Toward a psychoneuroimmune interpretation of anxiety and depression risk in cervical cancer

Abstract

Anxiety and depression significantly impair the quality of life of patients with cervical cancer. Identifying high-risk cases and elucidating the underlying biological mechanisms represent a central challenge in psycho-oncology. A recent study published in the World Journal of Psychiatry, Xie et al constructed a multifactorial predictive model that identified low household income, advanced tumor stage, comprehensive treatment regimen, and low hope level as independent risk factors for anxiety and depression. This model serves both as a risk assessment tool and as a valuable framework for exploring the potential psycho-neuro-immune (PNI) mechanisms of anxiety and depression. Using this model as a starting point, this perspective employs the PNI axis framework to explore how these four risk factors, through distinct pathways, may trigger peripheral immune activation and elevate pro-inflammatory cytokine levels. These inflammatory signals then cross the blood-brain barrier, disrupting central nervous system function, suggesting a convergent biological pathway for the development of anxiety and depression. This theoretical integration provides a plausible interpretation for the model’s high predictive efficacy and unifies disparate clinical risks in the framework of the PNI axis. Future research should incorporate neuroimmune markers to further elucidate their biological basis and enhance the precision of clinical interventions.

Key Words: Psycho-neuro-immune axis; Cervical cancer; Anxiety; Depression; Clinical predictive model; Mechanism

Core Tip: This commentary elucidates the innovative “psycho-neuro-immune” axis mechanism underlying a predictive model for anxiety/depression in cervical cancer. The four distinct risk factors, such as advanced cancer, comprehensive therapy, low hope level, and low income level, converge via the psycho-neuro-immune axis: Physical stressors trigger an “outside-in” immune-to-brain pathway, while psychosocial stressors drive a “top-down” neuroendocrine-to-immune pathway. These pathways interact, creating a vicious cycle that sustains peripheral and central inflammation, ultimately leading to mood symptoms. This integrative framework transforms clinical risk prediction into a targetable biological model for future interventions.

This editorial refers to “Influencing factors and predictive model construction of anxiety and depression in patients with cervical cancer” by Xie et al, 2025; https://dx.doi.org/10.5498/wjp.v15.i12.111761.

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INTRODUCTION

Cervical cancer is one of the most common malignancies among women globally, with its incidence and mortality ranking high among gynecological cancers[1]. The uncertainty surrounding disease progression, the physical damage caused by surgery and a comprehensive treatment regimen (including pain and fatigue), and the persistent risk of recurrence continuously burden patients, significantly exacerbating their psychological distress. Against this backdrop, anxiety and depression become the most common comorbidities, negatively influencing treatment adherence and quality of life, and potentially indirectly interfering with anti-tumor therapy prognosis by influencing neuroendocrine and immune functions[2]. Therefore, accurately identifying high-risk populations and elucidating their pathogenesis are critical issues that urgently need to be addressed in the field of psycho-oncology[3]. However, a long-observed phenomenon suggests that in cancer patients, stressors of vastly different natures - from physical (e.g., the disease itself, treatment toxicity) to psychosocial (e.g., financial pressure, negative cognition) - often converge to produce similar anxiety and depression outcomes. This raises the core question addressed in this editorial: Do these heterogeneous risk factors share a common biological pathway?

A recent study published in the World Journal of Psychiatry by Xie et al[4] provided valuable insights: Through rigorous clinical data analysis, it developed a multifactorial predictive model for anxiety and depression in cervical cancer patients, identifying four independent risk factors: Low family income, advanced tumor stage, comprehensive treatment regimen (defined in the original study as treatment regimens involving surgery, such as surgery combined with radiotherapy, surgery combined with chemotherapy, or surgery combined with chemoradiotherapy), and low levels of hope (measured using standardized tools like the Herth Hope Index). However, the model is primarily based on statistical associations and does not explain why the aforementioned risk factors from different dimensions lead to the same affective symptoms, nor does it reveal the underlying integrated mechanisms.

