Objective To develop and validate a nomogram prediction model of early knee function improvement after total knee arthroplasty (TKA). Methods One hundred and sixty-eight patients who underwent TKA at Sichuan Province Orthopedic Hospital between January 2018 and February 2021 were prospectively selected to collect factors that might influence the improvement of knee function in the early postoperative period after TKA, and the improvement of knee function was assessed using the Knee Score Scale of the Hospital for Special Surgery (HSS) at 6 months postoperatively. The patients were divided into two groups according to the postoperative knee function improvement. The preoperative, intraoperative and postoperative factors were compared between the two groups; multiple logistic regression was performed after the potential factors screened by LASSO regression; then, a nomogram predictive model was established by R 4.1.3 language and was validated internally. Results All patients were followed up at 6 months postoperatively, and the mean HSS score of the patients increased from 55.19±8.92 preoperatively to 89.27±6.18 at 6 months postoperatively (t=−40.706, P<0.001). LASSO regression screened eight influencing factors as potential factors, with which the results of multiple logistic regression analysis showed that preoperative body mass index, etiology, preoperative joint mobility, preoperative HSS scores, postoperative lower limb force line, and postoperative analgesia were independent influencing factors for the improvement of knee function in the early postoperative period after TKA (P<0.05). A nomogram model was established based on the multiple logistic regression results, and the calibration curve showed that the prediction curve basically fitted the standard curve; the receiver operating characteristic curve showed that the area under the curve of the nomogram model for the prediction of suboptimal knee function in the early postoperative period after TKA was 0.894 [95% confidence interval (0.825, 0.963)]. Conclusions There is a significant improvement in knee function in patients after TKA, and the improvement of knee function in the early postoperative period after TKA is influenced by preoperative body mass index, etiology, and preoperative joint mobility, etc. The nomogram model established accordingly can be used to predict the improvement of knee function in the early postoperative period after TKA with a high degree of differentiation and accuracy.
ObjectiveTo establish an individualized nomogram model and evaluate its efficacy to provide a possible evaluation basis for the prognosis of lower third and abdominal part of oesophageal adenocarcinoma (EAC). MethodsLower third and abdominal part of EAC patients were chosen from the SEER Research Plus Database (17 Regs, 2022nov sub). The patients were randomly allocated to the training cohort and the internal validation cohort with a ratio of 7∶3 using bootstrap resampling. The Cox proportional hazards regression analysis was used to determine significant contributors to overall survival (OS) in EAC patients, which would be elected to construct the nomogram prediction model. C-index, calibration curve and receiver operating characteristic (ROC) curve were performed to evaluate its efficacy. Finally, the efficacy to evaluate the OS of EAC patients was compared between the nomogram prediction model and TNM staging system. ResultsIn total, 3945 patients with lower third and abdominal part of EAC were enrolled, including 3475 males and 470 females with a median age of 65 (57-72) years. 2761 patients were allocated to the training cohort and the remaining 1184 patients to the internal validation cohort. In the training and the internal validation cohorts, the C-index of the nomogram model was 0.705 and 0.713, respectively. Meanwhile, the calibration curve also suggested that the nomogram model had a strong capability of predicting 1-, 3-, and 5-year OS rates of EAC patients. The nomogram also had a higher efficacy than the TNM staging system in predicting 1-, 3-, and 5-year OS rates of EAC patients. ConclusionThis nomogram prediction model has a high efficiency for predicting OS in the patients with lower third and abdominal part of EAC, which is higher than that of the current TNM staging system.
ObjectiveTo investigate the prognostic value of preoperative serum albumin-to-globulin ratio (AGR) and neutrophil-lymphocyte ratio (NLR) in the overall survival (OS) of patients with esophageal squamous cell carcinoma (ESCC), and to establish an individualized nomogram model and evaluate its efficacy, in order to provide a possible evaluation basis for the clinical treatment and postoperative follow-up of ESCC patients. MethodsAGR, NLR, clinicopathological and follow-up data of ESCC patients diagnosed via pathology in the Department of Thoracic Surgery, The First Affiliated Hospital of Xinjiang Medical University from 2010 to 2017 were collected. The correlation between NLR/AGR and clinicopathological data were analyzed. Kaplan-Meier analysis and log-rank test were used for survival analysis. The optimal cut-off values of AGR and NLR were determined by X-tile software, and the patients were accordingly divided into a high-level group and a low-level group. At the same time, univariate and multivariate Cox regression analyses were used to identify independent risk factors affecting OS in the ESCC patients, and a nomogram prediction model was constructed and internally verified. The diagnostic efficacy of the model was evaluated by receiver operating characteristic (ROC) curve and calibration curve, and the clinical application value was evaluated by decision curve analysis. ResultsA total of 150 patients were included in this study, including 105 males and 45 females with a mean age of 62.3±9.3 years, and the follow-up time was 1-5 years. The 5-year OS rate of patients in the high-level AGR group was significantly higher than that in the low-level group (χ2=6.339, P=0.012), and the median OS of the two groups was 25 months and 12.5 months, respectively. The 5-year OS rate of patients in the high-level NLR group was significantly lower than that in the low-level NLR group (χ2=5.603, P=0.018), and the median OS of the two groups was 18 months and 39 months, respectively. Multivariate Cox analysis showed that AGR, NLR, T stage, lymph node metastasis, N stage, and differentiation were independent risk factors for the OS of ESCC patients. The C-index of the nomogram model was 0.689 [95%CI (0.640, 0.740)] after internal validation. The area under the ROC curve of predicting 1-, 3-, and 5-year OS rate was 0.773, 0.724 and 0.725, respectively. At the same time, the calibration curve and the decision curve suggest that the model had certain efficacy in predicting survival and prognosis. ConclusionPreoperative AGR and NLR are independent risk factors for ESCC patients. High level of AGR and low level of NLR may be associated with longer OS in the patients; the nomogram model based on AGR, NLR and clinicopathological features may be used as a method to predict the survival and prognosis of ESCC patients, which is expected to provide a reference for the development of personalized treatment for patients.