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Alternative Outcome Definitions and Their Effect on the Performance of Methods for Observational Outcome Studies

Abstract

Background

A systematic risk identification system has the potential to test marketed drugs for important Health Outcomes of Interest or HOI. For each HOI, multiple definitions are used in the literature, and some of them are validated for certain databases. However, little is known about the effect of different definitions on the ability of methods to estimate their association with medical products.

Objectives

Alternative definitions of HOI were studied for their effect on the performance of analytical methods in observational outcome studies.

Methods

A set of alternative definitions for three HOI were defined based on literature review and clinical diagnosis guidelines: acute kidney injury, acute liver injury and acute myocardial infarction. The definitions varied by the choice of diagnostic codes and the inclusion of procedure codes and lab values. They were then used to empirically study an array of analytical methods with various analytical choices in four observational healthcare databases. The methods were executed against predefined drug-HOI pairs to generate an effect estimate and standard error for each pair. These test cases included positive controls (active ingredients with evidence to suspect a positive association with the outcome) and negative controls (active ingredients with no evidence to expect an effect on the outcome). Three different performance metrics where used: (i) Area Under the Receiver Operator Characteristics (ROC) curve (AUC) as a measure of a method’s ability to distinguish between positive and negative test cases, (ii) Measure of bias by estimation of distribution of observed effect estimates for the negative test pairs where the true effect can be assumed to be one (no relative risk), and (iii) Minimal Detectable Relative Risk (MDRR) as a measure of whether there is sufficient power to generate effect estimates.

Results

In the three outcomes studied, different definitions of outcomes show comparable ability to differentiate true from false control cases (AUC) and a similar bias estimation. However, broader definitions generating larger outcome cohorts allowed more drugs to be studied with sufficient statistical power.

Conclusions

Broader definitions are preferred since they allow studying drugs with lower prevalence than the more precise or narrow definitions while showing comparable performance characteristics in differentiation of signal vs. no signal as well as effect size estimation.

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Acknowledgments

The Observational Medical Outcomes Partnership is funded by the Foundation for the National Institutes of Health (FNIH) through generous contributions from the following: Abbott, Amgen, AstraZeneca, Bayer Healthcare Pharmaceuticals, Biogen Idec, Bristol-Myers Squibb, Eli Lilly & Company, GlaxoSmithKline, Janssen Research and Development, Lundbeck, Merck & Co., Novartis Pharmaceuticals Corporation, Pfizer, Pharmaceutical Research Manufacturers of America (PhRMA), Roche, Sanofi-Aventis, Schering-Plough Corporation, and Takeda. Dr. Reich is an employee of AstraZeneca. Drs. Ryan and Schuemie are employees of Janssen Research and Development. Dr. Schuemie received a fellowship from the Office of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration. Dr. Schuemie has previously received a grant from FNIH.

This article was published in a supplement sponsored by the Foundation for the National Institutes of Health (FNIH). The supplement was guest edited by Stephen J.W. Evans. It was peer reviewed by Olaf H. Klungel who received a small honorarium to cover out-of-pocket expenses. S.J.W.E has received travel funding from the FNIH to travel to the OMOP symposium and received a fee from FNIH for the review of a protocol for OMOP. O.H.K has received funding for the IMI-PROTECT project from the Innovative Medicines Initiative Joint Undertaking (http://www.imi.europa.eu) under Grant Agreement no 115004, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.

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Correspondence to Christian G. Reich.

Additional information

The OMOP research used data from Truven Health Analytics (formerly the Health Business of Thomson Reuters), and includes MarketScan® Research Databases, represented with MarketScan Lab Supplemental (MSLR, 1.2 m persons), MarketScan Medicare Supplemental Beneficiaries (MDCR, 4.6 m persons), MarketScan Multi-State Medicaid (MDCD, 10.8 m persons), MarketScan Commercial Claims and Encounters (CCAE, 46.5 m persons). Data also provided by Quintiles® Practice Research Database (formerly General Electric’s Electronic Health Record, 11.2 m persons) database. GE is an electronic health record database while the other four databases contain administrative claims data.

