Utility of serological biomarker’ panels for diagnostic accuracy of interstitial lung diseases

AbstractInterstitial lung diseases (ILD) are a heterogeneous group of illnesses of known and unknown aetiology. Differential diagnosis among the three disorders is often challenging. Specific biomarkers with good sensitivity and specificity are therefore needed to predict clinical outcome and guide clinical decisions. The aim of this study was to investigate inflammatory/fibrotic biomarkers, to determine whether single mediators or panels of mediators could be useful to stratify patients into three distinct domains: sarcoidosis, idiopathic pulmonary fibrosis (IPF) and chronic hypersensitivity pneumonitis (cHP). A total of 163 ILD patients monitored at Siena Referral Centre for Sarcoidosis and other Interstitial Lung Diseases were enrolled in the study. Clinical data, pulmonary function tests and biochemical analytes were retrospectively collected. SAA levels were detected by ELISA kit and Krebs von den Lungen 6 (KL-6) were measured by CLEIA method, for sarcoidosis, cHP and IPF patients. Multiple comparison analysis showed significant differences in C reactive protein (CRP), white blood cell count (WBC) and creatinine levels between the three groups. In the logistic regression model, KL-6, CRP and WBC showed areas under curves (AUC) 0.86, for sarcoidosis diagnosis. The logistic regression model KL-6 and SAA showed the best performance with an AUC 0.81 for discriminating IPF than cHP and sarcoidosis. For differential diagnosis of IPF and cHP, KL-6 and SAA were considered in the logistic regression model, showed an AUC 0.79. The combination of serum biomarkers proposed here offers insights into the pathobiology of ILDs. These panels of bioindicators will improve diagnostic accuracy and will be useful in the clinical management of ILDs.

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Modeling Incidence Rate by Region: Analysis of Asthma and Other Chronic Obstructive Lung Diseases

10.21203/rs.3.rs-450207/v1 ◽

2021 ◽

Author(s):

Ronald Wesonga ◽

Khidir Abdelbasit

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Lung Diseases ◽

Logistic Regression Model ◽

Incidence Rates ◽

Chronic Obstructive ◽

Binary Logistic Regression Model ◽

Obstructive Lung Diseases ◽

Geographical Regions ◽

Chronic Obstructive Lung Diseases

Abstract This study aimed to examine regional differences for asthma and other chronic obstructive lung diseases. The study was based on data collected from annual reports produced by the Ministry of Health over a ten-year period beginning from 2010 to 2019. Incidence rates for eleven regions in the Sultanate of Oman were analyzed using statistical tools including; analysis of variance and binary logistic regression model to determine the effect of region on asthma and other chronic obstructive lung diseases. The incident rates were found to be significantly different by region (F-value = 27.07, p = 0.00). There was no significant variation by year (F-value = 1.05, p > 0.407). Overall over the ten-year period the incidence rates stagnated between 250 and 300 per 10000 of the population, but showed a reducing trend between 2016 and 2019. The logistic regression model shows that compared to the Muscat region, all the other regions had significant increased odd ratios. There is a significant evidence of regional variation in the incidence of asthma and other chronic obstructive lung diseases. This implies probable characteristics in geographical regions that are associated with asthma and other chronic obstructive lung diseases’ exacerbation. Five asthma-region classifications were identified from our analysis. Findings of this study may be used to guide decision making towards the management and control of asthma and chronic obstructive lung diseases.

