ArticleFrontiers in oncology2025
Preoperative inflammation-based immune prognostic nomogram in bladder cancer: a multicenter study.
Article in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Editorial: Microbial biomarkers predicting BCG therapy response in non-muscle invasive bladder cancer.Frontiers in oncology · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The systemic inflammatory response has been increasingly recognized as a crucial determinant of tumor progression and prognosis across various malignancies, including bladder cancer (BCa). Preoperative inflammation-based indices, which reflect the dynamic interaction between the tumor and host immune system, offer promising prognostic insights. However, existing studies have largely overlooked the synergistic integration of these indices with histopathological factors into a validated clinical tool for individualized survival prediction following radical cystectomy (RC). Methods: We conducted a retrospective multicenter study involving 1,387 BCa patients who underwent RC at two tertiary hospitals in Yunnan, China, from 2014 to 2024. Key preoperative systemic inflammatory indices-including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI)-were extracted alongside clinical and pathological variables such as AJCC stage, perineural invasion (PNI), and lymphovascular invasion (LVI). Variable selection was performed via LASSO regression, and independent predictors were identified using multivariate Cox regression. A prognostic nomogram was developed and validated through concordance index (C-index), time-dependent ROC curves, calibration plots, and decision curve analysis (DCA). Results: The final nomogram included five independent predictors: NLR, PLR, AJCC stage, PNI, and LVI. The model demonstrated robust discrimination with C-indices of 0.78 in the training cohort and 0.72 in the external validation cohort. AUC values consistently exceeded 0.75 at 1-, 3-, and 5-year timepoints. Calibration plots showed excellent agreement between predicted and observed outcomes, and DCA confirmed meaningful clinical benefit across various threshold probabilities. Conclusion: This study presents a validated, inflammation-based prognostic nomogram that combines preoperative hematologic indices with pathological features to predict overall survival in BCa patients undergoing RC. The model is non-invasive, cost-effective, and easy to implement using routine clinical data. Its strong predictive performance supports its application in preoperative counseling, individualized surveillance strategies, and decision-making regarding adjuvant therapy, contributing to more precise and personalized management in bladder cancer care.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.