scholarly journals A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Na Sun ◽  
Jiadong Chu ◽  
Wei Hu ◽  
Xuanli Chen ◽  
Nengjun Yi ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Prognostic Model ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
External Validation ◽  
Gene Signature ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Bayesian Hierarchical ◽  
Hazards Model

AbstractThere have been few investigations of cancer prognosis models based on Bayesian hierarchical models. In this study, we used a novel Bayesian method to screen mRNAs and estimate the effects of mRNAs on the prognosis of patients with lung adenocarcinoma. Based on the identified mRNAs, we can build a prognostic model combining mRNAs and clinical features, allowing us to explore new molecules with the potential to predict the prognosis of lung adenocarcinoma. The mRNA data (n = 594) and clinical data (n = 470) for lung adenocarcinoma were obtained from the TCGA database. Gene set enrichment analysis (GSEA), univariate Cox proportional hazards regression, and the Bayesian hierarchical Cox proportional hazards model were used to explore the mRNAs related to the prognosis of lung adenocarcinoma. Multivariate Cox proportional hazard regression was used to identify independent markers. The prediction performance of the prognostic model was evaluated not only by the internal cross-validation but also by the external validation based on the GEO dataset (n = 437). With the Bayesian hierarchical Cox proportional hazards model, a 14-gene signature that included CPS1, CTPS2, DARS2, IGFBP3, MCM5, MCM7, NME4, NT5E, PLK1, POLR3G, PTTG1, SERPINB5, TXNRD1, and TYMS was established to predict overall survival in lung adenocarcinoma. Multivariate analysis demonstrated that the 14-gene signature (HR 3.960, 95% CI 2.710–5.786), T classification (T1, reference; T3, HR 1.925, 95% CI 1.104–3.355) and N classification (N0, reference; N1, HR 2.212, 95% CI 1.520–3.220; N2, HR 2.260, 95% CI 1.499–3.409) were independent predictors. The C-index of the model was 0.733 and 0.735, respectively, after performing cross-validation and external validation, a nomogram was provided for better prediction in clinical application. Bayesian hierarchical Cox proportional hazards models can be used to integrate high-dimensional omics information into a prediction model for lung adenocarcinoma to improve the prognostic prediction and discover potential targets. This approach may be a powerful predictive tool for clinicians treating malignant tumours.

scholarly journals Use of the Living Kidney Donor Profile Index in the Canadian Kidney Transplant Recipient Population: A Validation Study

2020 ◽  
Vol 7 ◽  
pp. 205435812090697
Author(s):  
Mohamed Shantier ◽  
Yanhong Li ◽  
Monika Ashwin ◽  
Olsegun Famure ◽  
Sunita K. Singh
Keyword(s):  
Validation Study ◽  
Graft Failure ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
External Validation ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Living Kidney Donor ◽  
Hazards Model

Background: The Living Kidney Donor Profile Index (LKDPI) was derived in a cohort of kidney transplant recipients (KTR) from the United States to predict the risk of total graft failure. There are important differences in patient demographics, listing practices, access to transplantation, delivery of care, and posttransplant mortality in Canada as compared with the United States, and the generalizability of the LKDPI in the Canadian context is unknown. Objective: The purpose of this study was to externally validate the LKDPI in a large contemporary cohort of Canadian KTR. Design: Retrospective cohort validation study. Setting: Toronto General Hospital, University Health Network, Toronto, Ontario, Canada Patients: A total of 645 adult (≥18 years old) living donor KTR between January 1, 2006 and December 31, 2016 with follow-up until December 31, 2017 were included in the study. Measurements: The predictive performance of the LKDPI was evaluated. The outcome of interest was total graft failure, defined as the need for chronic dialysis, retransplantation, or death with graft function. Methods: The Cox proportional hazards model was used to examine the relation between the LKDPI and total graft failure. The Cox proportional hazards model was also used for external validation and performance assessment of the model. Discrimination and calibration were used to assess model performance. Discrimination was assessed using Harrell’s C statistic and calibration was assessed graphically, comparing observed versus predicted probabilities of total graft failure. Results: A total of 645 living donor KTR were included in the study. The median LKDPI score was 13 (interquartile range [IQR] = 1.1, 29.9). Higher LKDPI scores were associated with an increased risk of total graft failure (hazard ratio = 1.01; 95% confidence interval [CI] = 1.0-1.02; P = .02). Discrimination was poor (C statistic = 0.55; 95% CI = 0.48-0.61). Calibration was as good at 1-year posttransplant but suboptimal at 3- and 5-years posttransplant. Limitations: Limitations include a relatively small sample size, predicted probabilities for assessment of calibration only available for scores of 0 to 100, and some missing data handled by imputation. Conclusions: In this external validation study, the predictive ability of the LKDPI was modest in a cohort of Canadian KTR. Validation of prediction models is an important step to assess performance in external populations. Potential recalibration of the LKDPI may be useful prior to clinical use in external cohorts.