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Data Analytical Approach for Regional Variation of Incidence Rates for Asthma and Other Chronic Obstructive Lung Diseases in Oman

10.21203/rs.3.rs-1032316/v1 ◽

2021 ◽

Author(s):

Ronald Wesonga ◽

Khidir Abdelbasit

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Regional Variation ◽

Lung Diseases ◽

Logistic Regression Model ◽

Incidence Rates ◽

Chronic Obstructive ◽

Obstructive Lung Diseases ◽

Geographical Regions ◽

Chronic Obstructive Lung Diseases

Abstract Background This study aimed to examine regional differences for asthma and other chronic obstructive lung diseases. Information pertaining influence of region on asthma is not well established. Method The study was based on data collected from annual reports produced by the Ministry of Health over a ten-year period beginning from 2010 to 2019. Incidence rates per 10000 populations for the eleven regions in the Sultanate of Oman were analyzed using statistical tools including; analysis of variance and binary logistic regression model to determine the effect of region on asthma and other chronic obstructive lung diseases. Results The incident rates were found to be significantly different by region (F-value=27.07, p=0.00). There was no significant variation by year (F-value=1.05, p>0.407). Overall over the ten-year period the incidence rates stagnated between 250 and 300 per 10000 of the population, but showed a reducing trend between 2016 and 2019. The logistic regression model shows that compared to the Muscat region, all the other regions had significant increased odd ratios. Conclusion There is a significant evidence of regional variation in the incidence of asthma and other chronic obstructive lung diseases. This implies probable characteristics in geographical regions that are associated with asthma and other chronic obstructive lung diseases’ exacerbation. Five asthma-region classifications were identified from our analysis. Findings of this study may be used to guide decision making towards the management and control of asthma and chronic obstructive lung diseases.

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Surgeon specific effects on the postoperative systemic inflammatory response and complications following surgery for colorectal cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2018.36.4_suppl.799 ◽

2018 ◽

Vol 36 (4_suppl) ◽

pp. 799-799

Author(s):

Stephen Thomas McSorley ◽

Campbell SD Roxburgh ◽

Donald C McMillan ◽

Paul G. Horgan

Keyword(s):

Colorectal Cancer ◽

Logistic Regression ◽

Inflammatory Response ◽

Regression Model ◽

Logistic Regression Model ◽

Binary Logistic Regression ◽

Systemic Inflammatory Response ◽

C Reactive Protein ◽

Binary Logistic Regression Model ◽

Reactive Protein

799 Background: The present study examined the impact of surgeon specific differences on the postoperative systemic inflammatory response (SIR) as measured by postoperative C-reactive protein (CRP), and complications, following elective surgery for colorectal cancer. Methods: 684 patients who underwent elective colorectal cancer resection performed by 10 consultant surgeons at single centre between 2008 and 2016 were included. Exceeding the established C-reactive protein (CRP) threshold of 150mg/L on postoperative days (POD) 3 and 4 was used to identify outliers by funnel plot analysis. Surgeons with significant differences in the proportion of patients exceeding POD 3 CRP 150mg/L were compared. Significantly different perioperative variables amongst surgeons, and the surgeons themselves, were then entered into a multivariate binary logistic regression model to asses association with POD 3 CRP. Results: Perioperative factors were compared between 3 surgeons with the highest volumes and greatest difference in the proportion of patients exceeding POD 3 CRP 150mg/L (Figure 1); (35% of 137, 50% of 117, 60% of 92, p < 0.001). Amongst the 3 surgeons there were significant differences in comorbid state (p = 0.042), the proportion of patients undergoing minimally invasive surgery (p < 0.001), or surgery lasting over 4 hours (p < 0.001), requiring blood transfusion (p = 0.038), epidural anaesthesia (p < 0.001), and receiving perioperative steroids (p < 0.001). When those factors which were significantly different between surgeons were entered into a multivariate binary logistic regression model to predict exceeding the POD 3 CRP threshold of 150mg/L, only perioperative dexamethasone (OR 0.40, 95% CI 0.19-0.82, p = 0.012), and postoperative complications (OR 2.22, 95% CI 1.14-4.32, p = 0.018), remained independently associated whilst the surgeons themselves were not significantly associated (OR 1.16, 95% CI 0.59-2.30, p = 0.663). Conclusions: This study suggests that surgeon specific difference in the magnitude of the postoperative systemic inflammatory response are related to differences in surgical approach, anaesthetic technique and complications.

