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Estimation of biomarker distributions using laboratory data collected during routine delivery of medical care.

ABSTRACT: To examine the extent to which commonly ordered laboratory values obtained from large health care databases are representative of the distribution of laboratory values from the general population as reflected in the National Health and Nutrition Examination Survey.Means of test values from commercial insurance laboratory data and National Health and Nutrition Examination Survey data were compared. Inverse probability of selection weighting was used to account for possible selection bias and to create comparability between the two data sources.The average values of most of the laboratory results from routine care were very close to their population means as estimated from NHANES. Tests that were more selectively ordered tended to differ. The inverse probability of selection weighting approach generally had a small effect on the estimated means but did improve estimation of some of the more selected tests.Commonly ordered laboratory tests appear to be representative of values from the underlying population. This suggests that trends and other patterns in biomarker levels in the population may be reasonably studied using data collected during the routine delivery of medical care.

SUBMITTER: Brookhart MA

PROVIDER: S-EPMC4476533 | biostudies-literature | 2014 Oct

REPOSITORIES: biostudies-literature

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Estimation of biomarker distributions using laboratory data collected during routine delivery of medical care.

Brookhart Maurice Alan MA Todd Jonathan V JV Li Xiaojuan X Reams B Diane BD Pate Virginia V Kshirsagar Abhijit V AV

Annals of epidemiology 20140806 10

<h4>Purpose</h4>To examine the extent to which commonly ordered laboratory values obtained from large health care databases are representative of the distribution of laboratory values from the general population as reflected in the National Health and Nutrition Examination Survey.<h4>Methods</h4>Means of test values from commercial insurance laboratory data and National Health and Nutrition Examination Survey data were compared. Inverse probability of selection weighting was used to account for ...[more]

PMID: 25238941

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Project description:BackgroundCOVID-19 restrictions and fear dramatically changed the use of medical care. Understanding the magnitude of cancelled and postponed appointments and associated factors can help identify approaches to mitigate unmet need.ObjectiveTo determine the proportion of medical visits cancelled or postponed and for whom. We hypothesized that adults with serious medical conditions and those with higher anxiety, depressive symptoms, and avoidance-oriented coping would have more cancellations/postponements.DesignFour nationally representative cross-sectional surveys conducted online in May, July, October, and December 2020.Participants59,747 US adults who completed 15-min online surveys. 69% cooperation rate.MeasuresPhysical and mental health visits and cancer screening cancelled or postponed over prior 2 months. Plan to cancel or postpone visits over the next 2 months. Relationship with demographics, medical conditions, local COVID-19 death rate, anxiety, depressive symptoms, coping, intolerance of uncertainty, and perceived COVID-19 risk.Key resultsOf the 58% (N = 34,868) with a medical appointment during the 2 months before the survey, 64% had an appointment cancelled or postponed in May, decreasing to 37% in December. Of the 41% of respondents with scheduled cancer screening, 20% cancelled/postponed, which was stable May to December. People with more medical conditions were more likely to cancel or postpone medical visits (OR 1.19 per condition, 95% CI 1.16, 1.22) and cancer screening (OR 1.20, 95% CI 1.15, 1.24). Race, ethnicity, and income had weak associations with cancelled/postponed visits, local death rate was unrelated, but anxiety and depressive symptoms were strongly related to cancellations, and this grew between May and December.ConclusionsCancelled medical care and cancer screening were more common among persons with medical conditions, anxiety and depression, even after accounting for COVID-19 deaths. Outreach and support to ensure that patients are not avoiding needed care due to anxiety, depression and inaccurate perceptions of risk will be important.

Project description:IntroductionSouth Africa is considered highly endemic for hepatitis A virus (HAV) although few seroprevalence studies have been conducted over the past two decades. The World Health Organization recommends integrating HAV vaccination into national childhood immunization schedules where there is transition from high to intermediate endemicity. As a means of gauging age-specific rates of infection, we report HAV seroprevalence rates among specimens tested for HAV serology within South Africa's public health sector from 2005-2015.Materials and methodsHepatitis A serology results (Anti-HAV IgM, IgG and total antibody) from 2005-2015 were extracted from South Africa's National Health Laboratory Service's Corporate Data Warehouse (NHLS CDW), the central data repository of all laboratory test-sets within the public health sector. Results were extracted according to test-set, result, date of testing, health facility, name, surname, age, and sex. Anti-HAV IgG results were merged with total antibody results to reflect anti-HAV seroprevalence. Testing volume, positivity rates and age-specific anti-HAV seroprevalence rates by year and geographic distribution are described.Results and discussionA total of 501 083 HAV IgM results were retrieved, of which 16 423 (3.3%) were positive, 484 259 (96.6%) negative and 401 (0.1%) equivocal; and 34 710 HAV total antibody/IgG tests of which 30 675 (88.4%) were positive, 4 020 (11.6%) negative and 15 equivocal. Whereas IgM positivity was highest among the 1-4 year age group (33.5%) and lowest among patients >45 years (<0.5%), total antibody positivity ranged from its lowest level of 52.7% in the 1-4 year age group increasing to levels of >90% only after 25 years of age.ConclusionAnti-HAV total antibody testing within the South African public health sector demonstrates seroprevalence rates reach levels >90% only in adulthood, suggesting South Africa could be in transition from high to intermediate endemicity. Prospective studies with geographically representative sampling are required to confirm these findings and evaluate provincial and urban/rural heterogeneity.

Project description:BACKGROUND: Abnormal uterine bleeding is often investigated in clinical studies and critical to identify during gynecological consultation. The current standard for quantification of menstrual blood loss is the alkaline-hematin-method. However, this method is expensive and inconvenient for patients. Bleeding diaries, although widely used, provide only qualitative information on menstrual blood loss. Other methods have been developed, but still do not provide reliable quantitative data. METHODS: We estimated blood loss volume using data from two clinical studies in women suffering abnormal menstrual bleeding. These estimations were derived from mixed linear models based on diary data, hematological parameters and age. To validate the models, we applied our results to data from a third study with a similar patient population. RESULTS: The resulting best fitting model uses diary entries on bleeding intensity at a particular day, information on occurrence and frequency of single bleeding intensities in defined time windows, hemoglobin and ferritin values and age of the patient all as predictors of menstrual blood loss volume. Sensitivity and specificity for the diagnosis of excessive bleeding were 87% and 70%, respectively. Our model-based estimates reflect the subjective assessment by physicians and patients in the same way as the measured values do.When applying the model to an independent study, we found a correlation of 0.73 between estimated and measured values for the blood loss in a single day. Further models with reduced number of parameters (simplified for easier practical use) still showed correlation values between 0.69 and 0.73. CONCLUSIONS: We present a method for estimating menstrual blood loss volume in women suffering from prolonged or excessive menstrual bleeding. Our statistical model includes entries from bleeding diaries, laboratory parameters and age and produces results which correlate well with data derived by the alkaline-hematin-method. Therefore, this model may be used to estimate menstrual blood loss volume in both routine gynecological counseling and clinical studies.

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Estimation of biomarker distributions using laboratory data collected during routine delivery of medical care.

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Estimation of biomarker distributions using laboratory data collected during routine delivery of medical care.

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