Early identification of symptomatic aortic stenosis using echocardiographic data

Background: Heart failure (CHF) is the most frequent and prognostically severe symptom of aortic stenosis (AS), and the most common indication for surgery. The mainstay of treatment for AS is aortic valve replacement (AVR), and the main indication for an AVR is development of symptomatic disease. ACC/AHA guidelines define severe AS as an aortic valve area (AVA) ≤1cm², but there is little data correlating echocardiogram AVA with the onset of symptomatic CHF. We evaluated the risk of developing CHF with progressively decreasing echocardiographic AVA. We also compared echocardiographic AVA with Jet velocity (V2) and indexed AVA (AVAI) to assess the best predictor of development of symptomatic CHF.^ Methods and Results: This retrospective cohort study evaluated 518 patients with asymptomatic moderate or severe AS from a single community based cardiology practice. A total of 925 echocardiograms were performed over an 11-year period. Each echocardiogram was correlated with concurrent clinical assessments while the investigator was blinded to the echocardiogram severity of AS. The Cox Proportional hazards model was used to analyze the relationship between AVA and the development of CHF. The median age of patients at entry was 76.1 years, with 54% males. A total of 116 patients (21.8%) developed new onset CHF during follow-up. Compared to patients with AVA >1.0cm², patients with lower AVA had an exponentially increasing risk of developing CHF for each 0.2cm² decrement in AVA, becoming statistically significant only at an AVA less than 0.8 cm². Also, compared to V2 and AVAI, AVA added more information to assessing risk for development of CHF (p=0.041). ^ Conclusion: In patients with normal or mildly impaired LVEF, the risk of CHF rises exponentially with decreasing valve area and becomes statistically significant after AVA falls below 0.8cm². AVA is a better predictor of CHF when compared to V2 or AVAI.^

Genetic variants in the mammalian target of rapamycin (mTOR) signaling pathway as predictors of survival and clinical response in women with ovarian cancer

Background. The mTOR pathway is commonly altered in human tumors and promotes cell survival and proliferation. Preliminary evidence suggests this pathway's involvement in chemoresistance to platinum and taxanes, first line therapy for epithelial ovarian cancer. A pathway-based approach was used to identify individual germline single nucleotide polymorphisms (SNPs) and cumulative effects of multiple genetic variants in mTOR pathway genes and their association with clinical outcome in women with ovarian cancer. ^ Methods. The case-series was restricted to 319 non-Hispanic white women with high grade ovarian cancer treated with surgery and platinum-based chemotherapy. 135 SNPs in 20 representative genes in the mTOR pathway were genotyped. Hazard ratios (HRs) for death and Odds ratios (ORs) for failure to respond to primary therapy were estimated for each SNP using the multivariate Cox proportional hazards model and multivariate logistic regression model, respectively, while adjusting for age, stage, histology and treatment sequence. A survival tree analysis of SNPs with a statistically significant association (p<0.05) was performed to identify higher order gene-gene interactions and their association with overall survival. ^ Results. There was no statistically significant difference in survival by tumor histology or treatment regimen. The median survival for the cohort was 48.3 months. Seven SNPs were significantly associated with decreased survival. Compared to those with no unfavorable genotypes, the HR for death increased significantly with the increasing number of unfavorable genotypes and women in the highest risk category had HR of 4.06 (95% CI 2.29–7.21). The survival tree analysis also identified patients with different survival patterns based on their genetic profiles. 13 SNPs on five different genes were found to be significantly associated with a treatment response, defined as no evidence of disease after completion of primary therapy. Rare homozygous genotype of SNP rs6973428 showed a 5.5-fold increased risk compared to the wild type carrying genotypes. In the cumulative effect analysis, the highest risk group (individuals with ≥8 unfavorable genotypes) was significantly less likely to respond to chemotherapy (OR=8.40, 95% CI 3.10–22.75) compared to the low risk group (≤4 unfavorable genotypes). ^ Conclusions. A pathway-based approach can demonstrate cumulative effects of multiple genetic variants on clinical response to chemotherapy and survival. Therapy targeting the mTOR pathway may modify outcome in select patients.^

Risk factors of pneumonia in traumatic spinal-cord-injured patients

Pneumonia is a well-documented and common respiratory infection in patients with acute traumatic spinal cord injuries, and may recur during the course of acute care. Using data from the North American Clinical Trials Network (NACTN) for Spinal Cord Injury, the incidence, timing, and recurrence of pneumonia were analyzed. The two main objectives were (1) to investigate the time and potential risk factors for the first occurrence of pneumonia using the Cox Proportional Hazards model, and (2) to investigate pneumonia recurrence and its risk factors using a Counting Process model that is a generalization of the Cox Proportional Hazards model. The results from survival analysis suggested that surgery, intubation, American Spinal Injury Association (ASIA) grade, direct admission to a NACTN site and age (older than 65 or not) were significant risks for first event of pneumonia and multiple events of pneumonia. The significance of this research is that it has the potential to identify patients at the time of admission who are at high risk for the incidence and recurrence of pneumonia. Knowledge and the time of occurrence of pneumonias are important factors for the development of prevention strategies and may also provide some insights into the selection of emerging therapies that compromise the immune system. ^

Adaptive clinical trial design for targeted therapy development

The development of targeted therapy involve many challenges. Our study will address some of the key issues involved in biomarker identification and clinical trial design. In our study, we propose two biomarker selection methods, and then apply them in two different clinical trial designs for targeted therapy development. In particular, we propose a Bayesian two-step lasso procedure for biomarker selection in the proportional hazards model in Chapter 2. In the first step of this strategy, we use the Bayesian group lasso to identify the important marker groups, wherein each group contains the main effect of a single marker and its interactions with treatments. In the second step, we zoom in to select each individual marker and the interactions between markers and treatments in order to identify prognostic or predictive markers using the Bayesian adaptive lasso. In Chapter 3, we propose a Bayesian two-stage adaptive design for targeted therapy development while implementing the variable selection method given in Chapter 2. In Chapter 4, we proposed an alternate frequentist adaptive randomization strategy for situations where a large number of biomarkers need to be incorporated in the study design. We also propose a new adaptive randomization rule, which takes into account the variations associated with the point estimates of survival times. In all of our designs, we seek to identify the key markers that are either prognostic or predictive with respect to treatment. We are going to use extensive simulation to evaluate the operating characteristics of our methods.^

Prevalência do baixo nível de atividade física e sua associação no comprometimento da mobilidade e risco para óbito em idosos residentes no município de São Paulo