Comorbidities and Overall Survival In Myelodysplastic Syndromes (MDS): Development of a Prognostic Model Incorporating IPSS and Age with ACE-27 Comorbidity Index

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 605-605 ◽  
Author(s):  
Kiran Naqvi ◽  
Maria E Suarez-Almazor ◽  
Sagar Sardesai ◽  
Jeong Oh ◽  
Carlos Vigil ◽  
...  
Keyword(s):  
Median Survival ◽  
Prognostic Model ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Risk Group ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Kaplan Meier ◽  
Comorbidity Scores

Abstract Abstract 605 Background: Cancer patients often experience comorbidities that may affect their therapeutic options, prognosis, and outcome. Limited studies have evaluated the characteristics and impact of comorbidities in MDS. The aim of this study was to determine the effect of comorbidities on the survival of patients with MDS. Methods: We reviewed the medical records of 600 consecutive MDS patients who presented to MD Anderson Cancer Center from 01–2002 to 06–2004. The Adult Comorbidity Evaluation-27 (ACE-27), a validated 27-item comorbidity index for cancer patients, was used to assess the severity of comorbid conditions. Data on demographic characteristics, International Prognostic Scoring System (IPSS), stem cell transplant (SCT) and outcomes (leukemic transformation and survival) was collected. Kaplan-Meier methods and log-rank tests were used to assess survival. Multivariate analysis was performed using the Cox Proportional Hazards Model. A prognostic model incorporating baseline comorbidities with age and IPSS was developed to predict survival. A score point for each significant factor (age, IPSS and ACE-27 comorbidity score) was obtained by dividing respective coefficients from the multivariate model by 0.3 and rounding to the nearest integer. Results: Of the 600 patients included in this study, 400 (65.7%) were male, and 518 (87.1%) were white; median age at presentation was 66.6 years (range 17.3 – 93.5); median duration of follow-up was 14.8 months (range 0–88). The ACE-27 comorbidity scores were as follows: none, 137 patients (28.8%); mild, 254 (42.3%); moderate, 127 (21.2%); and severe, 82 (13.7%). Four hundred and fifty six (76.0%) patients died, 123 (20.5%) suffered leukemic transformation and 51 (8.5%) patients underwent SCT. Overall median survival using the Kaplan-Meier method was 18.6 months. Median survival according to ACE-27 scores was: 31.8, 16.8, 15.2 and 9.7 months for none, mild, moderate and severe comorbidity scores respectively (p < 0.0001). The adjusted hazards ratios from the multivariate Cox Proportional Hazards Model were 1.3, 1.6 and 2.3 for mild, moderate and severe comorbidity scores when adjusted for age and IPSS (p < 0.0001). A final prognostic model incorporating comorbidity score with age and IPSS was developed. A risk score was derived based on the regression coefficients from the final multivariate model. The score points assigned were: Age > 65 years=2; IPSS of Intermediate-2= 2 and High= 3; ACE-27 score of mild or moderate= 1 and Severe= 3. Based upon their risk scores, patients were categorized into 3 groups: low (0 - 1), intermediate (2 - 4) and high (5 – 8). Almost 50% of the patients in our study were noted to be in the intermediate category with a median survival of 23 months. The model confirmed a better survival in patients in low risk group of 43 months versus 9 months in the high risk group (p < 0.001). Conclusion: Comorbidities had a significant impact on the survival of patients with myelodysplastic syndrome. Patients with higher ACE-27 comorbidity scores had a shorter survival than those with no comorbidity, independent of their age and the IPSS risk group. A comprehensive assessment of comorbidity is therefore needed to determine the prognosis in patients with MDS. Our newly developed prognostic model helps predict survival in such patients based on their comorbidities. Disclosures: No relevant conflicts of interest to declare.

scholarly journals Systematical identifications of prognostic meaningful lung adenocarcinoma subtypes and the underlying mutational and expressional characters

2019 ◽  
Author(s):  
Ting Lei ◽  
Zhenyang Lv
Keyword(s):  
Lung Adenocarcinoma ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Comprehensive Description ◽  
Common Cancer ◽  
Master Genes ◽  
Hazards Model ◽  
Cancer Types

Abstract Lung adenocarcinoma (LUAD) is one of the most common cancer types. However, the high heterogeneity and complexity of LUAD hinder effective treatments. This study aimed to identify the key prognosis impacting genes and the corresponding subtypes for LUAD. Specifically, the cox proportional hazards model was combined with a causal regulatory network to help reveal which genes play master roles among numerous prognosis impacting genes, and sub-types were identified based on expressional profiles of the master genes. As results, a collection of 75 genes were recognized as the master prognosis impacting genes, where some were enriched in mTOR signaling and lysosome pathways. Based on their expressions, the LUAD patients were separated into two sub-types displaying remarkable differences in expressional profiles, prognostic outcomes and genomic mutations. Meanwhile, the two subtypes were re-discovered from two additional LUAD cohorts based on only the top-10 important master genes. This study provides a comprehensive description on the key prognosis-relevant genes and an alternative way to classify LUAD subtypes which can promote LUAD precision treatment.

scholarly journals Systematical identifications of prognostic meaningful lung adenocarcinoma subtypes and the underlying mutational and expressional characters

2019 ◽  
Author(s):  
Ting Lei ◽  
Zhenyang Lv
Keyword(s):  
Lung Adenocarcinoma ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Comprehensive Description ◽  
Common Cancer ◽  
Master Genes ◽  
Hazards Model ◽  
Cancer Types

Abstract Lung adenocarcinoma (LUAD) is one of the most common cancer types. However, the high heterogeneity and complexity of LUAD hinder effective treatments. This study aimed to identify the key prognosis impacting genes and the corresponding subtypes for LUAD. Specifically, the cox proportional hazards model was combined with a causal regulatory network to help reveal which genes play master roles among numerous prognosis impacting genes, and sub-types were identified based on expressional profiles of the master genes. As results, a collection of 75 genes were recognized as the master prognosis impacting genes, where some were enriched in mTOR signaling and lysosome pathways. Based on their expressions, the LUAD patients were separated into two sub-types displaying remarkable differences in expressional profiles, prognostic outcomes and genomic mutations. Meanwhile, the two subtypes were re-discovered from two additional LUAD cohorts based on only the top-10 important master genes. This study provides a comprehensive description on the key prognosis-relevant genes and an alternative way to classify LUAD subtypes which can promote LUAD precision treatment.

scholarly journals Risk factors associated with major adverse cardiac and cerebrovascular events following percutaneous coronary intervention: a 10-year follow-up comparing random survival forest and Cox proportional-hazards model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Maryam Farhadian ◽  
Sahar Dehdar Karsidani ◽  
Azadeh Mozayanimonfared ◽  
Hossein Mahjub
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Coronary Intervention ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Cerebrovascular Events ◽  
Long Term Follow Up ◽  
Stent Length

Abstract Background Due to the limited number of studies with long term follow-up of patients undergoing Percutaneous Coronary Intervention (PCI), we investigated the occurrence of Major Adverse Cardiac and Cerebrovascular Events (MACCE) during 10 years of follow-up after coronary angioplasty using Random Survival Forest (RSF) and Cox proportional hazards models. Methods The current retrospective cohort study was performed on 220 patients (69 women and 151 men) undergoing coronary angioplasty from March 2009 to March 2012 in Farchshian Medical Center in Hamadan city, Iran. Survival time (month) as the response variable was considered from the date of angioplasty to the main endpoint or the end of the follow-up period (September 2019). To identify the factors influencing the occurrence of MACCE, the performance of Cox and RSF models were investigated in terms of C index, Integrated Brier Score (IBS) and prediction error criteria. Results Ninety-six patients (43.7%) experienced MACCE by the end of the follow-up period, and the median survival time was estimated to be 98 months. Survival decreased from 99% during the first year to 39% at 10 years' follow-up. By applying the Cox model, the predictors were identified as follows: age (HR = 1.03, 95% CI 1.01–1.05), diabetes (HR = 2.17, 95% CI 1.29–3.66), smoking (HR = 2.41, 95% CI 1.46–3.98), and stent length (HR = 1.74, 95% CI 1.11–2.75). The predictive performance was slightly better by the RSF model (IBS of 0.124 vs. 0.135, C index of 0.648 vs. 0.626 and out-of-bag error rate of 0.352 vs. 0.374 for RSF). In addition to age, diabetes, smoking, and stent length, RSF also included coronary artery disease (acute or chronic) and hyperlipidemia as the most important variables. Conclusion Machine-learning prediction models such as RSF showed better performance than the Cox proportional hazards model for the prediction of MACCE during long-term follow-up after PCI.

scholarly journals Elevated plasma growth and differentiation factor 15 predicts incident anemia in older adults aged 60 years and older

2020 ◽  
Author(s):  
Yuko Yamaguchi ◽  
Marta Zampino ◽  
Toshiko Tanaka ◽  
Stefania Bandinelli ◽  
Yusuke Osawa ◽  
...  
Keyword(s):  
Older Adults ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Differentiation Factor ◽  
Hazards Model ◽  
Increased Risk ◽  
The Relationship

Abstract Background Anemia is common in older adults and associated with greater morbidity and mortality. The causes of anemia in older adults have not been completely characterized. Although elevated circulating growth and differentiation factor 15 (GDF-15) has been associated with anemia in older adults, it is not known whether elevated GDF-15 predicts the development of anemia. Methods We examined the relationship between plasma GDF-15 concentrations at baseline in 708 non-anemic adults, aged 60 years and older, with incident anemia during 15 years of follow-up among participants in the Invecchiare in Chianti (InCHIANTI) Study. Results During follow-up, 179 (25.3%) participants developed anemia. The proportion of participants who developed anemia from the lowest to highest quartile of plasma GDF-15 was 12.9%, 20.1%, 21.2%, and 45.8%, respectively. Adults in the highest quartile of plasma GDF-15 had an increased risk of developing anemia (Hazards Ratio 1.15, 95% Confidence Interval 1.09, 1.21, P&lt;.0001) compared to those in the lower three quartiles in a multivariable Cox proportional hazards model adjusting for age, sex, serum iron, soluble transferrin receptor, ferritin, vitamin B12, congestive heart failure, diabetes mellitus, and cancer. Conclusions Circulating GDF-15 is an independent predictor for the development of anemia in older adults.

scholarly journals Dementia Adjudication Triggers Associated With Increased Mortality for Older Australians: Evidence From ASPREE

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 161-161
Author(s):  
Jane Banaszak-Holl ◽  
Xiaoping Lin ◽  
Jing Xie ◽  
Stephanie Ward ◽  
Henry Brodaty ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
The Elderly ◽  
Cox Proportional Hazards ◽  
Service Planning ◽  
Cox Proportional Hazards Model ◽  
Cognitive Test ◽  
Risk Of Death ◽  
Hazards Model ◽  
Using Data

Abstract Research Aims: This study seeks to understand whether those with dementia experience higher risk of death, using data from the ASPREE (ASPirin in Reducing Events in the Elderly) clinical trial study. Methods: ASPREE was a primary intervention trial of low-dose aspirin among healthy older people. The Australian cohort included 16,703 dementia-free participants aged 70 years and over at enrolment. Participants were triggered for dementia adjudication if cognitive test results were poorer than expected, self-reporting dementia diagnosis or memory problems, or dementia medications were detected. Incidental dementia was adjudicated by an international adjudication committee using the Diagnostic and Statistical Manual for Mental Disorders (DSM-IV) criteria and results of a neuropsychological battery and functional measures with medical record substantiation. Statistical analyses used a cox proportional hazards model. Results: As previously reported, 1052 participants (5.5%) died during a median of 4.7 years of follow-up and 964 participants had a dementia trigger, of whom, 575 (60%) were adjucated as having dementia. Preliminary analyses has shown that the mortality rate was higher among participants with a dementia trigger, regardless of dementia adjudication outcome, than those without (15% vs 5%, Χ2 = 205, p &lt;.001). Conclusion: This study will provide important analyses of differences in the hazard ratio for mortality and causes of death among people with and without cognitive impairment and has important implications on service planning.

scholarly journals Evaluation of Changes on World Stock Exchanges in Connection with the SARS-CoV-2 Pandemic. Survival Analysis Methods

Risks ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 121
Author(s):  
Beata Bieszk-Stolorz ◽  
Krzysztof Dmytrów
Keyword(s):  
Survival Analysis ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Stock Exchange ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Stock Exchanges ◽  
Analysis Methods ◽  
Hazards Model ◽  
Kaplan Meier

The aim of our research was to compare the intensity of decline and then increase in the value of basic stock indices during the SARS-CoV-2 coronavirus pandemic in 2020. The survival analysis methods used to assess the risk of decline and chance of rise of the indices were: Kaplan–Meier estimator, logit model, and the Cox proportional hazards model. We observed the highest intensity of decline in the European stock exchanges, followed by the American and Asian plus Australian ones (after the fourth and eighth week since the peak). The highest risk of decline was in America, then in Europe, followed by Asia and Australia. The lowest risk was in Africa. The intensity of increase was the highest in the fourth and eleventh week since the minimal value had been reached. The highest odds of increase were in the American stock exchanges, followed by the European and Asian (including Australia and Oceania), and the lowest in the African ones. The odds and intensity of increase in the stock exchange indices varied from continent to continent. The increase was faster than the initial decline.

scholarly journals Association between milk and yogurt intake and mortality: a community-based cohort study (Yamagata study)

BMC Nutrition ◽  
2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Akiko Nakanishi ◽  
Erika Homma ◽  
Tsukasa Osaki ◽  
Ri Sho ◽  
Masayoshi Souri ◽  
...  
Keyword(s):  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Hazard Analysis ◽  
Total Mortality ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Milk Intake ◽  
Community Based ◽  
Hazards Model ◽  
Kaplan Meier

Abstract Background Dairy products are known as health-promoting foods. This study prospectively examined the association between milk and yogurt intake and mortality in a community-based population. Methods The study population comprised of 14,264 subjects aged 40–74 years who participated in an annual health checkup. The frequency of yogurt and milk intake was categorized as none (< 1/month), low (< 1/week), moderate (1–6/week), and high (> 1/day) intake. The association between yogurt and milk intake and total, cardiovascular, and cancer-related mortalities was determined using the Cox proportional hazards model. Results During the follow-up period, there were 265 total deaths, 40 cardiovascular deaths and 90 cancer-related deaths. Kaplan–Meier analysis showed that the total mortality in high/moderate/low yogurt intake and moderate/low milk intake groups was lower than that in none group (log-rank, P < 0.01). In the multivariate Cox proportional hazard analysis adjusted for possible confounders, the hazard ratio (HR) for total mortality significantly decreased in high/moderate yogurt intake group (HR: 0.62, 95% confidence interval [CI]: 0.42–0.91 for high intake, HR: 0.70, 95%CI: 0.49–0.99 for moderate intake) and moderate milk intake group (HR: 0.67, 95% CI: 0.46–0.97) compared with the none yogurt and milk intake groups. A similar association was observed for cancer-related mortality, but not for cardiovascular mortality. Conclusions Our study showed that yogurt and milk intake was independently associated with a decrease in total and cancer-related mortalities in the Japanese population.

Sign in / Sign up

Export Citation Format

Share Document