scholarly journals Multivariate analysis of prognostic factors in patients with nodular melanoma

2021 ◽  
Author(s):  
L. Susok ◽  
M. Stücker ◽  
F. G. Bechara ◽  
E. Stockfleth ◽  
T. Gambichler
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Tumor Thickness ◽  
Rank Test ◽  
Disease Relapse ◽  
Nodular Melanoma ◽  
Male Sex

Abstract Purpose Nodular melanoma (NM) is associated with worse disease outcome when compared to superficial spreading melanoma (SSM). We aimed to perform a single-center analysis of prognostic factors in patients with NM and compare the data with SSM patients. Methods We studied 228 patients with NN and 396 patients with SSM. Patients with in situ melanomas or stage IV at diagnosis were not included in the study. Data were analyzed using the Mann–Whitney test, Chi-square test, Kaplan–Meier curves including the log-rank test, and logistic regression model. Results When compared to patients with SSM, patients with NM had less likely lower Clark level, higher tumor thickness, less likely tumor regression, more often ulcerated tumors, and less likely a history of precursor lesions such as a nevus. Within a 5-year follow-up we observed significantly more disease relapses and deaths in NM patients than in SSM patients. On multivariate analysis, disease relapse in NM patients was independently predicted by tumor thickness and positive SLNB, whereas melanoma-specific death of NM patients was independently predicted by male sex and tumor thickness. Histologic regression also remained in the logistic regression model as a significant independent negative predictor of NM death. Conclusions We did not observe that NM subtype was per se a significant independent predictor for disease relapse or melanoma-specific death. Among the well-known prognostic factors such as tumor thickness and male sex, NM is also associated with other unfavorable factors such as absence of regression.

scholarly journals Multivariate Analysis of Prognostic Factors in Patients With Nodular Melanoma

2021 ◽  
Author(s):  
Laura Susok ◽  
Markus Stücker ◽  
Falk G. Bechara ◽  
Eggert Stockfleth ◽  
Thilo Gambichler
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Tumor Thickness ◽  
Rank Test ◽  
Disease Relapse ◽  
Nodular Melanoma ◽  
Male Sex

Abstract Purpose Nodular melanoma (NM) is associated with worse disease outcome when compared to superficial spreading melanoma (SSM). We aimed to perform a single center analysis of prognostic factors in patients with NM and compare the data with SSM patients. Methods We studied 228 patients with NN and 396 patients with SSM. Patients with in-situ melanomas or stage IV at diagnosis were not included in the study. Data were analyzed using the Mann-Whitney test, Chi² test, Kaplan-Meier curves including the log-rank test, and logistic regression model.Results When compared to patients with SSM, patients with NM had less likely lower Clark level, higher tumor thickness, less likely tumor regression, more often ulcerated tumors, and less likely a history of precursor lesions such as a nevus. Within a 5-year follow-up we observed significantly more disease relapses and deaths in NM patients than in SSM patients. On multivariate analysis, disease relapse in NM patients was independently predicted by tumor thickness and positive SLNB, whereas melanom-specific death of NM patients was independently predicted by male sex and tumor thickness. Histologic regression also remained in the logistic regression model as a significant independent negative predictor of NM death.Conclusions We did not observe that NM subtype was a significant independent predictor for disease relapse or melanoma-specific death. Among the well-known prognostic factors such as tumor thickness and male sex, NM is also associated with other unfavorable factors such as absence of regression.

scholarly journals A comprehensive, contemporary assessment of the association between hepatosteatosis and coronary artery calcium scoring

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
T Heseltine ◽  
SW Murray ◽  
RL Jones ◽  
M Fisher ◽  
B Ruzsics
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Coronary Artery ◽  
Regression Model ◽  
Coronary Artery Calcium ◽  
Logistic Regression Model ◽  
Prediction Models ◽  
Multinomial Logistic Regression ◽  
Cvd Risk ◽  
Male Sex

Abstract Funding Acknowledgements Type of funding sources: None. onbehalf Liverpool Multiparametric Imaging Collaboration Background Coronary artery calcium (CAC) score is a well-established technique for stratifying an individual’s cardiovascular disease (CVD) risk. Several well-established registries have incorporated CAC scoring into CVD risk prediction models to enhance accuracy. Hepatosteatosis (HS) has been shown to be an independent predictor of CVD events and can be measured on non-contrast computed tomography (CT). We sought to undertake a contemporary, comprehensive assessment of the influence of HS on CAC score alongside traditional CVD risk factors. In patients with HS it may be beneficial to offer routine CAC screening to evaluate CVD risk to enhance opportunities for earlier primary prevention strategies. Methods We performed a retrospective, observational analysis at a high-volume cardiac CT centre analysing consecutive CT coronary angiography (CTCA) studies. All patients referred for investigation of chest pain over a 28-month period (June 2014 to November 2016) were included. Patients with established CVD were excluded. The cardiac findings were reported by a cardiologist and retrospectively analysed by two independent radiologists for the presence of HS. Those with CAC of zero and those with CAC greater than zero were compared for demographic and cardiac risks. A multivariate analysis comparing the risk factors was performed to adjust for the presence of established risk factors. A binomial logistic regression model was developed to assess the association between the presence of HS and increasing strata of CAC. Results In total there were 1499 patients referred for CTCA without prior evidence of CVD. The assessment of HS was completed in 1195 (79.7%) and CAC score was performed in 1103 (92.3%). There were 466 with CVD and 637 without CVD. The prevalence of HS was significantly higher in those with CVD versus those without CVD on CTCA (51.3% versus 39.9%, p = 0.007). Male sex (50.7% versus 36.1% p= <0.001), age (59.4 ± 13.7 versus 48.1 ± 13.6, p= <0.001) and diabetes (12.4% versus 6.9%, p = 0.04) were also significantly higher in the CAC group compared to the CAC score of zero. HS was associated with increasing strata of CAC score compared with CAC of zero (CAC score 1-100 OR1.47, p = 0.01, CAC score 101-400 OR:1.68, p = 0.02, CAC score >400 OR 1.42, p = 0.14). This association became non-significant in the highest strata of CAC score. Conclusion We found a significant association between the increasing age, male sex, diabetes and HS with the presence of CAC. HS was also associated with a more severe phenotype of CVD based on the multinomial logistic regression model. Although the association reduced for the highest strata of CAC (CAC score >400) this likely reflects the overall low numbers of patients within this group and is likely a type II error. Based on these findings it may be appropriate to offer routine CVD risk stratification techniques in all those diagnosed with HS.

scholarly journals Effectiveness of Mid-Regional Pro-Adrenomedullin (MR-proADM) as Prognostic Marker in COVID-19 Critically Ill Patients: an Observational Prospective Study

2020 ◽  
Author(s):  
Giorgia Montrucchio ◽  
Gabriele Sales ◽  
Francesca Rumbolo ◽  
Filippo Palmesino ◽  
Vito Fanelli ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Predictive Ability ◽  
Rank Test ◽  
Operating Characteristics ◽  
Icu Patients ◽  
D Dimer ◽  
Over Time

Abstract Background Due to the lack of validated biomarkers to predict disease progression and mortality in COVID-19 ICU-patients, we tested the effectiveness of mid-regional pro-adrenomedullin (MR-proADM) in comparison to C-reactive protein (CRP), procalcitonin (PCT), D-dimer, lactate dehydrogenase (LDH) in predicting outcome.Methods All consecutive COVID-19 adult patients admitted between March and June 2020 to the ICU of the ‘Città della Salute e della Scienza’ hospital in Turin (Italy) were enrolled. MR-proADM, clinical and routine laboratory test were measured within 48 hours from ICU admission, on day 3, 7 and 14. Survival curves difference with MR-proADM cut-off set to 1.8 nmol/L were tested using log-rank test. Predictive ability was compared using area under the curve and 95% confidence interval of different receiver-operating characteristics curves. Potential confounding effects were tested using a logistic regression model. Results Fifty-seven patients were enrolled. ICU and overall mortality were 54.4%. Within the first 24 hours, lymphocytopenia was present in 86%; increased D-dimer and CRP levels were found in 84.2% and 87.7% respectively, while PCT values higher than 0.5 μg/L were observed in 47.4%. MR-proADM, CRP and LDH were significantly different between surviving and non-surviving patients and over time, while PCT, D-dimer and NT-pro-BNP did not show any difference between the groups and over time; lymphocytes count was different between surviving and non-surviving patients only.MR-proADM was higher in dying patients (2.65+2.33vs1.18+0.47, p=0.0001) and a higher mortality characterized patients with MR-proADM exceeding 1.8 nmol/L (p=0.0157). The logistic regression model adjusted for age, gender, cardiovascular disease, diabetes mellitus and PCT values confirmed an odds ratio equal to 10.274 (95%CI 1.970-53.578) (p=0.0057) for MR-proADM higher than 1.8 nmol/L and equal to 22.206 (95%CI 1.56-316.960) (p=0.0223) for cardiovascular disease. Overall, MR-proADM was found to have the best predictive ability (AUC=0.846 – 95%CI 0.779-0.899).Conclusions In COVID-19 ICU-patients, MR-proADM seems able to provide a more precise stratification of disease severity and mortality risk than other biomarkers. Repeated MR-proADM measurement may support a rapid and effective decision-making. Further studies are needed to better explain the mechanisms responsible of the increase in MR-proADM observed in COVID-19 patients.

