Objective To explore the potential indicators of cervical lymph node metastasis in papillary thyroid microcarcinoma (PTMC) patients and to develop a nomogram model. Methods The clinicopathologic features of PTMC patients in the SEER database from 2004 to 2015 and PTMC patients who were admitted to the Center for Thyroid and Breast Surgery of Xuanwu Hospital from 2019 to 2020 were retrospectively analyzed. The records of SEER database were divided into training set and internal verification set according to 7∶3. The patients data of Xuanwu Hospital were used as the external verification set. Logistic regression and Lasso regression were used to analyze the potential indicators for cervical lymph node metastasis. A nomogram was developed and whose predictive value was verified in the internal and external validation sets. According to the preoperative ultrasound imaging characteristics, the risk scores for PTMC patients were further calculated. The consistency between the scores based on pathologic and ultrasound imaging characteristics was verified. Results The logistic regression analysis results illustrated that male, age<55 years old, tumor size, multifocality, and extrathyroidal extension were associated with cervical lymph node metastasis in PTMC patients (P<0.001). The C index of the nomogram was 0.722, and the calibration curve exhibited to be a fairly good consistency with the perfect prediction in any set. The ROC curve of risk score based on ultrasound characteristics for predicting lymph node metastasis in PTMC patients was 0.701 [95%CI was (0.637 4, 0.765 6)], which was consistent with the risk score based on pathological characteristics (Kappa value was 0.607, P<0.001). Conclusions The nomogram model for predicting the lymph node metastasis of PTMC patients shows a good predictive value, and the risk score based on the preoperative ultrasound imaging characteristics has good consistency with the risk score based on pathological characteristics.
ObjectiveTo explore the relation between preoperative serum gamma-glutamyl transpeptidase to platelet ratio (GPR) and overall survival (OS) of patients with hepatitis B virus-associated hepatocellular carcinoma (Abbreviated as “patients with HCC”), and to establish a nomogram for predicting OS. MethodsAccording to the inclusion and exclusion criteria, the clinicopathologic data of patients with HCC who underwent radical resection in the Department of Hepatobiliary Surgery of Xianyang Central Hospital, from January 15, 2012 to December 15, 2018, were retrospectively analyzed. The optimal critical value of GPR was determined by receiver operating characteristic curve, then the patients were divided into a low GPR group (GPR was optimal critical value or less ) and high GPR group (GPR was more optimal critical value). The Kaplan-Meier method was used to draw the survival curve and analyze the OS of patients. The univariate and multivariate Cox proportional hazards regression model were used to analyze the factors influencing prognosis in the patients with HCC. According to the risk factors of OS for patients with HCC, a nomogram was established. The consistency index and calibration curve in predicting the 3-year and 5-year accumulative OS rates of patients with HCC were evaluated. ResultsA total of 213 patients were gathered. The optimal critical value of GPR was 0.906. There were 114 patients in the low GPR group and 99 patients in the high GPR group. The Kaplan-Meier survival curve analysis showed that the 1-, 3- and 5-year accumulative OS rates were 99.1%, 81.8%, 60.6% in the low GPR group, respectively, which were 74.2%, 49.1%, 35.7% in the low GPR group, respectively. The OS curve of the low GPR group was better than that of the high GPR group (χ2=25.893, P<0.001). The multivariate analysis results showed that the microvascular invasion, incomplete capsule, intraoperative bleeding ＞1 000 mL, postoperative complications, GPR >0.906, low tumor differentiation, and late TNM stage did not contribute to accumulative OS in the patients with HCC (P<0.05). The consistency index (95%CI) of the nomogram in predicting accumulative OS rates at 3- and 5-year for patients with HCC were 0.761 (0.739, 0.783) and 0.735 (0.702, 0.838), respectively. The calibration curves of 3- and 5-year accumulative OS rates of the nomogram were in good agreement with the actual results. ConclusionsPreoperative GPR is associated with OS, and patients with higher GPR have worse prognosis. The nomogram based on GPR has a good accuracy and differentiation.
