scholarly journals MIRS: an AI scoring system for predicting the prognosis and therapy of breast cancer

2021 ◽  
Author(s):  
Chen Huang ◽  
Min Deng ◽  
Dongliang Leng ◽  
Elaine Lai-Han Leung ◽  
Baoqing Sun ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Scoring System ◽  
Risk Group ◽  
Scoring Systems ◽  
High Risk Group ◽  
Gene Profiling ◽  
Immune Infiltration ◽  
Checkpoint Inhibitor Therapy ◽  
Prognostic Feature ◽  
Profiling Analysis

Current scoring systems for prognosis of breast cancer are available but usually consider only one prognostic feature. We aim to develop a novel prognostic scoring system based on both immune-infiltration and metastatic features to not only assess the patient prognoses more accurately but also guide therapy for patients with breast cancer. Computational immune-infiltration and gene profiling analysis identified a 12-gene panel firstly characterizing immune-infiltrating and metastatic features. Neural network model yielded a precise prognostic scoring system called metastatic and immunogenomic risk score (MIRS). The influence of MIRS on the prognosis and therapy of breast cancer was then comprehensively investigated. MIRS significantly stratifies patients into high risk-group (MIRShigh) and low risk-group (MIRSlow) in both training and test cohorts. The MIRSlow patients exhibit significantly improved survival rate compared with MIRShigh patients. A series of analyses demonstrates that MIRS can well characterize the metastatic and immune landscape of breast cancer. Further analysis on the usage of MIRS in chemotherapy suggests that MIRShigh patients may benefit from three chemotherapeutic drugs (Cisplatin, Tamoxifen and Vincristine). Higher immune infiltration and significantly prolonged survival are observed in MIRSlow patients, indicating a better response in immune checkpoint inhibitor therapy. Our analysis demonstrates that MIRS could effectively improve the accuracy of prognosis for patients with breast cancer. Also, MIRS is a useful webtool, which is deposited at https://lva85.github.io/MIRS/, to help clinicians in designing personalized therapies for patients with breast cancer.

MD Anderson Scoring System (MDACC) Predicts Outcomes After Hematopoietic Stem Cell Transplantation (HSCT) Better Than Other Prognostic Classifications In MDS

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3340-3340
Author(s):  
Piyanuch Kongtim ◽  
Uday R Popat ◽  
Marcos de Lima ◽  
Guillermo Garcia-Manero ◽  
Elias J. Jabbour ◽  
...  
Keyword(s):  
High Risk ◽  
Scoring System ◽  
Risk Group ◽  
Univariate Analysis ◽  
Scoring Systems ◽  
Risk Groups ◽  
High Risk Group ◽  
Risk Scores ◽  
Hematopoietic Stem ◽  
Very High

Abstract MDS is a heterogeneous group of hematopoietic stem cell disorders. Various prognostic models have been established to categorize patients with MDS including the International Prognostic Scoring System (IPSS), the Revised-IPSS (r-IPSS) and MDACC Scoring System. In this analysis, we compared those three classification schemas for their outcome predictability after HSCT. We analyzed 291 MDS patients with a median age of 55 (interquartile range (IQR) 47-60.7 years) who underwent HSCT between January 2001 and December 2011. Histology by WHO classification included RA/RARS 48 (16.5%), RCMD 28 (9.6%), RAEB-1 59 (20.2%), RAEB-2 63 (21.7%), MDS unclassified 67 (23%), and CMML 26 (9%). Of 291, 117 patients (40.2%) had therapy related MDS (t-MDS). Conditioning regimen was myeloablative in 201 patients (69.1%) and reduced intensity in 90 patients (30.9%). Donors were matched related (MRD), matched unrelated (MUD), mismatched (MMD) in 131 (45%), 114 (39.2%) and 46 (15.8%) patients respectively. Risk categorization was performed by IPSS, r-IPSS and MDACC scoring systems at the time of diagnosis. IPSS, r-IPSS and MDACC scoring systems could be assessed in 239 (82.1%), 241 (82.8%) and 231 (79.4%) patients respectively. The median follow up time of 109 survivors was 45 months. The median time from diagnosis to HSCT was 7.3 months (IQR 4.6-12.4 months). Three-year overall survival (OS) was 38.1% (95%CI 32.3-43.9) with 3-year event free survival (EFS) of 34.2% (95%CI 28.4-40). Cumulative relapse incidence (RI) at 3-year was 28.8% (95%CI 23.3-34.5). Cumulative incidence of treatment related mortality (TRM) at 3 year post-transplant was 27.9% (95%CI 22.6-33.6). In univariate analysis, IPSS and r-IPSS were able to differentiate 2 risk groups for OS and EFS. High risk group per IPSS and very high risk group per r-IPSS had lower OS with hazard ratio (HR) of 2.4 to 3.1, lower EFS with HR of 2.2 to 2.7. While IPSS could not predict RI, very high risk group by r-IPSS had higher RI with HR of 3.6 compared with lower risk groups. Both IPSS and r-IPSS did not identify different risk groups for TRM. On the other hand, MDACC scoring system was able to identify 4 different risk groups for EFS and OS in univariate analysis. Three-year OS was 68%, 46.1%, 30.3% and 11.4% for patients with MDACC risk score of 0-4, 5-6, 7-8 and ≥9 respectively (p<0.001) (figure1). Three-year EFS with MDACC risk score of 0-4, 5-6, 7-8 and ≥9 was 61.7%, 40.8%, 28.1% and 7.4% respectively (p<0.001). For RI and TRM, only MDACC risk scores of ≥9 was associated with poor outcomes with 3-year RI of 38.9% and 3-year TRM of 41.7% compared with 13.3% and 15.5% in risk scores of 0-4 (p=0.01 and p=0.01 respectively). In multivariate analysis, MDACC score, matched unrelated and mismatched donors were associated with inferior OS (table1). As a summary, MDACC risk scoring system for MDS better differentiates prognostic groups than IPSS or r-IPSS. Considering the high frequency of t-MDS among transplanted MDS patients, we propose that MDACC scoring system should be used for prognostic classification for hematopoietic transplantation. Disclosures: No relevant conflicts of interest to declare.

