New validated prognostic models and prognostic calculators in patients with low-grade gliomas diagnosed by central pathology review: a pooled analysis of EORTC/RTOG/NCCTG phase III clinical trials.

Background In a previous study, the European Organisation for Research and Treatment of Cancer (EORTC) reported a scoring system to predict survival of patients with low-grade gliomas (LGGs). A major issue in the diagnosis of brain tumors is the lack of agreement among pathologists. New models in patients with LGGs diagnosed by central pathology review are needed. Methods Data from 339 EORTC patients with LGGs diagnosed by central pathology review were used to develop new prognostic models for progression-free survival (PFS) and overall survival (OS). Data from 450 patients with centrally diagnosed LGGs recruited into 2 large studies conducted by North American cooperative groups were used to validate the models. Results Both PFS and OS were negatively influenced by the presence of baseline neurological deficits, a shorter time since first symptoms (<30 wk), an astrocytic tumor type, and tumors larger than 5 cm in diameter. Early irradiation improved PFS but not OS. Three risk groups have been identified (low, intermediate, and high) and validated. Conclusions We have developed new prognostic models in a more homogeneous LGG population diagnosed by central pathology review. This population better fits with modern practice, where patients are enrolled in clinical trials based on central or panel pathology review. We could validate the models in a large, external, and independent dataset. The models can divide LGG patients into 3 risk groups and provide reliable individual survival predictions. Inclusion of other clinical and molecular factors might still improve models' predictions.

Assessing the improved discriminatory power of a new biomarker in prognostic models

Although the area under the receiver operating characteristic (AUC) is the most popular measure of the performance of prediction models, it has limitations, especially when it is used to evaluate the added discrimination of a new biomarker in the model. Pencina et al. (2008) proposed two indices, the net reclassification improvement (NRI) and integrated discrimination improvement (IDI), to supplement the improvement in the AUC (IAUC). Their NRI and IDI are based on binary outcomes in case-control settings, which do not involve time-to-event outcome. However, many disease outcomes are time-dependent and the onset time can be censored. Measuring discrimination potential of a prognostic marker without considering time to event can lead to biased estimates. In this dissertation, we have extended the NRI and IDI to survival analysis settings and derived the corresponding sample estimators and asymptotic tests. Simulation studies were conducted to compare the performance of the time-dependent NRI and IDI with Pencina’s NRI and IDI. For illustration, we have applied the proposed method to a breast cancer study.^ Key words: Prognostic model, Discrimination, Time-dependent NRI and IDI ^

Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Clinical Prognostic Factors Predicting Outcomes Of Patients With Recurrent Gbm And Nomograms

BACKGROUND: Prognostic models and nomograms were recently developed to predict survival of patients with newly diagnosed glioblastoma multiforme (GBM).1 To improve predictions, models should be updated with the most recent patient and disease information. Nomograms predicting patient outcome at the time of disease progression are required. METHODS: Baseline information from 299 patients with recurrent GBM recruited in 8 phase I or II trials of the EORTC Brain Tumor Group was used to evaluate clinical parameters as prognosticators of patient outcome. Univariate (log rank) and multivariate (Cox models) analyses were made to assess the ability of patients' characteristics (age, sex, performance status [WHO PS], and MRC neurological deficit scale), disease history (prior treatments, time since last treatment or initial diagnosis, and administration of steroids or antiepileptics) and disease characteristics (tumor size and number of lesions) to predict progression free survival (PFS) and overall survival (OS). Bootstrap technique was used for models internal validation. Nomograms were computed to provide individual patients predictions. RESULTS: Poor PS and more than 1 lesion had a significant prognostic impact for both PFS and OS. Antiepileptic drug use was significantly associated with worse PFS. Larger tumors (split by the median of the largest tumor diameter >42.5 mm) and steroid use had shorter OS. Age, sex, neurologic deficit, prior therapies, and time since last therapy or initial diagnosis did not show independent prognostic value for PFS or OS. CONCLUSIONS: This analysis confirms that PS but not age is a major prognostic factor for PFS and OS. Multiple or large tumors and the need to administer steroids significantly increase the risk of progression and death. Nomograms at the recurrence could be used to obtain accurate predictions for the design of new targeted therapy trials or retrospective analyses. (1. T. Gorlia et al., Nomograms for predicting survival of patients with newly diagnosed glioblastoma. Lancet Oncol 9 (1): 29-38, 2008.)

New prognostic factors and calculators for outcome prediction in patients with recurrent glioblastoma: A pooled analysis of EORTC Brain Tumour Group phase I and II clinical trials.

BACKGROUND: Prognostic models have been developed to predict survival of patients with newly diagnosed glioblastoma (GBM). To improve predictions, models should be updated with information at the recurrence. We performed a pooled analysis of European Organization for Research and Treatment of Cancer (EORTC) trials on recurrent glioblastoma to validate existing clinical prognostic factors, identify new markers, and derive new predictions for overall survival (OS) and progression free survival (PFS).¦METHODS: Data from 300 patients with recurrent GBM recruited in eight phase I or II trials conducted by the EORTC Brain Tumour Group were used to evaluate patient's age, sex, World Health Organisation (WHO) performance status (PS), presence of neurological deficits, disease history, use of steroids or anti-epileptics and disease characteristics to predict PFS and OS. Prognostic calculators were developed in patients initially treated by chemoradiation with temozolomide.¦RESULTS: Poor PS and more than one target lesion had a significant negative prognostic impact for both PFS and OS. Patients with large tumours measured by the maximum diameter of the largest lesion (⩾42mm) and treated with steroids at baseline had shorter OS. Tumours with predominant frontal location had better survival. Age and sex did not show independent prognostic values for PFS or OS.¦CONCLUSIONS: This analysis confirms performance status but not age as a major prognostic factor for PFS and OS in recurrent GBM. Patients with multiple and large lesions have an increased risk of death. With these data prognostic calculators with confidence intervals for both medians and fixed time probabilities of survival were derived.

MicroRNA Signature Obtained From the Comparison of Aggressive With Indolent Non-Hodgkin Lymphomas: Potential Prognostic Value in Mantle-Cell Lymphoma

Purpose Mantle-cell lymphoma (MCL) has a variable natural history but is incurable with current therapies. MicroRNAs (miRs) are useful in prognostic assessment of cancer. We determined an miR signature defining aggressiveness in B-cell non-Hodgkin lymphomas (NHL) and assessed whether this signature aids in MCL prognosis.MethodsWe assessed miR expression in a training set of 43 NHL cases. The miR signature was validated in 44 additional cases and examined on a training set of 119 MCL cases from four institutions in Canada. miRs significantly associated with overall survival were examined in an independent cohort of 114 MCL cases to determine association with patient outcome. miR expression was combined with current clinical prognostic factors to develop an enhanced prognostic model in patients with MCL.ResultsFourteen miRs were differentially expressed between aggressive and indolent NHL; 11 of 14 were validated in an independent set of NHL (excluding MCL). miR-127-3p and miR-615-3p were significantly associated with overall survival in the MCL training set. Their expression was validated in an independent MCL patient set. In comparison with Ki-67, expression of these miRs was more significantly associated with overall survival among patients with MCL. miR-127-3p was combined with Ki-67 to create a new prognostic model for MCL. A similar model was created with miR-615-3p and Mantle Cell Lymphoma International Prognostic Index scores.ConclusionEleven miRs are differentially expressed between aggressive and indolent NHL. Two novel miRs were associated with overall survival in MCL and were combined with clinical prognostic models to generate novel prognostic data for patients with MCL. (C) 2013 by American Society of Clinical Oncology

Structuring of Ranked Models

Prognostic procedures can be based on ranked linear models. Ranked regression type models are designed on the basis of feature vectors combined with set of relations defined on selected pairs of these vectors. Feature vectors are composed of numerical results of measurements on particular objects or events. Ranked relations defined on selected pairs of feature vectors represent additional knowledge and can reflect experts' opinion about considered objects. Ranked models have the form of linear transformations of feature vectors on a line which preserve a given set of relations in the best manner possible. Ranked models can be designed through the minimization of a special type of convex and piecewise linear (CPL) criterion functions. Some sets of ranked relations cannot be well represented by one ranked model. Decomposition of global model into a family of local ranked models could improve representation. A procedures of ranked models decomposition is described in this paper.

Indicadores de prognóstico em utentes com disfunção do ombro submetidos a uma intervenção terapêutica direcionada para a estabilidade dinâmica da escápulo-torácica

RESUMO: Introdução/ Objetivo: Segundo a revisão sistemática de Chester e colaboradores (2013b)apenas dois fatores de prognóstico demonstraram uma associação consistente com o resultado que foram a duração dos sintomas e a funcionalidade na avaliação inicial. O objetivo do estudo é identificar indicadores de bom e mau prognóstico em utentes com disfunção do complexo articular do ombro (DCAO), tendo por base, aspetos da avaliação inicial do utente e critérios de alta de abolição da dor, aumento da funcionalidade e da estabilidade dinâmica considerando uma intervenção terapêutica direcionada para o aumento da estabilidade dinâmica da escápulo-torácica. Metodologia: Efetuou-se um estudo de coorte clínico retrospetivo. Para tal, aplicou-se um protocolo de intervenção terapêutica e analisou-se os resultados. A amostra foi constituída por 82 indivíduos com DCAO [53 com síndrome do conflito subacromial (SCSA) e 29 com instabilidade da glenoumeral (IGU)], residentes nos distritos de Lisboa, Setúbal e Santarém com o intuito de iniciar tratamento de fisioterapia. A análise dos dados foi efetuada tendo em consideração dois procedimentos: análise univariada (através do método de Kaplan-Meier para cada CVP) e análise multifatorial (pela análise de regressão de Cox e regressão logística nos grupos de utentes com SCSA, IGU e DCAO). Resultados: O tempo mediano de continuação no tratamento em fisioterapia foi de 7 semanas para os utentes com SCSA e 6 semanas para utentes com IGU. Segundo o teste de Logrank, na análise univariada, existem sete e oito covariáveis preditoras (CVP) com associação estatisticamente significativa (p<0,05) para o subgrupo SCSA e IGU, respectivamente. De acordo com estes resultados, a primeira parte da DASH e a SPADI são as únicas CVP com associação comuns às duas disfunções. Pela análise multifatorial e, em congruência com o teste de Wald, nenhuma das CVP contribui estatisticamente para o modelo preditivo de continuidade do tratamento de fisioterapia em qualquer um dos três modelos estudados: subgrupo SCSA, subgrupo IGU e utentes com DCAO. Conclusão: Por uma análise univariada verificou-se que existem CVP associadas à alta dos tratamentos em fisioterapia e estas não são as mesmas em ambas as DCAO. Contudo, a magnitude do efeito de cada CVP nos modelos multifatoriais definidos para os grupos de utentes com SCSA, IGU e DCAO não demonstraram valor estatisticamente significativo pelo que não foi possível determinar modelos de prognóstico em utentes com DCAO.-------------ABSTRACT: Background/ Purpose: According with the systematic review from Chester and collaborators (2013b) just two prognostic factors demonstrated a consistent association with the outcome: the duration of symptoms and functionality in the initial assessment. The purpose of the study is to identify indicators of good and poor prognosis in patients with shoulder’s dysfunctions, based on aspects of the initial assessment and discharge criteria of absence of pain, increased functionality and dynamic stability considering a therapeutic intervention used to increase the dynamic stability of scapulo-thoracic. Methodology: It was conducted a retrospective study of clinical cohort. For this purpose it was applied a protocol with therapeutic intervention and the results were analyzed. The sample consisted of 82 individuals with shoulder’s dysfunction (53 with subacromial impingement (SIMP) and 29 with shoulder instability (SINS) residing in the districts of Lisbon, Setúbal and Santarém in order to start physiotherapy. Data analysis was performed taking into account two procedures: univariate analysis [using the Kaplan-Meier method for each co-variant predictor variable (CVP)] and multifactorial analysis [analysis by Cox regression and logistic regression on groups of patients with SIMP, SINS and shoulder’s dysfunction (SD)]. Results: The median time of follow-up treatment at physical therapy was 7 weeks for patients with SIMP and 6 weeks for patients with SINS. According to the Logrank test in the univariate analysis, there are seven and eight CVP with a statistically significant association (p<0.05) for the patients with SIMP and SINS, respectively. According to these results, the first part of the DASH and SPADI are the only CVP common to both disorders association. By multifatorial analyses, and in agreement with the Wald test, none of the CVP contributes statistically to the predictive model of continuity of physiotherapy treatment in any of the three studied models: patients with SIMP, patients with SINS and patients with SD. Conclusion: In an univariate analysis, it was verified that there are CVP associated with discharge from treatments of physical therapy and these are not the same in both SD. However, the magnitude of effect of each CVP in multifactorial models for defined patients groups with SIMP, SINS and SD showed no statistically significant. Therefore, it was not possible to determine prognostic models for patients with SD.

