• The Korean Journal of Pain
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• v.33 no.2
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• pp.153-165
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• 2020

Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its recurrence. Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service-National Sample Cohort enrolled from 2002 to 2010. We used Cox proportional hazards models. Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, income grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescription, and medical history of diseases. The Harrell's C-statistic was 0.812 (95% confidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions: LBP risk prediction models and simplified risk scores have been developed and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorporating other risk predictors in other settings, especially in this era of precision medicine.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1813-1816
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• 2015

Background: The aim of this study was to research the importance of the neutrophil to lymphocyte ratio (NLR) in prediction of PSA recurrence after radical prostatectomy, which has not been reported so far. Materials and Methods: The data of 175 patients who were diagnosed with localised prostate cancer and underwent retropubic radical prostatectomy was retrospectively examined. Patient pre-operative hemogram parameters of neutrophil count, lymphocyte count and NLR were assessed. The patients whose PSAs were too low to measure after radical prostatectomy in their follow-ups, and then had PSAs of 0,2 ng/mL were considered as patients with PSA recurrence. Patients with recurrence made up Group A and patients without recurrence made up Group B. Results: In terms of the power of NLR value in distinguishing recurrence, the area under OCC was statistically significant (p<0.001) .The value of 2.494 for NLR was found to be a cut-off value which can be used in order to distinguish recurrence according to Youden index. According to this, patients with a higher NLR value than 2.494 had higher rates of PSA recurrence with 89.7% sensitivity and 92.6% specificity. Conclusions: There are certain parameters used in order to predict recurrence with today's literature data.We think that because NLR is easy to use in clinics and inexpensive, and also has high sensitivity and specificity values, it has the potential to be one of the parameters used in order to predict biochemical recurrence in future.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.6
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• pp.2639-2642
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• 2012

Background: The patterns of gastric cancer recurrence vary across societies. We designed the current study in an attempt to evaluate and reveal the outbreak of the recurrence patterns of gastric cancer and also prediction of time to recurrence and its effected factors in Iran. Materials and Methods: This research was performed from March 2003 to February 2007. Demographic characteristics, clinical and pathological diagnosis and classification including pathologic stage, tumor grade, tumor site and tumor size in of patients with GC recurrent were collected from patients' data files. To evaluate of factors affected on the relapse of the GC patients, gender, age at diagnosis, treatment type and Hgb were included in the research. Data were analyzed using Kaplan-Meier and logistic regression models. Results: After treatment, 82 patients suffered recurrence, 42, 33 and 17 by the ends of first, second and third years. The mean ( SD) and median ( IQR) time to recurrence in patients with GC were 25.5 (20.6-30.1) and 21.5 (15.6-27.1) months, respectively. The results of multivariate analysis logistic regression showed that only pathologic stage, tumor grade and tumor site significantly affected the recurrence. Conclusions: We found that pathologic stage, tumor grade and tumor site significantly affect on the recurrence of GC which has a high positive prognostic value and might be functional for better follow-up and selecting the patients at risk. We also showed time to recurrence to be an important factor for follow-up of patients.

• Wind and Structures
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• v.39 no.2
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• pp.85-100
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• 2024

In light of extreme value distribution probability, an improved prediction method of the Recurrence Period Wind Speed (RPWS) is constructed considering wind direction, with the Equivalent Independent Wind Direction Number (EIWDN) introduced as a parameter variable. Firstly, taking the RPWS prediction of Beijing city as an example, the traditional Cook method is used to predict the RPWS of each wind direction based on the measured wind speed data in Beijing area. On basis of the results, the empirical formulae to determine the parameter variables are fitted to construct an improved expression of the non-exceedance probability of the RPWS. In this process, the statistical model of the optimal threshold is established, and thus the independent wind speed samples exceeding the threshold are extracted and fitted to follow the Generalized Pareto Distribution (GPD) model for analysis. In addition, the Extreme Value Type I (EVT I) distribution model is used to predict and analyze the RPWS. To verify its wide applicability, the improved method is further used in cities like Jinan, Nanjing, Wuxi, Shanghai and Shenzhen to predict and analyze the RPWS of each wind direction, and the prediction results are compared against those gained via the traditional Cook method and the whole direction. Results show that the 50-year RPWS results predicted by the improved method are basically consistent with those predicted by the traditional method, and the RPWS prediction values of most wind directions are within the envelope range of the whole wind direction prediction value. Compared with the traditional method, the improved method can readily predict the RPWS under different return periods through empirical formulae, and avoid the repeated operation process and some assumptions in the traditional Cook method, and then improve the efficiency of prediction. In addition, the improved RPWS prediction results corresponding to the GPD model are slightly larger than those of the EVT I distribution model.