To explore these questions, the psycho-neuro-immune (PNI) axis provides a compelling theoretical framework. The PNI axis breaks down disciplinary barriers among psychology, oncology, and physiology, systematically revealing the dynamic interaction among psychological stress, neuroendocrine regulation, and immune function[5]. Within this framework, the “neuroimmune” process specifically refers to the functional dialogue between the immune system and the central nervous system[6,7]. This article focuses on the core mechanism of this process in the context of cancer: Physical or psychosocial stressors act as initiating factors, triggering the transmission of peripheral inflammatory signals to the central nervous system, ultimately inducing emotional symptoms. This framework may offer a plausible biological link connecting the aforementioned four risk factors to mood symptoms. Consequently, this editorial will use this predictive model as a starting point to systematically explain how each factor induces mood disorders by activating the PNI axis (Figure 1). This not only provides a new, integrative mechanistic perspective for understanding the psychosomatic symptoms of cervical cancer patients but also demonstrates how a clinical predictive model can be transformed into a tool for advancing theory, thereby achieving a leap from “risk identification” to “mechanistic understanding” and providing a theoretical basis for future precision interventions targeting the PNI pathway.

Figure 1 A psycho-neuro-immune axis framework linking diverse stressors to anxiety and depression in cervical cancer. The figure illustrates the hypothesized mechanistic pathways by which the four key risk factors (advanced tumor stage, comprehensive treatment, low hope, and low income) identified in the predictive model converge to promote anxiety and depression. (1) Core convergent pathway: Diverse physical, psychological, and social stressors initiate distinct peripheral pathways (e.g., damage-associated molecular patterns release, hypothalamic-pituitary-adrenal axis dysfunction, sympathetic activation), which collectively elevate peripheral pro-inflammatory cytokines. These inflammatory signals are posited to access the brain, activate microglia, and disrupt central neurobiological processes (e.g., monoamine metabolism, neurotrophic signaling, amygdala activity), ultimately leading to clinical mood symptoms; (2) Dynamic clinical context: The model is superimposed on a clinical timeline (brown to blue text), showing how dominant stressors shift from tumor burden pre-treatment, to combined physical/psychosocial stress during active therapy, to persistent psychosocial stress and symptom feedback during survivorship; (3) Systemic interactions: A dashed feedback loop indicates how resulting anxiety and depression can exacerbate initial psychosocial stress, potentially sustaining the PNI axis dysregulation; and (4) Intervention implications: Capsule icons highlight potential therapeutic targets (e.g., β-blockers, psychosocial interventions, anti-inflammatory agents, microglial modulators, indoleamine 2,3-dioxygenase inhibitors) corresponding to key nodes in the proposed pathway. Solid arrows (→) indicate activation or promotion; T-bar arrows (⊣) represent inhibition. Created by Figdraw (permission license code: No. AUSUI1c714) (Copyright permission see Supplementary material). HPA: Hypothalamic-pituitary-adrenal; DAMPs: Damage-associated molecular patterns; TNF-α: Tumor necrosis factor alpha; IL-1β: Interleukin-1beta; IDO: Indoleamine 2,3-dioxygenase; 5-HT: 5-hydroxytryptamine; BDNF: Brain-derived neurotrophic factor; BLA: Basolateral amygdala.

DECONSTRUCTING THE BIOLOGICAL CONNOTATIONS OF THE PREDICTIVE MODEL

Advanced tumor stage: The primary link of chronic physical stress with neuroimmune activation

Advanced tumor stage, as a key risk factor in the predictive model, is essentially a persistent chronic physical stressor. The high tumor burden-induced tissue damage and abnormal metabolism of tumor cells collectively serve as key primary factors for activating the PNI axis. High tumor burden, through direct tissue destruction (inducing cell death, damaging blood and lymphatic vessels) releases danger signals such as damage-associated molecular patterns (DAMPs), coupled with the imbalanced microenvironment created by abnormal tumor cell metabolism (e.g., local acidification, oxidative stress)[8-11], collectively and continuously activates the innate immune system, promoting the polarization of myeloid cells (e.g., macrophages, neutrophils) towards a pro-inflammatory state and releasing inflammatory signals including tumor necrosis factor alpha (TNF-α) and interleukin-6 (IL-6), thereby establishing a chronic low-grade inflammatory state both locally and systemically[12]. This state constitutes the peripheral material basis upon which the subsequent “neuroimmune process” is initiated.

