Prognostic Features of Near-Infrared Spectroscopy Following Primary Radical Prostatectomy

Background: Only a few biomarkers have been evaluated for their prognostic value with regard to biochemical recurrence (BCR) following primary radical prostatectomy. We explored the possibilities of using near-infrared (NIR) spectroscopy as a prognostic biomarker for BCR-free survival (BCR-FS). Methods: Tissue specimens from 82 prostate cancer patients were obtained. Formalin-fixed paraffin-embedded slides (hematoxylin–eosin-stained) were analyzed using NIR spectroscopy. Prognostic features for BCR-FS were determined following normalization of the spectra. Results: Several differences were found throughout the NIR spectrum for the patients with or without BCR, for both the first derivative and second derivative of the NIR spectrum. Following categorization and Cox regression analysis, spectral regions at 5236 cm−1 (first derivative; median BCR-FS not reached versus 3.2 years; HRhigh = 0.18 [0.08–0.39]; and p < 0.0001) and at 5956 cm−1 (second derivative; median BCR-FS not reached versus 3.8 years; HRlow = 0.22 [0.10–0.48]; and p = 0.0002) showed prognostic properties for BCR-FS. The combination of both parameters further increased the prognostic value of NIR (p < 0.0001). Conclusions: We demonstrated NIR spectral variations between patients with or without BCR, which have been shown to have prognostic value. This easy-to-use technique could possibly further improve post-primary radical prostatectomy monitoring and swift referral to adjuvant local therapies. Further elaboration is highly recommended to fully elucidate these variations and to gain a deeper insight into the changing chemical and physical compositions of the prostate tumor architecture.

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Assessment of the early signs of decay of Populus deltoides wafers exposed to Trametes versicolor by near infrared spectroscopy

Holzforschung ◽

10.1515/hf-2012-0501 ◽

2012 ◽

Vol 66 (4) ◽

Cited By ~ 6

Author(s):

Benny Green ◽

Paul David Jones ◽

Darrel D. Nicholas ◽

Laurence R. Schimleck ◽

Rubin Shmulsky ◽

...

Keyword(s):

Mass Loss ◽

Compression Strength ◽

Trametes Versicolor ◽

Near Infrared ◽

Populus Deltoides ◽

Nir Spectroscopy ◽

Exposure Period ◽

White Rot ◽

Second Derivative ◽

First Derivative

Abstract The use of near infrared (NIR) spectroscopy to predict levels of white-rot degradation in Populus deltoides (cottonwood) by Trametes versicolor over the couse of 1–8 days was investigated. NIR spectra were collected from cross-sectional faces following laboratory soil block decay tests. Spectra in the range of 1100–2400 nm were calibrated in terms of mass loss, compression strength and exposure period based on data of standard methods. The first and second derivatives of NIR spectra were also included into the calibration, which was done by partial least squares regression. The best calibrations with the strongest R2 values were obtained in terms of exposure period (R2 0.92, second derivative), mass loss (R2 0.89, first derivative) and compression strength (R2 0.51, second derivative). As far as the validation (prediction) statistics are concerned, the following data were obtained: exposure period (R2=0.71; RPDp 1.81, second derivative), mass loss prediction (R2=0.43; RPDp=0.67, first derivative) and compression strength R2=0.28; RPDp=1.14 (second derivative). The weak statistical data can be interpreted only in a way that the data are not robust and thus an early prediction of fungal attack by NIR spectroscopy is not yet reliable.