scholarly journals Can we predict an incomplete capsule endoscopy? Results of a multivariate analysis using a logistic regression model

2021 ◽  
Author(s):  
Elena Macías ◽  
Alfonso Elosua González ◽  
José Francisco Juanmartiñena ◽  
Ana Borda Martín ◽  
Inmaculada Elizalde ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Regression Model ◽  
Capsule Endoscopy ◽  
Logistic Regression Model

scholarly journals Prognostic Factors for Inguinal Lymph Node Involvement and Tumor Recurrence in Squamous Cell Carcinoma of the Penis

2020 ◽  
Vol 29 (02) ◽  
pp. 084-090
Author(s):  
J. Gustavo Ramos ◽  
Angie Ramírez ◽  
Rodolfo Varela ◽  
Daniela Robledo ◽  
José De la Hoz-Valle ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Logistic Regression ◽  
Prognostic Factors ◽  
Lymph Node ◽  
Regression Model ◽  
Cell Carcinoma ◽  
Tumor Recurrence ◽  
Logistic Regression Model ◽  
Lymphovascular Invasion

Abstract Introduction Penile carcinoma is an aggressive disease with catastrophic consequences that frequently lead to death. Therefore, further knowledge on the prognostic factors that can help identify patients in need of more aggressive treatments becomes essential. Objective To identify the prognostic factors for lymph node (LN) involvement and tumor recurrence in patients diagnosed with squamous cell carcinoma of the penis (SCCP). Methods A retrospective cohort study was conducted. Patients diagnosed and treated for SCCP at Instituto Nacional de Cancerología between 2008 and 2015 were included in the sample. Cases in which no information on recurrence was available for the follow-up were excluded, as well as patients with no initial pathology and those getting penile reconstructions after cancer.Relevant data was retrieved from the medical records of each patient, and a descriptive analysis was performed. Subsequently, this data was used to apply a logistic regression model to determine the potential clinical and histopathological prognostic factors. Results A total of 104 patients were included in the present study. The average age of the sample was 59 years, while the follow-up averaged 24 months per patient. Inguinal lymphadenectomy was performed on 61 patients (59%) during the follow-up. The logistic regression model showed that lymphovascular invasion (odds ratio [OR]: 6.7; 95% confidence interval [95%CI]: 1.2–35) and poor tumor differentiation (OR: 17; 95%CI: 3.2–92) were associated with tumor recurrence. Likewise, the lymphadenectomy procedures showed that lymphovascular invasion was associated with LN involvement (OR: 3.3; 95%CI: 1.1–10). Conclusion Lymphovascular invasion was the strongest prognostic factor observed in our sample, aiding in the prediction of inguinal LN involvement and tumor recurrence in SCCP patients.

scholarly journals Do gliosarcomas have distinct imaging features on routine MRI?

2021 ◽  
pp. 197140092110123
Author(s):  
Christoph J Maurer ◽  
Irina Mader ◽  
Felix Joachimski ◽  
Ori Staszewski ◽  
Bruno Märkl ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Regression Model ◽  
Logistic Regression Model ◽  
External Validation ◽  
Area Under The Curve ◽  
Training Dataset ◽  
Validation Dataset ◽  
Imaging Features ◽  
Age And Sex

Purpose The aim of this study was the development and external validation of a logistic regression model to differentiate gliosarcoma (GSC) and glioblastoma multiforme (GBM) on standard MR imaging. Methods A univariate and multivariate analysis was carried out of a logistic regression model to discriminate patients histologically diagnosed with primary GSC and an age and sex-matched group of patients with primary GBM on presurgical MRI with external validation. Results In total, 56 patients with GSC and 56 patients with GBM were included. Evidence of haemorrhage suggested the diagnosis of GSC, whereas cystic components and pial as well as ependymal invasion were more commonly observed in GBM patients. The logistic regression model yielded a mean area under the curve (AUC) of 0.919 on the training dataset and of 0.746 on the validation dataset. The accuracy in the validation dataset was 0.67 with a sensitivity of 0.85 and a specificity of 0.5. Conclusions Although some imaging criteria suggest the diagnosis of GSC or GBM, differentiation between these two tumour entities on standard MRI alone is not feasible.