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Modeling Incidence Rate by Region: Analysis of Asthma and Other Chronic Obstructive Lung Diseases

10.21203/rs.3.rs-514019/v1 ◽

2021 ◽

Author(s):

Ronald Wesonga ◽

Khidir Abdelbasit

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Lung Diseases ◽

Logistic Regression Model ◽

Incidence Rates ◽

Chronic Obstructive ◽

Binary Logistic Regression Model ◽

Obstructive Lung Diseases ◽

Geographical Regions ◽

Chronic Obstructive Lung Diseases

Abstract This study aimed to examine regional differences for asthma and other chronic obstructive lung diseases. The study was based on data collected from annual reports produced by the Ministry of Health over a ten-year period beginning from 2010 to 2019. Incidence rates for eleven regions in the Sultanate of Oman were analyzed using statistical tools including; analysis of variance and binary logistic regression model to determine the effect of region on asthma and other chronic obstructive lung diseases. The incident rates were found to be significantly different by region (F-value=27.07, p=0.00). There was no significant variation by year (F-value=1.05, p>0.407). Overall over the ten-year period the incidence rates stagnated between 250 and 300 per 10000 of the population, but showed a reducing trend between 2016 and 2019. The logistic regression model shows that compared to the Muscat region, all the other regions had significant increased odd ratios. There is a significant evidence of regional variation in the incidence of asthma and other chronic obstructive lung diseases. This implies probable characteristics in geographical regions that are associated with asthma and other chronic obstructive lung diseases’ exacerbation. Five asthma-region classifications were identified from our analysis. Findings of this study may be used to guide decision making towards the management and control of asthma and chronic obstructive lung diseases.

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Prospects for the application of a new logistic regression model for the differential diagnosis of prostate cancer

Clinical Medicine (Russian Journal) ◽

10.30629/0023-2149-2021-99-2-98-102 ◽

2021 ◽

Vol 99 (2) ◽

pp. 98-102

Author(s):

S. V. Ponkratov ◽

I. B. Oleksjuk ◽

K. L. Kozlov ◽

A. V. Oleksjuk

Keyword(s):

Prostate Cancer ◽

Logistic Regression ◽

Differential Diagnosis ◽

Regression Model ◽

Prostate Specific Antigen ◽

Logistic Regression Model ◽

Specific Antigen ◽

Transrectal Ultrasound ◽

Modern Medicine ◽

Ultrasound Investigation

The differential diagnostic of prostate cancer is the actual task of modern medicine. The existing methods lack accuracy and specificity. It’s the reason of hyper- or hypo-diagnostic of this disease. We developed and tested the new logistic regression model for diagnostic of prostate cancer in men of various age. The model includes age, the volume of prostate, concentration of prostate specific antigen (PCA), 2-pro-PCA in the blood, the presence of the concretion revealed during digital rectal investigation of prostate and hypoechogenic area in transrectal ultrasound investigation. The model was tested in 114 patients. It has shown the higher accuracy and specificity of the new regression model in comparison to other methods of differential diagnostic of prostate cancer.

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Application of monoexponential, biexponential, and stretched-exponential models of diffusion-weighted magnetic resonance imaging in the differential diagnosis of metastases and myeloma in the spine-Univariate and multivariate analysis of related parameters

British Journal of Radiology ◽

10.1259/bjr.20190891 ◽

2020 ◽

Vol 93 (1112) ◽

pp. 20190891

Author(s):

Xiaoying Xing ◽

Jiahui Zhang ◽

Yongye Chen ◽

Qiang Zhao ◽

Ning Lang ◽

...

Keyword(s):

Logistic Regression ◽

Differential Diagnosis ◽

Diffusion Coefficient ◽

Decision Tree ◽

Regression Model ◽

Logistic Regression Model ◽

Decision Tree Model ◽

Tree Model ◽

Stretched Exponential ◽

Exponential Models

Objective: To explore the value of related parameters in monoexponential, biexponential, and stretched-exponential models of diffusion-weighted imaging (DWI) in differentiating metastases and myeloma in the spine. Methods: 53 metastases and 16 myeloma patients underwent MRI with 10 b-values (0–1500 s/mm2). Parameters of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), the distribution diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) from DWI were calculated. The independent sample t test and the Mann–Whiney U test were used to compare the statistical difference of the parameter values between the two. Receiver operating characteristics (ROC) curve analysis was used to identify the diagnostic efficacy. Then substituted each parameter into the decision tree model and logistic regression model, identified meaningful parameters, and evaluated their joint diagnostic performance. Results: The ADC, D, and α values of metastases were higher than those of myeloma, whereas the D* value was lower than that of myeloma, and the difference was significant (p < 0.05); the area under the ROC curve for the above parameters was 0.661, 0.710, 0.781, and 0.743, respectively. There was no significant difference in the f and DDC values (p > 0.05). D and α were found to conform to the decision tree model, and the accuracy of model diagnosis was 84.1%. ADC and α were found to conform to the logistic regression model, and the accuracy was 87.0%. Conclusion: The 3 models of DWI have certain values indifferentiating metastases and myeloma in spine, and the diagnostic performance of ADC, D, α and D*was better. Combining ADC with α may markedly aid in the differential diagnosis of the two. Advances in knowledge: Monoexponential, biexponential, and stretched-exponential models can offer additional information in the differential diagnosis of metastases and myeloma in the spine. Decision tree model and logistic regression model are effective methods to help further distinguish the two.

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Real-life prevalence of progressive fibrosing interstitial lung diseases

Scientific Reports ◽

10.1038/s41598-021-03481-8 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Maureen Gagliardi ◽

Damienne Vande Berg ◽

Charles-Edouard Heylen ◽

Sandra Koenig ◽

Delphine Hoton ◽

...

Keyword(s):

Lung Diseases ◽

Hypersensitivity Pneumonitis ◽

Vital Capacity ◽

Interobserver Agreement ◽

Pulmonary Function Tests ◽

Real Life ◽

Interstitial Lung Diseases ◽

Main Diagnosis ◽

High Resolution Computed Tomography ◽

Traction Bronchiectasis

AbstractThe concept of progressive fibrosing interstitial lung disease (PF-ILD) has recently emerged. However, real-life proportion of PF-ILDs outside IPF is still hard to evaluate. Therefore, we sought to estimate the proportion of PF-ILD in our ILD cohort. We also determined the proportion of ILD subtypes within PF-ILD and investigated factors associated with PF-ILDs. Finally, we quantified interobserver agreement between radiologists for the assessment of fibrosis. We reviewed the files of ILD patients discussed in multidisciplinary discussion between January 1st 2017 and December 31st 2019. Clinical data, pulmonary function tests (PFTs) and high-resolution computed tomography (HRCTs) were centrally reviewed. Fibrosis was defined as the presence of traction bronchiectasis, reticulations with/out honeycombing. Progression was defined as a relative forced vital capacity (FVC) decline of ≥ 10% in ≤ 24 months or 5% < FVC decline < 10% and progression of fibrosis on HRCT in ≤ 24 months. 464 consecutive ILD patients were included. 105 had a diagnosis of IPF (23%). Most frequent non-IPF ILD were connective tissue disease (CTD)-associated ILD (22%), hypersensitivity pneumonitis (13%), unclassifiable ILD (10%) and sarcoidosis (8%). Features of fibrosis were common (82% of CTD-ILD, 81% of HP, 95% of uILD). After review of HRCTs and PFTs, 68 patients (19% of non-IPF ILD) had a PF-ILD according to our criteria. Interobserver agreement for fibrosis between radiologists was excellent (Cohen’s kappa 0.86). The main diagnosis among PF-ILD were CTD-ILD (36%), HP (22%) and uILD (20%). PF-ILD patients were significantly older than non-F-ILD (P = 0.0005). PF-ILDs represent about 20% of ILDs outside IPF. This provides an estimation of the proportion of patients who might benefit from antifibrotics. Interobserver agreement between radiologists for the diagnosis of fibrotic ILD is excellent.

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