Next Article in Journal
Scientific and Public Health Challenges in Folic Acid Supplementation: Insights from Brazil and Global Implications
Next Article in Special Issue
Lacticaseibacillus rhamnosus AC1 Aggravates Bone Loss in a Male Rat Model of Deoxycorticosterone Acetate (DOCA)-Salt-Induced Osteoporosis
Previous Article in Journal
Presleep vs. Daytime Consumption of Casein-Enriched Milk: Effects on Muscle Function and Metabolic Health After Sleeve Gastrectomy
Previous Article in Special Issue
Postbiotics Derived from Lactococcus lactis and Streptococcus thermophilus Attenuate Experimental Periodontitis by Modulating Macrophage Polarization and Osteoclastogenesis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Nutrients
Volume 17
Issue 17
10.3390/nu17172751
nutrients-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Beyond Analgesia: Psychobiotics as an Adjunctive Approach to Pain Management in Gastrointestinal Oncology—A Post Hoc Analysis from the ProDeCa Study

by
Georgios Tzikos
1,
Alexandra-Eleftheria Menni
1,
Helen Theodorou
2,
Eleni Chamalidou
3,
Ioannis M. Theodorou
4,
George Stavrou
5,
Anne D. Shrewsbury
1,
Aikaterini Amaniti
6,
Anastasia Konsta
7,
Joulia K. Tsetis
8,
Vasileios Grosomanidis
6,† and
Katerina Kotzampassi
1,*,†
1
Department of Surgery, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece
2
Department of Sociology, School of Social Sciences, University of Crete, 74100 Rethymno, Greece
3
Outpatient Surgical Oncology Unit, Chemotherapy Department, AHEPA University Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece
4
Hellenic Institute for the Study of Sepsis (HISS), 11528 Athens, Greece
5
Department of Surgery, 417 NIMTS (Army Share Fund Hospital), 11521 Athens, Greece
6
Department of Anesthesiology and Intensive Care, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
7
First Department of Psychiatry, “Papageorgiou” General Hospital of Thessaloniki, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
8
Uni-Pharma S.A., 14564 Athens, Greece
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Nutrients 2025, 17(17), 2751; https://doi.org/10.3390/nu17172751
Submission received: 13 July 2025 / Revised: 11 August 2025 / Accepted: 23 August 2025 / Published: 25 August 2025
(This article belongs to the Special Issue Effects of Probiotics, Prebiotics, and Postbiotics on Human Health (2nd Edition))
Browse Figures
Review Reports Versions Notes

Abstract

Background: Pain is a multifaceted and debilitating symptom in patients with gastrointestinal cancer, especially those undergoing surgical resection followed by chemotherapy. The interplay between inflammatory, neuropathic, and psychosocial components often renders conventional analgesia insufficient. Psychobiotics—probiotic strains with neuroactive properties—have recently emerged as potential modulators of pain perception through neuroimmune and gut–brain axis pathways. Methods: This post hoc analysis is based on the ProDeCa randomized, placebo-controlled trial, which originally aimed to assess the psychotropic effects of a four-strain psychobiotic formulation in postoperative gastrointestinal cancer patients receiving chemotherapy. In the current analysis, we evaluated changes in pain perception among non-depressed and depressed participants, who received either psychobiotics or placebo, along with standard analgesic regimes. Pain was assessed at baseline, after a month of treatment, and at follow-up, 2 months thereafter, using the Short-Form McGill Pain Questionnaire (SF-MPQ), capturing both sensory and affective components, as well as with the Present Pain Intensity and the VAS scores. Results: Psychobiotic-treated participants—particularly the non-depressed ones—exhibited a significant reduction in both quantitative and qualitative pain indices over time compared with placebo-treated ones. Improvements were noted in total pain rating index scores, sensory and affective subscales, and present pain intensity. These effects were sustained up to 2 months after intervention. In contrast, placebo groups demonstrated worsening in pain scores, probably influenced by ongoing chemotherapy and disease progression. The analgesic effect was less pronounced but still observable in the subgroup with symptoms of depression. Conclusions: Adjunctive psychobiotic therapy appears to beneficially modulate pain perception in gastrointestinal oncology patients receiving chemotherapy, with the most pronounced effects being in non-depressed individuals. These findings suggest psychobiotics as a promising non-opioid add-on for comprehensive cancer pain management and support further investigation in larger pain-targeted trials.

1. Introduction

Pain is a common and debilitating symptom among patients with gastrointestinal [GI] cancer, particularly those undergoing surgical resection followed by chemotherapy. The etiology of pain, recently re-defined by the International Association for the Study of Pain as “an unpleasant sensory and emotional experience associated with, or resembling that associated with, actual or potential tissue damage” [1]—in this population—is multifactorial, involving tumor biology, surgical trauma, and the cytotoxic effects of adjuvant therapies. Despite advancements in oncologic care, pain remains under-recognized and under-treated, significantly impacting the quality of life, emotional well-being, and treatment adherence of patients [2,3,4].
Surgical resection, while potentially curative, often results in acute postoperative pain due to tissue injury, nerve damage, and inflammation [5,6,7]. In a significant proportion of patients, this pain shifts toward a chronic postoperative pain, defined as pain persisting beyond the expected healing period of 3 months. Studies indicate that up to 30–50% of patients experience persistent pain following major abdominal surgeries, including those for GI malignancies [8,9]. Moreover, neuropathic pain components may arise due to the involvement of somatic or visceral nerve plexuses affected during lymphadenectomy or aggressive dissection during extensive resections [7,10].
Chemotherapy further exacerbates the pain burden through both direct and indirect mechanisms, such as peripheral neurotoxicity, myelosuppression-induced bone pain, and mucositis. Platinum-based compounds, namely, oxaliplatin and taxanes (paclitaxel) are known to induce chemotherapy-related peripheral neuropathy, manifesting as burning, tingling, or diffuse pain, affecting 30–60% of patients and often persisting long after treatment ends [11,12]. Additionally, mucositis, myalgias, and arthralgias are common adverse side effects that aggravate the overall pain experience. The chemotherapy-induced systemic inflammatory milieu sensitizes both peripheral and central nociceptive pathways, leading to enhanced pain perception [13,14].
Cancer pain, affecting nearly 66% of cancer patients [15], is not merely a somatic experience but a complex phenomenon involving emotional and psychosocial dimensions. According to Mendoza-Contreras et al. [16], there are three main types: the sensory–discriminative, which involves the quality, location, duration, and intensity of pain; the motivational–affective, which includes subjective facets such as suffering, aversion, dislike, and experienced emotional changes; and the cognitive–evaluative, which comprises earlier experiences and response strategies. From this point of view, the close relationship of emotional response to any sensory dimension, and vice versa, suggests that anxiety and depression, being common comorbidities in cancer patients, can significantly amplify pain perception through top–down modulation in the central nervous system [17,18]. This bio-psycho-social model of pain underscores the need for comprehensive assessment and multimodal management approaches that go beyond pharmacological approaches [5,6].
Validated pain assessment tools, such as the McGill Pain Questionnaire, the Brief Pain Inventory (BPI), the Numerical Rating Scale (NRS), and the Visual Analog Scale (VAS), have been used from the past in oncology settings to quantify mainly the pain intensity and interference with daily functioning [19]. These tools are instrumental in monitoring the progression or remission of pain symptoms over time, especially in response to therapeutic interventions. Furthermore, in order to assess the sensory-discriminative and the motivational–affective dimensions of pain, the Short-Form McGill Pain Questionnaire was developed, and has been widely used for almost 40 years as a well-recognized assessment tool in both clinical and research settings [20].
Unmanaged pain in patients with GI cancers has been associated with poor nutritional intake, sleep disturbances, reduced mobility, reduced or eliminated ability to work, no desire to socially interact, and an overall decline in performance status [21,22,23]. It is also a major determinant of patient-reported outcomes and satisfaction with care. Therefore, effective pain control is not only an ethical imperative and a medical obligation under the right to health [24] but also a clinical necessity to support optimal recovery and therapeutic efficacy [3]. Given the complexity and multifactorial nature of cancer-related pain, there is a growing interest in integrative approaches that modulate pain perception, including those involving neuroimmune and gut–brain axis pathways [25,26]. While pharmacological analgesia remains the cornerstone of pain control, complementary approaches targeting both physiological and psychological aspects of pain are gaining ground [5].
Emerging research has increasingly highlighted the potential role of probiotics having psychotropic properties—referred to as psychobiotics—in modulating pain perception, particularly in postoperative and chemotherapy settings. The mechanisms by which these agents influence pain are multifaceted and include anti-inflammatory effects, immunomodulation, enhancement of intestinal barrier integrity, and modulation of both the gut–brain axis and the neuroendocrine signaling [25,26,27]. Specific strains, such as Lactobacillus acidophilus NCFM and L. rhamnosus GG, have been shown to increase the expression of μ-opioid and cannabinoid receptors in intestinal epithelial cells, as well as in animal models, directly influencing nociceptive pathways and reducing visceral hypersensitivity [28].
Preclinical studies in a rat model of colonic dilatation have demonstrated that administration of certain probiotic strains increases pain thresholds and reduces visceral motor responses—effects comparable to or synergistic with low-dose morphine [29,30,31]. Moreover, psychobiotics such as Lactiplantibacillus plantarum PS128 have been found to alleviate pain via suppression of the pro-inflammatory cytokines IL-6, IL-1β, and TNF-α and via the modulation of the hypothalamic–pituitary–adrenal axis, often being dysregulated due to cancer-related stress and pain [27]. The analgesic properties of psychobiotics are particularly important in the postoperative setting, where both inflammatory and neuropathic pain coexist, and in the chemotherapy phase, where intestinal dysbiosis and mucosal damage often exacerbate gastrointestinal and systemic pain syndromes. Notably, psychobiotics also contribute to analgesia by producing neuroactive compounds, such as gamma-aminobutyric acid (GABA), serotonin, and short-chain fatty acids, specifically butyrate, all of which are involved in the regulation of sensory neuron excitability [25].
Although clinical trials remain few in number, improvements in abdominal pain, pain interference scores, and the overall symptom burden in cancer patients receiving adjunctive probiotic therapy have been reported [32]. Collectively, evidence supports further investigation of psychobiotics as a promising non-opioid adjunct in the multidisciplinary management with GI cancer-related pain in patients undergoing surgical excision plus chemotherapy. Recently, we performed a randomized placebo-controlled trial (the ProDeCa study) to investigate the effects of a specific psychobiotic regime to ameliorate depression status, as well as anxiety and stress parameters, in participants in a chemotherapy course for a newly operated GI malignancy [33].
In the present post hoc analysis, we aimed to investigate the potential analgesic effects of psychobiotics or placebo, given as a 1-month add-on treatment to classically prescribed analgesics. We mainly focused on the non-depressed participants who—at the beginning of the postoperative chemotherapy course—were self-assessed by means of the McGill Pain Questionnaire and found to be experiencing pain. In parallel, we assessed the corresponding group of depressed individuals—already allocated to psychobiotics or placebo, both sub-groups receiving standardized analgesic treatment.

2. Materials and Methods

2.1. Study Design and Participants

This post hoc analysis is based on data derived from the recently published ProDeCa study [33]. Eligible participants were adults, aged ≥ 18 years, on postoperative chemotherapy for GI oncology, after tumor resection, having the ability to provide informed consent, and with no cognitive impairment. Exclusion criteria also included active psychiatric disorders or a history of suicide attempts and not being on prescribed antidepressants or recent antibiotic or probiotic use within 4 weeks prior to enrollment and severe immunosuppression.

2.2. Depression Assessment and Study Groups

Upon study enrollment, and after participants were randomly allocated to the psychobiotics or placebo groups, they were assessed for the existence of depression symptoms by means of the 17-item Hamilton Depression Rating Scale (HDRS-D-17) and the Beck’s Depression Inventory (BDI-II) score. Participants were thus classified as depressed or non-depressed based on an established cut-off point score; specifically, an HDRS-D-17 total score of ≤7 was considered indicative of non-depression, while scores above this threshold indicated clinically relevant depressive symptoms [34]. For this post hoc analysis, we predominantly used the participants classified as non-depressed in order to specifically evaluate the effects of 1-month psychobiotics treatment or placebo on pain perception; for comparisons, the depressed groups—psychobiotics- or placebo-treated—were also used. For the better understanding of the effects of psychobiotics on pain perception, in this analysis, we followed each participant from baseline (T0) to treatment termination at T1 and then to the end of the 3rd month, follow-up, at T2.

2.3. Pain Evaluation

Pain perception was assessed using the Short-Form McGill Pain Questionnaire (MPQ-SF), a validated and widely used self-report instrument that measures both sensory and affective components of pain through a series of descriptive adjectives, although it does not employ established clinical cut-off points [20,35]. It consists of (i) the Pain Rating Index, which has a multidimensional profile, by adding sensory (11 items) and affective (4 items) dimensions of pain quality and intensity, rated on a Likert scale (0 = no pain, 1 = mild, 2 = moderate, and 3 = severe), the possible range of scores being from 0 to 45; (ii) a visual analog VAS scale (16th item) ranging from 0 (no pain) to 100 (worst possible pain); and (iii) an indicator of present pain intensity (PPI), the 17th item. The PPI scale measures pain experienced right now based on a 6-point Likert scale with choices of 0 = no pain, 1 = mild, 2 = discomforting, 3 = distressing, 4 = horrible, and 5 = excruciating. Assessments were conducted at baseline (prior to treatment initiation—T0); 4 weeks later, upon treatment termination (T1), and at the end of the 3rd month—at follow-up (T2).
We initially assessed the participants quantitively: We recorded the number of subjects in pain at baseline within each group (non-depressed and depressed plus psychobiotics or placebo) and the differentiation in the number at T1 and T2. We then assessed them qualitatively: each subject was recorded as presenting pain intensity at T0, T1, and T2; and finally, in a more detailed manner, we recorded the pain rating index at T0, T1, and T2, analytically considering the sensory and affective components of their pain at each time-point.

2.4. Chemotherapy and Pain Management Scheme—Protocols

All GI cancer patients receiving chemotherapy after tumor surgical resection were allocated to either the FOLFOX scheme (5-fluorouracil (5-Fu), leucovorin (folinic acid), and oxaliplatin) mainly for colorectal cancer affecting the majority of our study population or the FOLFIRI scheme (5-Fu, leucovorin and irinotecan), per protocol.
Regarding pain management protocols, all participants were closely monitored as outpatients at the Chronic Pain Management Unit of our university hospital and treated according to the WHO three-step pain ladder [36], which, for decades, has remained the keystone to cancer pain management. According to this scheme, NSAIDs and paracetamol (acetaminophen) constitute the first step of the WHO ladder and have also been added as important components of the second and even third step, with moderate-to-severe pain. Weak opioids—codeine or tramadol—plus paracetamol or tramadol alone in higher doses of up to 300 mg/day constitute the second step, where codeine and tramadol may be switched for better patient response. Finally, strong opioids (morphine, fentanyl, methadone) in combination with NSAIDs or paracetamol are introduced at the third step [37]. In Greece, fentanyl is preferred to morphine and is used in the form of dermal patches plus nasal or sublingual sprays in the case of paroxysmal pain attack. However, between weak opioids and a strong one, fentanyl, the new therapeutics oxycodone or tapentadol may be taken orally. Almost all the participants of the present study relied on step 2, except for 9 pancreatic cancer patients additionally taking tapentadol.

2.5. Intervention Protocol

Individuals allocated to the psychobiotic group, twice daily, received a formulation of four psychobiotics at a daily dose of 1.76 × 1011 CFU; the regime contained the following bacterial strains at the specified doses: Bifidobacterium animalis subsp. lactis LMG P-21384 (BS01) (2.50 × 1010 CFU), Bifidobacterium breve DSM 16604 (BR03) (1.00 × 1010 CFU), Bifidobacterium longum DSM 16603 (BL04) (8.00 × 109 CFU), and Lacticaseibacillus rhamnosus ATCC 53103 (GG) (4.50 × 1010 CFU). The total duration of the intervention was 4 weeks, starting at the beginning of the chemotherapy course. The placebo sachets were identical in packaging, appearance, consistency, and solubility in drinking water, as well as in taste and smell, to ensure blinding. Compliance was assessed by capsule counts at the end of treatment.

2.6. Statistics

The normality of the data distribution was assessed by performing the Kolmogorov–Smirnov test. Continuous variables were presented as means ± standard deviation (SD) when normality was assumed or as median and interquartile range (IQR) when normality was violated. Categorical variables were presented as absolute numbers and proportions. For a comparison of means between independent samples, the Student t-test was applied when the data followed a normal distribution, whereas the Mann–Whitney U test otherwise. For related samples, the Wilcoxon signed-rank test was used for two-group comparisons, and the Friedman test for three consecutive assessments within the same group. For categorical data, the chi-square test was used. When subgroup comparisons were performed, Bonferroni correction was applied to adjust for multiple testing. Statistical significance was set at a two-tailed α level of 0.05. All analyses were performed using IBM SPSS Statistics for Windows, version 25.0 (IBM Corp., Armonk, NY, USA), while graphs were drawn with both the Microsoft Excel (Microsoft Office Professional Plus 2019) and the GraphPad Prism, version 10.5.0 for Windows (GraphPad Software, Boston, MA, USA).

3. Results

For this post hoc analysis, we used the participants of the ProDeCa study [33]—classified as non-depressed (HDRS-D-17 score ≤ 7) or depressed at baseline and then allocated to the psychobiotics or placebo groups—in order to evaluate the effects of 1-month psychobiotic treatment or placebo on pain perception. We specifically focused on the effectiveness of psychobiotics against placebo on cancer pain perception in the group of non-depressed individuals because it is, theoretically, a more mentally “stable” population. For comparisons, we referred to the matching depressed groups.

3.1. Demographics

In this post hoc analysis, we primarily referred to 167 non-depressed participants, already allocated to psychobiotics (n = 84) or to placebo (n = 83) groups. Regarding the other group of 99 depressed participants, there were 48 in the psychobiotics and 51 in the placebo groups (p = 0.775). Their baseline demographic characteristics and all other related information are tabulated in Supplementary Table S1.

3.2. Evaluation of the Number of Participants Experiencing Pain in Each Group

There was no statistically significant difference identified between the numbers of non-depressed and depressed participants experiencing pain, all self-assessing by means of the VAS scale: there were 58 out of the 167 (34.73%) and 41 out of the 99 (41.41%) (chi square = 1.188, p = 0.276).
When we further analyzed these pain-suffering participants with respect to the psychobiotic treatment they had been previously allocated, 27 out of 58 (46.55%) and 18 out of 41 (43.90%) were found in non-depressed and depressed groups, respectively. In the same manner, there were 31 out of 58 (53.45%) and 23 out of 41 in the non-depressed and depressed groups taking the placebo. In other words, there was no difference, at baseline, in the number (or the ratio) of participants suffering pain among each of the four groups (chi square = 0.068, p = 0.794) (Table 1).

3.3. Assessment of Pain Intensity Based on VAS Score

When the pain intensity was quantitatively analyzed using the Visual Analogue Scale (VAS—max 100 points), a statistically significant decline was found after the 1-month psychobiotics treatment in the non-depressed group (T0 to T1, p = 0.002), further declining progressively, beyond the treatment termination (T1 to T2 p = 0.001 and T0–T3 p < 0.001). Placebo-treated participants (non-depressed) presented a progressively significant increase in pain, obviously due to disease aggravation (T0–T2, p = 0.008) (Table 2).
Correspondingly, the depressed group taking the psychobiotics also presented a decrease in pain intensity at T1, p = 0.029, compared with T0, and, further on, at T2, p = 0.046, compared with T1, thus achieving a significant reduction (T0 to T2, p = 0.002). Placebo-treated participants (depressed) presented a small but statistically significant increase in pain intensity over time (p = 0.023 between T1 and T2, p = 0.035 between T0 and T2).
Based on all of the above, it is prominent that non-depressed individuals experience pain of higher intensity in comparison with depressed ones, independently of receiving either psychobiotics or placebo. This difference is clearly shown in Figure 1.

3.4. Present Pain Intensity Index

By analyzing the results obtained after self-assessment of the present pain intensity index (graded as 0—no pain; 1—mild; 2—discomfort; 3—distressing; 4—horrible; and 5—excruciating pain), we found a significant decrease in the groups of non-depressed and depressed participants who had taken psychobiotics and a significant increase in the groups of non-depressed and depressed participants who had taken placebo (Table 3, Figure 2).

3.5. Pain Rating Index

Finally, by calculating the total pain rating index, that is, the sum of the severity assessment (rating from 0 to 3) of each of the 15 items of the McGill short-form questionnaire, characterizing the pain quality at each time-point (T0, T1, and T2), we found the following deviations, both within the four groups and between them (Table 4).
The initial observations on these results are that (i) the non-depressed participants presented with a higher pain rating index in relation to the depressed group, irrespective of the treatment (psychobiotics or placebo); (ii) the psychobiotics significantly decreased the pain rating index over time in non-depressed participants, while a progressively, but not significant, decreasing index (less pain) was present in the depressed, psychobiotics-treated participants; and (iii) the placebo—independently of the mood status (non-depressed—depressed) of participants—kept the pain rating index stable during the treatment period, while presenting a significant increase (more pain) thereafter.
Next, we analyzed the pain rating index of each of the 15 items—descriptors, which are presented in Supplementary Table S2, per study group. Since it is known that the first 11 descriptors (items 1–11) refer to somatic or sensory pain and the other four (items 12–15) to emotional of affective pain, we then assessed them separately for each of the study groups. Thus, we identified the most common types of sensory pain (11 items) described by non-depressed participants at T0 to be throbbing, shooting, sharp, cramping, and gnawing, while stabbing, shooting, cramping, and gnawing were described by depressed participants. Regarding the affective dimension of pain (4 items), the most common was the fearful type in non-depressed and the sickening, fearful, and punishing/cruel types in depressed individuals. In both mood categories, the lowest proportion had the tender-type pain. Based on all of the above, it is clear again that non-depressed individuals expressed statistically higher pain scores in each one of the parameters—descriptors in relation to the depressed. Additionally, they used slightly different expressions to describe both the sensory and the affective pain in relation to depressed individuals. These differences are clearly shown in Figure 3a,b.
Then, we statistically assessed the above findings separated into the two types of pain, the sensory and the affective pain. It is clear that there was a statistically significant reduction in the sensory pain rating index (p = 0.04), as well as in the affective pain rating index (p < 0.001) in non-depressed participants who had taken psychobiotics. The same trend (reduction—but not significant) was observed in the sensory (p = 0.128) and the affective pain rating index (p = 0.28) in depressed participants who had taken psychobiotics.
However, there was a statistically significant increase in the sensory pain rating index (p < 0.001) and a trend towards an increase only in the affective pain rating index (p = 0.123) in non-depressed participants taking the placebo. The same trend (significant increase) was observed in the sensory (p = 0.03) and the affective pain rating index (p = 0.025) in depressed participants taking the placebo. The descriptive statistics (min, max, mean (SD), and median (IQR)) of both the pain-origin groups throughout the study periods are presented in Table 5, while the fluctuations of values in the pain rating index of each of the 11 sensory and the 4 affective descriptors at the three time-points per group of participants are presented in Figure 4a,b.
Finally, after psychobiotics or placebo treatment (T1), as well as at follow-up (T2) at 3 months from baseline (T0), a differentiation of the values of each descriptor is prominent, the sum of which expresses the total score of the pain rating index. The differences per item (increase, decrease, or remain stable) are illustrated in a spider graph (Figure 5a–d).

4. Discussion

In this post hoc analysis of patients who received psychobiotics or placebo after being operated on for gastrointestinal cancer and being on a chemotherapy course, we found that non-depressed ones—as determined by the HDRS-D-17 score—experienced a greater reduction in pain intensity, during and after psychobiotic treatment in comparison with placebo-treated ones. The same reduction trend, but to a much lower degree, and with no statistically significant differences between study time-points, was also observed in depressed individuals.
Cancer, of whatever etiology, is a multifactorial disease, directly associated with intense pain and fatigue. Furthermore, pain is the foremost distress experienced during cancer treatment, particularly as a consequence of surgical trauma and a major side effect of the subsequent chemotherapy [38,39]. Cancer-related pain involves a complex interplay of physiological, psychological, emotional, and social factors; additionally, spiritual components, gender, and even a preoperative pain history, pain fear, and pain sensitivity seem to ultimately have a significant impact on an individual’s pain and thus, finally, on their quality of life [40,41,42,43,44,45].
Despite the advancements and novelty in pharmacological approaches, the improvements in dosage monitoring being adjustable to personal needs [46,47], and the updated pain guidelines [48], the optimization of pain management remains a challenge [39,42]. Even today, it is an open secret that more than 70% of individuals with cancer experience the distressing symptom of pain, nearly half of which is inadequately controlled [15,49], and even more, some patients do not receive adequate pain medication [2,50,51,52]. At the same time, addiction to analgesics and the adverse events of pharmacological interventions in general also continue to pose critical challenges to pain management [53,54].
The European “Pain in Cancer” survey in adults reported that 56% of cancer patients experience moderate to severe pain (≥5 out of 10 on a numeric rating scale (NRS)) at least several days a month, while 27% rate their pain as severe (≥7 of 10 on NRS). Furthermore, only 24% of cancer patients receive strong opioids, and up to 11% of those with moderate to severe pain receive no analgesia at all. This inadequate pain management has led to distress in 67% of patients and the desire for death in 32% [55]. In the same manner, according to a recent meta-analysis, the prevalence of pain faced by cancer patients analyzed during the period 2014 to 2021 was found to be 44.5%, while the ratio of moderate to severe pain in the same population was 30.6% [56]. In the present analysis, we found, at baseline, that 99 out of the 266 participants (37.2%) had to live with some type and/or intensity of pain, the ratio being quite similar in both non-depressed and depressed participants, this occurring despite the adequate doses of analgesics taken, since all were routinely monitored by the medical staff of the Pain Management Clinic, as per protocol.
Emotional distress has been revealed to be significantly associated with pain perception; the higher the level of psychological distress, including depression, anxiety, hostility, mood disturbances, and anger, the higher the concomitant pain intensity [57,58]. In our cohort, when the participants were split according to their mood status—specifically depression or non-depression—41 out of the 99 depressed individuals (41.4%) as opposed to 58 out of the 167 (34.7%) reported various pain intensities. At a first glance, the difference is not so interesting. However, when the pain intensity was quantitatively analyzed by means of the Visual Analogue Scale, the maximum being 100 points, it was surprisingly found that the non-depressed had a higher intensity of pain, at a level of almost 10 points higher, in relation to the depressed; in other words, pain perception, contrary to general thoughts, was “depressed” in depressed participants, despite the fact that none received antidepressants (Table 2). Furthermore, when we calculated the pain rating index using the short-form 15-item questionnaire of McGill, we identified the median sensory pain score, being the sum of the first 11 items/descriptors, as only 7 (0 to 33) for the depressed participants in contrast with the non-depressed, which was 12 (0 to 33). Similarly, regarding the affective dimension of pain (4 items), the median score was 1.5 (0 to 12) in depressed and 4.5 (0 to 12) in non-depressed individuals. Based on these findings, we can assume that the depressed participants experienced dark moods, sadness, and uncertainty derived from their understanding of the progression of their illness, resulting in their giving up all interests in life and all efforts to fight the disease. This could be why they self-assessed with lower pain scores. This option is also further supported by the pain scores found during the study progress, which will be discussed a little below.
Besides the splanchnic pain due to gastrointestinal cancer itself and the postoperative pain, it is well accepted that more than half of such a population develops chemotherapy-induced peripheral neuropathy, caused by multiple chemotherapeutic drugs that can induce damage to sensory, motor, autonomic, or cranial nerves; such a neuropathy is perceived and commonly described as numbness, loss of proprioception sense, tingling, burning pins and needles, hyperalgesia, or an acute pain syndrome [12,59,60,61]. The chemotherapy-induced peripheral neuropathy is a prominent dose-limiting toxicity of either oxaliplatin or irinotecan given to cancer patients, all contained within the FOLFOX or FOLFIRI treatment schemes applied to our patients. Specifically, oxaliplatin, besides causing a dose-dependent chronic sensory neuropathy, is also able to trigger an acute sensory neuropathy, classically characterized by cold-induced paresthesia and muscle cramping sensations [61,62]. Furthermore, many of the post-treatment pain syndromes, including those related to surgical trauma—incidences of which vary relating to surgery type or even to the impact of muscle retractors [5,6,38,63]—have a component of neuropathic pain; Pogatzki-Zahn et al. [64] documented them using functional MRI changes in brain activation during incisional pain in healthy volunteers, affecting the secondary somatosensory cortex, the frontal cortex, and the limbic system. Neuropathic pain is clinically manifested as allodynia, that is, pain from innocuous stimuli, or hyperalgesia—exaggerated response to a common painful stimulus, alternatively, as spontaneous or continuous pain, described as paresthesia or dysesthesia, or lightning-like unprovoked pain, along with psychiatric comorbidities, which in turn enhance pain perception [65,66,67,68,69,70].
In recent years, several trials have emphasized the positive effects of probiotics on various aspects of mental and emotional state, from mood disorders to pain perception [71]. Early studies by Rousseaux et al. [28] on human HT-29 epithelial cells revealed the ability of L. acidophilus NCFM and L. salivarius Ls-33 to induce a sustained increase in OPRM1 mRNA (-opioid) expression and only of L. acidophilus NCFM to induce, additionally, CNR2 mRNA (cannabinoid) expression. Then, in a colonic distension rat model, the oral administration of L. acidophilus NCFM was found to decrease the normal visceral perception, allowing a 20% increase in pain threshold, or resulting in an anti-nociceptive effect of the same magnitude as that achieved by 0.1 mg/kg morphine, given subcutaneously. The authors thus concluded that the close contact of L. acidophilus NCFM with the gut epithelial cells is able to induce, via the NF-B pathway, opioid and cannabinoid receptors to mediate the normal perception of visceral pain, as also occurring with morphine [28]. Furthermore, in a more recent study, the probiotic regime of L. helveticus R0052 and B. longum R0175, both having psychotropic effects, was reported to attenuate the HPA axis-induced stress response [72], as also occurs with B. longum SX-1326 [73], which has also been found to alleviate irinotecan side effects by means of reversing gut dysbiosis, increasing the abundance of Dehalobacterium, Ruminococcus, and Mucispirillum in a colorectal cancer model in mice. At the same time, Wang et al. [74], in a murine model of chronic gut constriction injury, showed that a 15-probiotic regime can improve neuropathic pain and muscle atrophy, the improvement being attributed to the ability of probiotics to manage pain of inflammatory origin. Furthermore, their findings of probiotic-induced gut microbiota repair—mainly by reversing the significantly decreased abundance of Akkermansia and increased Ruminococcaceae, considered to be the cause of neuropathic pain—led them to suggest that probiotics could be utilized for treatment [74].
From this point of view, psychobiotics (a plethora of specific probiotic bacteria), since their introduction by Ted Dyan and John Cryan in 2013 [75,76], are well established due to their unique characteristics of producing and delivering neuroactive substances such as gamma-aminobutyric acid and tryptophan, which assist in serotonin synthesis, act on the brain–gut axis, and generally manifest beneficial effects in psychiatric illness, by means of modifying the disturbed microbiome abundance, on a strictly specific strain level [77,78,79,80]. Their psychotropic properties have already been established both experimentally and in humans [33,81,82,83,84], while the direct role of 5-HT in pain, and more specifically that of visceral origin, is also well documented [85,86,87,88].
In a recent randomized double-blind controlled clinical study [33], we found the a four-psychobiotic regime containing Bifidobacterium animalis subsp. lactis LMG P-21384 (BS01) (2.50 × 1010 cfu/dose), Bifidobacterium breve DSM 16604 (BR03) (1.00 × 1010 cfu/dose), Bifidobacterium longum DSM 16603 (BL04) (8.00 × 109 cfu/dose), and Lacticaseibacillus rhamnosus ATCC 53103 (GG) (4.50 × 1010 cfu/dose), administered for a month against placebo twice daily (total daily dose of 1.76 × 1011 cfu), resulted in a significant improvement in depression status, as well as in anxiety and stress levels. The present post hoc analysis of data from the previous study [33] revealed that, indeed, psychobiotic treatment significantly reduced the pain intensity assessed by the VAS score, as well as the present pain intensity index and the total pain rating index (McGill questionnaire, short form) after a month of treatment, only in the non-depressed participants; depressed participants, having at baseline a significantly lower pain perception than non-depressed ones, presented only a reduction trend with no statistical difference. For comparison, both groups taking placebo exhibited a progressive reduction in pain levels, clearly attributable to disease exacerbation.
The presence of a significantly lower pain intensity index and total pain rating index in the depressed participants versus the non-depressed ones—either receiving psychobiotics or placebo—sounds strange and questionable, since it is well recognized that a balanced mental state copes better with all stressful stimuli. The theory of “gate-control” might explain it, since its ultimate conclusion is that the pain process can be mediated by changing the way a person cognitively processes his/her pain experience [89]. Normally, the pain can be transmitted to the patient’s brain through nerves and activates the relevant prefrontal cortex and other regions, which could affect the normal emotion regulation when the region receives pain signals. The “gate”, located somewhere within the brain, may be opened or closed, its situation determining the amount of pain the individual experiences. The pain message originates at the point of aggravation, the signal is transmitted to the brain, and the pain is then perceived by the person only if the gate is open. The use of coping strategies may close the gate, meaning that the brain will not recognize or give credence to the pain signal; or the gate may be opened, bringing the pain signal to the brain’s awareness, meaning that the patient focuses on thoughts of pain [89].
Based on or affected by the “gate-control theory”, other authors further analyze and explain the findings either as due to perception and reporting bias or simply as due to differences in coping mechanisms. Depressed individuals may underreport their physical symptoms, including pain, due to general apathy, emotional blunting, or reduced interoceptive awareness that often accompanies depressive states. Others suggest that depressed individuals may develop pain tolerance or resignation as a coping mechanism, as opposed to non-depressed individuals who might be more reactive or attentive to pain sensations [90]. This option is also supported by the biochemical theory of depression, which suggests that a neurochemical imbalance of monoamines, as is serotonin, underlies depression, and since these neurotransmitters are likely to play a key role in modulatory pain pathways, this may lead to altered pain perception [91]. Additionally, a preliminary meta-analysis of 6 experimental studies [92] reported decreased pain in depressed groups relative to healthy control groups. This finding has become more significant after a new meta-analysis—the largest and most comprehensive to date—of 25 studies (567 depressed and 587 healthy participants) investigating responses to experimentally induced pain, which revealed a higher overall pain threshold, meaning reduced pain in the depressed in comparison with healthy participants [91].
The present host hoc analysis has some limitations: First of all, pain perception is a totally subjective experience, which means that each participant may subjectively sense, experience, and interpret the meaning of his/her pain uniquely; thus, we, as physicians, have no other choice but to rely on patient self-reports. Therefore, the assessment of pain at baseline and its response to the analgesic treatment protocol is totally affected by the patient’s emotional status, probably beyond the pain perception itself. Second, the present study is a post hoc analysis and not a double-blind randomized clinical trial. However, since the McGill short-form questionnaire was completed at the same time as the HDRS-D-17 and Beck’s II scores for depression, the investigation was blind and the participants had already been randomized to psychobiotics or placebo; thus, the participants were interviewed blindly as to the treatment, and the non-blind analysis refers only to the division of the participants according to their depression status and not to their treatment. Third, the “non-common sense” finding that non-depressed participants demonstrated greater pain reduction following psychobiotic intervention would be accepted under the knowledge of the difference in the severity of disruption of the gut microbiota diversity in non-depressed and depressed participants. An analysis of the participants’ microbiota could potentially shed more light on this issue, but the purpose of our research protocol was purely clinical and completely non-invasive. Fourth, we have to mention that the study participants received two distinct chemotherapy regimens, the FOLFOX and the FOLFIRI, which, theoretically, have the potential to affect the treatment outcome; since both depression and pain are closely related to the gut microbiota composition, a possible disturbance of microbial diversity could alter the severity of depression or pain perception. Finally, the number of depressed individuals who were allocated to psychobiotic treatment presented a decline after a month of treatment because of the improvement in depression status; it would be of interest to be able to study them as a sub-group of former depressed individuals who became non-depressed after psychobiotics, especially in relation to pain intensity. However, the number of such cases is too small for statistical analysis.

5. Conclusions

Based on the above, we conclude that the psychobiotic formula used, taken as adjuvant to routine analgesics for a month, seems to ameliorate pain intensity during the treatment period—and possibly up to 2 months thereafter. This is evidence at a highly significant level in non-depressed individuals and to a lesser degree in depressed individuals. The value of this finding becomes greater when taking into account the sub-cohorts of non-depressed and depressed participants taking placebo: they not only do not enjoy an alleviation of pain intensity, qualitatively and quantitively, but also experience deterioration due to both the disease progression and the continuing detrimental effects of chemotherapy on both the body and the mood.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/nu17172751/s1. Table S1: Demographic characteristics; Table S2: Descriptive statistics of the qualities of pain.

Author Contributions

Conceptualization, J.K.T., H.T., A.K., and K.K.; data curation, G.T. and H.T.; formal analysis, G.T.; investigation, A.A., A.-E.M., and I.M.T.; methodology, G.T. and G.S.; project administration, V.G. and K.K.; resources, E.C., A.A., and J.K.T.; software, G.T. and A.-E.M.; supervision, A.K. and K.K.; validation, V.G., A.-E.M., I.M.T., and G.S.; visualization, A.D.S. and K.K.; writing—review and editing, G.T. and G.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the AHEPA University Hospital of Thessaloniki, Greece (Scientific Council of the AHEPA Hospital, 313, 4 July 2023).

Informed Consent Statement

Informed consent was obtained from all the subjects involved in this study.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author, K.K.

Acknowledgments

We would like to thank the pharmaceutical company Uni-Pharma, SA, Athens, Greece, for the kind donation of psychobiotics.

Conflicts of Interest

The author Joulia K. Tsetis, a pharmacist, was employed by the company Uni-Pharma S.A. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Raja, S.N.; Carr, D.B.; Cohen, M.; Finnerup, N.B.; Flor, H.; Gibson, S.; Keefe, F.J.; Mogil, J.S.; Ringkamp, M.; Sluka, K.A.; et al. The revised International Association for the Study of Pain definition of pain: Concepts, challenges, and compromises. Pain 2020, 161, 1976–1982. [Google Scholar] [CrossRef]
  2. van den Beuken-van Everdingen, M.H.; de Rijke, J.M.; Kessels, A.G.; Schouten, H.C.; van Kleef, M.; Patijn, J. Prevalence of pain in patients with cancer: A systematic review of the past 40 years. Ann. Oncol. 2007, 18, 1437–1449. [Google Scholar] [CrossRef] [PubMed]
  3. Fallon, M.; Giusti, R.; Aielli, F.; Hoskin, P.; Rolke, R.; Sharma, M.; Ripamonti, C.I. Management of cancer pain in adult patients: ESMO Clinical Practice Guidelines. Ann. Oncol. 2018, 29, iv166–iv191. [Google Scholar] [CrossRef] [PubMed]
  4. Bennett, M.I.; Eisenberg, E.; Ahmedzai, S.H.; Bhaskar, A.; O’Brien, T.; Mercadante, S.; Krčevski Škvarč, N.; Vissers, K.; Wirz, S.; Wells, C.; et al. Standards for the management of cancer-related pain across Europe-A position paper from the EFIC Task Force on Cancer Pain. Eur. J. Pain 2019, 23, 660–668. [Google Scholar] [CrossRef]
  5. Fyntanidou, B.; Amaniti, A.; Soulioti, E.; Zagalioti, S.C.; Gkarmiri, S.; Chorti, A.; Loukipoudi, L.; Ioannidis, A.; Dalakakis, I.; Menni, A.E.; et al. Probiotics in Postoperative Pain Management. J. Pers. Med. 2023, 13, 1645. [Google Scholar] [CrossRef]
  6. Kotzampassi, K. Why Give My Surgical Patients Probiotics. Nutrients 2022, 14, 4389. [Google Scholar] [CrossRef]
  7. Kehlet, H.; Jensen, T.S.; Woolf, C.J. Persistent postsurgical pain: Risk factors and prevention. Lancet 2006, 367, 1618–1625. [Google Scholar] [CrossRef]
  8. Wildgaard, K.; Ravn, J.; Kehlet, H. Chronic post-thoracotomy pain: A critical review of pathogenic mechanisms and strategies for prevention. Eur. J. Cardiothorac. Surg. 2009, 36, 170–180. [Google Scholar] [CrossRef]
  9. Althaus, A.; Hinrichs-Rocker, A.; Chapman, R.; Arránz Becker, O.; Lefering, R.; Simanski, C.; Weber, F.; Moser, K.H.; Joppich, R.; Trojan, S.; et al. Development of a risk index for the prediction of chronic post-surgical pain. Eur. J. Pain 2012, 16, 901–910. [Google Scholar] [CrossRef] [PubMed]
  10. Woolf, C.J. Central sensitization: Implications for the diagnosis and treatment of pain. Pain 2011, 152, S2–S15. [Google Scholar] [CrossRef]
  11. Seretny, M.; Currie, G.L.; Sena, E.S.; Ramnarine, S.; Grant, R.; MacLeod, M.R.; Colvin, L.A.; Fallon, M. Incidence, prevalence, and predictors of chemotherapy-induced peripheral neuropathy: A systematic review and meta-analysis. Pain 2014, 155, 2461–2470. [Google Scholar] [CrossRef]
  12. Staff, N.P.; Grisold, A.; Grisold, W.; Windebank, A.J. Chemotherapy-induced peripheral neuropathy: A current review. Ann. Neurol. 2017, 81, 772–781. [Google Scholar] [CrossRef]
  13. Starobova, H.; Vetter, I. Pathophysiology of Chemotherapy-Induced Peripheral Neuropathy. Front. Mol. Neurosci. 2017, 10, 174. [Google Scholar] [CrossRef]
  14. Chen, X.; Gan, Y.; Au, N.P.B.; Ma, C.H.E. Current understanding of the molecular mechanisms of chemotherapy-induced peripheral neuropathy. Front. Mol. Neurosci. 2024, 17, 1345811. [Google Scholar] [CrossRef]
  15. van den Beuken-van Everdingen, M.H.; Hochstenbach, L.M.; Joosten, E.A.; Tjan-Heijnen, V.C.; Janssen, D.J. Update on Prevalence of Pain in Patients with Cancer: Systematic Review and Meta-Analysis. J. Pain Symptom Manag. 2016, 51, 1070–1090.e1079. [Google Scholar] [CrossRef]
  16. Mendoza-Contreras, L.A.; Domínguez Trejo, B.; Guillén Núñez, M.D.R.; Rodríguez Medina, D.A.; Pardo, X.M.; Estapé, T.; Vázquez, O.G. Psychometric properties of the Short-Form McGill Pain Questionnaire (SF-MPQ) in adult Mexican cancer patients with chronic pain. Palliat. Support. Care 2025, 23, e20. [Google Scholar] [CrossRef]
  17. Wiech, K.; Tracey, I. The influence of negative emotions on pain: Behavioral effects and neural mechanisms. Neuroimage 2009, 47, 987–994. [Google Scholar] [CrossRef]
  18. Schreier, A.M.; Johnson, L.A.; Vohra, N.A.; Muzaffar, M.; Kyle, B. Post-Treatment Symptoms of Pain, Anxiety, Sleep Disturbance, and Fatigue in Breast Cancer Survivors. Pain Manag. Nurs. 2019, 20, 146–151. [Google Scholar] [CrossRef]
  19. Cleeland, C.S.; Ryan, K.M. Pain assessment: Global use of the Brief Pain Inventory. Ann. Acad. Med. Singap. 1994, 23, 129–138. [Google Scholar]
  20. Melzack, R. The short-form McGill Pain Questionnaire. Pain 1987, 30, 191–197. [Google Scholar] [CrossRef]
  21. Bozzetti, F.; Mariani, L.; Lo Vullo, S.; Amerio, M.L.; Biffi, R.; Caccialanza, G.; Capuano, G.; Correja, I.; Cozzaglio, L.; Di Leo, A.; et al. The nutritional risk in oncology: A study of 1453 cancer outpatients. Support. Care Cancer 2012, 20, 1919–1928. [Google Scholar] [CrossRef]
  22. Cleeland, C.S.; Zhao, F.; Chang, V.T.; Sloan, J.A.; O’Mara, A.M.; Gilman, P.B.; Weiss, M.; Mendoza, T.R.; Lee, J.W.; Fisch, M.J. The symptom burden of cancer: Evidence for a core set of cancer-related and treatment-related symptoms from the Eastern Cooperative Oncology Group Symptom Outcomes and Practice Patterns study. Cancer 2013, 119, 4333–4340. [Google Scholar] [CrossRef]
  23. Bhuvan, K.C.; Yusoff, Z.B.M.; Alrasheedy, A.A.; Othman, S. The Characteristics and the Pharmacological Management of Cancer Pain and Its Effect on the Patients’ Daily Activities and their Quality of Life: A Cross—Sectional study from Malaysia. J. Clin. Diagn. Res. 2013, 7, 1408–1413. [Google Scholar] [CrossRef]
  24. Lohman, D.; Schleifer, R.; Amon, J.J. Access to pain treatment as a human right. BMC Med. 2010, 8, 8. [Google Scholar] [CrossRef]
  25. Cryan, J.F.; O’Riordan, K.J.; Cowan, C.S.M.; Sandhu, K.V.; Bastiaanssen, T.F.S.; Boehme, M.; Codagnone, M.G.; Cussotto, S.; Fulling, C.; Golubeva, A.V.; et al. The Microbiota-Gut-Brain Axis. Physiol. Rev. 2019, 99, 1877–2013. [Google Scholar] [CrossRef]
  26. Dinan, T.G.; Cryan, J.F. Gut microbiota: A missing link in psychiatry. World Psychiatry 2020, 19, 111–112. [Google Scholar] [CrossRef]
  27. Liu, Y.W.; Liu, W.H.; Wu, C.C.; Juan, Y.C.; Wu, Y.C.; Tsai, H.P.; Wang, S.; Tsai, Y.C. Psychotropic effects of Lactobacillus plantarum PS128 in early life-stressed and naïve adult mice. Brain Res. 2016, 1631, 1–12. [Google Scholar] [CrossRef]
  28. Rousseaux, C.; Thuru, X.; Gelot, A.; Barnich, N.; Neut, C.; Dubuquoy, L.; Dubuquoy, C.; Merour, E.; Geboes, K.; Chamaillard, M.; et al. Lactobacillus acidophilus modulates intestinal pain and induces opioid and cannabinoid receptors. Nat. Med. 2007, 13, 35–37. [Google Scholar] [CrossRef]
  29. Cuozzo, M.; Castelli, V.; Avagliano, C.; Cimini, A.; d’Angelo, M.; Cristiano, C.; Russo, R. Effects of Chronic Oral Probiotic Treatment in Paclitaxel-Induced Neuropathic Pain. Biomedicines 2021, 9, 346. [Google Scholar] [CrossRef]
  30. O’Mahony, S.M.; Clarke, G.; Borre, Y.E.; Dinan, T.G.; Cryan, J.F. Serotonin, tryptophan metabolism and the brain-gut-microbiome axis. Behav. Brain Res. 2015, 277, 32–48. [Google Scholar] [CrossRef]
  31. Ringel-Kulka, T.; Palsson, O.S.; Maier, D.; Carroll, I.; Galanko, J.A.; Leyer, G.; Ringel, Y. Probiotic bacteria Lactobacillus acidophilus NCFM and Bifidobacterium lactis Bi-07 versus placebo for the symptoms of bloating in patients with functional bowel disorders: A double-blind study. J. Clin. Gastroenterol. 2011, 45, 518–525. [Google Scholar] [CrossRef] [PubMed]
  32. Shi, H.; Chen, M.; Zheng, C.; Yinglin, B.; Zhu, B. Fecal Microbiota Transplantation Alleviated Paclitaxel-Induced Peripheral Neuropathy by Interfering with Astrocytes and TLR4/p38MAPK Pathway in Rats. J. Pain Res. 2023, 16, 2419–2432. [Google Scholar] [CrossRef] [PubMed]
  33. Tzikos, G.; Chamalidou, E.; Christopoulou, D.; Apostolopoulou, A.; Gkarmiri, S.; Pertsikapa, M.; Menni, A.-E.; Theodorou, I.M.; Stavrou, G.; Doutsini, N.-D.; et al. Psychobiotics Ameliorate Depression and Anxiety Status in Surgical Oncology Patients: Results from the ProDeCa Study. Nutrients 2025, 17, 857. [Google Scholar] [CrossRef]
  34. Zimmerman, M.; Martinez, J.H.; Young, D.; Chelminski, I.; Dalrymple, K. Severity classification on the Hamilton Depression Rating Scale. J. Affect. Disord. 2013, 150, 384–388. [Google Scholar] [CrossRef]
  35. Melzack, R.; Torgerson, W.S. On the language of pain. Anesthesiology 1971, 34, 50–59. [Google Scholar] [CrossRef]
  36. World Health Organization. WHO’s Pain Ladder. Available online: http://www.who.int/cancer/palliative/painladder/en/ (accessed on 1 June 2025).
  37. Daud, M.L.; Simone, G.G. Management of pain in cancer patients—An update. Ecancermedicalscience 2024, 18, 1821. [Google Scholar] [CrossRef] [PubMed]
  38. Coppes, O.J.M.; Yong, R.J.; Kaye, A.D.; Urman, R.D. Patient and Surgery-Related Predictors of Acute Postoperative Pain. Curr. Pain Headache Rep. 2020, 24, 12. [Google Scholar] [CrossRef]
  39. Yan, S.; Yan, F.; Liangyu, P.; Fei, X. Assessment of non-pharmacological nursing strategies for pain management in tumor patients: A systematic review and meta-analysis. Front. Pain Res. 2025, 6, 1447075. [Google Scholar] [CrossRef]
  40. Li, Z.; Aninditha, T.; Griene, B.; Francis, J.; Renato, P.; Serrie, A.; Umareddy, I.; Boisseau, S.; Hadjiat, Y. Burden of cancer pain in developing countries: A narrative literature review. Clin. Outcomes Res. 2018, 10, 675–691. [Google Scholar] [CrossRef]
  41. Scarborough, B.M.; Smith, C.B. Optimal pain management for patients with cancer in the modern era. CA Cancer J. Clin. 2018, 68, 182–196. [Google Scholar] [CrossRef]
  42. Kwon, J.H. Overcoming barriers in cancer pain management. J. Clin. Oncol. 2014, 32, 1727–1733. [Google Scholar] [CrossRef]
  43. Cepeda, M.S.; Carr, D.B. Women experience more pain and require more morphine than men to achieve a similar degree of analgesia. Anesth. Analg. 2003, 97, 1464–1468. [Google Scholar] [CrossRef]
  44. De Cosmo, G.; Congedo, E.; Lai, C.; Primieri, P.; Dottarelli, A.; Aceto, P. Preoperative psychologic and demographic predictors of pain perception and tramadol consumption using intravenous patient-controlled analgesia. Clin. J. Pain 2008, 24, 399–405. [Google Scholar] [CrossRef]
  45. Liu, Q.R.; Dai, Y.C.; Ji, M.H.; Liu, P.M.; Dong, Y.Y.; Yang, J.J. Risk Factors for Acute Postsurgical Pain: A Narrative Review. J. Pain Res. 2024, 17, 1793–1804. [Google Scholar] [CrossRef] [PubMed]
  46. Tsegaye, D.; Yazew, A.; Gedfew, M.; Yilak, G.; Yalew, Z.M. Non-Pharmacological Pain Management Practice and Associated Factors Among Nurses Working at Comprehensive Specialized Hospitals. SAGE Open Nurs. 2023, 9, 23779608231158979. [Google Scholar] [CrossRef] [PubMed]
  47. Alorfi, N.M. Pharmacological Methods of Pain Management: Narrative Review of Medication Used. Int. J. Gen. Med. 2023, 16, 3247–3256. [Google Scholar] [CrossRef] [PubMed]
  48. Carlson, C.L. Effectiveness of the World Health Organization cancer pain relief guidelines: An integrative review. J. Pain Res. 2016, 9, 515–534. [Google Scholar] [CrossRef]
  49. Neufeld, N.J.; Elnahal, S.M.; Alvarez, R.H. Cancer pain: A review of epidemiology, clinical quality and value impact. Future Oncol. 2017, 13, 833–841. [Google Scholar] [CrossRef]
  50. Cleeland, C.S.; Gonin, R.; Hatfield, A.K.; Edmonson, J.H.; Blum, R.H.; Stewart, J.A.; Pandya, K.J. Pain and its treatment in outpatients with metastatic cancer. N. Engl. J. Med. 1994, 330, 592–596. [Google Scholar] [CrossRef]
  51. Deandrea, S.; Montanari, M.; Moja, L.; Apolone, G. Prevalence of undertreatment in cancer pain. A review of published literature. Ann. Oncol. 2008, 19, 1985–1991. [Google Scholar] [CrossRef]
  52. Hong, S.H.; Roh, S.Y.; Kim, S.Y.; Shin, S.W.; Kim, C.S.; Choi, J.H.; Kim, S.Y.; Yim, C.Y.; Sohn, C.H.; Song, H.S.; et al. Change in cancer pain management in Korea between 2001 and 2006: Results of two nationwide surveys. J. Pain. Symptom Manag. 2011, 41, 93–103. [Google Scholar] [CrossRef]
  53. Simone, C.B., 2nd; Vapiwala, N.; Hampshire, M.K.; Metz, J.M. Cancer patient attitudes toward analgesic usage and pain intervention. Clin. J. Pain 2012, 28, 157–162. [Google Scholar] [CrossRef] [PubMed]
  54. Kim, Y.C.; Ahn, J.S.; Calimag, M.M.; Chao, T.C.; Ho, K.Y.; Tho, L.M.; Xia, Z.J.; Ward, L.; Moon, H.; Bhagat, A. Current practices in cancer pain management in Asia: A survey of patients and physicians across 10 countries. Cancer Med. 2015, 4, 1196–1204. [Google Scholar] [CrossRef]
  55. Breivik, H.; Cherny, N.; Collett, B.; de Conno, F.; Filbet, M.; Foubert, A.J.; Cohen, R.; Dow, L. Cancer-related pain: A pan-European survey of prevalence, treatment, and patient attitudes. Ann. Oncol. 2009, 20, 1420–1433. [Google Scholar] [CrossRef]
  56. Snijders, R.A.H.; Brom, L.; Theunissen, M.; van den Beuken-van Everdingen, M.H.J. Update on Prevalence of Pain in Patients with Cancer 2022: A Systematic Literature Review and Meta-Analysis. Cancers 2023, 15, 591. [Google Scholar] [CrossRef]
  57. Delgado-Guay, M.; Parsons, H.A.; Li, Z.; Palmer, J.L.; Bruera, E. Symptom distress in advanced cancer patients with anxiety and depression in the palliative care setting. Support. Care Cancer 2009, 17, 573–579. [Google Scholar] [CrossRef] [PubMed]
  58. Zaza, C.; Baine, N. Cancer pain and psychosocial factors: A critical review of the literature. J. Pain Symptom Manag. 2002, 24, 526–542. [Google Scholar] [CrossRef] [PubMed]
  59. Pachman, D.R.; Barton, D.L.; Swetz, K.M.; Loprinzi, C.L. Troublesome symptoms in cancer survivors: Fatigue, insomnia, neuropathy, and pain. J. Clin. Oncol. 2012, 30, 3687–3696. [Google Scholar] [CrossRef]
  60. Huang, Y.; Tan, T.; Liu, L.; Yan, Z.; Deng, Y.; Li, G.; Li, M.; Xiong, J. Exercise for reducing chemotherapy-induced peripheral neuropathy: A systematic review and meta-analysis of randomized controlled trials. Front. Neurol. 2023, 14, 1252259. [Google Scholar] [CrossRef]
  61. Davis, M.P. Novel drug treatments for pain in advanced cancer and serious illness: A focus on neuropathic pain and chemotherapy-induced peripheral neuropathy. Palliat. Care Soc. Pract. 2024, 18, 26323524241266603. [Google Scholar] [CrossRef]
  62. Lehky, T.J.; Leonard, G.D.; Wilson, R.H.; Grem, J.L.; Floeter, M.K. Oxaliplatin-induced neurotoxicity: Acute hyperexcitability and chronic neuropathy. Muscle Nerve 2004, 29, 387–392. [Google Scholar] [CrossRef]
  63. Flatters, S.J. Characterization of a model of persistent postoperative pain evoked by skin/muscle incision and retraction (SMIR). Pain 2008, 135, 119–130. [Google Scholar] [CrossRef]
  64. Pogatzki-Zahn, E.M.; Wagner, C.; Meinhardt-Renner, A.; Burgmer, M.; Beste, C.; Zahn, P.K.; Pfleiderer, B. Coding of incisional pain in the brain: A functional magnetic resonance imaging study in human volunteers. Anesthesiology 2010, 112, 406–417. [Google Scholar] [CrossRef]
  65. Hammond, E.A.; Pitz, M.; Lambert, P.; Shay, B. Quantitative sensory profiles of upper extremity chemotherapy induced peripheral neuropathy: Are there differences in sensory profiles for neuropathic versus nociceptive pain? Can. J. Pain 2019, 3, 169–177. [Google Scholar] [CrossRef]
  66. Gierthmühlen, J.; Baron, R. Neuropathic Pain. Semin. Neurol. 2016, 36, 462–468. [Google Scholar] [CrossRef]
  67. Finnerup, N.B.; Kuner, R.; Jensen, T.S. Neuropathic Pain: From Mechanisms to Treatment. Physiol. Rev. 2021, 101, 259–301. [Google Scholar] [CrossRef]
  68. Dosenovic, S.; Nikolic, Z.; Ivancev, B.; Jelicic Kadic, A.; Puljak, L. Awareness and acceptability of Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials core outcome set for chronic pain among surveyed neuropathic pain authors. J. Comp. Eff. Res. 2019, 8, 671–683. [Google Scholar] [CrossRef]
  69. Finnerup, N.B.; Sindrup, S.H.; Jensen, T.S. Chronic neuropathic pain: Mechanisms, drug targets and measurement. Fundam. Clin. Pharmacol. 2007, 21, 129–136. [Google Scholar] [CrossRef]
  70. Merskey, H. The taxonomy of pain. Med. Clin. N. Am. 2007, 91, 13–20, vii. [Google Scholar] [CrossRef]
  71. Pandey, H.; Tang, D.W.T.; Wong, S.H.; Lal, D. Gut Microbiota in Colorectal Cancer: Biological Role and Therapeutic Opportunities. Cancers 2023, 15, 866. [Google Scholar] [CrossRef]
  72. Ait-Belgnaoui, A.; Payard, I.; Rolland, C.; Harkat, C.; Braniste, V.; Théodorou, V.; Tompkins, T.A. Bifidobacterium longum and Lactobacillus helveticus Synergistically Suppress Stress-related Visceral Hypersensitivity Through Hypothalamic-Pituitary-Adrenal Axis Modulation. J. Neurogastroenterol. Motil. 2018, 24, 138–146. [Google Scholar] [CrossRef]
  73. Yue, F.; Zeng, X.; Wang, Y.; Fang, Y.; Yue, M.; Zhao, X.; Zhu, R.; Zeng, Q.; Wei, J.; Chen, T. Bifidobacterium longum SX-1326 ameliorates gastrointestinal toxicity after irinotecan chemotherapy via modulating the P53 signaling pathway and brain-gut axis. BMC Microbiol. 2024, 24, 8. [Google Scholar] [CrossRef] [PubMed]
  74. Wang, X.; Chen, Y.; Qian, S.; Kong, J.; Su, Z.; Wang, Q.; Liao, L. Compound Probiotics Improve Neuropathic Pain Prognosis in a Murine Model of Chronic Constriction Injury. J. Pain. Res. 2024, 17, 4213–4221. [Google Scholar] [CrossRef]
  75. Cryan, J.F.; Dinan, T.G. Mind-altering microorganisms: The impact of the gut microbiota on brain and behaviour. Nat. Rev. Neurosci. 2012, 13, 701–712. [Google Scholar] [CrossRef]
  76. Dinan, T.G.; Stanton, C.; Cryan, J.F. Psychobiotics: A novel class of psychotropic. Biol. Psychiatry 2013, 74, 720–726. [Google Scholar] [CrossRef]
  77. Strandwitz, P. Neurotransmitter modulation by the gut microbiota. Brain Res. 2018, 1693, 128–133. [Google Scholar] [CrossRef]
  78. Berding, K.; Bastiaanssen, T.F.S.; Moloney, G.M.; Boscaini, S.; Strain, C.R.; Anesi, A.; Long-Smith, C.; Mattivi, F.; Stanton, C.; Clarke, G.; et al. Feed your microbes to deal with stress: A psychobiotic diet impacts microbial stability and perceived stress in a healthy adult population. Mol. Psychiatry 2023, 28, 601–610. [Google Scholar] [CrossRef]
  79. Le Morvan de Sequeira, C.; Hengstberger, C.; Enck, P.; Mack, I. Effect of Probiotics on Psychiatric Symptoms and Central Nervous System Functions in Human Health and Disease: A Systematic Review and Meta-Analysis. Nutrients 2022, 14, 621. [Google Scholar] [CrossRef]
  80. Mörkl, S.; Butler, M.I.; Holl, A.; Cryan, J.F.; Dinan, T.G. Probiotics and the Microbiota-Gut-Brain Axis: Focus on Psychiatry. Curr. Nutr. Rep. 2020, 9, 171–182. [Google Scholar] [CrossRef]
  81. Menni, A.E.; Theodorou, H.; Tzikos, G.; Theodorou, I.M.; Semertzidou, E.; Stelmach, V.; Shrewsbury, A.D.; Stavrou, G.; Kotzampassi, K. Rewiring Mood: Precision Psychobiotics as Adjunct or Stand-Alone Therapy in Depression Using Insights from 19 Randomized Controlled Trials in Adults. Nutrients 2025, 17, 2022. [Google Scholar] [CrossRef]
  82. Tian, P.; Chen, Y.; Zhu, H.; Wang, L.; Qian, X.; Zou, R.; Zhao, J.; Zhang, H.; Qian, L.; Wang, Q.; et al. Bifidobacterium breve CCFM1025 attenuates major depression disorder via regulating gut microbiome and tryptophan metabolism: A randomized clinical trial. Brain Behav. Immun. 2022, 100, 233–241. [Google Scholar] [CrossRef]
  83. Messaoudi, M.; Lalonde, R.; Violle, N.; Javelot, H.; Desor, D.; Nejdi, A.; Bisson, J.F.; Rougeot, C.; Pichelin, M.; Cazaubiel, M.; et al. Assessment of psychotropic-like properties of a probiotic formulation (Lactobacillus helveticus R0052 and Bifidobacterium longum R0175) in rats and human subjects. Br. J. Nutr. 2011, 105, 755–764. [Google Scholar] [CrossRef]
  84. McVey Neufeld, K.A.; O’Mahony, S.M.; Hoban, A.E.; Waworuntu, R.V.; Berg, B.M.; Dinan, T.G.; Cryan, J.F. Neurobehavioural effects of Lactobacillus rhamnosus GG alone and in combination with prebiotics polydextrose and galactooligosaccharide in male rats exposed to early-life stress. Nutr. Neurosci. 2019, 22, 425–434. [Google Scholar] [CrossRef] [PubMed]
  85. Cenac, N.; Altier, C.; Motta, J.P.; d’Aldebert, E.; Galeano, S.; Zamponi, G.W.; Vergnolle, N. Potentiation of TRPV4 signalling by histamine and serotonin: An important mechanism for visceral hypersensitivity. Gut 2010, 59, 481–488. [Google Scholar] [CrossRef] [PubMed]
  86. Sommer, C. Serotonin in pain and analgesia: Actions in the periphery. Mol. Neurobiol. 2004, 30, 117–125. [Google Scholar] [CrossRef]
  87. O’Mahony, S.M.; Bulmer, D.C.; Coelho, A.M.; Fitzgerald, P.; Bongiovanni, C.; Lee, K.; Winchester, W.; Dinan, T.G.; Cryan, J.F. 5-HT(2B) receptors modulate visceral hypersensitivity in a stress-sensitive animal model of brain-gut axis dysfunction. Neurogastroenterol. Motil. 2010, 22, 573–578.e124. [Google Scholar] [CrossRef] [PubMed]
  88. O’Mahony, S.; Chua, A.S.; Quigley, E.M.; Clarke, G.; Shanahan, F.; Keeling, P.W.; Dinan, T.G. Evidence of an enhanced central 5HT response in irritable bowel syndrome and in the rat maternal separation model. Neurogastroenterol. Motil. 2008, 20, 680–688. [Google Scholar] [CrossRef]
  89. Halfaker, D.A.; Akeson, S.T.; Hathcock, D.R.; Mattson, C.; Wunderlich, T.L. Psychological Aspects of Pain. In Pain Procedures in Clinical Practice, 3rd ed.; Lennard, T.A., Walkowski, S., Singla, A.K., Vivian, D.G., Eds.; Hanley & Belfus: Saint Louis, MO, USA, 2011; pp. 13–22. [Google Scholar]
  90. Geisser, M.E.; Roth, R.S.; Theisen, M.E.; Robinson, M.E.; Riley, J.L., 3rd. Negative affect, self-report of depressive symptoms, and clinical depression: Relation to the experience of chronic pain. Clin. J. Pain 2000, 16, 110–120. [Google Scholar] [CrossRef]
  91. Thompson, T.; Correll, C.U.; Gallop, K.; Vancampfort, D.; Stubbs, B. Is Pain Perception Altered in People with Depression? A Systematic Review and Meta-Analysis of Experimental Pain Research. J. Pain 2016, 17, 1257–1272. [Google Scholar] [CrossRef]
  92. Dickens, C.; McGowan, L.; Dale, S. Impact of depression on experimental pain perception: A systematic review of the literature with meta-analysis. Psychosom. Med. 2003, 65, 369–375. [Google Scholar] [CrossRef]
Nutrients 17 02751 g001
Figure 1. Pain intensity based on VAS score per study period and per group. ¶: p = 0.007, decrease; $: p = 0.045, increase; ¥: p < 0.001, decrease; §: p = 0.003, increase, between T0, T1, and T2 in the four groups, respectively—Friedman test. ND: non-depressed; D: depressed; psy: psychobiotics; pla: placebo. Horizontal lines represent median and IQR.
Figure 1. Pain intensity based on VAS score per study period and per group. ¶: p = 0.007, decrease; $: p = 0.045, increase; ¥: p < 0.001, decrease; §: p = 0.003, increase, between T0, T1, and T2 in the four groups, respectively—Friedman test. ND: non-depressed; D: depressed; psy: psychobiotics; pla: placebo. Horizontal lines represent median and IQR.
Nutrients 17 02751 g001
Nutrients 17 02751 g002
Figure 2. Illustration of the changes in the present pain intensity per study period. The horizontal yellow lines represent median and interquartile range (IQR). The blue violins represent T0 (baseline) assessment; the red T1 and the green the follow-up [T2].
Figure 2. Illustration of the changes in the present pain intensity per study period. The horizontal yellow lines represent median and interquartile range (IQR). The blue violins represent T0 (baseline) assessment; the red T1 and the green the follow-up [T2].
Nutrients 17 02751 g002
Nutrients 17 02751 g003
Figure 3. (a) Non-depressed and depressed participants taking psychobiotics; (b) non-depressed and depressed participants taking placebo. The first column of each pain descriptor, being taller (dark or light blue), represents the severity of pain (as a mean of the rating 0 to 3), having the described character in non-depressed individuals; the second column (bright or dark green) is for depressed individuals. All values are expressed at baseline—T0 (no treatment yet).
Figure 3. (a) Non-depressed and depressed participants taking psychobiotics; (b) non-depressed and depressed participants taking placebo. The first column of each pain descriptor, being taller (dark or light blue), represents the severity of pain (as a mean of the rating 0 to 3), having the described character in non-depressed individuals; the second column (bright or dark green) is for depressed individuals. All values are expressed at baseline—T0 (no treatment yet).
Nutrients 17 02751 g003
Nutrients 17 02751 g004
Figure 4. (a) illustrates the sum of means of the 11 items/descriptors referring to sensitive pain at T0, baseline (max value 33), and the differences of means of each of the 11 items per group of participants. (b) illustrates the sum of means of the 4 items/descriptors referring to affective pain at T0, baseline (max value 33), as well as the differences of means of each of the 4 items, per group of participants. The different length on the x-axis expresses the difference in the mean value of each descriptor, presented with a different color as well, to make the variances between groups most prominent. ND: non-depressed; D: depressed; psy: psychobiotics; pla: placebo.
Figure 4. (a) illustrates the sum of means of the 11 items/descriptors referring to sensitive pain at T0, baseline (max value 33), and the differences of means of each of the 11 items per group of participants. (b) illustrates the sum of means of the 4 items/descriptors referring to affective pain at T0, baseline (max value 33), as well as the differences of means of each of the 4 items, per group of participants. The different length on the x-axis expresses the difference in the mean value of each descriptor, presented with a different color as well, to make the variances between groups most prominent. ND: non-depressed; D: depressed; psy: psychobiotics; pla: placebo.
Nutrients 17 02751 g004
Nutrients 17 02751 g005
Figure 5. (a–d) Spider graph of the value fluctuations of each the 15 descriptors consisting the pain rating index per study period. The blue line represents T0—baseline values; the red line represents T1—after psychobiotics or placebo treatment termination; and the yellow line represents values at follow-up. (a,b) represent non-depressed individuals receiving psychobiotics and placebo, respectively; (c,d) represent depressed individuals receiving psychobiotics and placebo, respectively.
Figure 5. (a–d) Spider graph of the value fluctuations of each the 15 descriptors consisting the pain rating index per study period. The blue line represents T0—baseline values; the red line represents T1—after psychobiotics or placebo treatment termination; and the yellow line represents values at follow-up. (a,b) represent non-depressed individuals receiving psychobiotics and placebo, respectively; (c,d) represent depressed individuals receiving psychobiotics and placebo, respectively.
Nutrients 17 02751 g005
Table 1. Pain-suffering participants with respect to psychobiotics or placebo treatment they had been previously allocated.
Table 1. Pain-suffering participants with respect to psychobiotics or placebo treatment they had been previously allocated.
TreatmentNon-Depressed [n = 58]Depressed [n = 41]p *
Psychobiotics27 [46.55%]18 [43.90%]0.794
Placebo31 [53.45%]23 [56.10%]
Numbers (percentage of the corresponding group) express the numbers of participants per treatment × depression status; * chi-square test.
Table 2. Pain intensity based on VAS score per group per study period.
Table 2. Pain intensity based on VAS score per group per study period.
GroupsTreatmentT0T1T2p *
Non-depressed
(n = 58)		Psychobiotics38.9 [25.3]29.3 [19.9]19.3 [13.9]0.007
Placebo34.1 [23.0]36.1 [21.9]39.7 [22.2]0.045
p ** 0.4910.240<0.001
Depressed
(n = 41)		Psychobiotics26.0 [19.9]17.3 [10.3]17.3 [10.3]<0.001
Placebo24.3 [11.7]24.6 [11.3]30.0 [12.5]0.031
p ** 0.5680.0180.001
Numbers express the mean (SD) of the pain intensity score; * Friedman Test; ** Student t-test.
Table 3. Present pain intensity per group and per study period.
Table 3. Present pain intensity per group and per study period.
GroupsTreatmentT0T1T2p *% Change
T0–T1		% Change
T1–T2		% Change
T0–T2
Non-Depressed
(n = 58)		Psychobiotics2.3 [1.1]1.9 [1.0]1.4 [0.9]0.0013.0 [60.7]−23.1 [38.8]−17.4 [39.3]
Placebo2.2 [1.3]2.2 [1.2]2.5 [1.3]0.0060.4 [21.1]22.2 [40.0]24.7 [40.9]
p ** 0.5260.5820.001 0.022<0.001<0.001
Depressed
(n = 41)		Psychobiotics1.5 [0.9]1.1 [0.6]0.8 [0.4]0.002−14.9 [26.3]−22.6 [39.0]−36.3 [40.2]
Placebo1.3 [0.5]1.6 [0.7]1.6 [0.6]0.01017.6 [39.3]23.5 [47.2]38.2 [48.5]
p ** 0.6720.0180.001 0.002<0.0010.003
Numbers express the mean (SD) of the present pain intensity; * Friedman test; ** Student t-test.
Table 4. Pain rating index per group and per study period (for all 15 items).
Table 4. Pain rating index per group and per study period (for all 15 items).
GroupsTreatmentT0T1T2p *
Non-depressed
(n = 58)		Psychobiotics18.6 [13.2]15.1 [11.1] #12.1 [8.7]<0.001
Placebo16.0 [10.3]16.5 [9.8]19.3 [11.0]<0.001
p ** 0.5580.7190.022
Depressed
(n = 41)		Psychobiotics9.7 [7.9]8.1 [6.1]7.1 [6.2]0.106
Placebo10.3 [5.8]10.9 [6.3]14.1 [7.8]0.002
p ** 0.4200.1330.008
Numbers express the sum of the severity index (rating from 0 to 3) of each of the 15 items of the McGill short-form questionnaire as mean (SD); * Friedman test; # p = 0.005 between T0 and T1; ** Student t-test.
Table 5. Descriptive statistics of the sensory pain rating index [11 items] and the affective pain rating index [4 items] in non-depressed and depressed individuals receiving either psychobiotics or placebo. * Comparison between Psychobiotics and Placebo, ** Comparison within the same Group between the three time-points.
Table 5. Descriptive statistics of the sensory pain rating index [11 items] and the affective pain rating index [4 items] in non-depressed and depressed individuals receiving either psychobiotics or placebo. * Comparison between Psychobiotics and Placebo, ** Comparison within the same Group between the three time-points.
Non-depressed
T = T0T = T1T = T2p-Value **
Subtotal Score RangeminmaxmeanSDmedianIQRminmaxmeanSDmedianIQRminmaxmeanSDmedianIQR
Items 1–11Psychobiotics0–3303213.2210.1012.0016.0002810.377.9512.0015.000188.136.358.0013.750.004
Placebo02711.907.0712.008.0003012.586.7711.008.0002914.597.5814.008.00<0.001
p-Value * 0.667 0.516 0.007
Items 12–15Psychobiotics0–120115.443.775.007.000114.703.545.007.000103.963.033.004.00<0.001
Placebo0114.103.714.007.000123.873.754.007.000114.744.084.009.000.123
p-Value * 0.165 0.372 0.535
Depressed
T = T0T = T1T = T2p-Value **
Subtotal Score RangeminmaxmeanSDmedianIQRminmaxmeanSDmedianIQRminmaxmeanSDmedianIQR
Items 1–11Psychobiotics0–330217.675.536.505.500166.334.736.007.000165.334.645.0010.000.128
Placebo0157.834.479.007.000158.224.8110.007.0001910.535.7910.008.500.003
p-Value * 0.750 0.245 0.011
Items 12–15Psychobiotics0–120102.113.070.504.00071.782.440.503.25051.732.090.003.000.280
Placebo092.432.682.004.000102.702.772.004.000103.592.924.002.500.025
p-Value * 0.394 0.171 0.074
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Tzikos, G.; Menni, A.-E.; Theodorou, H.; Chamalidou, E.; Theodorou, I.M.; Stavrou, G.; Shrewsbury, A.D.; Amaniti, A.; Konsta, A.; Tsetis, J.K.; et al. Beyond Analgesia: Psychobiotics as an Adjunctive Approach to Pain Management in Gastrointestinal Oncology—A Post Hoc Analysis from the ProDeCa Study. Nutrients 2025, 17, 2751. https://doi.org/10.3390/nu17172751

