scholarly journals Predictors for development of oxaliplatin-induced peripheral neuropathy in cancer patients as determined by ordered logistic regression analysis

2021 ◽  
Author(s):  
Yuko Kanbayashi ◽  
Takeshi Ishikawa ◽  
Yoshiaki Kuriu ◽  
Eigo Otsuji ◽  
Koichi Takayama
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Peripheral Neuropathy ◽  
Cancer Patients ◽  
Logistic Regression Analysis ◽  
Roc Analysis ◽  
Area Under The Curve ◽  
Ordered Logistic Regression ◽  
Number Of Cycles ◽  
Significant Factors

Abstract This retrospective study aimed to identify predictors for the development of oxaliplatin-induced peripheral neuropathy (OXAIPN). Between January 2017 and March 2021, a total 322 cancer patients at our hospital who were receiving oxaliplatin were enrolled. For the regression analysis of factors associated with oxaliplatin-induced peripheral neuropathy, variables were extracted manually from medical charts. The level of OXAIPN was evaluated using the National Cancer Institute’s Common Terminology Criteria for Adverse Events (version 5). Multivariate ordered logistic regression analysis was performed to identify predictors for the development of OXAIPN. Optimal cut-off thresholds were determined using receiver operating characteristic (ROC) analysis. Values of P < 0.05 (2-tailed) were considered significant. Significant factors identified included body mass index (BMI) (odds ratio [OR] = 1.06, 95% confidence interval [CI] = 1.00–1.12; P = 0.046), number of cycles (OR = 1.09, 95%CI = 1.05–1.14; P < 0.0001), S-1 plus oxaliplatin (SOX) regimen (OR = 0.54, 95%CI = 0.32–0.92; P = 0.023), concomitant use of proton pump inhibitors (PPIs) (OR = 1.64, 95%CI = 1.05–2.58; P = 0.031) and concomitant use of analgesic adjuvant (OR = 3.30, 95%CI = 1.09–9.97; P = 0.035). ROC analysis revealed that peripheral neuropathy (grade 2 or higher) was more likely to occur with ≥8 cycles, with 66.3% sensitivity and 56.5% specificity (area under the curve [AUC] = 0.65), and BMI ≥20.5 kg/m2, with 63.3% sensitivity and 47.8% specificity (AUC = 0.54). In conclusion, BMI, number of cycles, SOX regimen, concomitant use of PPIs and concomitant use of analgesic drugs were identified as significant predictors for the development of OXAIPN.

scholarly journals Predictors for Development of Oxaliplatin-induced Peripheral Neuropathy in Cancer Patients as Determined by Ordered Logistic Regression Analysis

2021 ◽  
Author(s):  
Yuko Kanbayashi ◽  
Takeshi Ishikawa ◽  
Yoshiaki Kuriu ◽  
Yusuke Tabuchi ◽  
Eigo Otsuji ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Peripheral Neuropathy ◽  
Cancer Patients ◽  
Logistic Regression Analysis ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Ordered Logistic Regression ◽  
Number Of Cycles ◽  
Significant Factors

Abstract Purpose This retrospective study aimed to identify predictors for the development of oxaliplatin-induced peripheral neuropathy (OXAIPN). Methods Between January 2017 and March 2021, a total 322 cancer patients at our hospital who were receiving oxaliplatin were enrolled. For the regression analysis of factors associated with oxaliplatin-induced peripheral neuropathy, variables were extracted manually from medical charts. The level of OXAIPN was evaluated using the National Cancer Institute’s Common Terminology Criteria for Adverse Events (version 5). Multivariate ordered logistic regression analysis was performed to identify predictors for the development of OXAIPN. Optimal cut-off thresholds were determined using receiver operating characteristic (ROC) analysis. Values of P <0.05 (2-tailed) were considered significant. Results Significant factors identified included body mass index (BMI) (odds ratio [OR] = 1.06, 95% confidence interval [CI] = 1.00–1.12; P = 0.046), number of cycles (OR = 1.09, 95%CI = 1.05–1.14; P <0.0001), S-1 plus oxaliplatin (SOX) regimen (OR = 0.54, 95%CI = 0.32–0.92; P = 0.023), concomitant use of proton pump inhibitors (PPIs) (OR = 1.64, 95%CI = 1.05–2.58; P = 0.031) and concomitant use of analgesic adjuvant (OR = 3.30, 95%CI = 1.09–9.97; P = 0.035). Conclusion BMI, number of cycles, SOX regimen, concomitant use of PPIs and concomitant use of analgesic drugs were identified as significant predictors for the development of OXAIPN.

scholarly journals Predictors for development of palbociclib-induced neutropenia in breast cancer patients as determined by ordered logistic regression analysis

2021 ◽  
Author(s):  
Yuko Kanbayashi ◽  
Koichi Sakaguchi ◽  
Takeshi Ishikawa ◽  
Koichi Takayama ◽  
Tetsuya Taguchi
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Logistic Regression Analysis ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Breast Cancer Patients ◽  
Ordered Logistic Regression ◽  
Significant Factors

Abstract This retrospective study aimed to identify predictors for the development of palbociclib-induced neutropenia. This study retrospectively analysed 78 breast cancer patients who had received palbociclib at our hospital between January 2018 and May 2020. For the regression analysis of factors associated with palbociclib-induced neutropenia, variables were extracted manually from medical charts. The level of palbociclib-induced neutropenia was evaluated using the National Cancer Institute’s Common Terminology Criteria for Adverse Events (version 5). Multivariate ordered logistic regression analysis was performed to identify predictors for the development of neutropenia. Optimal cut-off thresholds were determined using receiver operating characteristic (ROC) analysis. Values of P < 0.05 (2-tailed) were considered significant. Significant factors identified included concomitant use of statin (odds ratio [OR] = 0.104, 95% confidence interval [CI] = 0.018–0.598; P = 0.011] and body mass index (BMI) (OR = 1.118, 95% CI = 1.007–1.241; P = 0.037). ROC analysis revealed that neutropenia (grade 4) was more likely to occur with a BMI ≥ 22.3 kg/m2. In conclusion, no concomitant use of statins and high BMI were identified as significant predictors for the development of palbociclib-induced neutropenia.

scholarly journals Predictors for development of palbociclib-induced neutropenia in breast cancer patients as determined by ordered logistic regression analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuko Kanbayashi ◽  
Koichi Sakaguchi ◽  
Takeshi Ishikawa ◽  
Koichi Takayama ◽  
Tetsuya Taguchi
Keyword(s):  
Breast Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Logistic Regression Analysis ◽  
Roc Analysis ◽  
Operating Characteristic ◽  
Breast Cancer Patients ◽  
Ordered Logistic Regression ◽  
Significant Factors

AbstractThis retrospective study aimed to identify predictors for the development of palbociclib-induced neutropenia. This study retrospectively analysed 78 breast cancer patients who had received palbociclib at our hospital between January 2018 and May 2020. For the regression analysis of factors associated with palbociclib-induced neutropenia, variables were extracted manually from medical charts. The level of palbociclib-induced neutropenia was evaluated using the National Cancer Institute’s Common Terminology Criteria for Adverse Events (version 5). Multivariate ordered logistic regression analysis was performed to identify predictors for the development of neutropenia. Optimal cut-off thresholds were determined using receiver operating characteristic (ROC) analysis. Values of P < 0.05 (2-tailed) were considered significant. Significant factors identified included concomitant use of statin (odds ratio [OR] = 0.104, 95% confidence interval [CI] = 0.018–0.598; P = 0.011) and body mass index (BMI) (OR = 1.118, 95% CI = 1.007–1.241; P = 0.037). ROC analysis revealed that neutropenia (grade 4) was more likely to occur with a BMI ≥ 22.3 kg/m2. In conclusion, no concomitant use of statins and high BMI were identified as significant predictors for the development of palbociclib-induced neutropenia.

scholarly journals Predictors for development of denosumab-induced hypocalcaemia in cancer patients with bone metastases determined by ordered logistic regression analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuko Kanbayashi ◽  
Koichi Sakaguchi ◽  
Fumiya Hongo ◽  
Takeshi Ishikawa ◽  
Yusuke Tabuchi ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cancer Patients ◽  
Serum Calcium ◽  
Logistic Regression Analysis ◽  
Advanced Cancer Patients ◽  
Roc Curve Analysis ◽  
Ordered Logistic Regression ◽  
Pre Treatment ◽  
Clinical Records

AbstractThis retrospective study was undertaken to identify predictors for the development of hypocalcaemia even with prophylactic administration of calcium and vitamin D, and to help guide future strategies to improve the safety, efficacy, and QOL of patients receiving denosumab. Between January 2016 and February 2020, a total of 327 advanced cancer patients at our hospital who were receiving denosumab were enrolled. Variables associated with the development of hypocalcaemia were extracted from the clinical records. The level of hypocalcaemia was evaluated using CTCAE version 5. Multivariate ordered logistic regression analysis was performed to identify predictors for the development of hypocalcaemia. Optimal cut off thresholds were determined using ROC analysis. Values of P < 0.05 (2-tailed) were considered significant. 54 patients have developed hypocalcemia (≥ Grade 1). Significant factors identified included concomitant use of vonoprazan [odds ratio (OR) = 3.74, 95% confidence interval (CI) 1.14–12.26; P = 0.030], dexamethasone (OR = 2.45, 95%CI 1.14–5.42; P = 0.022), pre-treatment levels of serum calcium (OR = 0.27, 95%CI 0.13–0.54; P < 0.001), ALP/100 (OR = 1.04, 95%CI 1.01–1.07; P = 0.003), and haemoglobin (OR = 0.79, 95%CI 0.68–0.93; P = 0.004). ROC curve analysis revealed that the threshold for pre-treatment levels of serum calcium was ≤ 9.3 mg/dL, ALP was ≥ 457 U/L, and haemoglobin was ≤ 10.4 g/dL. In conclusion, concomitant use of vonoprazan or dexamethasone, and pre-treatment levels of serum calcium (low), ALP (high) and haemoglobin (low) were identified as significant predictors for the development of denosumab-induced hypocalcaemia.

scholarly journals Association between Carotid Artery Calcification and Periodontal Disease Progression in Japanese Men and Women: A Cross-Sectional Study

2020 ◽  
Vol 9 (10) ◽  
pp. 3365
Author(s):  
Nanae Dewake ◽  
Yasuaki Ishioka ◽  
Keiichi Uchida ◽  
Akira Taguchi ◽  
Yukihito Higashi ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Carotid Artery ◽  
Logistic Regression Analysis ◽  
Roc Analysis ◽  
Multivariate Logistic Regression Analysis ◽  
Multivariate Logistic Regression ◽  
Panoramic Radiographs ◽  
Carotid Artery Calcification ◽  
Univariate Analyses

Objective: To evaluate the association between alveolar bone loss (ABL) detected on panoramic radiographs and carotid artery calcification (CAC) detected on computed tomography (CT). Methods: The study subjects included 295 patients (mean age ± SD: 64.6 ± 11.8 years) who visited the Matsumoto Dental University Hospital. The rate of ABL and the number of present teeth were measured on panoramic radiographs. Univariate analyses with t-tests and chi-squared tests were performed to evaluate the differences in age, gender, history of diseases, number of present teeth, and the ABL between subjects, with and without CAC. Moreover, multivariate logistic regression analysis, with forward selection and receiver operating characteristic curve (ROC) analysis, was performed. Results: The number of subjects without and with CAC was 174 and 121, respectively. Univariate analyses revealed that CAC was significantly associated with age, hypertension, osteoporosis, number of present teeth, and ABL. Multivariate logistic regression analysis adjusted for covariates revealed that the presence of CAC was significantly associated with ABL (OR = 1.233, 95% CI = 1.167–1.303). In the ROC analysis for predicting the presence of CAC, the the area under the ROC curve was the highest at 0.932 (95% CI = 0.904–0.960) for ABL, which was significant. Conclusions: Our results suggest that the measurement of ABL on panoramic radiographs may be an effective approach to identifying patients with an increased risk of CAC.