Therefore, even without any external treatment, advanced cancer itself creates a pro-inflammatory, imbalanced local environment in the patient’s body. This clearly elucidates the primary direct mechanism by which tumor burden affects the nervous system: Namely, by shaping a persistent systemic pro-inflammatory internal environment. This process is considered to potentially set the stage for subsequent “superimposed stress” from a comprehensive treatment regimen (chemoradiotherapy) to trigger a stronger neuroimmune response. Together with other risk factors, it lays the primary inflammatory foundation for subsequently inducing mood symptoms through common neuroimmune pathways.

Comprehensive treatment: The amplifying effect of “superimposed stress” on the PNI axis

On top of the chronic inflammatory foundation established by advanced cancer, comprehensive treatment, particularly concurrent chemoradiotherapy, acts as a superimposed stressor that can significantly amplify the activation effect of the PNI axis, thereby increasing the risk of anxiety and depression in patients. The core mechanism of this effect lies in the fact that ionizing radiation from radiotherapy and the cytotoxic effects of chemotherapy drugs can induce immunogenic cell death in tumor cells and surrounding normal cells. This process releases a large amount of DAMPs, such as high mobility group box 1 and adenosine triphosphate[13,14]. These DAMPs further enhance the activation of macrophages and neutrophils by binding to pattern recognition receptors, including toll-like receptor 4 and the NLR family pyrin domain containing 3 inflammasome on innate immune cells, promoting the massive release of pro-inflammatory cytokines (e.g., IL-6 and TNF-α), thereby forming a more significant peripheral inflammatory signal[15]. The significantly increased peripheral inflammatory load from chemoradiotherapy, being consistent with the inflammatory state triggered by other risk factors, is considered to be the key material basis for transmitting stress signals to the brain, and may ultimately participate in disrupting the function and homeostasis of the central nervous system through the common pathways described in subsequent sections.

Low hope level: Psychological stress-driven HPA axis dysregulation and glucocorticoid resistance

Low hope level, as a negative cognitive-emotional state oriented towards the future, is essentially a chronic, persistent psychological stress. This state can significantly activate the brain’s stress response centers, particularly the hypothalamic-pituitary-adrenal (HPA) axis, thereby inducing functional dysregulation characterized by glucocorticoid resistance[16,17]. Under physiological conditions, cortisol, as the primary glucocorticoid, binds to target cell receptors and inhibits inflammatory signaling pathways (e.g., nuclear factor kappaB), suppressing the synthesis and release of pro-inflammatory factors, such as IL-6 and TNF-α, thus maintaining immune homeostasis[18]. However, in a state of glucocorticoid resistance, the responsiveness of target cells to glucocorticoid signals is significantly reduced, which is manifested as decreased receptor binding efficiency and impaired downstream signal transduction, preventing glucocorticoids from effectively exerting their immunosuppressive effects. This leads to the sustained release of pro-inflammatory factors, providing a pathological basis for the long-term persistence of systemic low-grade inflammation[19]. Therefore, low hope level is not an abstract psychological concept, but may directly shape a pro-inflammatory physiological internal environment by inducing the HPA axis dysfunction, participating in laying the biological foundation for the progression of anxiety and depression. The resulting low-grade, persistent inflammatory state is also a key factor driving the PNI axis, ultimately inducing mood symptoms through common central signaling pathways.

Low family income: Social stress-driven sympathetic activation and pro-inflammatory phenotype

Low family income, representing economic pressure and uncertainty, is a typical chronic social stressor. This pressure triggers survival anxiety signals through the limbic system (e.g., persistent worry about treatment costs and family burden), leading to sustained activation of the sympathetic nervous system[20]. Chronic sympathetic excitation causes persistently elevated levels of catecholamines, such as norepinephrine. These neurotransmitters exert bidirectional regulatory effects by binding to β2-adrenergic receptors on immune cells: On one hand, they inhibit the proliferation and function of T lymphocytes, weakening the body’s adaptive immune defense[21]; on the other hand, they promote the differentiation of monocytes into macrophages and their polarization towards a pro-inflammatory phenotype, promoting continuous secretion of low levels of inflammatory factors (e.g., IL-6 and TNF-α), further exacerbating the peripheral inflammatory load[22]. Crucially, psychosocial stress, due to its persistent and systemic nature, plays a significant role in shaping the patient’s low-grade inflammatory phenotype over the long term. The sustained sympathetic activation driven by low income not only may directly promote inflammation, but also mutually enhances the HPA axis dysregulation potentially caused by low hope level, together forming a vicious cycle on the PNI axis, increasing susceptibility to anxiety and depression.

Integration: Revealing the central role of the PNI axis

The four risk factors screened by this predictive model essentially may represent multiple “triggers” that activate the PNI axis from different dimensions. Based on their nature, they can be categorized into two types: The first type involves physical damage triggers: Advanced tumor stage and comprehensive treatment, which, through direct tissue damage and cell death, release DAMPs, activating the innate immune system in a bottom-up manner[8,13]. The second type includes psychosocial stress triggers: Low hope levels and low family income, which disrupt the function of the HPA axis and persistently activate the sympathetic nervous system, leading to neuroendocrine dysregulation in a top-down manner[16,20]. These two pathways are not parallel and independent. Instead, they intersect and enhance each other. This interaction forms a positive feedback loop that exacerbates PNI axis imbalance. Despite different starting points, all stress signals converge on a common downstream pathway, which is the accumulation of peripheral pro-inflammatory cytokines (e.g., IL-6 and TNF-α)[12,15,19,22].

It is important to clarify that psychosocial stressors (e.g., low hope, low income) are not thought to directly generate central inflammation, but rather to initiate this cascade via the activation of peripheral immune pathways. These accumulated peripheral inflammatory signals affect the central nervous system through defined biological pathways, including the “indirect pathway” activating blood-brain barrier endothelial cells to induce prostaglandin E₂ synthesis, and the “direct pathway” where inflammatory factors enter the brain directly at sites with less intact blood-brain barrier structures, such as the choroid plexus[23,24]. Regardless of the route, the core central effect is the preferential activation of microglia, transforming them into a pro-inflammatory morphology and releasing factors, such as IL-1β, TNF-α, and neurotoxic mediators (e.g., nitric oxide), thereby impairing neuroplasticity[25,26].

Ultimately, this microglial activation driven by multiple stressors and the resulting central inflammatory state uniformly translate into the clinical phenotype of anxiety and depression through three core mechanisms: Firstly, by activating the indoleamine 2,3-dioxygenase enzyme, which shifts tryptophan metabolism towards kynurenine, resulting in insufficient serotonin synthesis[27]; secondly, by inhibiting the expression of brain-derived neurotrophic factor, thereby impairing neuroplasticity[28]; and thirdly, by enhancing the activity of fear circuits in brain regions such as the amygdala[29]. Therefore, from a theoretical standpoint, the notable value of this predictive model may lie in its potential to unify disparate clinical risks within the PNI axis framework, outlining a testable neuroimmune hypothesis for how diverse risks might converge to influence mood symptoms.

The neuroimmune pathways proposed in this hypothesis are based on well-established PNI principles. While direct evidence linking the specific risk factors (e.g., low hope, treatment modality) to neuroimmune alterations in cervical cancer patients is still evolving, the postulated links between neuroimmune dysregulation (including inflammatory signaling) and mood disturbance in this population gain credence from emerging research. For example, a longitudinal study in cervical cancer survivors found significant correlations between fluctuations in pro-inflammatory cytokines (e.g., IL-6, TNF-α) and concurrent changes in anxiety and depression levels[30]. Although direct evidence for HPA axis involvement in this specific population is more limited, its role in stress-related mood disorders is well-established in broader psycho-oncology literature.

It is important to note that the PNI axis, while providing a powerful integrative lens, is not the only framework for understanding distress in cancer. Complementary perspectives offer valuable insights at different levels of analysis. For instance, cognitive-behavioral models focus on maladaptive thought patterns and behaviors as core drivers of anxiety and depression, directly informing effective psychotherapeutic interventions[31]. The social determinants of health framework emphasizes how socioeconomic status (including low income) shapes cancer survivors’ experience and quality of life through pathways such as access to care and chronic stress[32]. Furthermore, neuroendocrine-focused models detail the dysregulation of stress response systems, such as the HPA axis, whose critical role in stress-related mood disorders is a cornerstone of psychoneuroimmunology[5]. The present analysis foregrounds the PNI axis because it uniquely bridges the psychosocial and physical risk factors identified in the predictive model into a coherent biological narrative. This does not negate the validity of other models but rather suggests that the PNI framework may serve as a central, biologically-grounded nexus where multiple pathways of risk converge.

CURRENT TREATMENT PRACTICES

Pharmacotherapy: Expanding the perspective from neurotransmitters to neuroimmunity

Pharmacotherapy for mood symptoms in cervical cancer presents a clinical paradox. Despite widespread use (in approximately 10%-15% of patients), antidepressants are often prescribed for indications other than diagnosed depression, such as sleep aid or analgesia[33]. However, robust evidence supporting their efficacy for major depression in cancer patients remains limited. An updated 2023 Cochrane systematic review indicated that the evidence quality was “very low”, and no significant differences were identified in direct comparisons between different drug classes (e.g., selective serotonin reuptake inhibitors vs tricyclics)[34]. This leads to a misalignment in clinical practice characterized by potential overuse in mild cases and underuse in severe cases[33].

This dilemma indicates the need to move beyond the traditional “neurotransmitter” paradigm and reassess the therapeutic potential of drugs from the perspective of the PNI axis. Growing preclinical evidence indicates that the mechanism of action of drugs with antidepressant efficacy may extend far beyond increasing synaptic serotonin concentration. For instance, classic selective serotonin reuptake inhibitors (e.g., fluoxetine) and some natural compounds have been shown to potentially work through mechanisms, such as inhibiting the pro-inflammatory activation of microglia[35], promoting anti-inflammatory autophagy[36], and targeting the inhibition of the NLR family pyrin domain-containing 3 inflammasome pathway[37]. However, these mechanistic hypotheses must be rigorously validated through high-quality randomized controlled trials conducted in cancer patients.

Psychological and behavioral interventions: Regulating key upstream nodes of the PNI axis

Compared with the challenges faced by pharmacotherapy, psychosocial interventions represented by cognitive-behavioral therapy and mindfulness-based stress reduction have accumulated substantial empirical success in the cancer population[33]. The remarkable efficacy of these treatments is identified by a clear biological basis in the PNI axis. Research indicated that depression itself is closely associated with elevated levels of pro-inflammatory cytokines (e.g., IL-6 and TNF-α) and HPA axis dysfunction, and interventions, such as mindfulness, are proven to measurably reduce these inflammatory markers and regulate the HPA axis’s function (e.g., improving cortisol rhythm)[38]. This indicates that psychological interventions are not merely “talk therapy”, but are a “biological means” capable of directly regulating key upstream nodes (psychological stress → neuroendocrine → immune) in the PNI axis.

Traditional Chinese medicine and integrative therapies: Holistic practice of multi-target PNI axis regulation

Compared with Western interventions with relatively single targets, traditional Chinese medicine (TCM) interventions can be viewed as a form of multi-target therapy derived from natural products. TCM interventions exhibit unique potential in regulating the PNI axis due to their “holistic view” and “multi-target” characteristics. Extensive research showed that TCM formulations and their active components can exert anti-anxiety and antidepressant effects by modulating multiple links of the PNI axis[39-43]. Regarding compound formulations, the classic formula Xiaoyaosan (Free and Easy Wanderer Decoction), a formulation composed of herbs including Bupleurum (Chaihu), Angelica sinensis (Danggui), and Atractylodes macrocephala (Baizhu), can regulate metabolites in the hippocampus related to neurotransmitter balance and energy metabolism, and its active components (e.g., paeoniflorin, quercetin) target key neuroimmune signaling molecules (e.g., IL-6)[39]. Similarly, Chaihu Jia Longgu Muli Tang (Bupleurum Plus Dragon Bone and Oyster Shell Decoction), a formula containing Bupleurum (Chaihu), Dragon Bone (Longgu), Oyster Shell (Muli), and other herbs, has been proven to significantly reduce serum IL-6 and TNF-α levels in patients, in which its mechanism is potentially related to the regulation of core inflammatory signaling pathways, such as phosphatidylinositol 3-kinase-protein kinase B and nuclear factor kappaB[40].

In studies on single drug components, the active component of Astragalus (Huang qi), total flavonoids of Astragalus, not only reduces abnormally elevated corticosterone levels in the hippocampus and regulates the HPA axis’s function in animal chronic stress models, but also promotes myelin regeneration and repair[41]. Furthermore, non-pharmacological therapies, such as acupuncture and Tai Chi, have gained support from modern neuroscience for their mechanisms of regulating the PNI axis. For example, acupuncture at Zusanli (ST36) can activate the anti-inflammatory “vagal-adrenal axis” pathway[42], and Tai Chi can regulate HPA axis function and suppress systemic inflammation[43,44].

PROSPECTS AND IMPLICATIONS: TOWARDS PRECISION PSYCHO-ONCOLOGY

From association to mechanism: Deepening multi-omics research on the PNI axis

Current research based on the PNI axis primarily remains at the level of phenomenological association. To further strengthen the exploration of causal mechanisms, future studies will utilize cutting-edge technologies, such as single-cell sequencing, molecular imaging, and epigenetics, to deepen understanding at three key levels, systematically analyzing the regulatory network of the PNI axis[45,46]. Firstly, at the cellular level, the specific roles of key cell subpopulations can be further elucidated. While previous sections have highlighted the central role of microglia and peripheral macrophages in the PNI axis, future research will further clarify the unique contributions of different neuronal, microglial, and immune cell subpopulations in stress signal transmission, revealing cell-specific mechanisms. Secondly, at the mechanistic level, dynamically tracking stress signals could explore how psychosocial stressors, including “low hope level”, influence the function of HPA axis-related genes through mechanisms, such as epigenetic modifications (e.g., DNA methylation), thereby explaining the biological basis through which they shape the “inflammatory prelude” at the molecular level[47]. Finally, at the system level, the complete “peripheral-central” signaling map can be further explored. Defining how specific peripheral inflammatory cytokine profiles are precisely transmitted to the center and specifically participate in microglial activation and metabolic changes in limbic system brain regions may integrate disparate biological events into a unified pathophysiological process. The objective of this direction is the development of peripheral biological markers capable of non-invasively and accurately monitoring the central PNI axis’s activity. In recent years, highly sensitive biosensors based on electrochemical and optical sensing technologies have been developed rapidly, exhibiting potential in detecting stress-related markers, such as cortisol[48], providing key technical support for real-time dynamic monitoring of the PNI axis and personalized intervention.

From universal to precise: Developing stratified interventional strategies

Based on the different stress sources and PNI axis’s activation characteristics revealed by this predictive model, future clinical interventions can shift from homogeneous universal support to stratified interventions based on biophenotypes and psychosocial characteristics. This demonstrates that in clinical practice, attempts can be made to preliminarily subtype patients. For patients with a “high inflammation” phenotype, where advanced tumor stage and comprehensive treatment are the main risk factors, accompanied by clearly elevated neuroimmune inflammatory markers, such as peripheral blood IL-6, targeted pharmacological interventions addressing the PNI axis pathway can be explored alongside conventional psychological support within the context of rigorously designed clinical trials. For instance, beta-blockers (e.g., propranolol) can inhibit pro-inflammatory cytokine production by blocking catecholamine stimulation of immune cells, and preliminary research concluded that they may help improve cancer-related depressive symptoms[49]; at the central level, microglial modulators (e.g., minocycline) have exhibited in research to alleviate abnormal activation and neurotoxicity of microglia, improving stress-related depressive-like behaviors and neuroplasticity impairment[50]. However, their efficacy and safety in cancer patients with mood disorders require verification in subsequent clinical trials.

For patients with a “psychological stress” phenotype, where a low hope level and a low family income are the dominant risk factors and inflammation levels are not prominent, interventions should concentrate on regulating the HPA axis and autonomic nervous function. Mind-body interventions, such as cognitive-behavioral stress management and Tai Chi, have shown regulatory effects by improving HPA axis-related indicators, such as cortisol[43,51]. Future efforts need to further optimize such programs to enhance their applicability and effectiveness in populations facing multiple social adversities. It is noteworthy that the ultimate efficacy of the aforementioned interventions, whether pharmacological or non-pharmacological, must be validated in randomized controlled trials[52].

From static to dynamic: Developing a multidimensional prediction and management system

The core of achieving precise early warning and intervention for anxiety and depression symptoms in cervical cancer patients lies in developing a “clinical-psychological-biological” multidimensional prediction and management system. This highly aligns with the core concept of precision psychiatry, aiming to make mental health diagnosis and treatment decisions more objective by integrating multimodal biomarkers[53]. In the cervical cancer clinical setting, this indicates systematically integrating PNI axis-related biomarkers (e.g., readily measurable candidates like serum IL-6 and diurnal salivary cortisol slope) on the basis of assessing psychosocial risk factors, thereby achieving a quantitative assessment of the patient’s psychoneuroimmune risk.

More importantly, this system should possess dynamic evolution characteristics. Patients’ stress sources, inflammatory load, and psychological state change with the treatment phase and recovery process. Therefore, future research should concentrate on the development of predictive algorithms that can update dynamically along with the treatment process. For instance, at key time points, such as the initial phase of radiotherapy, between chemotherapy cycles, and post-treatment, multi-dimensional data should be collected repeatedly via mobile health technology or electronic patient-reported outcome systems, exploring advanced longitudinal data analysis models to achieve real-time, individualized prediction of anxiety and depression risk.

Ultimately, the purpose of this dynamic prediction system is to form a closed-loop clinical management pathway. High-risk alerts should automatically activate pre-established, graded intervention plans, ranging from providing self-help psychoeducational materials to prompting clinician assessments and even initiating multidisciplinary team consultations. Through the cycle of “assessment-prediction-intervention-re-assessment”, prospective, individualized, and comprehensive management of the patient's psychoneuroimmune risk can be realized, translating mechanistic insights into clinical practice[54].

Drawing on the PNI axis framework, this perspective proposes an integrative hypothesis to interpret the predictive model for anxiety and depression in cervical cancer patients. It suggests that the four seemingly disparate risk factors (advanced tumor stage, comprehensive treatment, low hope level, and low family income) might drive mood symptoms via activating the PNI axis. This hypothesis, while requiring empirical validation, transforms clinical risks into a coherent, targetable theoretical model. Consequently, the clinical intervention approach in psycho-oncology can be further refined through two complementary strategies: Maintaining conventional supportive care while actively exploring complementary strategies that target key nodes of the PNI axis. Importantly, future research should concentrate on developing dynamic prediction tools to identify high-risk patients early in cancer treatment and to provide new clinical pathways for improving patient psychosomatic outcomes through adjuvant mechanisms, such as regulating neuroimmune homeostasis.

CONCLUSION

Looking ahead, the empirical validation of this integrative framework is key to advancing the field. A direct and important research direction is to systematically examine, within a prospective cervical cancer cohort, whether peripheral inflammatory markers (e.g., IL-6, C-reactive protein) and HPA axis function indicators (e.g., cortisol rhythm) mediate the relationship between psychosocial risk factors (e.g., low hope level, low family income) and anxiety/depression symptoms. Such mechanistic validation studies will provide a solid biological basis for the predictive tool development and PNI pathway-targeted precision interventions (e.g., anti-inflammatory or neuromodulatory adjuvant therapies) mentioned above, ultimately achieving the translation from theoretical construction to clinical benefit.