Supplementing claims data with outpatient laboratory test results to improve confounding adjustment in effectiveness studies of lipid-lowering treatments

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Abstract

Background

Adjusting for laboratory test results may result in better confounding control when added to administrative claims data in the study of treatment effects. However, missing values can arise through several mechanisms.

Methods

We studied the relationship between availability of outpatient lab test results, lab values, and patient and system characteristics in a large healthcare database using LDL, HDL, and Hb _A1c in a cohort of initiators of statins or Vytorin (ezetimibe & simvastatin) as examples.

Results

Among 703,484 patients 68% had at least one lab test performed in the 6 months before treatment. Performing an LDL test was negatively associated with several patient characteristics, including recent hospitalization (OR = 0.32, 95% CI: 0.29-0.34), MI (OR = 0.77, 95% CI: 0.69-0.85), or carotid revascularization (OR = 0.37, 95% CI: 0.25-0.53). Patient demographics, diagnoses, and procedures predicted well who would have a lab test performed (AUC = 0.89 to 0.93). Among those with test results available claims data explained only 14% of variation.

Conclusions

In a claims database linked with outpatient lab test results, we found that lab tests are performed selectively corresponding to current treatment guidelines. Poor ability to predict lab values and the high proportion of missingness reduces the added value of lab tests for effectiveness research in this setting.

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Most cited references 14

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Using the outcome for imputation of missing predictor values was preferred.

Karel Moons, Rogier A. R. T. Donders, Theo Stijnen … (2006)

Epidemiologic studies commonly estimate associations between predictors (risk factors) and outcome. Most software automatically exclude subjects with missing values. This commonly causes bias because missing values seldom occur completely at random (MCAR) but rather selectively based on other (observed) variables, missing at random (MAR). Multiple imputation (MI) of missing predictor values using all observed information including outcome is advocated to deal with selective missing values. This seems a self-fulfilling prophecy. We tested this hypothesis using data from a study on diagnosis of pulmonary embolism. We selected five predictors of pulmonary embolism without missing values. Their regression coefficients and standard errors (SEs) estimated from the original sample were considered as "true" values. We assigned missing values to these predictors--both MCAR and MAR--and repeated this 1,000 times using simulations. Per simulation we multiple imputed the missing values without and with the outcome, and compared the regression coefficients and SEs to the truth. Regression coefficients based on MI including outcome were close to the truth. MI without outcome yielded very biased--underestimated--coefficients. SEs and coverage of the 90% confidence intervals were not different between MI with and without outcome. Results were the same for MCAR and MAR. For all types of missing values, imputation of missing predictor values using the outcome is preferred over imputation without outcome and is no self-fulfilling prophecy.

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Early intensive vs a delayed conservative simvastatin strategy in patients with acute coronary syndromes: phase Z of the A to Z trial.

James de Lemos, Michael Blazing, Stephen Wiviott … (2004)

Limited data are available evaluating how the timing and intensity of statin therapy following an acute coronary syndrome (ACS) event affect clinical outcome. To compare early initiation of an intensive statin regimen with delayed initiation of a less intensive regimen in patients with ACS. International, randomized, double-blind trial of patients with ACS receiving 40 mg/d of simvastatin for 1 month followed by 80 mg/d thereafter (n = 2265) compared with ACS patients receiving placebo for 4 months followed by 20 mg/d of simvastatin (n = 2232), who were enrolled in phase Z of the A to Z trial between December 29, 1999, and January 6, 2003. The primary end point was a composite of cardiovascular death, nonfatal myocardial infarction, readmission for ACS, and stroke. Follow-up was for at least 6 months and up to 24 months. Among the patients in the placebo plus simvastatin group, the median low-density lipoprotein (LDL) cholesterol level achieved while taking placebo was 122 mg/dL (3.16 mmol/L) at 1 month and was 77 mg/dL (1.99 mmol/L) at 8 months while taking 20 mg/d of simvastatin. Among the patients in the simvastatin only group, the median LDL cholesterol level achieved at 1 month while taking 40 mg/d of simvastatin was 68 mg/dL (1.76 mmol/L) and was 63 mg/dL (1.63 mmol/L) at 8 months while taking 80 mg/d of simvastatin. A total of 343 patients (16.7%) in the placebo plus simvastatin group experienced the primary end point compared with 309 (14.4%) in the simvastatin only group (40 mg/80 mg) (hazard ratio [HR], 0.89; 95% confidence interval [CI] 0.76-1.04; P =.14). Cardiovascular death occurred in 109 (5.4%) and 83 (4.1%) patients in the 2 groups (HR, 0.75; 95% CI, 0.57-1.00; P =.05) but no differences were observed in other individual components of the primary end point. No difference was evident during the first 4 months between the groups for the primary end point (HR, 1.01; 95% CI, 0.83-1.25; P =.89), but from 4 months through the end of the study the primary end point was significantly reduced in the simvastatin only group (HR, 0.75; 95% CI, 0.60-0.95; P =.02). Myopathy (creatine kinase >10 times the upper limit of normal associated with muscle symptoms) occurred in 9 patients (0.4%) receiving simvastatin 80 mg/d, in no patients receiving lower doses of simvastatin, and in 1 patient receiving placebo (P =.02). The trial did not achieve the prespecified end point. However, among patients with ACS, the early initiation of an aggressive simvastatin regimen resulted in a favorable trend toward reduction of major cardiovascular events.

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Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data.

S Schneeweiss, J Seeger, M Maclure … (2001)

Comorbidity is an important confounder in epidemiologic studies. The authors compared the predictive performance of comorbidity scores for use in epidemiologic research with administrative databases. Study participants were British Columbia, Canada, residents aged >or=65 years who received angiotensin-converting enzyme inhibitors or calcium channel blockers at least once during the observation period. Six scores were computed for all 141,161 participants during the baseline year (1995-1996). Endpoints were death and health care utilization during a 12-month follow-up (1996-1997). Performance was measured by using the c statistic ranging from 0.5 for chance prediction of outcome to 1.0 for perfect prediction. In logistic regression models controlling for age and gender, four scores based on the International Classification of Diseases, Ninth Revision (ICD-9) generally performed better at predicting 1-year mortality (c = 0.771, c = 0.768, c = 0.745, c = 0.745) than medication-based Chronic Disease Score (CDS)-1 and CDS-2 (c = 0.738, c = 0.718). Number of distinct medications used was the best predictor of future physician visits (R(2) = 0.121) and expenditures (R(2) = 0.128) and a good predictor of mortality (c = 0.745). Combining ICD-9 and medication-based scores improved the c statistics (1.7% and 6.2%, respectively) for predicting mortality. Generalizability of results may be limited to an elderly, predominantly White population with equal access to state-funded health care.

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Author and article information

Journal

Journal ID (nlm-ta): BMC Med Res Methodol

Journal ID (iso-abbrev): BMC Med Res Methodol

Title: BMC Medical Research Methodology

Publisher: BioMed Central

ISSN (Electronic): 1471-2288

Publication date Collection: 2012

Publication date (Electronic): 26 November 2012

Volume: 12

Page: 180

Affiliations

[1 ]Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, 1 Brigham Circle, Suite 3030, Boston, 02120, MA, USA

[2 ]The Brookings Institution, Washington, DC, USA

[3 ]HealthCore Inc, Wilmington, DE, USA

[4 ]RTI Health Solutions, RTP, Durham, NC, USA

Article

Publisher ID: 1471-2288-12-180

DOI: 10.1186/1471-2288-12-180

PMC ID: 3533513

PubMed ID: 23181419

SO-VID: 2eff2a8a-df50-400b-a2fc-faa6002fdaed

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 22 May 2012

Date accepted : 9 October 2012

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Supplementing claims data with outpatient laboratory test results to improve confounding adjustment in effectiveness studies of lipid-lowering treatments

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Abstract

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Most cited references 14

Using the outcome for imputation of missing predictor values was preferred.

Early intensive vs a delayed conservative simvastatin strategy in patients with acute coronary syndromes: phase Z of the A to Z trial.

Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data.

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Cited by 16

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