AMA Style

Tzikos G, Menni A-E, Theodorou H, Chamalidou E, Theodorou IM, Stavrou G, Shrewsbury AD, Amaniti A, Konsta A, Tsetis JK, et al. Beyond Analgesia: Psychobiotics as an Adjunctive Approach to Pain Management in Gastrointestinal Oncology—A Post Hoc Analysis from the ProDeCa Study. Nutrients. 2025; 17(17):2751. https://doi.org/10.3390/nu17172751

Chicago/Turabian Style

Tzikos, Georgios, Alexandra-Eleftheria Menni, Helen Theodorou, Eleni Chamalidou, Ioannis M. Theodorou, George Stavrou, Anne D. Shrewsbury, Aikaterini Amaniti, Anastasia Konsta, Joulia K. Tsetis, and et al. 2025. "Beyond Analgesia: Psychobiotics as an Adjunctive Approach to Pain Management in Gastrointestinal Oncology—A Post Hoc Analysis from the ProDeCa Study" Nutrients 17, no. 17: 2751. https://doi.org/10.3390/nu17172751

APA Style

Tzikos, G., Menni, A.-E., Theodorou, H., Chamalidou, E., Theodorou, I. M., Stavrou, G., Shrewsbury, A. D., Amaniti, A., Konsta, A., Tsetis, J. K., Grosomanidis, V., & Kotzampassi, K. (2025). Beyond Analgesia: Psychobiotics as an Adjunctive Approach to Pain Management in Gastrointestinal Oncology—A Post Hoc Analysis from the ProDeCa Study. Nutrients, 17(17), 2751. https://doi.org/10.3390/nu17172751

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop