ObjectiveTo analyze the factors influencing the hungry bone syndrome (HBS) in patients with secondary hyperparathyroidism (SHPT) after parathyroidectomy. MethodsThe clinical data of patients who underwent parathyroidectomy for SHPT in the 900th Hospital of the Joint Logistics Support Force from January 2016 to May 2021 were retrospectively analyzed. The risk factors for HBS were analyzed by binary logistic regression analysis. The cut-off value of risk factors for predicting postoperative HBS was analyzed by using recieve operating characteristic (ROC) curve. ResultsA total of 89 patients were included in this study, including 44 males and 45 females, with (47±11) years old. There were 42 (47.2%) patients with HBS. Compared with the patients without HBS, the patients with HBS was younger and had higher levels of preoperative parathyroid hormone, potassium, and alkaline phosphatase (ALP), the differences were statistically different (P<0.05). The multivariate binary logistic regression analysis showed that the higher preoperative ALP level was a risk factor for the HBS [OR (95%CI) = 1.014 (1.007, 1.020), P<0.001]. The area under the ROC curve (95%CI) of the preoperative ALP level in distinguishing the patients with HBS from without HBS was 0.957 (0.919, 0.996), and the optimal cut-off value of ALP for predicting postoperative HBS was 278.90 U/L. ConclusionsFrom the preliminary results of this study, it can be concluded that bone conversion status can be differentiated according to preoperative ALP level in patients with SHPT. When preoperative ALP level is higher than cut-off value, it is recommended that calcium supplementation should be given as soon as possible and blood calcium level should be closely monitored.
ObjectiveTo investigate the prognostic value of the alkaline phosphatase + gamma-glutamyl transpeptidase / platelet (AGPR) in predicting overall survival in patients with hepatocellular carcinoma (HCC) after curative hepatectomy, and to develop an AGPR-based nomogram prediction model to enhance the accuracy of prognostic risk stratification and individualized treatment decision-making. MethodsThis multicenter retrospective study included patients who underwent radical resection for HCC at the Affiliated Hospital of Southwest Medical University (2013–2023) as the training and internal validation sets, and at Leshan People’s Hospital (2018–2024) as the external validation set. Baseline characteristics, preoperative laboratory tests, surgical details, and pathological findings were collected. Optimal cutoff values for AGPR and the pan-immune-inflammation value (PIV) were determined using receiver operating characteristic (ROC) curves. Independent prognostic factors for overall survival were identified using univariate and multivariate Cox regression, then a nomogram was developed. Model performance was assessed using the area under the ROC curve (AUC), concordance index (C-index), calibration, and decision curve analysis for clinical utility assessment. Patients were stratified into low- and high-risk groups based on the median nomogram score, and overall survival was compared. ResultsA total of 618 patients were included: 250 in the training set, 167 in the internal validation set, and 201 in the external validation set. Optimal cutoff values were 1.06 for AGPR and 316.79 for PIV. Multivariate Cox regression identified alpha-fetoprotein (AFP), AGPR, PIV, and tumor diameter as independent prognostic factors (P＜0.05). The nomogram predicting 1-, 3-, and 5-year overall survival rates achieved AUCs of 0.820, 0.734, and 0.727 in the training set; 0.784, 0.722, and 0.705 in the internal validation set; and 0.789, 0.703, and 0.702 in the external validation set. C-indices were 0.748, 0.701, and 0.692, respectively. The Hosmer-Lemeshow test indicated good calibration (P>0.05), and calibration curves aligned closely with the ideal diagonal. Decision curve analysis demonstrated clinical net benefit across all datasets. Low-risk patients had significantly better overall survival than high-risk patients (P＜0.05). ConclusionsAGPR is an independent prognostic factor for overall survival in HCC patients after radical resection. The nomogram incorporating AGPR, AFP, PIV, and tumor diameter exhibits favorable discrimination, calibration, and clinical utility, supporting its use for postoperative risk stratification and individualized treatment planning.