Appendix: Health Outcome of Interest Definitions Used in the Study

Appendix: Health Outcome of Interest Definitions Used in the Study

HOI # Definition
Acute liver injury 1 Occurrence of at least one diagnostic code ICD-9-CM:
• 277.4 ‘Disorders of bilirubin excretion’
• 570* ‘Acute and subacute necrosis of the liver’a
• 572.2 ‘Hepatic coma (hepatorenal syndrome)’
• 572.4* ‘Hepatorenal syndrome’a
• 573* ‘Other disorders of the liver, including chemical or drug induced’a
• 576.8 ‘Other specified disorders of biliary tract’
• 782.4 ‘Jaundice, unspecified, not of newborn’
• 789.1* ‘Hepatomegaly’a
• 790.4* ‘Nonspecific elevation of transaminase or lactic dehydrogenase levels’a
• 794.8* ‘Abnormal liver function test results’a
2 Occurrence of at least one diagnostic code ICD-9-CM:
• 570* ‘Acute and subacute necrosis of the liver’a
• 572.2 ‘Hepatic coma (hepatorenal syndrome)’
• 572.4* ‘Hepatorenal syndrome’a
• 573* ‘Other disorders of the liver, including chemical or drug induced’a
3 Definition Acute Liver Injury #2 AND
Occurrence of at least one diagnostic procedure code within 30 days prior to diagnostic codea AND
Occurrence of at least one therapeutic procedure code within 60 days after the diagnostic codeb
4 Definition Acute Liver Injury #2 AND
Occurrence of at least one diagnostic procedure code within 30 days prior to diagnostic codeb AND
Occurrence of at least one therapeutic procedure code within 60 days after the diagnostic codeb AND
Definition Acute Liver Injury #5
5 Indicative of Hy’s law: Occurrence of the following lab tests and test results within 7 day period:
 Alanine aminotransferase ≥3 times the upper limit of normal as defined in data source, or 40 IU/L if not available OR
 Aspartate aminotransferase ≥3 times the upper limit of normal as defined in data source, or 40 IU/L if not available} AND
Total bilirubin ≥2 times the upper limit of normal as defined in data source, or 1.2 mg/dL if not available
6 Strongly indicative of Hy’s law: Occurrence of the following lab tests and test results within 7 day period:
 Alanine aminotransferase ≥10 times the upper limit of normal as defined in data source, or 40 IU/L if not available OR
 Aspartate aminotransferase ≥10 times the upper limit of normal as defined in data source, or 40 IU/L if not available AND
Total bilirubin ≥2 times the upper limit of normal as defined in data source, or 1.2 mg/dL if not available
7 Occurrence of at least one diagnostic code ICD-9-CM:
• 570* ‘Acute and subacute necrosis of the liver’a
• 572.4* ‘Hepatorenal syndrome’a
• 573.0 ‘Chronic passive congestion of liver’
• 573.1 ‘Hepatitis in viral diseases classified elsewhere’
• 573.4 ‘Hepatic infarction’
8 Definition of Acute Liver Failure #2 AND
Hospitalization at date of diagnostic code
Acute kidney injury 1 Occurrence of at least one diagnostic code ICD-9-CM:
• 584* ‘Acute renal failure’a
2 Definition Acute Kidney Injury #1 AND
Occurrence of at least one therapeutic ICD-9 Procedure code within 60 days after diagnostic code:
• 39.95 ‘Hemodialysis’
• 54.98 ‘Peritoneal dialysis’ AND
Excluding any diagnostic code for chronic dialysis status anytime before the diagnostic code ICD-9-CM:
• V45.1 ‘Renal dialysis status’
• V56.0 ‘Encounter for dialysis and dialysis catheter care’
• V56.31 ‘Encounter for adequacy testing for hemodialysis’
• V56.32 ‘Encounter for adequacy testing for peritoneal dialysis’
• V56.8 ‘Other dialysis’
3 Occurrence of the lab test code LOINC 2160-0 and the following test results:
• Serum creatinine ≥0.5 mg/dL for patients with a baseline level of ≤1.9 mg/dL
• Serum creatinine ≥1.0 mg/dL for patients with a baseline level of 2.0–4.9 mg/dL
• Serum creatinine ≥1.5 mg/dL for patients with a baseline level ≥5.0 mg/dL
The baseline level is defined as the occurrence of most recent lab test result any time prior to the elevated test result
4 Occurrence of at least one diagnostic code ICD-9-CM:
• 584 ‘Acute renal failure’ 584.5 ‘Acute renal failure with lesion of tubular necrosis’
• 584.6 ‘Acute renal failure with lesion of renal cortical necrosis’
• 584.7 ‘Acute renal failure with lesion of renal medullary (papillary) necrosis’
5 Definition of Acute Kidney Injury #1 AND Hospitalization at date of diagnostic code
Acute myocardial infarction 1 Occurrence of at least one broad diagnostic code ICD-9-CM:
• 410* ‘Acute myocardial infarction’a
• 411.1 ‘Intermediate coronary syndrome’
• 411.8 ‘Other acute coronary occlusion’
• 413.9 ‘Other and unspecified angina pectoris’ on or during hospitalization
2 Occurrence of at least one narrow diagnostic code ICD-9-CM:
• 410* ‘Acute myocardial infarction’a
3 Definition Acute Myocardial Infarction #2 AND Occurrence of at least one diagnostic procedure code within 30 days prior to diagnostic codea OR Occurrence of at least one therapeutic procedure code within 60 days after the diagnostic codec
4 American College of Cardiology/European Society of Cardiology Consensus Definition:
Occurrence of the following lab test results:
• Occurrence of the lab test ‘Blood Troponin’ LOINC codes 42757-5 or 10839-9, and lab test results ≥ the upper limit of normal in two sequential measurements, or ≥2 times the upper limit of normal in one measurement, and falling in a subsequent measurement. The ULN is defined as the 99th percentile of a non-MI control group, or 0.5 ng/mL if not available AND
• Occurrence of the lab test ‘Creatinine Phosphokinase MB Isozyme (CK-MB)’ LOINC codes 49551-5 or 13969-1, and lab test results ≥ the upper limit of normal in two sequential measurements, or ≥2 times the upper limit of normal in one measurement, and falling in a subsequent measurement. The ULN is defined as the 99th percentile of a non-MI control group, or 6 ng/mL if not available AND
Occurrence of an EKG test with the LOINC codes 11524-6, 8601-7, 18843-3, 18844-1, 18810-2, 8625-6 or 8634-8 within 10 days prior or after the lab test result and any of the following readings
• Any Q wave in leads V1 through V3, Q wave ≥5 to 30 ms in leads I, II, aVL, aVF, V4, V5, or V6 OR ST segment elevation: New or presumed new ST segment elevation at the J point in two or more contiguous leads with the cut-off of 0.2 mV in leads V1, V2, or V3 and ≥0.1 mV in other leads (contiguity in the frontal plane is defined by the lead sequence aVL, I, inverted aVR, II, aVF, III)
• ST segment depression OR T wave abnormalities
5 Definition Acute Myocardial Infarction #2 AND Hospitalization at date of diagnostic code
  1. aAn asterisk indicates a wildcard, i.e. any code with or without additional digits is included in the definition
  2. bA detailed list of all codes are available at http://omop.org/AcuteLiverInjury
  3. cA detailed list of all codes are available at http://omop.org/AcuteMyocardialInfarction

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Reich, C.G., Ryan, P.B. & Schuemie, M.J. Alternative Outcome Definitions and Their Effect on the Performance of Methods for Observational Outcome Studies. Drug Saf 36, 181–193 (2013). https://doi.org/10.1007/s40264-013-0111-1

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Keywords

  • Acute Kidney Injury
  • Diagnostic Code
  • Alternative Definition
  • Acute Liver Injury
  • Observational Medical Outcome Partnership