Dataset Information

Quantifying the value of biomarkers for predicting mortality.

ABSTRACT: In light of widespread interest in the prognostic value of biomarkers, we apply three discrimination measures to evaluate the incremental value of biomarkers--beyond self-reported measures--for predicting all-cause mortality. We assess whether all three measures--area under the receiver-operating characteristic curve, continuous net reclassification improvement, and integrated discrimination improvement--lead to the same conclusions.We use longitudinal data from a nationally representative sample of older Taiwanese (n = 639, aged 54 or older in 2000, examined in 2000 and 2006, with mortality follow-up through 2011). We estimate age-specific mortality using a Gompertz hazard model.The broad conclusions are consistent across the three discrimination measures and support the inclusion of biomarkers, particularly inflammatory markers, in household surveys. Although the rank ordering of individual biomarkers varies across discrimination measures, the following is true for all three: interleukin-6 is the strongest predictor, the other three inflammatory markers make the top 10, and homocysteine ranks second or third.The consistency of most of our findings across metrics should provide comfort to researchers using discrimination measures to evaluate the prognostic value of biomarkers. However, because the degree of consistency varies with the level of detail inherent in the research question, we recommend that researchers confirm results with multiple discrimination measures.

SUBMITTER: Goldman N

PROVIDER: S-EPMC4688113 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantifying the value of biomarkers for predicting mortality.

Goldman Noreen N Glei Dana A DA

Annals of epidemiology 20150829 12

<h4>Purpose</h4>In light of widespread interest in the prognostic value of biomarkers, we apply three discrimination measures to evaluate the incremental value of biomarkers--beyond self-reported measures--for predicting all-cause mortality. We assess whether all three measures--area under the receiver-operating characteristic curve, continuous net reclassification improvement, and integrated discrimination improvement--lead to the same conclusions.<h4>Methods</h4>We use longitudinal data from a ...[more]

PMID: 26419291

Similar Datasets

Project description:ObjectiveOlder emergency department (ED) patients are at high risk of mortality, and it is important to predict which patients are at highest risk. Biomarkers such as lactate, high-sensitivity cardiac troponin T (hs-cTnT), N-terminal pro-B-type natriuretic peptide (NT-proBNP), D-dimer and procalcitonin may be able to identify those at risk. We aimed to assess the discriminatory value of these biomarkers for 30-day mortality and other adverse outcomes.DesignProspective cohort study. On arrival of patients, five biomarkers were measured. Area under the curves (AUCs) and interval likelihood ratios (LRs) were calculated to investigate the discriminatory value of the biomarkers.SettingED in the Netherlands.ParticipantsOlder (≥65 years) medical ED patients, referred for internal medicine or gastroenterology.Primary and secondary outcome measures30-day mortality was the primary outcome measure, while other adverse outcomes (intensive care unit/medium care unit admission, prolonged length of hospital stay, loss of independent living and unplanned readmission) were the composite secondary outcome measure.ResultsThe median age of the 450 included patients was 79 years (IQR 73-85). In total, 51 (11.3%) patients died within 30 days. The AUCs of all biomarkers for prediction of mortality were sufficient to good, with the highest AUC of 0.73 for hs-cTnT and NT-proBNP. Only for the highest lactate values, the LR was high enough (29.0) to be applicable for clinical decision making, but this applied to a minority of patients. The AUC for the composite secondary outcome (intensive and medium care admission, length of hospital stay >7 days, loss of independent living and unplanned readmission within 30 days) was lower, ranging between 0.58 and 0.67.ConclusionsAlthough all five biomarkers predict 30-day mortality in older medical ED patients, their individual discriminatory value was not high enough to contribute to clinical decision making.Trial registration numberNCT02946398; Results.

Project description:Spontaneous intracerebral haemorrhage (SICH) has emerged as one of the most devastating forms of stroke in recent decades. This disease is noted to carry a 30-day mortality rate of approximately 45%. An increasing number of studies have implicated a complex immune-mediated and inflammation-mediated cascade of responses in the pathophysiology of SICH and the resultant neurologic outcome. Several clinical studies have demonstrated an association between inflammatory markers and outcome in patients with SICH. However, the exact relationship between serum biomarkers and functional outcomes amongst survivors has not been clearly elucidated. This study aimed to evaluate the changes in peripheral leukocyte count (WBC count) and C-reactive protein (CRP) levels in patients with SICH and to correlate these findings with survival and functional outcome.A prospective, descriptive and correlational study was conducted at Sarawak General Hospital (SGH) over the span of two years (April 2013-April 2015). Patients aged between 30 years and 75 years with supratentorial intracerebral bleed secondary to uncontrolled hypertension were recruited in this study. Data pertaining to the demography, clinical and radiological parameters, peripheral WBC count and CRP levels were obtained. Mortality and functional outcomes were determined at 6 months post ictus. Patients were recruited following the fulfilment of exclusion and inclusion criteria, and all obtained data were analysed with the Statistical Package for Social Sciences (SPSS) for Windows version 21.0.A total of 60 patients with a mean age of 56 years were recruited in this study. We found that approximately 16 patients were less than or equal to 50 years old (26.7%) and that 44 patients belonged to the older age group of above 50 years (73.3%). The Glasgow Coma Scale (GCS) score on admission ranged from 9 to 14/15 with a median value of 11/15. The mean clot volume was 20.1 cm3. The GCS score on admission and clot volume were significantly associated with the Glasgow Outcome Scale (GOS) at 6 months and overall survival (P < 0.05). The elevated WBC count and CRP level on admission and at 72 hours post admission were significantly associated with GOS at 6 months and overall survival (P < 0.05). Thus, the GCS score, clot volume, WBC count and CRP levels on admission and at 72 hours post admission can be used to predict functional outcome at 6 months and overall survival in patients with SICH.We could conclude via this study that for patients with SICH, the main determinants or predictors of functional outcome at 6 months and overall survival were noted to be the GCS score on admission, clot size, WBC count and CRP levels on admission and at 72 hours post admission.

Project description:IntroductionCoronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 virus, is a major public health concern spanning from healthy carriers to patients with life-threatening conditions. Although most of COVID-19 patients have mild-to-moderate clinical symptoms, some patients have severe pneumonia leading to death. Therefore, the early prediction of disease prognosis and severity is crucial in COVID-19 patients. The main objective of this study is to evaluate the haemocytometric parameters and identify severity score associated with SARS-CoV-2 infection.MethodsClinical and laboratory records were retrospectively reviewed from 97 cases of COVID-19 admitted to hospitals in Istanbul, Turkey. The patient groups were subdivided into three major groups: Group 1 (Non-critical): 59 patients, Group 2 (Critical-Survivors): 23 patients and Group 3 (Critical-Non-survivors):15 patients. These data was tested for correlation, including with derived haemocytometric parameters. The blood analyses were performed the Sysmex XN-series automated hematology analyser using standard laboratory protocols. All statistical testing was undertaken using Analyse-it software.Results97 patients with COVID-19 disease and 935 sequential complete blood count (CBC-Diff) measurements (days 0-30) were included in the final analyses. Multivariate analysis demonstrated that red cell distribution width (RDW) (>13.7), neutrophil to lymphocyte ratio (NLR) (4.4), Hemoglobin (Hgb) (<11.4 gr/dL) and monocyte to neutrophil ratio (MNR) (0.084) had the highest area under curve (AUC) values, respectively in discrimination critical patients than non-critical patients. In determining Group 3, MNR (<0.095), NLR (>5.2), Plateletcount (PLT) (>142 x103/L) and RDW (>14) were important haemocytometric parameters, and the mortality risk value created by their combination had the highest AUC value (AUC = 0.911, 95% CI, 0886-0.931). Trend analysis of CBC-Diff parameters over 30 days of hospitalization, NLR on day 2, MNR on day 4, RDW on day 6 and PLT on day 7 of admission were found to be the best time related parameters in discrimination non-critical (mild-moderate) patient group from critical (severe and non-survivor) patient group.ConclusionNLR is a strong predictor for the prognosis for severe COVID-19 patients when the cut-off chosen was 4.4, the combined mortality risk factor COVID-19 disease generated from RDW-CV, NLR, MNR and PLT is best as a mortality haematocytometric index.

Project description:UnlabelledBackgroundLittle is known about adult health and mortality relationships outside high-income nations, partly because few datasets have contained biomarker data in representative populations. Our objective is to determine the prognostic value of biomarkers with respect to total and cardiovascular mortality in an elderly population of a middle-income country, as well as the extent to which they mediate the effects of age and sex on mortality.MethodsThis is a prospective population-based study in a nationally representative sample of elderly Costa Ricans. Baseline interviews occurred mostly in 2005 and mortality follow-up went through December 2010. Sample size after excluding observations with missing values: 2,313 individuals and 564 deaths.Main outcomeprospective death rate ratios for 22 baseline biomarkers, which were estimated with hazard regression models.ResultsBiomarkers significantly predict future death above and beyond demographic and self-reported health conditions. The studied biomarkers account for almost half of the effect of age on mortality. However, the sex gap in mortality became several times wider after controlling for biomarkers. The most powerful predictors were simple physical tests: handgrip strength, pulmonary peak flow, and walking speed. Three blood tests also predicted prospective mortality: C-reactive protein (CRP), glycated hemoglobin (HbA1c), and dehydroepiandrosterone sulfate (DHEAS). Strikingly, high blood pressure (BP) and high total cholesterol showed little or no predictive power. Anthropometric measures also failed to show significant mortality effects.ConclusionsThis study adds to the growing evidence that blood markers for CRP, HbA1c, and DHEAS, along with organ-specific functional reserve indicators (handgrip, walking speed, and pulmonary peak flow), are valuable tools for identifying vulnerable elderly. The results also highlight the need to better understand an anomaly noted previously in other settings: despite the continued medical focus on drugs for BP and cholesterol, high levels of BP and cholesterol have little predictive value of mortality in this elderly population.

Dataset Information

Quantifying the value of biomarkers for predicting mortality.

Publications

Quantifying the value of biomarkers for predicting mortality.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets