With the global population and the proportion of elderly people growing, cancer has become one of the leading causes of death worldwide (1). Although the development of surgery and medical treatment has made great progress in cancer patients, the prognosis for these patients remains not yet satisfactory (2). Therefore, based on the estimated survival time of cancer patients, it is essential to develop individualized and effective treatment strategies to improve their chances of survival. Currently, anti-tumor therapy relies primarily on a conventional staging system. Nevertheless, in clinical practice, the staging system alone is not able to support treatment decision-making as well as prognosis assessment well (3, 4). It is therefore urgent to construct novel prognostic markers to guide more precise treatment for cancer patients.

The accumulating evidence suggests that host inflammation and immune status play an important role in the progression, treatment response and survival outcomes of cancer patients (5, 6). Based on this insight, several inflammation/immune-related biomarkers have been developed to predict the clinical outcomes of cancer patients, such as neutrophil to lymphocyte ratio (NLR) (7), platelet to lymphocyte ratio (PLR) (8) and monocyte to lymphocyte ratio (MLR) (9). Recently, a newly developed prognostic biomarker- the pan-immune-inflammation value (PIV), has garnered significant interest of clinicians (10). PIV integrates neutrophils, platelets, monocytes and lymphocyte together, and has been reported to be a better prognostic predictor than these simple biomarkers, including NLR, PLR and MLR (11, 12). To be specific, PIV is calculated using serum neutrophil, platelet, monocyte and lymphocyte (neutrophil x platelet x monocyte/ lymphocyte), which was first introduced by Fuca et al. (13) in 2020 as a prognostic index for metastatic colorectal cancer receiving chemotherapy combined with target therapy. After that, the prognostic role of the PIV has been explored in various cancers (14–16). A recent meta-analysis of 15 studies demonstrated that a high PIV was associated with a poor prognosis in cancer patients (17). Nonetheless, it is important to note that some common tumor types, such as pancreatic cancer and hepatic cancer, were not available in this meta-analysis. Besides, abstract without sufficient data was also included for analysis. These factors undoubtedly have a certain impact on the universality and reliability of the results.

As growing body of additional research has been addressed to further explore the prognostic value of PIV in cancer patients. We therefore performed an updated pooled analysis to systematically explore the relationship between the pretreatment PIV and survival outcomes in cancer patients.

Cancer-related inflammation is prevalent in patients with malignant diseases, which has been confirmed to promote cancer progression and advancement (6). Traditionally, host inflammation status can be detected through several blood biomarkers, such as neutrophil count, platelet count, and lymphocyte count. Additionally, evidence from numerous studies has demonstrated that their ratios can be applied to predict patient’s short-term and long-term outcomes, especially in cancer patients (7, 8). Importantly, these markers have the natural advantage of being non-invasive, objective, and cost-effective, which provides great potential for their wide clinical applications.

In recent years, a new biomarker, the pan-immune-inflammation value, which consists of serum neutrophil, platelet, monocyte and lymphocyte, has attracted the attention of clinicians due to its promising prognostic significance in several malignancies (12, 30, 39). A recent meta-analysis by Guven et al. (17) has initially demonstrated that high PIV was associated with decreased survival outcomes in cancer patients. Nevertheless, this meta-analysis included only 15 studies (including an abstract) and several common cancer types (such as pancreatic cancer, hepatic cancer and prostate cancer) were not available, which made the prognostic value of PIV in cancer patients still inconclusive. To clarify this issue accurately, an updated meta-analysis including 30 studies with 8,799 cancer patients was performed. Through our quantitatively analyses, we convinced that an elevated PIV markedly predicted poorer OS (HR = 2.07; 95%CI: 1.77–2.41) and PFS (HR = 1.83; 95%CI: 1.37–2.45) in cancer patients. Additionally, benefiting from the inclusion of sufficient studies, we were able to perform detailed subgroup analyses, as well as sensitivity and publication bias analyses It can be seen that the PIV achieved reliable performance in predicting prognosis. Therefore, the PIV may be a valuable and effective inflammatory index to evaluate the oncological outcomes of patients with malignancies.

Dysregulation of inflammatory and immune cells in the tumor microenvironment has been identified as being involved in the tumor progression (49–51). Simultaneously, a higher PIV may result from higher neutrophils, monocytes, and platelets and/or lower lymphocytes. Although the detailed mechanisms of the PIV’s prognostic value in malignancies are unclear, they can be explained as follows: First, neutrophils, as the most common innate immune cells, have been reported to promote tumor invasion and metastasis by secreting VEGFA, MMPs, and other chemokines such as IL-6 and TGF-β (52, 53). At the same time, elevated neutrophils can also cause T cell activation disorders by largely releasing nitric oxide, arginase, and reactive oxygen species, ultimately inhibiting the body’s killing effect on cancer cells (54). Second, monocytes, especially those differentiated into tumor-associated macrophages (TAMs), can induce apoptosis of T cells with antitumor functions (55). In addition, TAM density has been shown to affect tumor tissue angiogenesis by stimulating the production and secretion of pro-angiogenic factors (56, 57). Third, platelets, are reported to induce epithelial–mesenchymal transition and angiogenesis by secreting TGF-β, VEGF and FGF. Moreover, platelets are also able to recruit neutrophils and monocytes, thereby promoting the distant metastasis of tumor cells. Finally, lymphocytes, especially cytotoxic T lymphocytes, play an essential role in cancer immune surveillance and defense (58). It has been reported that high lymphocyte levels in the tumor microenvironment are beneficial for inducing lysis and apoptosis of cancer cells, thereby inhibiting cancer cell proliferation and metastasis (59). On the contrary, lymphopenia has been shown to be associated with a poor prognosis in cancer patients (60).

Notably, the pooled outcomes from subgroup analyses demonstrated that the prognostic value of the PIV for both OS and PFS was consistent in treatment strategies, such as surgery (HR = 1.66 and 1.80), chemo/radiotherapy (HR = 2.37 and 2.06), immunotherapy (HR = 1.95 and 1.40). Given that patients with malignancies would receive one or more anti-tumor treatment strategies, these results showed that PIV could provide prognosis prediction for malignant patients receiving different treatments, especially for those receiving chemo/radiotherapy. In addition, PIV has been shown to have considerable prognostic value across different tumor species, particularly in lung cancer (HR = 3.09 and 2.43). Moreover, the prognostic value of PIV was not affected by the country of publication, cut-off value, and tumor stage, further confirming the clinical universality and efficacy of PIV in cancer patients.

This meta-analysis had several limitations must be acknowledged. First, all of the included studies except one by Qi et al. (37) were designed to be retrospective, which may increase the risk of selection bias. Second, the heterogeneities of pooled outcomes for both OS and PFS were remarkable, even though the subgroup analyses and sensitivity analyses showed consistent results, we failed to find the sources of heterogeneity. Third, significant inconsistencies in the measurement of blood parameters in the included studies, including but not limited to factors such as measurement time, may have contributed to the large variability in the cut-off values of PIV, and may also have had some impact on the confidence of our pooled results. Finally, the cut-off values of PIV varied widely due to various factors such as disease type, population differences, sample size, and detection method, which somewhat limits the clinical use of PIV.

In conclusion, the present meta-analysis demonstrates an association between elevated pre-treatment PIV and poor survival outcomes in cancer patients. PIV has the potential to be a noninvasive and effective prognostic biomarker for cancer patients.

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

YH-J: Funding acquisition, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing. RS: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Writing – review & editing, Visualization. XJ-Q: Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing.