of treatment efficacies. Regardless, this analysis provides valuable information and justification for a larger clinical trial to confirm RBAC’s beneficial effects on cancer patients’ QoL.