• Journal of the Korean Geotechnical Society
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• v.25 no.10
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• pp.67-76
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• 2009

Statistical analysis was performed using a series of data on RMR, RMR* and crown settlements collected from sites of weathering rock tunnels in Korea. The crown settlements were predicted by recurrence analysis, exponential function, and artificial neural network (ANN) using collected in-situ data. The result of the prediction fitted well compared to the measured settlement in the order of ANN, exponential function, and recurrence analysis. The range of crown settlement predicted by recurrence analysis widely scattered and promised larger settlement than the measured. Also in all method, the predicted value by RMR well matched compared to the measured settlement predicted by RMR*.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.402-412
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• 2020

Objective: To evaluate the performance of predicting early recurrence using preoperative factors only in comparison with using both pre-/postoperative factors. Materials and Methods: We retrospectively reviewed 549 patients who had undergone curative resection for single hepatcellular carcinoma (HCC) within Milan criteria. Multivariable analysis was performed to identify pre-/postoperative high-risk factors of early recurrence after hepatic resection for HCC. Two prediction models for early HCC recurrence determined by stepwise variable selection methods based on Akaike information criterion were built, either based on preoperative factors alone or both pre-/postoperative factors. Area under the curve (AUC) for each receiver operating characteristic curve of the two models was calculated, and the two curves were compared for non-inferiority testing. The predictive models of early HCC recurrence were internally validated by bootstrap resampling method. Results: Multivariable analysis on preoperative factors alone identified aspartate aminotransferase/platelet ratio index (OR, 1.632; 95% CI, 1.056-2.522; p = 0.027), tumor size (OR, 1.025; 95% CI, 0.002-1.049; p = 0.031), arterial rim enhancement of the tumor (OR, 2.350; 95% CI, 1.297-4.260; p = 0.005), and presence of nonhypervascular hepatobiliary hypointense nodules (OR, 1.983; 95% CI, 1.049-3.750; p = 0.035) on gadoxetic acid-enhanced magnetic resonance imaging as significant factors. After adding postoperative histopathologic factors, presence of microvascular invasion (OR, 1.868; 95% CI, 1.155-3.022; p = 0.011) became an additional significant factor, while tumor size became insignificant (p = 0.119). Comparison of the AUCs of the two models showed that the prediction model built on preoperative factors alone was not inferior to that including both pre-/postoperative factors {AUC for preoperative factors only, 0.673 (95% confidence interval [CI], 0.623-0.723) vs. AUC after adding postoperative factors, 0.691 (95% CI, 0.639-0.744); p = 0.0013}. Bootstrap resampling method showed that both the models were valid. Conclusion: Risk stratification solely based on preoperative imaging and laboratory factors was not inferior to that based on postoperative histopathologic risk factors in predicting early recurrence after curative resection in within Milan criteria single HCC patients.

• Korean Circulation Journal
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• v.53 no.10
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• pp.677-689
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• 2023

Background and Objectives: There is limited evidence regarding machine-learning prediction for the recurrence of atrial fibrillation (AF) after electrical cardioversion (ECV). This study aimed to predict the recurrence of AF after ECV using machine learning of clinical features and electrocardiograms (ECGs) in persistent AF patients. Methods: We analyzed patients who underwent successful ECV for persistent AF. Machine learning was designed to predict patients with 1-month recurrence. Individual 12-lead ECGs were collected before and after ECV. Various clinical features were collected and trained the extreme gradient boost (XGBoost)-based model. Ten-fold cross-validation was used to evaluate the performance of the model. The performance was compared to the C-statistics of the selected clinical features. Results: Among 718 patients (mean age 63.5±9.3 years, men 78.8%), AF recurred in 435 (60.6%) patients after 1 month. With the XGBoost-based model, the areas under the receiver operating characteristic curves (AUROCs) were 0.57, 0.60, and 0.63 if the model was trained by clinical features, ECGs, and both (the final model), respectively. For the final model, the sensitivity, specificity, and F1-score were 84.7%, 28.2%, and 0.73, respectively. Although the AF duration showed the best predictive performance (AUROC, 0.58) among the clinical features, it was significantly lower than that of the final machine-learning model (p<0.001). Additional training of extended monitoring data of 15-minute single-lead ECG and photoplethysmography in available patients (n=261) did not significantly improve the model's performance. Conclusions: Machine learning showed modest performance in predicting AF recurrence after ECV in persistent AF patients, warranting further validation studies.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.2
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• pp.158-165
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• 2023

Backgrounds/Aims: Within two years of surgery, 70% of resected intrahepatic cholangiocarcinoma (iCCA) recur. Better biomarkers are needed to identify those at risk of "early recurrence" (ER). In this study, we defined ER and investigated whether preoperative neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic-inflammatory index were prognostic of both overall relapse and ER after curative hepatectomy for iCCA. Methods: A retrospective cohort of patients who underwent curative-intent hepatectomy for iCCA between 2005 and 2017 were created. The cut-off timepoint for the ER of iCCA was estimated using a piecewise linear regression model. Univariable analyses of recurrence were conducted for the overall, early, and late recurrence periods. For the early and late recurrence periods, multivariable Cox regression with time-varying regression coefficient analysis was used. Results: A total of 113 patients were included in this study. ER was defined as recurrence within 12 months of a curative resection. Among the included patients, 38.1% experienced ER. In the univariable model, a higher preoperative NLR (> 4.3) was significantly associated with an increased risk of recurrence overall and in the first 12 months after curative surgery. In the multivariable model, a higher NLR was associated with a higher recurrence rate overall and in the ER period (≤ 12 months), but not in the late recurrence period. Conclusions: Preoperative NLR was prognostic of both overall recurrence and ER after curative iCCA resection. NLR is easily obtained before and after surgery and should be integrated into ER prediction tools to guide preoperative treatments and intensify postoperative follow-up.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.17
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• pp.7463-7466
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• 2015

Aims: To analyse the predictors of recurrence, disease free survival and overall survival in cases with endometrial cancer. Materials and Methods: A total of 152 women diagnosed with endometrial cancer were screened using a prospectively collected database including age, smoking history, menopausal status, body mass index, CA125, systemic disorders, tumor histology, tumor grade, lymphovascular space invasion, tumor diameter, cervical involvement, myometrial invasion, adnexal metastases, positive cytology, serosal involvement, other pelvic metastases, type of surgery, fertility sparing approach to assess their ability to predict recurrence, disease free survival and overall survival. Results: In ROC analyses tumor diameter was a significant predictor of recurrence (AUC:0.771, P<0.001). The optimal cut off value was 3.75 with 82% sensitivity and 63% specificity. In correlation analyses tumor grade (r=0.267, p=0.001), tumor diameter (r=0.297, p<0.001) and the serosal involvement (r=0.464, p<0.001) were found to significantly correlate with the recurrence. In Cox regression analyses when some different combinations of variables included in the model which are found to be significantly associated with the presence of recurrence, tumor diameter was found to be a significant confounder for disease free survival (OR=1.2(95 CI,1.016-1.394, P=0.031). On Cox regression for overall survival only serosal involvement was found to be a significant predictor (OR=20.8 (95 % CI 2.4-179.2, P=0.006). In univariate analysis of tumor diameter > 3.75 cm and the recurrence, there was 14 (21.9 %) cases with recurrence in group with high tumor diameter where as only 3 (3.4 %) cases group with smaller tumor size (Odds ratio:7.9 (95 %CI 2.2-28.9, p<0.001). Conclusions: Although most of the significantly correlated variables are part of the FIGO staging, tumor diameter was also found to be predictor for recurrence with higher values than generally accepted.

• Korean Journal of Radiology
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• v.24 no.7
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• pp.660-667
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• 2023