Introdução: Em 2008, o baixo nível de atividade física (< 30 min de atividade moderada/vigorosa por dia) foi responsável por 9 por cento da ocorrência de óbito no mundo. Além disso, está associado ao comprometimento de mobilidade em idosos com 80 anos e mais. No entanto, devido a dificuldades metodológicas, poucos são os estudos populacionais que realizaram a associação entre baixo nível de atividade física e comprometimento de mobilidade e risco para óbito, utilizando método objetivo para avaliação da atividade física, e ainda não se tem conhecimento de pesquisas que verificaram essa associação na América Latina. Objetivo: Identificar a prevalência do baixo nível de atividade física e sua associação com o comprometimento da mobilidade e risco para óbito em idosos com 65 anos e mais residentes no município de São Paulo em 2010. Métodos: Estudo exploratório e quantitativo de base populacional, que utilizou a base de dados do Estudo SABE de 2010 e ocorrência de óbito em 2014. Foram avaliados 599 indivíduos em 2010. O nível de atividade física foi analisado de duas maneiras: 1) baixo nível de atividade física (< 30 minutos de atividade moderada e/ou vigorosa por dia) e alto nível de atividade física (> 30 minutos de atividade moderada e/ou vigorosa por dia); e 2) a amostra foi distribuída em tercis, de acordo com as contagens por minuto, e agrupada em dois grupos, sendo os idosos do mais baixo tercil classificados com baixo nível de atividade física e os idosos dos dois outros tercis como intermediário/alto nível de atividade física. A regressão logística hierárquica foi utilizada para: 1) identificar as variáveis associadas ao baixo nível de atividade física; 2) analisar a associação do baixo nível de atividade física no comprometimento da mobilidade; e 3) estimar o risco para óbito em idosos com baixo nível de atividade física. A curva de sobrevida foi analisada com o método de Kaplan-Meier utilizando o teste de log-rank e o risco proporcional foi calculado pelo modelo de risco proporcional de Cox. Resultados: A prevalência de baixo nível de atividade física em idosos foi de 85,4 por cento e as variáveis associadas, após ajuste, foram sexo (feminino), grupo etário (>75 anos), multimorbidade (> 2 doenças crônicas), dor crônica (dor crônica nos últimos 3 meses) e índice de massa corporal (maior valor médio). O baixo nível de atividade física permaneceu significativamente associado ao comprometimento de mobilidade (OR= 3,49; IC95 por cento = 2,00 6,13) e ao risco para (RP= 2,79; IC95 por cento = 1,71 4,57), mesmo após ajuste das variáveis sóciodemográficas e clínicas. Conclusão: A prevalência do baixo nível de atividade física em pessoas idosas residentes no Município de São Paulo é superior aos encontrados na população brasileira, mas se aproxima de outras populações que utilizaram o mesmo método de avaliação da atividade física. O baixo nível de atividade física (< 30 min de atividades moderadas/vigorosas) foi associado com variáveis sociodemográficas (sexo feminino e grupo etário) e clínicas (multimorbidade, dor crônica e índice de massa corporal). O baixo nível de atividade física (menor tercil de contagens por minuto) foi associado ao comprometimento de mobilidade e risco para óbito em quatro anos. Dessa forma, o baixo nível de atividade física pode ser utilizado como uma forma adequada para identificar idosos com maiores chances de apresentar comprometimento da mobilidade e aumento do risco para óbito.

Sobrevida de mulheres e homens com 60 anos e mais no município de São Paulo - Estudo SABE: as diferenças nas semelhanças em características do curso de vida

Objetivos: Avaliar numa coorte de idosos se há diferenças entre as situações do curso de vida que contribuem para uma maior chance de sobrevida em homens e mulheres com 60 anos e mais. Métodos: 2.143 idosos entrevistados em 2000 foram acompanhados durante quase 15 anos. Utilizou-se na análise estatística o teste de associação para amostras complexas (Rao-Scott), o estimador produto limite de Kaplan-Meier, o teste de log-rank, análise univariada e multivariada do modelo de riscos proporcionais de Cox, sendo construídos, através deste último, dois modelos finais por gênero, ao nível de significância de 5 por cento . Resultados e discussão: Dos 836.204 idosos paulistanos representados pelo estudo 51,6 por cento continuavam vivos (43,0 por cento dos homens e 57,7 por cento das mulheres). Em ambos os gêneros, os/as que tinham boas condições materiais e que realizavam sem dificuldade e sem ajuda mais da metade das atividades básicas e instrumentais de vida diária (ABVD/AIVD) apresentaram maior chance de sobrevivência. O mesmo foi verificado naquelas mulheres com menos de duas limitações de determinadas doenças, nas casadas, nas que ofereciam algum tipo de ajuda e nas que realizaram ações preventivas em relação a sua condição de saúde. Entre os homens o mesmo ocorreu naqueles que se referiram ser chefe de família, nos que tinham participação comunitária, nos que residiam com algum outro morador que foi ou ia à escola, que trabalharam predominantemente como proprietário ou por conta própria e nos que relataram ter tido alguma doença em seus primeiros quinzes anos de vida. Conclusão: As chances de sobrevida são diferentes entre gêneros, e entre si, mesmo em situações aparentemente semelhantes do curso de vida vivenciados e presentes em homens e mulheres idosas.

Fatores associados ao abandono do aleitamento materno durante os primeiros seis meses de vida

O objetivo da pesquisa foi identificar os fatores associados ao abandono do aleitamento materno (AM) e do aleitamento materno completo (AMC). Foram acompanhadas 248 mães que fizeram visita pós-parto. Os dados foram coletados mediante entrevista pessoal durante o primeiro mês pós-parto e, pelo telefone, aos quatro e seis meses seguintes. A análise se realizou mediante a Regressão de Cox. Os resultados mostram associação entre o abandono da AMC e do AM com o fato de não se ter amamentado anteriormente, com AM anterior ≤4 meses, e, com pior avaliação da experiência anterior. O menor nível de estudos se relaciona com maior abandono do AM e das chupetas, ou suplementos no hospital com o abandono da AMC. A educação pré-natal é fator protetor para o AMC e o AM. Conclui-se que o apoio ao AM deveria intensificar-se nas mães: sem experiência anterior, com experiência negativa, e, com pior acesso à informação; também deveria ser controlado o uso da chupeta e dos suplementos de leite artificial (LA) não indicados.

Randomized, controlled trial of topical exit-site application of honey (Medihoney) versus Mupirocin for the prevention of catheter-associated infections in hemodialysis patients

The clinical usefulness of hemodialysis catheters is limited by increased infectious morbidity and mortality. Topical antiseptic agents, such as mupirocin, are effective at reducing this risk but have been reported to select for antibiotic-resistant strains. The aim of the present study was to determine the efficacy and the safety of exit-site application of a standardized antibacterial honey versus mupirocin in preventing catheter-associated infections. A randomized, controlled trial was performed comparing the effect of thrice-weekly exit-site application of Medihoney versus mupirocin on infection rates in patients who were receiving hemodialysis via tunneled, cuffed central venous catheters. A total of 101 patients were enrolled. The incidences of catheter-associated bacteremias in honey-treated (n = 51) and mupirocin-treated (n = 50) patients were comparable (0.97 versus 0.85 episodes per 1000 catheter-days, respectively; NS). On Cox proportional hazards model analysis, the use of honey was not significantly associated with bacteremia-free survival (unadjusted hazard ratio, 0.94; 95% confidence interval, 0.27 to 3.24; P = 0.92). No exit-site infections occurred. During the study period, 2% of staphylococcal isolates within the hospital were mupirocin resistant. Thrice-weekly application of standardized antibacterial honey to hemodialysis catheter exit sites was safe, cheap, and effective and resulted in a comparable rate of catheter-associated infection to that obtained with mupirocin (although the study was not adequately powered to assess therapeutic equivalence). The effectiveness of honey against antibiotic-resistant microorganisms and its low likelihood of selecting for further resistant strains suggest that this agent may represent a satisfactory alternative means of chemoprophylaxis in patients with central venous catheters.

Platelet nitric oxide responsiveness - A novel prognostic marker in acute coronary syndromes

