| Title: | Association of systemic inflammatory response index and albumin-to-globulin ratio with prognosis in prostate cancer: a retrospective study |
| Journal: | European Journal of Medical Research |
| Published: | 8 Aug 2026 |
| DOI: | https://doi.org/10.1186/s40001-026-04544-0 |
Publication 21040
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Abstract
BackgroundCurrent research suggests that the prognosis of prostate cancer (PCa) patients may be related to their immune and nutritional status. We used systemic inflammatory response index (SIRI) and albumin-to-globulin ratio (AGR) to reflect the immune response and nutritional reserve status of the organism, with the aim of exploring the relationship between SIRI and AGR and the prognosis of prostate cancer patients.MethodWe retrospectively collected clinical and follow-up data of 316 patients first diagnosed with PCa in the First Affiliated Hospital of Xinjiang Medical University from 2011 to 2023, and used Kaplan-Meier survival analysis, unifactorial and multifactorial Cox proportional hazards models to analyze independent risk factors affecting overall survival (OS), and constructed a nomogram prediction model based on SIRI and AGR. Internal validation was performed using the Bootstrap method, and calibration curves and decision curves were plotted to assess the model's predictive accuracy and clinical net benefit. At the same time, the UK Biobank database was utilized to conduct external validation of the associations between SIRI and AGR and prostate cancer prognosis, and sensitivity analysis was performed to assess the robustness of the study findings.ResultsA total of 316 patients in the training cohort 282 survived, and 34 died at the end of follow-up. The differences in SIRI, AGR, age, and N stage between the survival and death groups were statistically significant (P < 0.05). Survival analysis showed that patients in the high AGR versus low SIRI group had significantly prolonged OS (P = 0.002 and P < 0.001), and the difference in OS between their combined subgroups was also statistically significant (P < 0.001). Cox regression analysis showed that AGR, SIRI, N stage, M stage, prostate-specific antigen, and age were independent factors affecting OS in PCa patients (P < 0.05). Internal validation using bootstrap sampling (B = 1000) shows that the model's mean absolute error for 1-year, 3-year, and 5-year survival predictions is 0.076, 0.045, and 0.023, respectively. Decision curve analysis indicates that, over 1 year (threshold 0.2-0.6), 3 years (0.1-0.7), and 5 years (0.1-0.8), the model's net benefit outperforms both the 'all treatment' and 'no treatment' strategies. External validation indicates that SIRI and AGR are factors influencing OS in patients with prostate cancer (P < 0.05). Sensitivity analysis results indicate that both variables are associated with overall survival in both the training cohort (AGR: HR: 0.22, 95% CI: 0.06-0.84, P = 0.027; SIRI: HR: 1.57, 95% CI: 1.14-2.15, P = 0.006) and the external validation cohort (AGR: HR: 0.56, 95% CI: 0.48-0.66, P < 0.001; SIRI: HR: 1.04, 95% CI: 1.02-2.01, P < 0.001).ConclusionSIRI and AGR can be used as effective predictors of prognosis in patients with PCa and may contribute to the development of effective adjuvant therapeutic regimens.</p>
9 Authors
- Yijie Zhou
- Tianqi Li
- Jueqi Wang
- Mingyue Chen
- Qiang Guo
- Zhenbo You
- Xinyi Bi
- Hengqing An
- Ning Tao
1 Application
| Application ID | Title |
|---|---|
| 540454 | Mediating effects of plasma proteomic biomarkers on the associations between sleep patterns and chronic diseases. |
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