Parametric Methods for Regression Model Fitting and Identification of Prognostic Factors

2003 ◽  
pp. 256-297
Keyword(s):  
Prognostic Factors ◽  
Regression Model ◽  
Model Fitting ◽  
Parametric Methods

scholarly journals Prognostic Factors Influencing Outcomes of High Tibial Osteotomy in The Varus Knee: The Role of The Deformity

2020 ◽  
Vol 8 (7_suppl6) ◽  
pp. 2325967120S0046
Author(s):  
Carola Pilone ◽  
Federico Verdone ◽  
Roberto Rossi ◽  
Davide Bonasia ◽  
Federica Rosso
Keyword(s):  
Prognostic Factors ◽  
Regression Model ◽  
High Tibial Osteotomy ◽  
Womac Score ◽  
Tibial Osteotomy ◽  
Varus Knee ◽  
Inclusion Criteria ◽  
Opening Wedge

Objectives: High Tibial Osteotomy (HTO) is widely performed to treat early arthiritis in the varus knee. The aim of this prospective study is to evaluate different prognostic factors affecting the outcomes of HTO and, with special attention to the role of the site of deformity. Methods: 231 Opening Wedge HTO (OWHTO) were performed in 202 patients and included in the study. Inclusion criteria were: 1) age > 18 years, 2) no major associated procedures (i.e. ACL reconstruction, major cartilage procedure, 3) only OWHTO, 4) pre-operative complete clinical and radiological evaluation available. Patients were evaluated with (1) the Knee Society score (KSS), (2) the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, (3) another self-evaluation scale, (4) long-leg radiographs, and (5) plain radiographs. On the x-ray different angles were evaluated, including Join Line Congruence Angle. Furthermore, the location of deformity was established. Three main outcomes were identified: Indication to Total Knee Arthroplasty (TKA), KSS poor or fair and WOMAC < 76 points), and different prognostic factors were identified (Fig. 1). All the variables were firstly tested in a single regression model to evaluate the association with each outcome. All the variables with p<0.1 were re-tested in a multiple regression model. Results: 32 patients were lost to follow-up and 31 patients did not meet the inclusion criteria, leaving 139 patients (156 OWHTOs) for the study. The average age was 52.9 ± 9.6 years, and the average follow-up was 97.7 ± 42.8 months. Post-operatively there was a significant improvement in both the KSS and WOMAC score compared to the pre-operative period (p<0.0001). The only variable related to TKA indication was a pre-operative JLCA ≥5° (OR=24.3, p=0.0483). Conversely, different variables were related to a worse KSS, including pre-operative BMI >30 Kg/m2 (OR=78.9, p=0.0028), pre-operative ROM <120° of flexion (OR=40.8, p=0.0421), pre-operative mLDFA ≥91° (OR=36,6,p=0.0401) and femoral pre-operative CORA ≥3° of varus (OR=39,9 p=0.0269). Furthermore, a pre-operative BMI >30 Kg/m2 (OR=29,5, p=0.0314) was associated to a worse WOMAC score. Conversely, patients with a pre-operative mMPTA ≤84° had lower risk to obtain a worse KSS oe WOMAC score (respectively OR= 0,2 p=0.0364 and OR=0,3 p=0.0071). The cumulative survivorship was calculated with the Kaplan-Meier method, and it resulted equal to 98.6% at 5 years and decreased to 85.5% at 10 years. Conclusion: OWHTO is a good treatment for early arthritis in the varus knee if the correct indications are applied. The outcomes can be considered good, with 85% of 10-year survivorship. It is mandatory to correctly address the location of the deformity, because the presence of a femoral varus deformity is related to worse outcomes. Similarly, presence of a pre-operative JLCA ≥5° is the only factor associated to TKA indication. [Table: see text]

The ratio of negative lymph node count inside the thoracic cavity to the positive lymph count is a prognostic factor in esophageal squamous cell carcinoma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e15545-e15545
Author(s):  
Jinling Zhang ◽  
Xueyuan Heng ◽  
Fengyuan Che
Keyword(s):  
Squamous Cell Carcinoma ◽  
Prognostic Factors ◽  
Prognostic Factor ◽  
Esophageal Squamous Cell Carcinoma ◽  
Lymph Nodes ◽  
Regression Model ◽  
Cell Carcinoma ◽  
Cox Regression ◽  
Thoracic Cavity ◽  
Rank Tests