Trust in police as an influencing factor on trust in government: 2SLS analysis using perception of safety

2020 ◽  
Vol 43 (4) ◽  
pp. 541-558
Author(s):  
Jisu Jeong ◽  
Seunghui Han
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Trust In Government ◽  
Content Type ◽  
Perception Of Safety ◽  
Ordered Logistic Regression ◽  
The Impact ◽  
The Relationship ◽  
Trust In Police

PurposeCitizen trust in police is important in terms of citizen consent to government policies and of police achieving their organizational goals. In the previous study, improvements in police policy, organizational operation and policing activities were developed to clarify which factors influence trust in police and how trust can be improved. This research raises the question, would changes in trust in police have an impact on trust in government? In this paper, this research question is discussed theoretically and the causal relationship analyzed empirically by applying OLS, ordered logistic, 2SLS and logistic regressions.Design/methodology/approachThe basic analysis methods are to apply the OLS and the ordered logistic regression. OLS regression analysis is an analytical method that minimizes an error range of a regression line. The assumptions for OLS are: linearity, independence, equilibrium, extrapolation and multicollinearity issues. These problems were statistically verified and analyzed, in order to confirm the robustness of the analysis results by comparing the results of the ordered logistic regression because of the sequence characteristic of the dependent variable. The data to be used in this study is the Asia Barometer Survey in 2013.FindingsTrust in police and citizen perception of safety are analyzed as important factors to increase trust in the government. The effects of trust in police are more significant than the effects of control variables, and the direction and strength of the results are stable. The effect of trust in police on trust in government is strengthened by the perception of safety (IV). In addition, OLS, ordered logistic regression analysis, which analyzed trust in central government and local government, and logistic regression analysis categorized by trust and distrust show the stability.Research limitations/implicationsThis paper has implications in terms of theoretical and empirical analysis of the relationship between trust in police and trust in government. In addition, the impact of perception of safety on trust in police can be provided to police officers, policymakers and governors who are seeking to increase trust in government. This paper is also meaningful in that it is the microscopic research based on the citizens' survey. One of the limitations of macroscopic research is that it does not consider the individual perceptions of citizens.Practical implicationsThe results of this paper can confirm the relationship of the virtuous cycle, which is perception of safety – trust in police – trust in government. The police will need to provide security services to improve citizens' perception of safety and make great efforts to create safer communities and society. Trust in police formed through this process can be an important component of trust in government. By making citizens feel safer and achieving trust in police, ultimately, trust in government will be improved.Originality/valueThe police perform one of the essential roles of government and are one of the major components of trust in government, but the police sector has been neglected compared to the roles of the economic and political sectors. These influences of macro factors are too abstract to allow specific policy directions to be suggested. If we consider trust in police, and factors that can improve trust in government, we can suggest practical policy alternatives.

Predictive Factors for Postherpetic Neuralgia Using Ordered Logistic Regression Analysis

2012 ◽  
Vol 28 (8) ◽  
pp. 712-714 ◽  
Author(s):  
Yuko Kanbayashi ◽  
Keiko Onishi ◽  
Keita Fukazawa ◽  
Kousuke Okamoto ◽  
Hiroshi Ueno ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Predictive Factors ◽  
Postherpetic Neuralgia ◽  
Ordered Logistic Regression
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