Comparison of SCORE and Reynolds cardiovascular risk assessments in a cohort without cardiovascular disease

2013 ◽  
Vol 154 (43) ◽  
pp. 1709-1712 ◽  
Author(s):  
Csaba Móczár
Keyword(s):  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Cardiovascular Risk ◽  
Screening Program ◽  
Risk Group ◽  
Scoring Systems ◽  
High Risk Group ◽  
Risk Assessments ◽  
Gender And Age ◽  
Medium Risk

Introduction: Cardiovascular risk assessment may help in the identification of symptom-free subjects with high cardiovascular risk. Aim: The author studied the correlation between SCORE and Reynolds risk assessment systems based on data from the cardiovascular risk screening program carried out in subjects without cardiovascular disease. Method: Data obtained from 4462 subjects (1977 men and 2485 women; mean age, 47,4 years) were analysed. The comparison was based on risk categories of the SCORE system. Results: There was a strong correlation between the two scoring systems in the low risk population (under <2% SCORE risk the Spearman rho = 1, p < 0.001). A weak correlation was found in the medium risk group (between 3–4% the Spearman rho = 0.59–0.49, p < 0.001 and between 10–14% the Spearman rho = 0.42, ns.) and a stronger correlation in the high risk group (>15% the Spearmen rho = 0.8, p = 0.017). When correlations were analysed in gender and age categories, the weakest correlation was detected in medium risk women over 40 years of age. In cases when the differences between the two scoring systems were significant, the hsCRP levels were significantly higher (4.1 vs. 5.67 mg/L, p < 0.001). Conclusions: Introduction of hsCRP into cardiovascular risk assessments can refine the risk status of symptom-free subjects, especially among intermediate risk middle-age women (two-step risk assessment). Orv. Hetil., 154 (43), 1709–1712.

Clinical impact of LncRNA XIST and LncRNA NEAT1 for diagnosis of high-risk group breast cancer patients

2021 ◽  
pp. 100709
Author(s):  
Menha Swellam ◽  
Hekmat M EL Magdoub ◽  
May A Shawki ◽  
Marwa Adel ◽  
Mona M Hefny ◽  
...  
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Group ◽  
High Risk Group ◽  
Clinical Impact ◽  
Breast Cancer Patients ◽  
Lncrna Xist ◽  
Lncrna Neat1

Exploration of Tumor Mutation Burden Combined with Immune Infiltrates in the Prognosis of Lung Adenocarcinoma

2021 ◽  
Author(s):  
Zhenyu Zhao ◽  
Boxue He ◽  
Qidong Cai ◽  
Pengfei Zhang ◽  
Xiong Peng ◽  
...  
Keyword(s):  
High Risk ◽  
Lung Adenocarcinoma ◽  
Clinical Application ◽  
Risk Group ◽  
High Risk Group ◽  
Immune Microenvironment ◽  
Tumor Mutation Burden ◽  
Immune Signature ◽  
Immune Infiltration ◽  
Mutation Burden

Abstract Background: Lung adenocarcinoma (LUAD) accounts for a majority of cancer-related deaths worldwide annually. A recent study shows that immunotherapy is an effective method of LUAD treatment, and tumor mutation burden (TMB) was associated with the immune microenvironment and affected the immunotherapy. Exploration of the gene signature associated with tumor mutation burden and immune infiltrates in predicting prognosis in lung adenocarcinoma in this study, we explored the correlation of TMB with immune infiltration and prognosis in LUAD.Materials and Methods: In this study, we firstly got mutation data and LUAD RNA-Seq data of the LUAD from The Cancer Genome Atlas (TCGA), and according to the TMB we divided the patients into high/low-TMB levels groups. The gene ontology (GO) pathway enrichment analysis and KOBAS-Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were utilized to explore the molecular function of the differentially expressed genes (DEGs) between the two groups. The function enrichment analyses of DEGs were related to the immune pathways. Then, the ESTIMATE algorithm, CIBERSORT, and ssGSEA analysis were utilized to identify the relationship between TMB subgroups and immune infiltration. According to the results, Venn analysis was utilized to select the immune-related genes in DEGs. Univariate and Lasso Cox proportional hazards regression analyses were performed to construct the signature which positively associated with the immune infiltration and affected the survival. Finally, we verified the correlation between the signature and immune infiltration. Result: The exploration of the immune infiltration suggested that high-TMB subgroups positively associated with the high level of immune infiltration in LUAD patients. According to the TMB-related immune signature, the patients were divided into High/Low-risk groups, and the high-risk group was positively associated with poor prognostic. The results of the PCA analysis confirmed the validity of the signature. We also verified the effectiveness of the signature in GSE30219 and GSE72094 datasets. The ROC curves and C-index suggested the good clinical application of the TMB-related immune signature in LUAD prognosis. Another result suggested that the patients of the high-risk group were positively associated with higher TMB levels, PD-L1expression, and immune infiltration levels.Conclusion: In conclusion, our signature provides potential biomarkers for studying aspects of the TMB in LUAD such as TMB affected immune microenvironment and prognosis. This signature may provide some biomarkers which could improve the biomarkers of PD-L1 immunotherapy response and were inverted for the clinical application of the TMB in LUAD. LUAD male patients with higher TMB-levels and risk scores may benefit from immunotherapy. The high-risk patients along with higher PD-L1 expression of the signature may suitable for immunotherapy and improve their survival by detecting the TMB of LUAD.

scholarly journals A model for predicting carotid instability plaque in high risk group of stroke individuals

2019 ◽  
Author(s):  
Junxiong Yin ◽  
Chuanyong Yu ◽  
Hongxing Liu ◽  
Mingyang Du ◽  
Feng Sun ◽  
...  
Keyword(s):  
Risk Factors ◽  
High Risk ◽  
Predictive Model ◽  
Doppler Ultrasound ◽  
Scoring System ◽  
Risk Group ◽  
High Risk Group ◽  
High Risk Population ◽  
Auc Value ◽  
Validation Set

Abstract Objective: To establish a predictive model of carotid vulnerable plaque through systematic screening of high-risk population for stroke.Patients and methods: All community residents who participated in the screening of stroke high-risk population by the China National Stroke Screening and Prevention Project (CNSSPP). A total of 19 risk factors were analyzed. Individuals were randomly divided into Derivation Set group and Validation Set group. According to carotid ultrasonography, the derivation set group patients were divided into instability plaque group and non-instability plaque group. Univariate and multivariable logistic regression were taken for risk factors. A predictive model scoring system were established by the coefficient. The AUC value of both derivation and validation set group were used to verify the effectiveness of the model.Results: A total of 2841 high-risk stroke patients were enrolled in this study, 266 (9.4%) patients were found instability plaque. According to the results of Doppler ultrasound, Derivation Set group were divided into instability plaque group (174 cases) and non-instability plaque group (1720 cases). The independent risk factors for carotid instability plaque were: male (OR 1.966, 95%CI 1.406-2.749)，older age (50-59, OR 6.012, 95%CI 1.410-25.629; 60-69, OR 13.915, 95%CI 3.381-57.267;≥70, OR 31.267, 95%CI 7.472-130.83) , married(OR 1.780, 95%CI 1.186-2.672)，LDL-c(OR 2.015, 95%CI 1.443-2.814), and HDL-C(OR 2.130, 95%CI 1.360-3.338). A predictive scoring system was created, range 0-10. The cut-off value of prediction model score is 6.5. The AUC value of derivation and validation set group were 0.738 and 0.737.Conclusion：For a high risk group of stroke individual, We provide a model that could distinguishing those who have a high probability of having carotid instability plaque. When resident’s predictive model score exceeds 6.5, the incidence of carotid instability plaque is high, carotid artery Doppler ultrasound would be checked immediately. This model can be helpful in the primary prevention of stroke.

Adjuvant Chemotherapy Guidance for pT1-3N0-1 Breast Cancer Patients with HR+, HER2- subtype: a study based on SEER database

2021 ◽  
Author(s):  
juanjuan Qiu ◽  
Li Xu ◽  
Yu Wang ◽  
Jia Zhang ◽  
Jiqiao Yang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
High Risk ◽  
Cancer Patients ◽  
Risk Group ◽  
High Risk Group ◽  
Low Risk ◽  
Rank Test ◽  
Breast Cancer Patients ◽  
Group Score

Abstract Background Although the results of gene testing can guide early breast cancer patients with HR+, HER2- to decide whether they need chemotherapy, there are still many patients worldwide whose problems cannot be solved well by genetic testing. Methods 144 735 patients with HR+, HER2-, pT1-3N0-1 breast cancer from the Surveillance, Epidemiology, and End Results database were included from 2010 to 2015. They were divided into chemotherapy (n = 38 392) and no chemotherapy (n = 106 343) group, and after propensity score matching, 23 297 pairs of patients were left. Overall survival (OS) and breast cancer-specific survival (BCSS) were tested by Kaplan–Meier plot and log-rank test and Cox proportional hazards regression model was used to identify independent prognostic factors. A nomogram was constructed and validated by C-index and calibrate curves. Patients were divided into high- or low-risk group according to their nomogram score using X-tile. Results Patients receiving chemotherapy had better OS before and after matching (p < 0.05) but BCSS was not significantly different between patients with and without chemotherapy after matching: hazard ratio (HR) 1.005 (95%CI 0.897, 1.126). Independent prognostic factors were included to construct the nomogram to predict BCSS of patients without chemotherapy. Patients in the high-risk group (score > 238) can get better OS HR 0.583 (0.507, 0.671) and BCSS HR 0.791 (0.663, 0.944) from chemotherapy but the low-risk group (score ≤ 238) cannot. Conclusion The well-validated nomogram and a risk stratification model was built. Patients in the high-risk group should receive chemotherapy while patients in low-risk group may be exempt from chemotherapy.

scholarly journals Determination of Risk Factors for Venous Thromboembolism by an Adapted Caprini Scoring System in Surgical Patients

2019 ◽  
Vol 9 (3) ◽  
pp. 36 ◽  
Author(s):  
Bui My Hanh ◽  
Le Quang Cuong ◽  
Nguyen Truong Son ◽  
Duong Tuan Duc ◽  
Tran Tien Hung ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Venous Thromboembolism ◽  
Scoring System ◽  
Risk Group ◽  
Risk Groups ◽  
High Risk Group ◽  
Assessment Model ◽  
Surgical Patients ◽  
Risk Scoring

Venous thromboembolism (VTE) is a frequent preventable complication among surgical patients. Precise risk assessment is a necessary step for providing appropriate thromboprophylaxis and reducing mortality as well as morbidity caused by VTE. We carried out this work to define the rate of VTE postoperatively, following a Caprini score, and to determine VTE risk factors through a modified Caprini risk scoring system. This multicenter, observational, cohort study involved 2,790,027 patients who underwent surgery in four Vietnamese hospitals from 01/2017 to 12/2018. All patients who were evaluated before surgery by using a Caprini risk assessment model (RAM) and monitored within 90 days after surgery. The endpoint of the study was ultrasound-confirmed VTE. Our data showed that the 90-day postoperative VTE was found in 3068 patients. Most of VTE (46.97%) cases were found in the highest risk group (Caprini score > 5). A total of 37.19% were observed in the high risk group, while the rest (15.84%) were from low to moderate risk groups. The likelihood of occurring VTE was heightened 2.83 times for patients with a Caprini score of 3–4, 4.83 times for a Caprini score of 5–6, 8.84 times for a score of 7–8, and 11.42 times for a score of >8, comparing to ones with a score of 0 to 2 (all p values < 0.05). Thus, the frequency of postoperative VTE rises substantially, according to the advanced Caprini score. Further categorizing patients among the highest risk group need delivering more appropriate thromboprophylaxis.

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