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Beyond Self-Reports: Changes in Biomarkers as Predictors of Mortality.

ABSTRACT: The proliferation of biosocial surveys has increased the importance of weighing the costs and benefits of adding biomarker collection to population-based surveys. A crucial question is whether biomarkers offer incremental value beyond self-reported measures, which are easier to collect and impose less respondent burden. We use longitudinal data from a nationally representative sample of older Taiwanese (n = 639, aged 54+ in 2000, examined in 2000 and 2006 with mortality follow-up through 2011) to address that question with respect to predicting all-cause mortality. A summary measure of biomarkers improves mortality prediction (as measured by the area under the receiver operating characteristic curve) compared with self-reports alone, but individual biomarkers perform better than the summary score. We find that incorporating change in biomarkers over a six-year period yields a small improvement in mortality prediction compared with one-time measurement. But, is the incremental value worth the costs?

SUBMITTER: Glei DA

PROVIDER: S-EPMC4117355 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature

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Beyond Self-Reports: Changes in Biomarkers as Predictors of Mortality.

Glei Dana A DA Goldman Noreen N Rodríguez Germán G Weinstein Maxine M

Population and development review 20140601 2

The proliferation of biosocial surveys has increased the importance of weighing the costs and benefits of adding biomarker collection to population-based surveys. A crucial question is whether biomarkers offer incremental value beyond self-reported measures, which are easier to collect and impose less respondent burden. We use longitudinal data from a nationally representative sample of older Taiwanese (<i>n</i> = 639, aged 54+ in 2000, examined in 2000 and 2006 with mortality follow-up through ...[more]

PMID: 25089065

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Project description:BackgroundThe National Cancer Institute's Common Terminology Criteria for Adverse Events (NCI-CTCAE) reporting system is widely used by clinicians to measure patient symptoms in clinical trials. The European Organization for Research and Treatment of Cancer's Quality of Life core questionnaire (EORTC QLQ-C30) enables cancer patients to rate their symptoms related to their quality of life. We examined the extent to which patient and clinician symptom scoring and their agreement could contribute to the estimation of overall survival among cancer patients.MethodsWe analyzed baseline data regarding six cancer symptoms (pain, fatigue, vomiting, nausea, diarrhea, and constipation) from a total of 2279 cancer patients from 14 closed EORTC randomized controlled trials. In each trial that was selected for retrospective pooled analysis, both clinician and patient symptom scoring were reported simultaneously at study entry. We assessed the extent of agreement between clinician vs patient symptom scoring using the Spearman and kappa correlation statistics. After adjusting for age, sex, performance status, cancer severity, and cancer site, we used Harrell concordance index (C-index) to compare the potential for clinician-reported and/or patient-reported symptom scores to improve the accuracy of Cox models to predict overall survival. All P values are from two-sided tests.ResultsPatient-reported scores for some symptoms, particularly fatigue, did differ from clinician-reported scores. For each of the six symptoms that we assessed at baseline, both clinician and patient scorings contributed independently and positively to the predictive accuracy of survival prognostication. Cox models of overall survival that considered both patient and clinician scores gained more predictive accuracy than models that considered clinician scores alone for each of four symptoms: fatigue (C-index = .67 with both patient and clinician data vs C-index = .63 with clinician data only; P <.001), vomiting (C-index = .64 vs .62; P = .01), nausea (C-index = .65 vs .62; P < .001), and constipation (C-index = .62 vs .61; P = .01).ConclusionPatients provide a subjective measure of symptom severity that complements clinician scoring in predicting overall survival.

Project description:ObjectivesNHS Digital issued new guidance on sepsis coding in April 2017 which was further modified in April 2018. During these timeframes some centres reported increased sepsis associated mortality, whilst others reported reduced mortality, in some cases coincident with specific quality improvement programmes. We hypothesised that changes in reported mortality could not be separated from changes in coding practice.MethodsHospital Episode Statistics from the Admitted Patient Care dataset for NHS hospitals in England, from April 2016 to March 2020 were analysed. Admissions of adults with sepsis: an International Classification of Diseases 10 (ICD-10) code associated with the Agency for Healthcare Research and Quality Clinical Classifications Software class 'Septicaemia (except in labour)', were assessed. Patient comorbidities were defined by other ICD-10 codes recorded within the admission episode.Results1,081,565 hospital episodes with a coded diagnosis of sepsis were studied. After April 2017 there was a significant increase in admission episodes with sepsis coded as the primary reason for admission. There were significant changes in the case-mix of patients with a primary diagnosis of sepsis after April 2017. An analysis of case-mix, hospital and year treated as random effects, defined a small reduction in sepsis associated mortality across England following the first change in coding guidance. No centre specific improvement in outcome could be separated from these random-effects.ConclusionChanges in sepsis coding practice altered case-mix and case selection, in ways that varied between centres. This was associated with changes in centre-specific sepsis associated mortality, over time. According to the direction of change these may be interpreted either as requiring local investigation for cause or as supporting coincident changes in clinical practice. A whole system analysis showed that centre specific changes in mortality cannot be separated from system-wide changes. Caution is therefore required when interpreting sepsis outcomes in England, particularly when using single centre studies to inform or support guidance or policy.

Dataset Information

Beyond Self-Reports: Changes in Biomarkers as Predictors of Mortality.

Publications

Beyond Self-Reports: Changes in Biomarkers as Predictors of Mortality.

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