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A novel nomogram based on inflammation biomarkers for predicting radiation cystitis in patients with local advanced
Jie Lin1, Jiexiang Lin2,3, Linying Liu1
1Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China.
Backgrounds:
Platelet-to-albumin ratio (PAR) is a new systemic inflammatory prognostic indicator associated with many inflammatory diseases. However, its role in radiation cystitis (RC) is obscure. This study aimed to explore whether PAR could be used as an effective parameter for predicting the RC risk in local advanced cervical cancer (CC) treated with radiotherapy.
Methods:
A total of 319 local advanced CC patients who received radical radiotherapy at Fujian Cancer Hospital were enrolled between December 2018 and January 2021. Demographics and clinical parameters were retrospectively analyzed. Univariate and multivariate analyses were used to identify the risk factors for RC. Backward and stepwise regression was applied to construct two monograms-one with primary significant factors and the other with extra inflammatory biomarkers. A DeLong test was applied to compare the prediction abilities of two nomograms. Calibration curves and decision curve analysis (DCA) evaluated its prediction consistency, discrimination ability, and clinical net benefit.
Results:
Univariate analysis showed that age, tumor size, stage, total radiation dose, pelvic radiation dose, Systemic Immune-Inflammation Index (SII), platelet-to-lymphocyte ratio (PLR), and PAR were significantly associated with RC occurrence (all p < 0.05). Multivariate analyses indicated that age, tumor size, stage, total radiation dose, and PAR were independent factors (all p < 0.05). Then, the area under curve (AUC) value of the nomogramSII+PAR was higher (AUC = 0.774) compared to that of the baseline nomogram (AUC = 0.726) (pDelong = 0.02). Also, the five-cross validation confirmed the stability of the nomogramSII+PAR. Moreover, the calibration curve and DCA exhibited the nomograms' good prediction consistency and clinical practicability.
Conclusions:
PAR and SII could be valued for CC patients who are treated with radiation therapy. The nomogram based on PAR and SII could stratify patients who need extra intervention and nursing care to prevent bladder radiation damage and improve patients' quality of life.
