Association between prognostic nutritional index (PNI)/Controlling Nutritional Status (CONUT) score and prognosis in patients with bladder cancer: a systematic review and meta-analysis

Introduction

Bladder cancer represents one of the most prevalent malignancies affecting the urinary tract. It ranks among the leading urological cancers in terms of incidence, with both its occurrence and mortality rates exhibiting a steady upward trend in recent years (1). Significant differences are observed in gender and age among patients with bladder cancer. Among them, the number of males far exceeds that of females, and the majority of patients are middle-aged and elderly (2). The pathogenesis of bladder cancer is highly complex. It is currently known that smoking and long-term exposure to occupational carcinogens may be important contributing factors (3). Two major subtypes of bladder cancer are distinguished according to tumor invasion depth: non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). Among clinical patients, about 75% are NMIBC (4). Transurethral resection of bladder tumor (TURBT) is currently the standard surgical treatment for NMIBC, supplemented by intravesical chemotherapy or immunotherapy after surgery, but the recurrence and progression rates remain high, significantly affecting patient quality of life. In recent years, as understanding and exploration of bladder cancer pathogenesis continue to advance, some biological tumor markers for NMIBC prognosis have been widely studied and applied (5). Therefore, identifying accurate and reliable prognostic biomarkers will help clinicians develop individualized treatment strategies and follow-up plans, and bring greater benefits to the prognosis and survival of NMIBC patients.

The nutritional and immunological status of cancer patients has a strong association with their prognosis (6). Prognostic nutritional index (PNI), calculated using peripheral lymphocyte count and serum albumin, functions as a marker for assessing both nutritional and immune function. Initially, it was introduced as a tool to evaluate these parameters in patients undergoing gastrointestinal surgical procedures. Growing evidence suggests that PNI may be a reliable prognostic indicator in individuals with lung cancer, breast cancer, esophageal cancer, hepatocellular carcinoma, and renal cancer (7-11). Hao et al. (12) conducted a prognostic study on PNI in individuals with esophageal squamous cell carcinoma and found that individuals with low PNI had a significantly worse prognosis. Fan et al. (13) pointed out in their analysis of PNI and the prognosis of patients with hepatocellular carcinoma after liver resection that preoperative PNI was an independent predictor of postoperative recurrence. Alongside PNI, the Controlling Nutritional Status (CONUT) has emerged as another objective and composite tool to evaluate a patient’s immunological and nutritional status (14,15). The CONUT is derived from three key biochemical parameters: serum albumin levels, peripheral lymphocyte count, and total cholesterol concentration, providing a potentially more comprehensive assessment of nutritional status by incorporating a parameter of energy reserve (16). Initially developed to screen for undernutrition in hospitalized patients, its prognostic utility has been increasingly recognized in various malignancies, including gastric cancer and colorectal cancer (17). A high CONUT, indicative of poorer nutritional and immune status, has been associated with worse survival outcomes in these cancer types (18). However, similar to PNI, the evidence regarding the prognostic value of CONUT specifically in bladder cancer patients remains scattered and warrants a systematic synthesis to establish its clinical relevance.

Although a meta-analysis by Jiao et al. (19) assessed the prognostic utility of PNI in the bladder cancer population, a range of more recent clinical studies have been published following its release. These newer investigations also explore the prognostic relevance of PNI, yet their findings remain inconsistent (20-27). Moreover, to our knowledge, no meta-analysis to date has thoroughly evaluated the predictive value of CONUT for outcomes in individuals with bladder cancer. Therefore, this study employs a systematic review and meta-analysis to re-evaluate the prognostic utility of PNI and CONUT in bladder cancer, incorporating the most recent evidence. It thereby provides up-to-date, evidence-based support for the development of prognostic predictive models. We present this article in accordance with the PRISMA reporting checklist (28) (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0105/rc).

Methods

Literature search

This systematic review and meta-analysis was prospectively submitted to the PROSPERO registry (CRD42024617724). A broad and systematic literature search was conducted across PubMed, Embase, Web of Science, and the Cochrane Library, covering studies published up to November 2025 that investigated the prognostic significance of PNI and CONUT in individuals diagnosed with bladder cancer. The detailed PubMed search strategy is presented below: (prognostic nutritional index OR PNI OR Controlling Nutritional Status score OR CONUT) AND ((“Urinary Bladder Neoplasms”[Mesh]) OR (“Urinary Bladder Neoplasm” OR “Bladder Neoplasms” OR “Bladder Tumors” OR “Bladder Cancer” OR “Cancer of the Bladder” OR “Malignant Tumor of Urinary Bladder”)). Sort by: Most Recent. Additionally, all bibliographic references from the selected studies were manually screened to detect any pertinent literature potentially overlooked during the original search process. Two researchers independently conducted the selection and evaluation of eligible articles. Discrepancies in study inclusion were resolved through discussion (shown in Table S1).

Inclusion and exclusion criteria

Inclusion criteria included: (I) randomized controlled trial (RCT), cohort study, or case-control; (II) the study population consisted of individuals with a confirmed diagnosis of bladder cancer; (III) the investigation focused on the prognostic relevance of PNI or CONUT; (IV) the study reported at least one survival outcome, including but not limited to progression-free survival (PFS), cancer-specific survival (CSS), relapse-free survival (RFS), overall survival (OS), or disease-specific survival (DFS); and (V) sufficient statistical data were available to calculate risk ratio (RR), odds ratio (OR), or hazard ratio (HR). Studies were excluded if they were protocols, unpublished manuscripts, non-original articles (e.g., letters, commentaries, abstracts, corrections, or replies), reviews, or lacked sufficient data for analysis.

Data abstraction

Data extraction was performed independently by two investigators. Any discrepancies were resolved with the involvement of a third reviewer. The following information was collected from each eligible study: first author’s name, year of publication, country, study period, study design, tumor type, treatment modalities, sample size, patient age, PNI and CONUT cut-off values, as well as survival outcomes including OS, CSS, PFS, and RFS. When essential data were missing or insufficient, attempts were made to obtain further details by reaching out to the respective corresponding author. The survival outcome measures analyzed in this meta-analysis are defined as follows: OS refers to the time from diagnosis or treatment to death from any cause; CSS refers to the time to death from bladder cancer (death from non-cancer causes is considered censored); RFS refers to the time to the first radiographically or pathologically confirmed tumor recurrence (local or distant) (death without recurrence is considered censored); PFS refers to the time to the first disease progression (according to RECIST criteria, etc.) or death from any cause. The specific definitions of these measures may vary slightly among original studies. This review followed the reports of the original studies during data extraction and considered them as potential sources of heterogeneity in the analysis.

Quality evaluation

The quality of the included cohort studies was rated using the Newcastle-Ottawa Scale (NOS) (29), with scores ranging from 7 to 9 points considered indicative of high methodological quality (30). Assessment of study quality was conducted independently by two reviewers, with conflicts addressed via mutual discussion.

Statistical analysis

HRs and their corresponding 95% confidence intervals (CIs) were employed to synthesize survival data. Heterogeneity among studies was evaluated using the χ² test (Cochran’s Q) and the I² statistic (31). Significant heterogeneity was indicated by a χ² P value <0.1 or an I² exceeding 50%, in which case pooled estimates were calculated using a random-effects model. When sufficient data were available, subgroup analyses were conducted to determine possible sources of heterogeneity, and sensitivity analyses were applied to evaluate the stability of pooled HRs by sequential exclusion of individual studies. Publication bias was examined through visual inspection of funnel plots and Egger’s regression test (32). A P value <0.05 was an indicator of statistically significant bias. All meta-analytic procedures were performed using Review Manager 5.4.1, with Egger’s test conducted in Stata 15.1 (StataCorp, College Station, TX, USA).

Results

Literature retrieval, study characteristics, and baseline

Figure 1 illustrates the whole process of literature identification and selection. A total of 276 potentially eligible articles were retrieved through a systematic search of PubMed (n=145), Embase (n=61), Web of Science (n=70), and the Cochrane Library (n=0). After duplicate entries were excluded, 177 titles and abstracts remained for screening. Following a detailed evaluation, our analysis included 17 retrospective cohort studies with 5,847 individuals (5,16,18,20-27,33-38). Their characteristics and quality assessment are presented in Table 1.

Figure 1 Flowchart of the systematic search and selection process.

PNI and OS

OS data from ten cohort studies were aggregated, and the meta-analysis indicated that individuals with low PNI had markedly decreased OS relative to those with higher PNI values (HR =1.86; 95% CI: 1.58–2.18; P<0.001). No notable heterogeneity was identified among the included studies (I²=0%, P=0.97) (Figure 2). Subgroup analyses based on tumor type, sample size, geographic region, and PNI cut-off value confirmed that the association between PNI and OS remained statistically significant across all categories. The detailed results of the subgroup analyses are provided in Table 2.

Figure 2 Forest plots of PNI and OS. CI, confidence interval; IV, inverse variance; OS, overall survival; PNI, prognostic nutritional index; SE, standard error.

PNI and RFS

RFS outcomes from five cohort studies were pooled, and the meta-analysis demonstrated that individuals with low PNI exhibited significantly shorter RFS compared to those with high PNI (HR =1.43; 95% CI: 1.25–1.64; P<0.001). No notable heterogeneity was identified (I²=3%, P=0.39) (Figure 3A).

Figure 3 Forest plots of PNI and RFS (A), CSS (B) and PFS (C). CI, confidence interval; CSS, cancer-specific survival; IV, inverse variance; PFS, progression-free survival; PNI, prognostic nutritional index; RFS, relapse-free survival; SE, standard error.

PNI and CSS

CSS data were derived from three cohort studies. Findings from the meta-analysis demonstrated that patients with lower PNI had markedly worse CSS outcomes than those with higher PNI levels (HR =2.05; 95% CI: 1.37–3.09; P<0.001). The analysis revealed minimal heterogeneity across the included studies, with no statistical significance (I²=20%, P=0.29) (Figure 3B).

PNI and PFS

PFS data were pooled from three cohort studies. The meta-analysis showed no significant relationship between PNI and PFS (HR =1.30; 95% CI: 0.89–1.91; P=0.17). The degree of heterogeneity among studies was moderate and statistically insignificant (I²=49%, P=0.14) (Figure 3C).

CONUT and OS

OS data were extracted from six cohort studies. The meta-analysis demonstrated that individuals with high CONUT had significantly reduced OS compared to those with low CONUT (HR =2.51; 95% CI: 1.67–3.78; P<0.001). A significant level of heterogeneity was identified among the studies (I²=66%, P=0.01) (Figure 4A).

Figure 4 Forest plots of CONUT and OS (A), CSS (B) and RFS (C). CI, confidence interval; CONUT, Controlling Nutritional Status; CSS, cancer-specific survival; IV, inverse variance; OS, overall survival; RFS, relapse-free survival; SE, standard error.

CONUT and CSS

CSS data were pooled from four cohort studies. The meta-analysis demonstrated that higher CONUT was associated with significantly poorer CSS outcomes in comparison to lower CONUT (HR =2.22; 95% CI: 1.05–4.70; P=0.04). A high degree of heterogeneity was identified (I²=82%, P<0.001) (Figure 4B).

CONUT and RFS

RFS outcomes were pooled from two cohort studies. According to the meta-analysis, individuals with elevated CONUT had notably shorter RFS than those with lower scores (HR =2.70; 95% CI: 1.89–3.84; P<0.001). No notable heterogeneity was identified among the studies (I²=0%, P=0.53) (Figure 4C).

Publication bias and sensitivity analysis

In the analysis of the relationship between PNI and prognosis, Egger’s test and funnel plot evaluation revealed no signs of publication bias for OS (P=0.09; Figure 5A), RFS (P=0.07; Figure 5B), CSS (P=0.09; Figure 5C), or PFS (P=0.48; Figure 5D). Sensitivity analyses were conducted for OS, RFS, CSS, and PFS to examine the influence of each individual study on the overall HR by sequentially excluding each eligible cohort. The pooled HRs for OS (Figure 6A), RFS (Figure 6B), and CSS (Figure 6C) remained consistent, indicating robust findings. In contrast, the sensitivity analysis for PFS revealed a change in the statistical significance of the association when the study by Ferro et al. was excluded, suggesting that the relationship between PNI and PFS may be unstable at this time (Figure 6D).

Figure 5 Funnel plots of PNI and OS (A), RFS (B), CSS (C) and PFS (D). CSS, cancer-specific survival; OS, overall survival; PFS, progression-free survival; PNI, prognostic nutritional index; RFS, relapse-free survival; SE, standard error.

Figure 6 Sensitivity analysis of PNI and OS (A), RFS (B), CSS (C) and PFS (D). CI, confidence interval; CSS, cancer-specific survival; OS, overall survival; PFS, progression-free survival; PNI, prognostic nutritional index; RFS, relapse-free survival.

With regard to the relationship between CONUT and prognosis, neither statistical testing (Egger’s test) nor visual assessment via funnel plots indicated the presence of publication bias for OS (P=0.99; Figure 7A) or CSS (P=0.95; Figure 7B). The sensitivity analysis demonstrated that the overall HR for OS remained consistent when each cohort study was sequentially excluded (Figure 8A). However, the sensitivity analysis of CSS demonstrated that the correlation between CONUT and CSS is currently unstable (Figure 8B).

Figure 7 Funnel plots of CONUT and OS (A), and CSS (B). CONUT, Controlling Nutritional Status; CSS, cancer-specific survival; OS, overall survival; SE, standard error.

Figure 8 Sensitivity analysis of CONUT and OS (A), and CSS (B). CI, confidence interval; CONUT, Controlling Nutritional Status; CSS, cancer-specific survival; OS, overall survival.

Discussion

Through data from 17 studies involving 5,847 bladder cancer patients, we identified two key findings: first, a lower PNI was significantly related to shorter OS, RFS, and CSS, but its association with PFS was not statistically significant. PFS as an outcome may be more driven by treatment response and tumor biology, while PNI, representing nutritional inflammatory status, may be more directly associated with long-term survival and recurrence in bladder cancer, and its association with disease progression may be less stable depending on the treatment modality. Second, a higher CONUT score also predicted shorter OS, CSS, and RFS. These results strongly confirm that PNI and CONUT, two nutritional and inflammatory assessment indicators based on routine blood tests, are effective predictors of prognosis in bladder cancer patients. Although significant heterogeneity was observed when analyzing the association between CONUT and OS and CSS, and sensitivity analysis suggested instability in some results, the pooled results for the primary outcome measures showed good consistency and low heterogeneity. No significant issues were found in the publication bias assessment, and sensitivity analysis further validated the robustness of these core findings. This study not only expands the evidence from Jiao et al.’s (19) earlier meta-analysis, enhancing the reliability of its conclusions by including more recent and extensive data, but more importantly, it is the first meta-analysis to assess and confirm the value of CONUT in bladder cancer prognosis, highlighting the importance of comprehensively evaluating patients’ nutritional and inflammatory status for risk stratification.