ObjectiveTo explore the influencing factors of cancer-specific survival of patients with large hepatocellular carcinoma, and draw a nomogram to predict the cancer-specific survival rate of large hepatocellular carcinoma patients.MethodsThe clinicopathological data of patients with large hepatocellular carcinoma during the period from 1975 to 2017 in the Surveillance, Epidemiology, and End Results (SEER) database were searched and randomly divided into training group and validation group at 1∶1. Using the training data, the Cox proportional hazard regression model was used to explore the influencing factors of cancer-specific survival and construct the nomogram; finally, the receiver operating characteristic curve (ROC curve) and the calibration curve were drawn to verify the nomogram internally and externally.ResultsThe results of the multivariate Cox proportional hazard regression model showed that the degree of liver cirrhosis, tumor differentiation, tumor diameter, T stage, M stage, surgery, and chemotherapy were independent influencing factors that affect the specific survival of patients with large hepatocellular carcinoma (P<0.05), and then these factors were enrolled into the nomogram of the prediction model. The areas under the 1, 3, and 5-year curves of the training group were 0.800, 0.827, and 0.814, respectively; the areas under the 1, 3, and 5-year curves of the validation group were 0.800, 0.824, and 0.801, respectively. The C index of the training group was 0.779, and the verification group was 0.777. The calibration curve of the training group and the verification group was close to the ideal curve of the actual situation.ConclusionThe nomogram of the prediction model drawn in this study can be used to predict the specific survival of patients with large hepatocellular carcinoma in the clinic.
ObjectiveTo explore the value of geriatric nutritional risk index (GNRI) and sarcopenia on predicting postoperative complications in elderly patients with gastric cancer. MethodsAccording to the inclusion and exclusion criteria, the elderly (aged ≥60 years) patients with gastric cancer underwent radical gastrectomy in the Department of Gastrointestinal Surgery of Xuzhou Central Hospital from January 1, 2017 to December 31, 2021 were retrospectively gathered. The occurrence of postoperative complications (grade 2 or beyond by the Clavien-Dindo classification) was analyzed. The risk factors affecting postoperative complications were analyzed by univariate and multivariate logistic regression analyses to construct the prediction model, then was visualized by drawing a nomogram. The differentiation of the nomogram between the patients with postoperative complications and without postoperative complications was evaluated by the receiver operating characteristic (ROC) curve. The accuracy of the nomogram was evaluated by the calibration curve. Further, the clinical net benefit rate was analyzed by the decision curve analysis (DCA) to evaluate the clinical practicability. ResultsA total of 236 patients were gathered, 97 (41.1%) of whom had postoperative complications during hospitalization. The results of multivariate logistic regression analysis showed that the age, gender, GNRI, sarcopenia, surgical mode, and American Society of Aneshesiologists classification were the factors influencing the postoperative complications (P<0.05). The differentiation of nomogram based on the influencing factors was well, the area under the ROC curve was 0.732. The calibration curve showed that the model prediction curve was close to the ideal curve. The clinical net benefit rate by the DCA was higher when the probability of postoperative complications was 0.18 to 0.72. ConclusionsThe efficiency of nomogram based on GNRI and sarcopenia is well for predicting the occurrence of postoperative complications in elderly patients with gastric cancer. However, the nomogram needs to be further validated by prospective studies and external data.
ObjectiveTo explore the risk factors for postoperative paraplegia in patients with Stanford type A aortic dissection and to construct a nomogram prediction model for postoperative paraplegia in these patients. MethodsStanford type A aortic dissection patients admitted to the First Affiliated Hospital with Nanjing Medical University from January 2021 to August 2024 were selected as the research subjects, and the occurrence of postoperative paraplegia was statistically analyzed. LASSO regression was used to screen the predictive factors, and further multivariate logistic regression analysis was conducted to identify the independent risk factors. A nomogram model was constructed based on R software (4.2.3), and internal validation was performed using the Bootstrap method. ResultsA total of 353 patients with Stanford type A aortic dissection were included, among whom 27 (7.65%) developed paraplegia after surgery. Multivariate logistic regression analysis showed that preoperative hypotension, prolonged cardiopulmonary bypass time, prolonged aortic cross-clamping time, preoperative renal insufficiency, postoperative infection, type Ⅰ spinal cord blood supply, and intraoperative mean arterial pressure <60 mmHg (1 mmHg=0.133 kPa) were independent risk factors for postoperative paraplegia in patients with Stanford type A aortic dissection (P<0.05). The area under the receiver operating characteristic curve of the nomogram model was 0.920 [95%CI (0.879, 0.961)]; the calibration curve showed that the predicted value of the nomogram model was basically consistent with the actual value (Hosmer-Lemeshow test, χ2=3.201, P=0.921); the decision curve analysis showed that within the threshold probability range of 1% to 100%, the nomogram prediction results had good benefit values for the intervention of postoperative paraplegia in patients with Stanford type A aortic dissection. ConclusionsPreoperative hypotension, prolonged cardiopulmonary bypass time, prolonged aortic cross-sectional time, preoperative renal insufficiency, postoperative infection, type Ⅰ spinal cord blood supply, and intraoperative mean arterial pressure <60 mmHg are all independent risk factors for postoperative paraplegia in patients with Stanford type A aortic dissection. The nomogram model constructed based on the above risk factors can effectively predict the postoperative paraplegia risk of patients with Stanford type A aortic dissection.
ObjectiveTo analyze the correlation between folate receptor-positive circulating tumor cells (FR+CTC) and the benign or malignant lesions of the lung, and to establish a malignant prediction model for pulmonary neoplasm based on clinical data, imaging and FR+CTC tests.MethodsA retrospective analysis was done on 1 277 patients admitted to the Affiliated Hospital of Qingdao University from September 2018 to December 2019, including 518 males and 759 females, with a median age of 57 (29-85) years. They underwent CTC examination of peripheral blood and had pathological results of pulmonary nodules and lung tumors. The patients were randomly divided into a trial group and a validation group. Univariate and multivariate analyses were performed on the data of the two groups. Then the nomogram prediction model was established and verified internally and externally. Receiver operating characteristic (ROC) curve was used to test the differentiation of the model and calibration curve was used to test the consistency of the model.ResultsTotally 925 patients suffered non-small cell lung cancer and 113 patients had benign diseases in the trial group; 219 patients suffered non-small cell lung cancer and 20 patients had benign diseases in the verification group. The FR+CTC in the peripheral blood of non-small cell lung cancer patients was higher than that found in the lungs of the patients who were in favorite conditions (P<0.001). Multivariate analysis showed that age≥60 years, female, FR+CTC value>8.7 FU/3 mL, positive pleural indenlation sign, nodule diameter, positive burr sign, consolidation/tumor ratio<1 were independent risk factors for benign and malignant lung tumors with a lesion diameter of ≤4 cm. Thereby, the nomogram prediction model was established. The area under the ROC curve (AUC) of the trial group was 0.918, the sensitivity was 86.36%, and the specificity was 83.19%. The AUC value of the verification group was 0.903, the sensitivity of the model was 79.45%, and the specificity was 90.00%, indicating nomogram model discrimination was efficient. The calibration curve also showed that the nomogram model calibration worked well.ConclusionFR+CTC in the peripheral blood of non-small cell lung cancer patients is higher than that found in the lungs of the patients who carry benign pulmonary diseases. The diagnostic model of clinical stage Ⅰ non-small cell lung cancer established in this study owns good accuracy and can provide a basis for clinical diagnosis.
ObjectiveTo analyze the current status and risk factors of postoperative complications in patients with retroperitoneal tumor (RPT) and to establish a nomogram for predicting the occurrence of postoperative complications. MethodsThe clinicopathologic data of patients with RPT who met the inclusion criteria in the West China Hospital of Sichuan University from June 2019 to May 2022 were retrospectively collected. The risk factors of postoperative complications were analyzed by using univariate and multivariate analyses, and the nomogram was constructed based on the risk factors and validated. ResultsA total of 205 patients were collected in this study, 70 (34.1%) of whom had postoperative complications. The multivariate analysis results of logistic regression showed that the preoperative serum albumin ＜35 g/L [OR=2.355, 95%CI (1.256, 4.416), P=0.008], tumor sarcoma [OR=2.498, 95%CI (1.219, 5.120), P=0.012], and visceral resection [OR=2.008, 95%CI (1.042, 3.868), P=0.037] increased the probability of postoperative complications for the patients with RPT. The area under the receiver operating characteristic curve of the nomogram based on the risk factors in predicting the occurrence of postoperative complications was 0.704 [95%CI (0.626, 0.781), P<0.001]. The consistency index of the nomogram by internal verification was 0.704 [95%CI (0.628, 0.779)]. The calibration curve of the nomogram showed that the predicted value was basically consistent with the actual value, the Hosmer-Lemeshow goodness-of-fit test model had a good goodness-of-fit (χ2=3.407, P=0.906). ConclusionsFrom the results of this study, the tumor sarcoma, lower preoperative serum albumin, and visceral resection are associated with postoperative complications for patients with RPT. The nomogram based on risk factors has a good predictive value for postoperative complications.
ObjectiveTo investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients. MethodsThe data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, they were divided into a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistical differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and a nomogram model was constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. ResultsA total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of (59.0±10.3) years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of (56.8±10.3) years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS (P＜0.05). Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody positive (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant (P＜0.05), while the association between STAS and spiculation was not significant anymore (P=0.438). Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter non-small cell lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had a good prediction efficiency for STAS. The DCA plot showed that the model had a good clinically utility. ConclusionMale, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, and the nomogram model established in this study has a good predictive value and provides reference for preoperative planning of patients.
Objective To explore the relationship between kinesiophobia, psychological resilience, and rehabilitation self-efficacy in postoperative patients with lumbar disc herniation (LDH) and constructing a nomogram prediction model for postoperative kinesiophobia. Methods LDH patients admitted to Shengjing Hospital of China Medical University between July 2021 and June 2024 were selected. Patients with LDH were assessed using a general information questionnaire, the Tampa Scale for Kinesiophobia, the Connor-Davidson Resilience Scale, and the Self-Efficacy for Rehabilitation Outcome Scale. Logistic regression was used to analyze the influencing factors of kinesiophobia in postoperative LDH patients, and a nomogram prediction model was constructed based on these factors. Results A total of 256 LDH patients were included. Among them, the average kinesiophobia score was (38.16±4.24) points, the average psychological resilience score was (55.36±4.26) points, and the average rehabilitation self-efficacy score was (96.06±6.06) points. Kinesiophobia was present in 149 patients (58.20%) after surgery. Kinesiophobia showed a negative correlation with both psychological resilience and rehabilitation self-efficacy (P<0.01). The results of multiple logistic regression analysis showed that, Age≥60 years, female gender, lack of pain guidance, low psychological resilience score, and low rehabilitation self-efficacy score were identified as independent risk factors for kinesiophobia in postoperative patients with lumbar disc herniation (P<0.05). The validation results of the nomogram model showed a C-index of 0.809, with the calibration curve approaching the ideal curve, and an area under the curve of 0.811. Conclusions Age ≥60 years, female gender, lack of pain guidance, low rehabilitation self-efficacy scores, and low rehabilitation self-efficacy scores were significantly associated with the risk of kinesiophobia in postoperative patients with LDH. The nomogram model constructed based on these factors demonstrated good predictive value for the occurrence of kinesiophobia in these patients.
ObjectiveCombined with long non-coding RNA (lncRNA) to find a regression model that can be used to predict the survival rate of patients with colon cancer before operation.MethodsThe clinical information and gene expression information of patients with colon cancer were downloaded by using TCGA database. The differentially expressed lncRNAs in tumor and paracancerous tissues were screened out, and then combined with the clinical information of patients to construct Cox proportional hazard regression model.ResultsA total of 26 kinds of lncRNAs with statistical difference in gene expression between paracancerous tissues and tumor tissues were selected (P<0.05). Through repeated screening and comparison of prediction efficiency, the prediction model was finally selected, which was constructed by patients’ age, M stage, N stage, and three kinds of lncRNAs (ZFAS1, SNHG25, and SNHG7) gene expression level: age [HR=4.00, 95%CI: (1.48, 10.84), P=0.006], M stage [HR=3.96, 95%CI: (2.23, 7.04), P<0.001], N stage [HR=1.87, 95%CI: (1.24, 2.84), P=0.003], ZFAS1 gene expression level [HR=0.60, 95%CI: (0.41, 0.86), P=0.006], SNHG25 gene expression level [HR=0.85, 95%CI: (0.73, 1.00), P=0.045], and SNHG7 gene expression level [HR=2.32, 95%CI: (1.53, 3.52), P<0.001] were all independent risk factors for postoperative survival of patients with colon cancer. The area under the ROC curves for predicting 1, 3, and 5-year overall survival were 0.802, 0.828, and 0.771, respectiely, which had a good prediction ability.ConclusionThe predictive model constructed by the combination of ZFAS1, SNHG25, SNHG7 genes expression level with M stage, N stage, and age can better predict the overall survival rate of patients before operation, which can effectively guide clinical decision-making and choose the most suitable treatment method for patients.