Impact of preoperative magnetic resonance imaging (MRI) on conservative surgery (CSur) among curable breast cancer (BC) patients treated in a specialized center in Latin America.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e12595-e12595
Author(s):  
Julianne Maria da Silva Lima ◽  
Thatyane Cunha ◽  
Thamyse Dassie ◽  
Sandro Melo ◽  
Lincon Mori ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Regression Model ◽  
Surgical Management ◽  
Surgical Outcomes ◽  
Logistic Regression Model ◽  
Neoadjuvant Treatment ◽  
Clinical Information ◽  
Screening Tests ◽  
Categorical Variables

e12595 Background: Preoperative breast MRI can provide important clinical information on the surgical management of BC patients (pts). However, there is no evidence that it can produce a statistical impact on surgical outcomes in the early BC setting. This retrospective study sought to evaluate whether preoperative MRI was significantly correlated with CSur among early BC pts. Methods: Digital and physical records from 532 pts treated in a specialized BC center in Brazil from 2005 to 2018 were analyzed. The institutional database registered pathological, radiological and clinical information. The categorical variables CSur and MRI were analyzed by Chi-squared coefficient of correlation, whereas significant correlations were included in a multivariate logistic regression model. All statistical analysis were performed in STATA version 15.1C. Results: The present analysis included 532 pts. The diagnosis was suspected through suspicious self-exam in 380 pts (71%), while 129 pts (24%) had altered mammary screening tests. Clinical T and N stages were: T0-1=154pts (29%); T2=179 pts (33%); T3=135 pts (25%); T4=49 pts (9%); N0=267 pts (50%); N1=172 pts (32%); N2=80 pts (15%). Neoadjuvant treatment was performed in 223 pts (42%). MRI was indicated in 248 pts (46%). CSur was performed in 149 pts (28%). Margins were positive in 15 cases. This study found a statistically significant correlation between CSur and MRI ( X2 = 8.07; p=0.018). Although, when controlled for neoadjuvant treatment, T, N, and age, the independent variable MRI was not a statistical predictor of CSur (R=0.008; t=0.25; p=0.8; 95%CI -0.57 – 0.74). Advanced T and neoadjuvant treatment were inversely correlated with CSur in the multivariate analysis (R= -0.11; t= -7.8; p<0.001 and R= -0.11; t= -2.88; p=0.004, respectively). One multivariate analysis to evaluate predictors of T stages showed that suspicious self-exam and N stage had a significant linear relationship with T stages when controlled for age (R=0.70; t=7.9; p<0.001; and R=0.76; t=15; p<0.001, respectively). Conclusions: Preoperative MRI can have impact on the conservative surgical management of curable BC patients and the present analysis showed a positive correlation. In the logistic regression model, MRI was not identified as a predictor of CSur, however the proportion of locally advanced BC may have influenced the results. Further studies must be strengthened for identifying in which subgroup of patients MRI may be a predictor of surgical outcomes.

Myocardial perfusion/metabolism mismatch and ventricular arrhythmias in the chronic post infarction state

2005 ◽  
Vol 44 (03) ◽  
pp. 69-75 ◽  
Author(s):  
T. D. Poeppel ◽  
M. Reinhardt ◽  
E.-G. Vester ◽  
M. Yong ◽  
J. Mau ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Myocardial Perfusion ◽  
Regression Model ◽  
Ventricular Arrhythmias ◽  
Logistic Regression Model ◽  
Viable Myocardium ◽  
Cardiac Events ◽  
99Mtc Tetrofosmin ◽  
Arrhythmogenic Substrate

Summary Aim: Ventricular arrhythmias have been shown to originate in the myocardial peri-infarct region due to irregular heterotopic conduction. Hypoperfused but viable myocardium is often localised in those areas and may be involved in the pathogenesis of arrhythmias. We tested the hypothesis that these myocardial perfusion/metabolism mismatches (MM) are significantly associated with ventricular arrhythmias in the chronic post infarction state. Patients, methods: 47 post infarction patients were included in the study. 33 suffered from ventricular arrhythmia whereas 14 did not. All patients underwent 99mTc tetrofosmin SPECT and 18F-FDG PET. A region-of-interest(ROI)-analysis was used to assess viable myocardium based on predefined MM-criteria. Univariate analyses as well as a logistic regression model for the multivariate analysis were carried out. Results: 94% of the arrhythmic patients displayed at least one MM-segment as compared to 64% of the non-arrhythmic patients. MMsegments and arrhythmia showed a statistically significant relation (p = 0.018). The logistic regression model predicted the occurrence or absence of arrhythmia in 85% of all cases. Multivariate analysis gave consistent results, after adjusting for symptomatic chronic heart failure (CHF), aneurysms and age. Conclusion: Our results support the hypothesis that hypoperfused but viable myocardium represents an arrhythmogenic substrate and is a relevant risk factor for developing ventricular arrhythmias following myocardial infarction. Therefore, the detection of MM-segments allows the identification of patients with a higher risk for future cardiac events.

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