Objectives - Nitric oxide (NO) is critically important in the regulation of vascular tone and the inhibition of platelet aggregation. We have shown previously that patients with acute coronary syndromes (ACS) or stable angina pectoris have impaired platelet responses to NO donors when compared with normal subjects. We tested the hypotheses that platelet hyporesponsiveness to NO is a predictor of (1) cardiovascular readmission and/or death and (2) all-cause mortality in patients with ACS (unstable angina pectoris or non-Q-wave myocardial infarction). Methods and Results - Patients (n = 51) with ACS had evaluation of platelet aggregation within 24 hours of coronary care unit admission using impedance aggregometry. Patients were categorized as having normal (>= 32% inhibition of ADP-induced aggregation with the NO donor sodium nitroprusside; 10 mu mol/L; n = 18) or impaired (>= 32% inhibition of ADP-induced aggregation; n = 33) NO responses. We then compared the incidence of cardiovascular readmission and death during a median of 7 years of follow-up in these 2 groups. Using a Cox proportional hazards model adjusting for age, sex, index event, postdischarge medical treatment, revascularization status, left ventricular systolic dysfunction, concurrent disease states, and cardiac risk factors, impaired NO responsiveness was associated with an increased risk of the combination of cardiovascular readmission and/or death (relative risk, 2.7; 95% CI, 1.03 to 7.10; P = 0.041) and all-cause mortality (relative risk, 6.3; 95% CI, 1.09 to 36.7; P = 0.033). Conclusions - Impaired platelet NO responsiveness is a novel, independent predictor of increased mortality and cardiovascular morbidity in patients with high-risk ACS.

Prognostic value of intraventricular dyssynchrony according to clinical stage of left ventricular impairment

Intraventricular dyssynchrony has prognostic implications in patients who have severe functional limitation and decreased ejection fraction. Patients with less advanced cardiac disease often exhibit intraventricular dyssynchrony, but there is little available information about its prognostic relevance in such patients. We investigated the prognostic effect of intraventricular dyssynchrony on outcome in 318 patients with known or suspected coronary artery disease who were classified according to the presence or absence of left ventricular dysfunction and heart failure symptoms. Mortality was considered the primary end point over a median follow-up of 56 months, and a Cox proportional hazards model was used for survival analysis. Despite a low prevalence (8%) of left bundle branch block, there was a high prevalence of intraventricular dyssynchrony even in patients without symptomatic heart failure. The magnitude of intraventricular dyssynchrony correlated poorly with QRS duration (r = 0.25),end-systolic volume index (r = 0.27), and number of scar segments (r = 0.25). There,were 58 deaths during follow-up. Ventricular volume, ischemic burden, and magnitude of intraventricular dyssynchrony predicted outcome, but magnitude of intraventricular dyssynchrony was an independent predictor of survival only in patients with asymptomatic left ventricular dysfunction. In conclusion, patients with known or suspected coronary artery disease have a high prevalence of intraventricular dyssynchrony. Although ventricular volume, ischemic burden, and intraventricular dyssynchrony are potentially important prognostic markers, the relative importance of intraventricular dyssynchrony changes with the clinical setting and, may be greatest-in patients with preclinical disease. (c) 2006 Elsevier Inc. All rights reserved.

Determinants of pharmaceutical innovation diffusion: social contagion and prescribing characteristics

This article studies the determinants of pharmaceutical innovation diffusion among specialists. To this end, it investigates the influences of six categories of factors—social embeddedness, socio-demography, scientific orientation, prescribing patterns, practice characteristics, and patient panel composition—on the use of new drugs for the treatment of type 2 diabetes mellitus in Hungary. Here, in line with international trends, 11 brands were introduced between April 2008 and April 2010, outperforming all other therapeutic classes. The Cox proportional hazards model identifies three determinants—social contagion (in the social embeddedness category) and prescribing portfolio and insulin prescribing ratio (in the prescribing pattern category). First, social contagion has a positive effect among geographically close colleagues—the higher the adoption ratio, the higher the likelihood of early adoption—but no influence among former classmates and scientific collaborators. Second, the wider the prescribing portfolio, the earlier the new drug uptake. Third, the lower the insulin prescribing ratio, the earlier the new drug uptake—physicians’ therapeutic convictions and patients’ socioeconomic statuses act as underlying influencers. However, this finding does not extend to opinion-leading physicians such as scientific leaders and hospital department and outpatient center managers. This article concludes by arguing that healthcare policy strategists and pharmaceutical companies may rely exclusively on practice location and prescription data to perfect interventions and optimize budgets.