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Relationship of megakaryocyte size at diagnosis to chemotherapeutic response in children with acute nonlymphocytic leukemia

Blood ◽

10.1182/blood.v61.5.867.867 ◽

1983 ◽

Vol 61 (5) ◽

pp. 867-870 ◽

Cited By ~ 13

Author(s):

CW Jackson ◽

GV Dahl

Keyword(s):

Complete Remission ◽

Prognostic Value ◽

Cox Regression ◽

Time To Failure ◽

Acute Nonlymphocytic Leukemia ◽

Spleen Size ◽

Cox Regression Analysis ◽

Biopsy Specimens ◽

Chemotherapeutic Response ◽

Relationship Of

Abstract Small megakaryocytes are frequently seen in patients with acute nonlymphocytic leukemia (ANLL). In this study, median megakaryocyte diameters were determined in marrow biopsy specimens of 32 children at diagnosis of ANLL and related to platelet count and chemotherapeutic response. The association between median megakaryocyte size and time-to- failure was striking. Seven of 9 patients with median megakaryocyte diameters greater than 20 microns remain in continuous complete remission for more than 3 yr, whereas 20 of 23 patients with smaller median megakaryocyte diameters failed therapy within 15 mo (p = 0.002). By Cox-regression analysis, megakaryocyte size had independent prognostic value (p less than 0.001), surpassing that of spleen size, the only other feature having significant association with time-to- failure. Megakaryocyte size at diagnosis may be useful for predicting the likelihood of prolonged complete remission in ANLL.

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Prognostic value of health-related quality of life in patients with acute dyspnea

European Heart Journal ◽

10.1093/ehjci/ehaa946.1186 ◽

2020 ◽

Vol 41 (Supplement_2) ◽

Author(s):

M Belkin ◽

D Wussler ◽

I Strebel ◽

E Michou ◽

N Kozhuharov ◽

...

Keyword(s):

Prognostic Value ◽

Cox Regression ◽

Acute Dyspnea ◽

Cox Regression Analysis ◽

Prognostic Accuracy ◽

Related Quality ◽

Health Related ◽

Complete Set ◽

Eq Vas

Abstract Background Previous studies have shown the prognostic value of health-related quality of life (HRQL) in stable and ambulatory chronic heart failure patients. However, it is unknown whether HRQL can predict all-cause mortality in patients presenting to the emergency department (ED) after acute onset of symptoms. In order to address this unmet need, the aim of this study was to assess the prognostic value of HRQL in patients with acute dyspnea caused by acute heart failure (AHF) and other dyspnea aetiologies for 360-day mortality. Purpose To assess prognostic value of HRQL using the generic EQ-5D and visual analogue scale (EQ VAS) in patients with acute dyspnea. Methods Basics in Acute Shortness of Breath EvaLuation (BASEL V) is a prospective, multicenter, diagnostic study enrolling adult patients presenting with acute dyspnea to the ED. For this analysis, only patients with a complete set of variables necessary for calculation of EQ-5D (range 0–10; with higher score indicating worse HRQL) and EQ VAS (range 0–100; with 100 being the best imaginable health state) at baseline were included. The endpoint was the prognostic value of EQ-5D and EQ VAS at 360 days of follow-up regarding all-cause death. Prognostic accuracy was calculated using c-statistics. In a cox regression analysis EQ-5D was treated as both, a continuous and categorical variable. Adjustments were made for clinically relevant covariates (age, sex, orthopnoea, edema, level of N-terminal pro-B-type natriuretic peptide (NT-proBNP) at presentation, history of coronary artery disease and chronic obstructive pulmonary disease, diuretics, β-blockers and ACE-inhibitors at discharge). Results Among 2605 patients enrolled, 1141 (43,8%) had a complete set of variables allowing the calculation of EQ-5D and EQ VAS. Of these patients 594 (52.1%) had an adjudicated final diagnosis of AHF. 211 (18.5%) patients died within 360 days of follow-up. Median EQ-5D was 3 (interquartile range (IQR) 1.5–5) and median EQ VAS was 50 (IQR 40–70). The prognostic accuracy for 360-day mortality was 0.65 (95% confidence interval ((CI) 0.61–0.69) and 0.58 (95% CI 0.54–0.62) for EQ-5D and EQ VAS, respectively (p=0.002). After combining EQ-5D and EQ VAS in a logistic regression model c-statistics regarding all-cause mortality within 360 days did not improve. The prognostic accuracy of EQ-5D was comparable to that of NT-proBNP (c-statistics 0.69, p=0.385). In an adjusted cox regression analysis the hazard ratio for patients with EQ-5D >4 was 2.2 (95% CI 1.7–2.9; p<0.001). Conclusions In patients presenting with acute dyspnea HRQL is a strong prognostic instrument. Independently of the aetiology of the dyspnea the prognostic value of the generic EQ-5D for 360-day mortality is comparable to NT-proBNP. Patients with an EQ-5D >4 are at significantly higher risk for mortality within 360 days. Figure 1. Prognostic value of HRQL Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): Swiss National Science Foundation, Swiss Heart Foundation

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Cancer Discrimination Using Fourier Transform Near-Infrared Spectroscopy with Chemometric Models

Journal of Chemistry ◽

10.1155/2015/619685 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Hui Chen ◽

Zan Lin ◽

Chao Tan

Keyword(s):

Cancer Diagnosis ◽

Near Infrared ◽

Nir Spectroscopy ◽

Principal Component ◽

Classification Model ◽

Support Vector ◽

Biomedical Analysis ◽

First Derivative ◽

Svm Model ◽

High Prediction

Near-infrared (NIR) spectroscopy technique offers many potential advantages as tool for biomedical analysis since it enables the subtle biochemical signatures related to pathology to be detected and extracted. In conjunction with advanced chemometrics, NIR spectroscopy opens the possibility of their use in cancer diagnosis. The study focuses on the application of near-infrared (NIR) spectroscopy and classification models for discriminating colorectal cancer. A total of 107 surgical specimens and a corresponding NIR diffuse reflection spectral dataset were prepared. Three preprocessing methods were attempted and least-squares support vector machine (LS-SVM) was used to build a classification model. The hybrid preprocessing of first derivative and principal component analysis (PCA) resulted in the best LS-SVM model with the sensitivity and specificity of 0.96 and 0.96 for the training and 0.94 and 0.96 for test sets, respectively. The similarity performance on both subsets indicated that overfitting did not occur, assuring the robustness and reliability of the developed LS-SVM model. The area of receiver operating characteristic (ROC) curve was 0.99, demonstrating once again the high prediction power of the model. The result confirms the applicability of the combination of NIR spectroscopy, LS-SVM, PCA, and first derivative preprocessing for cancer diagnosis.

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Cognitive impairment predicts conversion to multiple sclerosis in clinically isolated syndromes

Multiple Sclerosis Journal ◽

10.1177/1352458509350311 ◽

2009 ◽

Vol 16 (1) ◽

pp. 62-67 ◽

Cited By ~ 98

Author(s):

Valentina Zipoli ◽

Benedetta Goretti ◽

Bahia Hakiki ◽

Gianfranco Siracusa ◽

Sandro Sorbi ◽

...

Keyword(s):

Multiple Sclerosis ◽

Cognitive Impairment ◽

Prognostic Value ◽

Cox Regression ◽

Cox Regression Analysis ◽

Clinically Isolated Syndromes ◽

Kaplan Meier ◽

Sizable Proportion ◽

One Year ◽

Therapeutic Decision Making

Significant cognitive impairment has been found in 20—30% of patients with clinically isolated syndromes suggestive of multiple sclerosis. In this study we aimed to assess the prognostic value of the presence of cognitive impairment for the conversion to multiple sclerosis in patients with clinically isolated syndromes. All patients with clinically isolated syndromes consecutively referred to our centre since 2002 and who had been followed-up for at least one year underwent cognitive assessment through the Rao’s Battery and the Stroop test. Possible predictors of conversion to clinically definite multiple sclerosis were evaluated through the Kaplan Meier curves and Cox regression analysis. A total of 56 patients (41 women; age 33.2 ± 8.5 years; expanded disability scale score 1.2 ± 0.7) were recruited. At baseline, 32 patients (57%) fulfilled McDonald’s criteria for dissemination in space. During the follow-up (3.5 ± 2.3 years), 26 patients (46%) converted to a diagnosis of multiple sclerosis. In particular, 64% of patients failing ≥ 2 tests and 88% of patients failing ≥ 3 tests converted to multiple sclerosis. In the Cox regression model, the failure of at least three tests (HR 3.3; 95% CI 1.4—8.1; p = 0.003) and the presence of McDonald’s dissemination in space at baseline (HR 3.8; 95% CI 1.5—9.7; p = 0.005), were found to be predictors for conversion to multiple sclerosis. We conclude that cognitive impairment is detectable in a sizable proportion of patients with clinically isolated syndromes. In these subjects cognitive impairment has a prognostic value in predicting conversion to multiple sclerosis and may therefore play a role in therapeutic decision making.

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Identification and Validation of a Seven m6A-related lncRNAs Signature Predicting Prognosis of Ovarian Cancer

10.21203/rs.3.rs-915700/v1 ◽

2021 ◽

Author(s):

Yan Li ◽

Xiaoying Wang ◽

Yue Han ◽

Xun Li

Keyword(s):

Ovarian Cancer ◽

Regression Analysis ◽

Correlation Analysis ◽

Prognostic Value ◽

Cox Regression ◽

Risk Group ◽

Pearson Correlation ◽

Regression Analyses ◽

Cox Regression Analysis ◽

Pearson Correlation Analysis

Abstract Background: Long non-coding RNAs (lncRNAs) play an important role in angiogenesis, immune response, inflammatory response and tumor development and metastasis. m6 A (N6 - methyladenosine) is one of the most common RNA modifications in eukaryotes. The aim of our research was to investigate the potential prognostic value of m6A-related lncRNAs in ovarian cancer (OC).Methods: The data we need for our research was downloaded from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Pearson correlation analysis between 21 m6A regulators and lncRNAs was performed to identify m6A-related lncRNAs. Univariate Cox regression analysis was implemented to screen for lncRNAs with prognostic value. A least absolute shrinkage and selection operator (LASSO) Cox regression and multivariate Cox regression analyses was used to further reduct the lncRNAs with prognostic value and construct a m6A-related lncRNAs signature for predicting the prognosis of OC patients. Results: 275 m6A-related lncRNAs were obtained using pearson correlation analysis. 29 m6A-related lncRNAs with prognostic value was selected through univariate Cox regression analysis. Then, a seven m6A-related lncRNAs signature was identified by LASSO Cox regression. Each patient obtained a riskscore through multivariate Cox regression analyses and the patients were classified into high-and low-risk group using the median riskscore as a cutoff. Kaplan-Meier curve revealed that the patients in high-risk group have poor outcome. The receiver operating characteristic curve revealed that the predictive potential of the m6A-related lncRNAs signature for OC was powerful. The predictive potential of the m6A-related lncRNAs signature was successfully validated in the GSE9891, GSE26193 datasets and our clinical specimens. Multivariate analyses suggested that the m6A-related lncRNAs signature was an independent prognostic factor for OC patients. Moreover, a nomogram based on the expression level of the seven m6A-related lncRNAs was established to predict survival rate of patients with OC. Finally, a competing endogenous RNA (ceRNA) network associated with the seven m6A-related lncRNAs was constructed to understand the possible mechanisms of the m6A-related lncRNAs involed in the progression of OC.Conclusions: In conclusion, our research revealed that the m6A-related lncRNAs may affect the prognosis of OC patients and identified a seven m6A-related lncRNAs signature to predict the prognosis of OC patients.

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The Prognostic Value of the m6A Score in Multiple Myeloma Based on Machine Learning

BioMedInformatics ◽

10.3390/biomedinformatics1030006 ◽

2021 ◽

Vol 1 (3) ◽

pp. 77-87

Author(s):

Gong Xiao ◽

Qiongjing Yuan ◽

Wei Wang

Keyword(s):

Multiple Myeloma ◽

Cancer Progression ◽

Risk Score ◽

Prognostic Value ◽

Risk Model ◽

Cox Regression ◽

Microarray Dataset ◽

Immune Checkpoints ◽

Bioinformatics Analyses ◽

Cox Regression Analysis

Background: Multiple myeloma (MM) is one of the most common cancers of the blood system. N6-methyladenosine (m6A) plays an important role in cancer progression. We aimed to investigate the prognostic relevance of the m6A score in multiple myeloma through a series of bioinformatics analyses. Methods: The microarray dataset GSE4581 and GSE57317 used in this study were downloaded from the Gene Expression Omnibus (GEO) database. The m6A score was calculated using the GSVA package. The Random forests, univariate Cox regression analysis and Lasso analyses were performed for the differentially expressed genes (DEGs). Kaplan–Meier analysis and an ROC curve were used to diagnose the effectiveness of the model. Results: The GSVA R software package was used to predict the function. A total of 21 m6A genes were obtained, and 286 DEGs were identified between high and low m6A score groups. The risk model was constructed and composed of PRX, LBR, RB1, FBXL19-AS1, ARSK, MFAP3L, SLC44A3, UNC119 and SHCBP1. Functional analysis of risk score showed that with the increase in the risk score, Activated CD4 T cells, Memory B cells and Type 2 T helper cells were highly infiltrated. Conclusions: Immune checkpoints such as HMGB1, TGFB1, CXCL9 and HAVCR2 were significantly positively correlated with the risk score. We believe that the m6A score has a certain prognostic value in multiple myeloma.

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miR-181 Expression is Associated With The Prognosis in Lung Cancer.

10.21203/rs.3.rs-44942/v1 ◽

2020 ◽

Author(s):

Yue Zhao ◽

Xiangjun Kong ◽

Hongbing Wang

Keyword(s):

Lung Cancer ◽

Overall Survival ◽

Prognostic Value ◽

Cox Regression ◽

Suppressor Gene ◽

Rank Test ◽

High Morbidity ◽

Cox Regression Analysis ◽

Log Rank Test ◽

Cancer Tissues

Abstract Background: Lung cancer is one of the most common cancers, with high morbidity and mortality. MiRNAs are proved to play important roles in various human cancers. In our study, we aimed to explore the prognostic value of miR-181 in lung cancerMethods: Quantitative real-time polymerase chain reaction (QRT-PCR) was used to detect the expression level of miR-181 in lung cancer tissues and the paired non-cancerous tissues. The relationship between miR-181 expression and clinicopathologic parameters were analyzed by chi-square test. Kaplan-Meier method with log rank test was applied for overall survival analysis. Furthermore, the Cox regression analyses were performed to evaluate the prognostic value of miR-181 in lung cancer.Results: Down-regulated miR-181 expression was observed in lung cancer tissues (P<0.001), moreover, its expression was significantly correlated with TNM stage (P=0.015) and metastasis (P=0.000). In addition, lung cancer patients with lower miR-181 expression level had poorer overall survival than those with higher expression (log rank test, P=0.011). Cox regression analysis suggested that miR-181 was an independent prognostic factor for lung cancer (HR=1.961, 95%CI=1.135-3.388, P=0.016).Conclusion: MiR-181 may be a tumor suppressor gene in lung cancer, which can predict outcomes for the patients.

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Efficacy of Postoperative FOLFOX Versus XELOX Chemotherapy for Gastric Cancer and Prognostic Value of Platelet–Lymphocyte Ratio in Patients Receiving XELOX

Frontiers in Oncology ◽

10.3389/fonc.2020.584772 ◽

2020 ◽

Vol 10 ◽

Author(s):

Xin Yin ◽

Tianyi Fang ◽

Yimin Wang ◽

Chunfeng Li ◽

Yufei Wang ◽

...