Although subgroup analyses showed that PNI had significant predictive value for OS in both NMIBC and MIBC patients, it is crucial to recognize the fundamental differences between these two disease states in terms of biological behavior, treatment goals, and clinical outcomes. Therefore, the pathophysiological states and clinical significance reflected by PNI and CONUT scores may differ across disease stages. In NMIBC, a poor nutritional inflammatory state may be more associated with local mucosal immune dysfunction, affecting the efficacy of BCG infusion and increasing the risk of recurrence. In MIBC patients undergoing radical cystectomy, it is more likely to comprehensively reflect the patient’s “systemic vulnerability”, including surgical tolerance, perioperative inflammatory burden, and potential for response to adjuvant therapy. For patients with metastatic disease, these indicators may strongly characterize tumor-induced cachexia and systemic inflammatory responses. Therefore, although pooled analyses showed statistically consistent associations, the clinical interpretation and application of these indicators must be considered in conjunction with the specific disease stage and treatment context, avoiding a “homogenized” understanding of their biological roles and prognostic significance. Future research should focus on elucidating the specific mechanisms of action of these biomarkers in independent cohorts at different disease stages.

It is well known that serum albumin levels are essential in evaluating the nutritional status of oncology patients, and nutrition significantly influences the recovery of cancer patients (39). Good nutritional levels help improve the overall well-being of patients, while low nutritional levels can weaken the defense mechanisms of cancer patients, including anatomical barriers, cellular and humoral immunity, and phagocytic function, leading to a weakened immune status (40,41). At the same time, there is a connection between nutrition and inflammatory status. Proinflammatory cytokines such as interleukin-1, interleukin-6, and tumor necrosis factor α are involved in malignant tumor transformation, angiogenesis, and tumor progression, and are also responsible for regulating the production of hepatocyte albumin (42). Nutritional deficiency and the generation of inflammatory responses lead to reduced immune function in cancer patients, thereby providing favorable conditions for tumor development and metastasis (43). Lymphocytes, another key component of PNI, are important peripheral blood cells and are crucial in the cellular immune response related to tumor progression and recurrence. Lymphocytes can fight against the cytotoxic response of cancer cells as well as the proliferation, migration, and invasion of cancer cells (44). In the case of lymphopenia, the cellular immune system cannot function normally and cannot establish an appropriate inflammatory response, resulting in reduced immune surveillance of tumor cells and increased immune escape by tumor cells.

In parallel to PNI, our meta-analysis provides robust evidence that CONUT may serve as a significant predictor of adverse outcomes in individuals diagnosed with bladder cancer. We found that a high CONUT was significantly related to shorter OS, CSS, and RFS. The combined HR for these outcomes was notably higher than those observed for PNI, which might be attributed to the more comprehensive nature of the CONUT assessment. By incorporating total cholesterol levels alongside serum albumin and lymphocyte count, CONUT potentially captures not only visceral protein reserves and immune competence but also the body’s energy reserve and overall metabolic status (45). Hypocholesterolemia, a component of CONUT, has been linked to systemic inflammation, increased cytokine activity, and worse outcomes in chronic diseases and cancer, as cholesterol is essential for cell membrane integrity and hormone synthesis (46). Therefore, a high CONUT might identify a subset of patients with more profound malnutrition and a heightened inflammatory and catabolic state, which collectively contribute to tumor progression and poor survival (47). However, it is important to note that the analyses for CONUT and OS/CSS exhibited significant heterogeneity, which could be influenced by variations in study populations, disease stages (NMIBC vs. MIBC), or the chosen cut-off values for CONUT across different studies. Future studies should aim to standardize the application of CONUT in oncology settings.

This study confirms a robust statistical association between PNI and CONUT scores and poor prognosis in bladder cancer patients; however, the nature of this association must be carefully interpreted. Observational study design itself cannot establish causality, and the association we observed may have two possible interpretations. On the one hand, malnutrition and systemic inflammation may actively drive disease progression and poor prognosis by weakening immune surveillance and promoting immunosuppression in the tumor microenvironment (48). On the other hand, there is also the possibility of a significant reverse causal relationship: advanced tumors themselves lead to cachexia, chronic wasting, and inflammatory states, thereby reducing PNI and increasing CONUT scores (49). Therefore, low PNI/high CONUT may be a significant consequence and composite marker of advanced disease burden and deteriorating host condition, rather than necessarily an independent prognostic driver. Distinguishing between these two scenarios is crucial for understanding their biological role and clinical significance. Future research, through well-designed prospective studies that control for confounding factors such as disease stage and treatment, needs to further elucidate the direction and extent of their causal contribution.

At present, standardized cut-off points for PNI and SII have not been universally defined. Variations in race, gender, age, and tumor type may contribute to differences in their cut-off values. Jeon et al. (50) reported a PNI value of 51 in their study on renal cancer, and Mori et al. (51) calculated an optimal PNI cut-off value of 50 through receiver operating characteristic (ROC) curve analysis in their study on non-small cell lung cancer. In our study, a subgroup analysis of OS was performed based on PNI cut-off values, but the results indicated no significant difference in the predictive value of PNI between subgroups with cut-off ≥50 and those with cut-off <50. This could be attributed to the limited number of available studies. The optimal PNI cut-off range requires confirmation through further research. Similarly, establishing a universally applicable cut-off value for CONUT in individuals diagnosed with bladder cancer is a crucial step for its clinical implementation and should be validated in larger prospective cohorts.

This study confirms the prognostic value of PNI and CONUT, but it must be clearly pointed out that the cutoff values used by the included original studies in defining the “high” and “low” risk groups differed significantly, representing a core methodological challenge in the current evidence framework. This inconsistency may stem from various factors, including heterogeneity of study populations, differences in statistical methods, and the lack of bladder cancer-specific reference standards based on large prospective cohorts. Although we attempted to explore this through subgroup analysis, the non-standardization of cutoff values directly affected the accurate interpretation of pooled HRs and created a substantial obstacle to directly applying these indicators to clinical risk stratification. Therefore, the associations presented in this meta-analysis should be considered as statistical trends rather than definitive clinical evidence based on uniform thresholds. Future research urgently needs to focus on establishing and validating standardized cutoff values applicable to specific bladder cancer populations using robust methodologies in large, multicenter cohorts. This is a crucial step in transforming PNI and CONUT from research indicators into reliable clinical tools.

However, this analysis is not without limitations, which should be carefully considered. First, only retrospective cohort studies were included. As is widely recognized, retrospective designs are susceptible to confounding factors and an increased risk of bias, which represent notable methodological weaknesses. Second, the majority of included studies originated from Asia, with limited contributions from Europe and an absence of data from the Americas and Africa. This geographic concentration raises concerns about the generalizability of the findings to broader, more diverse populations. This limitation affects both the PNI and CONUT analyses. Furthermore, the heterogeneity of treatment modalities is a potentially significant confounding factor in this study. However, due to data limitations, we were unable to assess whether the prognostic value of PNI/CONUT is independent of treatment modality or whether there are differences across different treatment modalities. We recommend that future studies consider stratified analysis in their design. Lastly, the predictive value of PNI for PFS appears to be unstable, as indicated by the sensitivity analysis. Therefore, interpretations related to PFS should be made with caution. Likewise, the instability observed in the association between CONUT and CSS, as revealed by sensitivity analysis, necessitates cautious interpretation of this particular finding. Although certain limitations exist, this study represents the latest and most extensive analysis evaluating the prognostic significance of PNI and CONUT among patients with bladder cancer. The findings presented here highlight the clinical relevance of monitoring PNI levels and CONUT in managing bladder cancer, and emphasize the potential of developing more effective prognostic models incorporating inflammatory markers such as PNI and CONUT, with the goal of enhancing medical outcomes and overall patient well-being.

Conclusions

As clinically accessible, cost-effective, and non-invasive biomarkers, PNI and CONUT have demonstrated potential in predicting both survival outcomes and recurrence risk in patients with bladder cancer, thereby contributing to improved prognostic assessment. However, given the limitations of this meta-analysis—including regional limitations, limited sample sizes, potential result variability, and the retrospective nature of the included studies—there remains a clear need for large-scale, multicenter prospective cohort studies to further validate the prognostic significance of PNI and CONUT in this patient population.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0105/rc

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0105/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-2026-1-0105/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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