Outlier effects on robust joint modelling of longitudinal and survival data

Robust joint modelling is an emerging field of research. Through the advancements in electronic patient healthcare records, the popularly of joint modelling approaches has grown rapidly in recent years providing simultaneous analysis of longitudinal and survival data. This research advances previous work through the development of a novel robust joint modelling methodology for one of the most common types of standard joint models, that which links a linear mixed model with a Cox proportional hazards model. Through t-distributional assumptions, longitudinal outliers are accommodated with their detrimental impact being down weighed and thus providing more efficient and reliable estimates. The robust joint modelling technique and its major benefits are showcased through the analysis of Northern Irish end stage renal disease patients. With an ageing population and growing prevalence of chronic kidney disease within the United Kingdom, there is a pressing demand to investigate the detrimental relationship between the changing haemoglobin levels of haemodialysis patients and their survival. As outliers within the NI renal data were found to have significantly worse survival, identification of outlying individuals through robust joint modelling may aid nephrologists to improve patient's survival. A simulation study was also undertaken to explore the difference between robust and standard joint models in the presence of increasing proportions and extremity of longitudinal outliers. More efficient and reliable estimates were obtained by robust joint models with increasing contrast between the robust and standard joint models when a greater proportion of more extreme outliers are present. Through illustration of the gains in efficiency and reliability of parameters when outliers exist, the potential of robust joint modelling is evident. The research presented in this thesis highlights the benefits and stresses the need to utilise a more robust approach to joint modelling in the presence of longitudinal outliers.

Influence of Remote Monitoring on Long-Term Cardiovascular Outcomes after Cardioverter-Defibrillator Implantation

AIMS: Device-based remote monitoring (RM) has been linked to improved clinical outcomes at short to medium-term follow-up. Whether this benefit extends to long-term follow-up is unknown. We sought to assess the effect of device-based RM on long-term clinical outcomes in recipients of implantable cardioverter-defibrillators (ICD). METHODS: We performed a retrospective cohort study of consecutive patients who underwent ICD implantation for primary prevention. RM was initiated with patient consent according to availability of RM hardware at implantation. Patients with concomitant cardiac resynchronization therapy were excluded. Data on hospitalizations, mortality and cause of death were systematically assessed using a nationwide healthcare platform. A Cox proportional hazards model was employed to estimate the effect of RM on mortality and a composite endpoint of cardiovascular mortality and hospital admission due to heart failure (HF). RESULTS: 312 patients were included with a median follow-up of 37.7months (range 1 to 146). 121 patients (38.2%) were under RM since the first outpatient visit post-ICD and 191 were in conventional follow-up. No differences were found regarding age, left ventricular ejection fraction, heart failure etiology or NYHA class at implantation. Patients under RM had higher long-term survival (hazard ratio [HR] 0.50, CI 0.27-0.93, p=0.029) and lower incidence of the composite outcome (HR 0.47, CI 0.27-0.82, p=0.008). After multivariate survival analysis, overall survival was independently associated with younger age, higher LVEF, NYHA class lower than 3 and RM. CONCLUSION: RM was independently associated with increased long-term survival and a lower incidence of a composite endpoint of hospitalization for HF or cardiovascular mortality.

Impact on hip fracture mortality after the establishment of an orthogeriatric care program in a colombian hospital

El objetivo del estudio es evaluar la mortalidad a un año en pacientes con fractura de cadera, mayores de 65 años tratados en un programa establecido de orto-geriatría. 298 se trataron de acuerdo al protocolo de orto-geriatría, se calculo la mortalidad a un año, se establecieron los predictores de mortalidad orto-geriátrico. La sobrevida anual se incremento de 80% a 89% (p = .039) durante los cuatro años de seguimiento del programa y disminuyo el riesgo de mortalidad anual postoperatorio (Hazard Ratio = 0.54, p = .049). La enfermedad cardiaca y la edad maor a 85 años fueron predictores positivos para mortalidad.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.