Keyword(s):

Gastric Cancer ◽

Tumor Size ◽

Prognostic Value ◽

Cox Regression ◽

Postoperative Chemotherapy ◽

Chinese Patients ◽

Cox Regression Analysis ◽

Lymphocyte Ratio ◽

Platelet Lymphocyte Ratio ◽

Ptnm Stage

BackgroundSurgery combined with postoperative chemotherapy is an effective method for treating patients with gastric cancer (GC) in Asia. The important roles of systemic inflammatory response in chemotherapy have been gradually verified. The purpose of this study was to assess the difference in clinical effectiveness of FOLFOX (oxaliplatin + leucovorin + 5-fluorouracil) and XELOX (oxaliplatin + capecitabine), and the prognostic value of postoperative platelet–lymphocyte ratio (PLR) in the XELOX group.MethodsPatients who received radical gastrectomy combined with postoperative chemotherapy between 2004 and 2014 were consecutively selected into the FOLFOX and XELOX groups. Group bias was reduced through propensity score matching, which resulted in 278 patients in each group. Cut-off values of systemic immune inflammation (SII) score and PLR were obtained by receiver operating characteristic curve. Kaplan–Meier and Log-rank tests were used to analyze overall survival. The chi-square test was used to analyze the association between clinical characteristics and inflammatory indexes. Univariate and multivariate analyses based on Cox regression analysis showed independent risk factors for prognosis. The nomogram was made by R studio.ResultsPatients receiving XELOX postoperative chemotherapy had better survival than those receiving FOLFOX (P < 0.001), especially for stage III GC (P = 0.002). Preoperative SII was an independent risk factor for prognosis in the FOLFOX group, and PLR of the second postoperative chemotherapy regimen in the XELOX group, combined with tumor size and pTNM stage, could construct a nomogram for evaluating recurrence and prognosis.ConclusionXELOX is better than FOLFOX for treatment of GC in Chinese patients, and a nomogram constructed by PLR, tumor size and pTNM stage can predict recurrence and prognosis.

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Analysis of the Acid Detergent Fibre Content in Turnip Greens and Turnip Tops (Brassica rapa L. Subsp. rapa) by Means of Near-Infrared Reflectance

Foods ◽

10.3390/foods8090364 ◽

2019 ◽

Vol 8 (9) ◽

pp. 364 ◽

Cited By ~ 1

Author(s):

Sara Obregón-Cano ◽

Rafael Moreno-Rojas ◽

Ana María Jurado-Millán ◽

María Elena Cartea-González ◽

Antonio De Haro-Bailón

Keyword(s):

Standard Error ◽

Near Infrared ◽

Mathematical Treatment ◽

Second Derivative ◽

Infrared Reflectance ◽

Near Infrared Reflectance ◽

First Derivative ◽

Acid Detergent Fibre ◽

Turnip Greens ◽

Turnip Tops

Standard wet chemistry analytical techniques currently used to determine plant fibre constituents are costly, time-consuming and destructive. In this paper the potential of near-infrared reflectance spectroscopy (NIRS) to analyse the contents of acid detergent fibre (ADF) in turnip greens and turnip tops has been assessed. Three calibration equations were developed: in the equation without mathematical treatment the coefficient of determination (R2) was 0.91, in the first-derivative treatment equation R2 = 0.95 and in the second-derivative treatment R2 = 0.96. The estimation accuracy was based on RPD (the ratio between the standard deviation and the standard error of validation) and RER (the ratio between the range of ADF of the validation as a whole and the standard error of prediction) of the external validation. RPD and RER values were of 2.75 and 9.00 for the treatment without derivative, 3.41 and 11.79 with first-derivative, and 3.10 and 11.03 with second-derivative. With the acid detergent residue spectrum the wavelengths were identified and associated with the ADF contained in the sample. The results showed a great potential of NIRS for predicting ADF content in turnip greens and turnip tops.

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