Critical analysis of the allocation policy for liver transplantation in Brazil

Liver transplantation is now the standard treatment for end-stage liver disease. Given the shortage of liver donors and the progressively higher number of patients waiting for transplantation, improvements in patient selection and optimization of timing for transplantation are needed. Several solutions have been suggested, including increasing the donor pool; a fair policy for allocation, not permitting variables such as age, gender, and race, or third-party payer status to play any role; and knowledge of the natural history of each liver disease for which transplantation is offered. To observe ethical rules and distributive justice (guarantee to every citizen the same opportunity to get an organ), the "sickest first" policy must be used. Studies have demonstrated that death has no relationship with waiting time, but rather with the severity of liver disease at the time of inclusion. Thus, waiting time is no longer part of the United Network for Organ Sharing distribution criteria. Waiting time only differentiates between equally severely diseased patients. The authors have analyzed the waiting list mortality and 1-year survival for patients of the State of São Paulo, from July 1997 through January 2001. Only the chronological criterion was used. According to "Secretaria de Estado da Saúde de São Paulo" data, among all waiting list deaths, 82.2% occurred within the first year, and 37.6% within the first 3 months following inclusion. The allocation of livers based on waiting time is neither fair nor ethical, impairs distributive justice and human rights, and does not occur in any other part of the world.

Outpatient treatment of pulmonary embolism.

Pulmonary embolism (PE) is traditionally treated in hospital. Growing evidence from non randomized prospective studies suggests that a substantial proportion of patients with non-massive PE might be safely treated in the outpatient setting using low molecular weight heparins. Based on this evidence, professional societies started to recommend outpatient care for selected patients with non-massive PE. Despite these recommendations, outpatient treatment of non-massive PE appears to be uncommon in clinical practice. The major barriers to PE outpatient care are, firstly, the uncertainty as how to identify low risk patients with PE who are candidates for outpatient care and secondly the lack of high quality evidence from randomized trials demonstrating the safety of PE outpatient care compared to traditional inpatient management. Also, although clinical prognostic models, echocardiography and cardiac biomarkers accurately identify low risk patients with PE in prospective studies, the benefit of risk stratification strategies based on these instruments should be demonstrated in prospective management studies and clinical trials before they can be implemented as decision aids to guide PE outpatient treatment. Before high quality evidence documenting the safety of an outpatient treatment approach is published, outpatient management of non-massive PE cannot be generally recommended.

Interleukin-10 rs1800896 and CXCR2 rs1126579 polymorphisms modulate the predisposition to septic shock

Despite major improvements in its treatment and diagnosis, sepsis is still a leading cause of death and admittance to the intensive care unit (ICU). Failure to identify patients at high risk of developing septic shock contributes to an increase in the sepsis burden and rapid molecular tests are currently the most promising avenue to aid in patient risk determination and therapeutic anticipation. The primary goal of this study was to evaluate the genetic susceptibility that affects sepsis outcome in 72 sepsis patients admitted to the ICU. Seven polymorphisms were genotyped in key inflammatory response genes in sepsis, including tumour necrosis factor-α,interlelukin (IL)-1β, IL-10,IL-8, Toll-like receptor 4, CXCR1and CXCR2. The primary finding showed that patients who were homozygous for the major A allele in IL-10rs1800896 had almost five times higher chance to develop septic shock compared to heterozygotes. Similarly, selected clinical features and CXCR2rs1126579 single nucleotide polymorphisms modulated septic shock susceptibility without affecting survival. These data support the hypothesis that molecular testing has clinical usefulness to improve sepsis prognostic models. Therefore, enrichment of the ICU portfolio by including these biomarkers will aid in the early identification of sepsis patients who may develop septic shock.