e15545 Background: It was reported that the number of positive lymph nodes (PLN) and negative lymph nodes (NLN) resected in lymphadenectomy were both independent prognostic factors in esophageal squamous cell carcinoma (ESCC). However, it is unclear which kind of combination of them would have a stronger impact on the prognosis of the ESCC patients. Methods: A total of 229 patients with ESCC were retrospectively investigated. The Cox Proportional Hazards Model was used to investigate the relationship between the PLN or NLN and the overall survival of patients. Survival analysis was performed using the Kaplan-Meier method, and the survival difference between sub-groups were explored with log-rank tests. The cut-off number of the ratio of NLN count to PLN count resulted in an improved outcome for patients was investigated by a series of log-rank tests. Results: The numbers of PLN and NLN were both independent prognostic factors, supported by the results of Cox regression model analysis (hazard ratio [HR], 1.12, P < 0.001 and HR, 0.97, P = 0.024, respectively).The survival differences among sub-groups from N0 to N3 stage were statistically significant (P < 0.001). Analysis using a Cox regression model revealed that the number of NLN inside the thoracic cavity had a stronger impact on the prognosis compared to the number of NLN outside the thoracic cavity (HR,0.959, P = 0.042 vs.HR, 0.973, P = 0.179). As a combination analysis consisting of the number of PLN and NLN, the log-rank test result demonstrated that patients with the ratio of NLN count inside thoracic cavity to the PLN count less than 8 could achieve a better survival. Conclusions: The ratio of NLN count inside thoracic cavity to the PLN count was a independent prognostic factor.

scholarly journals Expression of lncRNAs Associated with GPCRs and Clinical Prognosis in GBM

2021 ◽  
Author(s):  
Hao Wang ◽  
Yaohui Wang ◽  
wei xiang
Keyword(s):  
Prognostic Factors ◽  
Regression Model ◽  
Multiple Regression ◽  
G Protein ◽  
Risk Score ◽  
Univariate Analysis ◽  
Multiple Regression Model ◽  
G Protein Coupled Receptors ◽  
Clinical Prognosis ◽  
G Protein Coupled

Abstract Background: Glioblastoma (GBM) is a primary malignant tumor of the central nervous system with a poor prognosis. Long non-coding RNAs (lncRNAs) play a variety of key regulatory roles in a variety of biological processes, and have an important influence on the occurrence and development of tumors by regulating the expression of target genes. However, their role in the prognosis of GBM is still lacking in accurate prognostic markers.This study aims to establish an effective lncRNAs model to evaluate the prognosis of GBM.Methods: We used data of mRNA, lncRNA and clinical follow-up from The Cancer Genome Atlas (TCGA) to conduct univariate analysis, clustering analysis, coding gene difference analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Ontology (GO) analysis for GBM patients. lncRNAs that are closely related to the survival and prognosis of GBM were found and a multiple regression model was constructed to calculate the risk score of the samples, so as to accurately predict the clinical prognosis of GBM patients.Results: Through multiple systematic analysis, we found 5 lncRNAs that are closely related to the survival and prognosis of GBM, and these 5 lncRNAs can be used as independent prognostic factors. Through GO enrichment analysis and KEGG pathway analysis, we found that there is a close relationship between GBM and G protein coupled receptors. Therefore, 93 mRNAs associated with G-protein-coupled receptors and 5 lncRNAs associated with independent prognostic factors were selected to calculate the correlation, respectively. In other words, a tumor-specific lncRNAs/mRNAs co-expression network was constructed through biological prediction based on correlation analysis. The results showed that lncRNAs and mRNAs interregulated very closely in GBM patients. In addition, we also constructed a multiple regression model with these 5 lncRNAs which was able to calculate the risk score of each sample to accurately predict the clinical prognosis of GBM patients.Conclusion: Our study found lncRNAs independently were related to the prognosis of GBM, and successfully constructed a multiple regression model related to lncRNAs, providing a new perspective for better evaluation of the role of lncRNAs in the clinical prognosis of GBM.

scholarly journals A Nomogram Predicting Survival in Patients with Breast Ductal Carcinoma in Situ with Microinvasion

2021 ◽  
Author(s):  
Yi-Zi Zheng ◽  
Hong-Bin Qin ◽  
Zi-Zheng Li ◽  
He-Sheng Jiang ◽  
Greg Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Regression Model ◽  
Cancer Patients ◽  
Ductal Carcinoma In Situ ◽  
Carcinoma In Situ ◽  
Ductal Carcinoma ◽  
Multivariate Logistic Regression Model ◽  
Breast Cancer Patients

Abstract Background: Ductal carcinoma in situ with microinvasion (DCISM) can be challenging to balance the risks of overtreatment versus undertreatment. We aim to identify prognostic factors in patients with DCISM and construct a nomogram to predict breast cancer-specific survival (BCSS).Methods: Women diagnosed with DCISM were selected from the Surveillance, Epidemiology and End Results database (1998-2015). Clinical variables and tumor characteristics were evaluated and Cox proportional-hazards regression model was performed. A nomogram was con­structed from the multivariate logistic regression model to combine all the prognostic factors to predict the prognosis of DCISM patients at 5 years, 10 years, and 15 years. Results: We identified 5,438 total eligible breast cancer patients with a median and max survival time of 78 and 227 months, respectively. Here, patients with poorer survival outcomes were those diagnosed between 1988-2001, African-American race, under 40 years of age, higher tumor N stage, progesterone receptor-negative tumor, and received no surgery (all P < 0.05). The nomogram was constructed by the seven variables and passed the calibration and validation steps. The area under the receiver operating characteristic (ROC) curve (AUC) of both the training set and the validating set (5-year AUC: 0.77 and 0.88, 10-year AUC: 0.75 and 0.73, 15-year AUC: 0.72 and 0.65) demonstrated excellent reliability and robust performance.Conclusion: Our current study is the first to construct nomograms of patients with DCISM which could help physicians identify breast cancer patients that more likely to benefit from more intensive treatment and follow-up.

scholarly journals Salivary Metabolomics for Prognosis of Oral Squamous Cell Carcinoma

2022 ◽  
Vol 11 ◽  
Author(s):  
Shigeo Ishikawa ◽  
Masahiro Sugimoto ◽  
Tsuneo Konta ◽  
Kenichiro Kitabatake ◽  
Shohei Ueda ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Prognostic Factors ◽  
Prognostic Factor ◽  
Oral Squamous Cell Carcinoma ◽  
Regression Model ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Validation Group ◽  
Cox Proportional Hazards Regression ◽  
Proportional Hazards Regression

This study aimed to identify salivary metabolomic biomarkers for predicting the prognosis of oral squamous cell carcinoma (OSCC) based on comprehensive metabolomic analyses. Quantified metabolomics data of unstimulated saliva samples collected from patients with OSCC (n = 72) were randomly divided into the training (n = 35) and validation groups (n = 37). The training data were used to develop a Cox proportional hazards regression model for identifying significant metabolites as prognostic factors for overall survival (OS) and disease-free survival. Moreover, the validation group was used to develop another Cox proportional hazards regression model using the previously identified metabolites. There were no significant between-group differences in the participants’ characteristics, including age, sex, and the median follow-up periods (55 months [range: 3–100] vs. 43 months [range: 0–97]). The concentrations of 5-hydroxylysine (p = 0.009) and 3-methylhistidine (p = 0.012) were identified as significant prognostic factors for OS in the training group. Among them, the concentration of 3-methylhistidine was a significant prognostic factor for OS in the validation group (p = 0.048). Our findings revealed that salivary 3-methylhistidine is a prognostic factor for OS in patients with OSCC.

Coauthorship Trends in the Leading Radiological Journals

1993 ◽  
Vol 34 (4) ◽  
pp. 316-320 ◽  
Author(s):  
S. Mussurakis
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Case Reports ◽  
Model Fitting ◽  
Limited Attention ◽  
Multiple Authorship ◽  
Excessive Pressure ◽  
Number Of Authors

Coauthorship trends have received limited attention in radiology. This paper examines the author inflation phenomenon in 12 leading radiological peer-reviewed journals and seeks explanations for the rise in multiple authorship. MEDLINE was searched from 1966 through 1991, and the indexed scientific material (67 758 articles) of the eligible core journals was analysed. During this 26-year period the average number of authors per original article (including case reports) doubled, increasing from 2.2 in 1966 to 4.4 in 1991. The linear regression model fitting the data was strongly significant, although since the late 1980s the rate of the coauthorship rise started to decrease. There was considerable variation in coauthorship patterns between journals. Other factors, such as the contributors' country, were also noted to influence coauthorship. The increasing complexity of radiological research explains in part the rise in multiple-author papers, but the main cause must undoubtedly be the excessive pressure to publish. Among the topics discussed are the incentives that stimulate radiologists to write, the dynamics of coauthorship, and the proposals made to standardize the requirements for authorship and to shift the emphasis from quantity of publication to quality.

scholarly journals Modelling Hypertension and Risk Factors among Adults Using Ordinal Logistics Regression Model

2020 ◽  
Author(s):  
Monday Osagie Adenomon ◽  
Daniel Owoicholofu John
Keyword(s):  
Risk Factors ◽  
Regression Model ◽  
Goodness Of Fit ◽  
Adult Population ◽  
Model Fitting ◽  
Data Sets ◽  
Intervention Programme ◽  
Rate Test ◽  
And Gender ◽  
One Year

There is high prevalence of hypertension and is rapidly increasing around the world, despite the intervention programme implemented, this study aimed at estimating the prevalence rate, test of association between hypertension and risk factors and model hypertension rate. Data used was obtained from the health record of Federal Medical Centre, Keffi from January 2016 &ndash; January 2019. Ordinal logistic regression model was used; Model Fitting Information, Goodness-of-Fit, Pseudo R-Square and Test of Parallel Lines are fitted to the data sets to test the accuracy and correctness of the model. The results indicated that the overall prevalence of hypertension rate is high at 36.4%, among the adult population, body mass index and gender are statistically significant, and Age is not significant in the study. Individuals that are overweight are more likely to be hypertensive compare to other weights. At age 40 &ndash; 49 years which have the highest rate of 26.5% and the odd ratio is 0.75 compared to others. One year increase in age 30 &ndash; 39, the cumulative odd of being hypertensive is 0.91 while other independent variables are held constant. The odd ratio of female being hypertensive is 0.85, therefore the females are more likely to be hypertensive with 54.4% compared to the males at 45.6% . There is no presence of multicolinearity among the variables and Logit models were formulated to calculate probabilities of the various possible outcomes.

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