Predictive value of Glasgow Coma Scale after brain trauma: change in trend over the past ten years.

BACKGROUND: Age and the Glasgow Coma Scale (GCS) score on admission are considered important predictors of outcome after traumatic brain injury. We investigated the predictive value of the GCS in a large group of patients whose computerised multimodal bedside monitoring data had been collected over the previous 10 years. METHODS: Data from 358 subjects with head injury, collected between 1992 and 2001, were analysed retrospectively. Patients were grouped according to year of admission. Glasgow Outcome Scores (GOS) were determined at six months. Spearman's correlation coefficients between GCS and GOS scores were calculated for each year. RESULTS: On average 34 (SD: 7) patients were monitored every year. We found a significant correlation between the GCS and GOS for the first five years (overall 1992-1996: r = 0.41; p<0.00001; n = 183) and consistent lack of correlations from 1997 onwards (overall 1997-2001: r = 0.091; p = 0.226; n = 175). In contrast, correlations between age and GOS were in both time periods significant and similar (r = -0.24 v r = -0.24; p<0.002). CONCLUSIONS: The admission GCS lost its predictive value for outcome in this group of patients from 1997 onwards. The predictive value of the GCS should be carefully reconsidered when building prognostic models incorporating multimodality monitoring after head injury.

Outpatient treatment of pulmonary embolism

Pulmonary embolism (PE) is traditionally treated in hospital. Growing evidence from non randomized prospective studies suggests that a substantial proportion of patients with non-massive PE might be safely treated in the outpatient setting using low molecular weight heparins. Based on this evidence, professional societies started to recommend outpatient care for selected patients with non-massive PE. Despite these recommendations, outpatient treatment of non-massive PE appears to be uncommon in clinical practice. The major barriers to PE outpatient care are, firstly, the uncertainty as how to identify low risk patients with PE who are candidates for outpatient care and secondly the lack of high quality evidence from randomized trials demonstrating the safety of PE outpatient care compared to traditional inpatient management. Also, although clinical prognostic models, echocardiography and cardiac biomarkers accurately identify low risk patients with PE in prospective studies, the benefit of risk stratification strategies based on these instruments should be demonstrated in prospective management studies and clinical trials before they can be implemented as decision aids to guide PE outpatient treatment. Before high quality evidence documenting the safety of an outpatient treatment approach is published, outpatient management of non-massive PE cannot be generally recommended.

Pulmonary embolism severity index and troponin testing for the selection of low-risk patients with acute symptomatic pulmonary embolism.

Summary Background: The combination of the Pulmonary Embolism Severity Index (PESI) and troponin testing could help physicians identify appropriate patients with acute pulmonary embolism (PE) for early hospital discharge. Methods: This prospective cohort study included a total of 567 patients from a single center registry with objectively confirmed acute symptomatic PE. On the basis of the PESI, each patient was classified into 1 of 5 classes (I to V). At the time of hospital admission, patients had troponin I (cTnI) levels measured. The endpoint of the study was all-cause mortality within 30 days after diagnosis. We calculated the mortality rates in 4 patient groups: group 1: PESI class I-II plus cTnI <0.1 ng mL(-1); group 2: PESI classes III-V plus cTnI <0.1 ng mL(-1); group 3: PESI classes I-II plus cTnI >/= 0.1 ng mL(-1); and group 4: PESI classes III-V plus cTnI >/= 0.1 ng mL(-1). Results: The study cohort had a 30-day mortality of 10% (95% confidence interval [CI], 7.6 to 12.5%). Mortality rates in the 4 groups were 1.3%, 14.2%, 0% and 15.4%, respectively. Compared to non-elevated cTnl, the low-risk PESI had a higher negative predictive value (NPV) (98.9% vs 90.8%) and negative likelihood ratio (NLR) (0.1 vs 0.9) for predicting mortality. The addition of non-elevated cTnI to low-risk PESI did not improve the NPV or the NLR compared to either test alone. Conclusions: Compared to cTnl testing, PESI classification more accurately identified patients with PE who are at low risk of all-cause death within 30-days of presentation.